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2023

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Inglés Adaptive equalization is crucial in mitigating distortions and compensating for frequency response variations in communication systems. It aims to enhance signal quality by adjusting the characteristics of the received signal. Particle swarm optimization (PSO) algorithms have shown promise in optimizing the tap weights of the equalizer. However, there is a need to enhance the optimization capabilities of PSO further to improve the equalization performance. This paper provides a comprehensive study of the issues and challenges of adaptive filtering by comparing different variants of PSO and analyzing the performance by combining PSO with other optimization algorithms to achieve better convergence, accuracy, and adaptability. Traditional PSO algorithms often suffer from high computational complexity and slow convergence rates, limiting their effectiveness in solving complex optimization problems. To address these limitations, this paper proposes a set of techniques aimed at reducing the complexity and accelerating the convergence of PSO. metadata Khan, Arooj and Shafi, Imran and Khawaja, Sajid Gul and de la Torre Díez, Isabel and López Flores, Miguel Ángel and Castanedo Galán, Juan and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, miguelangel.lopez@uneatlantico.es, juan.castanedo@uneatlantico.es, UNSPECIFIED (2023) Adaptive Filtering: Issues, Challenges, and Best-Fit Solutions Using Particle Swarm Optimization Variants. Sensors, 23 (18). p. 7710. ISSN 1424-8220

Article Subjects > Engineering
Subjects > Communication Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Inglés Chatbots are AI-powered programs designed to replicate human conversation. They are capable of performing a wide range of tasks, including answering questions, offering directions, controlling smart home thermostats, and playing music, among other functions. ChatGPT is a popular AI-based chatbot that generates meaningful responses to queries, aiding people in learning. While some individuals support ChatGPT, others view it as a disruptive tool in the field of education. Discussions about this tool can be found across different social media platforms. Analyzing the sentiment of such social media data, which comprises people’s opinions, is crucial for assessing public sentiment regarding the success and shortcomings of such tools. This study performs a sentiment analysis and topic modeling on ChatGPT-based tweets. ChatGPT-based tweets are the author’s extracted tweets from Twitter using ChatGPT hashtags, where users share their reviews and opinions about ChatGPT, providing a reference to the thoughts expressed by users in their tweets. The Latent Dirichlet Allocation (LDA) approach is employed to identify the most frequently discussed topics in relation to ChatGPT tweets. For the sentiment analysis, a deep transformer-based Bidirectional Encoder Representations from Transformers (BERT) model with three dense layers of neural networks is proposed. Additionally, machine and deep learning models with fine-tuned parameters are utilized for a comparative analysis. Experimental results demonstrate the superior performance of the proposed BERT model, achieving an accuracy of 96.49%. metadata R, Sudheesh and Mujahid, Muhammad and Rustam, Furqan and Shafique, Rahman and Chunduri, Venkata and Gracia Villar, Mónica and Brito Ballester, Julién and Diez, Isabel de la Torre and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, monica.gracia@uneatlantico.es, julien.brito@uneatlantico.es, UNSPECIFIED, UNSPECIFIED (2023) Analyzing Sentiments Regarding ChatGPT Using Novel BERT: A Machine Learning Approach. Information, 14 (9). p. 474. ISSN 2078-2489

Article Subjects > Biomedicine
Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Inglés In the last decade, artificial intelligence (AI) and AI-mediated technologies have undergone rapid evolution in healthcare and medicine, from apps to computer software able to analyze medical images, robotic surgery and advanced data storage system. The main aim of the present commentary is to briefly describe the evolution of AI and its applications in healthcare, particularly in nutrition and clinical biochemistry. Indeed, AI is revealing itself to be an important tool in clinical nutrition by using telematic means to self-monitor various health metrics, including blood glucose levels, body weight, heart rate, fat percentage, blood pressure, activity tracking and calorie intake trackers. In particular, the application of the most common digital technologies used in the field of nutrition as well as the employment of AI in the management of diabetes and obesity, two of the most common nutrition-related pathologies worldwide, will be presented. metadata Salinari, Alessia and Machì, Michele and Armas Diaz, Yasmany and Cianciosi, Danila and Qi, Zexiu and Yang, Bei and Ferreiro Cotorruelo, Maria Soledad and Gracia Villar, Santos and Dzul López, Luis Alonso and Battino, Maurizio and Giampieri, Francesca mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, santos.gracia@uneatlantico.es, luis.dzul@uneatlantico.es, maurizio.battino@uneatlantico.es, francesca.giampieri@uneatlantico.es (2023) The Application of Digital Technologies and Artificial Intelligence in Healthcare: An Overview on Nutrition Assessment. Diseases, 11 (3). p. 97. ISSN 2079-9721

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Fundación Universitaria Internacional de Colombia > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Inglés Chronic obstructive pulmonary disease (COPD) is a severe and chronic ailment that is currently ranked as the third most common cause of mortality across the globe. COPD patients often experience debilitating symptoms such as chronic coughing, shortness of breath, and fatigue. Sadly, the disease frequently goes undiagnosed until it is too late, leaving patients without the care they desperately need. So, COPD detection at an early stage is crucial to prevent further damage to the lungs and improve quality of life. Traditional COPD detection methods often rely on physical examinations and tests such as spirometry, chest radiography, blood gas tests, and genetic tests. However, these methods may not always be accurate or accessible. One of the key vital signs for detecting COPD is the patient’s respiration rate. However, it is crucial to consider a patient’s medical and demographic characteristics simultaneously for better detection results. To address this issue, this study aims to detect COPD patients using artificial intelligence techniques. To achieve this goal, a novel framework is proposed that utilizes ultra-wideband (UWB) radar-based temporal and spectral features to build machine learning and deep learning models. This new set of temporal and spectral features is extracted from respiration data collected non-invasively from 1.5 m distance using UWB radar. Different machine learning and deep learning models are trained and tested on the collected dataset. The findings are promising, with a high accuracy score of 100% for COPD detection. This means that the proposed framework could potentially save lives by identifying COPD patients at an early stage. The k-fold cross-validation technique and performance comparison with the state-of-the-art studies are applied to validate its performance, ensuring that the results are robust and reliable. The high accuracy score achieved in the study implies that the proposed framework has the potential for the efficient detection of COPD at an early stage. metadata Siddiqui, Hafeez-Ur-Rehman and Raza, Ali and Saleem, Adil Ali and Rustam, Furqan and Díez, Isabel de la Torre and Gavilanes Aray, Daniel and Lipari, Vivian and Ashraf, Imran and Dudley, Sandra mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, daniel.gavilanes@uneatlantico.es, vivian.lipari@uneatlantico.es, UNSPECIFIED, UNSPECIFIED (2023) An Approach to Detect Chronic Obstructive Pulmonary Disease Using UWB Radar-Based Temporal and Spectral Features. Diagnostics, 13 (6). p. 1096. ISSN 2075-4418

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Fundación Universitaria Internacional de Colombia > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Inglés The precise prediction of power estimates of wind–solar renewable energy sources becomes challenging due to their intermittent nature and difference in intensity between day and night. Machine-learning algorithms are non-linear mapping functions to approximate any given function from known input–output pairs and can be used for this purpose. This paper presents an artificial neural network (ANN)-based method to predict hybrid wind–solar resources and estimate power generation by correlating wind speed and solar radiation for real-time data. The proposed ANN allows optimization of the hybrid system’s operation by efficient wind and solar energy production estimation for a given set of weather conditions. The proposed model uses temperature, humidity, air pressure, solar radiation, optimum angle, and target values of known wind speeds, solar radiation, and optimum angle. A normalization function to narrow the error distribution and an iterative method with the Levenberg–Marquardt training function is used to reduce error. The experimental results show the effectiveness of the proposed approach against the existing wind, solar, or wind–solar estimation methods. It is envisaged that such an intelligent yet simplified method for predicting wind speed, solar radiation, and optimum angle, and designing wind–solar hybrid systems can improve the accuracy and efficiency of renewable energy generation. metadata Shafi, Imran and Khan, Harris and Farooq, Muhammad Siddique and Diez, Isabel de la Torre and Miró Vera, Yini Airet and Castanedo Galán, Juan and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, yini.miro@uneatlantico.es, juan.castanedo@uneatlantico.es, UNSPECIFIED (2023) An Artificial Neural Network-Based Approach for Real-Time Hybrid Wind–Solar Resource Assessment and Power Estimation. Energies, 16 (10). p. 4171. ISSN 1996-1073

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Fundación Universitaria Internacional de Colombia > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Inglés Project-based organizations need to procure different commodities, and the failure/success of a project depends heavily on procurement management. Companies must refine and develop methods to simplify and optimize the procurement process in a highly competitive environment. This paper presents a methodology to help managers of project-based organizations analyze procurement processes to determine the optimal framework for simultaneously addressing multiple objectives. These goals include minimizing the time between the generation and required approval for a purchase, identifying unnamed activities, and allocating the budget efficiently. In this paper, we apply process mining algorithms to a dataset consisting of event logs on Oracle Financials-based enterprise resource planning (ERP) procurement processes in ERP systems and demonstrate interesting results leading to project procurement intelligence (PPI). The provided log data is the real-life data consisting of 180,462 events referring to seven activities within 43,101 cases. The logged procurement processes are filtered and analyzed using the open-source process mining frameworks PrOM and Disco. As a result of the process mining activities, a simulation of the discovered process model derived from the event log of the entire procurement process is presented, and the most frequent potential behaviors are identified. This analysis and extraction of frequent processes from corporate event logs help organizations understand, adapt, and redesign procurement operations and, most importantly, make them more efficient and of higher quality. This study shows that after the successful formulation of guiding principles, data refinement, and process structure optimization, the case study results are considered significant by the organization’s management. metadata Butt, Naveed Anwer and Mahmood, Zafar and Sana, Muhammad Usman and Díez, Isabel de la Torre and Castanedo Galán, Juan and Brie, Santiago and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, juan.castanedo@uneatlantico.es, santiago.brie@uneatlantico.es, UNSPECIFIED (2023) Behavioral and Performance Analysis of a Real-Time Case Study Event Log: A Process Mining Approach. Applied Sciences, 13 (7). p. 4145. ISSN 2076-3417

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Inglés Internet of Things (IoT) has made significant strides in energy management systems recently. Due to the continually increasing cost of energy, supply–demand disparities, and rising carbon footprints, the need for smart homes for monitoring, managing, and conserving energy has increased. In IoT-based systems, device data are delivered to the network edge before being stored in the fog or cloud for further transactions. This raises worries about the data’s security, privacy, and veracity. It is vital to monitor who accesses and updates this information to protect IoT end-users linked to IoT devices. Smart meters are installed in smart homes and are susceptible to numerous cyber attacks. Access to IoT devices and related data must be secured to prevent misuse and protect IoT users’ privacy. The purpose of this research was to design a blockchain-based edge computing method for securing the smart home system, in conjunction with machine learning techniques, in order to construct a secure smart home system with energy usage prediction and user profiling. The research proposes a blockchain-based smart home system that can continuously monitor IoT-enabled smart home appliances such as smart microwaves, dishwashers, furnaces, and refrigerators, among others. An approach based on machine learning was utilized to train the auto-regressive integrated moving average (ARIMA) model for energy usage prediction, which is provided in the user’s wallet, to estimate energy consumption and maintain user profiles. The model was tested using the moving average statistical model, the ARIMA model, and the deep-learning-based long short-term memory (LSTM) model on a dataset of smart-home-based energy usage under changing weather conditions. The findings of the analysis reveal that the LSTM model accurately forecasts the energy usage of smart homes. metadata Iqbal, Faiza and Altaf, Ayesha and Waris, Zeest and Gavilanes Aray, Daniel and López Flores, Miguel Ángel and Díez, Isabel de la Torre and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, daniel.gavilanes@uneatlantico.es, miguelangel.lopez@uneatlantico.es, UNSPECIFIED, UNSPECIFIED (2023) Blockchain-Modeled Edge-Computing-Based Smart Home Monitoring System with Energy Usage Prediction. Sensors, 23 (11). p. 5263. ISSN 1424-8220

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Cerrado Inglés Agriculture is an important sector that plays an essential role in the economic development of a country. Each year farmers face numerous challenges in producing good quality crops. One of the major reasons behind the failure of the harvest is the use of unscientific agricultural practices. Moreover, every year enormous crop loss is encountered either by pests, specific diseases, or natural disasters. It raises a strong concern to employ sustainable advanced technologies to address agriculture-related issues. In this paper, a sustainable real-time crop disease detection and prevention system, called CROPCARE is proposed. The system integrates mobile vision, Internet of Things (IoT), and Google Cloud services for sustainable growth of crops. The primary function of the proposed intelligent system is to detect crop diseases through the CROPCARE -mobile application. It uses Super-Resolution Convolution Network (SRCNN) and the pretrained model MobileNet-V2 to generate a decision model trained over various diseases. To maintain sustainability, the mobile app is integrated with IoT sensors and Google Cloud services. The proposed system also provides recommendations that help farmers know about current soil conditions, weather conditions, disease prevention methods, etc. It supports both Hindi and English dictionaries for the convenience of the farmers. The proposed approach is validated by using the PlantVillage dataset. The obtained results confirm the performance strength of the proposed system. metadata Garg, Garima and Gupta, Shivam and Mishra, Preeti and Vidyarthi, Ankit and Singh, Aman and Ali, Asmaa mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, aman.singh@uneatlantico.es, UNSPECIFIED (2023) CROPCARE: An Intelligent Real-Time Sustainable IoT System for Crop Disease Detection Using Mobile Vision. IEEE Internet of Things Journal. p. 1. ISSN 2372-2541

Article Subjects > Biomedicine
Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Fundación Universitaria Internacional de Colombia > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Inglés Artificial intelligence has made substantial progress in medicine. Automated dental imaging interpretation is one of the most prolific areas of research using AI. X-ray and infrared imaging systems have enabled dental clinicians to identify dental diseases since the 1950s. However, the manual process of dental disease assessment is tedious and error-prone when diagnosed by inexperienced dentists. Thus, researchers have employed different advanced computer vision techniques, and machine- and deep-learning models for dental disease diagnoses using X-ray and near-infrared imagery. Despite the notable development of AI in dentistry, certain factors affect the performance of the proposed approaches, including limited data availability, imbalanced classes, and lack of transparency and interpretability. Hence, it is of utmost importance for the research community to formulate suitable approaches, considering the existing challenges and leveraging findings from the existing studies. Based on an extensive literature review, this survey provides a brief overview of X-ray and near-infrared imaging systems. Additionally, a comprehensive insight into challenges faced by researchers in the dental domain has been brought forth in this survey. The article further offers an amalgamative assessment of both performances and methods evaluated on public benchmarks and concludes with ethical considerations and future research avenues. metadata Shafi, Imran and Fatima, Anum and Afzal, Hammad and Díez, Isabel de la Torre and Lipari, Vivian and Breñosa, Jose and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, vivian.lipari@uneatlantico.es, josemanuel.brenosa@uneatlantico.es, UNSPECIFIED (2023) A Comprehensive Review of Recent Advances in Artificial Intelligence for Dentistry E-Health. Diagnostics, 13 (13). p. 2196. ISSN 2075-4418

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Fundación Universitaria Internacional de Colombia > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Inglés In the field of natural language processing, machine translation is a colossally developing research area that helps humans communicate more effectively by bridging the linguistic gap. In machine translation, normalization and morphological analyses are the first and perhaps the most important modules for information retrieval (IR). To build a morphological analyzer, or to complete the normalization process, it is important to extract the correct root out of different words. Stemming and lemmatization are techniques commonly used to find the correct root words in a language. However, a few studies on IR systems for the Urdu language have shown that lemmatization is more effective than stemming due to infixes found in Urdu words. This paper presents a lemmatization algorithm based on recurrent neural network models for the Urdu language. However, lemmatization techniques for resource-scarce languages such as Urdu are not very common. The proposed model is trained and tested on two datasets, namely, the Urdu Monolingual Corpus (UMC) and the Universal Dependencies Corpus of Urdu (UDU). The datasets are lemmatized with the help of recurrent neural network models. The Word2Vec model and edit trees are used to generate semantic and syntactic embedding. Bidirectional long short-term memory (BiLSTM), bidirectional gated recurrent unit (BiGRU), bidirectional gated recurrent neural network (BiGRNN), and attention-free encoder–decoder (AFED) models are trained under defined hyperparameters. Experimental results show that the attention-free encoder-decoder model achieves an accuracy, precision, recall, and F-score of 0.96, 0.95, 0.95, and 0.95, respectively, and outperforms existing models metadata Hafeez, Rabab and Anwar, Muhammad Waqas and Jamal, Muhammad Hasan and Fatima, Tayyaba and Martínez Espinosa, Julio César and Dzul López, Luis Alonso and Bautista Thompson, Ernesto and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, ulio.martinez@unini.edu.mx, luis.dzul@uneatlantico.es, ernesto.bautista@unini.edu.mx, UNSPECIFIED (2023) Contextual Urdu Lemmatization Using Recurrent Neural Network Models. Mathematics, 11 (2). p. 435. ISSN 2227-7390

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Fundación Universitaria Internacional de Colombia > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Inglés Automated dental imaging interpretation is one of the most prolific areas of research using artificial intelligence. X-ray imaging systems have enabled dental clinicians to identify dental diseases. However, the manual process of dental disease assessment is tedious and error-prone when diagnosed by inexperienced dentists. Thus, researchers have employed different advanced computer vision techniques, as well as machine and deep learning models for dental disease diagnoses using X-ray imagery. In this regard, a lightweight Mask-RCNN model is proposed for periapical disease detection. The proposed model is constructed in two parts: a lightweight modified MobileNet-v2 backbone and region-based network (RPN) are proposed for periapical disease localization on a small dataset. To measure the effectiveness of the proposed model, the lightweight Mask-RCNN is evaluated on a custom annotated dataset comprising images of five different types of periapical lesions. The results reveal that the model can detect and localize periapical lesions with an overall accuracy of 94%, a mean average precision of 85%, and a mean insection over a union of 71.0%. The proposed model improves the detection, classification, and localization accuracy significantly using a smaller number of images compared to existing methods and outperforms state-of-the-art approaches metadata Fatima, Anum and Shafi, Imran and Afzal, Hammad and Mahmood, Khawar and Díez, Isabel de la Torre and Lipari, Vivian and Brito Ballester, Julién and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, vivian.lipari@uneatlantico.es, julien.brito@uneatlantico.es, UNSPECIFIED (2023) Deep Learning-Based Multiclass Instance Segmentation for Dental Lesion Detection. Healthcare, 11 (3). p. 347. ISSN 2227-9032

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Fundación Universitaria Internacional de Colombia > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Inglés Monitoring tool conditions and sub-assemblies before final integration is essential to reducing processing failures and improving production quality for manufacturing setups. This research study proposes a real-time deep learning-based framework for identifying faulty components due to malfunctioning at different manufacturing stages in the aerospace industry. It uses a convolutional neural network (CNN) to recognize and classify intermediate abnormal states in a single manufacturing process. The manufacturing process for aircraft factory products comprises different phases; analyzing the components after the integration is labor-intensive and time-consuming, which often puts the company’s stake at high risk. To overcome these challenges, the proposed AI-based system can perform inspection and defect detection and alleviate the probability of components’ needing to be re-manufacturing after being assembled. In addition, it analyses the impact value, i.e., rework delays and costs, of manufacturing processes using a statistical process control tool on real-time data for various manufactured components. Defects are detected and classified using the CNN and teachable machine in the single manufacturing process during the initial stage prior to assembling the components. The results show the significance of the proposed approach in improving operational cost management and reducing rework-induced delays. Ground tests are conducted to calculate the impact value followed by the air tests of the final assembled aircraft. The statistical results indicate a 52.88% and 34.32% reduction in time delays and total cost, respectively. metadata Shafi, Imran and Mazhar, Muhammad Fawad and Fatima, Anum and Álvarez, Roberto Marcelo and Miró Vera, Yini Airet and Martínez Espinosa, Julio César and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, roberto.alvarez@uneatlantico.es, yini.miro@uneatlantico.es, ulio.martinez@unini.edu.mx, UNSPECIFIED (2023) Deep Learning-Based Real Time Defect Detection for Optimization of Aircraft Manufacturing and Control Performance. Drones, 7 (1). p. 31. ISSN 2504-446X

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production Abierto Español Las metodologías para el diseño y gestión de proyectos son cada vez más necesarias y aplicadas con mayor frecuencia en el sector público en Latinoamérica. Continuamente hay actualizaciones y nuevos enfoques en la gestión de proyectos de inversión, por lo que el estudio en las metodologías es relevante a nivel investigativo. El diseño de instrumentos de investigación confiables que sirvan para promover el uso de estas metodologías es importante para asegurar la calidad en el proceso. Por lo que el objetivo de este estudio es diseñar y validar un instrumento que permita recolectar y gestionar sistemáticamente información de proyectos para obtener las variables que permitan definir la metodología apropiada para cada organización, en este estudio se ha tomado como referencia en el sector público la Subsecretaría de Recursos Pesqueros (SRP) en Ecuador. El instrumento, toma como referencia la Norma International Organization for Standardization (ISO) 10006, la Guía de Fundamentos de Gestión de Proyectos, por su nombre en inglés Project Management Body of Knowledge (PMBOK), las Metodologías de Diseño de Proyectos de la Universidad Politécnica de Cataluña (MDP-UPC) y de la Secretaría Nacional de Planificación y Desarrollo (SENPLADES) del Ecuador. Como resultado, se desarrolló una encuesta, a cuyo instrumento se realizó la validación interna y externa en función de parámetros de confiabilidad, contenido y constructo. Se realizó análisis factorial para determinar variables utilizando sistema estadístico SPSS. Finalmente, se cuenta con la validación del instrumento diseñado asegurando que es confiable y cumple con los parámetros necesarios para obtener variables que definan la metodología para elaboración de proyectos en el sector público de Ecuador. metadata Bazurto Roldán, José Antonio and Álvarez, Roberto Marcelo and Miró Vera, Yini Airet and Brie, Santiago mail jose.bazurto@unini.org, roberto.alvarez@uneatlantico.es, yini.miro@uneatlantico.es, santiago.brie@uneatlantico.es (2023) Diseño y validación de un instrumento de investigación para proponer metodología de gestión de proyectos. Revista de Iniciación Científica, 9 (1). ISSN 2412-0464

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Fundación Universitaria Internacional de Colombia > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Inglés Traffic accidents present significant risks to human life, leading to a high number of fatalities and injuries. According to the World Health Organization’s 2022 worldwide status report on road safety, there were 27,582 deaths linked to traffic-related events, including 4448 fatalities at the collision scenes. Drunk driving is one of the leading causes contributing to the rising count of deadly accidents. Current methods to assess driver alcohol consumption are vulnerable to network risks, such as data corruption, identity theft, and man-in-the-middle attacks. In addition, these systems are subject to security restrictions that have been largely overlooked in earlier research focused on driver information. This study intends to develop a platform that combines the Internet of Things (IoT) with blockchain technology in order to address these concerns and improve the security of user data. In this work, we present a device- and blockchain-based dashboard solution for a centralized police monitoring account. The equipment is responsible for determining the driver’s impairment level by monitoring the driver’s blood alcohol concentration (BAC) and the stability of the vehicle. At predetermined times, integrated blockchain transactions are executed, transmitting data straight to the central police account. This eliminates the need for a central server, ensuring the immutability of data and the existence of blockchain transactions that are independent of any central authority. Our system delivers scalability, compatibility, and faster execution times by adopting this approach. Through comparative research, we have identified a significant increase in the need for security measures in relevant scenarios, highlighting the importance of our suggested model. metadata Farooq, Hamza and Altaf, Ayesha and Iqbal, Faiza and Castanedo Galán, Juan and Gavilanes Aray, Daniel and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, juan.castanedo@uneatlantico.es, daniel.gavilanes@uneatlantico.es, UNSPECIFIED (2023) DrunkChain: Blockchain-Based IoT System for Preventing Drunk Driving-Related Traffic Accidents. Sensors, 23 (12). p. 5388. ISSN 1424-8220

Article Subjects > Engineering
Subjects > Nutrition Europe University of Atlantic > Research > Scientific Production Abierto Inglés The present study assessed the responses, in terms of vegetative, productive, qualitative, and nutritional features, of plants and berries of three remontant strawberry cultivars cultivated in soil and irrigated using three irrigation regimes: standard irrigation regime (W100), 20% (W80) less irrigation than the standard irrigation, and 40% (W60) less irrigation than the standard irrigation. The tested plants were “Albion”, “San Andreas”, and “Monterey”, which were cultivated in the east coast area of Marche, Italy. Specifically, the study examined the response of the genotype to irrigation deficit, highlighting the performance of the “Monterey” cultivar, which showed improvement in terms of fruit firmness, folate content, and antioxidant capacity at the W80 irrigation regime without a significant yield reduction. In all the cultivars, when irrigation was reduced by up to 20% of the standard irrigation regime (W100), there were no significant losses of yield or reduction in the fruits’ sensorial quality or antioxidant activity. The results showed that the standard irrigation regime (W100) commonly adopted by the farmers in the Marche area uses more water than necessary. With more accurate water management, it will be possible to save almost 226 m3 of water per hectare per cultivation cycle. metadata Marcellini, Micol and Raffaelli, Davide and Mazzoni, Luca and Pergolotti, Valeria and Balducci, Francesca and Armas Diaz, Yasmany and Mezzetti, Bruno and Capocasa, Franco mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, bruno.mezzetti@uneatlantico.es, UNSPECIFIED (2023) Effects of Different Irrigation Rates on Remontant Strawberry Cultivars Grown in Soil. Horticulturae, 9 (9). p. 1026. ISSN 2311-7524

Article Subjects > Biomedicine
Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Inglés A novel approach is presented in this study for the classification of lower limb disorders, with a specific emphasis on the knee, hip, and ankle. The research employs gait analysis and the extraction of PoseNet features from video data in order to effectively identify and categorize these disorders. The PoseNet algorithm facilitates the extraction of key body joint movements and positions from videos in a non-invasive and user-friendly manner, thereby offering a comprehensive representation of lower limb movements. The features that are extracted are subsequently standardized and employed as inputs for a range of machine learning algorithms, such as Random Forest, Extra Tree Classifier, Multilayer Perceptron, Artificial Neural Networks, and Convolutional Neural Networks. The models undergo training and testing processes using a dataset consisting of 174 real patients and normal individuals collected at the Tehsil Headquarter Hospital Sadiq Abad. The evaluation of their performance is conducted through the utilization of K-fold cross-validation. The findings exhibit a notable level of accuracy and precision in the classification of various lower limb disorders. Notably, the Artificial Neural Networks model achieves the highest accuracy rate of 98.84%. The proposed methodology exhibits potential in enhancing the diagnosis and treatment planning of lower limb disorders. It presents a non-invasive and efficient method of analyzing gait patterns and identifying particular conditions. metadata Siddiqui, Hafeez Ur Rehman and Saleem, Adil Ali and Raza, Muhammad Amjad and Gracia Villar, Santos and Dzul Lopez, Luis and Diez, Isabel de la Torre and Rustam, Furqan and Dudley, Sandra mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, santos.gracia@uneatlantico.es, luis.dzul@unini.edu.mx, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED (2023) Empowering Lower Limb Disorder Identification through PoseNet and Artificial Intelligence. Diagnostics, 13 (18). p. 2881. ISSN 2075-4418

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Fundación Universitaria Internacional de Colombia > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Inglés Cricket has a massive global following and is ranked as the second most popular sport globally, with an estimated 2.5 billion fans. Batting requires quick decisions based on ball speed, trajectory, fielder positions, etc. Recently, computer vision and machine learning techniques have gained attention as potential tools to predict cricket strokes played by batters. This study presents a cutting-edge approach to predicting batsman strokes using computer vision and machine learning. The study analyzes eight strokes: pull, cut, cover drive, straight drive, backfoot punch, on drive, flick, and sweep. The study uses the MediaPipe library to extract features from videos and several machine learning and deep learning algorithms, including random forest (RF), support vector machine, k-nearest neighbors, decision tree, linear regression, and long short-term memory to predict the strokes. The study achieves an outstanding accuracy of 99.77% using the RF algorithm, outperforming the other algorithms used in the study. The k-fold validation of the RF model is 95.0% with a standard deviation of 0.07, highlighting the potential of computer vision and machine learning techniques for predicting batsman strokes in cricket. The study’s results could help improve coaching techniques and enhance batsmen’s performance in cricket, ultimately improving the game’s overall quality. metadata Siddiqui, Hafeez Ur Rehman and Younas, Faizan and Rustam, Furqan and Soriano Flores, Emmanuel and Brito Ballester, Julién and Diez, Isabel de la Torre and Dudley, Sandra and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, emmanuel.soriano@uneatlantico.es, julien.brito@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED (2023) Enhancing Cricket Performance Analysis with Human Pose Estimation and Machine Learning. Sensors, 23 (15). p. 6839. ISSN 1424-8220

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Fundación Universitaria Internacional de Colombia > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Inglés Classification is a commonly used technique in data mining and is applied in various fields such as sentiment analysis, fraud detection, and fault diagnosis. Multiclass classification, which involves more than two classes, is more complex than binary classification. There are mainly two ways to approach multiclass classification, one is to expand the binary classifier into a multiclass classifier through various strategies and the other is to divide the multiclass classification problem into multiple binary problems (binarization). Two popular approaches for binarization are One vs One (OvO) and One vs All (OvA). It is simpler to aggregate the outputs of all binary classifiers as the number of classifiers decreases. However, it causes an imbalance of positive and negative sample numbers, which affects the classification effect of each binary classifier. In this article, we contribute to the field of ensemble learning and multi-class classification by proposing a new method called Ensemble Partition Sampling (EPS). This article presents a new approach to multiclass classification using an "Ensemble Partition Sampling" method within the "one-vs-all" (OvA) framework. The primary goal of this method is to tackle the problem of data imbalance by incorporating ensemble learning and preprocessing techniques into each binary dataset. The study found that Ensemble Partition Sampling (EPS) is the most effective method for imbalanced and multiclass imbalanced classification, outperforming other methods including OvA, SMOTE, k-means-SMOTE, Bagging-RB, DES-MI, OvO-EASY, and OvO-SMB. The study used CART, Random Forest, and SVM as classifiers, and the results consistently showed that EPS outperformed all other algorithms. The findings suggest that EPS is a highly effective method for improving classification performance in imbalanced and multiclass imbalanced datasets. metadata Jabir, Brahim and Díez, Isabel De la Torre and Bautista Thompson, Ernesto and Ramírez-Vargas, Debora L. and Kuc Castilla, Ángel Gabriel mail UNSPECIFIED (2023) Ensemble Partition Sampling (EPS) for Improved Multi-Class Classification. IEEE Access. p. 1. ISSN 2169-3536

Article Subjects > Engineering
Subjects > Teaching Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Inglés The purpose of this research article was to contrast the benefits of the optimal probability threshold adjustment technique with other imbalanced data processing techniques, in its application to the prediction of post-graduate students’ late dropout from distance learning courses in two universities in the Ibero-American space. In this context, the optimization of the Logistic Regression, Random Forest, and Neural Network classifiers, together with different techniques, attributes, and algorithms (Hyperparameters, SMOTE, SMOTE_SVM, and ADASYN) resulted in a set of metrics for decision-making, prioritizing the reduction of false negatives. The best model was the Neural Network model in combination with SMOTE_SVM, obtaining a recall index of 0.75 and an f1-Score of 0.60. Likewise, the robustness of the Random Forest classifier for imbalanced data was demonstrated by achieving, with an optimal threshold of 0.427, very similar metrics to those obtained by the consensus of the three best models found. This demonstrates that, for Random Forest, the optimal prediction probability threshold is an excellent alternative to resampling techniques with different optimal thresholds. Finally, it is hoped that this research paper will contribute to boost the application of this simple but powerful technique, which is highly underrated with respect to data resampling techniques for imbalanced data. metadata Rodríguez Velasco, Carmen Lilí and García Villena, Eduardo and Brito Ballester, Julién and Durántez Prados, Frigdiano Álvaro and Silva Alvarado, Eduardo René and Crespo Álvarez, Jorge mail carmen.rodriguez@uneatlantico.es, eduardo.garcia@uneatlantico.es, julien.brito@uneatlantico.es, durantez@uneatlantico.es, eduardo.silva@funiber.org, jorge.crespo@uneatlantico.es (2023) Forecasting of Post-Graduate Students’ Late Dropout Based on the Optimal Probability Threshold Adjustment Technique for Imbalanced Data. International Journal of Emerging Technologies in Learning (iJET), 18 (04). pp. 120-155. ISSN 1863-0383

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production Abierto Inglés Forecasting of sediment load (SL) is essential for reservoir operations, design of water resource structures, risk management, water resource planning and for preventing natural disasters in the river basin systems. Direct measurement of SL is difficult, labour intensive, and expensive. The development of an accurate and reliable model for forecasting the SL is required. Sediment transport is highly non-linear and is influenced by a variety of factors. Forecasting of the SL using various conventional methods is not highly accurate because of the association of various complex phenomena. In this study, major key factors such as rock type (RT), relief (R), rainfall (RF), water discharge (WD), temperature (T), catchment area (CA), and SL are recognized in developing the one-step-ahead SL forecasting model in the Mahanadi River (MR), which is among India’s largest rivers. Artificial neural networks (ANN) in conjunction with multi-objective genetic algorithm (ANN-MOGA)-based forecasting models were developed for forecasting the SL in the MR. The ANN-MOGA model was employed to optimize the two competing objective functions (bias and error variance) with simultaneous optimization of all associated ANN parameters. The performances of the proposed novel model were finally compared to other existing methods to verify the forecasting capability of the model. The ANN-MOGA model improved the performance by 12.81% and 10.19% compared to traditional AR and MAR regression models, respectively. The results suggested that hybrid ANN-MOGA models outperform traditional autoregressive and multivariate autoregressive forecasting models. Overall, hybrid ANN-MOGA intelligent techniques are recommended for the forecasting of SL in rivers metadata Yadav, Arvind and Ali Albahar, Marwan and Chithaluru, Premkumar and Singh, Aman and Alammari, Abdullah and Kumar, Gogulamudi Vijay and Miró Vera, Yini Airet mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, aman.singh@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, yini.miro@uneatlantico.es (2023) Hybridizing Artificial Intelligence Algorithms for Forecasting of Sediment Load with Multi-Objective Optimization. Water, 15 (3). p. 522. ISSN 2073-4441

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Fundación Universitaria Internacional de Colombia > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Inglés With the advancement in information technology, digital data stealing and duplication have become easier. Over a trillion bytes of data are generated and shared on social media through the internet in a single day, and the authenticity of digital data is currently a major problem. Cryptography and image watermarking are domains that provide multiple security services, such as authenticity, integrity, and privacy. In this paper, a digital image watermarking technique is proposed that employs the least significant bit (LSB) and canny edge detection method. The proposed method provides better security services and it is computationally less expensive, which is the demand of today’s world. The major contribution of this method is to find suitable places for watermarking embedding and provides additional watermark security by scrambling the watermark image. A digital image is divided into non-overlapping blocks, and the gradient is calculated for each block. Then convolution masks are applied to find the gradient direction and magnitude, and non-maximum suppression is applied. Finally, LSB is used to embed the watermark in the hysteresis step. Furthermore, additional security is provided by scrambling the watermark signal using our chaotic substitution box. The proposed technique is more secure because of LSB’s high payload and watermark embedding feature after a canny edge detection filter. The canny edge gradient direction and magnitude find how many bits will be embedded. To test the performance of the proposed technique, several image processing, and geometrical attacks are performed. The proposed method shows high robustness to image processing and geometrical attacks metadata Faheem, Zaid Bin and Ishaq, Abid and Rustam, Furqan and de la Torre Díez, Isabel and Gavilanes, Daniel and Masías Vergara, Manuel and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, daniel.gavilanes@uneatlantico.es, manuel.masias@uneatlantico.es, UNSPECIFIED (2023) Image Watermarking Using Least Significant Bit and Canny Edge Detection. Sensors, 23 (3). p. 1210. ISSN 1424-8220

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production Abierto Inglés Rock art offers traces of our most remote past and was made with mineral and organic substances in shelters, walls, or the ceilings of caves. As it is notably fragile, it is fortunate that some instances remain intact—but a variety of natural and anthropogenic factors can lead to its disappearance. Therefore, as a valuable cultural heritage, rock art requires special conservation and protection measures. Geomatic remote-sensing technologies such as 3D terrestrial laser scanning (3DTLS), drone flight, and ground-penetrating radar (GPR) allow us to generate exhaustive documentation of caves and their environment in 2D, 2.5D, and 3D. However, only its combined use with 3D geographic information systems (GIS) lets us generate new cave maps with details such as overlying layer thickness, sinkholes, fractures, joints, and detachments that also more precisely reveal interior–exterior interconnections and gaseous exchange; i.e., the state of senescence of the karst that houses the cave. Information of this kind is of great value for the research, management, conservation, monitoring, and dissemination of cave art. metadata Bayarri Cayón, Vicente and Prada, Alfredo and García, Francisco and Díaz-González, Lucía M. and De Las Heras, Carmen and Castillo, Elena and Fatás, Pilar mail vicente.bayarri@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED (2023) Integration of Remote-Sensing Techniques for the Preventive Conservation of Paleolithic Cave Art in the Karst of the Altamira Cave. Remote Sensing, 15 (4). p. 1087. ISSN 2072-4292

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Inglés Agriculture is a critical domain, where technology can have a significant impact on increasing yields, improving crop quality, and reducing environmental impact. The use of renewable energy sources such as solar power in agriculture has gained momentum in recent years due to the potential to reduce the carbon footprint of farming operations. In addition to providing a source of clean energy, solar tracking systems can also be used for remote weather monitoring in the agricultural field. The ability to collect real-time data on weather parameters such as temperature, humidity, and rainfall can help farmers make informed decisions on irrigation, pest control, and other crop management practices. The main idea of this study is to present a system that can improve the efficiency of solar panels to provide constant power to the sensor in the agricultural field and transfer real-time data to the app. This research presents a mechanism to improve the arrangement of a photovoltaic (PV) array with solar power and to produce maximum energy. The proposed system changes its direction in two axes (azimuth and elevation) by detecting the difference between the position of the sun and the panel to track the sun using a light-dependent resistor. A testbed with a hardware experimental setup is designed to test the system’s capability to track according to the position of the sun effectively. In the end, real-time data are displayed using the Android app, and the weather data are transferred to the app using a GSM/WiFi module. This research improves the existing system, and results showed that the relative increase in power generation was up to 52%. Using intelligent artificial intelligence techniques with the QoS algorithm, the quality of service produced by the existing system is improved. metadata Kanwal, Tabassum and Rehman, Saif Ur and Ali, Tariq and Mahmood, Khalid and Gracia Villar, Santos and Dzul Lopez, Luis and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, santos.gracia@uneatlantico.es, luis.dzul@unini.edu.mx, UNSPECIFIED (2023) An Intelligent Dual-Axis Solar Tracking System for Remote Weather Monitoring in the Agricultural Field. Agriculture, 13 (8). p. 1600. ISSN 2077-0472

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production Abierto Inglés 5G has been launched in a few countries of the world, so now all focus shifted towards the development of future 6G networks. 5G has connected all aspects of society. Ubiquitous connectivity has opened the doors for more data sharing. Although 5G is providing low latency, higher data rates, and high-speed yet there are some security-related vulnerabilities. Those security issues need to be mitigated for securing 6G networks from existing challenges. Classical cryptography will not remain enough for securing the 6G network. As all classical cryptography can be disabled with the help of quantum mechanics. Therefore, in the place of traditional security solutions, in this article, we have reviewed all the existing quantum solutions of 5G existing security issues to mitigate them and secure 6G in a Future Quantum World. metadata Mangla, Cherry and Rani, Shalli and Faseeh Qureshi, Nawab Muhammad and Singh, Aman mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, aman.singh@uneatlantico.es (2023) Mitigating 5G security challenges for next-gen industry using quantum computing. Journal of King Saud University - Computer and Information Sciences. ISSN 13191578

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Inglés Society and the environment are severely impacted by catastrophic events, specifically floods. Inadequate emergency preparedness and response are frequently the result of the absence of a comprehensive plan for flood management. This article proposes a novel flood disaster management (FDM) system using the full lifecycle disaster event model (FLCNDEM), an abstract model based on the function super object. The proposed FDM system integrates data from existing flood protocols, languages, and patterns and analyzes viewing requests at various phases of an event to enhance preparedness and response. The construction of a task library and knowledge base to initialize FLCNDEM results in FLCDEM flooding response. The proposed FDM system improves the emergency response by offering a comprehensive framework for flood management, including pre-disaster planning, real-time monitoring, and post-disaster evaluation. The proposed system can be modified to accommodate various flood scenarios and enhance global flood management. metadata Khan, Saad Mazhar and Shafi, Imran and Butt, Wasi Haider and Díez, Isabel de la Torre and López Flores, Miguel Ángel and Castanedo Galán, Juan and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, miguelangel.lopez@uneatlantico.es, juan.castanedo@uneatlantico.es, UNSPECIFIED (2023) Model Driven Approach for Efficient Flood Disaster Management with Meta Model Support. Land, 12 (8). p. 1538. ISSN 2073-445X

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production Abierto Inglés COVID-19 is an infectious disease caused by the deadly virus SARS-CoV-2 that affects the lung of the patient. Different symptoms, including fever, muscle pain and respiratory syndrome, can be identified in COVID-19-affected patients. The disease needs to be diagnosed in a timely manner, otherwise the lung infection can turn into a severe form and the patient’s life may be in danger. In this work, an ensemble deep learning-based technique is proposed for COVID-19 detection that can classify the disease with high accuracy, efficiency, and reliability. A weighted average ensemble (WAE) prediction was performed by combining three CNN models, namely Xception, VGG19 and ResNet50V2, where 97.25% and 94.10% accuracy was achieved for binary and multiclass classification, respectively. To accurately detect the disease, different test methods have been proposed and developed, some of which are even being used in real-time situations. RT-PCR is one of the most successful COVID-19 detection methods, and is being used worldwide with high accuracy and sensitivity. However, complexity and time-consuming manual processes are limitations of this method. To make the detection process automated, researchers across the world have started to use deep learning to detect COVID-19 applied on medical imaging. Although most of the existing systems offer high accuracy, different limitations, including high variance, overfitting and generalization errors, can be found that can degrade the system performance. Some of the reasons behind those limitations are a lack of reliable data resources, missing preprocessing techniques, a lack of proper model selection, etc., which eventually create reliability issues. Reliability is an important factor for any healthcare system. Here, transfer learning with better preprocessing techniques applied on two benchmark datasets makes the work more reliable. The weighted average ensemble technique with hyperparameter tuning ensures better accuracy than using a randomly selected single CNN model. metadata Chakraborty, Gouri Shankar and Batra, Salil and Singh, Aman and Muhammad, Ghulam and Yélamos Torres, Vanessa and Mahajan, Makul mail UNSPECIFIED, UNSPECIFIED, aman.singh@uneatlantico.es, UNSPECIFIED, vanessa.yelamos@funiber.org, UNSPECIFIED (2023) A Novel Deep Learning-Based Classification Framework for COVID-19 Assisted with Weighted Average Ensemble Modeling. Diagnostics, 13 (10). p. 1806. ISSN 2075-4418

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production Cerrado Inglés The Internet of Things (IoT) has recently surpassed wired communication. WiMAX is a wireless transmission technology that allows for faster internet access. Wireless network innovations, like some other communication networks, are not safe and secure. Security and authorization models are intended to prevent unauthorized use of network services. Numerous authorization and encrypted communication mechanisms have been introduced for WiMAX privacy, but the communication systems are still insecure and vulnerable to attacks such as zero-day attacks, rouge base station attacks, Man in the Middle (MITM) attacks, and Denial of Service (DoS) attacks. Wireless technologies have come a long way in the last few decades. Because most wireless transmission systems rely on radio signals, the system channel is essentially vulnerable to interception. As a result, data security is always critical in the presentation of a system. Because WiMAX is a wireless communication technology, it is particularly vulnerable to interception, so security is a top priority. Individuals must be protected from security breaches that occur across network interfaces, networking devices, and everything in between. Robust security management is required to protect WiMAX from attacks and vulnerabilities, despite the fact that emerging Artificial Intelligence (AI) technologies necessitate different security governance than existing technologies. We proposed an Optimized Privacy Information Exchange Schema for Explainable AI Empowered WiMAX-based IoT that addresses vulnerabilities and threats during the identification and authorization phases to improve the functionality and performance characteristics of the traditional system. The Scyther tool was used to validate the proposed privacy scheme, which is safer and more secure than existing systems. metadata Chithaluru, Premkumar and Singh, Aman and Dhatterwal, Jagjit Singh and Sodhro, Ali Hassan and Albahar, Marwan Ali and Jurcut, Anca and Alkhayyat, Ahmed mail UNSPECIFIED, aman.singh@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED (2023) An Optimized Privacy Information Exchange Schema for Explainable AI Empowered WiMAX-based IoT networks. Future Generation Computer Systems, 148. pp. 225-239. ISSN 0167739X

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Fundación Universitaria Internacional de Colombia > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Inglés The rising popularity of online shopping has led to a steady stream of new product evaluations. Consumers benefit from these evaluations as they make purchasing decisions. Many research projects rank products using these reviews, however, most of these methodologies have ignored negative polarity while evaluating products for client needs. The main contribution of this research is the inclusion of negative polarity in the analysis of product rankings alongside positive polarity. To account for reviews that contain many sentiments and different elements, the suggested method first breaks them down into sentences. This process aids in determining the polarity of products at the phrase level by extracting elements from product evaluations. The next step is to link the polarity to the review’s sentence-level features. Products are prioritized following user needs by assigning relative importance to each of the polarities. The Amazon review dataset has been used in the experimental assessments so that the efficacy of the suggested approach can be estimated. Experimental evaluation of PRUS utilizes rank score ( RS ) and normalized discounted cumulative gain ( nDCG ) score. Results indicate that PRUS gives independence to the user to select recommended list based on specific features with respect to positive or negative aspects of the products. metadata Hussain, Naveed and Mirza, Hamid Turab and Iqbal, Faiza and Altaf, Ayesha and Shoukat, Ahtsham and Gracia Villar, Mónica and Soriano Flores, Emmanuel and Rojo Gutiérrez, Marco Antonio and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, monica.gracia@uneatlantico.es, emmanuel.soriano@uneatlantico.es, marco.rojo@unini.edu.mx, UNSPECIFIED (2023) PRUS: Product Recommender System Based on User Specifications and Customers Reviews. IEEE Access, 11. pp. 81289-81297. ISSN 2169-3536

Book Subjects > Engineering Europe University of Atlantic > Research > Scientific Production Cerrado Español El proyecto de conservación y recuperación de cepas ancestrales desarrollado en los últimos años por José M. Gómez Eguren, Pablo Oria Chaveli y Diego González Rodríguez ha permitido recuperar cepas presumiblemente antiguas de las variedades tintas petit verdot y graciano. La hipótesis que manejan estos estudiosos y técnicos es que pueden tratarse de cepas prefiloxéricas y que pueden responder a los restos de una tradición que está documentada en la zona, cuyos orígenes se remontan a la época romana, a raíz de la conquista del norte de la península ibérica por parte de las tropas de Augusto. metadata Oria Chaveli, Pablo and Gómez Eguren, José Manuel and González Rodríguez, Diego mail pablo.oria@uneatlantico.es, UNSPECIFIED, UNSPECIFIED (2023) Proyecto de conservación y recuperación de cepas ancestrales en el Municipio de Suances. Jose Manuel Gómez Eguren, Cantabria. ISBN 978-84-09-5111-0

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Fundación Universitaria Internacional de Colombia > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Inglés Railway track faults may lead to railway accidents and cause human and financial loss. Spatial, temporal, and weather elements, and wear and tear, lead to ballast, loose nuts, misalignment, and cracks leading to accidents. Manual inspection of such defects is time-consuming and prone to errors. Automatic inspection provides a fast, reliable, and unbiased solution. However, highly accurate fault detection is challenging due to the lack of public datasets, noisy data, inefficient models, etc. To obtain better performance, this study presents a novel approach that relies on mel frequency cepstral coefficient features from acoustic data. The primary objective of this study is to increase fault detection performance. As well as designing an ensemble model, we utilize selective features using chi-square(chi2) that have high importance with respect to the target class. Extensive experiments were carried out to analyze the efficiency of the proposed approach. The experimental results suggest that using 60 features, 40 original features, and 20 chi2 features produces optimal results both regarding accuracy and computational complexity. A mean accuracy score of 0.99 was obtained using the proposed approach with machine learning models using the collected data. Moreover, this performance was significantly better than that of existing approaches; however, the performance of models may vary in real-world settings. metadata Rustam, Furqan and Ishaq, Abid and Hashmi, Muhammad Shadab Alam and Siddiqui, Hafeez Ur Rehman and Dzul Lopez, Luis and Castanedo Galán, Juan and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, luis.dzul@unini.edu.mx, juan.castanedo@uneatlantico.es, UNSPECIFIED (2023) Railway Track Fault Detection Using Selective MFCC Features from Acoustic Data. Sensors, 23 (16). p. 7018. ISSN 1424-8220

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Fundación Universitaria Internacional de Colombia > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Inglés Non-word and real-word errors are generally two types of spelling errors. Non-word errors are misspelled words that are nonexistent in the lexicon while real-word errors are misspelled words that exist in the lexicon but are used out of context in a sentence. Lexicon-based lookup approach is widely used for non-word errors but it is incapable of handling real-word errors as they require contextual information. Contrary to the English language, real-word error detection and correction for low-resourced languages like Urdu is an unexplored area. This paper presents a real-word spelling error detection and correction approach for the Urdu language. We develop an extensive lexicon of 593,738 words and use this lexicon to develop a dataset for real-word errors comprising 125562 sentences and 2,552,735 words. Based on the developed lexicon and dataset, we then develop a contextual spell checker that detects and corrects real-word errors. For the real-word error detection phase, word-gram features are used along with five machine learning classifiers, achieving a precision, recall, and F1-score of 0.84,0.79, and 0.81 respectively. We also test the proposed approach with a 40% error density. For real-word error correction, the Damerau-Levenshtein distance is used along with the n-gram model for further ranking of the suggested candidate words, achieving an accuracy of up to 83.67%. metadata Aziz, Romila and Anwar, Muhammad Waqas and Jamal, Muhammad Hasan and Bajwa, Usama Ijaz and Kuc Castilla, Ángel Gabriel and Uc-Rios, Carlos and Bautista Thompson, Ernesto and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, carlos.uc@unini.edu.mx, ernesto.bautista@unini.edu.mx, UNSPECIFIED (2023) Real Word Spelling Error Detection and Correction for Urdu Language. IEEE Access. p. 1. ISSN 2169-3536

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Inglés Software cost and effort estimation is one of the most significant tasks in the area of software engineering. Research conducted in this field has been evolving with new techniques that necessitate periodic comparative analyses. Software project success largely depends on accurate software cost estimation as it gives an idea of the challenges and risks involved in the development. The great diversity of ML and Non-ML techniques has generated a comparison and progressed into the integration of these techniques. Based on varying advantages it has become imperative to work out preferred estimation techniques to improve the project development process. This study aims to present a systematic literature review (SLR) to investigate the trends of the articles published in the recent one and a half decades and to propose a way forward. This systematic literature review has proposed a three-stage approach to plan (Tollgate approach), conduct (Likert type scale), and report the results from five renowned digital libraries. For the selected 52 articles, artificial neural network model (ANN) and constructive cost model (COCOMO) based approaches have been the favored techniques. The mean magnitude of relative error (MMRE) has been the preferred accuracy metric, software engineering, and project management are the most relevant fields, and the promise repository has been identified as the widely accessed database. This review is likely to be of value for the development, cost, and effort estimations. metadata Rashid, Chaudhary Hamza and Shafi, Imran and Ahmad, Jamil and Bautista Thompson, Ernesto and Masías Vergara, Manuel and Diez, Isabel De La Torre and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, ernesto.bautista@unini.edu.mx, manuel.masias@uneatlantico.es, UNSPECIFIED, UNSPECIFIED (2023) Software Cost and Effort Estimation: Current Approaches and Future Trends. IEEE Access. p. 1. ISSN 2169-3536

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Fundación Universitaria Internacional de Colombia > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Inglés Safety critical spare parts hold special importance for aviation organizations. However, accurate forecasting of such parts becomes challenging when the data are lumpy or intermittent. This research paper proposes an artificial neural network (ANN) model that is able to observe the recent trends of error surface and responds efficiently to the local gradient for precise spare prediction results marked by lumpiness. Introduction of the momentum term allows the proposed ANN model to ignore small variations in the error surface and to behave like a low-pass filter and thus to avoid local minima. Using the whole collection of aviation spare parts having the highest demand activity, an ANN model is built to predict the failure of aircraft installed parts. The proposed model is first optimized for its topology and is later trained and validated with known historical demand datasets. The testing phase includes introducing input vector comprising influential factors that dictate sporadic demand. The proposed approach is found to provide superior results due to its simple architecture and fast converging training algorithm once evaluated against some other state-of-the-art models from the literature using related benchmark performance criteria. The experimental results demonstrate the effectiveness of the proposed approach. The accurate prediction of the cost-heavy and critical spare parts is expected to result in huge cost savings, reduce downtime, and improve the operational readiness of drones, fixed wing aircraft and helicopters. This also resolves the dead inventory issue as a result of wrong demands of fast moving spares due to human error. metadata Shafi, Imran and Sohail, Amir and Ahmad, Jamil and Martínez Espinosa, Julio César and Dzul Lopez, Luis Alonso and Bautista Thompson, Ernesto and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, luis.dzul@unini.edu.mx, ernesto.bautista@unini.edu.mx, UNSPECIFIED (2023) Spare Parts Forecasting and Lumpiness Classification Using Neural Network Model and Its Impact on Aviation Safety. Applied Sciences, 13 (9). p. 5475. ISSN 2076-3417

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production Abierto Inglés Stress is now a serious disease that exists due to changes in working life and food ecosystems around the world. In general, it is difficult for a person to know if they are under stress. According to previous research, temperature, heart rate variability (HRV), humidity, and blood pressure are used to assess stress levels with the use of instruments. With the development of sensor technology and wireless connectivity, people around the world are adopting and using smart devices. In this study, a bio signal detection device with Internet of Things (IoT) capability with a galvanic skin reaction (GSR) sensor is proposed and built for real-time stress monitoring. The proposed device is based on an Arduino controller and Bluetooth communication. To evaluate the performance of the system, physical stress is created on 10 different participants with three distinct tasks namely reading, visualizing the timer clock, and watching videos. MATLAB analysis is performed for identifying the three different levels of stress and obtaining the threshold values as if the person GSR voltage i.e., relaxed for <1.75 volts; Normal: between 1.75 and 1.44 volts and stressed: >1.44 volts. In addition, LabVIEW is used as a data acquisition system, and a Blueterm mobile application is also used to view the sensor reading received from the device through Bluetooth communication. metadata Singh, Rajesh and Gehlot, Anita and Saxena, Ritika and Alsubhi, Khalid and Anand, Divya and Delgado Noya, Irene and Vaseem Akram, Shaik and Choudhury, Sushabhan mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, divya.anand@uneatlantico.es, irene.delgado@uneatlantico.es, UNSPECIFIED, UNSPECIFIED (2023) Stress Detector Supported Galvanic Skin Response System with IoT and LabVIEW GUI. Computers, Materials & Continua, 74 (1). pp. 1217-1233. ISSN 1546-2226

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Inglés Data mining is an analytical approach that contributes to achieving a solution to many problems by extracting previously unknown, fascinating, nontrivial, and potentially valuable information from massive datasets. Clustering in data mining is used for splitting or segmenting data items/points into meaningful groups and clusters by grouping the items that are near to each other based on certain statistics. This paper covers various elements of clustering, such as algorithmic methodologies, applications, clustering assessment measurement, and researcher-proposed enhancements with their impact on data mining thorough grasp of clustering algorithms, its applications, and the advances achieved in the existing literature. This study includes a literature search for papers published between 1995 and 2023, including conference and journal publications. The study begins by outlining fundamental clustering techniques along with algorithm improvements and emphasizing their advantages and limitations in comparison to other clustering algorithms. It investigates the evolution measures for clustering algorithms with an emphasis on metrics used to gauge clustering quality, such as the F-measure and the Rand Index. This study includes a variety of clustering-related topics, such as algorithmic approaches, practical applications, metrics for clustering evaluation, and researcher-proposed improvements. It addresses numerous methodologies offered to increase the convergence speed, resilience, and accuracy of clustering, such as initialization procedures, distance measures, and optimization strategies. The work concludes by emphasizing clustering as an active research area driven by the need to identify significant patterns and structures in data, enhance knowledge acquisition, and improve decision making across different domains. This study aims to contribute to the broader knowledge base of data mining practitioners and researchers, facilitating informed decision making and fostering advancements in the field through a thorough analysis of algorithmic enhancements, clustering assessment metrics, and optimization strategies. metadata Chaudhry, Mahnoor and Shafi, Imran and Mahnoor, Mahnoor and Ramírez-Vargas, Debora L. and Bautista Thompson, Ernesto and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, debora.ramirez@unini.edu.mx, ernesto.bautista@unini.edu.mx, UNSPECIFIED (2023) A Systematic Literature Review on Identifying Patterns Using Unsupervised Clustering Algorithms: A Data Mining Perspective. Symmetry, 15 (9). p. 1679. ISSN 2073-8994

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Inglés Disaster management is a critical area that requires efficient methods and techniques to address various challenges. This comprehensive assessment offers an in-depth overview of disaster management systems, methods, obstacles, and potential future paths. Specifically, it focuses on flood control, a significant and recurrent category of natural disasters. The analysis begins by exploring various types of natural catastrophes, including earthquakes, wildfires, and floods. It then delves into the different domains that collectively contribute to effective flood management. These domains encompass cutting-edge technologies such as big data analysis and cloud computing, providing scalable and reliable infrastructure for data storage, processing, and analysis. The study investigates the potential of the Internet of Things and sensor networks to gather real-time data from flood-prone areas, enhancing situational awareness and enabling prompt actions. Model-driven engineering is examined for its utility in developing and modeling flood scenarios, aiding in preparation and response planning. This study includes the Google Earth engine (GEE) and examines previous studies involving GEE. Moreover, we discuss remote sensing; remote sensing is undoubtedly a valuable tool for disaster management, and offers geographical data in various situations. We explore the application of Geographical Information System (GIS) and Spatial Data Management for visualizing and analyzing spatial data and facilitating informed decision-making and resource allocation during floods. In the final section, the focus shifts to the utilization of machine learning and data analytics in flood management. These methodologies offer predictive models and data-driven insights, enhancing early warning systems, risk assessment, and mitigation strategies. Through this in-depth analysis, the significance of incorporating these spheres into flood control procedures is highlighted, with the aim of improving disaster management techniques and enhancing resilience in flood-prone regions. The paper addresses existing challenges and provides future research directions, ultimately striving for a clearer and more coherent representation of disaster management techniques. metadata Khan, Saad Mazhar and Shafi, Imran and Butt, Wasi Haider and Diez, Isabel de la Torre and López Flores, Miguel Ángel and Castanedo Galán, Juan and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, miguelangel.lopez@uneatlantico.es, juan.castanedo@uneatlantico.es, UNSPECIFIED (2023) A Systematic Review of Disaster Management Systems: Approaches, Challenges, and Future Directions. Land, 12 (8). p. 1514. ISSN 2073-445X

Article Subjects > Biomedicine
Subjects > Engineering
Subjects > Nutrition Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Cerrado Inglés Obesity and overweight has increased in the last year and has become a pandemic disease, the result of sedentary lifestyles and unhealthy diets rich in sugars, refined starches, fats and calories. Machine learning (ML) has proven to be very useful in the scientific community, especially in the health sector. With the aim of providing useful tools to help nutritionists and dieticians, research focused on the development of ML and Deep Learning (DL) algorithms and models is searched in the literature. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol has been used, a very common technique applied to carry out revisions. In our proposal, 17 articles have been filtered in which ML and DL are applied in the prediction of diseases, in the delineation of treatment strategies, in the improvement of personalized nutrition and more. Despite expecting better results with the use of DL, according to the selected investigations, the traditional methods are still the most used and the yields in both cases fluctuate around positive values, conditioned by the databases (transformed in each case) to a greater extent than by the artificial intelligence paradigm used. Conclusions: An important compilation is provided for the literature in this area. ML models are time-consuming to clean data, but (like DL) they allow automatic modeling of large volumes of data which makes them superior to traditional statistics. metadata Ferreras, Antonio and Sumalla Cano, Sandra and Martínez-Licort, Rosmeri and Elío Pascual, Iñaki and Tutusaus, Kilian and Prola, Thomas and Vidal Mazón, Juan Luis and Sahelices, Benjamín and de la Torre Díez, Isabel mail UNSPECIFIED, sandra.sumalla@uneatlantico.es, UNSPECIFIED, inaki.elio@uneatlantico.es, kilian.tutusaus@uneatlantico.es, thomas.prola@uneatlantico.es, juanluis.vidal@uneatlantico.es, UNSPECIFIED, UNSPECIFIED (2023) Systematic Review of Machine Learning applied to the Prediction of Obesity and Overweight. Journal of Medical Systems, 47 (1). ISSN 1573-689X

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Fundación Universitaria Internacional de Colombia > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Inglés With a view of the post-COVID-19 world and probable future pandemics, this paper presents an Internet of Things (IoT)-based automated healthcare diagnosis model that employs a mixed approach using data augmentation, transfer learning, and deep learning techniques and does not require physical interaction between the patient and physician. Through a user-friendly graphic user interface and availability of suitable computing power on smart devices, the embedded artificial intelligence allows the proposed model to be effectively used by a layperson without the need for a dental expert by indicating any issues with the teeth and subsequent treatment options. The proposed method involves multiple processes, including data acquisition using IoT devices, data preprocessing, deep learning-based feature extraction, and classification through an unsupervised neural network. The dataset contains multiple periapical X-rays of five different types of lesions obtained through an IoT device mounted within the mouth guard. A pretrained AlexNet, a fast GPU implementation of a convolutional neural network (CNN), is fine-tuned using data augmentation and transfer learning and employed to extract the suitable feature set. The data augmentation avoids overtraining, whereas accuracy is improved by transfer learning. Later, support vector machine (SVM) and the K-nearest neighbors (KNN) classifiers are trained for lesion classification. It was found that the proposed automated model based on the AlexNet extraction mechanism followed by the SVM classifier achieved an accuracy of 98%, showing the effectiveness of the presented approach. metadata Shafi, Imran and Sajad, Muhammad and Fatima, Anum and Gavilanes Aray, Daniel and Lipari, Vivian and Diez, Isabel de la Torre and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, daniel.gavilanes@uneatlantico.es, vivian.lipari@uneatlantico.es, UNSPECIFIED, UNSPECIFIED (2023) Teeth Lesion Detection Using Deep Learning and the Internet of Things Post-COVID-19. Sensors, 23 (15). p. 6837. ISSN 1424-8220

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production Abierto Inglés In this paper, a novel ultra-wideband UWB antenna element with triple-band notches is proposed. The proposed UWB radiator element operates from 2.03 GHz up to 15.04 GHz with triple rejected bands at the WiMAX band (3.28–3.8 GHz), WLAN band (5.05–5.9 GHz), and X-band (7.78–8.51 GHz). In addition, the radiator supports the Bluetooth band (2.4–2.483 GHz). Three different techniques were utilized to obtain the triple-band notches. An alpha-shaped coupled line with a stub-loaded resonator (SLR) band stop filter was inserted along the main feeding line before the radiator to obtain a WiMAX band notch characteristic. Two identical U-shaped slots were etched on the proposed UWB radiator to achieve WLAN band notch characteristics with a very high degree of selectivity. Two identical metallic frames of an octagon-shaped electromagnetic band gap structure (EBG) were placed along the main feeding line to achieve the notch characteristic with X-band satellite communication with high sharpness edges. A novel UWB multiple-input multiple-output (MIMO) radiator is proposed. The proposed UWB-MIMO radiator was fabricated on FR-4 substrate material and measured. The isolation between every two adjacent ports was below −20 dB over the FCC-UWB spectrum and the Bluetooth band for the four MIMO antennas. The envelope correlation coefficient (ECC) between the proposed antennas in MIMO does not exceed 0.05. The diversity gains (DG) for all the radiators are greater than 9.98 dB. metadata El-Gendy, Mohamed S. and Ali, Mohamed Mamdouh M. and Bautista Thompson, Ernesto and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, ernesto.bautista@unini.edu.mx, UNSPECIFIED (2023) Triple-Band Notched Ultra-Wideband Microstrip MIMO Antenna with Bluetooth Band. Sensors, 23 (9). p. 4475. ISSN 1424-8220

Article Subjects > Biomedicine
Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Fundación Universitaria Internacional de Colombia > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Inglés This study sought to investigate how different brain regions are affected by Alzheimer’s disease (AD) at various phases of the disease, using independent component analysis (ICA). The study examines six regions in the mild cognitive impairment (MCI) stage, four in the early stage of Alzheimer’s disease (AD), six in the moderate stage, and six in the severe stage. The precuneus, cuneus, middle frontal gyri, calcarine cortex, superior medial frontal gyri, and superior frontal gyri were the areas impacted at all phases. A general linear model (GLM) is used to extract the voxels of the previously mentioned regions. The resting fMRI data for 18 AD patients who had advanced from MCI to stage 3 of the disease were obtained from the ADNI public source database. The subjects include eight women and ten men. The voxel dataset is used to train and test ten machine learning algorithms to categorize the MCI, mild, moderate, and severe stages of Alzheimer’s disease. The accuracy, recall, precision, and F1 score were used as conventional scoring measures to evaluate the classification outcomes. AdaBoost fared better than the other algorithms and obtained a phenomenal accuracy of 98.61%, precision of 99.00%, and recall and F1 scores of 98.00% each. metadata Shahzadi, Samra and Butt, Naveed Anwer and Sana, Muhammad Usman and Elío Pascual, Iñaki and Briones Urbano, Mercedes and Díez, Isabel de la Torre and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, inaki.elio@uneatlantico.es, mercedes.briones@uneatlantico.es, UNSPECIFIED, UNSPECIFIED (2023) Voxel Extraction and Multiclass Classification of Identified Brain Regions across Various Stages of Alzheimer’s Disease Using Machine Learning Approaches. Diagnostics, 13 (18). p. 2871. ISSN 2075-4418

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production Cerrado Inglés The Internet of Things (IoT) is a network of interconnected devices that includes low-end devices (sensors) and high-end devices (servers). The routing protocol used the Low-Power and Lossy Networks (RPL) protocol, which was designed to collect data in Low-Power and Lossy Networks (LLN) efficiently and reliably. The RPL rank property specifies how sensor nodes are placed in Destination Oriented Directed Acyclic Graphs (DODAG) based on an Objective Function (OF). The OF includes information such as the Expected Transmission Count (ETX) and packet delivery rate. The rank property aids in routing path optimization, reducing control overhead, and maintaining a loop-free topology by using rank-based data path validation. However, it causes many issues, such as optimal parent selection, next-hop node selection, and network instability. We proposed an Enhanced Opportunistic Rank-based Parent Node Selection for Sustainable and Smart IoT Networks to address these issues. The optimal parent node is determined by forecasting the expected energy of each node using Received Signal Strength (RSS) and an enhanced reinforcement learning algorithm. The proposed method addresses the issue of selecting the next-hop neighbor node and improves routing stability. Furthermore, when a large number of new nodes try to join the sustainable IoT-based smart cities, the proposed technique provides optimal load balance metadata Chithaluru, Premkumar and Singh, Aman and Mahmoud, Mahmoud Shuker and Kumar, Sunil and Vidal Mazón, Juan Luis and Alkhayyat, Ahmed and Anand, Divya mail UNSPECIFIED, aman.singh@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, juanluis.vidal@uneatlantico.es, UNSPECIFIED, divya.anand@uneatlantico.es (2023) An enhanced opportunistic rank-based parent node selection for sustainable & smart IoT networks. Sustainable Energy Technologies and Assessments, 56. p. 103079. ISSN 22131388

2022

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Fundación Universitaria Internacional de Colombia > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Inglés The fast expansion of ICT (information and communications technology) has provided rich sources of data for the analysis, modeling, and interpretation of human mobility patterns. Many researchers have already introduced behavior-aware protocols for a better understanding of architecture and realistic modeling of behavioral characteristics, similarities, and aggregation of mobile users. We are introducing the similarity analytical framework for the mobile encountering analysis to allow for more direct integration between the physical world and cyber-based systems. In this research, we propose a method for finding the similarity behavior of users’ mobility patterns based on location and time. This research was conducted to develop a technique for producing co-occurrence matrices of users based on their similar behaviors to determine their encounters. Our approach, named SAA (similarity analysis approach), makes use of the device info i.e., IP (internet protocol) and MAC (media access control) address, providing an in-depth analysis of similarity behaviors on a daily basis. We analyzed the similarity distributions of users on different days of the week for different locations based on their real movements. The results show similar characteristics of users with common mobility behaviors based on location and time to showcase the efficacy. The results show that the proposed SAA approach is 33% more accurate in terms of recognizing the user’s similarity as compared to the existing similarity approach. metadata Memon, Ambreen and Kilby, Jeff and Breñosa, Jose and Martínez Espinosa, Julio César and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, josemanuel.brenosa@uneatlantico.es, ulio.martinez@unini.edu.mx, UNSPECIFIED (2022) Analysis and Implementation of Human Mobility Behavior Using Similarity Analysis Based on Co-Occurrence Matrix. Sensors, 22 (24). p. 9898. ISSN 1424-8220

Article Subjects > Social Sciences
Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Fundación Universitaria Internacional de Colombia > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Inglés Innovation plays a pivotal role in the progress and goodwill of an organization, and its ability to thrive. Consequently, the impact analysis of innovation on the performance of an organization holds great importance. This paper presents a two-stage analytical framework to examine the impact of business innovation on a firm’s performance, especially firms from the manufacturing sector. The prime objective is to identify the factors that have an impact on firm-level innovation, and to examine the impact of firm-level innovation on business performance. The framework and its analysis are based on the latest World Bank enterprise survey, with a sample size of 696 manufacturing firms. The first stage of the proposed framework establishes the analytical results through Bivariate Probit, which indicates that research and development (R&D) has a significantly positive impact on the product, process, marketing, and organizational innovations. It thus highlights the important role of the allocation of lump-sum amounts for R&D activities. The statistical analysis shows that innovation does not depend on the size of the firms. Moreover, the older firms are found to be wiser at conducting R&D than newer firms that are reluctant to take risks. The second stage of the proposed framework separately analyzes the impacts of the product and organizational innovation, and the process and marketing innovation on the firm performance, and finds them to be statistically significant and insignificant, respectively. metadata Aslam, Mahrukh and Shafi, Imran and Ahmad, Jamil and Álvarez, Roberto Marcelo and Miró Vera, Yini Airet and Soriano Flores, Emmanuel and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, roberto.alvarez@uneatlantico.es, yini.miro@uneatlantico.es, emmanuel.soriano@uneatlantico.es, UNSPECIFIED (2022) An Analytical Framework for Innovation Determinants and Their Impact on Business Performance. Sustainability, 15 (1). p. 458. ISSN 2071-1050

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production Abierto Inglés With the global spread of COVID-19, the governments advised the public for adopting safety precautions to limit its spread. The virus spreads from people, contaminated places, and nozzle droplets that necessitate strict precautionary measures. Consequently, different safety precautions have been implemented to fight COVID-19 such as wearing a facemask, restriction of social gatherings, keeping 6 feet distance, etc. Despite the warnings, highlighted need for such measures, and the increasing severity of the pandemic situation, the expected number of people adopting these precautions is low. This study aims at assessing and understanding the public perception of COVID-19 safety precautions, especially the use of facemask. A unified framework of sentiment lexicon with the proposed ensemble EB-DT is devised to analyze sentiments regarding safety precautions. Extensive experiments are performed with a large dataset collected from Twitter. In addition, the factors leading to a negative perception of safety precautions are analyzed by performing topic analysis using the Latent Dirichlet allocation algorithm. The experimental results reveal that 12% of the tweets correspond to negative sentiments towards facemask precaution mainly by its discomfort. Analysis of change in peoples’ sentiment over time indicates a gradual increase in the positive sentiments regarding COVID-19 restrictions. metadata Qamar, Usman and Ahmad, Ayaz and Rustam, Furqan and Saad, Eysha and Siddique, Muhammad Abubakar and Lee, Ernesto and Ortega-Mansilla, Arturo and Díez, Isabel de la Torre and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, arturo.ortega@uneatlantico.es, UNSPECIFIED, UNSPECIFIED (2022) Analyzing preventive precautions to limit spread of COVID-19. PLOS ONE, 17 (8). e0272350. ISSN 1932-6203

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production Abierto Inglés Industries need solutions that can automatically monitor oil leakage from deployed underwater pipelines and to rapidly report any damage. The location prediction of mineral reservoirs like oil, gas, or metals in deep water is a challenge during the extraction of these resources. Moreover, the problem of ores and mineral deposits on the seafloor comes into play. The abovementioned challenges necessitate for the deployment of underwater wireless sensor networks (UWSNs). Anchor-based localization techniques are segregated into range-free and range-based processes. Range-based schemes depend on various techniques like angle of arrival (AoA), time of arrival (ToA), time difference of arrival (TDoA), and received signal strength indicator (RSSI). In this article, the localization of these leakages is performed by using range-based metrics for calculating the distance among anchor nodes (ANs) and target nodes (TNs). This estimated distance is further optimized to minimize the estimation error. A multilateralism procedure is used to estimate the optimal position of each TN. The results exhibit that the proposed algorithm shows a high performance when compared to previous works, in terms of minimum energy consumption, lower packet loss, rapid location estimation, and lowest localization error. The benefit of using the proposed methodology greatly impacts on identifying the leakage area in mobility-assisted UWSN, where rapid reporting helps to lower the loss of resources. metadata Goyal, Nitin and Nain, Mamta and Singh, Aman and Abualsaud, Khalid and Alsubhi, Khalid and Ortega-Mansilla, Arturo and Zorba, Nizar mail UNSPECIFIED, UNSPECIFIED, aman.singh@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, arturo.ortega@uneatlantico.es, UNSPECIFIED (2022) An Anchor-Based Localization in Underwater Wireless Sensor Networks for Industrial Oil Pipeline Monitoring. IEEE Canadian Journal of Electrical and Computer Engineering, 45 (4). pp. 466-474. ISSN 2694-1783

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Fundación Universitaria Internacional de Colombia > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Inglés The demand for cloud computing has drastically increased recently, but this paradigm has several issues due to its inherent complications, such as non-reliability, latency, lesser mobility support, and location-aware services. Fog computing can resolve these issues to some extent, yet it is still in its infancy. Despite several existing works, these works lack fault-tolerant fog computing, which necessitates further research. Fault tolerance enables the performing and provisioning of services despite failures and maintains anti-fragility and resiliency. Fog computing is highly diverse in terms of failures as compared to cloud computing and requires wide research and investigation. From this perspective, this study primarily focuses on the provision of uninterrupted services through fog computing. A framework has been designed to provide uninterrupted services while maintaining resiliency. The geographical information system (GIS) services have been deployed as a test bed which requires high computation, requires intensive resources in terms of CPU and memory, and requires low latency. Keeping different types of failures at different levels and their impacts on service failure and greater response time in mind, the framework was made anti-fragile and resilient at different levels. Experimental results indicate that during service interruption, the user state remains unaffected. metadata Mir, Tahira Sarwar and Liaqat, Hannan Bin and Kiren, Tayybah and Sana, Muhammad Usman and Álvarez, Roberto Marcelo and Miró Vera, Yini Airet and Pascual Barrera, Alina Eugenia and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, roberto.alvarez@uneatlantico.es, yini.miro@uneatlantico.es, alina.pascual@unini.edu.mx, UNSPECIFIED (2022) Antifragile and Resilient Geographical Information System Service Delivery in Fog Computing. Sensors, 22 (22). p. 8778. ISSN 1424-8220

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production Abierto Inglés, Español Actualmente la gestión de proyectos cuenta con muchas herramientas y metodologías que buscan desarrollar proyectos exitosos, no siempre es posible cumplir con los objetivos fijados desde su concepción. Una gran parte de los proyectos de construcción son ejecutados sin ser evaluados y documentados adecuadamente a lo largo de su ciclo de vida, aumentando las probabilidades de ser un proyecto fallido y de no cumplir con la rentabilidad o uso esperado. El caso de estudio es sobre un proyecto hidroeléctrico que fue iniciado con personal propio de una empresa privada hondureña (EPH)[1], que al poco tiempo empezó a presentar una serie de inconvenientes que generaron desfases en costos y en tiempo. Cuando se había utilizado el 85% del presupuesto original estimado y se observa un avance de obra menor al 50%, la EPH decidió contratar a una empresa supervisora externa (ESE) para darle seguimiento al proyecto, revisar el diseño del mismo y que se asegurara que el proyecto fuera culminado. El proyecto fue culminado con un año y ocho meses adicionales de construcción y el costo del total final superó en 7.5 millones de dólares americanos del presupuesto original. El objetivo principal de esta investigación es la de analizar la eficiencia y sostenibilidad del proyecto para obtener lecciones que posibiliten la identificación de las fallas y aciertos en los desvíos alcanzados a lo largo del mismo y, a partir de ellos, generar recomendaciones que le permitan a la organización corregir y mejorar su actual metodología para sus futuros proyectos. metadata Ramírez López, Ana Mellissa and Mazzetto, Matías Ariel mail UNSPECIFIED (2022) Análisis y mejores prácticas proyectuales de una obra civil hidroeléctrica de Honduras. Project Design and Management, 4 (2). ISSN 2683-1597

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Inglés Population and industrial growth in Mexico’s Bajío region demand greater electricity consumption. The production of electricity from fuel oil has severe implications on climate change and people’s health due to SO2 emissions. This study describes the simulation of eight different scenarios for SO2 pollutant dispersion. It takes into account distance, geoenvironmental parameters, wind, terrain roughness, and Pasquill–Gifford–Turner atmospheric stability and categories of dispersion based on technical information about SO2 concentration from stacks and from one of the atmospheric monitoring stations in Salamanca city. Its transverse character, its usefulness for modeling, and epidemiological, meteorological, and fluid dynamics studies, as suggested by the models approved by the Environmental Protection Agency (EPA), show a maximum average concentration of 399 µg/m3, at an average distance of 1800 m. The best result comparison in the scenarios was scenery 8. Maximum nocturnal dispersion was shown at a wind speed of 8.4 m/s, and an SO2 concentration of 280 µg/m3 for stack 4, an atypical situation due to the geography of the city. From the validation process, a relative error of 14.7 % was obtained, which indicates the reliability of the applied Gaussian model. Regarding the mathematical solution of the model, this represents a reliable and low-cost tool that can help improve air quality management, the location or relocation of atmospheric monitoring stations, and migration from the use of fossil fuels to environmentally friendly fuels. metadata Violante Gavira, Amanda Enrriqueta and Sosa González, Wadi Elim and Pali-Casanova, Ramón and Yam Cervantes, Marcial Alfredo and Aguilar Vega, Manuel and Chacha Coto, Javier and Zavala Loría, José del Carmen and Dzul López, Luis Alonso and García Villena, Eduardo mail amanda@ugto.mx, UNSPECIFIED, ramon.pali@unini.edu.mx, marcial.yam@unini.edu.mx, UNSPECIFIED, UNSPECIFIED, jose.zavala@unini.edu.mx, luis.dzul@uneatlantico.es, eduardo.garcia@uneatlantico.es (2022) Application of the Gaussian Model for Monitoring Scenarios and Estimation of SO2 Atmospheric Emissions in the Salamanca Area, Bajío, Mexico. Atmosphere, 13 (6). p. 874. ISSN 2073-4433

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Inglés With rapid urbanization, high rates of industrialization, and inappropriate waste disposal, water quality has been substantially degraded during the past decade. So, water quality prediction, an essential element for a healthy society, has become a task of great significance to protecting the water environment. Existing approaches focus predominantly on either water quality or water consumption prediction, utilizing complex algorithms that reduce the accuracy of imbalanced datasets and increase computational complexity. This study proposes a simple architecture of neural networks which is more efficient and accurate and can work for predicting both water quality and water consumption. An artificial neural network (ANN) consisting of one hidden layer and a couple of dropout and activation layers is utilized in this regard. The approach is tested using two datasets for predicting water quality and water consumption. Results show a 0.96 accuracy for water quality prediction which is better than existing studies. A 0.99 R2 score is obtained for water consumption prediction which is superior to existing state-of-the-art approaches. metadata Rustam, Furqan and Ishaq, Abid and Kokab, Sayyida Tabinda and de la Torre Diez, Isabel and Vidal Mazón, Juan Luis and Rodríguez Velasco, Carmen Lilí and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, juanluis.vidal@uneatlantico.es, carmen.rodriguez@uneatlantico.es, UNSPECIFIED (2022) An Artificial Neural Network Model for Water Quality and Water Consumption Prediction. Water, 14 (21). p. 3359. ISSN 2073-4441

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production Abierto Inglés UNSPECIFIED metadata Kimothi, Sanjeev and Thapliyal, Asha and Akram, Shaik Vaseem and Singh, Rajesh and Gehlot, Anita and Mohamed, Heba G. and Anand, Divya and Ibrahim, Muhammad and Delgado Noya, Irene mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, divya.anand@uneatlantico.es, UNSPECIFIED, irene.delgado@uneatlantico.es (2022) Big Data Analysis Framework for Water Quality Indicators with Assimilation of IoT and ML. Electronics, 11 (13). p. 1927. ISSN 2079-9292

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Inglés The highly fragmented blockchain and cryptocurrency ecosystem necessitates interoperability mechanisms as a requirement for blockchain-technology acceptance. The immediate implication of interchain interoperability is automatic swapping between cryptocurrencies. We performed a systematic review of the existing literature on Blockchain interoperability and atomic cross-chain transactions. We investigated different blockchain interoperability approaches, including industrial solutions, categorized them and identified the key mechanisms used, and list several example projects for each category. We focused on the atomic transactions between blockchain, a process also known as atomic swap. Furthermore, we studied recent implementations along with architectural approaches for atomic swap and deduced research issues and challenges in cross-chain interoperability and atomic swap. Atomic swap can instantly transfer tokens and significantly reduce the associated costs without using any centralized authority, and thus facilitates the development of a sustainable payment system for wider financial inclusion. metadata Mohanty, Debasis and Anand, Divya and Aljahdali, Hani Moaiteq and Gracia Villar, Santos mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, santos.gracia@uneatlantico.es (2022) Blockchain Interoperability: Towards a Sustainable Payment System. Sustainability, 14 (2). p. 913. ISSN 2071-1050

Conference or Workshop Item Subjects > Engineering Europe University of Atlantic > Research > Scientific Production Cerrado Inglés Emergence of IoT applications and distributed computing has propelled the development of computing services which can handle dynamic requests at the network edge. Fog computing paradigm has evolved tremendously over the years for achieving above objective. Resource management in fog layer always remains the hot spot which is required to be addressed through some efficient load balancing techniques. Heuristic, Meta-heuristic, Probabilistic, Graph theory based and hybrid load balancing techniques are developed over the past few years to manage workload incurred at the fog servers. This paper provides the brief description of such methods and their comparative analysis in a tabular form. Major area of focus is the overall technique, simulation tool, parameters of evaluation, advantages and disadvantages of the proposed load balancing approaches. Potential researchers can carry forward and extend this research at the next level after analysing the research gaps from the literature survey. metadata Batra, Salil and Anand, Divya and Singh, Aman mail UNSPECIFIED, UNSPECIFIED, aman.singh@uneatlantico.es (2022) A Brief Overview of Load Balancing Techniques in Fog Computing Environment. In: 2022 6th International Conference on Trends in Electronics and Informatics (ICOEI 2022), 28-30 April 2022, Tirunelveli, India..

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Inglés Building energy consumption prediction has become an important research problem within the context of sustainable homes and smart cities. Data-driven approaches have been regarded as the most suitable for integration into smart houses. With the wide deployment of IoT sensors, the data generated from these sensors can be used for modeling and forecasting energy consumption patterns. Existing studies lag in prediction accuracy and various attributes of buildings are not very well studied. This study follows a data-driven approach in this regard. The novelty of the paper lies in the fact that an ensemble model is proposed, which provides higher performance regarding cooling and heating load prediction. Moreover, the influence of different features on heating and cooling load is investigated. Experiments are performed by considering different features such as glazing area, orientation, height, relative compactness, roof area, surface area, and wall area. Results indicate that relative compactness, surface area, and wall area play a significant role in selecting the appropriate cooling and heating load for a building. The proposed model achieves 0.999 R2 for heating load prediction and 0.997 R2 for cooling load prediction, which is superior to existing state-of-the-art models. The precise prediction of heating and cooling load, can help engineers design energy-efficient buildings, especially in the context of future smart homes metadata Chaganti, Rajasekhar and Rustam, Furqan and Daghriri, Talal and Díez, Isabel de la Torre and Vidal Mazón, Juan Luis and Rodríguez Velasco, Carmen Lilí and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, juanluis.vidal@uneatlantico.es, carmen.rodriguez@uneatlantico.es, UNSPECIFIED (2022) Building Heating and Cooling Load Prediction Using Ensemble Machine Learning Model. Sensors, 22 (19). p. 7692. ISSN 1424-8220

Conference or Workshop Item Subjects > Engineering Europe University of Atlantic > Research > Scientific Production Cerrado Inglés Education 4.0 is a gradually growing environment, which will affect every walks of our life over a couple of decades. The intent of this paper presents a brief study of the Education 4.0 environment. This study further elaborates and recommends the use of IFC (Internet of Things, Fog, and Cloud) technological-integration for the implementation of Education 4.0. The assessment and accreditation process that ensures the quality in the education industry will also be unveiled in this study. Real-time and intervallic scenarios of the assessment and accreditation process are also illustrated in this study. The intent of this study recommends the use of real-time assessment, prediction, irregularity detection, and alert generation under the ambient environment of Education 4.0. The study further recommends the use of an intervallic accreditation scenario for Education 4.0, which makes this modal suitable for both ideal and dynamic environments under Education 4.0. metadata Verma, Anil and Anand, Divya and Singh, Aman and Vij, Rishika mail UNSPECIFIED, divya.anand@uneatlantico.es, aman.singh@uneatlantico.es, UNSPECIFIED (2022) C-IoT Inspired Real-Time and Intervallic Accreditation Under Education 4.0. In: 2022 8th International Conference on Advanced Computing and Communication Systems (ICACCS).

Article Subjects > Biomedicine
Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Inglés Asthma is a deadly disease that affects the lungs and air supply of the human body. Coronavirus and its variants also affect the airways of the lungs. Asthma patients approach hospitals mostly in a critical condition and require emergency treatment, which creates a burden on health institutions during pandemics. The similar symptoms of asthma and coronavirus create confusion for health workers during patient handling and treatment of disease. The unavailability of patient history to physicians causes complications in proper diagnostics and treatments. Many asthma patient deaths have been reported especially during pandemics, which necessitates an efficient framework for asthma patients. In this article, we have proposed a blockchain consortium healthcare framework for asthma patients. The proposed framework helps in managing asthma healthcare units, coronavirus patient records and vaccination centers, insurance companies, and government agencies, which are connected through the secure blockchain network. The proposed framework increases data security and scalability as it stores encrypted patient data on the Interplanetary File System (IPFS) and keeps data hash values on the blockchain. The patient data are traceable and accessible to physicians and stakeholders, which helps in accurate diagnostics, timely treatment, and the management of patients. The smart contract ensures the execution of all business rules. The patient profile generation mechanism is also discussed. The experiment results revealed that the proposed framework has better transaction throughput, query delay, and security than existing solutions metadata Farooq, Muhammad Shoaib and Suhail, Maryam and Qureshi, Junaid Nasir and Rustam, Furqan and de la Torre Díez, Isabel and Vidal Mazón, Juan Luis and Rodríguez Velasco, Carmen Lilí and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, juanluis.vidal@uneatlantico.es, carmen.rodriguez@uneatlantico.es, UNSPECIFIED (2022) Consortium Framework Using Blockchain for Asthma Healthcare in Pandemics. Sensors, 22 (21). p. 8582. ISSN 1424-8220

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production Abierto Inglés Large-scale distributed systems have the advantages of high processing speeds and large communication bandwidths over the network. The processing of huge real-world data within a time constraint becomes tricky, due to the complexity of data parallel task scheduling in a time constrained environment. This paper proposes data parallel task scheduling in cloud to address the minimization of cost and time constraints. By running concurrent executions of tasks on multi-core cloud resources, the number of parallel executions could be increased correspondingly, thereby, finishing the task within the deadline is possible. A mathematical model is developed here to minimize the operational cost of data parallel tasks by feasibly assigning a load to each virtual machine in the cloud data center. This work experiments with a machine learning model that is replicated on the multi-core cloud heterogeneous resources to execute different input data concurrently to accomplish distributive learning. The outcome of concurrent execution of data-intensive tasks on different parts of the input dataset gives better solutions in terms of processing the task by the deadline at optimized cost. metadata Rajalakshmi, N. R. and Dumka, Ankur and Kumar, Manoj and Singh, Rajesh and Gehlot, Anita and Akram, Shaik Vaseem and Anand, Divya and Elkamchouchi, Dalia H. and Delgado Noya, Irene mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, divya.anand@uneatlantico.es, UNSPECIFIED, irene.delgado@uneatlantico.es (2022) A Cost-Optimized Data Parallel Task Scheduling with Deadline Constraints in Cloud. Electronics, 11 (13). p. 2022. ISSN 2079-9292

Article Subjects > Engineering
Subjects > Nutrition Europe University of Atlantic > Research > Scientific Production Abierto Inglés, Español El proyecto persigue el aprovechamiento de los residuos del sector alimentario cántabro (residuos cereales de la industria de bebidas espirituosas y el suero de leche), con el objeto de fabricar un sustrato plástico comestible, biodegradable y compostable, como alternativa a la producción de plásticos actual, aportando una solución a favor de la valorización de residuos industriales. Para el desarrollo del sustrato plástico comestible, se partió de los compuestos arabinoxilanos y kefirán, provenientes de residuos cereales y del suero lácteo respectivamente. Se desarrollaron varias formulaciones para crear un prototipo pre-industrial del biocompuesto para el sustrato plástico comestible, asimismo, se realizó una búsqueda sobre el uso del lactosuero para la obtención de biofilm. Se elaboró un plan de explotación que evidenció la necesidad de vender 1900 kg de pellets de bioplástico al mes para asegurar la viabilidad económica del proceso. Esta producción tendría un coste unitario de 15 €/kg, inferior al precio de venta estimado de 20€/kg. Aunque se estima que el margen de beneficio empresarial no sería muy alto, los impactos ambientales positivos son suficientemente buenos como para considerar la implantación de la solución desarrollada. metadata Balsa Núñez, María and Martínez de la Fuente, Jorge mail UNSPECIFIED (2022) Desarrollo de un bioplástico comestible y compostable a partir de residuos de la industria alimentaria. Environmental Sciences and Practices, 1 (1).

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Inglés To address the current pandemic, multiple studies have focused on the development of new mHealth apps to help in curbing the number of infections, these applications aim to accelerate the identification and self-isolation of people exposed to SARS-CoV-2, the coronavirus known to cause COVID-19, by being in close contact with infected individuals. The main objectives of this paper are: (1) Analyze the current status of COVID-19 apps available on the main virtual stores: Google Play Store and App Store for Spain, and (2) Propose a novel mobile application that allows interaction and doctor-patient follow-up without the need for real-time consultations (face-to-face or telephone). In this research, a search for eHealth and telemedicine apps related to Covid-19 was performed in the main online stores: Google Play Store and App Store, until May 2021. Keywords were entered into the search engines of the online stores and relevant apps were selected for study using a PRISMA methodology. For the design and implementation of the proposed app named COVINFO, the main weaknesses of the apps studied were taken into account in order to propose a novel and useful app for healthcare systems. The search yielded a total of 50 apps, of which 24 were relevant to this study, of which 23 are free and 54% are available for Android and iOS operating systems (OS). The proposed app has been developed for mobile devices with Android OS being compatible with Android 4.4 and higher. This app enables doctor-patient interaction and constant monitoring of the patient's progress without the need for calls, chats or face-to-face consultation in real time. This work addresses design and development of an application for the transmission of the user's symptoms to his regular doctor, based on the fact that only 16.6% of existing applications have this functionality. The COVINFO app offers a novel service: asynchronous doctor-patient communication, as well as constant monitoring of the patient’s condition and evolution. This app makes it possible to better manage the time of healthcare personnel and avoid overcrowding in hospitals, with the aim of preventing the collapse of healthcare systems and the spread of the coronavirus. metadata Herrera Montano, Isabel and Pérez Pacho, Javier and Gracia Villar, Santos and Aparicio Obregón, Silvia and Breñosa, Jose and de la Torre Díez, Isabel mail UNSPECIFIED, UNSPECIFIED, santos.gracia@uneatlantico.es, silvia.aparicio@uneatlantico.es, josemanuel.brenosa@uneatlantico.es, UNSPECIFIED (2022) Descriptive Analysis of Mobile Apps for Management of COVID-19 in Spain and Development of an Innovate App in that field. Scientific Reports, 12 (1). ISSN 2045-2322

Article Subjects > Biomedicine
Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Fundación Universitaria Internacional de Colombia > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Español Patient care and convenience remain the concern of medical professionals and caregivers alike. An unconscious patient confined to a bed may develop fluid accumulation and pressure sores due to inactivity and deficiency of oxygen flow. Moreover, weight monitoring is crucial for an effective treatment plan, which is difficult to measure for bedridden patients. This paper presents the design and development of a smart and cost-effective independent system for lateral rotation, movement, weight measurement, and transporting immobile patients. Optimal dimensions and practical design specifications are determined by a survey across various hospitals. Subsequently, the proposed hoist-based weighing and turning mechanism is CAD-modeled and simulated. Later, the structural analysis is carried out to select suitable metallurgy for various sub-assemblies to ensure design reliability. After fabrication, optimization, integration, and testing procedures, the base frame is designed to mount a hydraulic motor for the actuator, a DC power source for self-sustenance, and lockable wheels for portability. The installation of a weighing scale and a hydraulic actuator is ensured to lift the patient for weight measuring up to 600 pounds or lateral turning of 80 degrees both ways. The developed system offers simple operating characteristics, allows for keeping patient weight records, and assists nurses in changing patients’ lateral positions both ways, comfortably massage patients’ backs, and transport them from one bed to another. Additionally, being lightweight offers reduced contact with the patient to increase the healthcare staff’s safety in pandemics; it is also height adjustable and portable, allowing for use with multiple-sized beds and easy transportation across the medical facility. The feedback from paramedics is encouraging regarding reducing labor-intensive nursing tasks, alleviating the discomfort of long-term bed-ridden patients, and allowing medical practitioners to suggest better treatment plans metadata Shafi, Imran and Farooq, Muhammad Siddique and De La Torre Díez, Isabel and Breñosa, Jose and Martínez Espinosa, Julio César and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, josemanuel.brenosa@uneatlantico.es, ulio.martinez@unini.edu.mx, UNSPECIFIED (2022) Design and Development of Smart Weight Measurement, Lateral Turning and Transfer Bedding for Unconscious Patients in Pandemics. Healthcare, 10 (11). p. 2174. ISSN 2227-9032

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production Cerrado Inglés The Internet of Things (IoT) is a revolutionary technique of sharing data for smart devices that generates huge amounts of data from smart healthcare systems. Therefore, healthcare systems utilize the convergence power and traffic analysis of sensors that cannot be satisfactorily handled by the IoT. In this article, a novel mutation operator is devised and incorporated with the differential evolution (DE) algorithm. Two tests have been conducted in the validation process. Firstly, the newly dual adaption-based operators incorporated with the differential evolution algorithm are being proposed. The proposed approach provides sufficient diversity and enhances the search speed of nature’s local and global search environments in the problem. The proposed method incorporates the application of IoT-based smart healthcare. Second, an application-based test has been conducted, in which the proposed approach is applied to the application in the smart healthcare system. Therefore, IoT sensor deployment is an optimization problem to minimize service time, delay, and energy loss by considering the communication constraint between sensors(objects). The proposed algorithm is applied in this article to solve this optimization problem. Further, in the experimentation and comparative study, the proposed method is superior to the standard evolutionary algorithms in IoT applications concerning the minimum number of function evaluations and minimization of traffic services. The proposed approach also achieves efficiency in the minimum loss of energy in each service and reduces load and delay metadata Singh, Shailendra Pratap and Viriyasitavat, Wattana and Juneja, Sapna and Alshahrani, Hani and Shaikh, Asadullah and Dhiman, Gaurav and Singh, Aman and Kaur, Amandeep mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, aman.singh@uneatlantico.es, UNSPECIFIED (2022) Dual adaption based evolutionary algorithm for optimized the smart healthcare communication service of the Internet of Things in smart city. Physical Communication, 55. p. 101893. ISSN 18744907

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production Abierto Inglés Online learning systems have expanded significantly over the last couple of years. Massive Open Online Courses (MOOCs) have become a major trend on the internet. During the COVID-19 pandemic, the count of learner enrolment has increased in various MOOC platforms like Coursera, Udemy, Swayam, Udacity, FutureLearn, NPTEL, Khan Academy, EdX, SWAYAM, etc. These platforms offer multiple courses, and it is difficult for online learners to choose a suitable course as per their requirements. In order to improve this e-learning education environment and to reduce the drop-out ratio, online learners will need a system in which all the platform’s offered courses are compared and recommended, according to the needs of the learner. So, there is a need to create a learner’s profile to analyze so many platforms in order to fulfill the educational needs of the learners. To develop a profile of a learner or user, three input parameters are considered: personal details, educational details, and knowledge level. Along with these parameters, learners can also create their user profiles by uploading their CVs or LinkedIn. In this paper, the major innovation is to implement a user interface-based intelligent profiling system for enhancing user adaptation in which feedback will be received from a user and courses will be recommended according to user/learners’ preferences. metadata Kaur, Ramneet and Gupta, Deepali and Madhukar, Mani and Singh, Aman and Abdelhaq, Maha and Alsaqour, Raed and Breñosa, Jose and Goyal, Nitin mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, aman.singh@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, josemanuel.brenosa@uneatlantico.es, UNSPECIFIED (2022) E-Learning Environment Based Intelligent Profiling System for Enhancing User Adaptation. Electronics, 11 (20). p. 3354. ISSN 2079-9292

Article Subjects > Biomedicine
Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Fundación Universitaria Internacional de Colombia > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Inglés The diagnosis of early-stage lung cancer is challenging due to its asymptomatic nature, especially given the repeated radiation exposure and high cost of computed tomography(CT). Examining the lung CT images to detect pulmonary nodules, especially the cell lung cancer lesions, is also tedious and prone to errors even by a specialist. This study proposes a cancer diagnostic model based on a deep learning-enabled support vector machine (SVM). The proposed computer-aided design (CAD) model identifies the physiological and pathological changes in the soft tissues of the cross-section in lung cancer lesions. The model is first trained to recognize lung cancer by measuring and comparing the selected profile values in CT images obtained from patients and control patients at their diagnosis. Then, the model is tested and validated using the CT scans of both patients and control patients that are not shown in the training phase. The study investigates 888 annotated CT scans from the publicly available LIDC/IDRI database. The proposed deep learning-assisted SVM-based model yields 94% accuracy for pulmonary nodule detection representing early-stage lung cancer. It is found superior to other existing methods including complex deep learning, simple machine learning, and the hybrid techniques used on lung CT images for nodule detection. Experimental results demonstrate that the proposed approach can greatly assist radiologists in detecting early lung cancer and facilitating the timely management of patients. metadata Shafi, Imran and Din, Sadia and Khan, Asim and Díez, Isabel De La Torre and Pali-Casanova, Ramón and Tutusaus, Kilian and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, ramon.pali@unini.edu.mx, kilian.tutusaus@uneatlantico.es, UNSPECIFIED (2022) An Effective Method for Lung Cancer Diagnosis from CT Scan Using Deep Learning-Based Support Vector Network. Cancers, 14 (21). p. 5457. ISSN 2072-6694

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production Abierto Inglés, Español El objetivo general fue determinar la eficacia de la implementación de un Sistema de Información para el Seguimiento de Indicadores de Gestión en el incremento de sentencias o autos finales de los juzgados civiles de la Corte Superior de Justicia de Tacna – 2019. El tipo de investigación según su función es cuantitativo, desde un diseño preexperimental con subcategoría cuasiexperimental y un corte de investigación longitudinal. Se tomaron la totalidad de expedientes judiciales en los juzgados civiles durante el período 2018 y 2019 para poder llevar a cabo la evaluación de la eficacia del Sistema de Información. Para la construcción de la propuesta de solución se utilizó una metodología simplificada del proceso de extracción, transformación y carga de datos y para la elaboración del Sistema de Información se aplicó la metodología del Proceso Unificado Ágil. La conclusión principal fue que la implementación de un Sistema de Información para el Seguimiento de Indicadores de Gestión como una medida de e-Gobierno, sirvió para resolver la necesidad de incremento en la emisión de Sentencias y Autos Finales, teniendo al final de la experimentación una reducción de 3% en el tiempo de calificación de los expedientes, y a pesar de que se incrementó el tiempo en trámite de los expedientes judiciales en un 4%, se demostró que la cantidad de sentencias y autos finales tuvieron un incremento de 165 en los Juzgados Civiles de la Corte Superior de Justicia de Tacna para el período 2019 en comparación con el período 2018. metadata Domingo Soriano, Saúl and Arambarri, Jon and Flor Rodríguez, Alberto Johnatan mail saul_domingo@funiber.org, jon.arambarri@uneatlantico.es, UNSPECIFIED (2022) Egobierno: sistema de información para el seguimiento de indicadores y su incidencia en la producción judicial - caso Perú. Project Design and Management, 4 (1). pp. 20-35. ISSN 2683-1597

Article Subjects > Social Sciences
Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production Abierto Portugués A física relaciona-se com as necessidades humanas básicas, saúde, moradia, alimentação, transporte e muito mais. No entanto, a física tem demonstrado ter uma das maiores taxas de reprovação nas escolas há algum tempo. Muitos alunos veem isso como: muito difícil, abstrato e irrelevante para a vida cotidiana. No entanto, alguns pesquisadores atribuem essa percepção aos métodos tradicionais de ensino utilizados nas escolas, que dão mais ênfase à memorização de fórmulas, fatos, teorias, símbolos e modelos ao invés de proporcionar aos alunos a contextualização do conteúdo ao invés de se preocupar em explorar o contexto em que leis e teorias são apresentados, resultando na dogmatização do conhecimento científico. Portanto, o objetivo deste estudo foi compreender o processo de desenvolvimento desde o início da eletricidade até sua aplicação prática em escala comercial. Para tanto, foram realizadas revisões bibliográficas de literaturas científicas. O processo da geração à distribuição de energia elétrica, enfatizando o contexto histórico e social, promove o debate, a investigação e vincula o conhecimento físico à vida cotidiana, promovendo a compreensão do que se estuda metadata Alves Guimarães, Ueudison and Rodrigues Dantas de Brito, Junea Graciele and Olímpio dos Santos, José mail UNSPECIFIED (2022) Eletricidade estática: o processo da geração à distribuição de energia elétrica, enfatizando o contexto histórico e social. RECIMA21 - Revista Científica Multidisciplinar - ISSN 2675-6218, 3 (9). e391942. ISSN 2675-6218

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Fundación Universitaria Internacional de Colombia > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Inglés Facial emotion recognition (FER) is an important and developing topic of research in the field of pattern recognition. The effective application of facial emotion analysis is gaining popularity in surveillance footage, expression analysis, activity recognition, home automation, computer games, stress treatment, patient observation, depression, psychoanalysis, and robotics. Robot interfaces, emotion-aware smart agent systems, and efficient human–computer interaction all benefit greatly from facial expression recognition. This has garnered attention as a key prospect in recent years. However, due to shortcomings in the presence of occlusions, fluctuations in lighting, and changes in physical appearance, research on emotion recognition has to be improved. This paper proposes a new architecture design of a convolutional neural network (CNN) for the FER system and contains five convolution layers, one fully connected layer with rectified linear unit activation function, and a SoftMax layer. Additionally, the feature map enhancement is applied to accomplish a higher detection rate and higher precision. Lastly, an application is developed that mitigates the effects of the aforementioned problems and can identify the basic expressions of human emotions, such as joy, grief, surprise, fear, contempt, anger, etc. Results indicate that the proposed CNN achieves 92.66% accuracy with mixed datasets, while the accuracy for the cross dataset is 94.94%. metadata Qazi, Awais Salman and Farooq, Muhammad Shoaib and Rustam, Furqan and Gracia Villar, Mónica and Rodríguez Velasco, Carmen Lilí and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, monica.gracia@uneatlantico.es, carmen.rodriguez@uneatlantico.es, UNSPECIFIED (2022) Emotion Detection Using Facial Expression Involving Occlusions and Tilt. Applied Sciences, 12 (22). p. 11797. ISSN 2076-3417

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production Abierto Inglés The demand for digitization has inspired organizations to move towards cloud computing, which has increased the challenge for cloud service providers to provide quality service. One of the challenges is energy consumption, which can shoot up the cost of using computing resources and has raised the carbon footprint in the atmosphere; therefore, it is an issue that it is imperative to address. Virtualization, bin-packing, and live VM migration techniques are the key resolvers that have been found to be efficacious in presenting sound solutions. Thus, in this paper, a new live VM migration algorithm, live migration with efficient ballooning (LMEB), is proposed; LMEB focuses on decreasing the size of the data that need to be shifted from the source to the destination server so that the total energy consumption of migration can be reduced. A simulation was performed with a specific configuration of virtual machines and servers, and the results proved that the proposed algorithm could trim down energy usage by 18%, migration time by 20%, and downtime by 20% in comparison with the existing approach of live migration with ballooning (LMB) metadata Gupta, Neha and Gupta, Kamali and Qahtani, Abdulrahman M. and Gupta, Deepali and Alharithi, Fahd S. and Singh, Aman and Goyal, Nitin mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, aman.singh@uneatlantico.es, UNSPECIFIED (2022) Energy-Aware Live VM Migration Using Ballooning in Cloud Data Center. Electronics, 11 (23). p. 3932. ISSN 2079-9292

Revista Subjects > Engineering Ibero-american International University > Research > Scientific Magazines
Europe University of Atlantic > Research > Scientific Magazines
Fundación Universitaria Internacional de Colombia > Research > Scientific Magazines
Ibero-american International University > Research > Scientific Magazines
Universidad Internacional do Cuanza > Research > Scientific Magazines Abierto Español La revista Environmental Sciences and Practices (ESAP) nace como una publicación semestral con el objetivo de invitar a la reflexión y el debate para entender correctamente cual es la función, aporte y responsabilidad medioambiental no solo del mundo académico sino además en el espacio profesional. Comenzando por entender que el área de ESAP, es un espacio interdisciplinario, bajo un concepto innovador, colaborativo e integral hacia todas las áreas que convergen en una temática de interés común: el medio ambiente. Los artículos incluidos en esta revista se publican en español, portugués e inglés, atendiendo de esta manera a un espacio internacional y multicultural que permita una gestión del conocimiento actual, propia y necesaria del área medioambiental. A partir de esta página, podrá acceder a los índices de todas las ediciones de la revista Environmental Sciences and Practices, los resúmenes del artículo y los textos completos. Asimismo, en la sección "Acerca de" encontrará toda la información sobre nuestra revista, su equipo editorial, sistema de publicación y envíos en línea. metadata Multi-Lingual Scientific Journals, (MLS) mail mls@devnull.funiber.org (2022) Environmental Sciences and Practices. [Revista]

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production Abierto Inglés Genotype, environment, and cultivation system strongly influence strawberry yield and quality. Specifically, the growth of strawberry plants is dependent on the water supply. Nevertheless, the abuse of water in agriculture is necessitating the choice of the lowest water-consumptive plants. The following study showed the performance of ‘Romina’, ‘Sibilla’, and ‘Cristina’ cultivars, grown in open-field conditions, and treated with three doses of water (W): 100% local standard regime, and 20% (W80) and 40% (W60) reductions. The average amount of water administered for W100, W80, and W60 was 1120 m3 ha−1, 891 m3 ha−1, and 666 m3 ha−1, respectively. The water treatment at W60 negatively affected the plant growth and yield, resulting in reduced plant height, leaf number, leaf length and width, and a minor yield. Instead, fruit quality showed higher values of total soluble solids and titratable acidity. Conversely, plants watered with W80 showed results similar to the control (W100) in terms of development and yield. In conclusion, it is possible to assume that a reduction of water is desirable, guaranteeing economic and environmental gains for farmers. metadata Marcellini, Micol and Mazzoni, Luca and Raffaelli, Davide and Pergolotti, Valeria and Balducci, Francesca and Capocasa, Franco and Mezzetti, Bruno mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, bruno.mezzetti@uneatlantico.es (2022) Evaluation of Single-Cropping under Reduced Water Supply in Strawberry Cultivation. Agronomy, 12 (6). p. 1396. ISSN 2073-4395

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Fundación Universitaria Internacional de Colombia > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Inglés The purpose of this article is to help to bridge the gap between sustainability and its application to project management by developing a methodology based on artificial intelligence to diagnose, classify, and forecast the level of sustainability of a sample of 186 projects aimed at local communities in Latin American and Caribbean countries. First, the compliance evaluation with the Sustainable Development Goals (SDGs) within the framework of the 2030 Agenda served to diagnose and determine, through fuzzy sets, a global sustainability index for the sample, resulting in a value of 0.638, in accordance with the overall average for the region. Probabilistic predictions were then made on the sustainability of the projects using a series of supervised learning classifiers (SVM, Random Forest, AdaBoost, KNN, etc.), with the SMOTE resampling technique, which provided a significant improvement toward the results of the different metrics of the base models. In this context, the Support Vector Machine (SVM) + SMOTE was the best classification algorithm, with accuracy of 0.92. Lastly, the extrapolation of this methodology is to be expected toward other realities and local circumstances, contributing to the fulfillment of the SDGs and the development of individual and collective capacities through the management and direction of projects. metadata García Villena, Eduardo and Pascual Barrera, Alina Eugenia and Álvarez, Roberto Marcelo and Dzul López, Luis Alonso and Tutusaus, Kilian and Vidal Mazón, Juan Luis and Miró Vera, Yini Airet and Brie, Santiago and López Flores, Miguel A. mail eduardo.garcia@uneatlantico.es, alina.pascual@unini.edu.mx, roberto.alvarez@uneatlantico.es, luis.dzul@uneatlantico.es, kilian.tutusaus@uneatlantico.es, juanluis.vidal@uneatlantico.es, yini.miro@uneatlantico.es, santiago.brie@uneatlantico.es, miguelangel.lopez@uneatlantico.es (2022) Evaluation of the Sustainable Development Goals in the Diagnosis and Prediction of the Sustainability of Projects Aimed at Local Communities in Latin America and the Caribbean. Applied Sciences, 12 (21). p. 11188. ISSN 2076-3417

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production Cerrado Inglés Recently, the Internet of Medical Things (IoMT) could offload healthcare services to 5 G edge computing for low latency. However, some existing works assumed altruistic patients will sacrifice Quality of Service (QoS) for the global optimum. For priority-aware and deadline-sensitive healthcare, this sufficient and simplified assumption will undermine the engagement enthusiasm, i.e., unfairness. To address this issue, we propose a long-term proportional fairness-driven 5 G edge healthcare, i.e., FairHealth. First, we establish a long-term Nash bargaining game to model the service offloading, considering the stochastic demand and dynamic environment. We then design a Lyapunov-based proportional-fairness resource scheduling algorithm, which decouples the long-term fairness problem into single-slot sub-problems, realizing a trade-off between service stability and fairness. Moreover, we propose a block-coordinate descent method to iteratively solve non-convex fair sub-problems. Simulation results show that our scheme can improve 74.44% of the fairness index (i.e., Nash product), compared with the classic global time-optimal scheme. metadata Lin, Xi and Wu, Jun and Bashir, Ali Kashif and Yang, Wu and Singh, Aman and AlZubi, Ahmad Ali mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, aman.singh@uneatlantico.es, UNSPECIFIED (2022) FairHealth: Long-Term Proportional Fairness-Driven 5G Edge Healthcare in Internet of Medical Things. IEEE Transactions on Industrial Informatics. pp. 1-10. ISSN 1551-3203

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production Abierto Inglés The rapid expansion of Internet of Things (IoT) devices deploys various sensors in different applications like homes, cities and offices. IoT applications depend upon the accuracy of sensor data. So, it is necessary to predict faults in the sensor and isolate their cause. A novel primitive technique named fall curve is presented in this paper which characterizes sensor faults. This technique identifies the faulty sensor and determines the correct working of the sensor. Different sources of sensor faults are explained in detail whereas various faults that occurred in sensor nodes available in IoT devices are also presented in tabular form. Fault prediction in digital and analog sensors along with methods of sensor fault prediction are described. There are several advantages and disadvantages of sensor fault prediction methods and the fall curve technique. So, some solutions are provided to overcome the limitations of the fall curve technique. In this paper, a bibliometric analysis is carried out to visually analyze 63 papers fetched from the Scopus database for the past five years. Its novelty is to predict a fault before its occurrence by looking at the fall curve. The sensing of current flow in devices is important to prevent a major loss. So, the fall curves of ACS712 current sensors configured on different devices are drawn for predicting faulty or non-faulty devices. The analysis result proved that if any of the current sensors gets faulty, then the fall curve will differ and the value will immediately drop to zero. Various evaluation metrics for fault prediction are also described in this paper. At last, this paper also addresses some possible open research issues which are important to deal with false IoT sensor data. metadata Uppal, Mudita and Gupta, Deepali and Anand, Divya and S. Alharithi, Fahd and Almotiri, Jasem and Ortega-Mansilla, Arturo and Singh, Dinesh and Goyal, Nitin mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, arturo.ortega@uneatlantico.es, UNSPECIFIED, UNSPECIFIED (2022) Fault Pattern Diagnosis and Classification in Sensor Nodes Using Fall Curve. Computers, Materials & Continua, 72 (1). pp. 1799-1814. ISSN 1546-2226

Article Subjects > Engineering
Subjects > Psychology Europe University of Atlantic > Research > Scientific Production Abierto Inglés Background and Hypothesis The existing developmental bond between fingerprint generation and growth of the central nervous system points to a potential use of fingerprints as risk markers in schizophrenia. However, the high complexity of fingerprints geometrical patterns may require flexible algorithms capable of characterizing such complexity. Study Design Based on an initial sample of scanned fingerprints from 612 patients with a diagnosis of non-affective psychosis and 844 healthy subjects, we have built deep learning classification algorithms based on convolutional neural networks. Previously, the general architecture of the network was chosen from exploratory fittings carried out with an independent fingerprint dataset from the National Institute of Standards and Technology. The network architecture was then applied for building classification algorithms (patients vs controls) based on single fingers and multi-input models. Unbiased estimates of classification accuracy were obtained by applying a 5-fold cross-validation scheme. Study Results The highest level of accuracy from networks based on single fingers was achieved by the right thumb network (weighted validation accuracy = 68%), while the highest accuracy from the multi-input models was attained by the model that simultaneously used images from the left thumb, index and middle fingers (weighted validation accuracy = 70%). Conclusion Although fitted models were based on data from patients with a well established diagnosis, since fingerprints remain lifelong stable after birth, our results imply that fingerprints may be applied as early predictors of psychosis. Specially, if they are used in high prevalence subpopulations such as those of individuals at high risk for psychosis. metadata Salvador, Raymond and García-León, María Ángeles and Feria-Raposo, Isabel and Botillo-Martín, Carlota and Martín-Lorenzo, Carlos and Corte-Souto, Carmen and Aguilar-Valero, Tania and Gil Sanz, David and Porta-Pelayo, David and Martín-Carrasco, Manuel and del Olmo-Romero, Francisco and Maria Santiago-Bautista, Jose and Herrero-Muñecas, Pilar and Castillo-Oramas, Eglee and Larrubia-Romero, Jesús and Rios-Alvarado, Zoila and Antonio Larraz-Romeo, José and Guardiola-Ripoll, Maria and Almodóvar-Payá, Carmen and Fatjó-Vilas Mestre, Mar and Sarró, Salvador and McKenna, Peter J and González-Pablos, Emilio and Negro-González, Emilio and María Castells Bescos, Eva and Felipe Martínez, Elena and Muñoz Hermoso, Paula and Camaño Serna, Cora and Rebolleda Gil, Carlos and Feliz Muñoz, Carmen and Sevillano De La Fuente, Paula and Sánchez Perez, Manuel and Arrece Iriondo, Izascun and Vicente Jauregui Berecibar, José and Domínguez Panchón, Ana and Felices de la Fuente, Alfredo and Bosque Gabarre, Clara and Pomarol-Clotet, Edith mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, david.gil@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED (2022) Fingerprints as Predictors of Schizophrenia: A Deep Learning Study. Schizophrenia Bulletin. ISSN 0586-7614

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Cerrado Inglés The Information Centric Networking (ICN) is a future internet architecture to support efficient content distribution in a vehicular environment. In-network caching in ICN provides a realistic solution for vehicular communication due to storage of content replicas inside network vehicles. However, the challenge still exists while caching content replicas in resource constraint vehicles ( such as limited power and cache capacity) to minimize the communication latency. To address the above mentioned challenge, this paper proposes EPC - an ICN based Energy efficient Placement of Content chunk that fits well in a vehicular environment. The proposed resource management strategy mainly aims to reduce the content fetching delay by caching content replicas towards the network edge router. The EPC strategy decides on placement of content chunks on each vehicle by jointly considering residual power of current vehicle, local popularity of content, and caching gain. The EPC supports efficient utilization of network available resources by allowing only vehicles with their residual power greater than threshold to perform chunk caching and hence, further offers reduced content duplication in the whole network. The effectiveness of the proposed scheme is evaluated in Icarus- an ICN simulator for analyzing the performance of ICN caching and routing strategies. The EPC outperforms various state of the art caching strategies approximately by 30% when gets evaluated in terms of offered cache hit ratio, content retrieval delay, and the average number of hops utilized for fetching the requested content. metadata Gupta, Divya and Rani, Shalli and Singh, Aman and Rodrigues, Joel J. P. C. mail UNSPECIFIED, UNSPECIFIED, aman.singh@uneatlantico.es, UNSPECIFIED (2022) ICN Based Efficient Content Caching Scheme for Vehicular Networks. IEEE Transactions on Intelligent Transportation Systems. pp. 1-9. ISSN 1524-9050

Article Subjects > Social Sciences
Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Inglés Financial management is a critical aspect of firms, and entails the strategic planning, direction, and control of financial endeavors. Risk assessment, fraud detection, wealth management, online transactions, customized bond scheme, customer retention, virtual assistant and so on, are a few of the critical areas where Industry 4.0 technologies intervention are highly required for managing firms' finance. It has been identified from the previous studies that they are limited studies that have addressed the significance and application of integrating of Industry 4.0 technologies such as Internet of Things (IoT), cloud computing, big data, robotic process automation (RPA), artificial intelligence (AI), Blockchain, Digital twin, and Metaverse. With the motivation from the above aspects, this study aims to discuss the role of these technologies in the area of financial management of a firm. Based up on the analysis, it has been concluded that these technologies assist to credit risk management based on real-time data; financial data analytics of risk assessment, digital finance, digital auditing, fraud detection, and AI- and IoT- based virtual assistants. This study recommended that digital technologies be deeply integrated into the financial sector to improve service quality and accessibility, as well as the creation of innovative rules that allow for healthy competition among market participants. metadata Bisht, Deepa and Singh, Rajesh and Gehlot, Anita and Akram, Shaik Vaseem and Singh, Aman and Caro Montero, Elisabeth and Priyadarshi, Neeraj and Twala, Bhekisipho mail UNSPECIFIED (2022) Imperative Role of Integrating Digitalization in the Firms Finance: A Technological Perspective. Electronics, 11 (19). p. 3252. ISSN 2079-9292

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production Abierto Inglés A wireless body area network (WBAN) is a technology that is widely employed in the medical sector. It is a low-cost network that allows for mobility and variation. It can be used for long-distance, semiautonomous remote monitoring without interfering with people’s regular schedules. Detection devices are embedded in the human body in a simple WBAN configuration to continuously screen physiological boundaries or critical pointers. Confidence among shareholders (for example, medical care suppliers, clients, and medical teachers) is recognized as an essential achievement factor for data stream reliability in such an organization. Given the inherent characteristics of remote locations, it is critical to exercise confidence and security when conducting remote comprehension testing. In the present scenario, WBAN has majorly contributed towards healthcare and its application in medical services. Solid correspondence systems are frequently used to address trust and security concerns on WBANs. In terms of purpose, we present in this study a communication approach built on trust to protect the WBAN’s integrity and confidentiality. For ensuring authenticity, an enhanced bilingual distribution-based trust-management system (PDATMS) approach is used, while a cryptographic system is used to maintain anonymity. A MATLAB simulator is used to evaluate the performance of the recommended program. The recommended approach, according to the release information, improves accuracy by 96%, service delivery rate by 99%, throughput by 99%, as well as confidence, while reducing average latency metadata Singh, Sunny and Chawla, Muskaan and Prasad, Devendra and Anand, Divya and Alharbi, Abdullah and Alosaimi, Wael mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, divya.anand@uneatlantico.es, UNSPECIFIED, UNSPECIFIED (2022) An Improved Binomial Distribution-Based Trust Management Algorithm for Remote Patient Monitoring in WBANs. Sustainability, 14 (4). p. 2141. ISSN 2071-1050

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production Abierto Inglés In Smart Cities’ applications, Multi-node cooperative spectrum sensing (CSS) can boost spectrum sensing efficiency in cognitive wireless networks (CWN), although there is a non-linear interaction among number of nodes and sensing efficiency. Cooperative sensing by nodes with low computational cost is not favorable to improving sensing reliability and diminishes spectrum sensing energy efficiency, which poses obstacles to the regular operation of CWN. To enhance the evaluation and interpretation of nodes and resolves the difficulty of sensor selection in cognitive sensor networks for energy-efficient spectrum sensing. We examined reducing energy usage in smart cities while substantially boosting spectrum detecting accuracy. In optimizing energy effectiveness in spectrum sensing while minimizing complexity, we use the energy detection for spectrum sensing and describe the challenge of sensor selection. This article proposed the algorithm for choosing the sensing nodes while reducing the energy utilization and improving the sensing efficiency. All the information regarding nodes is saved in the fusion center (FC) through which blockchain encrypts the information of nodes ensuring that a node’s trust value conforms to its own without any ambiguity, CWN-FC pick high-performance nodes to engage in CSS. The performance evaluation and computation results shows the comparison between various algorithms with the proposed approach which achieves 10% sensing efficiency in finding the solution for identification and triggering possibilities with the value of α=1.5 and γ=2.5 with the varying number of nodes. metadata Rani, Shalli and Babbar, Himanshi and Shah, Syed Hassan Ahmed and Singh, Aman mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, aman.singh@uneatlantico.es (2022) Improvement of energy conservation using blockchain-enabled cognitive wireless networks for smart cities. Scientific Reports, 12 (1). ISSN 2045-2322

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production Abierto Inglés Several climatic trends are generally associated with altitude, that may influence the nutritional and phytochemical composition of plants. Strawberry is considered a functional food due to biological activities and health benefits. This systematic review and meta-analysis intend to expose possible variations on physicochemical composition and antioxidant capacity of strawberries in regard to altitude. Thirty eligible studies were included for the final meta-analysis. Two altitude ranges were established: 0 – 1000 and 1000—2000 m above sea level. A random-effects model was used to obtain the results. It was discovered that total soluble solids significantly decreased with altitude. Total titratable acidity increased with altitude. Vitamin C and total anthocyanins showed a significant difference between the groups before we discarded some studies. The analysis of altitude for phenolics and antioxidant capacity evaluated for the DPPH radical scavenging method did not identify any significant differences between the studies. The findings suggest that altitude does not affect the physicochemical composition and antioxidant capacity of strawberries; nonetheless, a more exhaustive study is recommended. metadata Guevara-Terán, Mabel and Gonzalez-Paramás, Ana M. and Beltrán-Noboa, Andrea and Giampieri, Francesca and Battino, Maurizio and Tejera, Eduardo and Alvarez-Suarez, José M. mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, francesca.giampieri@uneatlantico.es, maurizio.battino@uneatlantico.es, UNSPECIFIED, UNSPECIFIED (2022) Influence of altitude on the physicochemical composition and antioxidant capacity of strawberry: a preliminary systematic review and meta-analysis. Phytochemistry Reviews. ISSN 1568-7767

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production Cerrado Inglés In today’s modern world, information and communication technologies are playing an active role in increasing the standards and quality of life for the betterment of human beings. Due to these technologies, people are now learning and experiencing new things very effectively and efficiently. With the implementation of information technology (IT)-based smart technologies in music education, learners can learn and create quality music. There is a need for the employment of information technology in music classrooms. Governments and institutions need to provide adequate resources to achieve its implementation. The traditional methods of learning are not capable of providing enough quality education to students. The present study focuses on the crucial role of information technology in the enhancement of music education. The advancements in modern technologies are expanding music education very rapidly and productively. To help learners with the use of an accurate technological method for learning purposes, various features have been identified from the existing literature. Based on these identified features, different IT-based procedures are ranked by the employment of analytic hierarchy process (AHP) and TOPSIS. The outcomes of the study demonstrated the efficacy of the approachesCorr. metadata Fu, Yi and Zhang, Mengjia and Nawaz, Muhammad and Ali, Muhammad and Singh, Aman mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, aman.singh@uneatlantico.es (2022) Information technology-based revolution in music education using AHP and TOPSIS. Soft Computing. ISSN 1432-7643

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production Abierto Inglés The present technological era significantly makes use of Internet-of-Things (IoT) devices for offering and implementing healthcare services. Post COVID-19, the future of the healthcare system is highly reliant upon the inculcation of Artificial-Intelligence (AI) mechanisms in its day-to-day procedures, and this is realized in its implementation using sensor-enabled smart and intelligent IoT devices for providing extensive care to patients relative to the symmetric concept. The offerings of such AI-enabled services include handling the huge amount of data processed and sensed by smart medical sensors without compromising the performance parameters, such as the response time, latency, availability, cost and processing time. This has resulted in a need to balance the load of the smart operational devices to avoid any failure of responsiveness. Thus, in this paper, a fog-based framework is proposed that can balance the load among fog nodes for handling the challenging communication and processing requirements of intelligent real-time applications. metadata Malik, Swati and Gupta, Kamali and Gupta, Deepali and Singh, Aman and Ibrahim, Muhammad and Ortega-Mansilla, Arturo and Goyal, Nitin and Hamam, Habib mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, aman.singh@uneatlantico.es, UNSPECIFIED, arturo.ortega@uneatlantico.es, UNSPECIFIED, UNSPECIFIED (2022) Intelligent Load-Balancing Framework for Fog-Enabled Communication in Healthcare. Electronics, 11 (4). p. 566. ISSN 2079-9292

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Fundación Universitaria Internacional de Colombia > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Inglés This paper presents the design, development, and testing of an IoT-enabled smart stick for visually impaired people to navigate the outside environment with the ability to detect and warn about obstacles. The proposed design employs ultrasonic sensors for obstacle detection, a water sensor for sensing the puddles and wet surfaces in the user’s path, and a high-definition video camera integrated with object recognition. Furthermore, the user is signaled about various hindrances and objects using voice feedback through earphones after accurately detecting and identifying objects. The proposed smart stick has two modes; one uses ultrasonic sensors for detection and feedback through vibration motors to inform about the direction of the obstacle, and the second mode is the detection and recognition of obstacles and providing voice feedback. The proposed system allows for switching between the two modes depending on the environment and personal preference. Moreover, the latitude/longitude values of the user are captured and uploaded to the IoT platform for effective tracking via global positioning system (GPS)/global system for mobile communication (GSM) modules, which enable the live location of the user/stick to be monitored on the IoT dashboard. A panic button is also provided for emergency assistance by generating a request signal in the form of an SMS containing a Google maps link generated with latitude and longitude coordinates and sent through an IoT-enabled environment. The smart stick has been designed to be lightweight, waterproof, size adjustable, and has long battery life. The overall design ensures energy efficiency, portability, stability, ease of access, and robust features. metadata Farooq, Muhammad Siddique and Shafi, Imran and Khan, Harris and Díez, Isabel De La Torre and Breñosa, Jose and Martínez Espinosa, Julio César and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, josemanuel.brenosa@uneatlantico.es, ulio.martinez@unini.edu.mx, UNSPECIFIED (2022) IoT Enabled Intelligent Stick for Visually Impaired People for Obstacle Recognition. Sensors, 22 (22). p. 8914. ISSN 1424-8220

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production Abierto Inglés In today’s technological and stressful world, when everyone is busy in their daily routines and places blind faith in pharmaceutical advancements to protect their health, the sudden, horrifying effects of the COVID-19 pandemic have resulted in serious emotional and psychological impacts in the general population. In spite of advanced vaccination campaigns, fear and hesitation have become a part of human life since there are a number of people who do not want to take these immunity boosting vaccinations. Such people may become carriers of infectious viruses, leading to a more rapid rate of spread; therefore, this class of spreaders needs to be screened at the earliest opportunity. In this context, there is a need for advanced health monitoring systems which can assist the pharmaceutical industry to monitor and record the health status of people. To address this need and reduce the uncertainty of the situation, this study has designed and tested an Internet of Things (IoT) and Fog computing-based multi-node architecture was for real-time initial screening and recording of such subjects. The proposed system was able to record current body temperature and location coordinates along with the facial images. Further, the proposed system was able to transmit data to a cloud database using internet-connected services. An implementation and reviews-based working environment analysis was conducted to determine the efficacy of the proposed system. It was observed from the statistical analysis that the proposed IoT Fog-enabled ecosystem could be utilized efficiently. metadata Khullar, Vikas and Singh, Harjit Pal and Miró Vera, Yini Airet and Anand, Divya and Mohamed, Heba G. and Gupta, Deepali and Kumar, Navdeep and Goyal, Nitin mail UNSPECIFIED, UNSPECIFIED, yini.miro@uneatlantico.es, divya.anand@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED (2022) IoT Fog-Enabled Multi-Node Centralized Ecosystem for Real Time Screening and Monitoring of Health Information. Applied Sciences, 12 (19). p. 9845. ISSN 2076-3417

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production Abierto Inglés Remarkable progress in the Internet of Things (IoT) and the requirements in the Industrial era have raised new constraints of industrial data where huge data are gathered by heterogeneous devices. Recently, Industry 4.0 has attracted attention in various fields of industries such as medicines, automobiles, logistics, etc. However, every field is suffering from some threats and vulnerabilities. In this paper, a new model is proposed for detecting different types of attacks and it is analyzed with a deep learning technique, i.e., classifier-Convolution Neural Network and Long Short-Term Memory. The UNSW NB 15 dataset is used for the classification of various attacks in the field of Industry 4.0 for providing security and protection to the different types of sensors used for heterogeneous data. The proposed model achieves the results using Cortex processors, a 1.2 GHz processor, and four gigabytes of RAM. The attack detection model is written in Python 3.8.8 and Keras. Keras constructs the model using layers of Convolutional, Max Pooling, and Dense Layers. The model is trained using 250 batch size, 60 epochs, 10 classes. For this model, the activation functions are Relu and softmax pooling. metadata Anand, Ankita and Rani, Shalli and Singh, Aman and Elkamchouchi, Dalia H. and Delgado Noya, Irene mail UNSPECIFIED, UNSPECIFIED, aman.singh@uneatlantico.es, UNSPECIFIED, irene.delgado@uneatlantico.es (2022) Lightweight Hybrid Deep Learning Architecture and Model for Security in IIOT. Applied Sciences, 12 (13). p. 6442. ISSN 2076-3417

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production Abierto Inglés When we talk about the Internet of Things, we are referring to the connecting of things to a1 physical network that is embedded with software, sensors, and other devices that allow information2 to be exchanged between devices. It is possible that the interconnection of devices will present3 issues in terms of security, trustworthiness, reliability, and confidentiality, among other things.4 The proposed approach is effective at detecting intrusions into the Internet of Things network.5 Initially, the privacy-preserving technology was deployed utilising a Blockchain-based methodology6 to ensure that personal information was protected. Patients’ health records (PHR) security is the7 most crucial component of encryption over the Internet because of the value and importance of these8 records, particularly in the context of the Internet of Medical Things (IoMT). The search terms access9 mechanism is one of the most common approaches used to access personal health records from a10 database, but it is vulnerable to a number of security flaws. However, while blockchain-enabled11 healthcare systems provide increased security, they may also introduce weaknesses into the current12 state of the art. Blockchain-enabled frameworks have been proposed in the literature as a means13 of resolving those challenges. These solutions, on the other hand, are primarily concerned with14 data storage, with Blockchain serving as a database. To enable secure search and keyword-based15 access to a distributed database, this study proposes the use of blockchain technology as a distributed16 database, together with a homomorphic encryption mechanism. Aside from that, the suggested17 system includes a secure key revocation mechanism that can be used to automatically update various18 policies.As a result, our proposed approach provides greater security, efficiency, and transparency19 while also being more cost-effective. We have compared the findings of our proposed models with20 those of the benchmark models, if appropriate. Our comparison research demonstrates that our21 suggested framework provides a more secure and searchable mechanism for the healthcare system22 than the current state of the art. metadata Ali, Aitizaz and Delgado Noya, Irene and Ur Rehman, Ateeq and Ahmed, Mehmood and Singh, Aman and Anand, Divya mail UNSPECIFIED, irene.delgado@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, aman.singh@uneatlantico.es, divya.anand@uneatlantico.es (2022) A Lightweight Trust-less Authentication Framework for Massive IoT Systems [preprint]. Preprints. (Unpublished)

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production Abierto Inglés Electroporation is a next generation bioelectronics device. The emerging application of electroporation requires high voltage pulses having a pulse-width in the nanosecond range. The essential use of a capacitor results in an increase in the size of the electroporator circuit. This paper discusses the modification of a conventional Marx generator circuit to achieve the high voltage electroporation pulses with a minimal chip size of the circuit. The reduced capacitors are attributed to a reduction in the number of stages used to achieve the required voltage boost. The paper proposes the improved isolation between two capacitors with the usage of optocouplers. Parametric analysis is presented to define the tuneable range of the electroporator circuit. The output voltage of 49.4 V is achieved using the proposed 5-stage MOSFET circuit with an input voltage of 12 V. metadata Ganesan, Selvakumar and Ghosh, Debarshi and Taneja, Ashu and Saluja, Nitin and Rani, Shalli and Singh, Aman and Elkamchouchi, Dalia H. and Delgado Noya, Irene mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, aman.singh@uneatlantico.es, UNSPECIFIED, irene.delgado@uneatlantico.es (2022) A Modified Marx Generator Circuit with Enhanced Tradeoff between Voltage and Pulse Width for Electroporation Applications. Electronics, 11 (13). p. 2013. ISSN 2079-9292

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Inglés The world population is on the rise, which demands higher food production. The reduction in the amount of land under cultivation due to urbanization makes this more challenging. The solution to this problem lies in the artificial cultivation of crops. IoT and sensors play an important role in optimizing the artificial cultivation of crops. The selection of sensors is important in order to ensure a better quality and yield in an automated artificial environment. There are many challenges involved in selecting sensors due to the highly competitive market. This paper provides a novel approach to sensor selection for saffron cultivation in an IoT-based environment. The crop used in this study is saffron due to the reason that much less research has been conducted on its hydroponic cultivation using sensors and its huge economic impact. A detailed hardware-based framework, the growth cycle of the crop, along with all the sensors, and the block layout used for saffron cultivation in a hydroponic medium are provided. The important parameters for a hydroponic medium, such as the concentration of nutrients and flow rate required, are discussed in detail. This paper is the first of its kind to explain the sensor configurations, performance metrics, and sensor-based saffron cultivation model. The paper discusses different metrics related to the selection, use and role of sensors in different IoT-based saffron cultivation practices. A smart hydroponic setup for saffron cultivation is proposed. The results of the model are evaluated using the AquaCrop simulator. The simulator is used to evaluate the value of performance metrics such as the yield, harvest index, water productivity, and biomass. The values obtained provide better results as compared to natural cultivation. metadata Kour, Kanwalpreet and Gupta, Deepali and Gupta, Kamali and Anand, Divya and Elkamchouchi, Dalia H. and Mazas Pérez-Oleaga, Cristina and Ibrahim, Muhammad and Goyal, Nitin mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, divya.anand@uneatlantico.es, UNSPECIFIED, cristina.mazas@uneatlantico.es, UNSPECIFIED, UNSPECIFIED (2022) Monitoring Ambient Parameters in the IoT Precision Agriculture Scenario: An Approach to Sensor Selection and Hydroponic Saffron Cultivation. Sensors, 22 (22). p. 8905. ISSN 1424-8220

Other Subjects > Engineering Europe University of Atlantic > Research > Projects I+D+I Cerrado Español El objetivo de la investigación del proyecto Mosaic AgroData 4.0 consiste en obtener una solución, en su versión prototipo, que proporcione una visión y gestión 360º de las operaciones en cualquier explotación agraria, tanto de las tareas realizadas por trabajadores como de los datos recogidos de sensores y sistemas externos, facilitando la consolidación de información, trazabilidad, monitorización en tiempo real, predicción y análisis de datos para permitir aumentar drásticamente la eficiencia y reducir costes, mejorando además la calidad de los cultivos y la competencia de las empresas. El proyecto implica una innovación relevante de la cadena de valor en un entorno agro (explotación agraria, industria, etc.), centrada en la recopilación y posterior tratamiento (mediante IA y DSS) de información proveniente de sensores, activos T.I, y otros recursos (como recursos operativos en campo) que permita modernizar y transformar los servicios y operaciones agrícolas, transitando de un modelo de gestión de operaciones sobre aplicaciones de TI desconectadas a un modelo de gestión de operaciones sobre soluciones de TI convergentes para toda la organización. La potencialidad innovadora de esta solución Mosaic Agrodata reside en la implementación de las principales tecnologías que engloba la industria 4.0 como interoperabilidad con sensores IoT, desarrollos de Inteligencia Artificial, Cloud Computing, Data analytics, y Sistemas de Apoyo a la Decisión metadata Asociación Clúster Granada Plaza Tecnológica y Biotecnológica, and CITICAN-Universidad Europea del Atlántico, mail UNSPECIFIED (2022) Mosaic Agrodata 4.0: Diseño y prototipado de una solución cloud para la gestión de los datos, movilidad de los procesos y operaciones en entornos agro. Repositorio de la Universidad. (Unpublished)

Article Subjects > Biomedicine
Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Fundación Universitaria Internacional de Colombia > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Inglés Mobility and low energy consumption are considered the main requirements for wireless body area sensor networks (WBASN) used in healthcare monitoring systems (HMS). In HMS, battery-powered sensor nodes with limited energy are used to obtain vital statistics about the body. Hence, energy-efficient schemes are desired to maintain long-term and steady connectivity of the sensor nodes. A sheer amount of energy is consumed in activities such as idle listening, excessive transmission and reception of control messages, packet collisions and retransmission of packets, and poor path selection, that may lead to more energy consumption. A combination of adaptive scheduling with an energy-efficient protocol can help select an appropriate path at a suitable time to minimize the control overhead, energy consumption, packet collision, and excessive idle listening. This paper proposes a region-based energy-efficient multipath routing (REMR) approach that divides the entire sensor network into clusters with preferably multiple candidates to represent each cluster. The cluster representatives (CRs) route packets through various clusters. For routing, the energy requirement of each route is considered, and the path with minimum energy requirements is selected. Similarly, end-to-end delay, higher throughput, and packet-delivery ratio are considered for packet routing. metadata Akbar, Shuja and Mehdi, Muhammad Mohsin and Jamal, M. Hasan and Raza, Imran and Hussain, Syed Asad and Breñosa, Jose and Martínez Espinosa, Julio César and Pascual Barrera, Alina Eugenia and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, josemanuel.brenosa@uneatlantico.es, ulio.martinez@unini.edu.mx, alina.pascual@unini.edu.mx, UNSPECIFIED (2022) Multipath Routing in Wireless Body Area Sensor Network for Healthcare Monitoring. Healthcare, 10 (11). p. 2297. ISSN 2227-9032

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production Abierto Inglés This is an effort to analyze the reaction of stock prices of Indian public and private banks listed in NSE and BSE to the announcement of seven best case news events. Several recent studies have analyzed the correlation between stock prices and news announcements; however, there is no evidence on how private and public sector Indian bank stocks react to important news events independently. We examine these features by concentrating on a sample of banking and government news events. We classify these news events to create a group of negative and a group of positive tone of announcements (sentiments). The statistical results show that the negative banking news announcements had a one-month impact on private banks, with statistically significant negative mean CARs. However, with highly statistically substantial negative mean CARs, the influence of the negative banking news announcements on public banks was observed for two months after the news was published. Furthermore, the influence of the positive banking news on private banks persisted a month after the news was published. Positive banking news events had an influence on public banks for five days after they were published. The study concludes that public bank stocks react more to negative news announcements than positive news announcements in the same manner as the sentimental polarity of the news announcements as compared to private bank stocks. First, we retrieved the news articles published in prominent online financial news portals between 2017 and 2020, and the seven major news events were extracted and classified using multi-class text classification. The Random Forest classifier produced a significant accuracy of 94% with pre-trained embeddings of DistilBERT, a neural network model, which outperformed the traditional feature representation technique, TF-IDF. The training data for the classifier were balanced using the SMOTE sampling technique metadata Dogra, Varun and Alharithi, Fahd S. and Álvarez, Roberto Marcelo and Singh, Aman and Qahtani, Abdulrahman M. mail UNSPECIFIED, UNSPECIFIED, roberto.alvarez@uneatlantico.es, aman.singh@uneatlantico.es, UNSPECIFIED (2022) NLP-Based Application for Analyzing Private and Public Banks Stocks Reaction to News Events in the Indian Stock Exchange. Systems, 10 (6). p. 233. ISSN 2079-8954

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production Abierto Inglés The standard optimization of open-pit mine design and production scheduling, which is impacted by a variety of factors, is an essential part of mining activities. The metal uncertainty, which is connected to supply uncertainty, is a crucial component in optimization. To address uncertainties regarding the economic value of mining blocks and the general problem of mine design optimization, a minimum-cut network flow algorithm is employed to give the optimal ultimate pit limits and pushback designs under uncertainty. A structure that is computationally effective and can manage the joint presentation and treatment of the economic values of mining blocks under various circumstances is created by the push re-label minimum-cut technique. In this study, the algorithm is put to the test using a copper deposit and shows similarities to other stochastic optimizers for mine planning that have already been created. Higher possibilities of reaching predicted production targets are created by the algorithm’s earlier selection of more certain blocks with blocks of high value. Results show that, in comparison to a conventional approach using the same algorithm, the cumulative metal output is larger when the uncertainty in the metal content is taken into consideration. There is also an additional 10% gain in net present value. metadata Joshi, Devendra and Ali Albahar, Marwan and Chithaluru, Premkumar and Singh, Aman and Yadav, Arvind and Miró Vera, Yini Airet mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, aman.singh@uneatlantico.es, UNSPECIFIED, yini.miro@uneatlantico.es (2022) A Novel Approach to Integrating Uncertainty into a Push Re-Label Network Flow Algorithm for Pit Optimization. Mathematics, 10 (24). p. 4803. ISSN 2227-7390

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production Abierto Inglés Fog-assisted and IoT-enabled smart healthcare system with rapid response rates is the major area of concern now a days. Dynamic and heterogeneous fog networks are difficult to manage and a considerable amount of overhead could be realized while managing ever increasing load on foglets. Fog computing plays a vital role in managing ever increasing processing demands from diverse IoT-based applications. Smart healthcare systems work with the assistance of sensor-based devices and automatic data collection and processing can speed up overall system functionality. In the proposed work, a novel framework for smart health care is presented where a series of activities are performed with prime objective of reducing latency and execution time. Principal component analysis is used for feature reduction and support vector machines with radial basis function kernel is used for classification purpose. Workload optimization on the fog nodes is implemented using genetic algorithm. Data collection process also involves preprocessing as a leading step for generating cleaner data. Amalgamation of intelligent and optimization techniques in the presented framework certainly improves the efficiency of the overall system. Experimental results reveal that proposed work outperforms the existing fog-assisted smart healthcare systems in terms of latency, execution time, overall system accuracy, and system stability. metadata Abdellatif, Ahmed A. H. and Singh, Aman and Aldribi, Abdulaziz and Ortega-Mansilla, Arturo and Ibrahim, Muhammad and Rehman, Ateeq Ur mail UNSPECIFIED, aman.singh@uneatlantico.es, UNSPECIFIED, arturo.ortega@uneatlantico.es, UNSPECIFIED, UNSPECIFIED (2022) A Novel Framework for Fog-Assisted Smart Healthcare System with Workload Optimization. Computational Intelligence and Neuroscience, 2022. pp. 1-12. ISSN 1687-5265

Article Subjects > Biomedicine
Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Inglés The prevalence of anxiety among university students is increasing, resulting in the negative impact on their academic and social (behavioral and emotional) development. In order for students to have competitive academic performance, the cognitive function should be strengthened by detecting and handling anxiety. Over a period of 6 weeks, this study examined how to detect anxiety and how Mano Shakti Yoga (MSY) helps reduce anxiety. Relying on cardiac signals, this study follows an integrated detection-estimation-reduction framework for anxiety using the Intelligent Internet of Medical Things (IIoMT) and MSY. IIoMT is the integration of Internet of Medical Things (wearable smart belt) and machine learning algorithms (Decision Tree (DT), Random Forest (RF), and AdaBoost (AB)). Sixty-six eligible students were selected as experiencing anxiety detected based on the results of self-rating anxiety scale (SAS) questionnaire and a smart belt. Then, the students were divided randomly into two groups: experimental and control. The experimental group followed an MSY intervention for one hour twice a week, while the control group followed their own daily routine. Machine learning algorithms are used to analyze the data obtained from the smart belt. MSY is an alternative improvement for the immune system that helps reduce anxiety. All the results illustrate that the experimental group reduced anxiety with a significant (p < 0.05) difference in group × time interaction compared to the control group. The intelligent techniques achieved maximum accuracy of 80% on using RF algorithm. Thus, students can practice MSY and concentrate on their objectives by improving their intelligence, attention, and memory. metadata Pal, Rishi and Adhikari, Deepak and Heyat, Md Belal Bin and Guragai, Bishal and Lipari, Vivian and Brito Ballester, Julién and De la Torre Díez, Isabel and Abbas, Zia and Lai, Dakun mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, vivian.lipari@uneatlantico.es, julien.brito@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED (2022) A Novel Smart Belt for Anxiety Detection, Classification, and Reduction Using IIoMT on Students’ Cardiac Signal and MSY. Bioengineering, 9 (12). p. 793. ISSN 2306-5354

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Inglés Infectious Disease Prediction aims to anticipate the aspects of both seasonal epidemics and future pandemics. However, a single model will most likely not capture all the dataset’s patterns and qualities. Ensemble learning combines multiple models to obtain a single prediction that uses the qualities of each model. This study aims to develop a stacked ensemble model to accurately predict the future occurrences of infectious diseases viewed at some point in time as epidemics, namely, dengue, influenza, and tuberculosis. The main objective is to enhance the prediction performance of the proposed model by reducing prediction errors. Autoregressive integrated moving average, exponential smoothing, and neural network autoregression are applied to the disease dataset individually. The gradient boosting model combines the regress values of the above three statistical models to obtain an ensemble model. The results conclude that the forecasting precision of the proposed stacked ensemble model is better than that of the standard gradient boosting model. The ensemble model reduces the prediction errors, root-mean-square error, for the dengue, influenza, and tuberculosis dataset by approximately 30%, 24%, and 25%, respectively metadata Mahajan, Asmita and Sharma, Nonita and Aparicio Obregón, Silvia and Alyami, Hashem and Alharbi, Abdullah and Anand, Divya and Sharma, Manish and Goyal, Nitin mail UNSPECIFIED, UNSPECIFIED, silvia.aparicio@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, divya.anand@uneatlantico.es, UNSPECIFIED, UNSPECIFIED (2022) A Novel Stacking-Based Deterministic Ensemble Model for Infectious Disease Prediction. Mathematics, 10 (10). p. 1714. ISSN 2227-7390

Other Subjects > Engineering Europe University of Atlantic > Research > Projects I+D+I
Fundación Universitaria Internacional de Colombia > Research > Projects I+D+I
Ibero-american International University > Research > Projects I+D+I
Ibero-american International University > Research > Projects I+D+I
Universidad Internacional do Cuanza > Research > Projects I+D+I Cerrado Español La línea de actividad científico-técnica que se propone se titula “Observatorio 5G“ y está orientada a generar conocimiento en el ámbito de las nuevas redes de telecomunicaciones y servicios asociados al estándar tecnológico de quinta generación para redes móviles de banda ancha (5G). El despliegue de la quinta generación de tecnologías de telefonía móvil, conocida como 5G, está protagonizado por la necesidad de conseguir que las diferentes compañías fabricantes consigan implantar sus estándares a nivel internacional. A diferencia de las tecnologías de 3G y 4G donde era necesario un despliegue masivo para dar servicio a cuanto mayor número posible de población, la tecnología 5G se basa en el concepto de despliegues particulares, con soluciones críticas mediante soluciones ad-hoc. Por ello, es importante tanto la creación de un potente ecosistema 5G así como que el mismo contemple a los emprendedores y pequeñas empresas que será quienes creen los servicios que solucionen los problemas concretos de las industrias sobre esta nueva tecnología. La tecnología 5G será una realidad en breve. Por ello, se requiere realizar acciones que permitan que los países lideren su implantación de una manera sólida, ordenada y consensuada permitiendo una ventaja competitiva tanto a nivel gubernamental como industrial para desarrollar un ecosistema adecuado del despliegue de 5G. Para poder dar soluciones en tres ámbitos de actuación (Coordinación de Proyectos; Regulación y Legislación; e Innovación, Emprendimiento y Estandarización) se propone analizar la creación de un Observatorio 5G. El objetivo general del presente proyecto es elaborar un estudio que permita analizar la factibilidad de la creación de un Observatorio 5G. Para ello, será necesario identificar las grandes líneas maestras que deben ser comunes a un observatorio según las singularidades de cada territorio. En particular, nuestro interés será identificar oportunidades alrededor de lo que denominábamos “innovación y ecosistema 5G”, es decir, oportunidades que se puedan abrir especialmente: - Para la creación de un ecosistema científico-técnico que comparta la capacidad de Innovación mediante la tecnología 5G (Universidades, Centros Tecnológicos, Centros de I+D de las empresas, etc.). - Para la generación de conocimiento con el mundo científico y académico que permita adaptar la formación del talento para tener en cuenta las necesidades futuras en base a la tecnología. - Crear sinergias desde el ecosistema de innovación con el ecosistema de emprendimiento que favorezca la creación de nuevas empresas y productos para liderar el mercado. - Generar capacitaciones y formación continua. metadata , (MLS) mail mls@devnull.funiber.org (2022) Observatorio 5G. Repositorio de la Universidad. (Unpublished)

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production Abierto Inglés This study involves a working limestone mine that supplies limestone to the cement factory. The two main goals of this paper are to (a) determine how long an operating mine can continue to provide the cement plant with the quality and quantity of materials it needs, and (b) explore the viability of combining some limestone from a nearby mine with the study mine limestone to meet the cement plant’s quality and quantity goals. These objectives are accomplished by figuring out the maximum net profit for the ultimate pit limit and production sequencing of the mining blocks. The issues were resolved using a branch-and-cut based sequential integer and mixed integer programming problem. The study mine can exclusively feed the cement plant for up to 15 years, according to the data. However, it was also noted that the addition of the limestone from the neighboring mine substantially increased the mine’s life (85 years). The findings also showed that, when compared with the production planning formulation that the company is now using, the proposed approach creates 10% more profit. The suggested method also aids in determining the desired desirable quality of the limestone that will be transported from the nearby mine throughout each production stage. metadata Joshi, Devendra and Chithaluru, Premkumar and Singh, Aman and Yadav, Arvind and Elkamchouchi, Dalia H. and Breñosa, Jose and Anand, Divya mail UNSPECIFIED, UNSPECIFIED, aman.singh@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, josemanuel.brenosa@uneatlantico.es, divya.anand@uneatlantico.es (2022) An Optimized Open Pit Mine Application for Limestone Quarry Production Scheduling to Maximize Net Present Value. Mathematics, 10 (21). p. 4140. ISSN 2227-7390

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Fundación Universitaria Internacional de Colombia > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Inglés β-Thalassemia is one of the dangerous causes of the high mortality rate in the Mediterranean countries. Substantial resources are required to save a β-Thalassemia carriers’ life and early detection of thalassemia patients can help appropriate treatment to increase the carrier’s life expectancy. Being a genetic disease, it can not be prevented however the analysis of several indicators in parents’ blood can be used to detect disorders causing Thalassemia. Laboratory tests for Thalassemia are time-consuming and expensive like high-performance liquid chromatography, Complete Blood Count (CBC) with peripheral smear, genetic test, etc. Red blood indices from CBC can be used with machine learning models for the same task. Despite the available approaches for Thalassemia carriers from CBC data, gaps exist between the desired and achieved accuracy. Moreover, the data imbalance problem is studied well which makes the models less generalizable. This study proposes a highly accurate approach for β-Thalassemia detection using red blood indices from CBC augmented by supervised machine learning. In view of the fact that all the features do not carry predictive information regarding the target variable, this study employs a unified framework of two features selection techniques including Principal Component Analysis (PCA) and Singular Vector Decomposition (SVD). The data imbalance between β-Thalassemia carrier and non-carriers is handled by Synthetic Minority Oversampling Technique (SMOTE) and Adaptive Synthetic (ADASYN). Extensive experiments are performed using many state-of-the-art machine learning models and deep learning models. Experimental results indicate the superiority of the proposed approach over existing approaches with an accuracy score of 0.96. metadata Rustam, Furqan and Ashraf, Imran and Jabbar, Shehbaz and Tutusaus, Kilian and Mazas Pérez-Oleaga, Cristina and Pascual Barrera, Alina Eugenia and de la Torre Diez, Isabel mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, kilian.tutusaus@uneatlantico.es, cristina.mazas@uneatlantico.es, alina.pascual@unini.edu.mx, UNSPECIFIED (2022) Prediction β-Thalassemia carriers using complete blood count features. Scientific Reports, 12 (1). ISSN 2045-2322

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production Abierto Inglés Wearable monitoring devices are in demand in recent times for monitoring daily activities including exercise. Moreover, it is widely utilizing for preventing injuries of athletes during a practice session and in few cases, it leads to muscle fatigue. At present, emerging technology like the internet of things (IoT) and sensors is empowering to monitor and visualize the physical data from any remote location through internet connectivity. In this study, an IoT-enabled wearable device is proposing for monitoring and identifying the muscle fatigue condition using a surface electromyogram (sEMG) sensor. Normally, the EMG signal is utilized to display muscle activity. Arduino controller, Wi-Fi module, and EMG sensor are utilized in developing the wearable device. The Time-frequency domain spectrum technique is employed for classifying the three muscle fatigue conditions including mean RMS, mean frequency, etc. A real-time experiment is realized on six different individuals with developed wearable devices and the average RMS value assists to determine the average threshold of recorded data. The threshold level is analyzed by calculating the mean RMS value and concluded three fatigue conditions as >2 V: Extensive); 1–2 V: Moderate, and <1 V: relaxed. The warning alarm system was designed in LabVIEW with three color LEDs to indicate the different states of muscle fatigue. Moreover, the device is interfaced with the cloud through the internet provided with a Wi-Fi module embedded in wearable devices. The data available in the cloud server can be utilized for forecasting the frequency of an individual to muscle fatigue. metadata Gehlot, Anita and Singh, Rajesh and Siwach, Sweety and Vaseem Akram, Shaik and Alsubhi, Khalid and Singh, Aman and Delgado Noya, Irene and Choudhury, Sushabhan mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, aman.singh@uneatlantico.es, irene.delgado@uneatlantico.es, UNSPECIFIED (2022) Real Time Monitoring of Muscle Fatigue with IoT and Wearable Devices. Computers, Materials & Continua, 72 (1). pp. 999-1015. ISSN 1546-2226

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Inglés Deep learning is used to address a wide range of challenging issues including large data analysis, image processing, object detection, and autonomous control. In the same way, deep learning techniques are also used to develop software and techniques that pose a danger to privacy, democracy, and national security. Fake content in the form of images and videos using digital manipulation with artificial intelligence (AI) approaches has become widespread during the past few years. Deepfakes, in the form of audio, images, and videos, have become a major concern during the past few years. Complemented by artificial intelligence, deepfakes swap the face of one person with the other and generate hyper-realistic videos. Accompanying the speed of social media, deepfakes can immediately reach millions of people and can be very dangerous to make fake news, hoaxes, and fraud. Besides the well-known movie stars, politicians have been victims of deepfakes in the past, especially US presidents Barak Obama and Donald Trump, however, the public at large can be the target of deepfakes. To overcome the challenge of deepfake identification and mitigate its impact, large efforts have been carried out to devise novel methods to detect face manipulation. This study also discusses how to counter the threats from deepfake technology and alleviate its impact. The outcomes recommend that despite a serious threat to society, business, and political institutions, they can be combated through appropriate policies, regulation, individual actions, training, and education. In addition, the evolution of technology is desired for deepfake identification, content authentication, and deepfake prevention. Different studies have performed deepfake detection using machine learning and deep learning techniques such as support vector machine, random forest, multilayer perceptron, k-nearest neighbors, convolutional neural networks with and without long short-term memory, and other similar models. This study aims to highlight the recent research in deepfake images and video detection, such as deepfake creation, various detection algorithms on self-made datasets, and existing benchmark datasets. metadata Shahzad, Hina Fatima and Rustam, Furqan and Soriano Flores, Emmanuel and Vidal Mazón, Juan Luis and de la Torre Diez, Isabel and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, emmanuel.soriano@uneatlantico.es, juanluis.vidal@uneatlantico.es, UNSPECIFIED, UNSPECIFIED (2022) A Review of Image Processing Techniques for Deepfakes. Sensors, 22 (12). p. 4556. ISSN 1424-8220

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Cerrado Inglés Network slicing is expected to be critical in the deployment of 5G mobile networks and systems. On top of a single physical infrastructure, the technology enables operators to operate several virtual networks. As the 5G commercialization was recently deployed, network function virtualization (NFV) and software-defined networking (SDN) will drive network slicing. In this article, we present an overview of SDN in 5G, and the motivation, role, and market growth of network slicing. We then discuss usage scenarios of SDN in network slicing for 5G. The proposed architecture comprises the three usage scenarios: enhanced mobile broadband (eMBB) provides the support to varying types of services used; ultra-reliable low-latency communications (URLLC) provides a certain class of applications such as higher bandwidth, high definition video streaming, mobile TV, and so on; massive machine type communications (mMTC) throws light on the types of services used to connect huge numbers of devices. Finally, challenges and solutions based on network slicing in 5G are presented. metadata Babbar, Himanshi and Rani, Shalli and AlZubi, Ahmad Ali and Singh, Aman and Nasser, Nidal and Ali, Asmaa mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, aman.singh@uneatlantico.es, UNSPECIFIED, UNSPECIFIED (2022) Role of Network Slicing in Software Defined Networking for 5G: Use Cases and Future Directions. IEEE Wireless Communications, 29 (1). pp. 112-118. ISSN 1536-1284

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production Abierto Inglés MANET is a mobile ad hoc network with many mobile nodes communicating without a centralized module. Infrastructure-less networks make it desirable for many researchers to publish and bind multimedia services. Each node in this infrastructure-less network acts as self-organizing and re-configurable. It allows services to deploy and attain from another node over the ad hoc network. The service composition aims to provide a user’s requirement by combining different atomic services based on non-functional QoS parameters such as reliability, availability, scalability, etc. To provide service composition in MANET is challenging because of the node mobility, link failure, and topology changes, so a traditional protocol will be sufficient to obtain real-time services from mobile nodes. In this paper, the ad hoc on-demand distance vector protocol (AODV) is used and analyzed based on MANET’s QoS (Quality of Service) metrics. The QoS metrics for MANET depends on delay, bandwidth, memory capacity, network load, and packet drop. The requester node and provider node broker acts as a composer for this MANET network. The authors propose a QoS-based Dynamic Secured Broker Selection architecture (QoSDSBS) for service composition in MANET, which uses a dynamic broker and provides a secure path selection based on QoS metrics. The proposed algorithm is simulated using Network Simulator (NS2) with 53 intermediate nodes and 35 mobile nodes of area 1000 m × 1000 m. The comparative results show that the proposed architecture outperforms, with standards, the AODV protocol and affords higher scalability and a reduced network load metadata Ramalingam, Rajakumar and Muniyan, Rajeswari and Dumka, Ankur and Singh, Devesh Pratap and Mohamed, Heba G. and Singh, Rajesh and Anand, Divya and Delgado Noya, Irene mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, divya.anand@uneatlantico.es, irene.delgado@uneatlantico.es (2022) Routing Protocol for MANET Based on QoS-Aware Service Composition with Dynamic Secured Broker Selection. Electronics, 11 (17). p. 2637. ISSN 2079-9292

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production Abierto Inglés To provide faster access to the treatment of patients, healthcare system can be integrated with Internet of Things to provide prior and timely health services to the patient. There is a huge limitation in the sensing layer as the IoT devices here have low computational power, limited storage and less battery life. So, this huge amount of data needs to be stored on the cloud. The information and the data sensed by these devices is made accessible on the internet from where medical staff, doctors, relatives and family members can access this information. This helps in improving the treatment as well as getting faster medical assistance, tracking of routine activities and health focus of elderly people on frequent basis. However, the data transmission from IoT devices to the cloud faces many security challenges and is vulnerable to different security and privacy threats during the transmission path. The purpose of this research is to design a Certificateless Secured Signature Scheme that will provide a magnificent amount of security during the transmission of data. Certificateless signature, that removes the intricate certificate management and key escrow problem, is one of the practical methods to provide data integrity and identity authentication for the IoT. Experimental result shows that the proposed scheme performs better than the existing certificateless signature schemes in terms of computational cost, encryption and decryption time. This scheme is the best combination of high security and cost efficiency and is further suitable for the resource constrained IoT environment. metadata Kakkar, Latika and Gupta, Deepali and Tanwar, Sarvesh and Saxena, Sapna and Alsubhi, Khalid and Anand, Divya and Delgado Noya, Irene and Goyal, Nitin mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, divya.anand@uneatlantico.es, irene.delgado@uneatlantico.es, UNSPECIFIED (2022) A Secure and Efficient Signature Scheme for IoT in Healthcare. Computers, Materials & Continua, 73 (3). pp. 6151-6168. ISSN 1546-2226

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production Abierto Inglés One of the toughest biometrics and document forensics problems is confirming a signature’s authenticity and legal identity. A forgery may vary from a genuine signature by specific distortions. Therefore, it is necessary to continuously monitor crucial distinctions between real and forged signatures for secure work and economic growth, but this is particularly difficult in writer-independent tasks. We thus propose an innovative and sustainable writer-independent approach based on a Siamese neural network for offline signature verification. The Siamese network is a twin-like structure with shared weights and parameters. Similar and dissimilar images are exposed to this network, and the Euclidean distances between them are calculated. The distance is reduced for identical signatures, and the distance is increased for different signatures. Three datasets, namely GPDS, BHsig260 Hindi, and BHsig260 Bengali datasets, were tested in this work. The proposed model was analyzed by comparing the results of different parameters such as optimizers, batch size, and the number of epochs on all three datasets. The proposed Siamese neural network outperforms the GPDS synthetic dataset in the English language, with an accuracy of 92%. It also performs well for the Hindi and Bengali datasets while considering skilled forgeries metadata Sharma, Neha and Gupta, Sheifali and Mohamed, Heba G. and Anand, Divya and Vidal Mazón, Juan Luis and Gupta, Deepali and Goyal, Nitin mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, divya.anand@uneatlantico.es, juanluis.vidal@uneatlantico.es, UNSPECIFIED, UNSPECIFIED (2022) Siamese Convolutional Neural Network-Based Twin Structure Model for Independent Offline Signature Verification. Sustainability, 14 (18). p. 11484. ISSN 2071-1050

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production Cerrado Inglés Smart vehicle parking is a collaborative effort of technology and human innovation where the efforts are to be minimized to save time and efforts. In smart cities it is one of the common challenges to introduce smart parking to increase parking efficiency and combat numerous issues like identification of free parking slot and real-time dynamic updation on traffic to save fuel and energy. In this work, a new cloud-based smart parking architecture is proposed that can help in predicting the available free parking slots in smart cities. Initially, the methodology collects the car count at any near by parking using Internet of Things (IoT) and Cloud-based approach. Later, the approach uses the Kernel Least Mean Square algorithm to make heuristic predictions about future vacancy using auto-regression. The proposed approach thus utilizes the online learning or model training. To validate the efficacy of the proposed work, the testing is done on the real-time dataset. The extensive numerical investigation is performed on parking lots of four international airports of a smart city in actual deployment scenarios. The experimentation has revealed superior performance of the method in terms of vacancy prediction. metadata Anand, Divya and Singh, Aman and Alsubhi, Khalid and Goyal, Nitin and Abdrabou, Atef and Vidyarthi, Ankit and Rodrigues, Joel J. P. C. mail divya.anand@uneatlantico.es, aman.singh@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED (2022) A Smart Cloud and IoVT-Based Kernel Adaptive Filtering Framework for Parking Prediction. IEEE Transactions on Intelligent Transportation Systems. pp. 1-9. ISSN 1524-9050

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production Abierto Inglés Rivers play a major role within ecosystems and society, including for domestic, industrial, and agricultural uses, and in power generation. Forecasting of suspended sediment yield (SSY) is critical for design, management, planning, and disaster prevention in river basin systems. It is difficult to forecast the SSY using conventional methods because these approaches cannot handle complicated non-stationarity and non-linearity. Artificial intelligence techniques have gained popularity in water resources due to handling complex problems of SSY. In this study, a fully automated generalized single hybrid intelligent artificial neural network (ANN)-based genetic algorithm (GA) forecasting model was developed using water discharge, temperature, rainfall, SSY, rock type, relief, and catchment area data of eleven gauging stations for forecasting the SSY. It is applied at individual gauging stations for SSY forecasting in the Mahanadi River which is one of India’s largest peninsular rivers. All parameters of the ANN are optimized automatically and simultaneously using the GA. The multi-objective algorithm was applied to optimize the two conflicting objective functions (error variance and bias). The mean square error objective function was considered for the single-objective optimization model. Single and multi-objective GA-based ANN, autoregressive and multivariate autoregressive models were compared to each other. It was found that the single-objective GA-based ANN model provided the best accuracy among all comparative models, and it is the most suitable substitute for forecasting SSY. If the measurement of SSY is unavailable, then single-objective GA-based ANN modeling approaches can be recommended for forecasting SSY due to comparatively superior performance and simplicity of implementation metadata Yadav, Arvind and Chithaluru, Premkumar and Singh, Aman and Albahar, Marwan Ali and Jurcut, Anca and Álvarez, Roberto Marcelo and Mojjada, Ramesh Kumar and Joshi, Devendra mail UNSPECIFIED, UNSPECIFIED, aman.singh@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, roberto.alvarez@uneatlantico.es, UNSPECIFIED, UNSPECIFIED (2022) Suspended Sediment Yield Forecasting with Single and Multi-Objective Optimization Using Hybrid Artificial Intelligence Models. Mathematics, 10 (22). p. 4263. ISSN 2227-7390

Article Subjects > Biomedicine
Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Inglés Herbal medicine and nutritional supplements are suggested to treat premenstrual somatic and psycho-behavioural symptoms in clinical guidelines; nonetheless, this is at present based on poor-quality trial evidence. Hence, we aimed to design a systematic review and meta-analysis for their effectiveness in alleviating premenstrual symptoms. The published randomized controlled trials (RCTs) were extracted from Google scholar, PubMed, Scopus and PROSPERO databases. The risk of bias in randomized trials was assessed by Cochrane risk-of-bias tool. The main outcome parameters were analysed separately based on the Premenstrual Symptom Screening Tool and PMTS and DRSP scores. Secondary parameters of somatic, psychological, and behavioural subscale symptoms of PSST were also analysed. Data synthesis was performed assuming a random-effects model, and standardized mean difference (SMDs) was analysed using SPSS version 28.0.0 (IBM, Armonk, NY, USA). A total of 754 articles were screened, and 15 RCTs were included (n = 1211 patients). Primary results for participants randomized to an intervention reported reduced PSST (n = 9), PMTS (n = 2), and DSR (n = 4) scores with (SMD = −1.44; 95% CI: −1.72 to −1.17), (SMD = −1.69; 95% CI: −3.80 to 0.42) and (SMD = 2.86; 95% CI: 1.02 to 4.69) verses comparator with substantial heterogeneity. Physical (SMD = −1.61; 95% CI = −2.56 to −0.66), behavioural (SMD = −0.60; 95% CI = −1.55 to0.35) and mood (SMD = 0.57; 95% CI = −0.96 to 2.11) subscale symptom groupings of PSST displayed similar findings. Fifty-three studies (n = 8) were considered at low risk of bias with high quality. Mild adverse events were reported by four RCTs. Based on the existing evidence, herbal medicine and nutritional supplements may be effective and safe for PMS metadata Sultana, Arshiya and Heyat, Md Belal Bin and Rahman, Khaleequr and Kunnavil, Radhika and Fazmiya, Mohamed Joonus Aynul and Akhtar, Faijan and Sumbul, X. and Vidal Mazón, Juan Luis and Rodríguez Velasco, Carmen Lilí and De La Torre Díez, Isabel mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, juanluis.vidal@uneatlantico.es, carmen.rodriguez@uneatlantico.es, UNSPECIFIED (2022) A Systematic Review and Meta-Analysis of Premenstrual Syndrome with Special Emphasis on Herbal Medicine and Nutritional Supplements. Pharmaceuticals, 15 (11). p. 1371. ISSN 1424-8247

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Inglés The accelerated evolution in computing and transmission automation of the Internet of Vehicles (IoV) has led to enormous research standards that attract many researchers and industries. This century of the Internet of Things (IoT) is propulsive to the routine vehicular ad hoc networks (VANETs) in the IoV. It has emerged as one of the major driving forces for innovations in the intelligent vehicular industry. The World Health Organization (WHO) report confirms that approximately 1.35 million people die because of accidents on the road every year. This requires considerable attention to incorporate more and more safety measures into the automobile industry. Intelligent transportation systems can help bridge the gap between the traditional and the intelligent automotive industry by connecting vehicle to vehicle (V2V) and vehicle to infrastructure (V2I), hence adding much safety in vehicular communication. This paper provides a comprehensive review of the Internet of Vehicles (IoV) which discusses the architectures of IoV including layer types, functions of layers, application area, and communication type supported. Further, it also provides an in-depth insight into state-of-the-art Medium Access Control (MAC) protocols and routing protocols used in IoV communication. The routing protocol comparative summarization considers important parameters which include communication types broadcast, unicast, cluster, multicast, forwarding strategy, recovery strategy, availability of map, and the type of environment urban or highway. The summarization of various protocols highlights strengths, research gaps, and application areas. Finally, the paper addresses various research challenges along with potential future enhancements for the IoV communication. metadata Seth, Ishita and Guleria, Kalpna and Panda, Surya Narayan and Anand, Divya and Alsubhi, Khalid and Aljahdali, Hani Moaiteq and Singh, Aman and A Saeed, Rashid mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, divya.anand@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, aman.singh@unic.co.ao, UNSPECIFIED (2022) A Taxonomy and Analysis on Internet of Vehicles: Architectures, Protocols, and Challenges. Wireless Communications and Mobile Computing, 2022. pp. 1-26. ISSN 1530-8669

Article Subjects > Engineering
Subjects > Teaching Europe University of Atlantic > Research > Scientific Production Abierto Inglés This paper presents the first exploratory results of a research integrated in a more global project on digital and entrepreneurial skills of students at the University ***. The study reveals gaps in professional skills such as problem solving, strategic thinking and creativity. For this reason, a pedagogical project is created integrating the use of social media in training (entrepreneurship), research (knowledge management) and university transfer. The aim is to develop skills in digital talent, (techno)creativity and to implement work methodologies, such as design thinking and growth hacking. In addition, it will encourage selflearning of the students, improve their e-competences, creative capacity and practical skills for a better adaptation to the needs of social demand, where knowledge transfer generates development and growth scenarios (startup) and fosters innovation (competitive capacity). This innovative initiative will enable Higher Education students to acquire the most demanded skills in a multidisciplinary labour market that also requires specific ones in creativity, strategic capacity, project management, product innovation, solution generation and entrepreneurship. This is what forms the basis of an integral project of triangular synergy between University, Business and Society. metadata Comesaña-Comesaña, Patricia and Amorós-Pons, Anna and Alexeeva-Alexeev, Inna mail UNSPECIFIED, UNSPECIFIED, inna.alexeeva@uneatlantico.es (2022) Technocreativity, Social Networks and Entrepreneurship: Diagnostics of Skills in University Students. International Journal of Emerging Technologies in Learning (iJET), 17 (05). pp. 180-195. ISSN 1863-0383

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production Abierto Inglés The probability of medical staff to get affected from COVID19 is much higher due to their working environment which is more exposed to infectious diseases. So, as a preventive measure the body temperature monitoring of medical staff at regular intervals is highly recommended. Infrared temperature sensing guns have proved its effectiveness and therefore such devices are used to monitor the body temperature. These devices are either used on hands or forehead. As a result, there are many issues in monitoring the temperature of frontline healthcare professionals. Firstly, these healthcare professionals keep wearing PPE (Personal Protective Equipment) kits during working hours and as a result it would be very difficult to monitor their body temperature. Secondly, these healthcare professionals also wear face shields and in such cases monitoring temperature by exposing forehead needs removal of face shield. Doing so after regular intervals is surely uncomfortable for healthcare professionals. To avoid such issues, this paper is disclosing a technologically advanced face shield equipped with sensors capable of monitoring body temperature instantly without the hassle of removing the face shield. This face shield is integrated with a built-in infrared temperature sensor. A total of 10 such face shields were printed and assembled within the university lab and then handed over to a group of ten members including faculty and students of nursing and health science department. This sequence was repeated four times and as a result 40 healthcare workers participated in the study. Thereafter, feedback analysis was conducted on questionnaire data and found a significant overall mean score of 4.59 out of 5 which indicates that the product is effective and worthy in every facet. Stress analysis is also performed in the simulated environment and found that the device can easily withstand the typically applied forces. The limitations of this product are difficulty in cleaning the product and comparatively high cost due to the deployment of electronic equipment metadata Kumar Kaushal, Rajesh and Kumar, Naveen and Kukreja, Vinay and S. Alharithi, Fahd and H. Almulihi, Ahmed and Ortega-Mansilla, Arturo and Rani, Shikha mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, arturo.ortega@uneatlantico.es, UNSPECIFIED (2022) Technologically Advanced Reusable 3D Face Shield for Health Workers Confronting COVID19. Computers, Materials & Continua, 72 (2). pp. 2565-2579. ISSN 1546-2226

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Inglés Currently, sustainability is a vital aspect for every nation and organization to accomplish Sustainable Development Goals (SDGs) by 2030. Environmental, social, and governance (ESG) metrics are used to evaluate the sustainability level of an organization. According to the statistics, 53% of respondents in the BlackRock survey are concerned about the availability of low ESG data, which is critical for determining the organization’s sustainability level. This obstacle can be overcome by implementing Industry 4.0 technologies, which enable real-time data, data authentication, prediction, transparency, authentication, and structured data. Based on the review of previous studies, it was determined that only a few studies discussed the implementation of Industry 4.0 technologies for ESG data and evaluation. The objective of the study is to discuss the significance of ESG data and report, which is used for the evaluation of the sustainability of an organization. In this regard, the assimilation of Industry 4.0 technologies (Internet of Things (IoT), artificial intelligence (AI), blockchain, and big data for obtaining ESG data by an organization is detailed presented to study the progress of advancement of these technologies for ESG. On the basis of analysis, this study concludes that consumers are concerned about the ESG data, as most organizations develop inaccurate ESG data and suggest that these digital technologies have a crucial role in framing an accurate ESG report. After analysis a few vital conclusions are drawn such as ESG investment has benefited from AI capabilities, which previously relied on self-disclosed, annualized company information that was susceptible to inherent data issues and biases. Finally, the article discusses the vital recommendations that can be implemented for future work metadata Saxena, Archana and Singh, Rajesh and Gehlot, Anita and Akram, Shaik Vaseem and Twala, Bhekisipho and Singh, Aman and Caro Montero, Elisabeth and Priyadarshi, Neeraj mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, aman.singh@uneatlantico.es, elizabeth.caro@uneatlantico.es, UNSPECIFIED (2022) Technologies Empowered Environmental, Social, and Governance (ESG): An Industry 4.0 Landscape. Sustainability, 15 (1). p. 309. ISSN 2071-1050

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Fundación Universitaria Internacional de Colombia > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Inglés Technology’s expansion has contributed to the rise in popularity of social media platforms. Twitter is one of the leading social media platforms that people use to share their opinions. Such opinions, sometimes, may contain threatening text, deliberately or non-deliberately, which can be disturbing for other users. Consequently, the detection of threatening content on social media is an important task. Contrary to high-resource languages like English, Dutch, and others that have several such approaches, the low-resource Urdu language does not have such a luxury. Therefore, this study presents an intelligent threatening language detection for the Urdu language. A stacking model is proposed that uses an extra tree (ET) classifier and Bayes theorem-based Bernoulli Naive Bayes (BNB) as the based learners while logistic regression (LR) is employed as the meta learner. A performance analysis is carried out by deploying a support vector classifier, ET, LR, BNB, fully connected network, convolutional neural network, long short-term memory, and gated recurrent unit. Experimental results indicate that the stacked model performs better than both machine learning and deep learning models. With 74.01% accuracy, 70.84% precision, 75.65% recall, and 73.99% F1 score, the model outperforms the existing benchmark study. metadata Mehmood, Aneela and Farooq, Muhammad Shoaib and Naseem, Ansar and Rustam, Furqan and Gracia Villar, Mónica and Rodríguez Velasco, Carmen Lilí and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, monica.gracia@uneatlantico.es, carmen.rodriguez@uneatlantico.es, UNSPECIFIED (2022) Threatening URDU Language Detection from Tweets Using Machine Learning. Applied Sciences, 12 (20). p. 10342. ISSN 2076-3417

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Inglés Thyroid disease prediction has emerged as an important task recently. Despite existing approaches for its diagnosis, often the target is binary classification, the used datasets are small-sized and results are not validated either. Predominantly, existing approaches focus on model optimization and the feature engineering part is less investigated. To overcome these limitations, this study presents an approach that investigates feature engineering for machine learning and deep learning models. Forward feature selection, backward feature elimination, bidirectional feature elimination, and machine learning-based feature selection using extra tree classifiers are adopted. The proposed approach can predict Hashimoto’s thyroiditis (primary hypothyroid), binding protein (increased binding protein), autoimmune thyroiditis (compensated hypothyroid), and non-thyroidal syndrome (NTIS) (concurrent non-thyroidal illness). Extensive experiments show that the extra tree classifier-based selected feature yields the best results with 0.99 accuracy and an F1 score when used with the random forest classifier. Results suggest that the machine learning models are a better choice for thyroid disease detection regarding the provided accuracy and the computational complexity. K-fold cross-validation and performance comparison with existing studies corroborate the superior performance of the proposed approach. metadata Chaganti, Rajasekhar and Rustam, Furqan and De La Torre Díez, Isabel and Vidal Mazón, Juan Luis and Rodríguez Velasco, Carmen Lilí and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, juanluis.vidal@uneatlantico.es, carmen.rodriguez@uneatlantico.es, UNSPECIFIED (2022) Thyroid Disease Prediction Using Selective Features and Machine Learning Techniques. Cancers, 14 (16). p. 3914. ISSN 2072-6694

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production Abierto Inglés Using artificial intelligence (AI) based software defect prediction (SDP) techniques in the software development process helps isolate defective software modules, count the number of software defects, and identify risky code changes. However, software development teams are unaware of SDP and do not have easy access to relevant models and techniques. The major reason for this problem seems to be the fragmentation of SDP research and SDP practice. To unify SDP research and practice this article introduces a cloud-based, global, unified AI framework for SDP called DePaaS—Defects Prediction as a Service. The article describes the usage context, use cases and detailed architecture of DePaaS and presents the first response of the industry practitioners to DePaaS. In a first of its kind survey, the article captures practitioner’s belief into SDP and ability of DePaaS to solve some of the known challenges of the field of software defect prediction. This article also provides a novel process for SDP, detailed description of the structure and behaviour of DePaaS architecture components, six best SDP models offered by DePaaS, a description of algorithms that recommend SDP models, feature sets and tunable parameters, and a rich set of challenges to build, use and sustain DePaaS. With the contributions of this article, SDP research and practice could be unified enabling building and using more pragmatic defect prediction models leading to increase in the efficiency of software testing metadata Pandit, Mahesha and Gupta, Deepali and Anand, Divya and Goyal, Nitin and Aljahdali, Hani Moaiteq and Ortega-Mansilla, Arturo and Kadry, Seifedine and Kumar, Arun mail UNSPECIFIED, UNSPECIFIED, divya.anand@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, arturo.ortega@uneatlantico.es, UNSPECIFIED, UNSPECIFIED (2022) Towards Design and Feasibility Analysis of DePaaS: AI Based Global Unified Software Defect Prediction Framework. Applied Sciences, 12 (1). p. 493. ISSN 2076-3417

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Inglés Device-to-device (D2D) communication has attracted many researchers, cellular operators, and equipment makers as mobile traffic and bandwidth demands have increased. It supports direct communication within devices with no need for any intermediate node and, therefore, offers advantage in 5G network while providing wide cell coverage range and frequency reuse. However, establishing acceptable and secure mechanism for D2D communication which ensures confidentiality, integrity, and availability is an issue encountered in this situation. Furthermore, in a resource-constrained IoT environment, these security challenges are more critical and difficult to mitigate, especially during emergence of IoT with 5G network application scenarios. To address these issues, this paper proposed a security mechanism in 5G network for D2D wireless communication dependent on lightweight modified elliptic curve cryptography (LMECC). The proposed scheme follows a proactive routing protocol to discover services, managing link setup, and for data transfer with the aim to reduce communication overhead during user authentication. The proposed approach has been compared against Diffie–Hellman (DH) and ElGamal (ELG) schemes to evaluate the protocol overhead and security enhancement at network edge. Results proved the outstanding performance of the proposed LMECC for strengthening data secrecy with approximate 13% and 22.5% lower overhead than DH and ELG schemes. metadata Gupta, Divya and Rani, Shalli and Singh, Aman and Vidal Mazón, Juan Luis and Wang, Han mail UNSPECIFIED, UNSPECIFIED, aman.singh@unic.co.ao, juanluis.vidal@uneatlantico.es, UNSPECIFIED (2022) Towards Security Mechanism in D2D Wireless Communication: A 5G Network Approach. Wireless Communications and Mobile Computing, 2022. pp. 1-9. ISSN 1530-8669

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production Cerrado Inglés The development of underwater wireless sensor networks (UWSNs) has attracted great interest from many researchers and scientists to detect and monitor unfamiliar underwater domains. To achieve this goal, collecting data with an underwater network of sensors is primordial. Moreover, real-time information transmission needs to be achieved through efficient and enabling technologies for node deployment and data collection in UWSN. The Internet of Things (IoT) helps in real time data transmission, and it has great potential in UWSN, i.e., the Internet of Underwater Things (IoUT). The Internet of Underwater Things (IoUT) is a modern communication ecosystem for undersea things in marine and underwater environments. Intelligent boats and ships, automatic maritime transportation, location and navigation, undersea discovery, catastrophe forecasting and avoidance, as well as intelligent monitoring and security are all intertwined with IoUT technology. In this paper, the enabling technologies of UWSN along with several fundamental key aspects are scrupulously explained. The study aims to inquire about node deployment and data collection strategies, and then encourages researchers to lay the groundwork for new node deployment and advanced data collection techniques that enable effective underwater communication techniques. Besides different types of communication media, applications of UWSNs are also part of this paper. Various existing data collection protocols based on the deployment models are simulated using Network Simulator (NS 2.30) to analyse and compare the performance of state-of-the-art techniques. metadata Chaudhary, Monika and Goyal, Nitin and Benslimane, Abderrahim and Awasthi, Lalit Kumar and Alwadain, Ayed and Singh, Aman mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, aman.singh@uneatlantico.es (2022) Underwater Wireless Sensor Networks: Enabling Technologies for Node Deployment and Data Collection Challenges. IEEE Internet of Things Journal. p. 1. ISSN 2372-2541

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production Abierto Inglés For analytical approach-based word recognition techniques, the task of segmenting the word into individual characters is a big challenge, specifically for cursive handwriting. For this, a holistic approach can be a better option, wherein the entire word is passed to an appropriate recognizer. Gurumukhi script is a complex script for which a holistic approach can be proposed for offline handwritten word recognition. In this paper, the authors propose a Convolutional Neural Network-based architecture for recognition of the Gurumukhi month names. The architecture is designed with five convolutional layers and three pooling layers. The authors also prepared a dataset of 24,000 images, each with a size of 50 × 50. The dataset was collected from 500 distinct writers of different age groups and professions. The proposed method achieved training and validation accuracies of about 97.03% and 99.50%, respectively for the proposed dataset. metadata Singh, Tajinder Pal and Gupta, Sheifali and Garg, Meenu and Gupta, Deepali and Alharbi, Abdullah and Alyami, Hashem and Anand, Divya and Ortega-Mansilla, Arturo and Goyal, Nitin mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, divya.anand@uneatlantico.es, arturo.ortega@uneatlantico.es, UNSPECIFIED (2022) Visualization of Customized Convolutional Neural Network for Natural Language Recognition. Sensors, 22 (8). p. 2881. ISSN 1424-8220

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Inglés At this time, efforts are being made on a worldwide scale to accomplish sustainable development objectives. It has, thus, now become essential to investigate the part of technology in the accomplishment of these Sustainable Development Goals (SDGs), as this will enable us to circumvent any potential conflicts that may arise. The importance of wastewater management in the accomplishment of these goals has been highlighted in the study. The research focuses on the role of fourth industrial revolution in meeting the Sustainable Goals for 2030. Given that water is the most important resource on the planet and since 11 of the 17 Sustainable Goals are directly related to having access to clean water, effective water management is the most fundamental need for achieving these goals. The age of Industry 4.0 has ushered in a variety of new solutions in many industrial sectors, including manufacturing, water, energy, healthcare, and electronics. This paper examines the present creative solutions in water treatment from an Industry-4.0 viewpoint, focusing on big data, the Internet of Things, artificial intelligence, and several other technologies. The study has correlated the various concepts of Industry 4.0 along with water and wastewater management and also discusses the prior work carried out in this field with help of different technologies. In addition to proposing a way for explaining the operation of I4.0 in water treatment through a systematic diagram, the paper makes suggestions for further research as well. metadata Pandey, Shivam and Twala, Bhekisipho and Singh, Rajesh and Gehlot, Anita and Singh, Aman and Caro Montero, Elisabeth and Priyadarshi, Neeraj mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, aman.singh@uneatlantico.es, elizabeth.caro@uneatlantico.es, UNSPECIFIED (2022) Wastewater Treatment with Technical Intervention Inclination towards Smart Cities. Sustainability, 14 (18). p. 11563. ISSN 2071-1050

Article Subjects > Biomedicine
Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Magazines
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Inglés White blood cell (WBC) type classification is a task of significant importance for diagnosis using microscopic images of WBC, which develop immunity to fight against infections and foreign substances. WBCs consist of different types, and abnormalities in a type of WBC may potentially represent a disease such as leukemia. Existing studies are limited by low accuracy and overrated performance, often caused by model overfit due to an imbalanced dataset. Additionally, many studies consider a lower number of WBC types, and the accuracy is exaggerated. This study presents a hybrid feature set of selective features and synthetic minority oversampling technique-based resampling to mitigate the influence of the above-mentioned problems. Furthermore, machine learning models are adopted for being less computationally complex, requiring less data for training, and providing robust results. Experiments are performed using both machine- and deep learning models for performance comparison using the original dataset, augmented dataset, and oversampled dataset to analyze the performances of the models. The results suggest that a hybrid feature set of both texture and RGB features from microscopic images, selected using Chi2, produces a high accuracy of 0.97 with random forest. Performance appraisal using k-fold cross-validation and comparison with existing state-of-the-art studies shows that the proposed approach outperforms existing studies regarding the obtained accuracy and computational complexity. metadata Rustam, Furqan and Aslam, Naila and De La Torre Díez, Isabel and Khan, Yaser Daanial and Vidal Mazón, Juan Luis and Rodríguez Velasco, Carmen Lilí and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, juanluis.vidal@uneatlantico.es, carmen.rodriguez@uneatlantico.es, UNSPECIFIED (2022) White Blood Cell Classification Using Texture and RGB Features of Oversampled Microscopic Images. Healthcare, 10 (11). p. 2230. ISSN 2227-9032

2021

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Inglés Background: To address the current pandemic, multiple studies have focused on the development of new mHealth applications to help curb the number of infections, these applications aim to accelerate the identification and self-isolation of people exposed to SARS-CoV- 2, the coronavirus known to cause COVID-19, by being in close contact with infected individuals. Objective: The main objectives of this paper are: 1)To analyze the current status of COVID-19 apps available the main virtual stores: Google Play Store and App Store, and 2)To propose a novel mobile application based on the limitations of the analyzed apps. Methods: The search for apps in this research was carried out in the main virtual stores: Google Play Store and App Store, until May 2021. After the analysis of the selected apps, a novel app is proposed whose main function will be the multiple transmission of information about the patient's symptoms from the application, without the need for phone calls or chat in real time. For its development, the flowchart shown in this session is followed. Results: The search yielded a total of 50 apps, of which 24 were relevant to this study. It is important to note that 23 of the apps analyzed are free. Of the total number of apps, 54% are available for Android and iOS operating systems. 50% of the apps have more than 5 thousand downloads. This means that Covid-19 related apps are in high demand among mobile device users today. The developed app is called COVINFO and its name comes from the union of the words COVID-19 and information, inserted in such a way that the user can get an idea of the app's functionality just by listening or reading the resulting name. The application has been created for mobile devices with Android operating system, being compatible with Android 4.4 and higher. Conclusions: Of the apps found, 37.5% only offer information about the virus and the necessary measures to avoid infection. During the analysis it was detected that 12.5% of the apps are focused on locating outbreaks and that none of them have been successful for the following reasons: not being interconnected to share data; and the request for access to the user's geolocation, generating distrust on the part of the user who, consequently, rejects them. This work addresses the development of an application for the transmission of the user's symptoms to his regular doctor, based on the fact that only 16.6% of the existing applications have this functionality. The COVINFO app offers a service that no other application on the market has: doctor-patient interaction without the need for calls or chat in real time for constant monitoring by the doctor of the patient's condition and evolution. metadata Herrera Montano, Isabel and Pérez Pacho, Javier and Gracia Villar, Santos and Aparicio Obregón, Silvia and Breñosa, Jose and de la Torre Díez, Isabel mail UNSPECIFIED, UNSPECIFIED, santos.gracia@uneatlantico.es, silvia.aparicio@uneatlantico.es, josemanuel.brenosa@uneatlantico.es, UNSPECIFIED (2021) Analysis of mobile apps for information, prevention and monitoring of covid-19 and proposal of an innovative app in this field. JMIR Preprints. (Submitted)

Thesis Subjects > Engineering Europe University of Atlantic > Teaching > Final Degree Projects Cerrado Español El siguiente trabajo presenta un análisis de cinco parámetros que conforman a una ciudad inteligente adaptados a la Ciudad de Guatemala. Dichos parámetros fueron extraídos de l Modelo Europeo de Ciudades Inteligentes encontrado en el reporte “Ciudades Inteligentes: Clasificación de las ciudades europeas de gran tamaño” producido por el Dr.Giffinger y su equipo del Centro Regional de Ciencia de la Universidad Técnica de Viena(2007). Para evaluar dichos parámetros, es necesario hacer uso de distintos indicadores. Estos fueron desarrollados por la Dr. Patrizia Lombardi en el artículo “Modelando el rendimiento de una ciudad inteligente” encontrado en la Revista Europea de Investigación en Ciencias Sociales (2012). Debido a la incertidumbre que rodea al significado global de una ciudad inteligente, los parámetros propuestos para abarcar el tema en absoluto consisten en: Economía, Población, Gobernación, Movilidad y Ambiente. Cada uno de estos será evaluado con tres indicadores seleccionados con base en la disponibilidad delos datos requeridos para el análisis, con los que actualmente se cuentan para la Ciudad de Guatemala. Seguidamente, se fundamenta el estado de cada parámetro con un análisis y desarrollo con base a datos cualitativos y cuantitativos oficiales extraídos de los correspondientes ministerios, entidades públicas e informes de organizaciones sin lucro. Dada por concluida la recopilación de información y determinado el estado final de cada uno de los cinco parámetros en el cuerpo del trabajo, el capítulo de conclusiones sintetiza las brechas y limitaciones para la adaptación del Modelo a esta ciudad en particular. Por último, se incluyen recomendaciones para la difusión del presente estudio y la posible adaptación de éste para otras ciudades con características similares a las de la Ciudad de Guatemala. metadata Haeussler Vesco, Johan Chris mail johan.haeussler@alumnos.uneatlantico.es (2021) Análisis de la Ciudad de Guatemala aplicando el Modelo Europeo de Ciudades Inteligentes. Diploma thesis, Universidad Europea del Atlántico.

Thesis Subjects > Engineering Europe University of Atlantic > Teaching > Final Degree Projects Cerrado Español La Residencia Universitaria Uneatlántico ha estado operativa desde el 2017, la cual se ha encargado tanto de la gestión de las reservas para alumnos de la Universidad Europea del Atlántico como la administración diaria de los residentes actuales. Las tareas de la Residencia van desde la gestión diaria administrativa, incidencias, limpieza y mantenimiento, manejo de reservas de residentes actuales y solicitudes futuras, hasta el uso de las instalaciones como hotel. Por ende, se vuelve fundamental utilizar una herramienta capaz de integrar todas las funciones y recursos de la Residencia, logrando así una mayor diligencia y coordinación entre las distintas partes que la conforman. Tras analizar las necesidades y los problemas, se plantea la integración de un sistema de planificación de recursos empresariales, mejor conocido como Enterprise Resource Planning o ERP por sus siglas en inglés, para poder alcanzar un mayor orden y mejor manejo de ésta. En consecuencia, el trabajo busca analizar y comparar distintas herramientas ERPs disponibles que puedan ser utilizadas e implementadas a la gestión diaria en donde se logre manejar las distintas áreas que la conforman. El método de trabajo consiste en la comparación de estas herramientas disponibles en la gestión de residencias y determinar cuál es la que mejor se adecua y responde a las necesidades, tanto actuales como futuras. Igualmente, se busca hacer un modelo de prueba en estas distintas herramientas para ver si son adaptables al modelo que se maneja en la residencia. Tras la comparativa, se hará una matriz en donde se identifiquen, de manera visual, tanto las necesidades como los requisitos y la manera en que éstas responden a cada uno de ellos. Obteniendo así la herramienta flexible e iterativa que responda a los requisitos y optimice la gestión, la organización al igual que la coordinación en la Residencia. metadata Escobar Contreras, María Reneé mail maria.escobar@alumnos.uneatlantico.es (2021) Análisis de requisitos y evaluación de herramientas ERPS para la Residencia Universitaria Uneatlántico. Diploma thesis, Universidad Europea del Atlántico.

Thesis Subjects > Engineering Europe University of Atlantic > Teaching > Final Degree Projects Cerrado Español El Centro de Investigación y Tecnología Industrial de Cantabria (CITICAN) ha sido promovido como una iniciativa privada de la Universidad Europea del Atlántico y la Fundación Universitaria Iberoamericana (FUNIBER). Adopta líneas de investigación, cuyo desarrollo se centra en el capital humano para el impulso competitivo de la investigación y de la industria Cántabra. Actualmente el sitio web de CITICAN, presentó un problema para la atención de sus clientes, el cual ocasionó inconformidades en los usuarios tanto finales como técnicos; por lo tanto, se llevó a cabo un estudio que respaldase la decisión de rediseñar el sitio y que presenta a través de un prototipo, una solución con las correcciones necesarias que satisfacen las prioridades del servicio ofrecido a los clientes. La problemática descrita permitió delimitar las áreas de actuación bajo los perfiles sociales, temporales y espaciales, gracias a que las instalaciones de CITICAN se encuentran dentro de la Universidad y el equipo de usuarios técnicos formaron parte de los participantes evaluados fue más sencillo cumplir con los tiempos planificados y llevar a cabo el estudio. Las líneas de actuación ejecutadas se construyeron a través de un marco teórico el cual se compone de conceptos llevados a la práctica en la duración de la carrera profesional. Previo al desarrollo de un prototipo funcional que cumpliera con los requerimientos de los usuarios, fue necesario hacer un diagnóstico de usabilidad a la plataforma actual, el cual se ejecutó bajo tres métricas asegurando la integridad de sus resultados, iniciando con un diagnóstico WPO, tránsito web y por último, una prueba heurística con el fin de justificar adecuadamente bajo resultados verídicos una modificación. Las métricas arrojan resultados negativos para la plataforma actual, un tiempo de respuesta excesivo por el peso de los recursos y la renderización de su contenido. Al realizar un análisis de los resultados recopilados en el diagnóstico de usabilidad e identificar las necesidades del sitio web se procedió con la propuesta del rediseño tomando como principal eje de actuación los requerimientos del sistema y la implementación de las fases de las prácticas en el proceso de diseño web. Se detalla una estructura para cada página que compone el prototipo del sitio web presentado, añadiendo algunas secciones necesarias para distribuir correctamente la información y presentarla de manera ordenada. Con dicha propuesta para el rediseño se pretende tener un espacio más agradable e intuitivo para los usuarios, ya que la función principal del sitio es ofrecer información. El resultado del estudio demuestra que un nuevo sitio web para CITICAN garantizará tener una vitrina digital de los servicios que ofrece, expandiendo su alcance no solo a nivel nacional, si no que internacional, sin necesidad de que los clientes estén presentes en el Centro. Se recomienda implementar las fases del proceso de diseño, ya que representan un elemento crucial al rediseñar una plataforma web, facilitando el entendimiento de la estructura del sitio web. Además, es de utilidad para la creación de un estándar de diseño para el producto final mediante un sistema de diseño establecido. metadata Rodríguez Linares, Adriana Gabriela mail adriana.rodriguez@alumnos.uneatlantico.es (2021) Análisis de usabilidad y rediseño de la plataforma web del Centro de Investigación y Tecnología Industrial de Cantabria (CITICAN). Diploma thesis, Universidad Europea del Atlántico.

Other Subjects > Biomedicine
Subjects > Engineering Europe University of Atlantic > Research > Projects I+D+I Cerrado Español Background/main objectives: Spinal muscular atrophy (SMA) is a devastating neuromuscular disease characterized by degeneration of spinal cord motoneurons (MNs), muscle weakness, and severe disability. SMA is the most common genetic disease resulting in infantile death. It is caused by reduction of the survival motor neuron (SMN) protein due to the loss or mutations of SMN1 gene. In humans, a second duplicate gene (SMN2) produces little and insufficient functional SMN. Since the discovery of the SMN1 gene, intensive efforts have been aimed to develop therapies to increase SMN protein levels. The SNM2-directed antisense oligonucleotide nusinersen effectively increases SMN in clinical trials, but its effectiveness varies between individuals and is markedly diminished in post-symptomatic treated patients. We aim to examine here the possible beneficial effect of combining nusinersen with drugs directed to the CNS and peripheral tissues that we previously found to have beneficial in vivo and in vitro effects in SMA models. We will investigate how these new approaches change the phenotype and analyze in detail their impact on five hallmarks of the disease, i.e., MN deafferentation, spinal cord neuroinflammation, MN alterations in autophagy, neuromuscular junction neurotransmission deficiency, and skeletal muscle structural alterations. Methodology: In vivo experiments will be conducted in mouse models of SMA, which will be subjected to different single or combined treatments; motor behavior tests and survival analysis will be performed. In vitro studies will be carried out in SMA mouse MNs and in induced pluripotent stem cell (iPSC) lines from control and SMA patients. Immunocytochemistry, western blot, and conventional and pre- and post-embedding immunogold electron microscopy studies will be also performed. Additionally, electrophysiological recordings of endplate potentials will be conducted. Expected results: We expect that the use of SMN-independent strategies in combination with nusinersen will help to ameliorate the neuromuscular and systemic alterations in SMA. metadata , IRBLleida and , US mail UNSPECIFIED (2021) Análisis preclínica de nuevos tratamientos combinados para la atrofia muscular espinal: efectos sobre la supervivencia de la motoneurona, la integridad sináptica y la preservación del músculo esquelético. Repositorio de la Universidad. (Unpublished)

Other Subjects > Engineering Europe University of Atlantic > Research > Projects I+D+I Cerrado Español La actividad científico-técnica está orientada a una investigación que nos permita aplicar tecnologías de la información para simular entornos reales que son útiles en el ámbito de la educación y en concreto pretendemos avanzar en los sistemas de evaluación que permitan a los docentes emplear estos entornos digitales. El objetivo general es el de diseñar y desarrollar un entorno virtual experimental para la educación práctica universitaria con énfasis en el sistema de evaluación del proceso de aprendizaje y el control de calidad. Como aspectos novedosos proponemos desarrollar los siguientes puntos: diseño de una plataforma con herramientas de desarrollo de entornos virtuales para el profesorado no especializado y el desarrollo de un sistema de métricas que permita evaluar y cuantificar el aprendizaje. Los resultados perseguidos son los de obtener un sistema de métricas que permita evaluar y cuantificar el aprendizaje basado en entornos virtuales aumentados e inmersivos y los procedimientos para implantar un entorno virtual de prácticas para el profesorado no especializado. metadata CITICAN-Universidad Europea del Atlántico, mail UNSPECIFIED (2021) Aplicación de tecnologías basadas en entornos virtuales e inmersivos para la educación práctica universitaria. Repositorio de la Universidad. (Unpublished)

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production Abierto Inglés The COVID-19 pandemic has profoundly affected almost all facets of peoples’ lives, various economic areas and regions of the world. In such a situation implementation of a vaccination can be viewed as essential but its success will be dependent on availability and transparency in the distribution process that will be shared among the stakeholders. Various distributed ledgers (DLTs) such as blockchain provide an open, public, immutable system that has numerous applications due the mentioned abilities. In this paper the authors have proposed a solution based on blockchain to increase the security and transparency in the tracing of COVID-19 vaccination vials. Smart contracts have been developed to monitor the supply, distribution of vaccination vials. The proposed solution will help to generate a tamper-proof and secure environment for the distribution of COVID-19 vaccination vials. Proof of delivery is used as a consensus mechanism for the proposed solution. A feedback feature is also implemented in order to track the vials lot in case of any side effect cause to the patient. The authors have implemented and tested the proposed solution using Ethereum test network, RinkeyBy, MetaMask, one clicks DApp. The proposed solution shows promising results in terms of throughput and scalability. metadata Chauhan, Harsha and Gupta, Deepali and Gupta, Sheifali and Singh, Aman and Aljahdali, Hani Moaiteq and Goyal, Nitin and Delgado Noya, Irene and Kadry, Seifedine mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, irene.delgado@uneatlantico.es, UNSPECIFIED (2021) Blockchain Enabled Transparent and Anti-Counterfeiting Supply of COVID-19 Vaccine Vials. Vaccines, 9 (11). p. 1239. ISSN 2076-393X

Other Subjects > Biomedicine
Subjects > Engineering Europe University of Atlantic > Research > Projects I+D+I Cerrado Español El reto ambiental que asume el presente proyecto está enmarcado en la gestión de “Residuos del sector primario” dentro del “Plan de Residuos de Cantabria 2017-2023”. El proyecto se enmarca en la aplicación de residuos procedentes de la industria apícola en el ámbito de la biomedicina. La industria productora de cera tiene su origen en el siglo XIX en Alemania. A nivel internacional, la cera de abeja es producida por manufactureros especializados a los cuales los apicultores proporcionan los panales o la cera “cruda”, que después procesan. Para poder ser destinada a fines industriales, cosmética o farmacéutica, tiene que ser, además, purificada por filtración y centrifugada para la eliminación de restos de contaminantes (Stefan Bogdanov, 2009). En España, la producción de cera de abeja se ha mantenido constante a lo largo de los últimos 20 años. Según la última estimación del Ministerio de Agricultura, Pesca y Alimentación, en 2018 se han producido 1,519 toneladas de cera procedente del sector apícola (Programa Nacional de Ayuda a La Apicultura, 2019). En Cantabria, la industria agroalimentaria ha sido y es un pilar fundamental. En concreto la producción y tradición apícola ha pasado de generación en generación siendo signo de identidad en muchas comarcas de la región donde ha impulsado el empleo rural y la conservación del ecosistema. En los últimos años, la cría de abejas en la comunidad ha visto aumentar su trascendencia y difusión gracias a la ganancia de denominaciones de origen protegida (Miel de Liébana) y al incremento de la producción y venta de enjambres causada por la gran demanda a niveles tanto nacional como internacional derivada de lamortalidad de las colmenas (Consejeria de Desarrollo Rural, Ganaderia, Pesca y Biodiversidad, n.d.) La cría de abejas mediante el método tradicional aplicado en Cantabria de los dujos o corchos, permite el crecimiento de los enjambres en panales naturales caracterizados por la obtención de productos más puros y por tanto, con mayor concentración decomponentes bioactivos, debido al ecosistema singular en el que se encuentran, la menor carga parasitaria (por las propias características del panal) y la menor aplicación de tratamientos sanitarios y alimentación artificial (Pliego de Condiciones de La Denominación de Origen Protegida “Miel de Liébana,” n.d.). Precisamente por las características de la apicultura tradicional, creemos que el aprovechamiento o reciclado de los residuos derivados de la producción de la cera de abeja procedente de la comarca de Liébana tendría una potencial aplicación en la investigación biomédica, concretamente en la prevención y/o tratamiento del proceso inflamatorio. Esto promovería el reciclado de los residuos originados en el procesado de la cera de abeja creada mediante el método apícola tradicional, estimulando la economía circular. Además, la utilización de estas matrices podría poner a Cantabria como ejemplo a seguir en la estimulación de la cría de abeja de manera tradicional que, a su vez, favorece la protección de la biodiversidad del ecosistema. metadata CITICAN-Universidad Europea del Atlántico, mail UNSPECIFIED (2021) CAROZO: componentes bioactivos en residuos de producción apícola. Repositorio de la Universidad. (Unpublished)

Other Subjects > Engineering
Subjects > Nutrition Europe University of Atlantic > Research > Projects I+D+I Cerrado Español Tiene como objetivo estrechar las relaciones entre los Miembros del Grupo, a fin de aunar esfuerzos y establecer normas amplias de actuación que encaucen, incrementen y optimicen la capacidad de I+D que tiene cada uno de ellos por separado. Asimismo, tiene por objetivo la difusión y divulgación de las actividades de I+D desarrolladas por el Grupo. metadata CITICAN-Universidad Europea del Atlántico, mail UNSPECIFIED (2021) Creación de un Grupo Operativo orientado al sector de productos de la molinería. Repositorio de la Universidad. (Unpublished)

Thesis Subjects > Engineering Europe University of Atlantic > Teaching > Final Degree Projects Cerrado Español En el presente trabajo se detalla el proceso de investigación y desarrollo que fue necesario para la creación de una aplicación web, concretamente en el back-end, que permita a los usuarios gestionar videos e información de manera sencilla y centralizada. Esta aplicación planea centrarse en las organizaciones educativas quienes manejan una gran cantidad de recursos de video auxiliares para las materias que se imparten en sus programas. Este trabajo también presenta cada capítulo que fue necesario para el correcto desarrollo de la aplicación los cuales son: el marco teórico, los requerimientos y requisitos, la descripción de la propuesta y las conclusiones. metadata Cóbar Guardado, José Ricardo mail jose.cobar@alumnos.uneatlantico.es (2021) Desarrollo e implementación de un sistema de gestión de recursos de video para facilitar el manejo de videos y su información. Diploma thesis, Universidad Europea del Atlántico.

Other Subjects > Engineering
Subjects > Teaching Europe University of Atlantic > Research > Projects I+D+I Cerrado Español El proyecto (2022-2025) tiene como objetivo la mejora la formación práctica de los estudiantes de magisterio y maestros de escuela en los países de la UE, reduciendo el desgaste profesional. Liderado por la UNEAT, cuenta con equipos científicos y tecnológicos de las universidades de FUNIBER, la Universidad Jan Kochanowski (Polonia), la University Antwerp Plantijn (Bélgica), la Universidad de Limerick (Irlanda), y la Palacky University Olomouc (República Checa). También cuenta con la inclusión en el equipo de trabajo de los institutos de formación continua de la Świętokrzyskie Centrum Doskonalenia Nauczycieli -ŚCDN- (Polonia ) y el Centro de Formación del profesorado e Innovación Educativa de Segovia (CFIE), así como escuelas primarias y secundarias europeas e instituciones asociadas como la Asociación para la Formación Docente en Europa (ATEE), el Instituto de Ciencias de la Educación de la Universidad de Barcelona, el Consejo de Educación y Formación de Irlanda (ETBI), entre otros. En la propuesta del proyecto se quiere facilitar la transición de los docentes de los estudios al trabajo con el apoyo de medios digitales. Para alcanzar este objetivo, a partir de la definición de un enfoque europeo para este período de transición, el equipo de proyecto propone desarrollar una plataforma digital como marco común para la inducción docente, con una comunidad de aprendizaje basada en la práctica reflexiva que reunirá a los proveedores de formación inicial docente (educación previa al servicio) y desarrollo profesional continuo para docentes (educación en servicio). metadata UNEATLANTICO, and FUNIBER, mail UNSPECIFIED (2021) Digital Academy in teaching practice for a seamless transition from pre-service to in-service (DigitalTA). Repositorio de la Universidad. (Unpublished)

Other Subjects > Engineering Europe University of Atlantic > Research > Projects I+D+I Cerrado Inglés El proyecto de investigación está orientado en mejorar la difusión del conocimiento en nutrición humana, promover el compromiso social de los estudiantes y llenar el vacío de habilidades específicas en la educación dietética: habilidades prácticas, habilidades interpersonales/de coaching y competencias digitales. En este sentido, a través de un método eficaz de aprendizaje experiencial, el proyecto tiene como objetivo cubrir la brecha de competencias prácticas consideradas como un tema crítico para todos los profesionales de la salud, y se trata de aplicar tecnologías de la información para simular entornos reales que son útiles en el ámbito de la educación, e innovar en los sistemas de evaluación que permitan a los docentes emplear estos entornos digitales. metadata UNEATLANTICO, mail UNSPECIFIED (2021) Digital Lab for Education in Dietetics combining Experiential Learning and Community Service (E+ DIETING_lab). Repositorio de la Universidad. (Unpublished)

Thesis Subjects > Engineering Europe University of Atlantic > Teaching > Final Degree Projects Cerrado Español En el siguiente trabajo se propone el diseño de una serie de mobiliario urbano, con un poste cargador solar, que permita la incorporación de energía solar a la mayoría de estos elementos para facilitar el uso de energías renovables en el espacio público y reducir su coste para hacerlo más accesible. Durante su eleboración no sólo se diseñará el poste principal y varios elementos que lo acompañen, puesto que un elemento sin una serie no es un producto deseado en el mercado, sino que, se realizará el diseño del circuito eléctrico con el que contará el poste con panel solar y que permitirá que se adapate a las necesidades de cada elemento. Este circuito será el que dictamine las dimensiones que serán necearias para que el poste base pueda incorporar todos los elementos de manera segura. Posteriormente se realizará un pequeño estudio de costes para obtener un coste de producción estimado para cada elemento así como de la serie completa. metadata Balsa Nuñez, María mail UNSPECIFIED (2021) Diseño de elementos de mobiliario urbano con integración de energía solar. Diploma thesis, Universidad Europea del Atlántico.

Other Subjects > Biomedicine
Subjects > Engineering Europe University of Atlantic > Research > Projects I+D+I Cerrado Español Las miopatías hereditarias monogénicas, como la atrofia muscular espinal (SMA), la enfermedad de Duchenne o la distrofia miotónica I, están causadas por mutaciones o deleciones de genes que codifican proteínas esenciales para la homeostasis de las fibras musculares esqueléticas (miofibras). Estas miopatías son muy devastadoras, debutan muy precozmente con debilidad muscular, seguida de parálisis progresiva y, en las formas más severas, conducen a la muerte de los pacientes. Nuestro principal objetivo del presente proyecto es el diseño de un nuevo sistema de liberación de ASOs, basado en nanopartículas biopoliméricas (NPs) funcionalizadas, específicamente diseñado para la terapia génica por vía sistémica de miopatías hereditarias y, en particular, la SMA. Consideramos que la incorporación selectiva, mediante NPs funcionalizadas, de los ASOs Nusinersen y GapmeR Atrogin-1 en las miofibras SMA potenciaría su efecto terapéutico, especialmente de la función motora, al elevar los niveles de SMN en el músculo y disminuir la atrofia muscular característica de la miopatía SMA. Además, reduciría el elevado coste económico para el Sistema Nacional de Salud de los tratamientos con ASOs. metadata UNEATLANTICO, mail UNSPECIFIED (2021) Diseño de nanopartículas funcionalizadas con oligonucleótidos antisentido y Marizomib para la terapia génica de la miopatía en la atrofia muscular espinal. Repositorio de la Universidad. (Unpublished)

Thesis Subjects > Engineering Europe University of Atlantic > Teaching > Final Degree Projects Cerrado Español El presente trabajo tiene como objeto el diseño de las diferentes instalaciones y áreas básicas necesarias para la puesta en marcha de una planta en cultivo e investigación de algas en un establecimiento industrial. La nave en cuestión se situara en Cantabria, en el municipio de Reinosa, ya que cuenta con un gran polígono abastecido con todos los requerimientos a exigir, además de ser un enclave estratégico con fácil acceso a la A-67.El trabajo a desarrollar se basa en la necesidad de encontrar nuevas fuentes alimenticias para las futuras generaciones. Por ello el presente proyecto tendrá como objetivo el diseño de una nave dedicada a la investigación acuícola, centrada en el desarrollo y estudio de algas, creando un entorno adecuado para esta práctica con las comodidades correspondientes, mejorando la producción, la eficacia de trabajo. Es decir, conseguir un bioproceso seguro y estable, evitando las caídas en el rendimiento y que la producción se ajuste a la demanda de la planta. La especie utilizada para realizar los experimentos fue Ulva lactuca, más comúnmente conocida como lechuga de mar o Ulva rígida. Talo laminar de color verde claro con márgenes ondulados, base en forma de cuña; talo de 3.1-7-4 cm de largo, de 0.8-1.4 cm de ancho; células con disposición irregular en vista superficial, ovaladas, poliédricas a irregulares; en corte transversal se observa una separación entre membranas de 5 µm, células más largas que anchas de 5- 10 µm de ancho, de 15-20 µm de largo (León, Quiroz, Rivas, 2017). Los resultados mostraron que la Ulva rígida se ve muy afectada por los factores físico-químicos del medio de cultivo. La planta está sujeta a perturbaciones externas inevitables que obligan a ejercer una vigilancia continua sobre el proceso, por ello el diseño de esta tendrá en consideración estos factores. Se concluyó que: las especies de Ulva utilizadas presentan tasas de crecimiento comprendidas entre el 10 y 20 % día-1 y un alto contenido proteico y otros nutrientes esenciales. metadata Cuevas González, Luis Miguel mail miguel.cuevas@alumnos.uneatlantico.es (2021) Diseño de una nave industrial para la investigación y cultivo del macroalga ulva rígida. Diploma thesis, Universidad Europea del Atlántico.

Thesis Subjects > Engineering Europe University of Atlantic > Teaching > Final Degree Projects Cerrado Español La mayoría de las veces, las distintas evaluaciones que realizan los profesores no son los datos finales que necesita una Universidad, sino que estos datos deben de transformarse primero siguiendo una estructura base que provee la misma. Todo este proceso de transformación conlleva un trabajo extra al profesor, en el que debe de hacer uso de herramientas externas tales como hojas de cálculo o plantillas, y durante el cual incluso pueden llegar a darse errores en el manejo de los datos. Además, a la Universidad no les queda constancia sobre las evaluaciones del profesor por lo que si llegaran a perderse estos datos no habría forma de recuperarlos. En este documento se diseña e implementa una solución de software para este problema, que además puede llegar a integrarse con otros sistemas internos de la Universidad, aligerando así la carga del trabajo del profesor y el tiempo que invierte, así como también reduciendo la incerteza y errores que puedan contener los datos. metadata Arévalo Aguirre, Gerardo Javier mail gerardo.arevalo@alumnos.uneatlantico.es (2021) Diseño y desarrollo de api rest para plataforma docente malla. Diploma thesis, Universidad Europea del Atlántico.

Thesis Subjects > Engineering Europe University of Atlantic > Teaching > Final Degree Projects Cerrado Español El control de los trabajadores y sus horarios es una tarea compleja que cada empresa maneja de formas distintas y aunque existen softwares y aplicaciones que implementan funcionalidades que permiten a estas empresas la gestión de estos horarios, estas no terminan de satisfacer las necesidades de la empresa por las necesidades específicas de la misma. metadata Madera Arenas, Víctor René mail victor.madera@alumnos.uneatlantico.es (2021) Diseño y desarrollo de sistema de información para la gestión de los registros de personal de la Universidad Europea del Atlántico. Diploma thesis, Universidad Europea del Atlántico.

Thesis Subjects > Engineering Europe University of Atlantic > Teaching > Final Degree Projects Cerrado Español Con el paso del tiempo, la tecnología ha tenido un crecimiento exponencial, presentando significativos avances casi a diario. Haciendo muy difícil por no decir imposible, que hoy en día cualquier tipo de empresa u organización sobreviva sin tener una presencia digital. Dentro de las diversas ramas que envuelve la tecnología, se encuentra el concepto de Email marketing. Siendo este un canal de comunicación entre las empresas u organizaciones con sus potenciales y actuales clientes. Siendo un poco más concreto, el Email Marketing emplea el correo electrónico como medio de comunicación, mediante el cual hace llegar cualquier tipo de contenido a sus destinatarios. Este Trabajo Final de Grado, aborda el caso especifico del Email Marketing en relación con el departamento de comunicación de FUNIBER (Fundación Universitaria Iberoamericana), la cual hace uso de este canal para entregar su propuesta de valor en el sector educativo a sus clientes. Concretamente, se emplea para dar a conocer sus diversos programas educativos ya sean de grados, maestrías, especializaciones o doctorados. Así como también para comunicar acerca de eventos específicos programados a lo largo del año. Esto se realiza con el fin de, primeramente, aportar dicho valor y adquirir más clientes. Por lo que se puede decir que es un proceso fundamental para la organización. Sin embargo, el Email Marketing, no solo implica la acción de realizar el envío de correos electrónicos a una lista de usuarios. Implica a su vez, un proceso iterativo que incluye los procesos de planificación, desarrollo y estudio de impacto de los envíos realizados. Destacando que todos estos cuatro procesos tienen una vital importancia y dependen los unos de los otros. Este Trabajo de Fin de Grado, se centra en la problemática actual de la organización en referencia al proceso de estudio de impacto de los envíos masivos. Concretamente de optimización al momento de la obtención de las estadísticas que permiten al departamento de comunicación realizar dicho estudio de impacto, en el cual se basaran las planificaciones de las campañas futuras. Precisamente, se encontró? que este proceso puede optimizarse mediante el planteamiento y desarrollo de una plataforma web, que permitiera al equipo del departamento de comunicación de FUNIBER agilizar esta parte. La función de esta plataforma es reunir las estadísticas principales de los envíos masivos (KPI's) y presentarlas de una manera estructurada y clara a sus usuarios para que dediquen el menor tiempo posible en la obtención de las estadísticas para centrarse en el estudio de los envíos pasados y la planificación de los envíos futuros. Para esto, en el presente Trabajo Final de Grado, se detalla el Diseño y desarrollo del BackEnd de dicha plataforma web para la gestión y visualización de análisis estadísticos de los envíos masivos del departamento de comunicación de FUNIBER. metadata Galeano Quijano, Leonardo Enrique mail leonardo.galeano@alumnos.uneatlantico.es (2021) Diseño y desarrollo del backend de una plataforma web para la gestión y visualización de análisis estadísticos de los envíos masivos del departamento de comunicación de Funiber - kyrios. Diploma thesis, Universidad Europea del Atlántico.

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production Abierto Inglés Tomato is one of the most essential and consumable crops in the world. Tomatoes differ in quantity depending on how they are fertilized. Leaf disease is the primary factor impacting the amount and quality of crop yield. As a result, it is critical to diagnose and classify these disorders appropriately. Different kinds of diseases influence the production of tomatoes. Earlier identification of these diseases would reduce the disease’s effect on tomato plants and enhance good crop yield. Different innovative ways of identifying and classifying certain diseases have been used extensively. The motive of work is to support farmers in identifying early-stage diseases accurately and informing them about these diseases. The Convolutional Neural Network (CNN) is used to effectively define and classify tomato diseases. Google Colab is used to conduct the complete experiment with a dataset containing 3000 images of tomato leaves affected by nine different diseases and a healthy leaf. The complete process is described: Firstly, the input images are preprocessed, and the targeted area of images are segmented from the original images. Secondly, the images are further processed with varying hyper-parameters of the CNN model. Finally, CNN extracts other characteristics from pictures like colors, texture, and edges, etc. The findings demonstrate that the proposed model predictions are 98.49% accurate. metadata Trivedi, Naresh K. and Gautam, Vinay and Anand, Abhineet and Aljahdali, Hani Moaiteq and Gracia Villar, Santos and Anand, Divya and Goyal, Nitin and Kadry, Seifedine mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, santos.gracia@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED (2021) Early Detection and Classification of Tomato Leaf Disease Using High-Performance Deep Neural Network. Sensors, 21 (23). p. 7987. ISSN 1424-8220

Other Subjects > Engineering
Subjects > Teaching Europe University of Atlantic > Research > Projects I+D+I Cerrado Español Se trata de una actividad orientada a desarrollar una exploración que nos permita establecer un mecanismo fiable de análisis de la dimensión social de un emprendimiento tecnológico para alcanzar su sostenibilidad y ofrecer, a partir del diagnóstico, un servicio de orientación al/a emprendedor/a. El desarrollo sostenible es uno de los retos más complejos a los que se enfrentan los negocios en la actualidad. Se trata de un aspecto poco explorado en relación a emprendimientos, especialmente en relación a los factores sociales. Por ello se hace preciso poder disponer de metodologías para realizar un diagnóstico de sostenibilidad a un emprendimiento tecnológico, con énfasis en la dimensión social. metadata CITICAN-Universidad Europea del Atlántico, mail UNSPECIFIED (2021) Emprendimientos tecnológicos sostenibles: diagnóstico y orientación en su dimensión social. Repositorio de la Universidad. (Unpublished)

Thesis Subjects > Engineering
Subjects > Nutrition Europe University of Atlantic > Teaching > Final Degree Projects Cerrado Español Introducción: Se estima que actualmente la industria vitivinícola produce 1.5 toneladas de residuos por hectáreas al año, para 2021 la superficie total de viñedo a nivel mundial es de aproximadamente 7.3 millones de hectáreas. La cantidad de residuos generados por esta industria, supone un problema social, por lo que se debe encontrar la manera adecuada de gestionarlos. Siendo la valorización de residuos una solución óptima, ya que a su vez contribuirá a una economía circular. Los principales residuos generados son las lías y el orujo, que son de sumo provecho debido a las altas concentraciones de compuesto bioactivos que pueden ser extraídos para su reincorporación al sector industrial.Objetivos: Describir que métodos pueden emplearse para la extracción de compuestos bioactivos de los residuos de la industria vitivinícola. Material y métodos: Revisión bibliográfica, en la cual los documentos e información fue obtenida a partir de distintas bases de datos, como ScienceDirect, Google Academic, Research Gate, PubMed y Scientific Research. Se emplearon criterios de inclusión para seleccionar artículos cuyas fechas de publicación fueran desde 2015 hasta 2020.Resultados y discusión: Se contrastaron distintos datos sobre los métodos que presentaban un mayor rendimiento en la extracción de fenoles, polifenoles y antocianinas de orujo de uva y lías de vino. Se logró comprobar que aunque la extracción sólido-líquido es la más empleada se pueden mejorar los rendimientos de extracción al complementarlo con otros métodos como pueden ser las microondas, el ultrasonido o el uso de líquidos iónicos. Conclusiones: Existen variedad de métodos para la extracción los fenoles y las antocianinas presentes en los residuos de la industria vitivinícola. Aunque hay métodos que funcionan adecuadamente como la extracción a través de solventes, también hay métodos emergentes sobre los cuales hacen falta más estudios para asegurar su fiabilidad, como la extracción por ultrasonido y líquido iónico. La disolución etanol: agua probó ser un el solvente que permite un mayor rendimiento de extracción. metadata Aglietti Arcia, Alissa mail alissa.aglietti@alumnos.uneatlantico.es (2021) Estrategias para el aprovechamiento de residuos en la industria vitivinícola. Diploma thesis, Universidad Europea del Atlántico.

Other Subjects > Engineering Europe University of Atlantic > Research > Projects I+D+I
Fundación Universitaria Internacional de Colombia > Research > Projects I+D+I
Ibero-american International University > Research > Projects I+D+I
Ibero-american International University > Research > Projects I+D+I
Universidad Internacional do Cuanza > Research > Projects I+D+I Cerrado Español El proyecto de investigación que se pretende llevar a cabo se refiere a la “Formación práctica mediante la aplicación de tecnologías basadas en entornos virtuales, aumentados e inmersivos“, y está orientado a una investigación que nos permita aplicar tecnologías de la información para simular entornos reales que son útiles en el ámbito de la educación y en concreto pretendemos innovar en los sistemas de evaluación que permitan a los docentes emplear estos entornos digitales. Las plataformas y medios digitales están cada vez más presentes en la sociedad y por ende en las organizaciones empresariales. Los profesionales de la educación no son ajenos a esta situación y se aprovechan de estas tecnologías y a la vez se enfrentan al reto de adaptarse de manera constante al avance tecnológico y a las repercusiones que tiene en su desempeño. En este ámbito, el desarrollo de las plataformas digitales para aprendizaje se ha visto impulsado por la confluencia de múltiples factores entre los cuales se destaca el avance tecnológico, la disponibilidad de dispositivos, las nuevas generaciones de nativos digitales. La formación e-learning es un ejemplo del auge de estas plataformas digitales pero todavía nos encontramos tecnologías más avanzadas como la realidad virtual, tecnologías inmersivas, Internet de las Cosas, etc. que también tienen o tendrán cabida en el entorno educativo. Nuestro proyecto nace con el objetivo de aportar valor a este escenario alrededor de los conocidos como entornos virtuales. Desde el sector educativo universitario, se ha sabido ver la oportunidad de la aplicación de estas técnicas a los procesos formativos del alumnado, inicialmente desde las ramas de la ingeniería que se dedicaban al propio desarrollo de estas tecnologías, y posteriormente desde las disciplinas más afines al aprendizaje cognitivo humano como pueden ser la Psicología o la Pedagogía que buscan evaluar estas técnicas respecto a otras metodologías más clásicas presentes en la Educación. Sin embargo, como se puede extraer de diversos artículos científicos que aplican estas modalidades para la educación, persisten carencias para que los docentes de cualquier área/disciplina dispongan de herramientas lo suficientemente intuitivas para crear los entornos virtuales para simular los entornos profesionales de su especialidad. El diseño de herramientas para docentes (T. Budai, 2019), ayudaría a evitar estas barreras de entrada para extender su uso. Por otro lado, aunque las publicaciones que aplican este tipo de tecnologías a la enseñanza (N. Pellas, 2020), la formación profesional (H. B. Andersson, 2020), o incluso a aprendizajes cognitivos (E. Rho, 2020), consideran que son muy positivas desde el punto de vista pedagógico (H. Ardiny, 2018), se reclama una necesidad en cuanto a establecer unas métricas y metodologías de evaluación apropiadas al proceso de enseñanza-aprendizaje (A. Dengel, 2018), (A. Christopoulos, 2019). En algunos casos se habla la gran asignatura pendiente, que es el tema de la evaluación. Cuando los docentes intentan implementar instrumentos de evaluación basados en entornos digitales, encuentran dificultades para hallar el equilibrio entre la evaluación, la metodología y el uso de los nuevos medios. Ante este escenario, el proyecto pretende diseñar y desarrollar un entorno virtual experimental para la educación práctica universitaria con énfasis en el sistema de evaluación del proceso de aprendizaje y el control de calidad. metadata , (MLS) mail mls@devnull.funiber.org (2021) IMMERSIVE TECH: Formación práctica mediante la aplicación de tecnologías basadas en entornos virtuales, aumentados e inmersivos. Repositorio de la Universidad. (Unpublished)

Thesis Subjects > Engineering Europe University of Atlantic > Teaching > Final Degree Projects Cerrado Español Son muchas las organizaciones que están haciendo un cambio a arquitecturas CICD por los beneficios que esta presenta y los avances en los sistemas de automatización y las tecnologías relacionadas. En este trabajo se implementará una arquitectura CICD en un entorno de desarrollo de software de un centro de educación superior, se hará una integración de GitLab con Jenkins la cual estará basada en el patrón de diseño observer. Posterior al análisis y diseño de la arquitectura se hará una instalación de los servidores y la configuración para comunicar los servicios, se estudiará el funcionamiento detrás de todos esos servicios y archivos de configuración, y se identificará como cada servicio cumple su rol para satisfacer los requerimientos presentes. metadata Solano Flores, Ernesto Eduardo mail ernesto.solano@alumnos.uneatlantico.es (2021) Implementación de una arquitectura CICD en un entorno de desarrollo de software de un centro de educación superior. Diploma thesis, Universidad Europea del Atlántico.

Thesis Subjects > Engineering Europe University of Atlantic > Teaching > Final Degree Projects Cerrado Español La hamburguesa de atún es un producto de I+D que no se ha definido por ley y por lo tanto no se rige por alguna legislación especifica. En este supuesto partimos de la necesidad de adaptar la producción a las normas de calidad IFS/BRC de una empresa. Los estudios de APPCC se han hecho a partir de documentos de orientación de la Comisión Europea. Se han tomado en cuenta los criterios de control y de definición de varias legislaciones como las bases de los criterios que el producto debe cumplir. El resultado esperado es la integración de la hamburguesas de atún al sistema de calidad de la empresa para cumplir sus aspectos técnicos y que se pueda comercializar en grandes superficies internacionales. metadata Velásquez Herrera, Gabriel mail gabriel.velasquez@alumnos.uneatlantico.es (2021) Integración de protocolos IFS/BRC a una línea de hamburguesas de atún. Diploma thesis, Universidad Europea del Atlántico.

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production Abierto Inglés In this work a complete proof of the Collatz Conjecture is presented. The solution assumes as hypothesis that Collatz's Conjecture is a consequence. We found that every natural number n_i∈N can be calculated starting from 1, using the function n_i=((2^(i-Ω)-C))⁄3^Ω , where: i≥0 represents the number of steps (operations of multiplications by two subtractions of one and divisions by three) needed to get from 1 to n_i, Ω≥0 represents the number of multiplications by three required and 0≤C≤2^(i-⌊i/3⌋ )-2^((i mod 3)) 3^⌊i/3⌋ is an accumulative constant that takes into account the order in which the operations of multiplication and division have been performed. Reversing the inversion, we have obtained the function: ((3^Ω n_i+C))⁄2^(i-Ω)=1 that proves that Collatz Conjecture it’s a consequence of the above and also proofs that Collatz Conjecture it’s true since ((3^Ω n_i+C))⁄2^(i-Ω) is the recursive form of the Collatz’s function. metadata Crespo Álvarez, Jorge mail jorge.crespo@uneatlantico.es (2021) Orbits Theory. A Complete Proof of the Collatz Conjecture. Cambridge Open Engage. (Unpublished)

Thesis Subjects > Engineering Europe University of Atlantic > Teaching > Final Degree Projects Cerrado Español El proyecto consiste en el diseño para la rehabilitación de un edificio existente ubicado en Soba (Cantabria), a fin de adecuarlo a una línea de producción para elaborar queso madurado a partir de pequeños volúmenes de leche cruda. La leche para la producción de queso se obtendrá de la explotación ganadera del promotor del proyecto, la cual está ubicada en la misma zona donde será emplazada la quesería. La quesería está diseñada y equipada con el fin de controlar las fases de elaboración, envasado y etiquetado. Adicionalmente, se ha agregado un área de degustación para poder realizar catas. Para lograr elaborar un queso de buena calidad, es necesario poner especial atención al diseño y disposición de la quesería. Además, esta debe estar personalizada y adaptada a las necesidades reales del productor y conforme a la legislación vigente. Para la realización de este proyecto se contó con el asesoramiento de una arquitecta y de un especialista en quesos artesanos. De esta manera, el diseño se adaptó lo más posible a las necesidades reales promotor. Además, se realizó un estudio de viabilidad económica para comprobar que la empresa tendrá éxito. metadata Kuestermann Briz, Elianne mail elianne.kustermann@alumnos.uneatlantico.es (2021) Proyecto de rehabilitación de un inmueble para la creación de una quesería artesanal. Diploma thesis, Universidad Europea del Atlántico.

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production Abierto Inglés The Internet of Things (IoT) has changed the worldwide network of people, smart devices, intelligent things, data, and information as an emergent technology. IoT development is still in its early stages, and numerous interrelated challenges must be addressed. IoT is the unifying idea of embedding everything. The Internet of Things offers a huge opportunity to improve the world’s accessibility, integrity, availability, scalability, confidentiality, and interoperability. However, securing the Internet of Things is a difficult issue. The IoT aims to connect almost everything within the framework of a common infrastructure. This helps in controlling devices and, will allow device status to be updated everywhere and at any time. To develop technology via IoT, several critical scientific studies and inquiries have been carried out. However, many obstacles and problems remain to be tackled in order to reach IoT’s maximum potential. These problems and concerns must be taken into consideration in different areas of the IoT, such as implementation in remote areas, threats to the system, development support, social and environmental impacts, etc. This paper reviews the current state of the art in different IoT architectures, with a focus on current technologies, applications, challenges, IoT protocols, and opportunities. As a result, a detailed taxonomy of IoT is presented here which includes interoperability, scalability, security and energy efficiency, among other things. Moreover, the significance of blockchains and big data as well as their analysis in relation to IoT, is discussed. This article aims to help readers and researchers understand the IoT and its applicability to the real world. metadata Kumar, Arun and Sharma, Sharad and Singh, Aman and Alwadain, Ayed and Choi, Bong-Jun and Breñosa, Jose and Ortega-Mansilla, Arturo and Goyal, Nitin mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, josemanuel.brenosa@uneatlantico.es, arturo.ortega@uneatlantico.es, UNSPECIFIED (2021) Revolutionary Strategies Analysis and Proposed System for Future Infrastructure in Internet of Things. Sustainability, 14 (1). p. 71. ISSN 2071-1050

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production Cerrado Inglés People still drown on beaches in unacceptable numbers due to the lack of knowledge about the risks taking place in them. The proposed methodology forecasts electronic bathing flags in beaches by integrating the benefits of metocean operational systems, machine learning and web-based decision support technologies into a 24/7 risk assessment service that could be easily implemented at any beach worldwide with low costs of maintenance. Firstly, a crosscutting analysis between metocean conditions, beach characteristics and flag records was performed. Secondly, an expert system, based on Deep Learning, was developed to obtain electronic bathing flags as an indicator of the dynamic risk of drowning on beaches. The input variables of the Deep Neural Network were significant wave height, mean wave period, wind velocity, marine current velocity, incidence angle, and beach modal state. Finally, the application of the method to the Santa Catarina’s beaches (Brazil) conveniently reproduced the status flag of beaches. metadata García-Alba, Javier and Bárcena, Javier F. and Pedraz, Luis and Fernández, Felipe and García, Andrés and Mecías-Calvo, Marcos and Costas-Veiga, Javier and Sámano Celorio, María Luisa and Szpilman, David mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, marcos.mecias@uneatlantico.es, javier.costas@uneatlantico.es, marialuisa.samano@uneatlantico.es, UNSPECIFIED (2021) SOSeas Web App: An assessment web-based decision support tool to predict dynamic risk of drowning on beaches using deep neural networks. Journal of Operational Oceanography. pp. 1-20. ISSN 1755-876X

Other Subjects > Engineering Europe University of Atlantic > Research > Projects I+D+I Cerrado Español "CITICAN, para el desarrollo de este proyecto contará con la colaboración del Instituto de Hidráulica Ambiental de la Universidad de Cantabria (IHCantabria). Ambas instituciones ya han colaborado y desarrollado el proyecto Desarrollo de una herramienta de evaluación para predecir el riesgo dinámico de ahogamiento en las playas “SOSeas” generando una herramienta capaz de establecer una bandera electrónica en función de datos históricos de riesgos y condiciones de marea, viento y corriente en espacios acuáticos naturales. Y finalmente queremos destacar el apoyo explícito de diversas entidades nacionales e internacionales (Bandera Azul, Sociedade Brasileira de Salvamento “SOBRASA”), así como de diversos grupos de investigación de universidades españolas (Grupo de Investigación en Actividades Acuáticas y Socorrismo “GIAAS”, de la Universidad de A Coruña; y el Grupo de Investigación de Rendimiento y Motricidad en Salvamento y Socorrismo “REMOSS”, de la Universidad de Vigo)." metadata CITICAN-Universidad Europea del Atlántico, mail UNSPECIFIED (2021) SOSeas-CANT (continuación del SOSeas). Repositorio de la Universidad. (Unpublished)

Thesis Subjects > Engineering Europe University of Atlantic > Teaching > Final Degree Projects Cerrado Español Este último año de pandemia ha sido difícil para muchas personas el tener que pasar todo el día dentro de sus hogares y, con la creciente popularidad de los videojuegos, se ha abierto una nueva opción en el catálogo del entretenimiento. Con esta fama, las plataformas de streaming se han hecho eco de este crecimiento y han conseguido una subida nunca vista y, en concreto, dentro del género competitivo (Stream Hatchet, 2020), permitiendo llegar a un mayor número de gente de todas las condiciones. Esto hace que las compañías se hayan interesado en adaptar sus consolas y videojuegos a personas con distintas discapacidades, desde filtros para daltonismo hasta mandos adaptables. Este documento se ocupará de detallar el diseño y desarrollo de un videojuego multijugador en línea en dónde se pretende lograr un acceso un público general, tanto casual como experto. metadata Cabezón Arias, Miguel Ángel mail miguel.cabezon@alumnos.uneatlantico.es (2021) SUIN: Diseño y desarrollo de un videojuego 3D en línea para público de 3 o más años. Diploma thesis, Universidad Europea del Atlántico.

Other Subjects > Engineering
Subjects > Nutrition Europe University of Atlantic > Research > Projects I+D+I Cerrado Español A través del presente proyecto de transferencia se pretende aportar una innovación en relación a un marcador en plasma que se correlacione con el consumo de frutas y verduras por parte de la población. A partir de ello, se pretenden comercializar nuevos servicios basados en la tecnología y orientados a la mejora de la salud en la población general y en el deporte. metadata , Universidad de León mail UNSPECIFIED (2021) Servicios tecnológicos para la industria alimentaria y la salud en torno al consumo de frutas y verduras. Repositorio de la Universidad. (Unpublished)

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production Abierto Inglés COVID-19 had led to severe clinical manifestations. In the current scenario, 98 794 942 people are infected, and it has responsible for 2 124 193 deaths around the world as reported by World Health Organization on 25 January 2021. Telemedicine has become a critical technology for providing medical care to patients by trying to reduce transmission of the virus among patients, families, and doctors. The economic consequences of coronavirus have affected the entire world and disrupted daily life in many countries. The development of telemedicine applications and eHealth services can significantly help to manage pandemic worldwide better. Consequently, the main objective of this paper is to present a systematic review of the implementation of telemedicine and e-health systems in the combat to COVID-19. The main contribution is to present a comprehensive description of the state of the art considering the domain areas, organizations, funding agencies, researcher units and authors involved. The results show that the United States and China have the most significant number of studies representing 42.11% and 31.58%, respectively. Furthermore, 35 different research units and 9 funding agencies are involved in the application of telemedicine systems to combat COVID-19. metadata Alonso, Susel Góngora and Marques, Goncalo and Barrachina, Isidro and Garcia-Zapirain, Begonya and Arambarri, Jon and Salvador, Javier Cabo and de la Torre Díez, Isabel mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, jon.arambarri@citican.org, UNSPECIFIED, UNSPECIFIED (2021) Telemedicine and e-Health research solutions in literature for combatting COVID-19: a systematic review. Health and Technology, 11 (2). pp. 257-266. ISSN 2190-7188

Other Subjects > Engineering
Subjects > Teaching Europe University of Atlantic > Research > Projects I+D+I Cerrado Español El presente proyecto se orienta a crear una plataforma digital que permita mejorar el seguimiento de estudiantes universitarios que cursan programas formativos a través de entornos virtuales de aprendizaje. Nuestra propuesta propone crear un modelo para la captura datos de relativos a alumnos que estudian en un entorno virtual de aprendizaje haciendo énfasis en datos que evolucionan en el tiempo, así como datos referidos a las interacciones y participaciones de los estudiantes. A partir de los datos recogidos, y a través de tecnologías de clustering crearemos un sistema de modelado dinámico de estudiantes de forma no supervisada y, paralelamente, desarrollaremos tecnologías de análisis de datos del perfil social de los estudiantes. Contando con el modelado de los estudiantes (global y social), clasificaremos de forma dinámica a los estudiantes, identificando aquellos que requieren de especial atención, particularmente por situación de riesgo de abandono, y asociaremos posibles indicadores que motivan su estado. Como fase final, crearemos un primer sistema de actuación basado en mecanismos de comunicación personalizada con los estudiantes y la generación de alertas a docentes. Todo ello ajustado al contexto y perfil dinámico de cada alumno. Así mismo, propondremos un sistema que pudiera actuar específicamente para fomentar interacciones sociales entre estudiantes con objeto a mejorar su motivación y ayuda mutua. metadata Editores y Consultores Especializados, and UNEATLANTICO, and Universitat Politècnica de Catalunya, mail UNSPECIFIED (2021) WITH_YOU: Tecnologías de modelado dinámico de estudiantes y asistentes digitales para la mejora de resultados en plataformas de e-learning. Repositorio de la Universidad. (Unpublished)

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production Abierto Inglés This research article reports a compact fractal 4 × 4 UWB extended bandwidth MIMO antenna with physical dimensions of 44 × 44 mm2 for high-speed wireless applications. The reported antenna comprises four fractal radiating elements that are symmetrical and placed orthogonal to each other with a respective rectangular ground printed on the opposite plane. A higher isolation is achieved between the radiating elements by the placement of a fractal patch orthogonally and no separate decoupling structure is required. The antenna offers a −10 dB transmission capacity of 2.84–15.88 GHz. The fractal radiating element, which is embedded by an inverted T-type stub placed within a rectangular slot and an etched rotated C-type slot, provides band-stop filters for WiMAX (Worldwide inter-operability for Microwave Access) and WLAN (wireless local area network)-interfering bands. The key parameters of diversity performance are compared by simulation and measurement (fabricated prototype) of ECC (envelope correlation coefficient), DG (directive gain), TARC (total active reflection coefficient) and CCL (channel capacity loss). The antenna offers an omnidirectional radiation pattern with an average gain of 3.52 dBi metadata Sharma, Manish and Vashist, Prem Chand and Alsukayti, Ibrahim and Goyal, Nitin and Anand, Divya and Mosavi, Amir H. mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, divya.anand@uneatlantico.es, UNSPECIFIED (2021) A Wider Impedance Bandwidth Dual Filter Symmetrical MIMO Antenna for High-Speed Wideband Wireless Applications. Symmetry, 14 (1). p. 29. ISSN 2073-8994

Other Subjects > Engineering
Subjects > Nutrition Europe University of Atlantic > Research > Projects I+D+I Cerrado Español La Organización de las Naciones Unidas para la Alimentación y la Agricultura (FAO) estima que una de las vías para alimentar a los más de 9000 millones de personas y miles de millones de animales que previsiblemente habrá en la Tierra en 2050 será con insectos. Dicha alternativa se adelanta a la previsión de que este aumento demográfico coincidirá con una importante degradación del planeta como consecuencia del cambio climático y la sobreexplotación de los recursos. necesitaremos un aumento del 70% se proteína para alimentar el planeta y recomendaban el insecto como fuentes de alimentación. Un aspecto en el que la insectocultura aprueba con buena nota es que la cría industrializada de tenebrio genera menos residuos y emisiones de gases de efecto invernadero que la ganadería convencional. Desde ese momento comienzan a apoyar al máximo mediante leyes y subvenciones muy importantes, como la del 1 enero del 2017 y el uso y comercialización del Tenebrio Molitor como fuente sostenible y saludable de alimento. La Soja está deforestando gran parte del planeta y se tiende a eliminar la dependencia que tenemos de ella y las harinas de pescado se pretende restringir una media de una tonelada menos al año en pesca para no sobrecargar a nuestros océanos. Esto hace que ahora sea el momento prefecto para comenzar con este tipo de producción. Además, se sabe que es una opción saludable: actualmente la entomofagia está regulada en la Unión Europea, Asia, América Latina y África, donde unos 2000 millones de personas ya complementan su dieta con insectos comestibles que se pueden encontrar en supermercados o restaurantes. En este proyecto se pretende, por un lado, desarrollar una BAC (Barrita Alimentaria Concentrada) con harina de tenebrio molitor y, por otro lado, estudiar la aceptabilidad que tendría en potenciales consumidores. metadata , YNSECTO mail UNSPECIFIED (2021) YNSECTO: Desarrollo de un nuevo producto a partir de harinas de tenebrio molitor con fines de alimentación humana. Repositorio de la Universidad. (Unpublished)

2020

Other Subjects > Engineering Europe University of Atlantic > Research > Projects I+D+I Cerrado Español El Centro de Investigación y Tecnología Industrial de Cantabria (CITICAN) fue creado en 2014 para el desarrollo de proyectos y servicios I+D+i , en pro de la innovación y el crecimiento tecnológico en el ámbito industrial de Cantabria. Actualmente, CITICAN se plantea como estrategia de crecimiento, la mejora de sus estructuras y procesos para una mayor flexibilidad, capacidad y eficiencia en sus servicios de investigación y de proyectos. Una vía de actuación clave ha sido la implantación de una herramienta TIC específicamente diseñada según las características y los requerimientos propios de la organización. Ésta ha significado un avance innovador, bajo el concepto ampliamente conocido y expuesto por la Organización de Cooperación y Desarrollo Económicos (OECD, 2005), sobre la implantación de cambios con el propósito de mejorar los resultados. De este modo, la actuación para la cual se solicita la subvención, consistió en el diseño, desarrollo, implementación y validación de una herramienta TIC, adaptada a medida, según los requerimientos específicos de la organización, para la estandarización de los procesos relacionados con la gestión de proyectos de investigación. El objetivo último de esta actuación ha sido la mejora significativa de la eficiencia y de la gestión de la calidad en el desarrollo de proyectos I+D+i. Entre las funcionalidades desarrolladas para esta herramienta se destacan: gestión documental, verificación de estado, emisión de alertas y generación de informes. - Organización de Cooperación y Desarrollo Económicos (OCDE) (2005). Manual de Oslo. Guía para la recogida e interpretación de datos sobre innovación. 3ra ed. Editorial, Tragasa. metadata CITICAN-Universidad Europea del Atlántico, and UNEATLANTICO, mail UNSPECIFIED (2020) Diseño, desarrollo e implementación de un sistema de gestión de investigación adaptado a un centro de investigación de carácter privado. Repositorio de la Universidad. (Unpublished)

Other Subjects > Engineering
Subjects > Teaching Europe University of Atlantic > Research > Projects I+D+I
Fundación Universitaria Internacional de Colombia > Research > Projects I+D+I
Ibero-american International University > Research > Projects I+D+I
Ibero-american International University > Research > Projects I+D+I
Universidad Internacional do Cuanza > Research > Projects I+D+I Cerrado Español 1- Gestionar online el proceso de revisión de contenidos recibidos y gestionarlo a distancia, contando con usuarios que se conectan al sistema de forma online y aportan sus valoraciones a través de la misma plataforma. En este caso se trata de facilitar un flujo de trabajo entre los diferentes participantes en el proceso (director de revista, editor en jefe, editor y revisor), de forma que puedan optimizar su productividad y trabajar de forma asincrónica sobre unos mismos contenidos editoriales y siguiendo un proceso homogéneo de acuerdo a nuestros procedimientos. 2- Automatizar determinados procesos de revisión de contenidos. En concreto, habíamos considerado de interés mejorar el proceso de revisión del formato de los artículos recibidos gracias a un software basado en inteligencia artificial. Teniendo en cuenta que los artículos científicos tienen una estructura y contenidos normalizados, pensamos que era posible automatizar algunos elementos de la revisión preliminar de contenidos. 3- Disponer de una solución para la fidelización de autores-revisores generando automáticamente certificados de participación como revisores de artículos científicos. Teniendo en cuenta la dificultad de lograr la participación de revisores científicos, y como parte del sistema de fidelización, se propuso una innovación en la plataforma, que permite generar de forma automática un auto-certificado para los revisores. 4- Estudiar la aplicación de los metadatos, las plataformas multilingües y las de e-commerce para distribución de contenidos. En este caso, lo que se hizo fue solicitar unos estudios de vigilancia tecnológica relacionados con: - Estándares internacionales para la creación de metadatos que nos permitan indexar de la mejor manera posible nuestros contenidos. - Estándares para plataformas multilingües que nos fueran de aplicación para crear un sistema de gestión de contenidos multi-idioma enlazado con los procesos de traducción. - Plataformas de e-commerce adaptadas a la distribución de contenidos electrónicos que nos permitiesen monetizar determinados contenidos y venderlos en Internet. metadata , (MLS) mail mls@devnull.funiber.org (2020) Estudios de vigilancia tecnológica y proyecto piloto para revista electrónica. Repositorio de la Universidad. (Unpublished)

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production Cerrado Inglés Employing software engineering to build an integrated, standardized, and scalable solution is closely associated with the healthcare domain. Furthermore, new diagnostic techniques have been developed to obtain better results in less time, saving costs, and bringing services closer to the most unprotected areas. This paper presents the integration of a top-notch component, such as hardware, software, telecommunications, and medical equipment, to produce a complete system of Electronic Health Record (EHR). The EHR implementation aims to contribute to the expansion of the health services offer concerning people who live in locations where typically have difficult access to medical care. The methodology throughout the work is a Strategic Planning to set priorities, focus energy and resources, strengthen operations, ensure that directors, managers, employees, and other stakeholders are working toward common goals, establish agreement around intended outcomes/results. A medical and technical team is incorporated to complete the tasks of process and requirements analysis, software coding and design, technical support, training, and coaching for EHR system users throughout the implementation process. The adoption of those tools reflect notably some expected results and benefits on patient care. The EHR implementation ensures that information collection does not duplicate already existing information or duplicate effort and maximize the practical use of the data collected. Moreover, the EHR reduces mistakes in hospital readmissions, improves paperwork, promotes the progress of the state's health care system providing emergency, specialty, and primary health care in a rural area of Campeche. The EHR implementation is critical to support decision making and to promote public health. The total number of consults increased markedly from 2012 (14021) to 2019 (34751). The most commonly treated diseases in this region of Mexico are hypertension (17632) and diabetes (13156). The best results are obtained in the Nutrition (20,61%) and clinical psychology services (16,67%), and the worst levels are registered in pediatric and surgical oncology services where only 1,59% and 1,97% of the patients are admitted in less than 30 min, respectively. metadata Uc, Belmar Mex and Castillo-Sánchez, Gema and Marques, Gonçalo and Arambarri, Jon and de la Torre-Díez, Isabel mail UNSPECIFIED (2020) An Experience of Electronic Health Records Implementation in a Mexican Region. Journal of Medical Systems, 44 (6). ISSN 0148-5598

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production Abierto Inglés, Español, Portugués La importancia de la seguridad de la información en las empresas corporativas de tecnología de la información tiene el objetivo principal de proponer medidas de seguridad para proteger la información en las empresas corporativas de tecnología de la información. En este sentido, la investigación es una investigación cualitativa, exploratoria y descriptiva, ya que se basa en la búsqueda de material bibliográfico que permita sugerir medidas de seguridad para la protección de la información. Los datos secundarios se recopilaron sistemáticamente, buscando la palabra clave: medidas de seguridad y sus sinónimos. La búsqueda se realizó en bases de datos computarizadas, como Google Acadêmico® y el Portal de Periódicos Capes. Se ha identificado un conjunto de sugerencias para medidas de seguridad que permiten a las empresas corporativas en el campo de la tecnología de la información aprovechar. Se destaca como conclusión que las medidas preventivas, de detección y correctivas propuestas deben estar involucradas en un plan de seguridad y contingencia difundido en toda la organización.. metadata Cassinda Quissanga, Fernando and Fernandes, Roberto Fabiano mail UNSPECIFIED, roberto.fabiano@funiber.org (2020) Importancia de la seguridad de la información en las empresas de tecnología de información corporativa. Project, Design and Management, 2 (1). pp. 87-102. ISSN 26831597

Other Subjects > Engineering
Subjects > Teaching Europe University of Atlantic > Research > Projects I+D+I Cerrado Español La idea de nuestro proyecto parte de los conocidos como bots, chatbots o asistentes virtuales. El planteamiento del proyecto se orienta a explorar y desarrollar tecnologías alrededor del procesamiento del lenguaje natural, la inteligencia artificial y la gestión del conocimiento para minimizar las tareas repetitivas de los empleados que trabajan con plataformas digitales. La aplicación de estas tecnologías se encuentra en una fase inmadura, con escasez de soluciones, y sobre todo con retos tecnológicos pendientes de resolver como se denota en el estado del arte: “Poco se sabe de cómo incorporar empleados digitales dentro de los procesos de negocio actuales.... por lo que retamos a la comunidad científica a desarrollar mayor investigación en este campo”, “Centrarse en los desarrolladores para ofrecer herramientas que permitan a cualquier profesor integrar bots en sus clases, sin dificultad”, “Revisando las publicaciones recientes se revela la falta de investigación en relación con la integración de la tecnología de los chatbots con los sistemas de gestión del conocimiento”. En definitiva, se requiere aportar saltos tecnológicos que permitan cubrir carencias y necesidades como: disponer de herramientas que permitan a cualquier empleado personalizar y crear bots, contar con sistemas de gestión del conocimiento que permitan superar la escasez de datos de entrenamiento, etc. El presente proyecto pretende generar el conocimiento necesario para avanzar en el desarrollo tecnológico de asistentes virtuales cognitivos para instituciones educativas con énfasis en el desarrollo de herramientas que permitan a un empleado crear la versión digital de sí mismo y a la vez estén integrados en un sistema corporativo de gestión del conocimiento. A tal fin, entre otros puntos, proponemos crear una ontología semántica para el dominio de instituciones educativas, desarrollar una tecnología de gestión del conocimiento corporativo integrable con soluciones de asistentes cognitivos, desarrollar una nueva tecnología de intermediación entre las soluciones de procesado natural del lenguaje y de bots y finalmente crear y validar un prototipo experimental de creación de estos asistentes cognitivos. Esta propuesta se alinea con el ámbito tecnológico transversal de “servicios TIC” de la Estrategia de Especialización Inteligente RIS3 de Cantabria y encuadrada en el Clúster TIC de Cantabria. metadata CITICAN-Universidad Europea del Atlántico, and UNEATLANTICO, and Universidad de León, mail UNSPECIFIED (2020) Tecnologías de gestión del conocimiento y de intermediación para asistentes virtuales cognitivos en organizaciones del ámbito educativo (DigitalWorker.edu). Repositorio de la Universidad. (Unpublished)

Conference or Workshop Item Subjects > Engineering
Subjects > Communication Europe University of Atlantic > Research > Scientific Production Cerrado Inglés The TELEDU tele-education ecosystem, integrated by software and hardware components, allows the use of Web resources through Interactive Digital TV (iDTV) without the need to be continuously connected. It works with any existing digital TV standard and is especially useful for users who do not have broadband, being a very effective solution in places where there is a digital divide. The user must have, at least, a cell phone with 3G connection and any of these three options: Digital Terrestrial TV (DTT), Satellite TV or Cable TV. The conception of TELEDU is based on the premise that the software will offer a friendly interaction. Based on this, an interoperable, open and scalable environment has been developed, which works with PCs, tablets, smartphones and digital TV, offering a visual interface oriented to children, the elderly and people with functional diversity and people with technophobia. The concept of Transmedia Online Object Content (TOOC) is introduced, so that digital contents are in different formats and people with functional diversity and people with technophobia. The concept of TOOC is introduced, so that digital contents are in different formats (paper book, e-book, post, audio, interactive video, virtual reality, serious game, webinar, etc.), on different devices and platforms, locally or in the cloud, with usable multimodal access designed for everyone, and adapting to each user, regardless of the accessibility problems they have. metadata de Castro Lozano, Carlos and Ramírez Uceda, José Miguel and Sainz de Abajo, Beatriz and Salcines, Enrique García and Arambarri, Jon and Aguilar Cordón, Joaquín and Cabo Salvador, Javier and Alcantud Marín, Francisco mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, jon.arambarri@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED (2020) Teledu: Transmedia Learning Ecosystem for People at Risk of Exclusion. In: Applications and Usability of Interactive TV 9th Iberoamerican Conference, jAUTI 2020, Aveiro, Portugal.

2019

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production Abierto Español El presente tema se refiere a la caracterización de los sistemas operativos móviles móviles: Android, Symbian, iPhone, Windows Phone. En el caso de los sistemas operativos móviles, es más seguro y más susceptible a los virus informáticos, la metodología de forma cualitativa basada en el referencial bibliográfico, los datos recogidos en libros, manuales técnicos, informaciones de fabricante y en sitios de Internet; al análisis de los datos documentales, hecha en tablas. Sin embargo, se concluye que no todo tipo de virus informáticos infectan los teléfonos celulares, depende del núcleo (núcleo) del sistema operativo. Es posible saber que Symbian es el sistema operativo más propenso a la contaminación de los virus informáticos, este sistema operativo está hecho de un lenguaje de programación C ++ proveniente del lenguaje C una de las más populares y posee muchos desarrolladores. Android es un sistema operativo para dispositivos móviles, no tan seguro, basado en el núcleo (Linux) de Linux, siendo un software libre permite mayor número de desarrolladores de la tecnología. Windows Phone es el menos susceptible a las plagas virtuales. Y Microsoft ha invertido bastante en su sistema de seguridad, ha restringido el acceso al app store para impedir que el usuario descargue programas fuera del mercado, ya que cada día se plantean numerosas aplicaciones. La tecnología bluetooth representa una mayor forma de transmisión de virus. metadata Cassinda Quissanga, Fernando mail UNSPECIFIED (2019) Caracterización de sistemas operacionales móviles celular: Android, Symbian, iphone y Windows phone. Project Design and Management, 1 (2). pp. 75-88. ISSN 2683-1597

Other Subjects > Engineering Europe University of Atlantic > Research > Projects I+D+I Cerrado Español La Unión Europea es la segunda productora de plásticos del mundo, y España es el cuarto país de la Unión Europea con mayor demanda de plásticos. El 27 de marzo 2019, la Eurocámara aprobó la directiva que prohíbe a partir de 2021, la venta de plásticos de un solo uso. Los bioplásticos comestibles y biodegradables podrían constituir una alternativa real a la producción de plásticos contaminantes. El proyecto persigue el aprovechamiento de los residuos del sector alimentario cántabro (los residuos cereales de la industria de bebidas espirituosas y el suero de la leche, residuo de la producción de quesos), con el objeto de fabricar un substrato plástico comestible, biodegradable y compostable, como alternativa a la presencia de plásticos contaminantes y no reciclables, uno de los principales desafíos de la contaminación del planeta. Para desarrollar soluciones sostenibles de economía circular, se propone la creación de un bioplástico con buenas propiedades mecánicas, con la finalidad de crear envases y film de plástico comestibles, en concreto bandejas para alimentos y biofilm, para envasar productos del sector agroalimentario. Este proyecto se desarrolla en Cantabria, España y está financiado por la convocatoria SODERCAN EC. El período que comprende este proyecto: 2019-2020 metadata CITICAN-Universidad Europea del Atlántico, and UNEATLANTICO, mail UNSPECIFIED (2019) Desarrollo de un bioplástico comestible y compostable a partir de residuos de la industria cántabra (BIOC3). Repositorio de la Universidad. (Unpublished)

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production Abierto Inglés Seven aromatic polyamides and copolyamides were synthesized from two different aromatic diamines: 4,4′-(Hexafluoroisopropylidene)bis(p-phenyleneoxy)dianiline (HFDA) and 2,4-Aminobenzenesulfonic acid (DABS). The synthesis was carried out by polycondensation using isophthaloyl dichloride (1SO). The effect of an increasing molar concentration of the sulfonated groups, from DABS, in the copolymer properties was evaluated. Inherent viscosity tests were carried out to estimate molecular weights. Mechanical tests were carried out under tension, maximum strength ( σ max), Young’s modulus (E), and elongation at break (εmax) to determine their mechanical properties. Tests for water sorption and ion exchange capacity (IEC) were carried out. Proton conductivity was measured using electrochemical impedance spectroscopy (EIS). The results indicate that as the degree of sulfonation increase, the greater the proton conductivity. The results obtained showed conductivity values lower than the commercial membrane Nafion 115 of 0.0065 S cm−1. The membrane from copolyamide HFDA/DABS/1S0-70/30 with 30 mol DABS obtained the best IEC, with a value of 0.747 mmol g−1 that resulted in a conductivity of 2.7018 × 10−4 S cm−1, lower than the data reported for the commercial membrane Nafion 115. According to the results obtained, we can suggest that further developments increasing IEC will render membranes based on aromatic polyamides that are suitable for their use in PEM fuel cells. metadata Pali-Casanova, Ramón and Yam Cervantes, Marcial Alfredo and Zavala-Loría, José and Loría-Bastarrachea, María and Aguilar-Vega, Manuel and Dzul Lopez, Luis Alonso and Sámano Celorio, María Luisa and Crespo-Álvarez, Jorge and García Villena, Eduardo and Agudo-Toyos, Pablo and Méndez-Martínez, Francisco mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, luis.dzul@unini.edu.mx, marialuisa.samano@uneatlantico.es, jorge.crespo@uneatlantico.es, eduardo.garcia@uneatlantico.es, pablo.agudo@uenatlantico.es, UNSPECIFIED (2019) Effect of Sulfonic Groups Concentration on IEC Properties in New Fluorinated Copolyamides. Polymers, 11 (7). p. 1169. ISSN 2073-4360

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production Abierto Inglés, Español La migración a la Televisión Digital Terrestre o Televisión Digital Abierta, con el estándar ISDB-Tb, es una transición que supone cambios severos y grandes inversiones en la transmisión y elaboración de contenidos por parte de las empresas televisivas y también significa un cambio para la audiencia, ya que también deben adecuar sus televisores para tener acceso a la nueva señal con más calidad de audio y video. Por ello, se hace necesaria una guía metodológica para estudiar la normativa, apuntar los requisitos esenciales para las distintas fases de implementación, en trabajar mancomunadamente con empresas y profesionales especializados, con buenas prácticas en dirección de proyectos reconocidas a nivel internacional. En Bolivia, la ley de Telecomunicaciones 164 se modificó el 31 de agosto de 2017 para disponer un conglomerado de resoluciones y decretos que promueven la migración digital de los distintos canales de televisión analógicos y posteriormente se estableció una serie de disposiciones para la habilitación de licencias de funcionamiento por 15 años más de forma gratuita para los actuales operadores. Los canales tienen un nuevo plazo de apagón digital para las 3 ciudades principales hasta noviembre de 2021 y otros de menor cobertura hasta noviembre de 2025. La guía resultante de este trabajo, se ha aplicado ya y se espera sea aporte para todos los demás 600 canales que aún no han migrado. metadata Mejia Noe, Alex Fernando Mejia and Arambarri, Jon mail UNSPECIFIED, jon.arambarri@uneatlantico.es (2019) Guía metodológica para la implementación de televisión digital en Bolivia. Project Design and Management, 1 (2). pp. 89-110. ISSN 2683-1597

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production Abierto Inglés The objectives this study were to examine the integrated use of oil–coagulant for the direct extraction of coagulant from Moringa oleifera (MO) with 5% and 10% (NH4)2SO4 extractor solution to harvest Scenedesmus obliquus cultivated in urban wastewater and to analyze the oil extracted from MO and S. obliquus. An average content of 0.47 g of coagulant and 0.5 g of oil per gram of MO was obtained. Highly efficient algal harvest, 80.33% and 72.13%, was achieved at a dose of 0.38 g L−1 and pH 8–9 for 5% and 10% extractor solutions, respectively. For values above pH 9, the harvest efficiency decreases, producing a whitish water with 10% (NH4)2SO4 solution. The oil profile (MO and S. obliquus) showed contents of SFA of 36.24–36.54%, monounsaturated fatty acids of 32.78–36.13%, and polyunsaturated fatty acids of 27.63–30.67%. The biodiesel obtained by S. obliquus and MO has poor cold flow properties, indicating possible applications limited to warm climates. For both biodiesels, good fuel ignition was observed according to the high cetane number and positive correlation with SFA and negative correlation with the degree of saturation. This supports the use of MO as a potentially harmless bioflocculant for microalgal harvest in wastewater, contributing to its treatment, and a possible source of low-cost biodiesel. metadata Ruiz-Marin, Alejandro and Canedo-Lopez, Yunuen and Narvaez-Garcia, Asteria and Zavala Loría, José del Carmen and Dzul Lopez, Luis Alonso and Sámano Celorio, María Luisa and Crespo-Álvarez, Jorge and García Villena, Eduardo and Agudo-Toyos, Pablo mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, jose.zavala@unini.edu.mx, luis.dzul@unini.edu.mx, marialuisa.samano@uneatlantico.es, jorge.crespo@uneatlantico.es, eduardo.garcia@uneatlantico.es, pablo.agudo@uenatlantico.es (2019) Harvesting Scenedesmus obliquus via Flocculation of Moringa oleifera Seed Extract from Urban Wastewater: Proposal for the Integrated Use of Oil and Flocculant. Energies, 12 (20). p. 3996. ISSN 1996-1073

Revista Subjects > Engineering Europe University of Atlantic > Research > Scientific Magazines
Fundación Universitaria Internacional de Colombia > Research > Scientific Magazines
Ibero-american International University > Research > Scientific Magazines
Ibero-american International University > Research > Scientific Magazines
Universidad Internacional do Cuanza > Research > Scientific Magazines Abierto Español La revista Project Design and Management nace como una publicación semestral con el objetivo de invitar a la reflexión y el debate para entender correctamente cual es la función, aporte y responsabilidad del área Project, Design y Management (PDM) en la actualidad, no solo del mundo académico sino además en el espacio profesional. Comenzando por entender que el área de PDM, es un espacio interdisciplinario, bajo un concepto innovador, colaborativo e integral hacia todas las áreas que participan, no solo en la administración de los recursos necesarios para un proyecto sino además, en el diseño o desarrollo del mismo. Los artículos incluidos en esta revista se publican en español, portugués e inglés, atendiendo de esta manera a un espacio internacional y multicultural que permita una gestión del conocimiento actual, propia y necesaria del área PDM. metadata Multi-Lingual Scientific Journals, (MLS) mail mls@devnull.funiber.org (2019) Project Design and Management. [Revista]

Other Subjects > Engineering Europe University of Atlantic > Research > Software Cerrado Español El ahogamiento es una de las principales causas de muerte en el mundo, alrededor de 372.000 personas al año, siendo una cifra que se considera subestimada (OMS, 2014). En consecuencia, existe la necesidad de mejorar esta situación considerada de salud pública. El objetivo del proyecto SOSeas es el desarrollo de una herramienta de evaluación para predecir el riesgo dinámico de los ahogamientos en las playas. En los espacios acuáticos recreativos se espera que una herramienta informática pueda mejorar la gestión de la seguridad por parte de los socorristas y también la información de riesgo de ahogamiento para los bañistas. Este proyecto es una continuidad del trabajo realizado en PreventSOS. En aquel caso el foco era el desarrollo de un sistema experto para la identificación, análisis y gestión del riesgo en espacios acuáticos y el diseño de una aplicación web para el registro de incidentes y accidentes. SOSeas pretende mejorar el servicio anterior integrando el sistema de información que provee el Copernicus Marine Environment Monitoring Service (CMEMS) en todo el mundo. Se pretende conseguir suficientes datos para poder nutrir a un sistema basado en técnicas de aprendizaje-máquina. La herramienta SOSeas se desarrolla para dos tipos de usuarios : gestores de playas/socorristas y usuarios recreativos (nadadores, navegantes, surfistas...). Estos usuarios podrán acceder a las condiciones meteorológicas y oceanográficas así como a información a medida sobre las amenazas de estos entornos siempre cambiantes. metadata CITICAN-Universidad Europea del Atlántico, mail UNSPECIFIED (2019) SOSeas: An assessment tool for predicting the dynamic risk of drowning on beaches. Repositorio de la Universidad. (Unpublished)

2018

Other Subjects > Engineering Europe University of Atlantic > Research > Projects I+D+I Cerrado Español El proyecto de desarrollo de competencias transversales a través de plataformas y medios digitales que se propone, se orienta al desarrollo de competencias personales de carácter transversal aprovechando las posibilidades que ofrecen las plataformas y medios digitales. El objetivo principal es el desarrollo de técnicas de simulación que se puedan aplicar en un entorno virtual de colaboración/aprendizaje. Las características del proyecto son las siguientes: (1) el desarrollo de unas nuevas técnicas a partir de un diseño experimental de técnicas de simulación en plataformas digitales; (2) el enfoque de la propuesta en competencias transversales para el uso de las plataformas digitales; (3) la contextualización del método de simulación en plataformas digitales para el desarrollo de competencias transversales (asimilar este método críticamente, y generar unas técnicas validadas en entornos virtuales). Las características más innovadoras que comprenderá la presente actividad tanto para nuestra entidad como en el ámbito científico-técnico son las siguientes: Generación de nuevas técnicas para el desarrollo de competencias transversales en plataformas digitales. Análisis en competencias transversales. metadata CITICAN-Universidad Europea del Atlántico, mail UNSPECIFIED (2018) Desarrollo de competencias personales de carácter transversal - TRANS COMP. Repositorio de la Universidad. (Unpublished)

Other Subjects > Engineering Europe University of Atlantic > Research > Projects I+D+I Cerrado Español Nuestra propuesta se orienta a diseñar un sistema experimental para la creación, a partir del lactosuero residual de quesería, de dos hidrogeles respetuosos con el medio ambiente que sirvan a la industria agrícola para el ahorro de insumos de producción (agua y fertilizantes) y, adicionalmente, eviten la contaminación de suelos y aguas subterráneas que causa el residuo original. Para alcanzar dicha meta deberemos asumir: Objetivo específico 1: evaluar distintos agentes de formación de hidrogel que sean ambientalmente sostenibles y compatibles con las características del lactosuero residual. Objetivo específico 2: diseñar un proceso de producción de un hidrogel medioambientalmente sostenible a partir del lactosuero residual destinado a medio de germinación de semillas de plantas hortícolas en semillero y determinar las condiciones donde la extracción de minerales sea óptima sin producción de fisiopatías en las plántulas y se consiga una máxima depuración del lactosuero usado para su fabricación. Objetivo específico 3: diseñar un proceso de producción de un hidrogel medioambientalmente sostenible a partir del lactosuero residual destinado a medio de cultivo de plantas in situ y determinar la dosis de aplicación para que el hidrogel permanezca más tiempo en la rizosfera y la planta no muestre síntomas de deficiencia hídrica ni nutricional, sin que se produzca lixiviación a capas inferiores.“ metadata CITICAN-Universidad Europea del Atlántico, and UNEATLANTICO, mail UNSPECIFIED (2018) HIDROGEL: Desarrollo de tecnologías para la reutilización sostenible del lactosuero. Repositorio de la Universidad. (Unpublished)

2017

Thesis Subjects > Engineering Europe University of Atlantic > Teaching > Final Master Projects Cerrado Español Se establecen los requisitos de diseño y gestión de la construcción de parques eólicos en Bolivia desde un punto de vista meramente técnico, con el análisis del potencial eólico del emplazamiento, las obras civiles, la red eléctrica y su interconexión al sistema de potencia, describiendo indicadores clave para el diseño, selección, dimensionamiento de los equipos y procedimientos de gestión de las pruebas a realizar durante su construcción metadata Dorado Galatoire, Erick Andrés mail doradogalatoire@gmail.com (2017) Diseño y Gestión de la Construcción e Interconexión al SIN de un Parque Eólico en Bolivia. Masters thesis, FUNIBER - Universidad Europea del Atlántico.

Other Subjects > Engineering
Subjects > Nutrition Europe University of Atlantic > Research > Projects I+D+I Cerrado Español El objetivo del proyecto es diseñar una metodología para la realización de estudios epidemiológicos en nutrición basada en la gamificación y en el uso de nuevos sensores físicos. La tecnología resultante permite obtener el patrón de consumo nutricional del usuario que utiliza el sistema de una forma atractiva e integrada en sus hábitos de consumo y que requiere poco esfuerzo para el mismo con el objeto de obtener una información fiable y simplificada de la realización de registros dietéticos. De esta forma se obtienen datos útiles para realizar estudios epidemiológicos a nivel nutricional de los usuarios que utilicen el sistema. Los datos obtenidos serán de gran utilidad para poder aplicarlos en numerosos estudios epidemiológicos que se pueden realizar al tener acceso continuo a información nutricional. La idea es poder dirigir los estudios epidemiológicos hacia la obtención de datos concretos sobre un determinado colectivo de la sociedad o patrón de consumo según la información que se crea de interés tanto para fines de investigación como para fines de salud o comerciales según cada caso. De esta forma, la aplicación de la herramienta se puede extender a numerosos entornos y mercados tanto nacionales como internacionales. Objetivo del Proyecto Diseñar una metodología para la realización de estudios epidemiológicos en nutrición basada en la gamificación. Financiación Este proyecto ha sido cofinanciado dentro del Programa INNOVA 2016 por el Fondo Europeo de Desarrollo Regional. Programa Operativo FEDER de Cantabria 2014-2020. “Una manera de hacer Europa”. Objetivo del Proyecto Diseñar una metodología para la realización de estudios epidemiológicos en nutrición basada en la gamificación. Financiación Este proyecto ha sido cofinanciado dentro del Programa INNOVA 2016 por el Fondo Europeo de Desarrollo Regional. Programa Operativo FEDER de Cantabria 2014-2020. “Una manera de hacer Europa”. Inicio: 01/01/2017 Fin: 30/11/2018 Código Externo: 2016/INN/62 metadata CITICAN-Universidad Europea del Atlántico, and UNEATLANTICO, mail UNSPECIFIED (2017) Metodología de captura de información dietética para investigaciones epidemiológicas - DIETEPID. Repositorio de la Universidad. (Unpublished)

2016

Other Subjects > Engineering
Subjects > Nutrition Europe University of Atlantic > Research > Projects I+D+I Cerrado Español Realización de una cartografía de algas comestibles que aporten un beneficio nutricional en humanos. El desarrollo de este trabajo es de carácter meramente documental no siendo necesario en este punto ningún tipo de trabajo experimental, análisis sensorial, catas, etc. En concreto, la realización de la cartografía se basará en los siguientes aspectos: 1. Estudio de la cartografía de algas de Noja 2. Identificación de las algas comestibles capaces de proveer un aporte nutricional adecuado en humanos 3. Establecimiento de recomendaciones de consumo de las algas previamente identificadas 4. Recetario Objetivo del Proyecto: Estudio preliminar de la variedad de algas comestibles presentes en la franja costera de Noja, así como sus posibles usos en preparaciones culinarias. Financiación: Investigación contractual realizada por empresa privada Inicio: 11/05/2016 Fin 08/06/2016 metadata CITICAN-Universidad Europea del Atlántico, mail UNSPECIFIED (2016) Identificación de algas comestibles presentes en la franja costera de Noja. Repositorio de la Universidad. (Unpublished)

Other Subjects > Biomedicine
Subjects > Engineering
Subjects > Nutrition Europe University of Atlantic > Research > Projects I+D+I Cerrado Español En el mundo, algunas de las principales enfermedades no transmisibles se producen principalmente por hipertensión arterial, sobrepeso/obesidad e hiperglucemia. El proyecto pretende desarrollar la tecnología digital necesaria para mejorar sensiblemente el seguimiento de los tratamientos dietéticos analizando, comparando y clasificando perfiles de individuos obtenidos a partir de datos digitales correspondientes a personas que incluyen rasgos de la personalidad e informaciones que evolucionan en el tiempo. La tecnología clave a desarrollar debe permitir obtener perfiles característicos de los individuos (pacientes), analizarlos comparativamente y visualmente, y clasificarlos con objeto a poder lanzar actuaciones personalizadas, principalmente por mensajería, y realizar una evaluación posterior sobre la eficacia de las actuaciones promovidas por el sistema hacia dichos individuos. Estratégicamente, CITICAN pretende contar con tecnologías propias de análisis de perfiles de individuos que tienen aplicación potencial en otros campos como la formación online o el desarrollo de servicios digitales personalizados. Objetivo del Proyecto: Desarrollar la tecnología digital necesaria para mejorar sensiblemente el seguimiento de los tratamientos dietéticos analizando, comparando y clasificando perfiles de individuos obtenidos a partir de datos digitales correspondientes a personas que incluyen rasgos de la personalidad e informaciones que evolucionan en el tiempo. Financiación Este proyecto ha sido cofinanciado por la Sociedad de Desarrollo Regional de Cantabria (SODERCAN) y el el Programa Operativo FEDER de Cantabria en el marco del programa denominado I+C= +C 2016 (Investigación + Conocimiento= +Cantabria) que tiene por objetivo el fortalecimiento del tejido industrial de la región. Inicio: 01/09/2016 Fin: 31/08/2018 Código Externo: BI16-IN-005 metadata CITICAN-Universidad Europea del Atlántico, and UNEATLANTICO, mail UNSPECIFIED (2016) NUTRIX: Desarrollo de tecnologías para el análisis de pacientes en tratamientos dietéticos mediante sistemas expertos y redes neuronales. Repositorio de la Universidad. (Unpublished)

Other Subjects > Engineering Europe University of Atlantic > Research > Software Cerrado Español Como resultado del proyecto “Nuevos mecanismos para conocer el riesgo de lesión en el deporte en diferentes tramos de la temporada deportiva” se ha generado una herramienta digital que permite llevar el control de las lesiones de cada deportista, así como sus constantes biomecánicas, hábitos de alimentación y estado de salud emocional de tal forma que, se cuenta con información que combina varios factores a un nivel de detalle importante y de modo personalizado para cada jugador. De este modo, se obtienen los inputs para generar el análisis estadístico que alerta sobre las probabilidades de sufrir determinada lesión. Objetivo del Proyecto: Desarrollar una herramienta que permita identificar el riesgo de lesión de un deportista, independientemente del nivel o categoría del mismo, y poder actuar en consecuencia de manera individualizada, según el período de la temporada en el que se encuentre. Financiación: Este proyecto ha sido cofinanciado por la Sociedad de Desarrollo Regional de Cantabria (SODERCAN) y el el Programa Operativo FEDER de Cantabria en el marco del programa denominado I+C= +C 2016 (Investigación + Conocimiento= +Cantabria) que tiene por objetivo el fortalecimiento del tejido industrial de la región. Inicio: 15/12/2016 Fin: 14/12/2018 Código Externo: ID16-IN-022 metadata REND & PREV, and CITICAN-Universidad Europea del Atlántico, and UNEATLANTICO, mail UNSPECIFIED (2016) Nuevos mecanismos para conocer el riesgo de lesión en el deporte en diferentes tramos de la temporada deportiva. R&P (Recovery and Performance). Repositorio de la Universidad. (Unpublished)

Other Subjects > Engineering Europe University of Atlantic > Research > Software Cerrado Español El proyecto se centra en el desarrollo de tecnologías para la identificación de riesgos en espacios acuáticos naturales. A partir del conocimiento que se pretende generar, la entidad espera comercializar servicios de soporte para la gestión de riesgos, la acción preventiva y comunicación de emergencias. La propuesta se orienta a crear un sistema experto en la gestión de riesgos en espacios acuáticos naturales (playas), basado por un lado en una aplicación para la evaluación de riesgos, y por otro, en un sistema de registro y análisis de sucesos y accidentes. Esta herramienta debe permitir a los responsables de la gestión de la seguridad en zonas de baño una gestión adecuada y eficaz de los recursos preventivos para minimizar la probabilidad y severidad de riesgos que puedan afectar a la integridad física o a la salud de las personas, y en consecuencia, el aumento de la seguridad acuática en las costas. Objetivo del Proyecto: Desarrollar tecnologías para la identificación de riesgos en espacios acuáticos naturales con el objeto de prevenir ahogamientos y otros incidentes en zonas de playa. Financiación: Este proyecto ha sido cofinanciado por la Sociedad de Desarrollo Regional de Cantabria (SODERCAN) y el el Programa Operativo FEDER de Cantabria en el marco del programa denominado I+C= +C 2016 (Investigación + Conocimiento= +Cantabria) que tiene por objetivo el fortalecimiento del tejido industrial de la región. Inicio: 09/12/2016 Fin: 08/12/2018 Código Externo: ID16-IN-038 metadata CITICAN-Universidad Europea del Atlántico, and UNEATLANTICO, mail UNSPECIFIED (2016) PREVENT-SOS: Desarrollo de tecnologías para la identificación de riesgos en espacios acuáticos naturales. Repositorio de la Universidad. (Unpublished)

Other Subjects > Engineering
Subjects > Teaching Europe University of Atlantic > Research > Software Cerrado Español A pesar del gran incremento de la práctica deportiva en la sociedad occidental en los últimos años, aún hay, según fuentes de la UE, aproximadamente un 50% de la población europea que no hace ejercicio regularmente, lo que está generando un grave problema de salud, especialmente preocupante en la población infantil y juvenil. Del 50% de la población que hace deporte de forma regular, un porcentaje muy alto lo hace solo, en casa o en lugares abiertos públicos sin ninguna supervisión o control por parte de personal especializado, lo que conlleva un cierto riesgo de sufrir lesiones y/o patologías de diferente pronósticos. Ante esta situación compleja de tener la necesidad de promover la actividad física pero intentando aminorar el riesgo de la propia práctica, se propone el desarrollo de una aplicación móvil “freemium” que fomente el ejercicio y que integre una serie de tecnologías innovadoras para incorporar inteligencia artificial que aplicará sobre unos elementos de alerta que puedan generar avisos y geolocalizar al practicante de una forma rápida y eficaz. Entendemos que el desarrollo de este tipo de negocios de carácter tecnológico y de alto grado de responsabilidad social hacia la ciudadanía incrementará el tejido empresarial de Cantabria y generará nuevos puestos de trabajo estables y de alto nivel de formación. Las sinergias que se proponen con instituciones universitarias y de investigación fomentarán los ecosistemas profesionales relacionados con las nuevas tecnologías de la información, la salud y la seguridad. El objetivo de este sistema complejo que se propone es promover la actividad física segura de forma global. metadata IVITALIA, and UNEATLANTICO, mail UNSPECIFIED (2016) SMART ACTIVE LIFE: Desarrollo de tecnologías inteligentes para la promoción de la vida activa y segura. Repositorio de la Universidad. (Unpublished)

Other Subjects > Engineering
Subjects > Nutrition Europe University of Atlantic > Research > Projects I+D+I Cerrado Español El Sobao Pasiego es un producto típico de la comarca pasiega. Los factores humanos son los que han contribuido a lo largo de los años a dar notoriedad al producto, una reputación que se ha ido generando y transmitiendo de generación en generación, un saber hacer que, por tanto, pertenece al patrimonio de la comarca pasiega y de ahí que el producto lleve y se reconozca por su nombre. En este sentido, Joselín Sobaos Pasiegos y Quesadas - como una empresa que apuesta por la innovación, pero manteniendo la tradición que les ha mantenido como referencia en el mercado de productos regionales de Cantabria desde 1948 - quiere fundir su filosofía de mantener la misma pureza de los ingredientes y la misma fórmula tradicional de fabricación de sus productos con las mejoras que puedan provenir de la transferencia de tecnología y de conocimientos de especialistas conocedores de los procesos que implica la elaboración de un sobao, pero desde una perspectiva científica a fin de lograr una mejora en un producto que, en sí mismo, ya ha demostrado tener una calidad excelente. Para ello, se pretende estudiar la viabilidad de generar un auténtico sobao pasiego de calidad suprema (“sobao premium”) respetando, tanto el modo de elaboración, como la receta tradicional. Objetivo del Proyecto: Estudiar la viabilidad de generar un auténtico sobao pasiego de calidad suprema (“sobao premium”) respetando, tanto el modo de elaboración, como la receta tradicional. Financiación: Este proyecto ha sido cofinanciado por la Sociedad de Desarrollo Regional de Cantabria (SODERCAN) y el el Programa Operativo FEDER de Cantabria en el marco del programa denominado I+C= +C 2016 (Investigación + Conocimiento= +Cantabria) que tiene por objetivo el fortalecimiento del tejido industrial de la región. Inicio: 11/11/2016 Fin: 10/11/2017 Código Externo: TF16-XX-006 metadata UNEATLANTICO, and CITICAN-Universidad Europea del Atlántico, and Sobaos Joselín, mail UNSPECIFIED (2016) SOBAO PREMIUM: Estudio de viabilidad para el desarrollo de un auténtico sobao pasiego de calidad suprema con base en la receta y el modo de elaboración tradicionales. Repositorio de la Universidad. (Unpublished)

Other Subjects > Engineering
Subjects > Nutrition Europe University of Atlantic > Research > Projects I+D+I Cerrado Español El objetivo de PEPANPI es el de poder ofrecer el primer servicio de mejora avanzada de productos alimentarios a partir del cual se puedan mejorar cuatro aspectos fundamentales del alimento: calidad nutricional, organoléptica, sanitaria y comercial. En particular, se aborda el desarrollo de alimentos de segunda generación en el ámbito de harinas y derivados. Para ello la empresa solicita la colaboración de la Universidad Europea del Atlántico dada su especialización en los ámbitos de la agroalimentación y de la nutrición humana. Objetivo del Proyecto: Desarrollo de alimentos de segunda generación en el ámbito de harinas y derivados. Financiación: Este proyecto ha sido cofinanciado por la Sociedad de Desarrollo Regional de Cantabria (SODERCAN) y el el Programa Operativo FEDER de Cantabria en el marco del programa denominado I+C= +C 2016 (Investigación + Conocimiento= +Cantabria) que tiene por objetivo el fortalecimiento del tejido industrial de la región. Inicio: 18/11/2016 Fin: 17/11/2018 metadata CITICAN-Universidad Europea del Atlántico, mail UNSPECIFIED (2016) Servicio para el diseño de alimentos funcionales de segunda generación: aplicaciones a la industria agroalimentaria - ALIMENT2.0. Repositorio de la Universidad. (Unpublished)

Other Subjects > Engineering
Subjects > Nutrition Europe University of Atlantic > Research > Projects I+D+I Cerrado Español Objetivo del Proyecto: Desarrollar un nuevo negocio y plan de explotación del suero de queso Picón en Cantabria a través de la comercialización de nuevos productos elaborados a partir de éste. Financiación: Este proyecto ha sido cofinanciado por la Sociedad de Desarrollo Regional de Cantabria (SODERCAN) y el el Programa Operativo FEDER de Cantabria en el marco del programa denominado I+C= +C 2016 (Investigación + Conocimiento= +Cantabria) que tiene por objetivo el fortalecimiento del tejido industrial de la región. Inicio 01/09/2016 Fin 31/08/2018 Código Externo BI16-IN-010 Categoría Alimentación Entidad Financiadora Sociedad para el Desarrollo de Cantabria metadata Probocado S.L., and CITICAN-Universidad Europea del Atlántico, mail UNSPECIFIED (2016) Valorización del subproducto lácteo suero de queso Picón para la producción de productos de valor añadido. Repositorio de la Universidad. (Unpublished)

2014

Other Subjects > Engineering
Subjects > Nutrition Europe University of Atlantic > Research > Projects I+D+I Cerrado Español El objetivo de este proyecto es la creación de una nueva unidad de investigación en tecnologías alimentarias y nutrición en el centro privado de I+D CITICAN. Para alcanzar este objetivo general, la actuación contempla la contratación de personal investigador y la adquisición de equipamiento científico para dotar dos laboratorios, uno de bromatología y otro de microbiología. Estas instalaciones se ubican en el Parque Científico-Tecnológico de Cantabria en las instalaciones de la Universidad Europea del Atlántico (entidad promotora y patrona de la Fundación CITICAN). Estos recursos permitirán a CITICAN posicionarse como una entidad de referencia en el campo de la investigación alimentaria y el apoyo a las industrias productoras de alimentos. En concreto: Dotar a CITICAN de un laboratorio de última generación para la realización de actividades de I+D relacionadas con las tecnologías de la alimentación y la nutrición humana. Contar con un equipo humano capaz de generar conocimiento así como de aplicarlo y transferirlo al sector industrial y a los consumidores. Posibilitar el desarrollo de líneas de investigación de interés para las industrias alimentarias y para el consumidor. Ofrecer servicios de investigación contractual en materia de investigación, desarrollo y análisis de alimentos y sus procesos de producción. Objetivo del Proyecto: Crear una nueva unidad de investigación en tecnologías alimentarias y nutrición en CITICAN. Para alcanzar este objetivo general, la actuación contempló la contratación de personal investigador y la adquisición de equipamiento científico para dotar dos laboratorios, uno de bromatología y otro de microbiología. Financiación: Este proyecto ha sido cofinanciado dentro del Programa INNPULSA Cantabria 2014 – Línea INNOVA por el Fondo Europeo de Desarrollo Regional. Programa Operativo FEDER de Cantabria 2014-2020. “Una manera de hacer Europa”. Inicio: 01/09/2014 Fin: 16/06/2016 Código Externo: 2014/INN/037 metadata CITICAN-Universidad Europea del Atlántico, mail UNSPECIFIED (2014) Creación de la unidad de investigación en tecnologías alimentarias y nutrición en el Centro de Investigación y Tecnología Industrial de Cantabria - CITICAN. Repositorio de la Universidad. (Unpublished)

2013

Other Subjects > Social Sciences
Subjects > Engineering Europe University of Atlantic > Research > Scientific Production Cerrado Inglés Este proyecto se centra en contribuir a desarrollar las habilidades sociales emprendedoras y empresariales, con el propósito de mejorar las perspectivas de empleabilidad de adultos desempleados o empleados que quieren emprender sus propios negocios o mejorar su rendimiento en el trabajo. Se busca aprovechar el potencial empresarial de las personas con una sólida experiencia laboral, desarrollando su confianza y sus habilidades para lograr sus ambiciones, en el contexto del trabajo por cuenta propia y la creación de nuevas empresas en toda Europa. La herramienta digital se basa en el reconocido sistema psicométrico de prueba de comportamiento en el trabajo (DISC), validada por la Universidad de Cambridge metadata UNSPECIFIED mail UNSPECIFIED (2013) DAISS2: Diagnostics for enterprise soft skills. Repositorio de la Universidad.

Other Subjects > Engineering Europe University of Atlantic > Research > Projects I+D+I Cerrado Inglés La fase operacional de los edificios representa el 80% del ciclo de vida de un edificio, del cual el 50% es consecuencia del uso energético. Este proyecto desarrolla un enfoque integrado de control y operación, que combina las técnicas actuales con el desarrollo de una innovadora técnica de control basada en la simulación, para así automatizar la generación de planes operativos óptimos adaptados a los edificios y las necesidades de los usuarios. El proyecto tiene por objetivo reducir el consumo de energía y el coste operacional de los edificios, empleando técnicas novedosas basadas en la predicción de las condiciones de confortabilidad en interiores y el comportamiento de los usuarios. El proyecto es coordinado por Acciona y participan otros 12 socios entre empresas, centros tecnológicos y universidades de España, Irlanda, Francia, Finlandia, Italia, Portugal , Reino Unido y Rumanía. metadata UNSPECIFIED mail UNSPECIFIED (2013) ENERGY IN TIME: Intelligent control and simulation system in buildings. Repositorio de la Universidad.

This list was generated on Sun Sep 24 23:42:04 2023 UTC.

Effects of enzymatic treatment on the in vitro digestion and fermentation patterns of mulberry fruit juice: A focus on carbohydrates

The aim of this study was to investigate the effects of enzymatic treatments (pectinase, pectin lyase, and cellulase) on the in vitro digestion and fermentation characteristics of whole mulberry fruit juice. The analysis focused on changes in carbohydrate properties within the black mulberry fruit matrix during simulated digestion and fermentation. Human fecal microbiota were collected and introduced to the fruit matrix to monitor the fate of both soluble and insoluble polysaccharides during fermentation. The results revealed that enzymatic treatments enhanced the solubilization of carbohydrates from mulberry fruits, with pectinase showing the most significant effect. Throughout the process of in vitro digestion, there was a gradual increase in the percentage of solubilized carbohydrates from the mulberry juice substrate. The digested suspensions underwent dialysis to remove degradation fragments, and a lower quantity of carbohydrate in the enzyme-treated groups compared to the control. Polysaccharide populations with varying molecular weights (Mw) were obtained from the soluble fractions of mulberry residues for subsequent fermentation. An increase in Mw of soluble polysaccharides was detected by HPSEC during fermentation in certain cases. The gut microbiota demonstrated the ability to convert specific insoluble fractions into soluble components, which were subsequently subjected to microbial utilization. Enzymatic treatments during mulberry juice preparation can potentially positively impact health by influencing gut microbiota and short-chain fatty acid (SCFA) modulations. Enzymes could serve as valuable tools for producing functional fruit and vegetable juices, with the need to specify processing conditions for specific raw materials remaining a subject of further investigation.

Producción Científica

Peihuan Luo mail , Jian Ai mail , Yuxin Wang mail , Songen Wang mail , Henk A. Schols mail , Hauke Smidt mail , Maurizio Battino mail maurizio.battino@uneatlantico.es, Weibin Bai mail , Lingmin Tian mail ,

Luo

Can the phenolic compounds of Manuka honey chemosensitize colon cancer stem cells? A deep insight into the effect on chemoresistance and self-renewal

Manuka honey, which is rich in pinocembrin, quercetin, naringenin, salicylic, p-coumaric, ferulic, syringic and 3,4-dihydroxybenzoic acids, has been shown to have pleiotropic effects against colon cancer cells. In this study, potential chemosensitizing effects of Manuka honey against 5-Fluorouracil were investigated in colonspheres enriched with cancer stem cells (CSCs), which are responsible for chemoresistance. Results showed that 5-Fluorouracil increased when it was combined with Manuka honey by downregulating the gene expression of both ATP-binding cassette sub-family G member 2, an efflux pump and thymidylate synthase, the main target of 5-Fluorouracil which regulates the ex novo DNA synthesis. Manuka honey was associated with decreased self-renewal ability by CSCs, regulating expression of several genes in Wnt/β-catenin, Hedgehog and Notch pathways. This preliminary study opens new areas of research into the effects of natural compounds in combination with pharmaceuticals and, potentially, increase efficacy or reduce adverse effects.

Producción Científica

Danila Cianciosi mail , Yasmany Armas Diaz mail , José M. Alvarez-Suarez mail , Xiumin Chen mail , Di Zhang mail , Nohora Milena Martínez López mail nohora.martinez@uneatlantico.es, Mercedes Briones Urbano mail mercedes.briones@uneatlantico.es, José L. Quiles mail jose.quiles@uneatlantico.es, Adolfo Amici mail , Maurizio Battino mail maurizio.battino@uneatlantico.es, Francesca Giampieri mail francesca.giampieri@uneatlantico.es,

Cianciosi

An Optimized Privacy Information Exchange Schema for Explainable AI Empowered WiMAX-based IoT networks

The Internet of Things (IoT) has recently surpassed wired communication. WiMAX is a wireless transmission technology that allows for faster internet access. Wireless network innovations, like some other communication networks, are not safe and secure. Security and authorization models are intended to prevent unauthorized use of network services. Numerous authorization and encrypted communication mechanisms have been introduced for WiMAX privacy, but the communication systems are still insecure and vulnerable to attacks such as zero-day attacks, rouge base station attacks, Man in the Middle (MITM) attacks, and Denial of Service (DoS) attacks. Wireless technologies have come a long way in the last few decades. Because most wireless transmission systems rely on radio signals, the system channel is essentially vulnerable to interception. As a result, data security is always critical in the presentation of a system. Because WiMAX is a wireless communication technology, it is particularly vulnerable to interception, so security is a top priority. Individuals must be protected from security breaches that occur across network interfaces, networking devices, and everything in between. Robust security management is required to protect WiMAX from attacks and vulnerabilities, despite the fact that emerging Artificial Intelligence (AI) technologies necessitate different security governance than existing technologies. We proposed an Optimized Privacy Information Exchange Schema for Explainable AI Empowered WiMAX-based IoT that addresses vulnerabilities and threats during the identification and authorization phases to improve the functionality and performance characteristics of the traditional system. The Scyther tool was used to validate the proposed privacy scheme, which is safer and more secure than existing systems.

Producción Científica

Premkumar Chithaluru mail , Aman Singh mail aman.singh@uneatlantico.es, Jagjit Singh Dhatterwal mail , Ali Hassan Sodhro mail , Marwan Ali Albahar mail , Anca Jurcut mail , Ahmed Alkhayyat mail ,

Chithaluru

open

Voxel Extraction and Multiclass Classification of Identified Brain Regions across Various Stages of Alzheimer’s Disease Using Machine Learning Approaches

This study sought to investigate how different brain regions are affected by Alzheimer’s disease (AD) at various phases of the disease, using independent component analysis (ICA). The study examines six regions in the mild cognitive impairment (MCI) stage, four in the early stage of Alzheimer’s disease (AD), six in the moderate stage, and six in the severe stage. The precuneus, cuneus, middle frontal gyri, calcarine cortex, superior medial frontal gyri, and superior frontal gyri were the areas impacted at all phases. A general linear model (GLM) is used to extract the voxels of the previously mentioned regions. The resting fMRI data for 18 AD patients who had advanced from MCI to stage 3 of the disease were obtained from the ADNI public source database. The subjects include eight women and ten men. The voxel dataset is used to train and test ten machine learning algorithms to categorize the MCI, mild, moderate, and severe stages of Alzheimer’s disease. The accuracy, recall, precision, and F1 score were used as conventional scoring measures to evaluate the classification outcomes. AdaBoost fared better than the other algorithms and obtained a phenomenal accuracy of 98.61%, precision of 99.00%, and recall and F1 scores of 98.00% each.

Producción Científica

Samra Shahzadi mail , Naveed Anwer Butt mail , Muhammad Usman Sana mail , Iñaki Elío Pascual mail inaki.elio@uneatlantico.es, Mercedes Briones Urbano mail mercedes.briones@uneatlantico.es, Isabel de la Torre Díez mail , Imran Ashraf mail ,

Shahzadi

open

Adaptive Filtering: Issues, Challenges, and Best-Fit Solutions Using Particle Swarm Optimization Variants

Adaptive equalization is crucial in mitigating distortions and compensating for frequency response variations in communication systems. It aims to enhance signal quality by adjusting the characteristics of the received signal. Particle swarm optimization (PSO) algorithms have shown promise in optimizing the tap weights of the equalizer. However, there is a need to enhance the optimization capabilities of PSO further to improve the equalization performance. This paper provides a comprehensive study of the issues and challenges of adaptive filtering by comparing different variants of PSO and analyzing the performance by combining PSO with other optimization algorithms to achieve better convergence, accuracy, and adaptability. Traditional PSO algorithms often suffer from high computational complexity and slow convergence rates, limiting their effectiveness in solving complex optimization problems. To address these limitations, this paper proposes a set of techniques aimed at reducing the complexity and accelerating the convergence of PSO.

Producción Científica

Arooj Khan mail , Imran Shafi mail , Sajid Gul Khawaja mail , Isabel de la Torre Díez mail , Miguel Ángel López Flores mail miguelangel.lopez@uneatlantico.es, Juan Castanedo Galán mail juan.castanedo@uneatlantico.es, Imran Ashraf mail ,

Khan

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