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24th EEEIC International Conference on Environment and Electrical engineering and 8th I and CPS Industrial and Commercial Power Systems Europe, EEEIC/I and CPS Europe 2024

作者： Grabowski, Dariusz Klimas, MacIej Lange, Andrzej Silesian University of Technology Faculty of Electrical Engineering Department of Electrical Engineering and Computer Science Gliwice Poland University of Warmia and Mazury Faculty of Technical Sciences Department of Electrical and Power Eng. Electronics and Automation Olsztyn Poland

ISBN: (纸本)9798350355185

This paper focuses on analyzing power quality issues resulting from electric arc furnace operation. It highlights the challenges posed by the stochastic nature of the arc and proposes strategies to mitigate its impact on the power grid. Through measurements carried out on the medium and low voltage side of the furnace, fluctuations in parameters such as voltage, current, and power factor were observed, indicating significant disturbances in power quality. Mitigation strategies, including e.g. installing compensators, are suggested to stabilize the network and improve power quality, enhancing efficiency and reducing energy consumption and electrode usage. © 2024 IEEE.

关键词： Electric arc furnaces

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A Deep Reinforcement Learning Control Strategy with Integrated Droop Control for Parallel DC-DC Buck Converters with CPLs 10th

A Deep Reinforcement Learning Control Strategy with Integrat...

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10th International Conference of Pioneering computer Scientists, Engineers and Educators, ICPCSEE 2024

作者： Fan, Zhongyang Cui, Chenggang Yang, Tianxiao Zhang, Chuanlin College of Computer Science and Technology Shanghai University of Electric Power Shanghai China College of Automation Engineering Shanghai University of Electric Power Shanghai China College of Aeronautical and Automotive Engineering Loughborough University Loughborough United Kingdom

ISBN: (纸本)9789819787425

The establishment of DC microgrids presents difficulties in ensuring stability and optimizing transient-time control performance. In response to the various issues in bus voltage control of parallel DC-DC buck converters, a control strategy based on model-free deep reinforcement learning (DRL) combined with droop control is proposed in this paper. Utilizing DRL controllers to independently control multiple DC-DC buck converters, achieving bus voltage stability and precise power distribution. Compared to traditional controllers such as PID control, model predictive control (MPC), and sliding mode control (SMC), the proposed strategy, leveraging the fast adaptive capability of DRL, significantly reduces the performance recovery time when disturbances occur. The simulation results illustrate the effectiveness of the approach in the presence of significant signal disturbances. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Deep reinforcement learning

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A New Fuzzy Adaptive Algorithm to Classify Imbalanced Data

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computers, Materials & Continua 2022年第1期70卷 73-89页

作者： Harshita Patel Dharmendra Singh Rajput Ovidiu Petru Stan Liviu Cristian Miclea School of Information Technology&Engineering Vellore Institute of TechnologyVellore632014India Technical University of Cluj Napoca Faculty of Automation and Computer ScienceCluj Napoca400114Romania

Classification of imbalanced data is a well explored issue in the data mining and machine learning community where one class representation is overwhelmed by other *** Imbalanced distribution of data is a natural occurrence in real world datasets,so needed to be dealt with carefully to get important *** case of imbalance in data sets,traditional classifiers have to sacrifice their performances,therefore lead to *** paper suggests a weighted nearest neighbor approach in a fuzzy manner to deal with this *** have adapted the‘existing algorithm modification solution’to learn from imbalanced datasets that classify data without manipulating the natural distribution of data unlike the other popular data balancing *** K nearest neighbor is a non-parametric classification method that is mostly used in machine learning *** classification with the nearest neighbor clears the belonging of an instance to classes and optimal weights with improved nearest neighbor concept helping to correctly classify imbalanced *** proposed hybrid approach takes care of imbalance nature of data and reduces the inaccuracies appear in applications of original and traditional *** show that it performs well over the existing fuzzy nearest neighbor and weighted neighbor strategies for imbalanced learning.

关键词： Machine learning fuzzy classification nearest neighbor adaptive approach optimal weights

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A Unified Arbitrary Style Transfer Framework via Adaptive Contrastive Learning

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ACM Transactions on Graphics 2023年第5期42卷 1-16页

作者： Zhang, Yuxin Tang, Fan Dong, Weiming Huang, Haibin Ma, Chongyang Lee, Tong-Yee Xu, Changsheng MAIS Institute of Automation China and School of Artificial Intelligence CAS UCAS China Institute Of Computing Technology CAS China Kuaishou Technology China Department of Computer Science and Information Engineering National Cheng-Kung University Taiwan

This work presents Unified Contrastive Arbitrary Style Transfer (UCAST), a novel style representation learning and transfer framework, that can fit in most existing arbitrary image style transfer models, such as CNN-based, ViT-based, and flow-based methods. As the key component in image style transfer tasks, a suitable style representation is essential to achieve satisfactory results. Existing approaches based on deep neural networks typically use second-order statistics to generate the output. However, these hand-crafted features computed from a single image cannot leverage style information sufficiently, which leads to artifacts such as local distortions and style inconsistency. To address these issues, we learn style representation directly from a large number of images based on contrastive learning by considering the relationships between specific styles and the holistic style distribution. Specifically, we present an adaptive contrastive learning scheme for style transfer by introducing an input-dependent temperature. Our framework consists of three key components: a parallel contrastive learning scheme for style representation and transfer, a domain enhancement (DE) module for effective learning of style distribution, and a generative network for style transfer. Qualitative and quantitative evaluations show the results of our approach are superior to those obtained via state-of-the-art methods. The code is available at https://***/zyxElsa/CAST_pytorch. © 2023 Copyright held by the owner/author(s).

关键词： Deep neural networks

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Accelerated Algorithm for Counting the Amount of Numbers in Specified Ranges

Accelerated Algorithm for Counting the Amount of Numbers in ...

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2022 Conference of Russian Young Researchers in Electrical and Electronic engineering, ElConRus 2022

作者： Krutikov, Alexander K. Strabykin, Dmitry A. Lapitsky, Alexey A. Vyatka State University Faculty of Automation and Computer Engineering Department of Electronic Computers Kirov Russia

ISBN: (纸本)9781665409933

An accelerated algorithm for calculating the number of array numbers that fit in each of the specified ranges is proposed. The algorithm assumes that the number of ranges is a multiple of the power of two, the bit depth of the maximum number of the array does not exceed the bit depth of the memory cell used to store it. The acceleration of counting numbers is based on the conversion of the analyzed number of the source array to the address of the memory cell corresponding to the range of the number. This conversion reduces the time for counting the number of numbers in the source array that fit into the specified ranges by eliminating memory accesses to read the boundary values of the addresses of the ranges. The time estimates of the algorithm execution are given, the prospects of using the algorithm in solving problems are noted. © 2022 IEEE.

关键词： Array processing

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Vector-Logical In-Memory Simulation of Faults as Truth Table Addresses

Vector-Logical In-Memory Simulation of Faults as Truth Table...

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2024 IEEE East-West Design and Test Symposium, EWDTS 2024

作者： Hahanov, Vladimir Litvinova, Eugenia Hahanova, Hanna Chumachenko, Svetlana Davitadze, Zaza Hahanova, Irina Kulak, Heorhii Ponomarova, Veronika Abdullayev, Vugar Hacimahmud Kharkiv National University of Radio Electronics Design Automation Department Kharkiv Ukraine Batumi Shota Rustaveli State University Department of Computer Sciences Batumi Georgia Azerbaijan State Oil and Industry University Computer Engineering Department Baku Azerbaijan

ISBN: (纸本)9798331515768

A vector-logical mechanism to faults as addresses simulation on smart data structures that eliminate the simulation algorithm of test sets to obtain a testing map for logic functionality is proposed. Smart data structures are represented by a logical vector and its derivatives as truth tables and matrices. The testing map is a matrix whose coordinates are determined by the combinations of all logical faults detected on the binary sets of the exhaustive test. The construction of the testing map is focused on the architecture of in-memory computing based on read-write transactions, which makes the simulation mechanism economical regarding simulation time and energy consumption due to the absence of a central processor. The logic vector, as the only component of the input data, does not require synthesis into a technologically permitted structure of elements. Synthesizing smart data structures based on four matrix operations creates a fault-detected testing map for any logic. The proposed mechanism is focused on servicing SoC IP cores under the IEEE 1500 standard, which can be positively received by engineers in the EDA market. In terms of simplicity and predictability of the size of data structures and the absence of a simulation algorithm of test sets, the proposed mechanism has no analogues in design and industry tests. The introduction presents useful technological trends DAC 61 in the development of computing for the IT industry and academic science of tomorrow. The following areas are highlighted: in-memory computing, immersion computing, and AI computing, which are focused on energy saving and reducing computation time when providing services. © 2024 IEEE.

关键词： Vectors

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Adaptive Optimal Output-Feedback Control of Discrete-Time Systems based on Hybrid Iteration 63

Adaptive Optimal Output-Feedback Control of Discrete-Time Sy...

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63rd IEEE Conference on Decision and Control, CDC 2024

作者： Liu, Sitong Gao, Weinan Jiang, Zhong-Ping Northeastern University State Key Laboratory of Synthetical Automation for Process Industries Lianning Shenyang110819 China Tandon School of Engineering New York University Department of Electrical and Computer Engineering BrooklynNY11201 United States

ISBN: (纸本)9798350316339

In this paper, a novel adaptive dynamic programming (ADP) algorithm, named output-feedback hybrid iteration (HI),is proposed to address the adaptive optimal control problem of discrete-time linear systems. The proposed output-feedback HI strategy learns the optimal control policy through two phases. First, a novel data-driven value-iteration (VI) scheme is employed to learn an admissible output-feedback control policy using the input/output data without relying on the knowledge of system matrices. Then, with the obtained admissible control policy, the optimal output feedback-control policy is approximated with an accelerated convergence rate through output-feedback policy iteration (PI). Online input/output data are utilized to reconstruct the full state of the system and integrated into the new output-feedback HI algorithm. Simulation results are presented and demonstrate the efficacy and practicality of the proposed output-feedback HI approach in comparison with traditional PI and VI techniques. © 2024 IEEE.

关键词： Dynamic programming

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Enhanced Experts with Uncertainty-Aware Routing for Multimodal Sentiment Analysis 24

Enhanced Experts with Uncertainty-Aware Routing for Multimod...

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32nd ACM International Conference on Multimedia, MM 2024

作者： Gao, Zixian Hu, Disen Jiang, Xun Lu, Huimin Shen, Heng Tao Xu, Xing Center for Future Media School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu China School of Automation Southeast University Nanjing China College of Electronic and Information Engineering Tongji University Shanghai China

ISBN: (纸本)9798400706868

Multimodal sentiment analysis, which has garnered widespread attention in recent years, aims to predict human emotional states using multimodal data. Previous studies have primarily focused on enhancing multimodal fusion and integrating information across different modalities, while overlooking the impact of noisy data on the internal features of each single modality. In this paper, we propose the Enhanced experts with Uncertainty-Aware Routing (EUAR) method to address the influence of noisy data on multimodal sentiment analysis by capturing uncertainty and dynamically altering the network. Specifically, we introduce the Mixture of Experts approach into multimodal sentiment analysis for the first time, leveraging its properties under conditional computation to dynamically alter the network in response to different types of noisy data. Particularly, we refine the experts within the MoE framework to capture uncertainty in the data and extract clearer features. Additionally, a novel routing mechanism is introduced. Through our proposed U-loss, which utilizes the quantified uncertainty by experts, the network learns to route different samples to experts with lower uncertainty for processing, thus obtaining clearer, noise-free features. Experimental results demonstrate that our method achieves state-of-the-art performance on three widely used multimodal sentiment analysis datasets. Moreover, experiments on noisy datasets show that our approach outperforms existing methods in handling noisy data. © 2024 ACM.

关键词： Data assimilation

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Optimal Formation Control for Second-Order Multi-Agent Systems With Obstacle Avoidance

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IEEE/CAA Journal of Automatica Sinica 2023年第2期10卷 563-565页

作者： Jiaxin Zhang Wei Liu Yongming Li the State Key Laboratory of Synthetical Automation for Process Industries Northeastern UniversityShenyang 110000China the School of Computer Science and Engineering Northeastern UniversityShenyang 110000China IEEE the College of Science Liaoning University of TechnologyJinzhou 121001China

Dear Editor,The optimal formation control design problem is studied for a class of second-order multi-agent systems(MASs) with obstacle *** on the actor-critic framework, an optimized formation controller is proposed by constructing a novel performance index function. Furthermore, the stability of MAS is proved by constructing the Lyapunov function. The simulation results are provided to depict the effectiveness of the proposed strategies.

关键词： function agent constructing

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Development of ANFIS Controller for Trajectory Tracking Control Using ROBO2L MATLAB Toolbox for KUKA Industrial Robot via RSI 21

Development of ANFIS Controller for Trajectory Tracking Cont...

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21st International Multi-Conference on Systems, Signals and Devices, SSD 2024

作者： Mousa, Mohamed Al-Mahasneh, Ahmad Baniyounis, Mohammed Biesenbach, Rolf Falkenhain, Jan Philadelphia University Mechatronics Engineering Department Amman Jordan Institute for Automation and Industry 4.0 Bochum University of Applied Sciences Bochum Germany Bochum University of Applied Sciences Electrical Engineering and Computer Science Department Bochum Germany

ISBN: (纸本)9798350374131

A new control scheme is proposed in the MATLAB/Simulink environment based on ANFIS technology using ROBO2L MATLAB toolbox with RSI to control the motion of the real KUKA robot. In detail, the control system has two subsystems designed for trajectory tracking error regulation in closed-loop control. One is a fuzzy logic controller, and the other is an ANFIS controller. These two controllers were used to control the velocity of the KUKA robot located inside the Hochschule Bochum laboratory. The testing process for these controllers was done by switching between FLC and ANFIS controllers and then studying each response separately. The results were compared with a linear controller produced in Hochschule Bochum experiments. The ROBO2L MATLAB toolbox provides many functions, such as sending and receiving positions and rotation for the end effector via UDP/IP communication, which RSI established to provide remote control for the robot using a PC. This work mainly emphasizes the ability to track the trajectories supported by the robotics toolbox in smooth motion. After observing the simulation results, the comparison between the linear, FLC, and ANFIS controllers is confirmed. The performance of the proposed approach is efficient for trajectory tracking control for the manipulator. © 2024 IEEE.

关键词： Controllers

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