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SSRN 2024年

作者： Li, Hexing Chronis, Ioannis Chen, Rui Wu, Yingrui Psomopoulos, Constantinos S. Tang, Chao College of Engineering and Technology Southwest University Chongqing400715 China International R & D Center for New Technologies of Smart Grid and Equipment Southwest University Chongqing400715 China High Voltage and Energy Systems Research Lab Dept. of Electrical and Electronics Engineering University of West Attica 250 Thivon & P. Ralli Ave. EgaleoGR-122 44 Greece

Furfural as an ageing product of cellulose paper can be detected by the furfural content in the oil. With the construction of green power grid, more and more power equipment adopts environmentally friendly insulating fluids. The investigation of the diffusion behaviors of furfural at different oil-paper interfaces can provide a basis for fault detection in power transformers. The liquid-solid interface diffusion behaviors of furfural in natural ester-cellulose paper and mineral oil-cellulose paper insulating systems are investigated by molecular dynamics simulation in this paper. Results show that the range of center-of-mass movement distances of furfural in mineral oil-cellulose paper is about 5 times that of natural ester-cellulose paper. The main reason for this is that the long-chain macromolecules composing the natural ester undergo curling in the extended flow. As a polar molecule, natural ester can attract furfural, a polar molecule. And the electrostatic potential mapping interval of furfural is about 4.4 times that of mineral oil, but 1.1 times that of natural ester, with which it overlaps more. These hinder the diffusion of furfural molecules in the natural ester-cellulose paper liquid-solid interface. © 2024, The Authors. All rights reserved.

关键词： Furfural

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Adaptive Siamese Tracking with a Compact Latent Network

arXiv

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arXiv 2023年

作者： Dong, Xingping Shen, Jianbing Porikli, Fatih Luo, Jiebo Shao, Ling The Inception Institute of Artificial Intelligence Abu Dhabi United Arab Emirates The State Key Laboratory of Internet of Things for Smart City Department of Computer and Information Science University of Macau China The Research School of Engineering The Australian National University Australia The Department of Computer Scienece University of Rochester United States Terminus AI Lab Terminus Group China

In this paper, we provide an intuitive viewing to simplify the Siamese-based trackers by converting the tracking task to a classification. Under this viewing, we perform an in-depth analysis for them through visual simulations and real tracking examples, and find that the failure cases in some challenging situations can be regarded as the issue of missing decisive samples in offline training. Since the samples in the initial (first) frame contain rich sequence-specific information, we can regard them as the decisive samples to represent the whole sequence. To quickly adapt the base model to new scenes, a compact latent network is presented via fully using these decisive samples. Specifically, we present a statistics-based compact latent feature for fast adjustment by efficiently extracting the sequence-specific information. Furthermore, a new diverse sample mining strategy is designed for training to further improve the discrimination ability of the proposed compact latent network. Finally, a conditional updating strategy is proposed to efficiently update the basic models to handle scene variation during the tracking phase. To evaluate the generalization ability and effectiveness and of our method, we apply it to adjust three classical Siamese-based trackers, namely SiamRPN++, SiamFC, and SiamBAN. Extensive experimental results on six recent datasets demonstrate that all three adjusted trackers obtain the superior performance in terms of the accuracy, while having high running speed. © 2023, CC BY-NC-ND.

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Coordination of networking and computing: toward new information infrastructure and new services mode

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Frontiers of Information Technology & Electronic engineering 2024年第5期25卷 629-632页

作者： Xiaoyun WANG Tao SUN Yong CUI Rajkumar BUYYA Deke GUO Qun HUANG Hassnaa MOUSTAFA Chen TIAN Shangguang WANG China Mobile Communications Corporation Beijing 100032China China Mobile Research Institute Beijing 100053China Department of Computer Science and Technology Tsinghua UniversityBeijing 100084China CLOUDS Lab School of Computing and Information SystemsUniversity of MelbourneMelbourneVIC 3010Australia National Key Laboratory of Information Systems Engineering National University of Defense TechnologyChangsha 410073China School of Computer Science Peking UniversityBeijing 100871China Intel Corporation Santa ClaraCA 95054USA State Key Laboratory for Novel Sofiware Technology Nanjing UniversityNanjing 210023China State Key Laboratory of Networking and Switching Technology Bejing University of Posts and TelecommunicationsBeijing 100876China

Computing,serving as the cornerstone of information processing,plays a pivotal role in the digital service ***"network"and"computing,"responsible for information transmission and processing respectively,traditionally belong to different stakeholders and have evolved ***,the recent trend toward the coordination and integration of computing and networks has garnered significant attention from both industry and *** such as"computility network"and"computing force network"have emerged,and the International Telecommunication Union-Telecommunication Standardization(ITU-T)has initiated efforts to develop standards for the coordination of networking and computing(CNC),focusing on the architecture and framework.

关键词： computing services network

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A comprehensive review of predictive analytics models for mental illness using machine learning algorithms

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Healthcare Analytics 2024年 6卷 100350-100350页

作者： Islam, Md. Monirul Hassan, Shahriar Akter, Sharmin Jibon, Ferdaus Anam Sahidullah, Md. Department of Software Engineering Daffodil International University Daffodil Smart City (DSC) Birulia Savar Dhaka 1216 Bangladesh Rising Research Lab Sheikh Bari Malancha Melandah Jamalpur Mymensingh 2012 Bangladesh Department of Computer Science and Engineering Gono Bishwabidyalay Savar Dhaka 1344 Bangladesh Department of Computer Science and Engineering Atish Dipankar University of Science and Technology Dhaka Bangladesh Department of Computer Science and Engineering IUBAT - International University of Business Agriculture and Technology Dhaka Bangladesh Department of Computer Science and Engineering Asian University of Bangladesh (AUB) Bangabandhu Road Tongabari Ashulia Dhaka 1349 Bangladesh

Our emotional, psychological, and social well-being are all parts of our mental health, influencing our thoughts, emotions, and behaviors. Mental health also influences how we respond to stress, interact with others, and make good or bad decisions. There has been growing interest in the use of machine learning for the early detection of mental illness. This study reviews the machine learning models, algorithms, and applications for the early detection of mental disease, particularly emphasizing the data modalities. We further propose a comprehensive methodology for assessing mental health that synergistically combines social media monitoring, data analytics from wearable devices, verbal polls, and individualized support. We provide an overview of the field's current state, highlight the potential benefits and challenges of using machine learning in mental health care, and a new taxonomy of mental disorders issues based on five domains of data types. We review existing research on using machine learning to detect and treat mental illness and discuss the implications for future research. Finally, the value of this work lies in its potential to provide a fast and accurate method for predicting the mental health status of a person, which may assist in the diagnosis and treatment of mental illness. © 2024 The Authors

关键词： Diagnosis Healthcare Machine learning classification Mental disorder taxonomy Mental illness prediction Mental illness treatment

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Fault Analysis of Microgrids with Inverter Interfaced Resources in Grid-Connected and Islanded Modes

Fault Analysis of Microgrids with Inverter Interfaced Resour...

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On-Line Conference (ONCON), Industrial Electronics Society Annual

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

The increasing penetration of inverter-based generation such as solar, wind and battery energy storage systems (BESS) has an impact on the fault currents in a microgrid. Also, if the microgrid is grid-connected or islanded affects the fault current. As such, it is important to conduct fault analysis of microgrids in grid-connected and islanded modes with different penetration levels of inverter-based generation sources to understand the impact of increasing levels of renewable energy on the fault currents. Different types of faults in a microgrid with inverter-based resources are simulated and the results are discussed and analyzed in this paper.

关键词： Wind energy generation Industrial electronics Renewable energy sources Wind energy Microgrids Inverters Batteries

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Supporting a 'Glocal' Energy Transition: from Local Energy Communities to Global Simulation Networks

Supporting a 'Glocal' Energy Transition: from Local Energy C...

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2023 International Conference on smart Energy systems and Technologies, SEST 2023

作者： Benedetto, G. Mazza, A. Pons, E. Bompard, E. De Paola, A. Thomas, D. Kotsakis, E. Fulli, G. Vogel, S. Monti, A. Bruno, S. Giannoccaro, G. Scala, M. La Bonfiglio, A. Invernizzi, M. Rossi, M. De Caro, F. Villacci, D. Politecnico di Torino & G-RTS Lab Department of Energy 'Galileo Ferraris' Turin Italy Joint Research Centre - European Commission Smart Grid Interoperability Laboratory Ispra Italy OPAL-RT Germany Aachen Germany Institute for Automation of Complex Power Systems Rwth Aachen University Aachen Germany Politecnico di Bari & LabZERO Department of Electrical & Information Engineering Bari Italy Università di Genova Electrical Electronics & Telecom. Eng. Naval Architecture Dep. Genoa Italy Università Del Sannio Department of Engineering Benevento Italy Università di Napoli 'Federico II' Department of Industrial Engineering Naples Italy

ISBN: (纸本)9798350397901

Managing a large share of non-dispatchable renewable energy sources requires new approaches, which have to be integrated with existing and well-established control systems currently used to guarantee power system operation. In this context, the number of energy communities is expected to increase, and hence their effective integration is fundamental. This paper aims at assessing the role and impact of energy communities on the operation of a transition power system, still having a share of active traditional power plants. Simulation models and real hardware have been included in the experiment, based on a live real-time co-simulation. The results highlight both the significant contribution that the methodology (i.e., geographically-distributed real-time co-simulation) can give in informing and driving energy transition policies and the important role that energy communities may have in supporting the transition towards completely de-carbonized power systems. © 2023 IEEE.

关键词： Renewable energy resources

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Ranking matters: Does the new format select the best teams for the knockout phase in the UEFA Champions League?

arXiv

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arXiv 2025年

作者： Csató, László Devriesere, Karel Goossens, Dries Gyimesi, András Lambers, Roel Spieksma, Frits Laboratory on Engineering and Management Intelligence Research Group of Operations Research and Decision Systems Budapest Hungary Institute of Operations and Decision Sciences Department of Operations Research and Actuarial Sciences Hungary Ghent University Department of Business Informatics and Operations Management Belgium FlandersMake@UGent – core lab CVAMO Ghent Belgium University of Pécs Hungary Eindhoven University of Technology Department of Mathematics and Computer Science Netherlands

Starting in the 2024/25 season, the Union of European Football Associations (UEFA) has fundamentally changed the format of its club competitions: the group stage has been replaced by a league phase played by 36 teams in an incomplete round robin format. This makes ranking the teams based on their results challenging because teams play against different sets of opponents, whose strengths vary. In this research note, we apply several well-known ranking methods for incomplete round robin tournaments to the 2024/25 UEFA Champions League league phase. Our results show that it is doubtful whether the currently used point-based system provides the best ranking of the *** Codes 15A06, 91B14 Copyright © 2025, The Authors. All rights reserved.

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Intelligent systems engineering in Open Pit Mines: Intelligent systems for Mining Fleet Management

Intelligent Systems Engineering in Open Pit Mines: Intellige...

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International Conference on Wireless Networks and Mobile Communications (WINCOM)

作者： Bnouachir Hajar Chergui Meriyem Medromi Hicham Engineering research laboratory (LRI) System Architecture Team (EAS) National and high school of electricity and mechanic (ENSEM) Hassan II University Casablanca Morocco Computer Science & Smart Systems (C3S) National and high school of electricity and mechanic (ENSEM) Hassan II University Casablanca Morocco

The open pit mining industry is a pillar of the global economy, yet it faces challenges in terms of safety, operational efficiency and environmental impact. To overcome these challenges, intelligent systems and artificial intelligence (AI) offer unique opportunities to improve the productivity and sustainability of mining. This article explores how intelligent systems engineering applied to the systems lifecycle is revolutionising the open pit mining industry. Applying this approach, we will define an intelligent real-time fleet management system for mining equipment (trucks, shovels), based on stakeholder requirements using SysML diagrams.

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Anti-Collision System for Accident Prevention in Underground Mines using computer Vision 22

Anti-Collision System for Accident Prevention in Underground...

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Proceedings of the 6th International Conference on Advances in Artificial Intelligence

作者： Mohamed Imam Karim Baïna Youness Tabii Intissar Benzakour Youssef Adlaoui El Mostafa Ressami El Hassan Abdelwahed Alqualsadi Research Team Rabat IT Center ENSIAS Mohammed V University in Rabat ENSIAS Morocco and Digitalization & Microelectronic Smart Devices - MAScIR Moroccan Foundation for Advanced Science Innovation and Research (MAScIR) Morocco Alqualsadi Research Team Rabat IT Center ENSIAS Mohammed V University in Rabat ENSIAS Morocco Information Retrieval and Data Analytics (IRDA) Research Team Rabat IT Center ENSIAS ENSIAS Morocco Reminex Research and Engineering center MANAGEM Group REMINEX Morocco Digitalization & Microelectronic Smart Devices - MAScIR Moroccan Foundation for Advanced Science Innovation and Research (MAScIR) Morocco Laboratory of Computer Systems Engineering (LISI) FSSM Cadi Ayyad University FSSM Morocco

ISBN: (纸本)9781450396943

Underground prospecting operations are often characterized by critical safety issues mainly due to poor visibility and blind spots around large vehicles and equipment. This can result in vehicle-to-vehicle collisions, as well as vehicle-to-pedestrian or structural-element collisions, resulting in accidents. In this article, we discuss an anti-collision system for pedestrian identification in deep mines under the premise that we are looking to prevent collisions with moving machinery. This study presents the findings from testing an image processing module and sensory system based on deep learnig in the context of "smart connected mine" project.

关键词： Yolov5 Pedestrian detection Deep Learning Underground mining

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Numerical Assessment of Microwave Bone Imaging: Reconstruction of Realistic Phantoms for Diagnosing Different Bone Diseases

Numerical Assessment of Microwave Bone Imaging: Reconstructi...

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International Conference on Applied Electromagnetics and Communications (ICECom)

作者： Alessia Cannatà Atif Shahzad Martin O’Halloran Adnan Elahi Marco Pasian Simona Di Meo Giulia Matrone Bilal Amin Dept. of Electrical Computer and Biomedical Engineering University of Pavia Pavia Italy Centre for Systems Modelling and Quantitative Biomedicine Institute of Metabolism and Systems Research University of Birmingham Birmingham UK School of Medicine University of Galway Galway Ireland Translational Medical Device Lab University of Galway Galway Ireland

Microwave imaging (MWI) can be used as an alternative modality for monitoring human bone health. So far, studies on microwave bone imaging have considered bone as a homogenous tissue; however, bone is composed of a cortical and trabecular layer having significantly different dielectric properties and microarchitecture. The trabecular bone is more susceptible to diseases like osteoporosis. Contrarily, osteoarthritis, another significant bone disease, has a more severe impact on cortical bone. Therefore, considering cortical and trabecular bone as two different bone types is of paramount importance for diagnosing different bone diseases. To this end, this study has made the first attempt to design and reconstruct the cortical and trabecular bone phantoms separately. The bone phantoms were designed as a single-layered heel-shaped structure. A Distorted Born Iterative Method (DBIM) approach in combination with the Iterative Method with Adaptive Thresholding for Compressed Sensing (IMATCS) has been employed for solving the electromagnetic inverse scattering problem. The simulation results have shown that the cortical and the trabecular bone can be distinguished based on the reconstructed dielectric properties even for low values of the signal-to-noise ratio (SNR). The findings of this study have shown that the adopted approach can be used to reconstruct the cortical and trabecular bones with reasonable accuracy and hence aid in monitoring different bone diseases based on their reconstructed dielectric properties.

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