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2023 IEEE International Conference on Artificial Intelligence and Green Energy, ICAIGE 2023

作者： Naceur, Ferdaws Ben Toumi, Sana Salah, Chokri Ben Mahjoub, Mohamed Ali National School of Engineers of Sousse University of Sousse LATIS- Laboratory of Advanced Technology and Intelligent Systems Sousse4023 Tunisia Higher Institute of Computer Science and Communication Technologies of Hammam Sousse University of Sousse Sousse4011 Tunisia Department of Electrical Engineering Monastir Tunisia Brest29238 France Issat Sousse Sousse Tunisia

ISBN: (纸本)9798350325539

This paper deals with an intelligent decision-making strategy of energy management for a smart grid within an element storage in order to reduce the system cost and improve its reliability. Indeed, the integration of distributed energy storage devices allows the customers to store energy and reuse at a later time or delayed some appliances operation according to a time-varying price signal. The adopted strategy is based on an artificial intelligence control algorithm 'fuzzy logic'. The main objective is to determine the appropriate source (grid or battery) used for meeting the consumer. The decision solution shows the system reliability where the switches are synchronized. Switches draw electricity from the grid for both load and battery when price is low and in contrary when electricity price is high, we find a variation's price correspondance with the switch drawing electricity from the battery. The obtained results are verified carrying out Matlab simulation using real data such as the electricity price (Price (t)) and the battery state of charge (SOC (t)). © 2023 IEEE.

关键词： Decision making

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Empowering Software Engineering Students: The Role of Gamification in Promoting Learning Independence 7

Empowering Software Engineering Students: The Role of Gamifi...

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7th International Conference on Vocational Education and Electrical Engineering, ICVEE 2024

作者： Hidayat, Wahyu Nur Hamdan, Achmad Ichwanto, Muhammad Aris Muslihati Cakir, Gulsun Kurubacak Sari, Rahajeng Kartika Afni, Nur Hisyam, Mochammad Raffi Fadhil Universitas Negeri Malang Faculty of Engineering Department of Electrical Engineering and Informatics Malang Indonesia Universitas Negeri Malang Faculty of Vocational Department of Electronic Systems Engineering Technology Malang Indonesia Universitas Negeri Malang Faculty of Engineering Department of Civil Engineering and Planning Malang Indonesia Universitas Negeri Malang Faculty of Education Science Department of Guidance and Counseling Malang Indonesia Ankara Haci Bayram Veli University College of Communication Department of Journalism Ankara Turkey Smk Negeri 10 Malang Department of Computer Network and Telecommunication Engineering Malang Indonesia

ISBN: (纸本)9798331505103

The role of learning media greatly supports the learning process, increasing motivation and interest in the process. Learning media can also be a place to improve competence optimally through bootcamp training menus and the like with more specific training objectives. The main objective of this study is to develop a gamification-based website to enhance students' preparedness for their Final Competency Test by tackling challenges in comprehending programming absent practical experience. The learning method implemented in this website is case-based learning that integrates dynamic coding activities. The research method uses the Plomp approach with 3 main stages, namely preliminary research, prototyping, and assessment stage. The trial of the gamification website began with media and content validation followed by small group testing and large group testing. Validation by media and material experts led to the execution of small group trials (95.7%) and large group trials (91.7%), producing exceptionally positive outcomes. The results of the small group test with 12 respondents produced a very suitable value with a score of 95.7 and the large group test with 27 respondents produced a score of 9 1. 7 % with very suitable criteria. This indicates that the web-based platform is highly viable for assisting vocational students in acquiring software development skills, enhancing their preparedness for practical IT positions such as software developers and system analysts. Subsequent study involved the incorporation of gamification, such as computer-supported collaborative learning. © 2024 IEEE.

关键词： Software testing

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A Switching Event-Triggered Approach to Proportional Integral Synchronization Control for Complex Dynamical Networks

A Switching Event-Triggered Approach to Proportional Integra...

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2022 International Conference on Edge Computing and Applications, ICECAA 2022

作者： Sengeni, D. Muthuraman, A. Vurukonda, Naresh Priyanka, G. Suram, Priyanka Vidhya, R.G. Department of Electronics and Communication Engineering CK College of Engineering and Technology Tamil Nadu Cuddalore607003 India Department of Electrical and Electronics Engineering Mailam Engineering College Tamil Nadu Mailam604304 India Department of Computer Science and Engineering Koneru Lakshmaiah Education Foundation Andhra Pradesh Vaddeswaram522302 India Department of Computer Science and Business Systems Sri Eshwar College of Engineering Tamil Nadu Coimbatore641202 India Telangana Adilabad504001 India Department of Electronics and Communication Engineering HKBK College of Engineering Karnataka Bengaluru560045 India

ISBN: (数字)9781665482325

ISBN: (纸本)9781665482325

A switching event-triggered method is used to explore the proportional-integral (PI) synchronization problem for a session of complex dynamical networks (CDNs) with coupling delay (SETM). With restricted network capacity, the aim is to establish CDN synchronization. For network resource conservation, a SETM is used, which decreases packet delivery and eliminates Zeno behavior. A synchronization condition for CDNs is constructed using a proportional-integral (PI) control approach. Furthermore, SETM and PI controllers were created in collaboration with the goal of assuring CDN synchronization. A mathematical sample might be used to establish the appropriateness and practicality of the suggestedoutcomes. © 2022 IEEE.

关键词： Synchronization

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Enhancing Music Recommendations with Emotional Insight: A Facial Expression Approach in AI 7

Enhancing Music Recommendations with Emotional Insight: A Fa...

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7th International Conference on Electronics, communication and Aerospace Technology, ICECA 2023

作者： Gupta, Manish Venkatesh, S.N. Suraskar, Rupali Praveena, K. Jegadesan, S. Suneetha, Sampathirao GLA University Department of Electronics and Communication Engineering Uttar Pradesh Mathura India Brindavan College of Engineering Department of ECE Karnataka Bangalore India Larsen and Toubro Edutech Department of Electronic Maharashtra Nagpur India Department of ECE Tirupati India Velammal College of Engineering and Technology Department of Information Technology Tamilnadu Madurai India Andhra University College of Engineering Andhra University Department of Computer Science & Systems Engineering Andhra Pradesh Visakhapatnam India

ISBN: (纸本)9798350340600

Music recommendation systems are only one of the many fields that artificial intelligence (AI) has transformed. A developing field called 'emotion-aware music recommendation' aims to improve user experience by including emotional context into the suggestion procedure. This study investigates how AI -powered music recommendation systems can incorporate facial expression analysis. The proposed system suggests a unique method that makes use of deep learning methods to instantly recognize and assess user facial emotions. The proposed system creates music suggestions that fit the user's emotional state by identifying emotions like joy, melancholy, and enthusiasm. Experimental findings that show how our strategy might increase user engagement and pleasure. The results show how emotion-aware AI systems have the ability to produce individualized and emotionally impactful musical experiences. © 2023 IEEE.

关键词： Music

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Applications of Three Introductory C Programming Exercise Problems in Nihon University

Applications of Three Introductory C Programming Exercise Pr...

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IEEE International Conference on Consumer Electronics-Taiwan (ICCE-TW)

作者： Xiqin Lu Nobuo Funabiki Kiyoshi Ueda Wen-Chung Kao Department of Information and Communication Systems Okayama University Okayama Japan Department of Computer Science Nihon University Koriyama Japan Department of Electrical Engineering National Taiwan Normal University Taipei Taiwan

To assist self-study of C programming, we have proposed three types of introductory exercise problems: grammar-concept understanding problem (GUP), value trace problem (VTP) and phase fill-in-blank problem (PFP). GUP and VTP aim at code reading study whereas PFP aims at code writing study. Students can solve them using the browser-based answer interface that has the automatic marking function. In this paper, we present their application results to first-year undergraduate students taking a C programming course in Nihon University, Japan. The same instances were assigned twice this time, where they were assigned once in the previous year. The results show that the correct answer rate was improved for any type as the course elapsed, where that for PFP was no sufficient. Thus, the effectiveness of the proposal is confirmed for basic C programming study.

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The Future of Smart Grids: Revolutionizing Energy Distribution with Advanced IoT, and Renewable Integration 5

The Future of Smart Grids: Revolutionizing Energy Distributi...

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5th IEEE Global Conference for Advancement in Technology, GCAT 2024

作者： Avinash, S. Vinitha, J.C. Dharinya, S. Sree Samuthira Pandi, V. Lakshmi Priya, J. Jaishika, S. St. Joseph's College of Engineering Department of Mba Chennai India Rajalakshmi Engineering College Department of Electrical and Electronics Engineering Tamil Nadu Chennai India Vit University School of Computer Science Engineering and Information Systems Vellore India Chennai Institute of Technology Centre for Advanced Wireless Integrated Technology Tamil Nadu Chennai India Saveetha Engineering College Department of Ece Chennai India Vel Tech Rangarajan Dr.Sagunthala R&d Institute of Science and Technology Department of Electronics and Communication Engineering Avadi Chennai India

ISBN: (纸本)9798350376685

Smart grids, which integrate modern Internet of Things (IoT) technology and renewable energy sources to boost efficiency, sustainability, and dependability, are poised to bring about a dramatic shift in the future of energy distribution. Intelligent grids are expected to bring about this shift. Focusing on the role of the Internet of Things (IoT) in enabling real-time monitoring and control, as well as the incorporation of renewable energy to support a low-carbon future, this research investigates the potential for smart grids to change the energy sector. This study gives insights into how smart grids can be efficiently deployed to satisfy the growing energy needs of society by studying the technological breakthroughs, obstacles, and benefits of smart grids. Specifically, the study's focus is on smart grids. The research highlights the essential role that smart grids play in aiding the shift towards a more sustainable and resilient energy infrastructure by conducting an in-depth analysis of case studies, pilot projects, and industry trends all around the world. Providing recommendations for policymakers, industry stakeholders, and utilities to exploit the full potential of smart grids in determining the future of energy distribution, the findings contribute to the continuing discourse on the strategic development and implementation of smart grid technologies. Both of these topics are currently being discussed. © 2024 IEEE.

关键词： Demand Response Management distributed Generation Energy Efficiency Energy Storage systems Grid Resilience Low-Carbon Future Real-Time Monitoring and Control

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Machine Learning based Beamwidth Adaptation for mmWave Vehicular communications 16

Machine Learning based Beamwidth Adaptation for mmWave Vehic...

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16th IEEE Malaysia International Conference on communication, MICC 2023

作者： Manic, Setinder Foh, Chuan Heng Kose, Abdulkadir Lee, Haeyoung Leow, Chee Yen Chatzimisios, Periklis Moessner, Klaus Suthaputchakun, Chakkaphong University of Surrey 5GIC & 6GIC Guildford United Kingdom Abdullah Gul University Department of Computer Engineering Kayseri Turkey School of Physics Engineering and Computer Science University of Hertfordshire Hatfield United Kingdom Universiti Teknologi Malaysia Wireless Communication Centre Johor Malaysia International Hellenic University Department of Information and Electronic Systems Engineering Thessaloniki Greece Technical University Faculty of Electronics and Information Technology Chemnitz Germany Bangkok University Electrical and Computer Engineering Department Khlong Nueng Thailand

ISBN: (纸本)9798350304343

The incorporation of mmWave technology in vehicular networks has unlocked a realm of possibilities, propelling the advancement of autonomous vehicles, enhancing interconnectedness, and facilitating communication for intelligent transportation systems (ITS). Despite these strides in connectivity, challenges such as high path-loss have arisen, impacting existing beam management procedures. This work aims to address this issue by improving beam management techniques, specifically focusing on enhancing the service time between vehicles and base stations through adaptive mmWave beamwidth adjustments, accomplished using a Contextual Multi-Armed Bandit Algorithm. By leveraging various conditions to train the ML agent of the Contextual Multi-Armed Bandit Algorithm, it seeks to learn about vehicle mobility profiles and optimize the usage of different antenna beamwidth settings to maximize seamless connection time. The extensive simulation results showcase the effectiveness of an adaptive beamwidth for mobility profiles, extending the connection time a vehicle experiences with a base station when compared to the existing strategies. © 2023 IEEE.

关键词： Base stations

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Hybrid Near-field and Far-field Localization with Holographic MIMO

arXiv

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arXiv 2025年

作者： Cao, Mengyuan Zhang, Haobo Eldar, Yonina C. Zhang, Hongliang State Key Laboratory of Advanced Optical Communication Systems and Networks School of Electronics Peking University Beijing100871 China School of Electronic and Computer Engineering Peking University Shenzhen Graduate School Shenzhen518055 China Department of Mathematics and Computer Science Weizmann Institute of Science Rehovot7610001 Israel

Due to its ability to precisely control wireless beams, holographic multiple-input multiple-output (HMIMO) is expected to be a promising solution to achieve high-accuracy localization. However, as the scale of HMIMO increases to improve beam control capability, the corresponding near-field (NF) region expands, indicating that users may exist in both NF and far-field (FF) regions with different electromagnetic transmission characteristics. As a result, existing methods for pure NF or FF localization are no longer applicable. We consider a hybrid NF and FF localization scenario in this paper, where a base station (BS) locates multiple users in both NF and FF regions with the aid of a reconfigurable intelligent surface (RIS), which is a low-cost implementation of HMIMO. In such a scenario, it is difficult to locate the users and optimize the RIS phase shifts because whether the location of the user is in the NF or FF region is unknown, and the channels of different users are coupled. To tackle this challenge, we propose a RIS-enabled localization method that searches the users in both NF and FF regions and tackles the coupling issue by jointly estimating all user locations. We derive the localization error bound by considering the channel coupling and propose an RIS phase shift optimization algorithm that minimizes the derived bound. Simulations show the effectiveness of the proposed method and demonstrate the performance gain compared to pure NF and FF techniques. Copyright © 2025, The Authors. All rights reserved.

关键词： communication channels (information theory)

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Optimal Deep Learning Enabled Statistical Analysis Model for Traffic Prediction

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computers, Materials & Continua 2022年第9期72卷 5563-5576页

作者： Ashit Kumar Dutta S.Srinivasan S.N.Kumar T.S.Balaji Won Il Lee Gyanendra Prasad Joshi Sung Won Kim Department of Computer Science and Information Systems College of Applied SciencesAlMaarefa UniversityAd DiriyahRiyadh13713Kingdom of Saudi Arabia Institute of Biomedical Engineering Saveetha School of EngineeringSaveetha Institute of Medical and Technical SciencesSaveetha UniversitySaveetha NagarThandalamChennai602105India Department of Electrical&Electronics Engineering Amal Jyothi College of EngineeringKanjirappallyKerala686518India Saveetha School of Engineering Saveetha Institute of Medical and Technical SciencesSaveetha UniversitySaveetha NagarThandalamChennai602105India Department of Electronics and Communication Engineering College of Engineering and TechnologySRM Institute of Science and TechnologyVadapalani CampusChennai600026India Department of Business Administration Hanbat National National UniversityDaejeon34158Korea Department of Computer Science and Engineering Sejong UniversitySeoul05006Korea Department of Information and Communication Engineering Yeungnam UniversityGyeongsan-siGyeongbuk-do38541Korea

Due to the advances of intelligent transportation system(ITSs),traffic forecasting has gained significant interest as robust traffic prediction acts as an important part in different ITSs namely traffic signal control,navigation,route mapping,*** traffic prediction model aims to predict the traffic conditions based on the past traffic *** more accurate traffic prediction,this study proposes an optimal deep learning-enabled statistical analysis *** study offers the design of optimal convolutional neural network with attention long short term memory(OCNN-ALSTM)model for traffic *** proposed OCNN-ALSTM technique primarily preprocesses the traffic data by the use of min-max normalization ***,OCNN-ALSTM technique was executed for classifying and predicting the traffic data in real time *** enhancing the predictive outcomes of the OCNN-ALSTM technique,the bird swarm algorithm(BSA)is employed to it and thereby overall efficacy of the network gets *** design of BSA for optimal hyperparameter tuning of the CNN-ALSTM model shows the novelty of the *** experimental validation of the OCNNALSTM technique is performed using benchmark datasets and the results are examined under several *** simulation results reported the enhanced outcomes of the OCNN-ALSTM model over the recent methods under several dimensions.

关键词： Statistical analysis predictive models deep learning traffic prediction bird swarm algorithm

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Shortest Job First with Gateway-based Resource Management Strategy for Fog Enabled Cloud Computing

Shortest Job First with Gateway-based Resource Management St...

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Data Engineering and communication systems (ICDECS), International Conference on

作者： K. Anbazhagan Rotash Kumar R. Thilagavathy D. Anuradha Department of Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai India Department of Electronics and Communication Engineering Government Engineering College Jhalawar Rajasthan India Department of Computing Technologies College of Engineering and Technology SRM Institute of Science and Technology Kattankulathur Chennai India Department of Computer Science and Business Systems Panimalar Engineering College Chennai India

In recent years, fog computing has extended cloud services to the network edge, lowering network latency and congestion and overcoming cloud computing restrictions. Many hurdles, however, must be overcome before the benefits of the fog-IoT paradigm for low-latency applications can be completely realized. The most challenging difficulty in IoT applications is developing efficient resource management strategies that maximize throughput while minimizing delay. IoT and fog computing, rather than simply utilizing cloud computing technology, have brought intriguing new data management solutions. Fog computing makes real-time analytics applications conceivable. After combining fog computing technologies with Internet of Things (IoT) applications, the system can reply in milliseconds. Existing fog resource managers focus on a subset of fog resource management parameters such as system response time, network bandwidth, energy consumption, and latency. No Fog resource management takes multiple factors into account at the same time for decision-making, which will become increasingly crucial in intelligent homes. Gateway-based Fog Computing pioneered the introduction of the shortest job (SJFGFC) to address these difficulties. The technique is validated in an IoT-based imaginative house automation scenario before being evaluated in a small-scale bright home experiment using the iFogSim toolbox and empirical models.

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