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IEEE Transportation Electrification Conference and Expo (ITEC)

作者： Anindita Golder Sheldon S. Williamson Department of Electrical and Computer Engineering Smart Transportation Electrification and Energy Research (STEER) Group Advanced Storage Systems and Electric Transportation (ASSET) Laboratory Ontario Tech-Automotive Center of Excellence (ACE) Faculty of Engineering and Applied Science Ontario Tech University Oshawa Canada

ISBN: (数字)9798350317664

ISBN: (纸本)9798350317671

As the adoption for electric vehicles (EV) increases, the need for proper charging infrastructure also increases. As such, it is necessary to ensure proper charging infrastructure to meet the charging demand. Hence, studies concerning the planning of EV charging stations which include the sizing of distributed energy resources (DERs) in the station to reduce the peak demand on the grid. In this paper, EV charging stations were designed keeping in mind factors such as the EV charging load profile (on demand charging versus deferred charging), uncertainties in the load profile as well as the tariff rates. A sensitivity analysis was also carried out in order to examine the impact of several techno-economic parameters on the overall cost of the system.

关键词： Vehicle-to-grid Costs Uncertainty Sensitivity analysis Tariffs Vehicular ad hoc networks Transportation

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Data-Driven Adequacy and Security Assessment: Machine Learning Trends for Reliable Smart Energy Networks

Data-Driven Adequacy and Security Assessment: Machine Learni...

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Smart Grid Conference (SGC)

作者： Mohammad Mohsen Hayati Hassan Majidi Hossein Shahinzadeh Mehdi Abapour Mahmud Fotuhi-Firuzabad Gevork B. Gharehpetian Faculty of Electrical and Computer Engineering Energy Systems Research Institute (ESRI) University of Tabriz Tabriz Iran Department of Electrical Engineering Amirkabir University of Technology Tehran Iran Center of Excellence in Power System Management and Control (CEPSMC) Sharif University of Technology Tehran Iran

ISBN: (数字)9798331511333

ISBN: (纸本)9798331511340

Smart energy networks (SENs) face numerous challenges related to security, reliability, operational uncertainties, and increasing penetration of renewable energies (REs), necessitating advanced methodologies for adequacy and security assessment. This study delves into the utilization of machine learning-driven approaches (MLDAs) to quantify reliability and gauge the dependability of future sustainable SENs. By autonomously acquiring knowledge from datasets, MLDAs offer swift and reliable evaluations, surpassing traditional methodologies. The integration of artificial intelligence (AI) in enhancing power system reliability is highlighted, emphasizing the importance of extensive datasets and evolving AI algorithms. Data-driven approaches empower energy network operators to proactively identify and mitigate security risks, enhancing the reliability of critical infrastructure systems. The research underscores the significance of constructing reliable databases, addressing challenges in real-time operations, and ensuring the performance and trustworthiness of machine learning (ML) algorithms. Overall, the study showcases the potential of ML techniques in revolutionizing reliability management and risk assessment in smart energy networks, paving the way for sustainable and reliable power systems.

关键词： Uncertainty Machine learning algorithms Databases Machine learning Power system reliability Smart grids Management Reliability Security Risk management

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Semi-Supervised Graph Representation Learning with Human-centric Explanation for Predicting Fatty Liver Disease

arXiv

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arXiv 2024年

作者： Kim, So Yeon Wang, Sehee Choe, Eun Kyung Department of Artificial Intelligence Ajou University Suwon Korea Republic of Department of Software and Computer Engineering Ajou University Suwon Korea Republic of Department of Surgery Seoul National University Hospital Healthcare System Gangnam Center Seoul Korea Republic of

Addressing the challenge of limited labeled data in clinical settings, particularly in the prediction of fatty liver disease, this study explores the potential of graph representation learning within a semi-supervised learning framework. Leveraging graph neural networks (GNNs), our approach constructs a subject similarity graph to identify risk patterns from health checkup data. The effectiveness of various GNN approaches in this context is demonstrated, even with minimal labeled samples. Central to our methodology is the inclusion of human-centric explanations through explainable GNNs, providing personalized feature importance scores for enhanced interpretability and clinical relevance, thereby underscoring the potential of our approach in advancing healthcare practices with a keen focus on graph representation learning and human-centric explanation. © 2024, CC BY.

关键词： Diseases

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Expedited Block Transmission in Blockchain Network by using Clusters

Expedited Block Transmission in Blockchain Network by using ...

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2024 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2024

作者： Hua, Xiaoqi Chen, Jian Zhang, Peiyun Fu, Zhangjie Zhu, Haibin Lu, Kezhong Ren, Jigang School of Software Nanjing University of Information Science and Technology Nanjing210044 China Engineering Research Center of Digital Forensics of Ministry of Education The School of Computer Science Nanjing University of Information Science and Technology Nanjing210044 China School of Computer Science Nanjing University of Information Science and Technology Nanjing210044 China Nipissing University Department of Computer Science and Mathematics North BayONP1B 8L7 Canada School of Big Data and Artificial Intelligence Chizhou University Chizhou247000 China

ISBN: (纸本)9781665410205

Blockchain technology has garnered increasing attention from researchers. Because blockchain systems may contain malicious or spatially limited nodes that may delay block verification and reduce block transmission rate, this work proposes a block transmission model by designing and using special clusters. This work proposes the cluster formation and selection mechanisms. Nodes are grouped into clusters in a blockchain, and clusters with high fitness values are chosen to transmit blocks by calculating their trust values and block transmission rates. The proposed method is compared with the peers: Layer-Chain, BlockP2P-EP and RNS. According to experimental findings, the proposed method is superior to its peers regarding the time needed for block synchronization and transmission, block occupation storage ratio, transaction throughput, and block transmission success ratio. © 2024 IEEE.

关键词： Blockchain

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The effect of real-time pose recognition on badminton learning performance

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Interactive Learning Environments 2023年第8期31卷 4772-4786页

作者： Lin, Kuo-Chin Ko, Cheng-Wen Hung, Hui-Chun Chen, Nian-Shing Center for Physical and Health Education National Sun Yat-sen University Kaohsiung Taiwan Department of Computer Science and Engineering National Sun Yat-sen University Kaohsiung Taiwan Graduate Institute of Network Learning Technology National Central University Chung-Li Taiwan Institute for Research Excellence in Learning Sciences and Program of Learning Sciences National Taiwan Normal University Taipei Taiwan

Badminton is a very popular subject in Physical Education (PE). Many students enroll badminton courses in every semester which pose a tremendous teaching load to the instructors. The one-on-one guiding/feedback time provided by the instructor to each student is also greatly reduced. To overcome this challenge, some studies have tried to adopt pose recognition technique in teaching badminton. However, the lack of mobility and recognition accuracy problems hinder its applicability. To address this issue, a new pose recognition technique, OpenPose, was employed to develop a real-time pose recognition badminton teaching APP in this study. The APP was then installed on a mobile device to enhance badminton smash skill learning performance. The scores distribution of the experimental group shows majority of students achieved satisfactory performance, this implies the badminton teaching APP is helpful to all students no matter what their initial skill levels are. © 2021 Informa UK Limited, trading as Taylor & Francis Group.

关键词： badminton teaching motor skill learning physical education Pose recognition real-time feedback

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Worldwide Research Trends and Hotspot on IOMT Based on Bibliometric Analysis 20

Worldwide Research Trends and Hotspot on IOMT Based on Bibli...

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20th International computer Conference on Wavelet Active Media Technology and Information Processing, ICCWAMTIP 2023

作者： Zeeshan, Hafiz Muhammad Bin Heyat, Md Belal Bin Hayat, Mohd Ammar Parveen, Saba Akhtar, Faijan Sayeed, Eram Akhtar, Soha Singh, Priya Mohsin, Mohd Parveen, Saima Singh, Bandana Iqbal, Abid Li, Jian Ping Abdelgeliel, Asmaa Sayed National College of Business Administration and Economics Department of Computer Science Lahore Pakistan CenBRAIN Neurotech Center of Excellence School of Engineering Westlake University Hangzhou China M.A.H. Inter College Laxmipur Deoria India College of Electronics and Information Engineering Shenzhen University Shenzhen China School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu China Government Co-ed Sarvodaya Vidyalaya New Delhi India Hamdard Public School New Delhi India Dreamvessels Technology UP India Meerut Institute of Engineering and Technology Department of Electronics and Communication Engineering Meerut India Shah Abdul Latif University Department of Mathematics Khairpur Pakistan School of Media and Communication Shenzhen University Shenzhen China Central Library Prince Sultan University Riyadh Saudi Arabia South Valley University Botany & Microbiology Department Qena83523 Egypt

ISBN: (纸本)9798350318982

COVID-19's control hinges on precise virus identification in healthcare. The Internet of Medical Things (IoMT) denotes the online network of medical devices and apps facilitating data exchange. IoMT's recent rapid expansion indicates a rising use of internet-linked medical tools in healthcare. However, concerns about security and timely healthcare delivery impede IoMT-based application adoption. Safeguarding patient information and averting unauthorized access to medical systems remain paramount. Digital Clinical Trials (DCTs) are gaining significance, offering participation avenues regardless of time or location constraints. For their widespread adoption, IoMT and IoHT-based medical device development is crucial. The Internet of Health Things (IoHT), interlinking medical devices and apps, simplifies health data sharing. Scopus, a comprehensive academic database, was searched for IoMT-related papers between January 2017 and December 2022. Utilizing statistical tools like R, Biblioshiny, Bibliometrix, VOSviewer, and Microsoft Excel 365, 578 pertinent publications were analyzed, offering valuable insights. Additionally, 500 relevant papers were found in the Web of Science (WoS) database, contributing to this field's understanding and advancement. © 2023 IEEE.

关键词： Intelligent systems

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Solving water scarcity challenges in arid regions: A novel approach employing human-based meta-heuristics and machine learning algorithm for groundwater potential mapping

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Chemosphere 2024年 363卷 142859页

作者： Razavi-Termeh, Seyed Vahid Sadeghi-Niaraki, Abolghasem Farhangi, Farbod Khiadani, Mehdi Pirasteh, Saied Choi, Soo-Mi Dept. of Computer Science & Engineering and Convergence Engineering for Intelligent Drone XR Research Center Sejong University Seoul Korea Republic of Geoinformation Tech. Center of Excellence Faculty of Geodesy and Geomatics Engineering K.N. Toosi University of Technology Tehran19697 Iran School of Engineering Edith Cowan University 270 Joondalup Drive JoondalupWA6027 Australia Institute of Artificial Intelligence School of Mechanical and Electrical Engineering Shaoxing University China Department of Geotechnics and Geomatics Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai602105 India

Addressing water scarcity challenges in arid regions is a pressing concern and demands innovative solutions for accurate groundwater potential mapping (GPM). This study presents a comprehensive evaluation of advanced modeling techniques to enhance the precision of GPM. This study, conducted in the Zayandeh Rood watershed, Iran, employed a spatial database comprising 16 influential factors on groundwater potential and data from 175 wells. This study introduced an innovative approach to GPM by enhancing the Random Forest (RF) algorithm. This enhancement involved integrating three metaheuristic algorithms inspired by human behavior: ICA (Imperialist Competitive Algorithm), TLBO (Teaching-Learning-Based Optimization), and SBO (Student Psychology Based Optimization). The modeling process used 70% training data and 30% evaluation data. Data preprocessing was performed using the multicollinearity test method and frequency ratio (FR) technique to refine the dataset. Subsequently, the GPM was generated using four distinct models, demonstrating the combined power of machine learning and human-inspired metaheuristic algorithms. The performance of the models was systematically assessed through extensive statistical analyses, including root mean squared error (RMSE), mean absolute error (MAE), area under the curve (AUC) for the receiver operating characteristic curve (ROC), Friedman tests, chi-squared tests, and Wilcoxon signed-rank tests. RF-ICA and RF-SPBO emerged as frontrunners, displaying statistically comparable accuracy and significantly outperforming RF-TLBO and the non-optimized RF model. The results of the GPM revealed the exceptional accuracy of RF-ICA, which exhibited a commanding AUC score of 0.865, underscoring its superiority in discriminating between different groundwater potential classes. RF-SPBO also displayed strong performance with an AUC of 0.842, highlighting its effectiveness in inaccurate classification. RF-TLBO and the non-optimized RF model achieved AU

关键词： Geographic information systems

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Choosing the Discipline of Restoring computer Systems with Acceptable Degradation with Consolidation of Node Resources Saved After Failures 6

Choosing the Discipline of Restoring Computer Systems with A...

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6th International Scientific Conference on Information, Control, and Communication Technologies, ICCT 2022

作者： Bogatyrev, Vladimir A. Bogatyrev, Stanislav V. Bogatyrev, Anatoly V. Security Saint-Petersburg State University of Aerospace Instrumentation Department Information Systems Saint Petersburg Russia Itmo University Faculty of Software Engineering and Computer Systems Saint Petersburg Russia Yadro Cloud Storage Development Center Saint Petersburg Russia

ISBN: (数字)9781665493673

ISBN: (纸本)9781665493673

An approach to substantiating the choice of a discipline for the maintenance of a redundant computer system, with the possible use of node resources saved after failures, is considered. The choice is aimed at improving the reliability and profitability of the system, taking into account the operational costs of restoring nodes. Models of reliability of systems with service disciplines are proposed, providing both the possibility of immediate recovery of nodes after failures, and allowing degradation of the system when using node resources stored after failures in it. The models take into account the conditions of the admissibility or inadmissibility of the loss of information accumulated during the operation of the system. The operating costs are determined, taking into account the costs of restoring nodes for the system maintenance disciplines under consideration © 2022 IEEE.

关键词： Fault tolerance

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Control of Multipath Transmissions in the Nodes of Switching Segments of Reserved Paths 6

Control of Multipath Transmissions in the Nodes of Switching...

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6th International Scientific Conference on Information, Control, and Communication Technologies, ICCT 2022

作者： Bogatyrev, Vladimir A. Bogatyrev, Stanislav V. Bogatyrev, Anatoly V. Saint-Petersburg State University of Aerospace Instrumentation Department Information Systems Security Saint Petersburg Russia Itmo University Faculty of Software Engineering and Computer Systems Saint Petersburg Russia Yadro Cloud Storage Development Center Saint Petersburg Russia

ISBN: (数字)9781665493673

ISBN: (纸本)9781665493673

The options for ensuring timely delivery of packages to the addressee in networks with duplication of communication paths with the addressee for some subscribers are analyzed. Connecting subscribers to two communication routes with the addressee allows you to load-balance routes and carry out duplicated transmissions aimed at increasing the probability of delivering at least one copy of the transmitted packet in the required time. The possibilities of using route switch nodes for traffic management and replication of transmitted packets are analyzed. At the same time, two variants of duplicated transmissions are considered. For the first option, new replicas and ways of their transmission to the addressee are formed in one of the nodes connecting the existing paths by the first accepted replica. The replica coming in second is destroyed. For the second option, changing the transmission paths of replicas generated from the source in the nodes linking the paths is not carried out. The area of effectiveness of the proposed variants of duplicated transmissions is shown. The influence of the location of route switches on the timeliness of package delivery from subscribers connected to one or two communication paths with the addressee is investigated. The existence of an optimal arrangement of route switches is shown. © 2022 IEEE.

关键词： Real time control

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Current Trends in Automated Test Case Generation

Current Trends in Automated Test Case Generation

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Federated Conference on computer Science and Information Systems (FedCSIS)

作者： Tomas Potuzak Richard Lipka Department of Computer Science and Engineering/NTIS – New Technologies for the Information Society European Center of Excellence Faculty of Applied Sciences University of West Bohemia Plzen Czech Republic

The testing is an integral part of the software development. At the same time, the manual creation of individu-al test cases is a lengthy and error-prone process. Hence, an intensive research on automated test generation methods is ongoing for more than twenty years. There are many vastly dif-ferent approaches, which can be considered automated test case generation. However, a common feature is the generation of the data for the test cases. Ultimately, the test data decide the prog-ram branching and can be used on any testing level, starting with the unit tests and ending with the tests focused on the behavior of the entire application. The test data are also mostly independent on any specific technology, such as programming language or paradigm. This paper is a survey of existing literature of the last two decades that deals with test data generation or with tests based on it. This survey is not a systematic literature review and it does not try to answer specific scientific questions formulated in advance. Its purpose is to map and categorize the existing methods and to summarize their common features. Such a survey can be helpful for any teams developing their methods for test data generation as it can be a starting point for the exploration of related work.

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