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Efficient Power Control for UAV Based on Trajectory and Game Theory

computers, Materials & Continua 2023年第3期74卷 5589-5606页

作者： Fadhil Mukhlif Ashraf Osman Ibrahim Norafida Ithnin Roobaea Alroobaea Majed Alsafyani Information Assurance and Security Research Group(IASRG) School of ComputingFaculty of EngineeringUniversiti Teknologi MalaysiaJohorMalaysia Faculty of Computing and Informatics University Malaysia SabahKota KinabaluMalaysia Department of Computer Science College of Computers and Information TechnologyTaif UniversityTaifSaudi Arabia

Due to the fact that network space is becoming more limited,the implementation of ultra-dense networks(UDNs)has the potential to enhance not only network coverage but also network *** Aerial Vehicle(UAV)communications have recently garnered a lot of attention due to the fact that they are extremely versatile and may be applied to a wide variety of contexts and purposes.A cognitive UAV is proposed as a solution for the Internet of Things ground terminal’s wireless nodes in this *** the IoT system,the UAV is utilised not only to determine how the resources should be distributed but also to provide power to the wireless *** quality of service(QoS)offered by the cognitive node was interpreted as a price-based utility function,which was demonstrated in the form of a non-cooperative game theory in order to maximise customers’net utility *** energyefficient non-cooperative game theory power allocation with pricing strategy abbreviated as(EE-NGPAP)is implemented in this study with two trajectories Spiral and Sigmoidal in order to facilitate effective power management in Internet of Things(IoT)wireless *** has also been demonstrated,theoretically and by the use of simulations,that the Nash equilibrium does exist and that it is one of a *** proposed energy harvesting approach was shown,through simulations,to significantly reduce the typical amount of power thatwas *** is taken into consideration to agree with the objective of 5G *** order to converge to Nash Equilibrium(NE),the method that is advised only needs roughly 4 iterations,which makes it easier to utilise in the real world,where things aren’t always the same.

关键词： UAV spiral&sigmoid trajectory drones IoT game theory energy efficiency 6G

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Developing Engagement in the Learning Management System Supported by Learning Analytics

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computer Systems Science & engineering 2022年第7期42卷 335-350页

作者： Suraya Hamid Shahrul Nizam Ismail Muzaffar Hamzah Asad W.Malik Department of Information System Faculty of Computer Science and Information TechnologyUniversiti MalayaKuala LumpurMalaysia Faculty of Computing and Informatics Universiti Malaysia SabahSabahMalaysia Department of Computing School of Electrical Engineering and Computer Science(SEECS)National University of Sciences and Technology(NUST)IslamabadPakistan

Learning analytics is an emerging technique of analysing student par-ticipation and *** recent COVID-19 pandemic has signiﬁcantly increased the role of learning management systems(LMSs).LMSs previously only complemented face-to-face teaching,something which has not been possible between 2019 to *** date,the existing body of literature on LMSs has not analysed learning in the context of the pandemic,where an LMS serves as the only interface between students and ***,productive results will remain elusive if the key factors that contribute towards engaging students in learning are notﬁrst identiﬁ***,this study aimed to perform an exten-sive literature review with which to design and develop a student engagement model for holistic involvement in an *** required data was collected from an LMS that is currently utilised by a local Malaysian *** model was validated by a panel of experts as well as discussions with *** is our hope that the result of this study will help other institutions of higher learning determine factors of low engagement in their respective LMSs.

关键词： Engagement analysis learning analytics learning management system student engagement

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Analysis of selected dielectric parameters of insulating liquids 23

Analysis of selected dielectric parameters of insulating liq...

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23rd International Scientific Conference on Electric Power engineering, EPE 2023

作者： Pluzek, Aleksandra Nagi, Lukasz Koziol, Michal Zygarlicka, Malgorzata Opole University of Technology Faculty of Electrical Engineering Automatic Control and Informatics Department of Electrical Power and Renewable Energy Opole Poland Opole University of Technology Faculty of Electrical Engineering Automatic Control and Informatics Department of Computer Science Opole Poland

ISBN: (纸本)9798350335934

During the last few years, there has been a growing interest in the topic of using natural or synthetic esters as an alternative to mineral oils in oil transformers due to the easier way to obtain them and their ability to exhibit better electrical properties. In addition, more and more researchers are describing in their work that doping esters with nanoparticles is capable of further improving these properties. Therefore, in the current work, it was decided to see what effect the addition of a hydrophobic carbon shell iron nanoparticle to ORLEN mineral oil and Midel 7131 synthetic ester would have on selected electrical parameters of the insulating fluid, i.e. breakdown voltage and electrical strength. © 2023 IEEE.

关键词： Nanoparticles

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Retrieval Augmented Generation in Large Language Models: Development of AI Chatbot for Student Support 15

Retrieval Augmented Generation in Large Language Models: Dev...

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15th International Conference on eLearning, eLearning 2024

作者： Oreški, Dijana Vlahek, Dino University of Zagreb Faculty of Organization and Informatics Pavlinska 2 Varaždin42000 Croatia University of Maribor Faculty of Electrical Engineering and Computer Science Koroška cesta 46 MariborSI-2000 Slovenia

Large Language Models (LLMs) are being employed in various domains to support different tasks. There are many challenges when working with LLMs, such as hallucination and domain knowledge gaps. Retrieval Augmented Generation (RAG) has emerged as one of the best paradigms for enabling LLMs to access domain-specific data and as a mechanism for mitigating hallucinations. In this paper, we are employing RAG and investigating how large language models use repositories of pre-existing knowledge to enhance the quality and relevance of generated responses. The focus of the paper is the development of real-world RAG applications in the educational domain. The research aims to develop an AI-based chatbot for university students that could answer students` frequently asked questions. Such a chatbot solves several challenges faced by the faculty administration and guides the improvement of the student's study experience. In the implementation, a low-code approach of Flowise AI is used. As a result, the prototype is developed. From the domain point of view, the prototype represents a step toward an AI-powered educational system that has the potential to further enhance the level of individualized educational support. From the technological point of view, such implementation emphasizes the benefits of LLM and RAG integration and the advantages of generative artificial intelligence. © 2024 Copyright for this paper by its authors.

关键词： Students

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Micro Frontend Architecture

Micro Frontend Architecture

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Zooming Innovation in Consumer Electronics International Conference (ZINC)

作者： Vladimír Kunštnár Patrik Podhorský Faculty of Informatics and Information Technologies Institute of Computer Engineering and Applied Informatics Bratislava Slovakia

ISBN: (数字)9798350349153

ISBN: (纸本)9798350349160

Our paper focuses on software architectures in web application environments, specifically their evolution in client interface development. We will focus on implementing client interfaces with Micro Frontends, which are based on the principle of microservices. We will explain how to implement this architecture and integrate multiple Micro Frontends into a single web application. Additionally, we will evaluate the efficiency and performance of Micro Frontends compared to monolithic client interfaces. Finally, we will compare the performances of the two architectures and propose an improvement to implementing Micro Frontends. Our improvement proposal will explain how Micro Frontends can be implemented to create more modular and reusable user interfaces using well-known methodologies and design patterns.

关键词： Technological innovation Software architecture Design methodology Microservice architectures computer architecture User interfaces Proposals

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Efficient Machine Learning for Prediction of Malicious URLs under Neutrosophic Uncertainty Framework

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Neutrosophic Sets and Systems 2025年 83卷 456-468页

作者： Eassa, Mohamed Abdelhafeez, Ahmed Metwaly, Ahmed A. Salama, Ahmed S. Computer Science Department Faculty of Information Systems and Computer Science October 6th University Giza12585 Egypt Department of Computer Science Faculty of Computers and Informatics Zagazig University Zagazig44519 Egypt Department of Computer Engineering and Electronics Cairo Higher Institute for Engineering Computer Science and Management New Cairo Egypt

With more than 5.44 billion users, the Internet is an essential component of everyday life, facilitating e-commerce, interaction, learning, and more. But with the proliferation of harmful Uniform Resource Locators (URLs), this widespread Internet access also raises questions about online security and privacy. Due to their significant advantages of lowering model variance, increasing predictive performance, raising prediction accuracy, and exhibiting strong generalization potential, traditional ensemble models have recently drawn interest. However, there is still work to be done on how to use it to combat rogue URLs. These URLs are dangerous to people and organizations because they frequently lurk behind static links in emails or web pages. Many malicious websites avoid detection despite blacklisting services because they are either newly created or not closely monitored. Hence, we use different machine learning (ML) models such as decision tree, AdaBoosting, Naïve Bayes, random forest, gradient boosting, and XGBoosting. Then these models are evaluated under the neutrosophic framework to deal with uncertainty. The WASPAS method is used to select the best ML model from different models. The results show that the random forest is the best ML model. © 2025, University of New Mexico. All rights reserved.

关键词： Learning systems

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Monitoring of Heart and Respiration Rate Using a 3D Knitted T-shirt with Textile-based Electrodes

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IFAC-PapersOnLine 2024年第30期58卷 49-54页

作者： Nada Al-azzawi Irem Yunculer Asli Tuncay Atalay Ozgur Atalay Gökhan Ince Faculty of Computer and Informatics Engineering Computer Engineering Department Istanbul Technical University Istanbul 34469 Turkey Faculty of Textile Technologies and Design Textile Engineering Department Istanbul Technical University Istanbul 34437 Turkey

The emergence of e-textiles has facilitated impressive growth in the field of wearable technologies in recent years. Textile-based electrodes enabled long-period electrocardiogram monitoring within the health care field as they are less irritant to the skin and can be naturally embedded into the clothes. Beyond the specific health-oriented applications, physiological signals monitoring is also beneficial during other activities such as daily activities and sports. In this work, a system of a knitted t-shirt embedded with textile electrodes that targets measuring heart rate and respiration rate during various positions and activities is created. The performance of the implemented system is benchmarked against the performance of an off-the-shelf product using root mean square error. It has been shown that the proposed system can achieve good performance with heart rate respiration rate values close to that of the benchmark device.

关键词： E-textile technology smart t-shirt wearable technology heart rate monitoring ECG ECG derived respiration

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AVIG: A Real-Time Visual Inspection for Guava Grading System Using computer Vision and XGBoost 23

AVIG: A Real-Time Visual Inspection for Guava Grading System...

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8th International Conference on Sustainable Information engineering and Technology, SIET 2023

作者： Setyawan, Raden Arief Perdana, Rizal Setya Harilegawa, Made Wena Balantimuhe, Alan Stevrie Basuki, Achmad Department of Electrical Engineering Faculty of Engineering Brawijaya University Malang Indonesia Department of Informatics Engineering Faculty of Computer Science Brawijaya University Malang Indonesia Directorate of Information Technology Brawijaya University Malang Indonesia

ISBN: (纸本)9798400708503

The conventional approach to manual inspection can be described by its considerable time and labor demands and the unavoidable occurrence of human error when faced with the inspection of a large number of products. Therefore, the application of an automated visual inspection system is frequently employed. The camera(s) can easily capture visual features for automatic visual inspection. However, it is essential to note that there are limitations when using this method to estimate the size-based grading system. The volume measurement is an essential feature in the field of automatic image analysis for fruit and vegetable grading, specifically guava. In this study, we propose a novel image analysis approach that utilizes a dual-view camera system to enhance the accuracy of volume approximation, particularly in scenarios involving non-perfect spherical objects. Hence, this research presents the training process of a comprehensive model for estimating the volume of objects with irregular shapes, named AVIG (Automatic Visual Inspection for Grading). The model utilizes the ellipsoid approximation technique, a dual-view camera, and XGBoost algorithm. The results from the accuracy comparison demonstrate that XGBoost shows the highest degree of accuracy, specifically 86%, thereby outperforming the performance of other algorithms. The comprehensive experiment conducted in this study has shown that the proposed architecture, AVIG, exhibits superior performance compared to previous research in terms of automatic evaluation of moving objects. © 2023 ACM.

关键词： computer vision

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Comparison of The Accuracy of Predicting The Number Of Positive Covid-19 Between The Neural Network and LSTM Methods

Comparison of The Accuracy of Predicting The Number Of Posit...

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2023 International Conference on informatics, Multimedia, Cyber and Information Systems, ICIMCIS 2023

作者： Riyanto, Eko Amalia, Rifka Dwi Stmik Himsya Informatics Engineering Semarang Indonesia Universitas Pembangunan Nasional Veteran Jakarta Information Systems Faculty of Computer Science Jakarta Indonesia

ISBN: (纸本)9798350307306

The COVID-19 pandemic (Coronavirus) is likely to be one of the most serious global problems in the last year. Countries do not have similar experiences with the spread of the virus and its impact from various fields. Estimating the number of COVID-19 cases in the past can help in decision-making about action and plan for virus prevention. The study aims to provide accurate predictive model in predicting confirmed cases of COVID-19 in Semarang city. In predicting the number of people exposed to Covid-19 positive need to be accurate and accurate methods, in some previous studies the two methods most recommended are neural network and LSTM (Long Short Term Memory) which have high levels of accuracy. Based on research that has been carried out that the results of accurate prediction comparison between RNN and LSTM obtain the smallest MSE result is the method. © 2023 IEEE.

关键词： Forecasting

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Early Detection of Alzheimer’s Disease Based on Laplacian Re-Decomposition and XGBoosting

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computer Systems Science & engineering 2023年第9期46卷 2773-2795页

作者： Hala Ahmed Hassan Soliman Shaker El-Sappagh Tamer Abuhmed Mohammed Elmogy Information Technology Department Faculty of Computers and InformationMansoura UniversityMansoura35511Egypt Faculty of Computer Science and Engineering Galala UniversitySuez435611Egypt Faculty of Computers and Artificial Intelligence Benha UniversityBanha13518Egypt College of Computing and Informatics Sungkyunkwan UniversitySuwonKorea

The precise diagnosis of Alzheimer’s disease is critical for patient treatment,especially at the early stage,because awareness of the severity and progression risks lets patients take preventative actions before irreversible brain damage *** is possible to gain a holistic view of Alzheimer’s disease staging by combining multiple data modalities,known as image *** this paper,the study proposes the early detection of Alzheimer’s disease using different modalities of Alzheimer’s disease brain ***,the preprocessing was performed on the ***,the data augmentation techniques are used to handle ***,the skull is removed to lead to good *** the second phase,two fusion stages are used:pixel level(early fusion)and feature level(late fusion).We fused magnetic resonance imaging and positron emission tomography images using early fusion(Laplacian Re-Decomposition)and late fusion(Canonical Correlation Analysis).The proposed system used magnetic resonance imaging and positron emission tomography to take advantage of *** resonance imaging system’s primary benefits are providing images with excellent spatial resolution and structural information for specific *** emission tomography images can provide functional information and the metabolisms of particular *** characteristic helps clinicians detect diseases and tumor progression at an early ***,the feature extraction of fused images is extracted using a convolutional neural *** the case of late fusion,the features are extracted first and then ***,the proposed system performs XGB to classify Alzheimer’s *** system’s performance was evaluated using accuracy,specificity,and *** medical data were retrieved in the 2D format of 256×256 *** classifiers were optimized to achieve the final results:for the decision tree,the maximum depth of a tree was *** best number of trees for the random forest was 60;for

关键词： Alzheimer’s disease(AD) machine learning(ML) image fusion Laplacian Re-decomposition(LRD) XGBoosting

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