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arXiv 2025年

作者： Zhang, Kunpeng Xu, Lei Yi, Xinlei Cao, Ming Johansson, Karl H. Chai, Tianyou Yang, Tao State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang110819 China Department of Mechanical Engineering University of Victoria VictoriaBCV8W 2Y2 Canada Shanghai Institute of Intelligent Science and Technology National Key Laboratory of Autonomous Intelligent Unmanned Systems Frontiers Science Center for Intelligent Autonomous Systems Ministry of Education Shanghai201210 China Engineering and Technology Institute Groningen Faculty of Science and Engineering University of Groningen GroningenAG 9747 Netherlands Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Sweden Digital Futures Stockholm10044 Sweden

This paper considers distributed online nonconvex optimization with time-varying inequality constraints over a network of agents. For a time-varying graph, we propose a distributed online primal–dual algorithm with compressed communication to efficiently utilize communication resources. We show that the proposed algorithm establishes an O(T max{1−θ1,θ1}) network regret bound and an O(T 1−θ1/2) network cumulative constraint violation bound, where T is the number of iterations and θ1 ∈ (0, 1) is a user-defined trade-off parameter. When Slater’s condition holds (i.e, there is a point that strictly satisfies the inequality constraints at all iterations), the network cumulative constraint violation bound is reduced to O(T 1−θ1). These bounds are comparable to the state-of-the-art results established by existing distributed online algorithms with perfect communication for distributed online convex optimization with (time-varying) inequality constraints. Finally, a simulation example is presented to validate the theoretical results. Copyright © 2025, The Authors. All rights reserved.

关键词： Convex optimization

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A SINS Error Correction Approach Based on Dual-Threshold ZV Detection and Cubature Kalman Filter

A SINS Error Correction Approach Based on Dual-Threshold ZV ...

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IEEE International Conference on Systems, Man and Cybernetics

作者： Ruijie Xu Shichao Chen Wenqiao Sun Yisheng Lv Jialiang Luo Ying Tang The State Key Laboratory for Management and Control of Complex System State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences College of Information Science & Technology Beijing University of Chemical Technology Beijing China The State Key Laboratory for Management and Control of Complex System State Key Laboratory of Multimodal Artificial Intelligence Systems The Center of National Railway Intelligent Transportation System Engineering and Technology Institute of Automation Chinese Academy of Sciences China Academy of Railway Sciences Corporation Limited Beijing China China Academy of Railway Sciences Corporation Limited Transportation and Economics Research Institute and the Center of National Railway Intelligent Transportation System Engineering and Technology Beijing China The State Key Laboratory for Management and Control of Complex System State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences Beijing China The State Key Laboratory for Management and Control of Complex System State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences School of Information Engineering China University of Geosciences Beijing Beijing China Department of Electrical and Computer Engineering Rowan University Glassboro USA

Global Navigation Satellite Systems (GNSS) can provide real-time positioning information for outdoor users, but cannot for indoor scenarios or heavily occluded outdoor scenarios. Strap-down Inertial Navigation System (SINS) are widely used to locate people in complex interior or heavily occluded outdoor scenarios due to its light weight and low power consumption. However, IMU of SINS are noisy, and the sampling data error is large, which is a divergence of the error with time. Therefore, it will generate a positioning accumulation error, which affects the final positioning accuracy. The problem of cumulative IMU errors is usually dealt with by Zero-Velocity Update (ZUPT). The zero-velocity detection part of basic ZUPT method usually uses a single threshold to determine the gait of pedestrian, which often has the problem of gait misjudgment and omission. To address these problems, this paper proposes a composite conditional detection method to solve the problem of misjudgment in the zero-velocity interval. In addition, we redesign the zero-velocity update algorithm and uses the Cubature Kalman filter (CKF) for pedestrian positioning error correction. The experimental results demonstrate that the proposed ZUPT method based on dual-threshold detection can better detect the interval between pedestrian motion and stationery than ones with single threshold. The zero-velocity update algorithm based on CKF has higher performance than conventional EKF and UKF methods, which constrains the cumulative error of SINS to about 0.2% of the whole walking distance.

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An enhanced MES strategy for economic recovery and low-carbon operations: Incorporating time-lag superposition and hydrogen-electricity interdependency in chain accidents

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Energy 2025年 330卷

作者： Chen, Jie Zhang, Hongwei Tang, Zao Cao, Yijia Hunan Engineering Research Center of Multi-Energy Cooperative Control Technology College of Automation and Electronic Information Xiangtan University Xiangtan411105 China Department of Automation Hangzhou Dianzi University Hangzhou310018 China College of Electrical and Information Engineering Hunan University Hunan 410000 China

Chain accidents pose a threat to the economic operation of Multi-Energy System (MES). By leveraging the coupling characteristics and time-lag effects of energy sources, losses during chain accidents can be mitigated through coordination among multiple energy systems, thereby offering an economically viable solution. Therefore, in this paper, an enhanced optimization method for MES following chain accidents is proposed. Firstly, a refined thermal-grid inertia model and a gas-grid inertia model are introduced, both of which can help mitigate time-lag effects during accidents in the MES. Secondly, a Z-score statistical measure enhancement strategy is proposed to address unregulated external energy procurement during chain accidents. By considering historical energy prices and their changing trends, this strategy ensures more efficient energy utilization during periods of low prices, thereby facilitating economic recovery under interconnected circumstances. Thirdly, to address the challenging problem of nonlinearity and non-convexity, auxiliary flow variables and piecewise linearization methods are introduced to simplify the solution and improve solving efficiency. Finally, the effectiveness of the proposed multi-level optimization method is confirmed through extensive case studies. Compared to the baseline method, the proposed method achieves a 45.9 % improvement in economic performance. © 2025 Elsevier Ltd

关键词： Energy utilization

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Initial Study on Implementation of Smoothing Filters for the Purpose of Bioimpedance Spectroscopy Parameters Classification

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IFAC-PapersOnLine 2022年第4期55卷 393-398页

作者： Aleksandra Kawala-Sterniuk Amir F. Al-Bakri Mariusz Pelc Katarzyna Cichoń Wojciech Chlewicki Stepan Ozana Radek Martinek Jakub Możaryn Volodymyr Khoma Halyna Kenyo Edward Jacek Gorzelańczyk Michał Podpora Jarosław Zygarlicki Opole University of Technology Faculty of Electrical Engineering Automatic Control and Informatics 45-758 Opole Poland Department of Biomedical Engineering College of Engineering University of Babylon 51001 Babylon Iraq University of Greenwich School of Computing and Mathematical Sciences SE10 9LS London UK West Pomeranian University of Technology in Szczecin Faculty of Electrical Engineering 70-313 Szczecin Poland Faculty of Mechatronics Warsaw University of Technology 02-525 Warsaw Poland Lviv Polytechnic National University Institute of Computer Technologies Automation and Metrology Lviv Ukraine Institute of Philosophy Kazimierz Wielki University 85-092 Bydgoszcz Poland Faculty of Mathematics and Computer Science Adam Mickiewicz University in Poznań 61-614 Poznań Poland

Bioimpedance is a commonly used method for various conditions monitoring. In this paper, the authors carried out some research where they implemented various smoothing filters to enable identification of the bioimpedance spectroscopy parameters. The proposed filtering methods may also be used for application on embedded systems, which have smaller computing power but have become recently very popular. The obtained results with the implementation of smoothing filters were promising, however, some of the obtained results were unsatisfactory. This work also contains a brief introduction to bioimpedance spectroscopy and smoothing filters.

关键词： Bioimpedance Spectroscopy smoothing-filtering Savitzky-Golay Filter Median Filtering Moving-Average Filters

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Formation control for mobile robot using fuzzy - PI controller

Formation control for mobile robot using fuzzy - PI controll...

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2020 International Conference on Advanced Robotics and Intelligent Systems, ARIS 2020

作者： Lee, Min-Fan Ricky Willybrordus, H.P.M. Sukamto Hassen, Sharfiden Nugroho, Asep National Taiwan University of Science and Technology Taipei Taiwan National Taiwan University of Science and Technology Department of Electrical Engineering Taipei Taiwan National Taiwan University of Science and Technology Department of Computer Science and Information Engineering Taipei Taiwan National Taiwan University of Science and Technology College of Graduate Institute of Automation and Control Taipei Taiwan National Taiwan University of Science and Technology Graduate Institute of Automation and Control Taipei Taiwan

ISBN: (纸本)9781728198231

Protecting soldiers in the long march of platoon formation is crucial mission in the military operation. Autonomous ground mobile robots can be deployed to carry out such kind of the mission. The primary task is maintaining robot position automatically based on the movement of soldier in a platoon formation. The GPS is employed to determine the soldier current pose. This information is used as an input to create a dynamic convex hull around a platoon. The Proportional-Integral (PI) controller is applied to control each robot so it can move in a desired trajectory. The fuzzy logic control (FLC) is involved to tune the gain of PI controller to optimize the performance. Three protective robots and nine soldiers are used to evaluate the algorithm in simulation. The proposed algorithm will provide a platoon soldiers with optimal protection encirclement and enhance their safety. The simulation results show good performance using the proposed controller. © 2020 IEEE.

关键词： Mobile robots

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Robust light bullets in Rydberg gases with moiré lattice

arXiv

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arXiv 2023年

作者： Li, Ze-Yang Li, Jun-Hao Zhao, Yuan Cui, Jin-Long He, Jun-Rong Ruan, Guo-Long Malomed, Boris A. Xu, Si-Liu School of Electronics and Information Engineering Hubei University of Science and Technology Xianning437100 China Laboratory of Optoelectronic Information and Intelligent Control Hubei University of Science and Technology Xianning437100 China School of Biomedical Engineering and Medical Imaging Xianning Medical College Hubei University of Science and Technology Xianning437100 China Department of Physical Electronics School of Electrical Engineering Faculty of Engineering Tel Aviv University P.O.B. 39040 Ramat Aviv Tel Aviv Israel Instituto de Alta Investigación Universidad de Tarapacá Casilla 7D Arica Chile

Rydberg electromagnetically-induced transparency has been widely studied as a medium supporting light propagation under the action of nonlocal nonlinearities. Recently, optical potentials based on moiré lattices (MLs) were introduced for exploring unconventional physical states. Here, we predict a possibility of creating fully three-dimensional (3D) light bullets (LBs) in cold Rydberg gases under the action of ML potentials. The nonlinearity includes local self-defocusing and long-range focusing terms, the latter one induced by the Rydberg-Rydberg interaction. We produce zero-vorticity LB families of the fundamental, dipole, and quadrupole types, as well as vortex LBs. They all are gap solitons populating finite bandgaps of the underlying ML spectrum. Stable subfamilies are identified utilizing the combination of the anti-Vakhitov-Kolokolov criterion, computation of eigenvalues for small perturbations, and direct simulations. Copyright © 2023, The Authors. All rights reserved.

关键词： Eigenvalues and eigenfunctions

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Robust Light Bullets in Rydberg Gases with Moiré Lattice

SSRN

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SSRN 2023年

作者： Li, Ze-Yang Li, Jun-Hao Zhao, Yuan Cui, Jin-Long He, Jun-Rong Ruan, Guo-Long Malomed, Boris A. Xu, Si-Liu School of Electronic and Information Engineering Hubei University of Science and Technology Xianning437100 China Laboratory of Optoelectronic Information and Intelligent Control Hubei University of Science and Technology Xianning437100 China School of Biomedical Engineering and Medical Imaging Xianning Medical College Hubei University of Science and Technology Xianning437100 China Department of Physical Electronics School of Electrical Engineering Faculty of Engineering Tel Aviv University P.O.B. 39040 Ramat Aviv Tel Aviv Israel Instituto de Alta Investigación Universidad de Tarapacá Casilla 7D Arica Chile

关键词： Eigenvalues and eigenfunctions

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Methodology for Detecting Non-Technical Energy Losses Using an Ensemble of Machine Learning Algorithms

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Computer Modeling in engineering & Sciences 2025年第5期143卷 1381-1399页

作者： Irbek Morgoev Roman Klyuev Angelika Morgoeva Department of Computer Modeling and Design Automation Faculty of Information Technology and Electronic EngineeringNorth Caucasian Institute of Mining and Metallurgy(State Technological University)Vladikavkaz362021Russia Department of Automation and Control Moscow Polytechnic UniversityMoscow107023Russia

Non-technical losses(NTL)of electric power are a serious problem for electric distribution *** solution determines the cost,stability,reliability,and quality of the supplied *** widespread use of advanced metering infrastructure(AMI)and Smart Grid allows all participants in the distribution grid to store and track electricity *** the research,a machine learning model is developed that allows analyzing and predicting the probability of NTL for each consumer of the distribution grid based on daily electricity consumption *** model is an ensemble meta-algorithm(stacking)that generalizes the algorithms of random forest,LightGBM,and a homogeneous ensemble of artificial neural *** best accuracy of the proposed meta-algorithm in comparison to basic classifiers is experimentally confirmed on the test *** a model,due to good accuracy indicators(ROC-AUC-0.88),can be used as a methodological basis for a decision support system,the purpose of which is to form a sample of suspected NTL *** use of such a sample will allow the top management of electric distribution companies to increase the efficiency of raids by performers,making them targeted and accurate,which should contribute to the fight against NTL and the sustainable development of the electric power industry.

关键词： Non-technical losses smart grid machine learning electricity theft fraud ensemble algorithm hybrid method forecasting classification supervised learning

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The stratified K-folds cross-validation and class-balancing methods with high-performance ensemble classifiers for breast cancer classification

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Healthcare Analytics 2023年 4卷 100247-100247页

作者： T R, Mahesh V, Vinoth Kumar V, Dhilip Kumar Geman, Oana Margala, Martin Guduri, Manisha Department of Computer Science and Engineering Faculty of Engineering and Technology JAIN (Deemed-to-be University) Bangalore 562112 India School of Computer Science Engineering & Information Systems (SCORE) Vellore Institute of Technology (VIT) 632014 India School of Computing Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Chennai 600062 India Department of Computers Electronics and Automation Faculty of Electrical Engineering and Computer Science Stefan cel Mare University of Suceava Suceava 720229 Romania School of Computing and Informatics University of Louisiana at Lafayette United States

Breast cancer is one of the most common causes of death among women, and early diagnosis is vital for reducing the fatality rate. This study evaluates the most widely used machine-learning breast cancer prediction and diagnosis methods. We use synthetic minority over-sampling to handle imbalanced data in the breast cancer diagnosis dataset obtained from the Wisconsin Machine Learning Repository. We use a variety of machine learning algorithms, including Logistic Regression (LR), Support Vector Machine (SVM), K-Nearest Neighbours (KNN), Classification and Regression Tree (CART), Naive Bayes (NB), and well-known ensembles methods like Majority-Voting, eXtreme Gradient Boosting algorithm (XGBoost), and Random Forest (RF) for the breast cancer classification. The findings show that the Majority-Voting ensemble method, built on the top three classifiers (LR, SVM, and CART), outperforms all other individual classifiers and offers the highest accuracy of 99.3%. © 2023 The Author(s)

关键词： Breast cancer Class-balancing Cross-validation Diagnostic analytics Ensemble method Machine learning

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An invisible DWT watermarking algorithm using noise removal with application to dermoscopic images 9

An invisible DWT watermarking algorithm using noise removal ...

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9th International Conference on Mathematical Modeling in Physical Sciences, IC-MSQUARE 2020

作者： Moldovanu, S. Michis, F.A. Moraru, L. Dunarea de Jos University of Galati Department of Computer Science and Information Technology Faculty of Automation Computers Sciences Electronics and Electrical Engineering 2 Stiintei Street GalatiRO-800210 Romania Department of Chemistry Physics and Environment Faculty of Sciences and Environment Dunarea de Jos University of Galati 47 Domneasca Street Galati800008 Romania Dunarea de Jos University of Galati Modelling and Simulation Laboratory Galati Romania

A new approach for the digital watermarking process is proposed to be part of the pre-processing stage of a computer-aided diagnosis system. We propose to embed a denoised image acting as the watermark image in the original host image with the final goal of improving the quality of demoscopic images for further image processing operation related to CAD. The proposed algorithm uses Discrete Wavelet Transform (DWT) corroborated with some basic properties of Human Visual System such as Contrast Sensitive Function (CSF) and Noise Visibility Function (NVF) with the goal of correlating the texture properties and noise. This approach hides the watermark (i.e. denoised version of the host image) in high-pass subbands that are focused on image features. The main concern is to evaluate the distortion produced to the host image by watermarking and an objective quality measure function, i.e. Weighted Peak Signal-to-Noise Ratio (WPSNR), is used to evaluate the existing differences between the original and watermarked images. The proposed approach is tested using the available skin lesion images from the digital image archive of the department of Dermatology of the University Medical Center Groningen. The experiment results show the improved performance of the proposed scheme against a 3 × 3 median filtering attack in comparison with the a 5 × 5 median filtering attack. © Published under licence by IOP Publishing Ltd.

关键词： Discrete wavelet transforms

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