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15th international conference on e Infrastructure and e Services for Developing Countries

作者： Abdalla, Rania Salih Ali, Elmustafa Sayed Mahbub, Sara A. Mokhtar, Rania A. Ahmed, Zeinab E. Taif Univ Dept Comp Engn Al Taif Saudi Arabia Red Sea Univ Dept Elect & Elect Engn Port Sudan Sudan Sudan Univ Sci & Technol Dept Elect Engn Khartoum Sudan Int Islamic Univ Malaysia Dept Elect & Comp Engn Kuala Lumpur Malaysia Univ Gezira Dept Comp Engn Wad Madani Sudan

ISBN: (纸本)9783031815690;9783031815706

Design of energy resources, transmission, distribution, and consumption in network architecture is becoming a challenging energy optimization issue. The demand for power analysis becomes a key pillar in sustainable renewable energy and adaptation to climate change. State-of-the-art technologies can play a vital role in realizing the new architectural design for smart grids and cities. The 4th generation mobile network is considered a critical technology and enabler. The 3GPP standard body is set to a target of 35% of the deployment of the 4G to be Low Power Wide Area (LPWA) network by 2020. LPWA is an Internet of Energy (IoE) structure that can provide a comprehensive stream of energy sector applications. The IoE with intelligent computing tools can dramatically enhance energy efficiency, improve and sustain renewable energy, and diminish energy contamination's ecological effects. This paper reviews the literature on the IoE design principles and architecture models comprehensively. it also explains IoE enabling technologies, including fog computing and various interoperability and data analysis standards.

关键词： Communications and measurement technology smart energy systems smart grid IoE Computational Tools IoE Design IoE Interoperability IoE Standards IoE Cyber Security

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Location Data Publishing Mechanism in Semi-Trusted Vehicle Networks based on Differential Privacy

Location Data Publishing Mechanism in Semi-Trusted Vehicle N...

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2024 international conference on Mechatronics and Intelligent Control, ICMIC 2024

作者： Zhao, Zheng Zhang, Tianhao Mao, Qian Zhao, Qi Xie, Xin Dalian Maritime University Dalian China Liaoning University Shenyang China Northeastern University Shenyang China Hunan University of Information Technology Changsha China Hunan Province Higher Education Key Laboratory of Intelligent Sensing and Computing Changsha China

ISBN: (数字)9781510686847

ISBN: (纸本)9781510686830

Vehicular ad-hoc networks (VANETs) are essential in mobile ad-hoc network applications, utilizing vehicle location data. However, safeguarding the privacy and security of this data is challenging, especially with untrusted roadside units. To address this, we propose a novel differential privacy-based location data publishing mechanism. It consists of three key components: dynamic group leader selection, data aggregation, and privacy-preserving data publishing. The group leader selection algorithm is based on directional thresholds, hop cycles, and lifespans, assuming semi-trusted vehicles. Additionally, the differential privacy-based algorithm uses map grid segmentation, privacy budget recovery, and a filtering mechanism to ensure location privacy. Comparative experiments show that our scheme outperforms existing models in total hops, group leader lifetime, and mean absolute error. © 2025 SPIE.

关键词： Differential privacy

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Variational Autoencoder Based Automatic Clustering for Multivariate Time Series Anomaly Detection 18th

Variational Autoencoder Based Automatic Clustering for Mult...

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18th international conference on Wireless Artificial Intelligent computing Systems and applications, WASA 2024

作者： Yan, Li Hu, Hailin Yang, Kun Wang, Gaozhou Guan, Ti Zheng, Yanwei State Grid Shandong Electric Power Company Information and Communication Company Beijing China State Grid Shandong Electric Power Company Beijing China School of Computer Science and Technology Shandong University Shandong China

ISBN: (纸本)9783031714696

Multivariate time series anomaly detection is of great significance in monitoring and ensuring the stable operation of complex systems. The multivariate time series generated in real scenes often have complex dependency patterns, summarized as temporal dynamics and spatial dynamics. Specifically, temporal dynamics manifested as complex dependencies between values at different timestamps, while spatial dynamics refer to uncertain similarity relationships between different sequences. In order to simultaneously model temporal and spatial dynamics, we propose a variational autoencoder based automatic clustering method for multivariate time series anomaly detection (ACVAE), which maps input sequences to latent representations using VAE and reconstructs input sequences based on the latent representations, while detecting anomalies based on reconstruction errors. Specifically, we design an encoder network that combines TCN and GRU to learn multi-scale long short-term temporal dependencies, and introduce the Dirichlet prior to automatically capture the similarity between sequences. Finally, we conduct extensive experiments on two publicly available datasets, and the results show that the ACVAE is superior to other baseline methods. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Time series

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Deep Reinforcement Learning Based Economic Dispatch with Cost Constraint in Cyber Physical Energy System 18th

Deep Reinforcement Learning Based Economic Dispatch with Co...

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18th international conference on Wireless Artificial Intelligent computing Systems and applications, WASA 2024

作者： Chen, Xue Cui, Chen Wang, Ning Zhang, Zhaogong He, Jinghong Guan, Xin Heilongjiang University Harbin150080 China State Grid Heilongjiang Electric Power Company Limited Harbin150090 China

ISBN: (纸本)9783031714696

The integration of renewable energy sources and carbon capture system in cyber physical energy system is the basis for coping with the challenge of global warming. It is very important to give full play to the role of carbon capture equipment to maximize carbon emission reduction. First of all, we propose a joint dispatch model for wind power, energy storage, and thermal power units, which may minimize the operation costs of system. Then an optimal dispatch model for wind power, energy storage, carbon capture, and thermal power units is established. In this model, the optimal operation cost of the economic dispatch with no carbon capture equipment is considered as one of the constraints, and the optimization goal is to minimize the carbon emissions of the economic dispatch. Due to the fact that the dispatch problem can be defined as a Markov decision process, deep reinforcement learning model is employed to solve the optimal dispatch problem in cyber physical energy system. The experimental results indicate that the proposed scheduling model can effectively reduce operation costs and carbon emissions. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Carbon capture and utilization

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A Cloud-Edge Integrated Water Extraction Using Superpixel Segmentation 18th

A Cloud-Edge Integrated Water Extraction Using Superpixel Se...

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18th international conference on Wireless Artificial Intelligent computing Systems and applications, WASA 2024

作者： Zhang, Qingmin Chen, Chen Zhou, Yang Wang, Zhiyi Jin, Fan Lu, Haitao Wan, Shaohua School of Communication Engineering Xidian University Xi’an China Xidian Hangzhou Institute of Technology Hangzhou311231 China The State Grid Jilin Province Electric Power Company Limited Information Communication Company Changchun130000 China National Key Laboratory of Science and Technology on Space Microwave CAST Xi’an710100 China Ningbo Joynext Technology Corporation Ningbo361000 China The Shenzhen Institute for Advanced Study University of Electronic Science and Technology of China Shenzhen518110 China

ISBN: (纸本)9783031714665

With the development of the Industrial Internet of Things (IIoT) and the proposal of smart water conservancy, the integration of the Internet of Things (IoT), edge computing, and computer vision for hydrological information monitoring has become a trend in water conservancy. Difficult to provide comprehensive hydrological data from hydrological observation stations, hydrological forecasting in uninformative basins has become one of the research hotspots. water extraction can provide support for many hydrological monitoring. However, The water is difficult to extract when the water in the near-water image has reflection and water surface ripples. We propose a multi-condition water extraction method based on superpixel segmentation under cloud-edge integration architecture. Firstly, based on the color characteristics of the water and the surrounding vegetation, we propose a reflection processing mechanism. Secondly, we propose a mechanism based on superpixel segmentation for the effect of reflection on water extraction. Then, we propose a contour correction mechanism. Finally, the flood-filling algorithm is used to extract the water. We compare the traditional image segmentation algorithm with our proposed segmentation method. The results show that the proposed method outperforms other algorithms in all evaluation metrics. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Image segmentation

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Synthesis of Dynamic Virtual-Inertia for Microgrid System applications

Synthesis of Dynamic Virtual-Inertia for Microgrid System Ap...

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2025 international conference on Intelligent Control, computing and Communications, IC3 2025

作者： Justo, Jackson J. Demidova, Galina Lukichev, Dmitry Poliakov, Nikolai Makolo, Peter Bansal, Ramesh C. Itmo University Faculty of Control System and Robotics Saint-Petersburg Russia University of Dar es Salaam Department of Electrical Engineering P.O. Box 33335 Dar es Salaam Tanzania United Republic of University of Sharjah Depatment of Electrical Engineering Sharjah United Arab Emirates University of Pretoria Department of Electric Electronic and Computer Engineering Pretoria South Africa

ISBN: (纸本)9798331527495

During the last two decades, interest in grid integrated renewable energy sources (RERs) into the electrical power grids has significantly grown. The motive being a promising strategy to reduce greenhouse gas emissions generated by conventional power plants (CPPs) and hence environmental consequences, decrease losses in distribution lines to improve power system supply efficiency and reliability to consumers. As a result, several CPPs are being replaced by RERs such as solar PV system, wind energy, micro hydro-turbine, fuel cell, and small gas power plants. These are installed close to customers on low-voltage and medium-voltage sites to reduce losses in the network and improve power quality, overall efficiency and reliability. However, grid-connected RERs via inverter decreases system inertia due to decrease in CPPs with rotating mass serving as an immediate natural response to frequency deviations following network disturbances. Therefore, this paper presents the design of dynamic virtual-inertia control (DVIC) scheme. The developed DVIC incorporates the mechanism to adjust active and reactive demand in response to any frequency and voltage variations to ensure system stability. To validate the suitability of the presented technique, MATLAB/Simulink model is developed and simulated under various operating scenarios. Using the results obtained simulation study, it is evidently the proposed DVIC shows improved performance is achieved than when no inertia control system applied. © 2025 IEEE.

关键词： Solar fuels

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Special section: Selected papers from the 7th IEEE/ACM international conference on grid computing (grid2006)

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FUTURE GENERATION COMPUTER SYSTEMS-THE international JOURNAL OF grid computing THEORY METHODS AND applications 2008年第5期24卷 402-403页

作者： Badia, Rosa M. Gannon, Dennis Lee, Craig Barcelona Supercomp Ctr Barcelona 08034 Spain Indiana Univ Dept Comp Sci Bloomington IN 47405 USA Aerosp Corp El Segundo CA 90245 USA

The highlights of the 7th IEEE/ACM international conference on grid computing held in Barcelona on September 28-29, 2006 were presented. The program for this conference covered all areas of grid computing research, which include Internet-based computing models, applications, including eScience and eBusiness applications, middleware and toolkits, and virtual Instrumentation. One of the paper presented an approach to grid scheduling that focused in the global cost optimization problem rather than in the details of individual applications taking into account the entire workload and dynamically adjusting to the varying service demands. Another contribution presented the design of a desktop grid implemented over a modified Peer-to-Peer architecture. Another paper summarized ongoing research and recent results on the development of flexible access control infrastructure for complex resource provisioning in grid-based collaborative applications and on-demand network services provisioning.

关键词： grid computing

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Feasibility Analysis Study on Constructing a grid Intrusion Detection System Using Semi-supervised Learning Models 2nd

Feasibility Analysis Study on Constructing a Grid Intrusion ...

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2nd international conference on Security and Information Technologies with AI, Internet computing and Big-data applications, SITAIBA 2023

作者： Tsai, Chia-Wei Lin, Jason Yang, Chun-Wei Loo, Fu-Nie Department of Computer Science and Information Engineering National Taichung University of Science and Technology No.129 Sec.3 Sanmin Rd North District Taichung404 Taiwan Department of Computer Science and Engineering National Chung Hsing University No. 145 Xingda Rd. South District Taichung40227 Taiwan Master Program for Digital Health Innovation China Medical University No. 100 Sec. 1 Jingmao Rd. Beitun Dist. Taichung406040 Taiwan

ISBN: (纸本)9789819777853

In recent years, due to the proliferation of information and communication technology, as well as AI technology, industrial control systems, which were once in a closed network environment, have also integrated related technologies and gradually connected to external networks. Although this can enhance the efficiency of industrial production, it greatly increases the information security threats to industrial control systems. Among them, the information security issues of critical infrastructures are a key issue. If these critical infrastructures are attacked by cyber hackers, it could pose threats that jeopardize the safety of the general population. In light of this, this study focuses on the critical infrastructure of the power grid, proposing a semi-supervised intrusion detection system (IDS) technology by using the one-class classification. It analyzes data from the electricity distribution system to assess whether the system has been attacked. This research employs a power grid dataset to train the proposed model and execute the experiments. The experimental results demonstrate the feasibility of the proposed method. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Network intrusion

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Special Section: Third IEEE international conference on e-Science and grid computing

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FUTURE GENERATION COMPUTER SYSTEMS-THE international JOURNAL OF grid computing-THEORY METHODS AND applications 2009年第4期25卷 444-445页

作者： Chiu, Kenneth Fox, Geoffrey C. SUNY Binghamton Dept Comp Sci Binghamton NY 13902 USA Indiana Univ Community Grids Lab Sch Informat Bloomington IN 47404 USA

The third IEEE international conference Computer Society's Technical Committee for Scalable computing (TCSC) brought together leading international and interdisciplinary research communities, developers, and users of e-science applications and IT technologies. The conference was organized by the Center for Development of Advanced computing (C-DAC). The themes included were enabling technologies, applications, workflow's, service-oriented architectures, resource management, scientific data management, sensors and instruments, and programming paradigms. The total of 206 papers from the continents of Asia, Australia, Europe, North and South America were received out of which the top 60 papers were selected for presentation in one of the sessions in the conference. Some technology areas covered included grid infrastructure, grid steering, grid monitoring, workflow and grid programming, scheduling, resource discovery and allocation, security and algorithms.

关键词： e-science grid computing Cyberinfrastructure

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Intelligent Urban Futures: Exploring AI and Machine Learning applications in Smart Cities 5th

Intelligent Urban Futures: Exploring AI and Machine Learning...

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5th international conference on Advances in Information Communication Technology and computing, AICTC 2024

作者： Yadav, Anit Kumar Sharma, Ajay Kumar Patel, Mayank Rathore, Narendra Singh Department of Computer Science Engineering GITS Udaipur India GITS Udaipur India

ISBN: (纸本)9789819761050

The primary goals of smart cities are efficiently managing the rapid urbanization process, energy consumption, environmental protection, citizen economic and living standards, and people's capacity to utilize and accept contemporary information and communication technology (ICT). The development, decision-making, implementation, and delivery of final, beneficial services under the smart city idea all depend on ICT. The aim of the research is to explore the development of smart cities in terms of AI, ML, and DRL. The methods discussed are effectively used to create the best plans of action for a variety of intricate problems pertaining to smart cities. A comprehensive review of prior approaches used in the fields of cyber-security, energy-efficient smart grid utilization, intelligent transportation systems (ITSs), effective use of UAVs to ensure optimal communications services that can even go beyond 5G, and smart cities with health care systems that are smart enough is provided in this survey. Ultimately, a number of research problems and potential future avenues where the aforementioned methodologies can flourish are detailed in order to make smart city concept real. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Smart city

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