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2023 IEEE Symposium Series on Computational Intelligence, SSCI 2023

作者： Artelt, Andre Malialis, Kleanthis Panayiotou, Christos G. Polycarpou, Marios M. Hammer, Barbara Bielefeld University Faculty of Technology Bielefeld Germany Kios Research and Innovation Center of Excellence Cyprus University of Cyprus Department of Electrical and Computer Engineering Nicosia Cyprus

ISBN: (纸本)9781665430654

Concept drift refers to a change in the data distribution affecting the data stream of future samples. Consequently, learning models operating on the data stream might become obsolete, and need costly and difficult adjustments such as retraining or adaptation. Existing methods usually implement a local concept drift adaptation scheme, where either incremental learning of the models is used, or the models are completely retrained when a drift detection mechanism triggers an alarm. This paper proposes an alternative approach in which an unsupervised and model-agnostic concept drift adaptation method at the global level is introduced, based on autoencoders. Specifically, the proposed method aims to 'unlearn' the concept drift without having to retrain or adapt any of the learning models operating on the data. An extensive experimental evaluation is conducted in two application domains. We consider a realistic water distribution network with more than 30 models in-place, from which we create 200 simulated data sets / scenarios. We further consider an image-related task to demonstrate the effectiveness of our method. © 2023 IEEE.

关键词： autoencoders concept drift adaptation data streams nonstationary environments

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Hybrid CNN & Random Forest Model for Effective Tea Leaf Disease Diagnosis 4

Hybrid CNN & Random Forest Model for Effective Tea Leaf Dise...

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4th International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies, ICAECT 2024

作者： Kumar, Ravi Ranjan Bhandari, Rahul Jain, Anuj Kumar Sharma, Neha Sharma, Vikrant Chawla, Sunil Chitkara University Institute of Engineering and Technology Chitkara University Vlsi Center of Excellence Punjab India Chandigarh University Department of Computer Science and Engineering Punjab Mohali India Chitkara University Institute of Engineering and Technology Chitkara University Punjab India Graphic Era Hill University Uttarakhand Dehradun India

ISBN: (纸本)9798350343670

Tea leaf diseases represent a substantial danger to tea plants and agricultural production. In this study, we investigate the usefulness of an automated learning-based technique for the exact classification of diverse tea leaf diseases. We used precision, recall, F1-Score, assistance, and overall accuracy as critical performance indicators to evaluate the categorization model's proficiency using a large dataset covering eight separate disease categories. The results revealed exceptional model performance, including precision, recall, and overall F1-Score values consistently surpassing 91% across all illness classes. The model achieved an amazing general precision of 98%, suggesting its ability to accurately recognize and distinguish between distinct tea leaf illnesses. This study sheds light on the potential of artificial intelligence as an effective tool for illness classification in leaves of tea. The findings are a significant resource for investigators, agronomists, and business practitioners working to improve tea leaf disease control, so adding to the long-term viability and efficiency of tea farms. © 2024 IEEE.

关键词： Precision Production Research Security

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A Strengthened Primal-Dual Decomposition Algorithm for Solving Electricity Market Pricing With Revenue-Adequacy and FFR Constraints

IEEE Transactions on Energy Markets, Policy and Regulation

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IEEE Transactions on Energy Markets, Policy and Regulation 2024年第3期2卷 379-391页

作者： Goudarzi, Hamed Hesamzadeh, Mohammad Reza Bunn, Derek Fotuhi-Firuzabad, Mahmud Shahidehpour, Mohammad Sharif University of Technology Center of Excellence in Power System Management and Control Tehran11365-11155 Iran Kth Royal Institute of Technology School of Electrical Engineering and Computer Science Stockholm10044 Sweden London Business School Department of Management Science and Operations LondonNW1 4SA United Kingdom Illinois Institute of Technology Electrical and Computer Engineering Department ChicagoIL60616 United States

This paper develops a new decomposition algorithm for solving Electricity Market Pricing (EMP) problem, taking into account both revenue-adequacy and Fast Frequency Reserve (FFR) constraints. Due to revenue-adequacy constraint, a bilevel model of the EMP problem is introduced (BL-EMP). The upper level of the BL-EMP model represents the non-convex unit commitment (UC) decisions as well as the revenue-adequacy constraints of the market participants (generators, loads, and battery-storage owner). The lower level is a convex economic dispatch model with FFR constraint. To tackle the computational complexity of the considered BL-EMP model, this paper develops, tests, and proposes a Strengthened Primal-Dual Decomposition (SPDD) algorithm, which takes benefits from both Benders-like and Lagrange Dual-like algorithms. The new SPDD algorithm has a series of interesting computational properties, which are theoretically discussed in the paper. The SPDD algorithm has better computational performance than standard Benders decomposition algorithm and it also does not need tuning of the Big-M (or disjunctive) parameters for solving the proposed BL-EMP problem. Results from the modified IEEE 24-bus, the IEEE 118-bus, and the IEEE 300-bus system show the superiority of proposed SPDD algorithm over the classic Benders algorithm. © 2023 IEEE.

关键词： Power markets

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DtS-IoT Resource Allocation Analysis Framework: Assessing DQ and RESS-IoT 10

DtS-IoT Resource Allocation Analysis Framework: Assessing DQ...

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10th IEEE World Forum on Internet of Things, WF-IoT 2024

作者： Gerard, Jason Fraire, Juan A. Ortigueira, Raydel Cespedes, Sandra Concordia University Department of Computer Science and Software Engineering Montreal Canada CONICET - Universidad Nacional de Córdoba Córdoba Argentina Universidad Técnica Federico Santa María Advanced Center for Electrical and Electronic Engineering Valparaíso Chile

ISBN: (纸本)9798350373011

The demand for expanding connectivity to remote and isolated areas has intensified the need for global Internet of Things (IoT) solutions. Direct-to-Satellite IoT (DtS-IoT), enabled by advances in nanosatellite technology, allows cost-effective global and direct connectivity between IoT devices and low Earth orbit satellites. However, the most cost-effective DtSIoT networks face resource limitations in user, ground, and space segments, demanding scalable solutions to fully realize their scalability potential. While several resource allocation protocols have been proposed for DtS-IoT, they have mainly been evaluated using static topologies or simplified simulations, overlooking the time-evolving orbital and channel dynamics crucial to DtS-IoT performance. This work bridges this gap by introducing the DtS-IoT Resource Allocation Analysis Framework (DRAAF), a comparison methodology and toolchain for evaluating resource allocation mechanisms in realistic DtS-IoT scenarios. Our method is framed in scalability, energy efficiency, throughput, delay, fairness, and overhead metrics. Utilizing FLoRaSat, a realistic LoRa-based DtS-IoT network simulator, we showcase the methodology with a use case investigating two energy-efficient MAC protocols for DtS-IoT: RESS-IoT and Distributed Queuing (DQ). Results indicate that DQ excels in throughput and node energy efficiency, whereas RESS-IoT reduces delay. Both protocols maintain satellite energy efficiency and enhance fairness in uplink transmissions. These findings underscore the value of our approach in evaluating resource allocation within complex DtS-IoT systems. © 2024 IEEE.

关键词： Scalability

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Competition Dynamics in the Meme Ecosystem

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ACM Transactions on Social Computing 2023年第3-4期6卷 1-19页

作者： Ford, Trenton W. Krohn, Rachel Weninger, Tim Integrated Science Center College of William and Mary 540 Landrum Dr WilliamsburgVA23185 United States Department of Computer Science and Software Engineering Rose-Hulman Institute of Technology Moench Hall Terre HauteIN47803 United States Department of Computer Science and Engineering 380 Fitzpatrick Hall University of Notre Dame Notre DameIN46556 United States

Creating and sharing memes is a common modality of online social interaction. Because of the prevalence of memes, an abundance of research focuses on understanding how memes are shared and perceived within their online social environment and in what ways they differ from other modalities of online communication. In the present work, we present findings that suggest a relationship between how memes are introduced, shared, and diminish in online social systems and the behavior of biological species within an ecosystem. Framed by this perspective, we borrow ecological methodologies and concepts like resource availability, speciation, and competition to study human attention, creativity, and sharing dynamics (respectively) over a large collection of memes shared on Reddit. Specifically, we find that the population of memes has scaled almost exactly with the total amount of content created over the past decade. We find a consequence of limited human attention in the face of a growing number of memes is that the diversity of memes has decreased at the community level, albeit slightly, in the same period. A further consequence is that the average life span of memes has decreased dramatically, which is further evidence of an increase in competition and a decrease in a meme species’ primary resource: human attention. From this work, we have found reasonable preliminary support for linking memes to species and, thus, meme research to ecological research. We believe that future research should work to strengthen this relationship and transfer more methodologies to meme and information research from ecology. © 2023 Copyright held by the owner/author(s)

关键词： Ecosystems

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Review of on-board conductive charger topologies for electric transportation

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International Journal of Power Electronics 2023年第4期17卷 406-442页

作者： Vijaya Anand, N. Jaya Sai Praneeth, A.V. Yalla, Naveen Sood, Vijay K. Department of EEE P.V.P. Siddhartha Institute of Technology Kanuru Vijayawada520007 India Advance Engineering Group Borg Warner Technical Center Bascharage Luxembourg Varanasi221005 India Department of Electrical Computer and Software Engineering Faculty of Engineering and Applied Science Ontario Tech University 2000 Simcoe Street North OshawaONL1H 7K4 Canada

This paper presents an overview of on-board conductive charger topologies for electric vehicles (EVs). Battery packs in electric and plug-in hybrid electric vehicles (EVs/PHEVs) need frequent energy refills to fulfil their duty cycles and overcome the range anxiety of vehicle owners. Due to the limited availability of fast charging infrastructures, all automotive manufacturers prefer an on-board battery charger in their vehicles. However, there are power level limitations for these chargers because of the weight, space and cost constraints. On-board charging systems can be either conductive or inductive. This paper reviews the topologies that are involved in conductive charging only. Globally, all automotive companies provide levels 1 and 2 for residential charging of vehicles. Single- and two-stage power converter topologies are summarised with their limitations. Furthermore, the current trends in the DC-DC converters for the two-stage conversion battery charger topologies are also outlined. This paper provides an overview of various topologies and configurations involved in EV charging with their limitations. © 2023 Inderscience Enterprises Ltd.

关键词： Topology

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Submarine Hunter: Efficient and Secure Multi-Type Unmanned Vehicles

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computers, Materials & Continua 2023年第7期76卷 573-589页

作者： Halah Hasan Mahmoud Marwan Kadhim Mohammed Al-Shammari Gehad Abdullah Amran Elsayed Tag eldin Ala R.Alareqi Nivin A.Ghamry Ehaa A.Lnajjar Esmail Almosharea Computer Center University of BaghdadBaghdad6751Iraq Department of Management Science and Engineering Dalian University of TechnologyLiaoningDalian116024China Department of Information Technology Faculty of Computer Sciences and Information Technology AL Razi UniversitySana’aYemen Faculty of Engineering and Technology Future University in EgyptNew Cairo11835Egypt Faculty of Engineering Mechanics Dalian University of TechnologyLiaoningDalian116024China Faculty of Computers and Artificial Intelligence Cairo UniversityGizaEgypt Department of Business Administration Dalian University of TechnologyLiaoningDalian116024China College of Software Engineering Dalian University of TechnologyChina

Utilizing artificial intelligence(AI)to protect smart coastal cities has become a novel vision for scientific and industrial *** of these AI technologies is using efficient and secure multi-environment Unmanned Vehicles(UVs)for anti-submarine *** study’s contribution is the early detection of a submarine assault employing hybrid environment UVs that are controlled using swarm optimization and secure the information in between UVs using a decentralized cybersecurity *** Dragonfly Algorithm is used for the orientation and clustering of the UVs in the optimization approach,and the Re-fragmentation strategy is used in the Network layer of the TCP/IP protocol as a cybersecurity *** research’s noteworthy findings demonstrate UVs’logistical capability to promptly detect the target and address the problem while securely keeping the drone’s geographical *** results suggest that detecting the submarine early increases the likelihood of averting a *** dragonfly strategy of sensing the position of the submersible and aggregating around it demonstrates the reliability of swarm intelligence in increasing access *** communication between Unmanned Aerial Vehicles(UAVs)improves the level of secrecy necessary for the *** swarm navigation is based on a peer-to-peer system,which allows each UAV to access information from its ***,in turn,helps the UAVs to determine the best route to take and to avoid collisions with other *** dragonfly strategy also increases the speed of the mission by minimizing the time spent finding the target.

关键词： Unmanned vehicles unmanned aerial vehicles unmanned underwater vehicles high altitude unmanned aerial vehicles anti-submarine warfare re-fragmentation dragonfly algorithm

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Cyber Security Threats on Multifunctional Devices and Mitigation Techniques 2

Cyber Security Threats on Multifunctional Devices and Mitiga...

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2nd International Conference on Business Analytics for Technology and Security, ICBATS 2023

作者： Al-Dmour, Nidal A. Farooq, Umer Sarwar, Irfan Iqbal, Muhammad Waseem Aqeel, Muhammad Khan, Wasim Ahmad Al Hamadi, Hussam Mutah University College of Engineering Department of Computer Engineering Jordan LGU Department of Computer Science Lahore Pakistan Superior University Department of Computer Science Lahore54000 Pakistan Superior University Department of Software Engineering Lahore54000 Pakistan NCBA&E Lahore School of Computer Science Pakistan Applied Science Research Center Applied Science Private University Amman11937 Jordan University of Dubai College of Engineering and IT PO Box 14143 United Arab Emirates

ISBN: (纸本)9798350335644

The risks discussed in this document are related to smart printers/ fax/ photocopiers/ or e-mail-enabled smart devices, also known as "document centers,". These devices can be purchased outright or rented every month. When an item reaches its end of life, it is either donated to a non-profit organization or returned to the manufacturer (OEM) or supplier at the end of a lease arrangement. These network-interconnected devices have an inherent susceptibility that most IT operations teams or information security professionals are unaware of. This effort will raise awareness of the dangers of losing a company's data. This discussion will focus on reported vulnerabilities, previous discussions, and given the author's view on the potential danger. Create instructions for potential users on how to use and disassemble these devices safely to prevent losing sensitive data. Lastly, the technological structure of two potential attack vectors against a document center of an organization will be demonstrated in this study. The study was conducted in government as well as the private sector, medium-sized enterprises (300 employees of each entity) settings, outside of normal business hours, with special authorizations and engagement, limiting the scope to a minimal set of devices. © 2023 IEEE.

关键词： Sensitive data

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A PID-incorporated Latent Factorization of Tensors Approach to Dynamically Weighted Directed Network Analysis

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IEEE/CAA Journal of Automatica Sinica 2022年第3期9卷 533-546页

作者： Hao Wu Xin Luo MengChu Zhou Muhyaddin J.Rawa Khaled Sedraoui Aiiad Albeshri Chongqing Institute of Green and Intelligent Technology Chinese Academy of SciencesChongqing 400714and also with the University of Chinese Academy of SciencesBeijing 100049China Department of Electrical and Computer Engineering New Jersey Institute of TechnologyNewark NJ 07102 USA IEEE Center of Research Excellence in Renewable Energy and Power Systems Department of Electrical and Computer EngineeringFaculty of Engineeringand K.A.CARE Energy Research and Innovation CenterKing Abdulaziz UniversityJeddah 21589Saudi Arabia College of Engineering King Abdulaziz UniversityJeddah 21589Saudi Arabia Department of Computer Science King Abdulaziz UniversityJeddah 21481Saudi Arabia

A large-scale dynamically weighted directed network(DWDN)involving numerous entities and massive dynamic interaction is an essential data source in many big-data-related applications,like in a terminal interaction pattern analysis system(TIPAS).It can be represented by a high-dimensional and incomplete(HDI)tensor whose entries are mostly *** such an HDI tensor contains a wealth knowledge regarding various desired patterns like potential links in a DWDN.A latent factorization-of-tensors(LFT)model proves to be highly efficient in extracting such knowledge from an HDI tensor,which is commonly achieved via a stochastic gradient descent(SGD)***,an SGD-based LFT model suffers from slow convergence that impairs its efficiency on large-scale *** address this issue,this work proposes a proportional-integralderivative(PID)-incorporated LFT *** constructs an adjusted instance error based on the PID control principle,and then substitutes it into an SGD solver to improve the convergence *** studies on two DWDNs generated by a real TIPAS show that compared with state-of-the-art models,the proposed model achieves significant efficiency gain as well as highly competitive prediction accuracy when handling the task of missing link prediction for a given DWDN.

关键词： Big data high dimensional and incomplete(HDI)tensor latent factorization-of-tensors(LFT) machine learning missing data optimization proportional-integral-derivative(PID)controller

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The Impact of Weather Conditions on the Harmonic Behaviour of Grid-Connected Photovoltaic Systems 13

The Impact of Weather Conditions on the Harmonic Behaviour o...

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13th International Conference on Power, Energy and Electrical engineering, CPEEE 2023

作者： Althobiti, Ahmad Awadh Almalki, Faisal Alhussainy, Abdullah Ali Alghamdi, Sultan Rawa, Muhyaddin Al-Turki, Yusuf A. King Abdulaziz University K. A. Care Energy Research and Innovation Center Department of Electrical and Computer Engineering Jeddah21589 Saudi Arabia King Abdulaziz University Department of Electrical and Computer Engineering Jeddah Saudi Arabia King Abdulaziz University Smart Grids Research Group Center of Research Excellence in Renewable Energy and Power Systems Department of Electrical and Computer Engineering Jeddah21589 Saudi Arabia King Abdulaziz University K. A. Care Energy Research and Innovation Center Smart Grids Research Group Center of Research Excellence in Renewable Energy and Power Systems Department of Electrical and Computer Engineering Jeddah21589 Saudi Arabia

ISBN: (纸本)9781665490146

The utilization of solar photovoltaic systems has seen a marked uptick in recent years. Research efforts have been geared towards improving efficiency and reducing the cost of solar PV plants. In light of concerns over the potential consequences of high penetration of PV systems, governments have been implementing renewable energy programs. This study presents a time-domain model for analyzing harmonic effects in utility-scale PV plants under varying levels of irradiance and temperature conditions. © 2023 IEEE.

关键词： Harmonic analysis

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