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Digital Service Quality from Elderly Generation Perspective to Improve Online Business and Economy: A Theoretical Framework 1

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6th World Conference on Smart Trends in Systems, Security and Sustainability, WS4 2022

作者： Yahaya, Jamaiah Deraman, Aziz Jusoh, Yusmadi Yah Kumar, Sathya Nantha Faculty of Information Science and Technology Universiti Kebangsaan Malaysia Bangi Malaysia Faculty of Ocean Engineering Technology and Informatics Universiti Malaysia Terengganu Terengganu Kuala Terengganu Malaysia Faculty of Computer Science & Information Technology Universiti Putra Malaysia Seri Kembangan Malaysia

ISBN: (数字)9789811976605

ISBN: (纸本)9789811976599

During the current COVID-19 pandemic, older people are encouraged to use information, communication and technology in their everyday lives and discouraged from physical interactions. In Malaysia, it shows that implementing the Movement Control Order (MCO) to control the spread of the COVID-19 pandemic saw a shift in consumer trends, prompting businesses to explore new strategies to interact with consumers. But there is no study indicating the contributions of older people in this new business environment. Several complaints were reported regarding the usability, acceptability, and suitability of these applications for the elderly. The objectives of this study: (1) to investigate issues and challenges on older citizens in current software design quality;(2) To identify current practises on software usage amongst the older citizens, especially in e-commerce and e-business applications;and (3) To propose a model a software design quality that meets older people requirements, limitations, and expectations. The new model helps the developers design and construct software compatible with the elderly based on a quality perspective. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Digital service quality Elderly software quality model Older generation Theoretical framework

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Assessing Biological Responses of Saccharomyces Cerevisiae to Low-Frequency Electromagnetic Fields: Insights and Implications 15

Assessing Biological Responses of Saccharomyces Cerevisiae t...

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15th International Conference Elektro, ELEKTRO 2024

作者： Bajtos, Marek Radil, Roman Janousek, Ladislav Dang, Nhat University of Zilina Faculty of Electrical Engineering and Information Technology Department of Electromagnetic and Biomedical Engineering Zilina Slovakia University of Colorado Boulder Department of Electrical Computer and Energy Engineering BoulderCO United States

ISBN: (纸本)9798350372359

This study investigates the biological effects of Low-Frequency Electromagnetic Fields (LF-EMF) on Saccharomyces cerevisiae yeast cells, an essential model organism in biological research. To achieve controlled exposure, the exposure system ensuring uniform exposition while maintaining identical cultivation conditions for both exposed and control samples is used. To evaluate the impact of LF-EMF, yeast cell growth and proliferation were quantified using a Bürker chamber before and after exposure. Our findings reveal statistically significant differences between the exposed and control samples, suggesting a potential biological response to LF-EMF. The present research offers valuable insights into the effects of LF-EMF on biological cells, contributing to the broader understanding of electromagnetic field's impact on living organisms. Furthermore, the proposed exposure system provides a reliable platform for future bioelectromagnetic research, facilitating health risk assessments and investigations into the therapeutic potential of LF-EMF exposure. © 2024 IEEE.

关键词： Electromagnetic fields

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Challenges in Mobile Network Capacity Monitoring & Solutions to Improve Capacity Problems Using Various Parameters 4

Challenges in Mobile Network Capacity Monitoring & Solutions...

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4th International Conference on Technological Advancements in Computational Sciences, ICTACS 2024

作者： Gupta, Vikas Chakraverti, Ashish Kumar Kumar, Manoj School of Engineering and Technology Sharda University Department of Computer Science and Engineering Uttar Pradesh Greater Noida201310 India University of Wollongong Faculty of Engineering and Information Science Dubai United Arab Emirates

ISBN: (纸本)9798350387490

This paper has an overview on study of traffic capacity of Mobile network parameter that affect the network utilization and network experience in Mobile network era., This capacity study & analytics provide a conception of how the various networks function, capacity parameters & constraints of different domain of Mobile Network like RAN (Radio access Network),CN (Core Network), IP & TX (Internet Protocol & Transport Network) & their associated capacity parameter have correlations in network utilization. It also has the access of Mobile Network KPIs detail, for readers to easily retrieve a variety of capacity parameters for effective capacity management. In order to manage end to end capacity requirement in telecom domain & can help for solving capacity problem with the help of various network parameters. These various capacity parameters can be used to generate systematic, rule-based decision which are standardized, more flexible, and faster to take decision on capacity expansion well in advance through the parametric behaviour. furthermore, the review concludes the published work their gaps and future work in the direction of improving Mobile network capacity management. © 2024 IEEE.

关键词： Internet protocols

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Al-Biruni Earth Radius(BER)Metaheuristic Search Optimization Algorithm

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computer Systems Science & engineering 2023年第5期45卷 1917-1934页

作者： El-Sayed M.El-kenawy Abdelaziz A.Abdelhamid Abdelhameed Ibrahim Seyedali Mirjalili Nima Khodadad Mona A.Al duailij Amel Ali Alhussan Doaa Sami Khafaga Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Faculty of Artificial Intelligence Delta University for Science and TechnologyMansoura35712Egypt Department of Computer Science Faculty of Computer and Information SciencesAin Shams UniversityCairo11566Egypt Department of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt Centre for Artificial Intelligence Research and Optimization Torrens University AustraliaFortitude ValleyQLD 4006Australia Yonsei Frontier Lab Yonsei UniversitySeoul03722Korea Department of Civil and Environmental Engineering Florida International UniversityMiamiUSA Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia

Metaheuristic optimization algorithms present an effective method for solving several optimization problems from various types of applications and *** metaheuristics and evolutionary optimization algorithms have been emerged recently in the literature and gained widespread attention,such as particle swarm optimization(PSO),whale optimization algorithm(WOA),grey wolf optimization algorithm(GWO),genetic algorithm(GA),and gravitational search algorithm(GSA).According to the literature,no one metaheuristic optimization algorithm can handle all present optimization *** novel optimization methodologies are still *** Al-Biruni earth radius(BER)search optimization algorithm is proposed in this *** proposed algorithm was motivated by the behavior of swarm members in achieving their global *** search space around local solutions to be explored is determined by Al-Biruni earth radius calculation method.A comparative analysis with existing state-of-the-art optimization algorithms corroborated the findings of BER’s validation and testing against seven mathematical optimization *** results show that BER can both explore and avoid local *** has also been tested on an engineering design optimization *** results reveal that,in terms of performance and capability,BER outperforms the performance of state-of-the-art metaheuristic optimization algorithms.

关键词： Metaheuristics evolutionary optimization exploration exploitation mutation Al-biruni earth radius

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A Deep Learning Approach Towards Student Performance Prediction in Online Courses: Challenges Based on a Global Perspective 24

A Deep Learning Approach Towards Student Performance Predict...

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24th International Arab Conference on information technology, ACIT 2023

作者： Moubayed, Abdallah Injadat, MohammadNoor Alhindawi, Nouh Samara, Ghassan Abuasal, Sara Alazaidah, Raed School of Computing and Augmented Intelligence Arizona State University GilbertAZ United States Lebanese American University Electrical and Computer Engineering Department Byblos Lebanon Western University Electrical and Computer Engineering Department LondonON Canada Zarqa University Faculty of Information Technology Data Science and Artificial Intelligence Department Zarqa Jordan Jadara University Faculty of Science and Information Technology Irbid Jordan Zarqa University Faculty of Information Technology Computer Science Department Zarqa Jordan Zarqa University Faculty of Information Technology Software Engineering Department Zarqa Jordan

ISBN: (纸本)9798350384307

Analyzing and evaluating students' progress in any learning environment is stressful and time consuming if done using traditional analysis methods. This is further exasperated by the increasing number of students due to the shift of focus toward integrating the Internet technologies in education and the focus of academic institutions on moving toward e-Learning, blended, or online learning models. As a result, the topic of student performance prediction has become a vibrant research area in recent years. To address this, machine learning and data mining techniques have emerged as a viable solution. To that end, this work proposes the use of deep learning techniques (CNN and RNN-LSTM) to predict the students' performance at the midpoint stage of the online course delivery using three distinct datasets collected from three different regions of the world. Experimental results show that deep learning models have promising performance as they outperform other optimized traditional ML models in two of the three considered datasets while also having comparable performance for the third dataset. © 2023 IEEE.

关键词： Deep Learning e-Learning Online Courses Student Performance Prediction

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Hybrid Reptile-Snake Optimizer Based Channel Selection for Enhancing Alzheimer’s Disease Detection

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Journal of Bionic engineering 2025年第2期22卷 884-900页

作者： Digambar Puri Pramod Kachare Smith Khare Ibrahim Al-Shourbaji Abdoh Jabbari Abdalla Alameen Department of Electronics and Telecommunication Ramrao Adik Institute of TechnologyD.Y.Patil CampusNavi-MumbaiMaharashtra400706India Maersk Mc-Kinney Moller Institute Faculty of EngineeringUniversity of Southern DenmarkOdenseDenmark Department of Electrical and Electronics Engineering Jazan UniversityJazan45142Saudi Arabia Department of Computer Science University of HertfordshireHatfieldUK Department of Computer Engineering and Information College of Engineering in Wadi AlddawasirPrince Sattam Bin Abdulaziz UniversityWadi Alddawasir11991Saudi Arabia

The global incidence of Alzheimer's Disease(AD)is on a swift *** Electroencephalogram(EEG)signals is an effective tool for the identification of AD and its initial Mild Cognitive Impairment(MCI)stage using machine learning *** of AD using EEG involves multi-channel ***,the use of multiple channels may impact the classification performance due to data redundancy and *** this work,a hybrid EEG channel selection is proposed using a combination of Reptile Search Algorithm and Snake Optimizer(RSO)for AD and MCI detection based on decomposition *** Mode Decomposition(EMD),Low-Complexity Orthogonal Wavelet Filter Banks(LCOWFB),Variational Mode Decomposition,and discrete-wavelet transform decomposition techniques have been employed for subbands-based EEG *** extracted thirty-four features from each subband of EEG ***,a hybrid RSO optimizer is compared with five individual metaheuristic algorithms for effective channel *** effectiveness of this model is assessed by two publicly accessible AD EEG *** accuracy of 99.22% was achieved for binary classification from RSO with EMD using 4(out of 16)EEG ***,the RSO with LCOWFBs obtained 89.68%the average accuracy for three-class classification using 7(out of 19)*** performance reveals that RSO performs better than individual Metaheuristic algorithms with 60%fewer channels and improved accuracy of 4%than existing AD detection techniques.

关键词： Alzheimer's Disease Brain disorder Electroencephalogram Reptile Search Algorithm Snake Optimizer Optimization

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Explainable AI for Epileptic Seizure Prediction: A SHAPE and LIME Approach 25

Explainable AI for Epileptic Seizure Prediction: A SHAPE and...

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25th International Arab Conference on information technology, ACIT 2024

作者： Talukder, Md. Simul Hasan Mondal, Sohag Kumar Aditi, Oyshi Tabassum Aljaidi, Mohammad Sulaiman, Rejwan Bin Al-Qerem, Ahmad Dhaka University of Engineering & Technology Gazipur Bangladesh Khulna University of Engineering and Technology Khulna Bangladesh Daffodil International University Department of Computer Science and Engineering Savar Bangladesh Zarqa University Faculty of Information Technology Department of Computer Science Zarqa Jordan University of Business and Technology College of Engineering Jeddah21448 Saudi Arabia Northumbria University School of Computer Science & Technology Newcastle Tayne United Kingdom

ISBN: (纸本)9798331540012

Epilepsy is a neurological chaos typified by frequent, spontaneous seizures. Early recognition of epilepsy by utilising AI techniques to scan EEG signals can enhance the prevention and management of it. This study aims to improve the classification of epileptic seizures by using the preprocessed version of the Epileptic Seizure (ERS) dataset. The preprocessed dataset is subjected to multiple stages in order to improve its quality and achieve balanced class representation. Data cleaning, outlier management, merging, and oversampling are those. After that, an 80:20 split of the dataset is made into subsets for testing and training. Next, training, testing, and evaluation are performed on the models of Gradient Boosting Classifier (GBC), Decision Tree Classifier (DTC), Random Forest Classifier (RFC), CatBoost Classifier (CBC), and ExtraTree Classifier (ETC). The ExtraTree Classifier is remarkably accurate, with a 99.51% accuracy rate, which is the highest accuracy. Finally, explainable artificial intelligence (SHAP and LIME) is used to clarify the ExtraTree Classifier's decision-making procedure. By providing a visual representation of significant variables and their influence on the model's predictions, this interpretability tool improves comprehension of the classification results. © 2024 IEEE.

关键词： Neurology

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Early Detection of Down Syndrome Through Ultrasound Imaging Using Deep Learning Strategies - A Review 2

Early Detection of Down Syndrome Through Ultrasound Imaging ...

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2nd International Conference on Emerging Trends in information technology and engineering, ic-ETITE 2024

作者： Vidhyasagar, B.S. Madamanchi, Sree Chandana Kalimuthu, Sivakumar Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Chennai India Build Environment and Information Technology SEGi University Damansara Faculty of Engineering Kuala Lumpur Malaysia

ISBN: (纸本)9798350328202

Another name for Down syndrome is Trisomy 21, which is a complex chromosomal disorder that poses a substantial challenge in prenatal care due to its widespread prevalence. An additional copy of chromosome 21 is the defining feature of this disorder, leading to numerous physical and cognitive impairments. Typical physical traits of Down syndrome include a flattened facial structure, most notably in the nose bridge region, as well as upward-slanted almond-shaped eyes and a shortened neck. Apart from these features, individuals with Down syndrome also experience a range of intellectual disabilities, spanning from mild to severe. These challenges manifest in various areas, such as expressive communication, verbal memory, and attention. Furthermore, children with this disorder may exhibit behavioral issues that require special attention and care. Early and accurate detection of this condition is essential for informed decision-making by expectant parents. This review explores an overview of the data sets and results of recent studies that have used deep learning and machine learning methodologies to create effective models for the identification of Down syndrome. © 2024 IEEE.

关键词： Chromosomes

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Integrated Smart Patch for Heart Rate and Respiratory Rate Monitoring 14

Integrated Smart Patch for Heart Rate and Respiratory Rate M...

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14th International Conference on Measurement, MEASUREMENT 2023

作者： Gogola, Daniel Ackovska, Nevena Bagin, Richard Koteska, Bojana Bogdanova, Ana Madevska Kostoska, Magdalena Lehocki, Fedor Tysler, Milan Slovak Academy of Sciences Institute of Measurement Science Bratislava Slovakia Faculty of Computer Science and Engineering Skopje Macedonia Stu Faculty of Electrical Engineering and Information Technology Bratislava Slovakia

ISBN: (纸本)9788097262976

A wearable smart patch was designed to monitor the vital parameters of mass casualties' victims after the first triage. The device captures ECG, PPG, and respiration signals and triggers an alarm if the heart rate (HR) or respiration rate (RR) exceeds the specified limits and indicates a threat to the victim's life. To obtain a robust and reliable solution, the same parameters are derived from two or three independent signals. In this study, ECG signals have been recorded from different positions on the chest, and the performance of several algorithms for HR and RR extraction was tested. The initial measurements show that HR estimation is more accurate and reliable than RR estimation. The best results, considering both, the HR and RR calculations, were achieved when Pan-Tompkins's algorithm was used, and ECG electrodes were placed vertically on the right anterior chest. Increasing the length of the evaluated ECG signal above 30 seconds did not significantly affect the HR and RR calculation, regardless of the algorithm used. © 2023 Institute of Measurement Science, Slovak Academy o.

关键词： Electrocardiograms

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CloudyPages: A Secure and Scalable Serverless Web-Based Blogging Application 1

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2nd International Conference on Advances in Data-driven Computing and Intelligent Systems, ADCIS 2023

作者： Prakash, Vijay Jaiswal, Shrestha Purohit, Saumya Singh, Pardeep Garg, Lalit School of Computer Science University of Petroleum and Energy Studies Dehradun India Department of Computer Science and Engineering Graphic Era Hill University Dehradun India Department of Computer Information Systems Faculty of Information and Communication Technology University of Malta MsidaMSD 2080 Malta

ISBN: (数字)9789819995318

ISBN: (纸本)9789819995301

The CloudyPages app is a precise and trustworthy platform for bloggers to create and effectively manage blogs. The CloudyPages application provides bloggers a platform for creating and managing their blogs. The application can achieve remarkable accuracy, precision, and review rates by utilizing AWS services, assuring minimal errors and enhancing the discoverability and accessibility of bloggers’ content. Collectively, these metrics contribute to an optimized user experience. AWS WAF (Amazon Web Services Web Application Firewall) provides robust protection against common web application vulnerabilities such as SQL injection, cross-site scripting (XSS), and cross-site request forgery (CSRF) attacks. By implementing this security layer, the application effectively protects the data of bloggers and readers from potential attacks. The AWS Web Application Firewall (WAF) protects against known attack patterns and continuously monitors and detects harmful activities to prevent unauthorized access. The application's serverless architecture lets bloggers focus on content creation and administration instead of server maintenance. The application's affordable price makes it an appealing, adaptable, and inclusive solution. The application's serverless design and AWS WAF and AWS Open make it flexible, affordable, and accessible for bloggers of all sizes. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Blogs

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