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International Conference on computer Supported Cooperative Work in Design

作者： Bingshu Shi Meiling Liu Jiyun Zhou Kaiqun Fu School of Computer and Control Engineering Northeast Forestry University Harbin China Lieber Institute Johns Hopkins University Baltimore USA Department of Electrical Engineering and Computer Science South Dakota State University Brookings USA

ISBN: (数字)9798350349184

ISBN: (纸本)9798350349191

Sentiment summary generation task is very valuable in social media, which can extract different aspects from people’s evaluation of products or services, such as the quality of products, and generate summarized opinionated sentiment summaries. And nowadays, sentiment summarization still suffers from insufficient contextual information capture and incorrect and comprehensive aspect extraction. In this paper, we propose a new strategy to solve the above problems: firstly, MILNET is used to automatically identify aspects related to a product or service from a large number of user reviews, and then the results are inputted into GCN, which is used to enhance the importance of contextual words close to the aspect; meanwhile, E-MABA is utilized for further optimization of the model on aspect extraction. By conducting a large number of experiments on the OPOSUM dataset and comparing the existing state-of-the-art methods, it is found that our method achieves better performance than other methods, proving the feasibility and effectiveness of our proposed strategy.

关键词： Analytical models Vocabulary Sentiment analysis Social networking (online) Reviews Predictive models Data mining

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Direct data-driven state-feedback control of general nonlinear systems

arXiv

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arXiv 2023年

作者： Verhoek, Chris Koelewijn, Patrick J.W. Haesaert, Sofie Tóth, Roland The Dept. of Electrical Engineering The Eindhoven University of Technology Netherlands The Institute for Computer Science and Control Budapest Hungary

Through the use of the Fundamental Lemma for linear systems, a direct data-driven state-feedback control synthesis method is presented for a rather general class of nonlinear (NL) systems. The core idea is to develop a data-driven representation of the so-called velocity-form, i.e., the time-difference dynamics, of the NL system, which is shown to admit a direct linear parameter-varying (LPV) representation. By applying the LPV extension of the Fundamental Lemma in this velocity domain, a state-feedback controller is directly synthesized to provide asymptotic stability and dissipativity of the velocity-form. By using realization theory, the synthesized controller is realized as a NL state-feedback law for the original unknown NL system with guarantees of universal shifted stability and dissipativity, i.e., stability and dissipativity w.r.t. any (forced) equilibrium point, of the closed-loop behavior. This is achieved by the use of a single sequence of data from the system and a predefined basis function set to span the scheduling map. The applicability of the results is demonstrated on a simulation example of an unbalanced disc. © 2023, CC BY-NC-SA.

关键词： Linear systems

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Carbon-Aware Computing in a Network of Data Centers: A Hierarchical Game-Theoretic Approach

Carbon-Aware Computing in a Network of Data Centers: A Hiera...

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European control Conference (ECC)

作者： Enno Breukelman Sophie Hall Giuseppe Belgioioso Florian Dörfler Division of Decision and Control Systems KTH Royal Institute of Technology School of Electrical Engineering and Computer Science Stockholm Sweden Department of Electrical Engineering and Information Technology Automatic Control Laboratory ETH Zurich Zürich Switzerland

ISBN: (数字)9783907144107

ISBN: (纸本)9798331540920

Over the past decade, the continuous surge in cloud computing demand has intensified data center workloads, leading to significant carbon emissions and driving the need for improving their efficiency and sustainability. This paper focuses on the optimal allocation problem of batch compute loads with temporal and spatial flexibility across a global network of data centers. We propose a bilevel game-theoretic solution approach that captures the inherent hierarchical relationship between supervisory control objectives, such as carbon reduction and peak shaving, and operational objectives, such as priority-aware scheduling. Numerical simulations with real carbon intensity data demonstrate that the proposed approach success-fully reduces carbon emissions while simultaneously ensuring operational reliability and priority-aware scheduling.

关键词： Data centers Processor scheduling Computational modeling Carbon dioxide Games Supervisory control Resource management

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Few-shot Object Detection Algorithm Based on YOLOv8-Mamba-Like Linear Attention 16

Few-shot Object Detection Algorithm Based on YOLOv8-Mamba-Li...

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16th International Conference on Communication Software and Networks, ICCSN 2024

作者： Wang, Hongliang Wang, Kaizhu Ji, Binglong Deng, Changyi Shenyang Institute of Computing Technology Chinese Academy of Sciences University of Chinese Academy of Sciences Liaoning Province Human- Computer Interaction System Engineering Research Center Based on DigitTwin Shenyang China Shenyang Institute of Computing Technology Chinese Academy of Sciences University of Chinese Academy of Sciences Shenyang China Institute of Software China Industrial Control Systems Cyber Emergency Response Team Beijing China

ISBN: (纸本)9798331506322

In the production and assembly process, the accuracy of detection is usually low due to limited resources and small quantities. In this paper, we propose a few-shot learning method for object detection based on the combination of YOLOv8 and Mamba-Like Linear Attention (MLLA) module. This method utilizes a high-pixel camera to capture the shape and size of the workpiece. By consistency-based mutual augmentation structure for few-shot samples data augmentation. By introducing the efficient and lightweight MLLA module, the model's speed and accuracy in object detection and segmentation tasks on mobile devices are significantly improved. Specifically, MLLA mainly integrates the two key elements of 'forget gate' and 'block design' in Mamba, and MLLA replaces forget gate by using position coding (RoPE) to provide necessary location information while maintaining parallel computation and fast inference speed. This makes MLLA improves the accuracy of detection and segmentation recognition. Experimental results show that compared to the original YOLOv8 model, the model with the MLLA module exhibits improvements in segmentation precision and recognition accuracy. This method demonstrates high accuracy and robustness in workpiece recognition, making it suitable for real-time industrial applications. © 2024 IEEE.

关键词： Object detection

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A Distributed Time-Varying Optimization Algorithm For Networked Lagrangian Agents Generating Continuous control Torques

A Distributed Time-Varying Optimization Algorithm For Networ...

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American control Conference (ACC)

作者： Yong Ding Hanlei Wang Jie Mei Wei Ren Department of Electrical and Computer Engineering University of California Riverside CA USA Science and Technology on Space Intelligent Control Laboratory Beijing Institute of Control Engineering Beijing China School of Mechanical Engineering Harbin Institute of Technology Shenzhen China

In this paper, the distributed time-varying optimization problem is investigated for networked Lagrangian systems with parametric uncertainties. Due to the usage of the signum function in the control torque design, there might exist chattering while implementing the distributed time-varying optimization algorithms for networked Lagrangian agents in the existing works. To this end, we design a distributed optimization algorithm that is capable of generating continuous control torques and achieving exact optimum tracking. A simulation is presented to validate the effectiveness of the proposed algorithm.

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A GRU-based Automatic Weighting Factors Optimization Strategy for PMSM

A GRU-based Automatic Weighting Factors Optimization Strateg...

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Chinese Automation Congress (CAC)

作者： Jiaao Li Jie Jin Jianhua Zhang Zhuang Liu Xiaoning Shen School of Astronautics Harbin Institute of Technology Harbin China School of Control and Computer Engineering North China Electric Power University Beijing China

ISBN: (数字)9798350368604

ISBN: (纸本)9798350368611

The performance of model predictive control (MPC) in permanent magnet synchronous motor (PMSM) still remains a challenging problem due to the large torque ripple in lower speed. The cost function in conventional MPC generally use fixed weighting factors, which is not easy to adapt different operation scenario and keep balance between torque ripple suppression and current tracking accuracy. To address this issue, a gated recurrent units (GRU) network based weighting factors automated-regulation strategy is proposed for the MPC in PMSM. Through offline training, the weighting factors in MPC are tuned in real time and the current tracking accuracy as well as torque ripple in different conditions are ensured, which is superior to the conventional fixed weighting factors-based MPC. Finally, some simulation results verify the effectiveness of the proposed method.

关键词： Employee welfare Training Accuracy Simulation Predictive models Permanent magnet motors Real-time systems Table lookup Torque measurement Predictive control

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STC: Student-Teacher Collaborative Model for Multi-Target Domain Adaptation

STC: Student-Teacher Collaborative Model for Multi-Target Do...

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International Conference on Wavelet Active Media Technology and Information Processing (ICWAMTIP)

作者： Xu Jiayi Yu Jiaqi Wang Yixin Han Shijia School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu China Beijing Institute of Control and Electronic Technology Beijing China

ISBN: (数字)9798331519254

ISBN: (纸本)9798331519261

Cross-domain object detection poses significant challenges due to the susceptibility of object detection models to data variance, particularly the domain shifts that can occur between different domains. To address the limitation, we draw inspiration from knowledge distillation, proposing a collaborative learning framework. Our method employs CycleGAN to generate target-style images, and during pretraining, an unsupervised domain adaptation teacher model is trained for each source-target pair. In the distillation process, our proposed algorithm implements an out-of-distribution estimation strategy to select samples that best align with the current model, thereby enhancing the cross-domain distillation process. Furthermore, each expert model is encouraged to collaborate by designating the student model as a bridge between different target domains, facilitated by the Exponential Moving Average (EMA) algorithm. Experiments show that the proposed method leverages structured information, not only does it perform well across various target domains, but it also yields favorable results compared to state-of-the-art unsupervised methods that are specifically trained on single source-target pair.

关键词： Bridges Adaptation models Federated learning Large language models Estimation Object detection Information processing Media Explosions Periodic structures

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A Multi-Player Potential Game Approach for Sensor Network Localization with Noisy Measurements 63

A Multi-Player Potential Game Approach for Sensor Network Lo...

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63rd IEEE Conference on Decision and control, CDC 2024

作者： Xu, Gehui Chen, Guanpu Fidan, Baris Hong, Yiguang Qi, Hongsheng Parisini, Thomas Johansson, Karl H. Kth Royal Institute of Technology Division of Decision and Control Systems School of Electrical Engineering and Computer Science Stockholm100 44 Sweden University of Waterloo Department of Mechanical and Mechatronics Engineering WaterlooONN2L 3G1 Canada Tongji University Department of Control Science and Engineering shanghai201804 China Shanghai Research Institute for Intelligent Autonomous Systems Shanghai201210 China Key Laboratory of Systems and Control Academy of Mathematics and Systems Science Beijing China University of Chinese Academy of Sciences School of Mathematical Sciences Beijing China Aalborg University Department of Electronic Systems Denmark Imperial College London Department of Electrical and Electronic Engineering LondonSW7 2AZ United Kingdom University of Trieste Department of Engineering and Architecture Italy

ISBN: (纸本)9798350316339

Sensor network localization (SNL) is a challenging problem due to its inherent non-convexity and the effects of noise in inter-node ranging measurements and anchor node position. We formulate a non-convex SNL problem as a multiplayer non-convex potential game and investigate the existence and uniqueness of a Nash equilibrium (NE) in both the ideal setting without measurement noise and the practical setting with measurement noise. We first show that the NE exists and is unique in the noiseless case, and corresponds to the precise network localization. Then, we study the SNL for the case with errors affecting the anchor node position and the inter-node distance measurements. Specifically, we establish that in case these errors are sufficiently small, the NE exists and is unique. It is shown that the NE is an approximate solution to the SNL problem, and that the position errors can be quantified accordingly. Based on these findings, we apply the results to case studies involving only inter-node distance measurement errors and only anchor position information inaccuracies. © 2024 IEEE.

关键词： Nash equilibrium

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Differentially Private Online Federated Learning with Correlated Noise

Differentially Private Online Federated Learning with Correl...

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IEEE Conference on Decision and control

作者： Jiaojiao Zhang Linglingzhi Zhu Mikael Johansson Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden Department of Systems Engineering and Engineering Management Chinese University of Hong Kong

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

We introduce a novel differentially private algorithm for online federated learning that employs temporally correlated noise to enhance utility while ensuring privacy of continuously released models. To address challenges posed by DP noise and local updates with streaming non-iid data, we develop a perturbed iterate analysis to control the impact of the DP noise on the utility. Moreover, we demonstrate how the drift errors from local updates can be effectively managed under a quasi-strong convexity condition. Subject to an $(\epsilon, \delta)$ DP budget, we establish a dynamic regret bound over the entire time horizon, quantifying the impact of key parameters and the intensity of changes in dynamic environments. Numerical experiments confirm the efficacy of the proposed algorithm.

关键词： Privacy Federated learning Heuristic algorithms Noise Signal processing algorithms Servers

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Configuration Optimization of Hybrid Electrolyzer for Wind-Based Green Hydrogen Production System

Configuration Optimization of Hybrid Electrolyzer for Wind-B...

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China International Electrical and Energy Conference (CIEEC)

作者： Jiahu Lin Wenbo Hao Mingfei Ban Northeast Forestry University College of Computer and Control Engineering Harbin China State Grid Heilongjiang Electric Power Research Institute Harbin China

ISBN: (数字)9798350359558

ISBN: (纸本)9798350359565

As the development of renewable energy progresses, the prospects for the application of green hydrogen are gradually expanding, with countries strengthening the construction of industries related to green hydrogen. This paper investigates the hybrid electrolytic hydrogen production system and its configuration optimization problem, considering wind power decomposition and multiple types of electrolyzers. Firstly, a model for wind power redistribution is established based on the characteristics of different types of electrolyzers to determine the power loads of each type. Subsequently, based on the solution results of the redistribution model, a hybrid electrolyzer system configuration optimization model with the objective of maximizing annual revenue is proposed. Finally, case studies show that Hybrid electrolyzer system offers advantages in terms of energy efficiency, reliability and economy. Compared to alkaline electrolyzer system, hybrid system can improve the efficiency and stability of energy utilization and better cope with the uncertainty of renewable energy sources. The hybrid system can significantly reduce the initial capital investment and number of configurations compared to proton exchange membrane electrolyzer system, thereby lowering the operating cost of the overall energy system.

关键词： Production systems Costs Uncertainty Wind energy Wind speed Wind power generation Green hydrogen

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