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arXiv 2024年

作者： Wang, Jingyi Xia, Xiaobo Lan, Long Wu, Xinghao Yu, Jun Yang, Wenjing Han, Bo Liu, Tongliang The Department of Intelligent Data Science College of Computer Science and Technology National University of Defense Technology Changsha410073 China The Trustworthy Machine Learning Lab School of Computer Science Faculty of Engineering University of Sydney DarlingtonNSW2008 Australia The State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and Engineering Beihang University Beijing100191 China The Department of Automation University of Science and Technology of China Hefei230026 China The Department of Computer Science Hong Kong Baptist University Hong Kong

Given data with noisy labels, over-parameterized deep networks suffer overfitting mislabeled data, resulting in poor generalization. The memorization effect of deep networks shows that although the networks have the ability to memorize all noisy data, they would first memorize clean training data, and then gradually memorize mislabeled training data. A simple and effective method that exploits the memorization effect to combat noisy labels is early stopping. However, early stopping cannot distinguish the memorization of clean data and mislabeled data, resulting in the network still inevitably overfitting mislabeled data in the early training stage. In this paper, to decouple the memorization of clean data and mislabeled data, and further reduce the side effect of mislabeled data, we perform additive decomposition on network parameters. Namely, all parameters are additively decomposed into two groups, i.e. , parameters w are decomposed as w = σ + γ. Afterward, the parameters σ are considered to memorize clean data, while the parameters γ are considered to memorize mislabeled data. Benefiting from the memorization effect, the updates of the parameters σ are encouraged to fully memorize clean data in early training, and then discouraged with the increase of training epochs to reduce interference of mislabeled data. The updates of the parameters γ are the opposite. In testing, only the parameters σ are employed to enhance generalization. Extensive experiments on both simulated and real-world benchmarks confirm the superior performance of our method. The implementation is available at: https://***/wangjingyi9924/TNLPAD. Copyright © 2024, The Authors. All rights reserved.

关键词： Benchmarking

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Fusionfrfcm: An Image Fusion Approach Driven by Non-Global Fuzzy Pre-Enhancement Framework

SSRN

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SSRN 2024年

作者： Zhang, Xiangbo Liu, Gang Huang, Lei Ning, Shangkun Bavirisetti, Durga Prasad School of Automation Engineering Shanghai University of Electric Power Shanghai201306 China Shanghai Shishang Information Technology Co. Ltd Shanghai201306 China Library Shanghai University of Electric Power Shanghai201306 China Department of Computer Science Faculty of Information Technology and Electrical Engineering Norwegian University of Science and Technology Trondheim7034 Norway

Most of the existing image fusion models adopt a global strategy, which usually reduces the contrast of infrared images. In this paper, we propose an image fusion approach driven by a non-global fuzzy pre-enhancement framework (FusionFRFCM), which is more suitable for the structure of the infrared (IR) image. A contrast equalization algorithm based on Fourth-order Partial Differential Equation (FPDE) algorithm is proposed, which is used to enhance the background region. Due to the differences between IR and visible (VIS) images, a hybrid fusion strategy based on Expectation Maximization algorithm (EM) and Principal Component Analysis algorithm (PCA) is designed. Compared with other state-of-the-art fusion methods, the experimental results show that the proposed algorithm has better fusion performance in both qualitative and quantitative results. In addition, to verify the effectiveness of our proposed FusionFRFCM in practical application, the fusion framework is embedded into the RGBT target tracking task under the VOT-RGBT2019 and OTCBVS datasets. Through comparative experiments, it is found that the FusionFRFCM framework can easily be integrated with the tracking task and can improve the tracking accuracy in many scenes. © 2024, The Authors. All rights reserved.

关键词： Image fusion

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A novel strategy for sparse attack detection and localization in secure state estimation of power systems

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Electric Power Systems Research 2025年 248卷

作者： Marzieh Samimiat Ali-Akbar Ahmadi Abolfazl Nateghi Manoochehr Kelarestaghi Industrial Automation laboratory Electrical and Computer Engineering Department Kharazmi University Tehran Iran Electrical and Computer Engineering Department Faculty of Engineering Kharazmi University Tehran Iran

In this paper, problem of secure state estimation in power systems in the presence of sparse attack is investigated. Using secure measurements technique for the first time, the required secure measurements are determined for each sparse attack. In the proposed scheme, it is not necessary that all measurements be encoded or transmitted in a dedicated communication channels such as fiber optic links. Therefore, implementation of it is cost-effective. Using the secure measurements technique, modified measurement Jacobian matrices are obtained and then modified residual vectors are designed. The residual vectors are designed such that only one detector is reacted to the specific sparse attack, so attacks are localized. The design procedure is based on a simple search which can be done easily and in a fast manner even for the large power systems. Due to the fact that the exact location of the attack in the power system is identified (measurements under the sparse attack), an algorithm is proposed that obtains the correct state estimation. The simulation results on the IEEE-14 bus power system are presented to show the effectiveness of the proposed scheme.

关键词： Bad data detection algorithms Consistent set Detection and localization Minimum sparse attack Similar sparse attack set

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A Technical Framework for Selection of Autonomous UAV Navigation Technologies and Sensors

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computers, Materials & Continua 2021年第8期68卷 2771-2790页

作者： Izzat Al-Darraji Morched Derbali Houssem Jerbi Fazal Qudus Khan Sadeeq Jan Dimitris Piromalis Georgios Tsaramirsis Department of Automated Manufacturing University of BaghdadBaghdadIraq Department of Mechanical Engineering University of KirkukIraq Department of Information Technology Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Industrial Engineering College of EngineeringUniversity of Ha’ilHail1234Saudi Arabia Department of Computer Science&IT University of Engineering&Technology PeshawarPakistan Department of Automation University of West AtticaAthensGreece Abu Dhabi Women’s College Higher Colleges of TechnologyAbu DhabiUAE

The autonomous navigation of an Unmanned Aerial Vehicle(UAV)relies heavily on the navigation *** UAV’s level of autonomy depends upon the various navigation systems,such as state measurement,mapping,and obstacle *** the correct components is a critical part of the design ***,this can be a particularly difficult task,especially for novices as there are several technologies and components available on the market,each with their own individual advantages and *** example,satellite-based navigation components should be avoided when designing indoor *** them in the design brings no added value to the final product and will simply lead to increased cost and power *** issue is the number of vendors on the market,each trying to sell their hardware solutions which often incorporate similar *** aim of this paper is to serve as a guide,proposing various methods to support the selection of fit-for-purpose technologies and components whilst avoiding system layout *** paper presents a study of the various navigation technologies and supports engineers in the selection of specific hardware solutions based on given *** selection methods are based on easy-to-follow flow charts.A comparison of the various hardware components specifications is also included as part of this work.

关键词： UAV navigation sensors selection UAV navigation autonomous navigation UAV development navigation sensors study navigation systems mapping systems obstacle-avoidance systems

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Long-Term Time Series Anomaly Detection with Transformer and Variational Autoencoder for Water Quality

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SSRN 2024年

作者： Lin, Yongze Qiao, Junfei Bi, Jing Yuan, Haitao Zhou, MengChu Beijing Laboratory of Smart Environmental Protection Beijing University of Technology Beijing100124 China Faculty of Information Technology Beijing University of Technology Beijing100124 China School of Automation Science and Electrical Engineering Beihang University Beijing100191 China Department of Electrical and Computer Engineering New Jersey Institute of Technology NewarkNJ07102 United States

In many fields, time series anomaly detection is gaining more and more attention, \textit{e.g.}, air pollution, geological hazards, and network traffic detection. Time series anomaly detection in water quality aims to identify anomalous samples. However, there are several challenges in anomaly detection of water quality time series: 1) Difficulty in obtaining local and global temporal dependencies of time series;2) Difficulty in learning a representation map from time series that enables effective discrimination of anomalies;and 3) Complex nonlinear relationship in water quality time series, making it difficult to detect long-term anomalies. To solve these problems, this work proposes a time series anomaly detection model called Transformer with Variational Autoencoder (TransVAE). First, this work integrates local and global temporal position embedding to improve temporally dependent representation. Second, It adopts a Variational Autoencoder (VAE) to fuse signals and reconstruct their expected distribution. Third, we use a Transformer to process nonlinear relationships in the time series and use residual mechanisms to improve long-term series anomaly detection accuracy. This work adopts two real-world datasets to evaluate the proposed TransVAE, and experiments demonstrate that TransVAE outperforms several state-of-the-art methods in terms of time series anomaly detection accuracy. © 2024, The Authors. All rights reserved.

关键词： Time series

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An Optimal Path Planning Method with Assigned Endpoints in Grid Maps

An Optimal Path Planning Method with Assigned Endpoints in G...

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IEEE Conference on Industrial Electronics and Applications (ICIEA)

作者： Xiaoxiong Wang Zhuo Wang Zhikang Ge Zhihong Man Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China School of Computer Science and Technology University of Chinese Academy of Sciences Beijing China Faculty of Science Engineering and Technology Swinburne University of Technology Melbourne Australia

ISBN: (数字)9798350360868

ISBN: (纸本)9798350360875

In this paper, an optimal path planning method with assigned endpoints is developed for complete coverage in grid maps. It is shown that, the complete coverage path can be generated by merging the coverage paths of multiple subregions. Initially, several path planning templates are constructed to minimize repetition in regular regions. Subsequently, the grid map is decomposed into multiple subregions based on the locations of the assigned endpoints. Each region is then traversed with the corresponding template according to the parity of the region. Finally, all paths within the subregions are merged to form a comprehensive coverage path. It is demonstrated that the resulting path exhibits minimal repetition while covering the grid map completely with assigned endpoints. Simulation results are provided to validate the excellent performance of presented path planning method.

关键词： Industrial electronics Simulation Merging Path planning Computational complexity

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Choosing a Suitable Requirement Prioritization Method: A Survey

arXiv

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arXiv 2024年

作者： Alhenawi, Esraa Awawdeh, Shatha Khurma, Ruba Abu García-Arenas, Maribel Castillo, Pedro A. Hudaib, Amjad Faculty of Information Technology Zarqa University Zarqa Jordan Applied Science Private University Amman Jordan MEU Research Unit Faculty of Information Technology Middle East University Amman11831 Jordan Department of Computer Engineering Automation and Robotics University of Granada Granada Spain King Abdullah II School for Information Technology The University of Jordan Amman Jordan

Software requirements prioritization plays a crucial role in software development. It can be viewed as the process of ordering requirements by determining which requirements must be done first and which can be done later. Powerful requirements prioritization techniques are of paramount importance to finish the implementation on time and within budget. Many factors affect requirement prioritization such as stakeholder expectations, complexity, dependency, scalability, risk, and cost. Therefore, finding the proper order of requirements is a challenging process. Hence, different types of requirements prioritization techniques have been developed to support this task. In this survey, we propose a novel classification that can classify the prioritization techniques under two major classes: relative and exact prioritization techniques class, where each class is divided into two subclasses. We depend in our classification on the way the value of ranking is given to the requirement, either explicitly as a specific value in the case of the exact prioritization techniques class, or implicitly in the case of the Relative prioritization technique class. An overview of fifteen different requirements prioritization techniques are presented and organized according to the proposed classification criteria’s. Moreover, we make a comparison between methods that are related to the same subclass to analyze their strengths and weaknesses. Based on the comparison results, the properties for each proposed subclass of techniques are identified. Depending on these properties, we present some recommendations to help project managers in the process of selecting the most suitable technique to prioritize requirements based on their project characteristics (number of requirements, time, cost, and accuracy). © 2024, CC BY.

关键词： Requirements engineering

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Integrated Extended SIR-type Epidemiological Modeling Platform for Covid-19

Integrated Extended SIR-type Epidemiological Modeling Platfo...

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E-Health and Bioengineering Conference (EHB)

作者： Adrian Brezulianu Iolanda Popa Oana Geman Iuliana Chiuchisan Carmen Nastase GREENSOFT S.R.L. Iasi Romania Computer Science Electronics and Automation Department Faculty of Electrical Engineering and Computer Science “Stefan cel Mare” University of Suceava Suceava Romania Faculty of Economics Administration and Business “Stefan cel Mare” University of Suceava

ISBN: (数字)9781665485579

ISBN: (纸本)9781665485586

In these conditions of Covid-19 pandemic, the design and implementation of an epidemiological modeling platform with an API-type integration with beneficiary entities and data providers is a priority for the healthcare system and other organizations. An epidemiological platform (PLIS), replicable and adaptable for managing an epidemic, based on an integrated extended SIR-type model, is presented in this paper. This solution has an open architecture, respecting the scalability and interoperability, requirements, and is based on international communication standards and protocols, and SOA technology.

关键词： COVID-19 Adaptation models Pathology Liver diseases Biological system modeling Scalability Standards organizations

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Event-based Video Reconstruction via Spatial-Temporal Heterogeneous Spiking Neural Network

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IEEE Transactions on Circuits and Systems for Video Technology 2025年

作者： Yu, Jiajie Lu, Xing Guo, Lijun Wang, Chong Li, Guoqi Qian, Jiangbo Ningbo University Faculty of Electrical Engineering and Computer Science Ningbo315211 China University of Nottingham Ningbo China Ningbo315100 China Ningbo University Merchants’ Guild Economics and Cultural Intelligent Computing Laboratory Ningbo315211 China Chinese Academy of Sciences Key Laboratory of Brain Cognition and Brain-inspired Intelligence Technology Institute of Automation Beijing100045 China

Event cameras detect per-pixel brightness changes and output asynchronous event streams with high temporal resolution, high dynamic range, and low latency. However, the unstructured nature of event streams means that humans cannot analyze and interpret them in the same way as natural images. Event-based video reconstruction is a widely used method aimed at reconstructing intuitive videos from event streams. Most reconstruction methods based on traditional artificial neural networks (ANNs) have high energy consumption, which counteracts the low-power advantage of event cameras. Spiking neural networks (SNNs) are a new generation of event-driven neural networks that encode information via discrete spikes, which leads to greater computational efficiency. Previous methods based on SNNs overlooked the asynchronous nature of event streams, leading to reconstructions that suffer from artifacts, flickering, low contrast, etc. In this work, we analyze event streams and spiking neurons and explain poor reconstruction quality. We specifically propose a novel spatial-temporal heterogeneous (STH) spiking neuron suitable for reconstructing asynchronous event streams. The STH neuron adjusts the membrane decay coefficient adaptively and has better spatiotemporal perception. In addition, we propose a temporal-frequency calibration module (TFCM) based on the Fourier transform to improve the contrast of the reconstructions. On the basis of the above proposed neuron and module, we construct two SNN-based models, referred to as the STHSNN and TFCSNN. The goal of the former is to reduce the artifacts and flickering in reconstructions, whereas the latter focuses on enhancing the contrast. The experimental results demonstrate that our models can yield reconstructions in various scenarios, achieving better quality and lower energy consumption than previous SNNs. Specifically, the TFCSNN and STHSNN achieve top-2 performance among the SNN-based models, with energy consumption reductions of 3.

关键词： Image reconstruction

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GreenChain: A Solana Blockchain-based Management Platform for Academic/Commercial Areas

GreenChain: A Solana Blockchain-based Management Platform fo...

引用

E-Health and Bioengineering Conference (EHB)

ISBN: (数字)9781665485579

ISBN: (纸本)9781665485586

Technologies based on distributed chains (blockchain) are compared, by some authors, as being as innovative as the transition from analog to digital, with revolutionary consequences in the medium and long term regarding the strategies for generating, transmitting, and storing data/information and the relationships between them. This paper presents a proposal for a management platform solution based on Solana blockchain and Agile software methodologies, for academic areas (for example, for the dissemination of doctoral theses) and also, for the commercial area (various types of economic contracts, etc.).

关键词： Costs Education Medical services Organizations Intellectual property Blockchains Security

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