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Renewable Energy Technologies and Modern Communications Systems: Future and Challenges, Conference on

作者： Nusrat Hamid Shah Saiful Adli Ismail Azizul Azizan Lubna Hamid Shah Durdana Taranum Khan Faculty of Artificial Intelligence Universiti Teknologi Malaysia Kuala Lampur Malaysia Dept. of Management and Marketting College of Business Jazan University Jazan Saudi Arabia College of Engineering and Computer Science Jazan University Jazan Saudi Arabia

ISBN: (数字)9798331519445

ISBN: (纸本)9798331519452

The concept of smart cities has gained significant traction globally as urban populations continue to grow, necessitating innovative solutions to enhance urban living. This research article explores the multifaceted challenges and opportunities associated with implementing smart city initiatives across various global contexts. Through a comprehensive review of existing studies from various regions, this research seeks to uncover common barriers- such as resource limitations, policy constraints, and public acceptance issues-that cities face when striving to integrate smart technologies. In addition, it highlights effective practices and lessons learned from cities that have pioneered smart city models, offering actionable insights that can aid urban planners, policymakers, and technologists in overcoming these obstacles. Ultimately, the findings aim to guide future research and policy directions, supporting cities in their journey to harness technology for improved urban living and sustainable development.

关键词： Renewable energy sources Smart cities Reviews Communication systems Sustainable development Faces

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AI-Driven Network Effects and Tokenization for Next-Gen Communication Networks in Energy Systems

AI-Driven Network Effects and Tokenization for Next-Gen Comm...

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Cognitive Computing in engineering, Communications, Sciences and Biomedical Health Informatics (IC3ECSBHI), International Conference on

作者： Mukul Singh Devesh Singh Pal Priyanka Yadav M.A. Ansari Vishwamitra Singh Vikas Beniwal School of Engineering Gautam Buddha University Gautam Budh Nagar India Dept. of Information Technology HIMT Group of Institutions Gautam Budh Nagar India Dept. of Computer Applications HIMT Group of Institutions Gautam Budh Nagar India Indian Institute of Management Kozhikode Kozhikode Kerela India UNSW Engineering University of New South Wales New South Wales Australia

ISBN: (数字)9798331518523

ISBN: (纸本)9798331518530

The decentralization of energy systems, driven by rapid adoption of renewable energy sources, has posed new challenges in communication, data sharing, and energy trading. Traditional grid structures rarely cope with the fast-changing dynamics of distributed generation resources (DERs), thus demanding smarter and scalable communication networks and mechanisms of synchronizing and optimizing operations. The set of technologies on AI-driven and tokenization-like approaches practically allows for the change. AI-driven networks support this by enabling real-time decision-making and predictive analytics through smart energy distribution and demand forecasting and massively automated grid optimization. Tokenization, reinforced by blockchain technologies, allows the decentralization of energy trading through transparent peer-to-peer (P2P) transactions that ease the encumbrances of the traditional utility. The paper focuses on how AI-driven networks and tokenization integrate to form the future communication networks in energy systems. It highlights their contribution to improving grid efficiency, securing grid infrastructure, diminishing operational costs, and democratizing energy markets. Additionally, it discusses technical challenges, regulatory barriers, and long-term implications while looking ahead and thinking about how these innovations can be used to reorganize energy infrastructures all over the globe and rapidly quicken the shift to decentralized sustainable energy ecosystems.

关键词： Technological innovation Renewable energy sources Tokenization Real-time systems Communications technology Peer-to-peer computing Distributed power generation Blockchains Communication networks Predictive analytics

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Enhancing Cybersecurity in Sustainable Energy: Regulatory Compliance, Challenges, and Policy Innovations

Enhancing Cybersecurity in Sustainable Energy: Regulatory Co...

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Sustainable Energy Technologies and Computational Intelligence (SETCOM), International Conference on

作者： Shruti Saxena Shivani Saxena Nikunj Tahilramani Ujjawal Patel Vandana P. Talreja Ashish Patel Dept. of School of Cyber Security & Digital Forensics National Forensics Sciences University Gandhinagar India Dept. of Computer Sciences & Engineering Institute of Advanced Research Gandhinagar India Dept. of Big Data Analytics Adani Institute of Digital Technology Management Gandhinagar India Electrical engg.dept R.C.Technical Institute Ahmedabad India Sr AWS AI ML Solution Architect IBM India

ISBN: (数字)9798331520540

ISBN: (纸本)9798331520557

The global switch to renewable energy is both a necessity for sustainable development and climate change mitigation. However, this transition is coupled with unique cyber security issues because of the greater reliance on networked digital systems. This paper identifies significant flaws in the current cyber security regulations and procedures while highlighting their effectiveness in the renewable energy sector. Recent research with the analysis highlighted the necessity of adaptable regulatory tools and the particular vulnerabilities that exist in renewable energy networks. According to the report, stronger regulations on the policymaking side must be enforced: rigorous regulatory compliance, increased robustness, and the incorporation of newer security practices that address changing threats. We explore how the integration of cutting-edge technology such as artificial intelligence (AI) could strengthen system resilience using current case studies like China’s renewable energy projects and Germany’s Energiewende. Furthermore, the importance of cybersecurity in the attainment of the Sustainable Development Goals (SDGs) is evaluated based on how it supports environmental conservation, economic development, and renewable energy. This research will aid the stakeholders and policymakers in making a safe and sustainable energy future.

关键词： Renewable energy sources Climate change Energy measurement Regulation Stakeholders Sustainable development Artificial intelligence computer crime computer security Risk management

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Intelligent Operational Decision Support System for Sugar Factory Resource Efficiency

Intelligent Operational Decision Support System for Sugar Fa...

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International Conference on Modern Electrical and Energy Systems (MEES)

作者： Nataliia Lutska Nataliia Zaiets Lidiia Vlasenko Stefan Junge Dept. of Automation and Computer Technologies of Control Systems National University of Food Technologies Kyiv Ukraine Dept. of Automation and Robotic Systems National University of Life and Environmental Sciences of Ukraine Kyiv Ukraine Dept. of Software Engineering and Cyber Security State University of Trade and Economics Kyiv Ukraine Dept. of Packaging Technology Berlin University of Applied Sciences Berlin Germany

With the economic crisis that is looming over the world due to changes in the energy sector and a reduction in the supply of certain types of products, energy and resource efficiency issues are becoming more relevant for the food industry. Also important is the preservation of the environment and the implementation of Cleaner Production trends. Most enterprises follow the concept of Industry 4.0 and increase efficiency through the implementation of intelligent methods, in particular machine learning. The paper proposes a neural network model of sugar production. The model makes it possible to predict the main estimates of resource efficiency used to correct the technological modes of production by the operator-technologist. The structure of the operational decision support system has been developed and is used by personnel to model and predict changes in resource efficiency estimates and KPIs calculated on their basis. Its feature is the integration of methods for achieving resource efficiency, improving environmental performance and ensuring KPIs. To do this, at the initial stage, an analysis of the main flows that affect resource efficiency and an assessment of their importance was carried out. Ensuring Production Performance is confirmed by the simulation and the adequacy of the created neural network accuracy of more than 95%.

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Enhancing Encrypted Internet Traffic Classification Through Advanced Data Augmentation Techniques

arXiv

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arXiv 2024年

作者： Zion, Yehonatan Aharon, Porat Dubin, Ran Dvir, Amit Hajaj, Chen Department of Computer Science Ariel Cyber Innovation Center Ariel University Israel Dept. of Computer and Software Eng. Ariel Cyber Innovation Center Ariel University Israel Department of Industrial Engineering and Management Data Science Artificial Intelligence Research Center Ariel University Israel

The increasing popularity of online services has made Internet Traffic Classification a critical field of study. However, the rapid development of internet protocols and encryption limits usable data availability. This paper addresses the challenges of classifying encrypted internet traffic, focusing on the scarcity of open-source datasets and limitations of existing ones. We propose two Data Augmentation (DA) techniques to synthetically generate data based on real samples: Average augmentation and MTU augmentation. Both augmentations are aimed to improve the performance of the classifier, each from a different perspective: The Average augmentation aims to increase dataset size by generating new synthetic samples, while the MTU augmentation enhances classifier robustness to varying Maximum Transmission Units (MTUs). Our experiments, conducted on two well-known academic datasets and a commercial dataset, demonstrate the effectiveness of these approaches in improving model performance and mitigating constraints associated with limited and homogeneous datasets. Our findings underscore the potential of data augmentation in addressing the challenges of modern internet traffic classification. Specifically, we show that our augmentation techniques significantly enhance encrypted traffic classification models. This improvement can positively impact user Quality of Experience (QoE) by more accurately classifying traffic as video streaming (e.g., YouTube) or chat (e.g., Google Chat). Additionally, it can enhance Quality of Service (QoS) for file downloading activities (e.g., Google Docs). © 2024, CC BY-NC-ND.

关键词： Quality of service

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Would ecological and technological consciousness shape e-vehicle purchase intentions? Insights from an emerging market

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Socio-Ecological Practice Research 2024年第1期6卷 55-67页

作者： Sharma, Hemendra Kovid, Raj K. Tewari, Alok Singh, Thipendra P. Choudhury, Tanupriya Ajeenkya DY Patil University Pune India Sharda School of Business Studies Sharda University Greater Noida India Faculty of Management Dr. A.P.J. Abdul Kalam Technical University Lucknow India School of Computer Science Engineering and Technology Bennett University Greater Noida India Symbiosis Institute of Technology Symbiosis International (Deemed University) Maharashtra Pune 412115 India CSE Dept. Graphic Era (Deemed to be University) Uttarakhand Dehradun 248002 India

Ecological consciousness is increasingly influencing receptivity of consumers toward electric vehicles by consumers. This study examines factors influencing Indian potential car buyers' intent to purchase electric vehicles by applying the theory of planned behavior (TPB) to assess the impact of technological consciousness, ecological consciousness, and opinion-seeking on their purchase intention. The survey method was used to collect data from 445 respondents in the northern region of India, employing a structured questionnaire. Responses were analyzed using structural equation modeling for testing the proposed hypotheses. The findings of the study reveal that attitude, subjective norms, perceived behavioral control, technological consciousness, ecological consciousness, and opinion-seeking significantly influence customers' intention to purchase electric vehicles. This study is a novel attempt to predict how ecological consciousness, technological consciousness, and opinion-seeking influence potential buyers’ intentions to purchase electric cars. In doing so, it extends the TPB in context of an emerging economy. © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2023.

关键词： Ecological consciousness Electric vehicles Opinion-seeking Technological consciousness Technology adoption

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Live Demo: E2P-Events to Polarization Reconstruction from PDAVIS Events

Live Demo: E2P-Events to Polarization Reconstruction from PD...

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2023 IEEE/CVF Conference on computer Vision and Pattern Recognition Workshops, CVPRW 2023

作者： Delbruck, Tobi Wang, Zuowen Mei, Haiyang Haessig, Germain Joubert, Damien Haque, Justin Chen, Yingkai Milde, Moritz B. Gruev, Viktor Univ. of Zurich and ETH Zurich Sensors Group Institute of Neuroinformatics Switzerland Center for Vision Automation & Control High-Performance Vision Systems AIT Austrian Institute of Technology Vienna Austria Western Sydney University Intl. Centre for Neuromorphic Systems The MARCS Institute Sydney Australia University of Illinois at Urbana-Champaign Dept. of Electrical and Computer Engineering UrbanaIL United States

This demonstration shows live operation of of PDAVIS polarization event camera reconstruction by the E2P DNN reported in the main CVPR conference paper Deep Polarization Reconstruction with PDAVIS Events (paper 9149 [... 详细信息

ISBN: (纸本)9798350302493

关键词： Polarization

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Decentralized Federated Learning for Nonintrusive Load Monitoring in Smart Energy Communities

Decentralized Federated Learning for Nonintrusive Load Monit...

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Mediterranean Conference on control and Automation (MED)

作者： Alessandro Giuseppi Sabato Manfredi Danilo Menegatti Antonio Pietrabissa Cecilia Poli Dept. of Computer Control and Management Engineering (DIAG) University of Rome "La Sapienza" Rome Italy Dept. of Electrical Engineering and Information Technology University of Naples "Federico II" Naples Italy National Centre for Innovative Technologies in Public Health (TISP) Istituto Superiore di Sanit&#x00E0 Rome Italy

ISBN: (数字)9781665406734

ISBN: (纸本)9781665406741

Federated Learning is a distributed learning solution for machine learning problems without the need of collecting the available data in a single centralized data centre. With the standard FL approaches, model training is performed locally and a centralized server collects and elaborates the trainable parameters of the local models: even if data are not shared, the presence of the centralized server still rises trust and security issues. In this work, we introduce the Decentralized Federated Learning (DECFEDAVG) algorithm, which aims at achieving complete decentralization by the lack of a coordination server, and compare its performance against the original federated learning algorithm Federated Averaging (FEDAVG) over the Nonintrusive Load Monitoring problem.

关键词： Training Load monitoring Distance learning Distributed databases Machine learning Collaborative work Data models

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controlling Weather Dependent Tasks Using Random Forest Algorithm 3

Controlling Weather Dependent Tasks Using Random Forest Algo...

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3rd International Conference on Advances in Electronics, computers and Communications, ICAECC 2020

作者： Mishra, Shivam Shukla, Aakash Arora, Sandeep Kathuria, Himandhu Singh, Mandeep HMR Institute of Technology Management Dept. of Computer Science Engineering Delhi India

ISBN: (纸本)9781728191836

A variety of tasks and works are depend directly or indirectly on the weather conditions. Sectors like agricultural sectors and industrial sectors are principally dependent on weather conditions. Weather conditions are also used to warn about natural disasters. These are the reasons that an accurate weather forecast is required to control the tasks dependent on the weather or to make decisions for these tasks according the weather forecast. The prediction of the weather using the right values of weather parameters is known as weather forecast. In this paper dataset for weather is taken for the training process and then random forest algorithm is used to predict the weather conditions to control different tasks which are dependent on these weather conditions directly or indirectly. The weather parameters used are temperature, pressure and humidity and the tasks which are taken in this study are irrigation, heath outcomes related to temperature and humidity. A hardware setup is used which works as a live weather station which sends the weather data on cloud platform. © 2020 IEEE.

关键词： Decision trees

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Pursuit-Evasion on a Sphere and When It Can Be Considered Flat

arXiv

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arXiv 2024年

作者： Milutinović, Dejan Von Moll, Alexander Manyam, Satyanarayana G. Casbeer, David W. Weintraub, Isaac E. Pachter, Meir Electrical and Computer Engineering Dept. University of California Santa Cruz Santa CruzCA United States The Control Science Center Aerospace Systems Directorate Air Force Research Laboratory DaytonOH45435 United States DCS Corporation DaytonOH United States Dept. of Electrical Engineering Air Force Institute of Technology Wright-Patterson AFB OH United States

In classical works on a planar differential pursuit-evasion game with a faster pursuer, the intercept point resulting from the equilibrium strategies lies on the Apollonius circle. This property was exploited for the construction of the equilibrium strategies for two faster pursuers against one evader. Extensions for planar multiple-pursuer single-evader scenarios have been considered. We study a pursuit-evasion game on a sphere and the relation of the equilibrium intercept point to the Apollonius domain on the sphere. The domain is a generalization of the planar Apollonius circle set. We find a condition resulting in the intercept point belonging to the Apollonius domain, which is the characteristic of the planar game solution. Finally, we use this characteristic to discuss pursuit and evasion strategies in the context of two pursuers and a single slower evader on the sphere and illustrate it using numerical *** Codes 58E10, 86A30, 37D40, 91A23, 49L12, 49Q10 © 2024, CC BY-NC-ND.

关键词： Spheres

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