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2023 IEEE International Conference on Web Services, ICWS 2023

作者： Liu, Zhizhong Huang, Guangyu Chu, Dianhui Sun, Yuhang Yantai University School of Computer and Control Engineering Yantai China Harbin Institute of Technology School of Computer Science and Technology Weihai China

ISBN: (纸本)9798350304855

In the past three years, global COVID-19 pandemic not only impacted people's physical health but also significantly affected their mental health, which resulting in rapid increase of psychological problems. Emotions are a common manifestation of psychological changes, and some services (such as music, video, or psychological counseling services) can help users to adjust their emotions in a timely manner, thus to avoid bringing extreme events (e.g., running away from home or committing suicide). Therefore, how to perceive users' real-time emotions and then recommend the most appropriate services to users has become a challenge. To address this issue, this work proposes an approach for proactive services recommendation driven-by multimodal emotion recognition (named as PSRMER). Specifically, PSRMER first actively identifies a user's emotion with a multimodal emotion recognition model based on BiGRU and Transformer;Then, considering the user's emotion and preferences, PSRMER selects the optimal services based on an index-graph linking different emotions and various services;Finally, PSRMER proactively recommends the selected optimal service to the user. Extensive experiments have been conducted and the effectiveness of our proposed method have been proved. Moreover, the proposed method can also be used in smart education, smart transportation, smart elderly care and other modern industry fields. © 2023 IEEE.

关键词： COVID-19

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Attention-Based Residual Dense Shrinkage Network for ECG Denoising

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computer Modeling in Engineering & sciences 2024年第3期138卷 2809-2824页

作者： Dengyong Zhang Minzhi Yuan Feng Li Lebing Zhang Yanqiang Sun Yiming Ling Hunan Provincial Key Laboratory of Intelligent Processing of Big Data on Transportation Changsha University of Science and TechnologyChangsha410114China School of Computer and Communication Engineering Changsha University of Science and TechnologyChangsha410114China School of Computer and Artificial Intelligence Huaihua UniversityHuaihua418000China School of Computer National University of Defense TechnologyChangsha410073China New Energy Centralized Control Center CHN Energy Hunan Power New Energy Co.Ltd.Changsha410000China

Electrocardiogram(ECG)signal is one of the noninvasive physiological measurement techniques commonly usedin cardiac ***,in real scenarios,the ECGsignal is susceptible to various noise erosion,which affectsthe subsequent pathological ***,the effective removal of the noise from ECG signals has becomea top priority in cardiac diagnostic *** at the problem of incomplete signal shape retention andlow signal-to-noise ratio(SNR)after denoising,a novel ECG denoising network,named attention-based residualdense shrinkage network(ARDSN),is proposed in this ***,the shallow ECG characteristics are extractedby a shallow feature extraction network(SFEN).Then,the residual dense shrinkage attention block(RDSAB)isused for adaptive noise ***,feature fusion representation(FFR)is performed on the hierarchicalfeatures extracted by a series of RDSABs to reconstruct the de-noised ECG *** on the MIT-BIHarrhythmia database and MIT-BIH noise stress test database indicate that the proposed scheme can effectively resistthe interference of different sources of noise on the ECG signal.

关键词： Electrocardiogram signal denoising signal-to-noise ratio attention-based residual dense shrinkage network MIT-BIH

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Neighborhood Combination Search for Single-Machine Scheduling with Sequence-Dependent Setup Time

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Journal of computer science & Technology 2024年第3期39卷 737-752页

作者：刘晓路徐宏云陈嘉铭苏宙行吕志鹏丁俊文 College of System Engineering National University of Defense TechnologyChangsha 410015China School of Artificial Intelligence Jianghan UniversityWuhan 430056China Xi’an Satellite Control Center Xi’an 710043China School of Computer Science and Technology Huazhong University of Science and TechnologyWuhan 430074China CCF

In a local search algorithm,one of its most important features is the definition of its neighborhood which is crucial to the algorithm's *** this paper,we present an analysis of neighborhood combination search for solv-ing the single-machine scheduling problem with sequence-dependent setup time with the objective of minimizing total weighted tardiness(SMSWT).First,We propose a new neighborhood structure named Block Swap(B1)which can be con-sidered as an extension of the previously widely used Block Move(B2)neighborhood,and a fast incremental evaluation technique to enhance its evaluation ***,based on the Block Swap and Block Move neighborhoods,we present two kinds of neighborhood structures:neighborhood union(denoted by B1UB2)and token-ring search(denoted by B1→B2),both of which are combinations of B1 and ***,we incorporate the neighborhood union and token-ring search into two representative metaheuristic algorithms:the Iterated Local Search Algorithm(ILSnew)and the Hybrid Evolutionary Algorithm(HEA_(new))to investigate the performance of the neighborhood union and token-ring ***-sive experiments show the competitiveness of the token-ring search combination mechanism of the two *** on the 120 public benchmark instances,our HEA_(new)has a highly competitive performance in solution quality and computational time compared with both the exact algorithms and recent *** have also tested the HEA,new algorithm with the selected neighborhood combination search to deal with the 64 public benchmark instances of the single-machine scheduling problem with sequence-dependent setup *** is able to match the optimal or the best known results for all the 64 *** particular,the computational time for reaching the best well-known results for five chal-lenging instances is reduced by at least 61.25%.

关键词： single-machine scheduling sequence-dependent setup time neighborhood combination search token-ring search hybrid evolutionary algorithm

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Energy Efficient Dual User Association for Large Scale IRS-Aided mmWave Communication Networks

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China Communications 2025年第1期22卷 182-195页

作者： Chen Guolin Deng Yiqin Huang Xiaoxia Fang Yuguang School of Electronics and Communication Engineering Sun Yat-sen UniversityShenzhen 518107China School of Control Science and Engineering Shandong UniversityJinan 250100China Department of Computer Science City University of Hong KongHong Kong 999077China

The deployment of multiple intelligent reflecting surfaces(IRSs)in blockage-prone millimeter wave(mmWave)communication networks have garnered considerable attention *** the remarkably low circuit power consumption per IRS element,the aggregate energy consumption becomes substantial if all elements of an IRS are turned on given a considerable number of IRSs,resulting in lower overall energy efficiency(EE).To tackle this challenge,we propose a flexible and efficient approach that individually controls the status of each IRS ***,the network EE is maximized by jointly optimizing the associations of base stations(BSs)and user equipments(UEs),transmit beamforming,phase shifts of IRS elements,and the associations of individual IRS elements and *** problem is efficiently addressed in two ***,the Gale-Shapley algorithm is applied for BS-UE association,followed by a block coordinate descent-based algorithm that iteratively solves the subproblems related to active beamforming,phase shifts,and element-UE *** reduce the tremendous dimensionality of optimization variables introduced by element-UE associations in large-scale IRS networks,we introduce an efficient algorithm to solve the associations between IRS elements and *** results show that the proposed elementwise control scheme improves EE by 34.24% compared to the network with IRS-all-on scheme.

关键词： energy efficiency intelligent reflecting surface,millimeter-wave communication

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Wave refrigeration control via deep reinforcement learning 4

Wave refrigeration control via deep reinforcement learning

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2024 4th International Conference on Artificial Intelligence and Industrial Technology Applications, AIITA 2024

作者： Cui, Xuesong Hu, Xiaopeng Wang, Fan Li, Qi School of Computer Science and Technology Dalian University of Technology Dalian China School of Control Science and Engineering Dalian University of Technology Dalian China

Wave refrigerating technology is a new type of refrigerating technology that performs more efficiently and is more environmentally friendly. Nowadays, the commonly used control method is the PID control method. However, although the above control methods are simple in structure, they have the problems of difficult parameter tuning, large overshoot, and unstable and inaccurate output response. Therefore, to improve the above problems, we propose a framework of deep reinforcement learning-based wave refrigerating control system. An improved SAC algorithm is used to learn the control system. The evaluation method is established according to the working condition requirements as well as the safety requirements in the operation process. Experiments show that this method can effectively improve the control efficiency as well as the control quality, which can make the control system operate stably. © Published under licence by IOP Publishing Ltd.

关键词： Deep reinforcement learning

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Slow Convergence of Interacting Kalman Filters in Word-of-Mouth Social Learning 60

Slow Convergence of Interacting Kalman Filters in Word-of-Mo...

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60th Annual Allerton Conference on Communication, control, and Computing, Allerton 2024

作者： Krishnamurthy, Vikram Rojas, Cristian R. School of Electrical and Computer Engineering Cornell University United States School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Division of Decision and Control Systems Stockholm Sweden

ISBN: (纸本)9798331541033

We consider word-of-mouth social learning involving m Kalman filter agents that operate sequentially. The first Kalman filter receives the raw observations, while each subsequent Kalman filter receives a noisy measurement of the conditional mean of the previous Kalman filter. The prior is updated by the m-th Kalman filter. When m=2, and the observations are noisy measurements of a Gaussian random variable, the covariance goes to zero as k-1/3 for 7kappa;observations, instead of O(k-1) in the standard Kalman filter. In this paper we prove that for m agents, the covariance decreases to zero as k-(2m-1), i.e, the learning slows down exponentially with the number of agents. We also show that by artificially weighing the prior at each time, the learning rate can be made optimal as k-1. The implication is that in word-of-mouth social learning, artificially re-weighing the prior can yield the optimal learning rate. © 2024 IEEE.

关键词： Kalman filters

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RFNet: A Redundancy-Reduced and Frequency-Aware Feature Fusion Network for RGB-T Semantic Segmentation 10

RFNet: A Redundancy-Reduced and Frequency-Aware Feature Fusi...

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10th IEEE Smart World Congress, SWC 2024

作者： Guo, Yixin Chen, Zhenxue Rong, Xuewen Liu, Chengyun Li, Yidi Shandong University School of Control Science and Engineering Jinan China Taiyuan University of Technology Computer Science and Technology Taiyuan China

ISBN: (纸本)9798331520861

Traditional semantic segmentation approaches primarily utilize RGB images, which struggle in complex scenes. To address this challenge, the multi-modal solution that fuses RGB and thermal (RGB-T) images can exploit the advantages of these modalities to improve accuracy and stability of segmentation. However, how to effectively fuse multi-modal and multi-level features remains a significant challenge. To this end, a Redundancy-Reduced and Frequency-Aware Feature Fusion Network (RFNet) is proposed. The RFNet employs a dual-stream encoder-decoder architecture to separately handle the extracted features from two modalities. This network reduces redundancy in shallow feature fusion and integrates frequency-aware attention mechanisms in deep feature fusion, efficiently capturing complementary information from multi-modal and multi-level features. Experiments on the MFNet dataset indicate that RFNet outperforms the majority of current networks in terms of segmentation performance. © 2024 IEEE.

关键词： Semantic Segmentation

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Leveraging Data Fitting and Trust Assessment to Improve the Security of Industrial Networks 43

Leveraging Data Fitting and Trust Assessment to Improve the ...

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43rd Chinese control Conference, CCC 2024

作者： Zhang, Heng Wang, Yinchu Xue, Yawen Deng, Ruilong Li, Hongran Zhang, Jian Jiangsu Ocean University School of Computer Engineering China Zhejiang University College of Control Science and Engineering China

ISBN: (纸本)9789887581581

Industrial network control systems (INCSs) are easy to be targeted by attackers due to their high economic value. Most of the existing defense methods are deployed at the network boundary, which causes high-security risks to INCS once an attacker enters the system. In addition, many existing intrusion detection systems (IDSs) build detection models based on historical data. When INCS lacks sufficient historical data, it is difficult to build detection models with high accuracy. In this paper, we propose a trust assessment model for INCS based on Fourier series fitting employing concept of zero trust to assess the real-time trust of INCS. The model alerts when INCS has low trust. We test two data injection attacks in the experiment to prove the effectiveness of our approach. © 2024 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Network intrusion

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SliceFormer: Deep Dense Depth Estimation from a Single Indoor Omnidirectional Image Using a Slice-Based Transformer

SliceFormer: Deep Dense Depth Estimation from a Single Indoo...

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2024 International Conference on Electronics, Information, and Communication, ICEIC 2024

作者： Wu, Yihong Heng, Yuwen Niranjan, Mahesan Kim, Hansung School of Electronics and Computer Science University of Southampton Vision Learning and Control Research Group Southampton United Kingdom

ISBN: (纸本)9798350371888

In this research, we tackle the task of estimating depth from a single indoor omnidirectional image. Acknowledging gravity's critical influence in artificially constructed indoor environments, we process the input from equirectangular projection by dividing it into vertical slices. These slices are then utilized as patch embeddings for the transformer encoder, a strategy designed to recreate an equirectangular depth map. Our architecture is evaluated against leading models using real-world datasets, namely Stanford2D3D and Matterport3D, demonstrating its superior performance. These results underscore the significance of our gravity-aligned approach for depth estimation in omnidirectional images, especially in man-made settings. © 2024 IEEE.

关键词： Gravitation

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Switching control for Identification Deception in Cyber-Physical Systems 63

Switching Control for Identification Deception in Cyber-Phys...

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63rd IEEE Conference on Decision and control, CDC 2024

作者： Mavridis, Christos Kanellopoulos, Aris Sandberg, Henrik Johansson, Karl Henrik Kth Royal Institute of Technology Division of Decision and Control School of Electrical Engineering and Computer Science Stockholm Sweden

ISBN: (纸本)9798350316339

We investigate the problem of deceiving a malicious agent employing an identification method to estimate the closed-loop dynamics of a cyber-physical system. In particular, we propose a moving target defense mechanism that utilizes stochastic switching between linear closed-loop dynamics to drive a linear system identification process of a potential adversary to sub-optimal solutions with non-vanishing error. We provide a statistical analysis of the induced identification error and show that it is not possible for any linear system identification method to reconstruct the average dynamics of a stochastic switched linear system. Finally, we utilize the theory of Markov jump linear systems to guarantee asymptotic stability of the switching system, and formulate the switching control problem as an optimization problem that guarantees stability while taking into account the trade-off between security and switching effort. Simulation results showcase the efficacy of the proposed approach in inducing identification error for the adversary using minimal switching. © 2024 IEEE.

关键词： Markov processes

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