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Radio resource management and path planning in intelligent transportation systems via reinforcement learning for environmental sustainability

Radio resource management and path planning in intelligent t...

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international conference on Innovation and Technological advances for Sustainability, ITAS 2023

作者： Norouzi, S. Azarasa, N. Abedi, M.R. Mokari, N. Seyedabrishami, S.E. Saeedi, H. Jorswieck, E.A. Department of Electrical and Computer Engineering Tarbiat Modares University Tehran Iran Department of Civil and Environmental Engineering Tarbiat Modares University Tehran Iran College of Engineering Doha University for Science and Technology Doha Qatar Institute of Communications Technology TU Braunschweig Lower Saxony Germany

ISBN: (纸本)9781032803722

Efficient and dynamic path planning has become an important topic for urban areas with larger density of connected vehicles (CV) which results in reduction of travel time and directly contributes to environmental sustainability through reducing energy consumption. CVs exploit the cellular wireless vehicle-to-everything (C-V2X) communication technology to disseminate the vehicle-to-infrastructure (V2I) messages to the Base-station (BS) to improve situation awareness on urban roads. In this paper, we investigate radio resource management (RRM) in such a framework to minimize the age of information (AoI) so as to enhance path planning results. We use the fact that V2I messages with lower AoI value result in less error in estimating the road capacity and more accurate path planning. Through simulations, we compare road travel times and volume over capacity (V/C) against different levels of AoI and demonstrate the promising performance of the proposed framework. © 2025 The Author(s).

关键词： Resource allocation

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25th international conference on Internet Computing and IoT, ICOMP 2024, and 22nd international conference on Embedded Systems, Cyber-physical Systems, and Applications, ESCS 2024, held as part of the World Congress in computer science, computer engineering and Applied Computing, CSCE 2024

25th International Conference on Internet Computing and IoT,...

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25th international conference on Internet Computing and IoT, ICOMP 2024, and 22nd international conference on Embedded Systems, Cyber-physical Systems, and Applications, ESCS 2024, held as part of the World Congress in computer science, computer engineering and Applied Computing, CSCE 2024

ISBN: (纸本)9783031859229

The proceedings contain 33 papers. The special focus in this conference is on Internet Computing and IoT. The topics include: Malware Detection in the IoT Home Network;IoT-Based Analysis of Environmental and Motion Data for Comfort and Energy Conservation in Optimizing HVAC Systems;improving Critical Controls Using IoT and computer Vision;A Data-Driven Driving Under the Influence (DUI) Detection, Notification and Prevention System Using Artificial Intelligence and Internet-Of-Things (IoT);understanding User Interactions with IoT Process Models: A Demographic Perspective;Advancing IoT Process Modeling: A Comparative Evaluation of BPMNE4IoT and Traditional BPMN on User-Friendliness, Effectiveness, and Workload;Threat Detection Using MLP for IoT Network;harnessing Social Robotics and the Internet of Things to Reduce the Risk of Older Adults Developing Hypothermia and Dehydration;re/Imagining Smart Home Automation Framework in the Era of 6G-Enabled Smart Cities;smart Roadway Monitoring: Pothole Detection and Mapping via Google Street View;Energy-Efficiency Modeling for AI Applications on Edge Computing;optimizing Wireless Sensor Network Node Placement Using Bacterial Foraging Optimization;The Vital Role of Small and Marginal Farmer in Future of Our Climate: Democratization of Machine Learning, Artificial Intelligence, and Dairy Cow Necklace Sensors in Achieving the UN Climate Change Goals (COP21) and the Paris Agreement;autonomous Driving Prototype with Raspberry Pi by Using Image Processing Technology;towards Implementation of Privacy-Preserving Federated Learning Aggregation Using Multi-key Homomorphic Encryption;advancing Nursing Education Through Virtual Reality Training: A Revolutionary Approach to Ensuring Patient Safety;multiDrone Simulator An Open Source Multi-plataform Tool to Use in Tests of Optimized Flight of Group of Drones;Revolutionizing Multiplayer Gaming: A Deep Dive into VisionXO, a 3D Multiplayer Tic-Tac-Toe Game.

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8th international conference on Applied Cognitive Computing, ACC 2024, and 26th international conference on Artificial Intelligence, ICAI 2024, held as part of the World Congress in computer science, computer engineering and Applied Computing, CSCE 2024

8th International Conference on Applied Cognitive Computing,...

引用

8th international conference on Applied Cognitive Computing, ACC 2024, and 26th international conference on Artificial Intelligence, ICAI 2024, held as part of the World Congress in computer science, computer engineering and Applied Computing, CSCE 2024

ISBN: (纸本)9783031856273

The proceedings contain 37 papers. The special focus in this conference is on Applied Cognitive Computing. The topics include: Assessing Information Influence for Node Attribute Prediction;in-Vehicle Sensing Platform for the Inference of Older Drivers’ Mild Cognitive Condition;infusing Human Feedback into Intermediate Prompting Steps of Large Language Models;experimental Analysis of Contemporary Trends, Performance, and Limitations in Graph Embeddings: A Concise Review;a Secure Self-Adaptive System in Applications of Cognitive Computing;revisiting the Nexus Between Handwriting and Personality: Graphology;from Static Graph Attention Generation to Dynamic Graph Attention Coefficient;An Integrated Approach for AI-Assisted Survey Systems Using Deterministic and Nondeterministic Models;a Voxel-Representation-Based Data Generator of Adversarial Objects for Robotic Manipulators;an Analysis of Different Information Granularity Distribution Protocols to Improve Consistency in Intuitionistic Reciprocal Preference Relations;enhancing Differential Evolution for Neural Network Optimization Through Boundary Individual Consideration;predictive Modeling of Shading Effects on Photovoltaic Panels Using Regression Analysis;enhancing Cultural Algorithm Guided Policy Gradients with Parameter-Based Exploration Through Topographic Knowledge and Adaptive Weighting;Enhancing Clinical Documentation Through NLP-Driven Disease Categorization and Visualization: A Case Study Utilizing the Llama2 AI Model;automatic Modulation Recognition: A Hybrid Approach Using Deep Learning and K-Means Clustering;An ISR Asset Planning Application;causal Discovery with Interactive Human Inputs;implementation of a Lightweight Gradient Descent Trained Expert System Algorithm;Leveraging JSBSim and Gymnasium: A Reinforcement Learning Approach for Air Combat Simulation;orthogonal Activation Functions in Neural Networks: Utilizing Chebyshev, Legendre, and Hermite Polynomials;XAI-Based Assessment of Software Vulnerabil

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A Framework for Ontology-Based engineering Systems: advances and Open Questions About Knowledge Capture and Use in Aerospace Manufacturing 5th

A Framework for Ontology-Based Engineering Systems: Advances...

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5th international conference on Innovative Intelligent Industrial Production and Logistics

作者： Mas, Fernando Arista, Rebeca Skrzek, Murillo Oliva, Manuel Morales-Palma, Domingo Szejka, Anderson Luis Univ Seville Seville Spain Airbus SAS Toulouse France Pontif Catholic Univ Parana PUCPR Curitiba Parana Brazil Airbus Def & Space Seville Spain CT Engn Grp Madrid Spain

ISBN: (纸本)9783031807749;9783031807756

Modern Ontology-Based engineering (OBE) systems, built over the foundations of Knowledge-Based engineering (KBE), leverage ontology-based technologies and the semantic web to capture and formalise knowledge holistically. This comprehensive knowledge repository can subsequently feed design and decision support tools with robust generative features. However, the integration and reuse of knowledge poses challenges for which it is necessary to develop appropriate methods and tools capable of handling diverse types of knowledge from both human experience and databases. The objective of this paper is to discuss the current limitations of OBE systems to address knowledge integration and reuse, based on the research and experiences of the authors in the aerospace manufacturing industry. This aims to provide a set of Research Questions (RQ) and the author's position to them, to serve as future research work and topics of discussion for the scientific community.

关键词： Ontology-Based engineering (OBE) Knowledge-Based engineering (KBE) Models for Manufacturing (MfM) Ontologies

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AES Efficient Encryption of Multimedia Data using Threads for 5G System 2

AES Efficient Encryption of Multimedia Data using Threads fo...

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2nd international conference on Machine Learning and Autonomous Systems, ICMLAS 2025

作者： Govinda Rajulu, G. Sharmila, L. Venkatesan, D. Kumar, Nathi Kranthi Venkateswaramma, Jarabhala Nirosha, Chelumala Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Department of Computer Science and Design Tamil Nadu Chennai India Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Department of Computer Science and Engineering Tamil Nadu India St. Martin's Engineering College Dept. of Artificial Intelligence and Machine Learning Hyderabad India Hyderabad India Secunderabad India St. Martin's Engineering College Department of EEE Telangana Secunderabad500 100 India

ISBN: (纸本)9798331505745

As technology advances, encryption methods must adapt to protect sensitive information. Organizations must stay informed about emerging threats and regularly update their protocols to stay ahead. Investing in advanced encryption technologies can mitigate potential breaches. Encryption protects intellectual property, multimedia data, and personal data from cyber threats, a crucial consideration for businesses and individuals in the digital age. This work introduces four AES-based threads for encrypting and decoding multimedia data in 5G. Both sequential and parallel methods have been used for data security. Furthermore, time analyses for sequential and parallel processing algorithms have been conducted using images of various sizes and formats. The results indicate that the encryption process will be completed faster and will provide network-wide data safety in parallel method. © 2025 IEEE.

关键词： Sensitive data

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Wireless Charging Technologies for Electric Vehicles: State of the Art and Future Outlook

Wireless Charging Technologies for Electric Vehicles: State ...

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2025 IEEE international Students' conference on Electrical, Electronics and computer science, SCEECS 2025

作者： Sarathkumar, D. Parrthipan, B.K. Manivel, Murugesan Jayakumar, T. Rao, R Subramani Sambooranalaxmi, S. Department of Electrical and Electronics Engineering Tamil Nadu 638060 India Kamaraj College of Engineering and Technology Department of Mechanical Engineering Tamil Nadu Vellakulam625701 India Karpagam Institute of Technology Department of Electrical and Electronics Engineering Tamilnadu Coimbatore641021 India Nandha Engineering College Department of Electrical and Electronics Engineering Tamilnadu 638052 India V.S.B Engineering College Department of Electrical and Electronics Engineering Karur India Psr Engineering College Department of Electronics and Communication Engineering Tamil Nadu Sivakasi626140 India

ISBN: (纸本)9798331529833

Wireless charging technology for electric vehicles (EVs) represents a significant advancement in the transition to sustainable transportation, offering a convenient and efficient alternative to traditional plug-in charging systems. This paper provides a comprehensive review of the state-of-the-art wireless charging techniques, with a focus on inductive power transfer (IPT), resonant inductive coupling, and emerging capacitive and magnetic resonance methods. Key components of wireless charging systems, including power electronics, coil design, alignment techniques, and communication protocols, are discussed. We also address the challenges related to efficiency, safety, standardization, and scalability, particularly in dynamic charging systems designed for highway applications. The paper further explores the integration of wireless charging into smart grids, considering the potential for vehicle-to-grid (V2G) applications and renewable energy sources. A comparative analysis of existing technologies and their readiness for widespread adoption is provided, alongside an outlook on future trends, including high-power charging, autonomous charging infrastructure, and advances in materials and control algorithms. The paper concludes by identifying research gaps and potential directions for innovation in wireless charging for EVs. © 2025 IEEE.

关键词： Wireless charging

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Machine Learning-Enhanced Voice Interaction: Revolutionizing Windows Desktop Applications 1

Machine Learning-Enhanced Voice Interaction: Revolutionizing...

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1st international conference on advances in computer science, Electrical, Electronics, and Communication Technologies, CE2CT 2025

作者： Vora, Raj Chakrawarti, Rajesh Kumar Raghuwanshi, Namrata Sushila Devi Bansal College of Technology Computer Science and Engineering Indore India

ISBN: (纸本)9798331518578

The use of voice interaction is changing the way human being communicate with devices as it offers a simple and effective way of interaction. To implement voice interaction within desktop applications and make it more effective as it is integrated with the operating system, there is a various need models, to particularly improve Convolutional its neural quality. Networks This (CNNs), paper Recurrent considers Neural how Networks (RNNs), and transformers, can enhance the effectiveness of voice interaction in the context of Windows desktop platforms. The research focuses on several major issues: enhancing the speech recognition performance in the presence of background noise, handling the differences in user's accent and speech manner, and real-time operation with reduced delay. It also examines issues of privacy relating to handling of sensitive voice information and ways of reducing these vulnerabilities. Using and enhanced user machine intent learning and results operating encompass connecting detection strategies, the indicate system the in this user's and that voice possibility developing voice research experience provides the interaction the of recognition in is an application with next increasing systems. Different designed better of other these generation the practical user to machine current models of multilingual applications experience. Improve learning and are desktop capabilities, including the enhances future assessed apps. Implementing productivity current The AI from the tools, limited paper effectiveness solutions, the ability accessibility capabilities also and thus perspective to features of provides quality stating of recognize and contextual recommendations of that performance, users' intelligent understanding for voice flexibility emotions, assistants. Future control is and the research, commands the which on key them to Windows. © 2025 IEEE.

关键词： Speech recognition

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Comparative Study of Machine Learning and Deep Learning Models for Food Waste Detection Using Image Processing

Comparative Study of Machine Learning and Deep Learning Mode...

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2025 IEEE international Students' conference on Electrical, Electronics and computer science, SCEECS 2025

作者： Rajagopal, R. Chaithanya, K. Sonth, Ankita Kallappagoudar, Prasanna Basanagouda Mohammadishaq Nadaf, Mohammadzaid Ananda Theertha, H. Dept of Computer Science Alliance College of Engineering and Design Alliance University Bangalore India Bangalore India Alliance College of Engineering and Design Dept of Computer Science Bangalore India Alliance College of Engineering and Design Dept of Computer Science and Engineering Bangalore India

ISBN: (纸本)9798331529833

For the purpose of reducing financial losses and environmental impacts, food waste detection is essential. Inorder to detect food waste using image processing, this study investigates the efficiency of several machine learning algorithms, including Convolutional Neural Network (CNN), K-Nearest Neighbors (KNN), Random Forest, and Inception Model (IV3). A set of images of food are then processed. Before each algorithm is used for classification, pre-processing methods like segmentation and feature extraction are used. © 2025 IEEE.

关键词： k-nearest neighbors

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An efficient extraction of the maximum power in a photovoltaic system based on enhanced P&O-Fuzzy logic controller

An efficient extraction of the maximum power in a photovolta...

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international conference on Innovation and Technological advances for Sustainability, ITAS 2023

作者： Elzein, I.M. Kurdi, M. Department of Telecommunication and Networking Engineering University of Doha for Science and Technology Doha Qatar Department of Computer Science City University Lebanon

ISBN: (纸本)9781032803722

The concept of solar cell is changing the world in obtaining a clean energy that is an environment user friendly source of energy. Solar arrays process and convert the irradiance which is representing the quantity of light that comes from sun to a usable energy. The maximum power point which is denoted by Maximum power (Pmax) can be efficiently extracted from solar panels through the implementation of a tracking system denoted by the maximum power point tracking algorithm (MPPT). Such a tracking system is well known and utilized in detecting the ultimate maximum power that can be taken from the PV solar arrays under the circumstances of the various changes in both the temperature and irradiance. Through this analysis study, the Perturb and Observe (P&O) algorithm will be proposed to adjust the perturbation steps that will be controlled by an enhanced fuzzy logic controller. It will utilize the fuzzy concepts to extract the maximum power. In this research paper an analysis will be conducted to find the unknown parameters of the PV module along in selecting the appropriate set of fuzzy rules/fuzzy table as well as introducing a high gain dc-dc boost converter to improve the efficiency of power, response time, and reducing the oscillation around the Pmax in the proposed photovoltaic system. © 2025 The Author(s).

关键词： Solar irradiance

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Ensuring Data Integrity in Multi-Tenant Cloud Environments Through Advanced Testing 1

Ensuring Data Integrity in Multi-Tenant Cloud Environments T...

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1st international conference on advances in computer science, Electrical, Electronics, and Communication Technologies, CE2CT 2025

作者： Gali, Vinay Kumar Chauhan, Sansar Singh Gupta, Gopal Kumar Bulani, Padmini Rajendra Ravalji, Vardhansinh Yogendrasinnh Jayaraman, Kumaresan Durvas Nagarjuna University Andhra Pradesh Guntur522510 India G.L. Bajaj Institute of Technology and Management Department of Computer Science and Engineering Greater Noida201306 India Nagpur Campus Pune440008 India Institute of Chartered Accountants of India India Northeastern University BostonMA United States Bharathidasan University Tamil Nadu Tiruchirappalli India

ISBN: (纸本)9798331518578

fortunately, multi-tenant cloud environments offer a more cost-effective provisioning model that consumes infrastructure to store and access data. As the volume of sensitive data processed and stored in the cloud continues to grow, ensuring data integrity has become a top concern for organizations. Data integrity is the information that is correct, consistent, and reliable is stored in the cloud. To address this issue, we also present a solution that allows us to maintain integrity in a multi-tenant cloud environment using advanced testing. The standard approach to testing (functional and performance testing) does not identify and will enable us to prevent data integrity problems. That's because these approaches describe the system's functionality and performance rather than the accuracy of the system's data. They proposed a solution that used techniques like anomaly detection, data profiling, and data quality checks to discover possible integrity issues in the dataset. The new techniques work within the testing process, while all data is assessed for integrity before being stored in the cloud. © 2025 IEEE.

关键词： Data integrity

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