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Distributed Optimization and Scaling Design for Solving Sylvester Equations

Journal of Systems Science & Complexity 2024年第6期37卷 2487-2510页

作者： CHENG Songsong YU Xin ZENG Xianlin LIANG Shu HONG Yiguang Anhui Engineering Laboratory of Human-Robot Integration System and Intelligent Equipment School of Electrical Engineering and AutomationAnhui UniversityHefei 230601China Key Laboratory of Intelligent Control and Decision of Complex Systems School of AutomationBeijing Institute of TechnologyBeijing 100081China Department of Control Science and Engineering Tongji UniversityShanghai 201804China Shanghai Research Institute for Intelligent Autonomous Systems Tongji UniversityShanghai 201210China

This paper develops distributed algorithms for solving Sylvester *** authors transform solving Sylvester equations into a distributed optimization problem,unifying all eight standard distributed matrix *** the authors propose a distributed algorithm to find the least squares solution and achieve an explicit linear convergence *** results are obtained by carefully choosing the step-size of the algorithm,which requires particular information of data and Laplacian *** avoid these centralized quantities,the authors further develop a distributed scaling technique by using local information *** a result,the proposed distributed algorithm along with the distributed scaling design yields a universal method for solving Sylvester equations over a multi-agent network with the constant step-size freely chosen from configurable ***,the authors provide three examples to illustrate the effectiveness of the proposed algorithms.

关键词： Distributed optimization least squares solution linear convergence rate step-size interval Sylvester equation

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Tackling Challenges of Low-texture and Illumination Variations for Endoscopy Self-supervised Monocular Depth Estimation

Tackling Challenges of Low-texture and Illumination Variatio...

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2023 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2023

作者： Zhou, Luyan Luo, Jingjing Wang, Hongbo Zhao, Shizun Han, Yuan Li, Wenxian Fudan University Academy for Engineering and Technology Shanghai200433 China Intelligent Robot Engineering Research Center of Ministry of Education Shanghai2000433 China Shanghai Intelligent Robot Engineering Technology Research Center Shanghai200433 China Eye & Ent Hospital of Fudan University Shanghai200031 China

ISBN: (纸本)9798350337488

Extracting 3D environmental insights from endoscopy images holds immense value for minimally invasive surgical procedures. The Self-supervised Monocular Depth Estimation (SMDE) framework is promising for achieving this objective. However, existing methods struggle with low-texture and drastic illumination fluctuations in endoscopic images. To tackle this, we incorporate Photometric Aliagnment method based on pixel-wise Color Offset, and propose a carefully designed Color Offset penalty based on Reconstruction Confidence. We furthur apply an Auto-Mask mechanism and a cutting-edge backbone to enhance the performance. Our experiments employ a dataset of airway intubation images captured with a low-resolution and near-field electronic bronchoscope. The experimental results unequivocally highlight the exceptional performance of our approach, achieving root mean square error of 1.64 ± 0.22 mm after point cloud registration, which decreases by 16% than the current SoTA. Furthermore, we introduce an innovative evaluation metric rooted in Photometric Alignment Symmetry, and conduct ablation experiments on this metric. The ablation experiments furthur validate the effectiveness of proposed modules. This study underscores the efficacy of the Reconstruction Confidence-based Color Offset penalty and symmetric alignment evaluations in extracting 3D information from low-resolution and near-field endoscopy images. © 2023 IEEE.

关键词： low-texture photometric alignment reconstruction confidence self-supervised monocular endoscopy depth estimation

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Type Synthesis of Self-Alignment Parallel Ankle Rehabilitation robot with Suitable Passive Degrees of Freedom

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Chinese Journal of Mechanical engineering 2024年第1期37卷 160-175页

作者： Ya Liu Wenjuan Lu Dabao Fan Weijian Tan Bo Hu Daxing Zeng School of Mechanical Engineering Yanshan UniversityQinhuangdao 066004China School of Mechanical Engineering Dongguan University of TechnologyDongguan 523808China Dongguan Engineering Technology Research Center for Parallel Robot Dongguan 523808China The DGUT Innovation Center of Robotics and Intelligent Equipment Dongguan 523808China

The current parallel ankle rehabilitation robot(ARR)suffers from the problem of difficult real-time alignment of the human-robot joint center of rotation,which may lead to secondary injuries to the *** study investigates type synthesis of a parallel self-alignment ankle rehabilitation robot(PSAARR)based on the kinematic characteristics of ankle joint rotation center drift from the perspective of introducing"suitable passive degrees of freedom(DOF)"with a suitable number and ***,the self-alignment principle of parallel ARR was proposed by deriving conditions for transforming a human-robot closed chain(HRCC)formed by an ARR and human body into a kinematic suitable constrained system and introducing conditions of"decoupled"and"less limb".Second,the relationship between the self-alignment principle and actuation wrenches(twists)of PSAARR was analyzed with the velocity Jacobian matrix as a"bridge".Subsequently,the type synthesis conditions of PSAARR were ***,a PSAARR synthesis method was proposed based on the screw theory and type of PSAARR synthesis ***,an HRCC kinematic model was established to verify the self-alignment capability of the *** this study,93 types of PSAARR limb structures were synthesized and the self-alignment capability of a human-robot joint axis was verified through kinematic analysis,which provides a theoretical basis for the design of such an ARR.

关键词： Ankle rehabilitation robot Self-alignment Parallel mechanism Type synthesis Screw theory

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A comprehensive review on rectification and power management strategies for triboelectric nanogenerators

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Science China(Technological Sciences) 2025年第3期68卷 1-29页

作者： Zhongjie LI Bingyan CUI Biao WANG Fan SHEN Hao WU Ying GONG Yan PENG Hengyu GUO Dan ZHANG Institute of Artificial Intelligence School of Future TechnologyShanghai UniversityShanghai200444China School of Mechatronic Engineering and Automation Shanghai UniversityShanghai200444China Department of Applied Physics Chongqing UniversityChongqing400044China Engineering Research Center of Unmanned Intelligent Marine Equipment Shanghai UniversityShanghai200444China

Nanogenerators utilize nanomaterials to harvest mechanical or thermal energy at the micro-nano scale,thereby providing power for small self-sustaining *** to traditional generators,nanogenerators offer advantages such as compact size,high flexibility,and broad *** nanogenerators(TENGs),based on triboelectric theory,can collect energy from mechanical sources such as vibrations or sliding *** hold promise for powering small ***,the high pulse characteristics of their output voltage prevent them from directly charging electronic *** address the requirements of the internet of things(IoTs),this paper comprehensively reviews state-of-the-art power management systems used to enhance the current stability and output power of ***,the working principle and resistive load output characteristics of TENGs are *** management circuits(PMCs)based on full-wave rectifiers,half-wave rectifiers,and Bennet's doublers are subsequently analyzed and *** and electronic switches proposed to further improve rectifier performance are also *** switches are categorized as travel and voltagetriggered switches,while electronic switches include silicon-controlled rectifiers(SCRs),metal-oxide-semiconductor fieldeffect transistors(MOSFETs),and integrated *** conclusion,the characteristics and applications of PMCs are summarized,along with the identification of existing limitations in their ***,appropriate solutions and prospects for further development are explored.

关键词： triboelectric nanogenerators power management circuit rectifier switch

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Improving low-complexity and real-time DeepFilterNet2 for personalized speech enhancement

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International Journal of Speech technology 2024年第2期27卷 299-306页

作者： Wang, Shilin Guan, Haixin Wei, Shuang Long, Yanhua Shanghai Engineering Research Center of Intelligent Education and Bigdata Shanghai Normal University Shanghai200234 China Unisound AI Technology Co. Ltd Beijing China

DeepFilterNet2, a recently proposed real-time and low-complexity speech enhancement (SE) technique, has shown state-of-the-art SE performance in many deep noise suppression tasks. This paper proposes a new approach, termed pDeepFilterNet2, to generalize and improve the original DeepFilterNet2 for personalized speech enhancement (PSE) tasks under multi-talker noisy and reverberant conditions. Three improvements are investigated: a frame-wise speaker adaptation (FSA) is first proposed to achieve dynamic target speaker cues for generalizing the DeepFilterNet2 to pDeepFilterNet2;Then, we remove a redundant skip connection in original DeepFilterNet2 and add a simple layer of causal multi-head self-attention to enhance the model for aggregating global context information;Finally, a multi-domain loss function combing both time and frequency domain losses is introduced to further improve the PSE system performance. Moreover, different types of target speaker embedding are also investigated in this study to see their effectiveness. Our experiments are conducted on the DNS4 Challenge dataset and results show that the proposed pDeepFilterNet2 outperforms the original DeepFilterNet2 significantly across multiple evaluation metrics. Furthermore, it exhibits competitive performance when compared to our previously proposed sDPCCN, which was specifically designed for target speaker extraction. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Speech enhancement

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Base position planning of mobile manipulators for assembly tasks in construction environments

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Advances in Manufacturing 2023年第1期11卷 93-110页

作者： Dai-Jun Xie Ling-Dong Zeng Zhen Xu Shuai Guo Guo-Hua Cui Tao Song Shanghai Key Laboratory of Intelligent Manufacturing and Robotics School of Mechatronic Engineering and AutomationShanghai UniversityShanghai200444People’s Republic of China National Demonstration Center for Experimental Engineering Training Education Shanghai UniversityShanghai200444People’s Republic of China School of Mechanical and Automotive Engineering Shanghai University of Engineering ScienceShanghai201620People’s Republic of China Shanghai Collaborative Innovation Center of Intelligent Manufacturing Robot Technology for Large Components Shanghai201620People’s Republic of China

With good mobility and flexibility,mobile manipulators have shown broad applications in construction *** position(BP)planning,which refers to the robot autonomously determining its working station in the environment,is an important technique for mobile manipulators when performing the construction assembly task,especially in a large-scale construction ***,the BP planning process is tedious and time-consuming for a human worker to carry ***,to improve the efficiency of construction assembly tasks,a novel BP planning method is proposed in this paper,which can lead to appropriate BPs and minimize the number of BPs at the same ***,the feasible BP regions are generated based on the grid division and the variable workspace of the mobile ***,the positioning uncertainties of the mobile manipulator are considered in calculating the preferred BP areas using ***,a set coverage optimization model is established to obtain the minimum number of BPs using an optimization algorithm according to the greedy *** simulated experiment based on a 9-degree of free(DoF)mobile manipulator has been *** results illustrated that the time for BP planning was significantly reduced and the number of BPs was reduced by 63.41%compared to existing manual planning,which demonstrated the effectiveness of the proposed method.

关键词： Base position(BP)planning Mobile manipulators Variable workspace Positioning uncertainties Construction environments

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A multi-step regularity assessment and joint prediction system for ordering time series based on entropy and deep learning

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Autonomous intelligent Systems 2024年第1期4卷 109-125页

作者： Yichen Zhou Wenhe Han Heng Zhou Science and Technology Development Co. Ltd.of Shanghai Research Institute of Building SciencesShanghai 201506China Shanghai Engineering Research Center for Safety Intelligent Control of Building Machinery Shanghai 200032China

Customer maintenance is of vital importance to the enterprise *** assessment and efficientprediction for customer ordering behavior can offer better decision-making and reduce business costs *** to existing studies about customer behavior regularity segment and demand prediction most focus one-commerce and other fields with large amount of data,making them not suitable for small enterprises and datafeatures like sparsity and outliers are not mined when doing regularity ***,more and morecomplex network structures for demand prediction are proposed,which builds on the assumption that all thesamples have predictive value,ignoring the fine-grained analysis of different time series regularity with high *** with the above issues,a multi-step regularity assessment and joint prediction system for ordering time series *** extracting features,comprehensive assessment of customer regularity based on entropy weightmethod with the result of predictability quantification using K-Means clustering algorithm,real entropy,LZWalgorithm and anomaly detection adopting Isolation Forest algorithm not only gives an objective result to‘how highthe regularity of customers is’,filling the gap in the field of regularity quantification,but also provides a theoreticalbasis for demand prediction models *** models:Random Forest regression,XGBoost,CNN andLSTM network are experimented with sMAPE and MSLE for performance evaluation to verify the effectiveness of theproposed regularity quantitation ***,a merged CNN-BiLSTM neural network model is established forpredicting those customers with low regularity and difficult to predict by traditional machine leaning algorithms,which performs better on the data set compared to *** Forest is still used for prediction of customerswith high regularity due to its high training ***,the results of prediction,regularity quantificatio

关键词： Regularity quantification Customer assessment Time series prediction Machine learning Deep learning

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Neurobiology of Obsessive–Compulsive Disorder from Genes to Circuits:Insights from Animal Models

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Neuroscience Bulletin 2024年第12期40卷 1975-1994页

作者： Ying-Dan Zhang Dong-Dong Shi Zhen Wang Shanghai Mental Health Center Shanghai Jiao Tong University School of MedicineShanghai200030China Shanghai Key Laboratory of Psychotic Disorders Shanghai Mental Health CenterShanghai Jiao Tong University School of MedicineShanghai201108China Shanghai Intelligent Psychological Evaluation and Intervention Engineering Technology Research Center Shanghai200030China

Obsessive-compulsive disorder(OCD)is a chronic,severe psychiatric disorder that has been ranked by the World Health Organization as one of the leading causes of illness-related disability,and first-line interventions are limited in efficacy and have side-effect ***,the exact pathophysiology underlying this complex,heterogeneous disorder remains *** scenario is now rapidly changing due to the advancement of powerful technologies that can be used to verify the function of the specific gene and dissect the neural circuits underlying the neurobiology of OCD in *** and circuit-specific manipulation in rodents has provided important insights into the neurobiology of OCD by identifying the molecular,cellular,and circuit events that induce OCD-like *** review will highlight recent progress specifically toward classic genetic animal models and advanced neural circuit findings,which provide theoretical evidence for targeted intervention on specific molecular,cellular,and neural circuit events.

关键词： Obsessive-compulsive disorder(OCD) Animal models Genes Circuits Neurobiology

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Combining permissioned blockchain and Bayesian best-worst method for transparent supplier selection in supply chain management

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Science China(Technological Sciences) 2024年第8期67卷 2579-2593页

作者： LIU JiaJun ZHANG Jie LENG JieWu Shanghai Engineering Research Center of Industrial Big Data and Intelligent System Institute of Artificial IntelligenceDonghua UniversityShanghai 201620China State Key Laboratory of Precision Electronic Manufacturing Technology and Equipment Guangdong University of TechnologyGuangzhou 510006China

Supplier selection is an important business activity in order to realize the purchasing function in supply chain *** supplier selection process includes four stages,i.e.,bidding inviting,bidding,group decision-making,and results disclosure,involving the participation of manufacturing service demanders(MSDs),manufacturing service suppliers(MSSs),and ***,all the participants have raised concerns about the increased transparency in supplier ***,this study proposes a transparent supplier selection method by considering the engagement of *** this method,the Bayesian best-worst method(Bayesian BWM)is used to aggregate decision-makers'preferences into the overall optimal weights of the alternative MSSs,and the MSS with the largest weight is considered the suitable MSS for ***,blockchain is introduced to record the decision-making process information about supplier selection through a customized smart contract,where MSSs act as supervisors to supervise the decision-making process through the distributed consensus mechanism rather than directly participate in the decision-making ***,a case study of supplier selection in purchasing vibration acceleration sensors is *** result shows that the proposed method can support MSDs in selecting suitable MSS from alternative MSSs by aggregating decision-makers'preferences,and blockchain can provide credible information about the supplier selection process for MSSs,MSDs,and *** this way,the transparency of supplier selection is enhanced.

关键词： blockchain supplier selection supply chain transparency Bayesian BWM group decision-making

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Nanotwining induced by tensile fatigue and dynamic impact of laser powder bed fusion additively manufactured CoCrFeNi high-entropy alloy

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Journal of Materials Science & technology 2024年第16期183卷 241-257页

作者： Guoqing Huang Bo Li Yinan Chen Fuzhen Xuan School of Mechanical and Power Engineering East China University of Science and TechnologyShanghai 200237China Additive Manufacturing and Intelligent Equipment Research Institute East China University of Science and TechnologyShanghai 200237China Shanghai Collaborative Innovation Center for High-end Equipment Reliability Shanghai 200237China

The laser powder bed fusion(L-PBF)additively manufactured CoCrFeNi high-entropy alloy(HEA),with face-centered cubic(FCC)crystal structure,demonstrates better comprehensive mechanical properties in the building direction(BD).Loading quasi-static,dynamic fatigue,and dynamic separated Hopkinson press bar(SHPB)impact stress conditions along the BD of the L-PBF processed HEA exhibit intriguing mi-crostructural evolution *** L-PBF generates hierarchical dislocation grids containing nu-merous cell substructures within the HEA FCC grains,impeding dislocation motion during deformation and improving the *** subjected to dynamic fatigue loading,the dislocation grids restrict the mean free path of dislocations and thus trigger the activation of abundant stacking ***,nu-merous nanotwins form near the end of the fatigue *** twinning systems can also be activated under dynamic high-speed impact *** at a low temperature of 77 K,the stacking fault energy of the CoCrFeNi HEA decreases,resulting in increased activation of nanotwins,exhibiting excep-tional toughness and resistance to dynamic *** twin boundaries also impede dislocation movement for the strain *** findings hold valuable implications for the study of additively manufactured HEA parts working in extreme environments.

关键词： High-entropy alloy Nanotwins Fatigue Impact behavior Additive manufacturing

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