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arXiv 2023年

作者： Yi, Xinlei Li, Xiuxian Yang, Tao Xie, Lihua Hong, Yiguang Chai, Tianyou Johansson, Karl H. Lab for Information & Decision Systems Massachusetts Institute of Technology CambridgeMA02139 United States Department of Control Science and Engineering College of Electronics and Information Engineering Tongji University Shanghai201804 China Shanghai Research Institute for Intelligent Autonomous Systems China The State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang110819 China School of Electrical and Electronic Engineering Nanyang Technological University 50 Nanyang Avenue Singapore639798 Singapore 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 convex optimization with adversarial constraints. In this setting, a network of agents makes decisions at each round, and then only a portion of the loss function and a coordinate block of the constraint function are privately revealed to each agent. The loss and constraint functions are convex and can vary arbitrarily across rounds. The agents collaborate to minimize network regret and cumulative constraint violation. A novel distributed online algorithm is proposed and it achieves an O(T max{c,1−c}) network regret bound and an O(T 1−c/2) network cumulative constraint violation bound, where T is the number of rounds and c ∈ (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), the network cumulative constraint violation bound is reduced to O(T 1−c). Moreover, if the loss functions are strongly convex, then the network regret bound is reduced to O(log(T)), and the network cumulative constraint violation bound is reduced to O(√log(T)T) and O(log(T)) without and with Slater’s condition, respectively. To the best of our knowledge, this paper is the first to achieve reduced (network) cumulative constraint violation bounds for (distributed) online convex optimization with adversarial constraints under Slater’s condition. Finally, the theoretical results are verified through numerical simulations. Copyright © 2023, The Authors. All rights reserved.

关键词： Economic and social effects

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Offboard Occupancy Refinement with Hybrid Propagation for Autonomous Driving

arXiv

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arXiv 2024年

作者： Shi, Hao Wang, Song Zhang, Jiaming Yin, Xiaoting Wang, Zhongdao Wang, Guangming Zhu, Jianke Yang, Kailun Wang, Kaiwei The State Key Laboratory of Extreme Photonics and Instrumentation The National Engineering Research Center of Optical Instrumentation Zhejiang University Hangzhou310027 China The School of Robotics The National Engineering Research Center of Robot Visual Perception and Control Technology Hunan University Changsha410082 China The College of Computer Science and Technology Zhejiang University Hangzhou310027 China The Institute for Anthropomatics and Robotics Karlsruhe Institute of Technology Karlsruhe76131 Germany Huawei Noah’s Ark Lab. Canada The Department of Engineering University of Cambridge CambridgeCB2 1PZ United Kingdom

Vision-based occupancy prediction, also known as 3D Semantic Scene Completion (SSC), presents a significant challenge in computer vision. Previous methods, confined to onboard processing, struggle with simultaneous geometric and semantic estimation, continuity across varying viewpoints, and single-view occlusion. Our paper introduces OccFiner, a novel offboard framework designed to enhance the accuracy of vision-based occupancy predictions. OccFiner operates in two hybrid phases: 1) a multi-to-multi local propagation network that implicitly aligns and processes multiple local frames for correcting onboard model errors and consistently enhancing occupancy accuracy across all distances. 2) the region-centric global propagation, focuses on refining labels using explicit multi-view geometry and integrating sensor bias, especially to increase the accuracy of distant occupied voxels. Extensive experiments demonstrate that OccFiner improves both geometric and semantic accuracy across various types of coarse occupancy, setting a new state-of-the-art performance on the SemanticKITTI dataset. Notably, OccFiner elevates vision-based SSC models to a level even surpassing that of LiDAR-based onboard SSC models. Furthermore, OccFiner is the first to achieve automatic annotation of SSC in a purely vision-based approach. Quantitative experiments prove that OccFiner successfully facilitates occupancy data loop-closure in autonomous driving. Additionally, we quantitatively and qualitatively validate the superiority of the offboard approach on city-level SSC static maps. The source code will be made publicly available at https://***/MasterHow/OccFiner. Copyright © 2024, The Authors. All rights reserved.

关键词： Semantic Segmentation

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A High-Fidelity Virtual Liver Model Incorporating Biological Characteristics

SSRN

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SSRN 2023年

作者： Zhang, Xiaorui Zhang, Wenzheng Sun, Wei Song, Aiguo Xu, Tong Engineering Research Center of Digital Forensics Ministry of Education Jiangsu Engineering Center of Network Monitoring School of Computer and Software Nanjing University of Information Science & Technology Nanjing210044 China Wuxi Research Institute Nanjing University of Information Science & Technology Wuxi214100 China School of Automation Nanjing University of Information Science & Technology Nanjing210044 China State Key Laboratory of Bioelectronics Jiangsu Key Lab of Remote Measurement and Control School of Instrument Science and Engineering Southeast University Nanjing210096 China University of Southern California Los AngelesCA United States

Flexible tissue modeling plays an important role in the field of telemedicine. It is related to whether the soft tissue deformation process can be accurately, real-time and vividly simulated during surgery. However, most existing models lack the unique biological characteristics. To solve this problem, a high-fidelity virtual liver model incorporating biological characteristics, such as the viscoelastic, anisotropic and nonlinear biological characteristics, is proposed based on the finite element model. When simulating the resection of diseased livers, the model undergoes a plastic deformation process where the model loses elasticity due to excessive deformation, but does not reach the cutting fracture threshold. To improve the fidelity of the liver model, this study is the first to introduce the viscoplasticity of biological tissues to the liver model. The 3DMax2020 and OpenGL4.6 were used to build a liver surgery simulation platform, and the PHANTOM OMNI manual controller was used to sense the feedback force during the operation. The proposed model was verified from three aspects of accuracy, fidelity and real-time performance. The experimental results show that the proposed virtual liver model can enhance visual perception ability, improve deformation accuracy and fidelity. © 2023, The Authors. All rights reserved.

关键词： Simulation platform

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Biocompatible chitosan/polyethylene glycol/multi-walled carbon nanotube composite scaffolds for neural tissue engineering

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Journal of Zhejiang University-Science B(Biomedicine & Biotechnology) 2022年第1期23卷 58-73页

作者： Shengbo SANG Rong CHENG Yanyan CAO Yayun YAN Zhizhong SHEN Yajing ZHAO Yanqing HAN Shanxi Key Laboratory of Micro Nano Sensors&Artificial Intelligence Perception College of Information and ComputerTaiyuan University of TechnologyTaiyuan030024China Key Lab of Advanced Transducers and Intelligent Control System of the Ministry of Education Taiyuan University of TechnologyTaiyuan030024China College of Information Science and Engineering Hebei North UniversityZhangjiakou075000China Shanxi Six-Dimensional Artificial Intelligence Biomedical Research Institute Taiyuan030031China Department of Neurology Shanxi Provincial Cardiovascular HospitalTaiyuan030024China

Carbon nanotube(CNT)composite materials are very attractive for use in neural tissue engineering and biosensor *** scaffolds are excellent mimics of extracellular matrix due to their hydrophilicity,viscosity,and *** can also impart conductivity to other insulating materials improve mechanical stability guide neuronal cell behavior and trigger axon *** performance of chitosan(CS)/polyethylene glycol(PEG)composite scaffolds could be optimized by introducing multi-walled CNTs(MWCNTs).CS/PEG/CNT composite scaffolds with CNT content of 1%,3%,and 5%(1%=0.01 g/mL)were prepared by *** physical and chemical properties and biocompatibility were *** electron microscopy(SEM)showed that the composite scaffolds had a highly connected porous *** electron microscope(TEM)and Raman spectroscopy proved that the CNTs were well dispersed in the CS/PEG matrix and combined with the CS/PEG nanofiber *** enhanced the elastic modulus of the *** porosity of the scaffolds ranged from 83%to 96%.They reached a stable water swelling state within 24 h,and swelling decreased with increasing MWCNT *** electrical conductivity and cell adhesion rate of the scaffolds increased with increasing MWCNT *** showed that rat pheochromocytoma(PC12)cells grown in the scaffolds had characteristics similar to nerve *** measured changes in the expression of nerve cell markers by quantitative real-time polymerase chain reaction(qRT-PCR),and found that PC12 cells cultured in the scaffolds expressed growth-associated protein 43(GAP43),nerve growth factor receptor(NGFR),and class IIIβ-tubulin(TUBB3)*** research showed that the prepared CS/PEG/CNT scaffold has good biocompatibility and can be further applied to neural tissue engineering research.

关键词： Multi-walled carbon nanotube(MWCNT) Cell-scaffold PC12 cells Biocompatibility

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Resilience centrality in complex networks

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Physical Review E 2020年第2期101卷 022304-022304页

作者： Yongtao Zhang Cunqi Shao Shibo He Jianxi Gao State Key Laboratory of Industrial Control Technology Department of Control Science and Engineering Zhejiang University Hangzhou 310027 China Department of Computer Science Rensselaer Polytechnic Institute Troy New York 12180 USA

Resilience describes a system's ability to adjust its activity to retain the basic functionality when errors or failures occur in components (nodes) of the network. Due to the complexity of a system's structure, different components in the system exhibit diversity in the ability to affect the resilience of the system, bringing us a great challenge to protect the system from collapse. A fundamental problem is therefore to propose a physically insightful centrality index, with which to quantify the resilience contribution of a node in any systems effectively. However, existing centrality indexes are not suitable for the problem because they only consider the network structure of the system and ignore the impact of underlying dynamic characteristics. To break the limits, we derive a new centrality index: resilience centrality from the 1D dynamic equation of systems, with which we can quantify the ability of nodes to affect the resilience of the system accurately. Resilience centrality unveils the long-sought relations between the ability of nodes in a system's resilience and network structure of the system: the capacity is mainly determined by the degree and weighted nearest-neighbor degree of the node, in which weighted nearest-neighbor degree plays a prominent role. Further, we demonstrate that weighted nearest-neighbor degree has a positive impact on resilience centrality, while the effect of the degree depends on a specific parameter, average weighted degree βeff, in the 1D dynamic equation. To test the performance of our approach, we construct four real networks from data, which corresponds to two complex systems with entirely different dynamic characteristics. The simulation results demonstrate the effectiveness of our resilience centrality, providing us theoretical insights into the protection of complex systems from collapse.

关键词： Network resilience Network structure High dimensional systems

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Complete Z-intuitionistic Fuzzy MULTIMOORA Method with AHP and its Application to COVID-19

Research Square

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Research Square 2021年

作者： Zhang, Yijin Huang, Jie Lin, Zongbing Key Lab of Intelligent Analysis and Decision on Complex Systems Key Laboratory of Industrial Internet of Things and Networked Control Ministry of Education Chongqing University of Posts and Telecommunications Chongqing400065 China School of Mathematics and Computer Science Panzhihua University Panzhihua617000 China

For emergencies, the reliability of information can not be guaranteed. At the same time, due to the lack of information and knowledge, neither the criteria itself nor the credibility can be given a precise evaluation by decision-makers(DMs). Therefore, we combine intuitionistic fuzzy set and Z-number to get a new class of fuzzy set, complete Z-intuitionistic fuzzy set(CZIFS), and its degenerate form, A-type Z-intuitionistic fuzzy set(AZIFS) and B-type Z-intuitionistic fuzzy set(BZIFS). CZIFS can serve as a reliable tool to depict the hesitant degree both on the ambiguity and reliability of uncertain information. In addition, we introduce the score and accuracy functions and distance measure of complete Z-intuitionistic fuzzy number(CZIFN), with which we have considered both reliability information and DM-s’ preference on it. Then, we improve traditional MULTIMOORA by developing reference point(RP) model to consider both the risk and profile of alternatives and integrating analytic hierarchy process(AHP) in the process of ranking aggregation method to take into account the preference of DMs on three subordinate rankings. Besides, to solve multicriteria group decision making(MCGDM) problem, we develop improved MULTIMOORA method to the environment of CZIFN. Finally, to illustrate the proposed method, we give a numerical example, solving site selecting of Fangcang shelter hospital for COVID-19. © 2021, CC BY.

关键词： Analytic hierarchy process

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Outage Performance of Uplink Rate Splitting Multiple Access with Randomly Deployed Users

arXiv

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arXiv 2022年

作者： Lu, Huabing Xie, Xianzhong Shi, Zhaoyuan Lei, Hongjiang Zhao, Nan Cai, Jun The Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education Dalian University of Technology Dalian116024 China The School of Computer Science and Technology Chongqing University of Posts and Telecommunications Chongqing400065 China The Key Laboratory of Intelligent Perception and Computing of Anhui Province Anqing Normal University Anqing246011 China The School of Communication and Information Engineering Chongqing University of Posts and Telecommunications Chongqing400065 China Department of Electrical and Computer Engineering Concordia University MontrealQCH3G 1M8 Canada

With the rapid proliferation of smart devices in wireless networks, more powerful technologies are expected to fulfill the network requirements of high throughput, massive connectivity, and diversify quality of service. To this end, rate splitting multiple access (RSMA) is proposed as a promising solution to improve spectral efficiency and provide better fairness for the next-generation mobile networks. In this paper, the outage performance of uplink RSMA transmission with randomly deployed users is investigated, taking both user scheduling schemes and power allocation strategies into consideration. Specifically, the greedy user scheduling (GUS) and cumulative distribution function (CDF) based user scheduling (CUS) schemes are considered, which could maximize the rate performance and guarantee scheduling fairness, respectively. Meanwhile, we re-investigate cognitive power allocation (CPA) strategy, and propose a new rate fairness-oriented power allocation (FPA) strategy to enhance the scheduled users' rate fairness. By employing order statistics and stochastic geometry, an analytical expression of the outage probability for each scheduling scheme combining power allocation is derived to characterize the performance. To get more insights, the achieved diversity order of each scheme is also derived. Theoretical results demonstrate that both GUS and CUS schemes applying CPA or FPA strategy can achieve full diversity orders, and the application of CPA strategy in RSMA can effectively eliminate the secondary user's diversity order constraint from the primary user. Simulation results corroborate the accuracy of the analytical expressions, and show that the proposed FPA strategy can achieve excellent rate fairness performance in high signal-to-noise ratio region. Copyright © 2022, The Authors. All rights reserved.

关键词： Wireless networks

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Integral Sliding Mode control for PMSM with Uncertainties and Disturbances via Nonlinear Disturbance Observer

Integral Sliding Mode Control for PMSM with Uncertainties an...

引用

Chinese control Conference (CCC)

作者： Jianxiong Li Hongmei Ren Songhua Wang Yiming Fang Research Center of the Ministry of Education for Intelligent Control System and Intelligent Equipment Yanshan University Qinhuangdao China The Key Lab of Industrial Computer Control Engineering of Yanshan University Qinhuangdao China

ISBN: (数字)9789881563903

ISBN: (纸本)9781728165233

In this paper, a nonlinear disturbance observer-based (NDOB) integral sliding mode control (SMC) algorithm is proposed for speed control of permanent magnet synchronous motor (PMSM) in the presence of uncertain parameters and external time-varying load toque. Firstly, three nonlinear disturbance observers (NDOs) are constructed to estimate the lumped disturbances comprising of uncertain parameters and/or disturbances in speed loop and two current loops, respectively. Secondly, an integral sliding mode controller is developed based on the NDOs. It can be proved that the resulting closed loop system is asymptotically stable and the speed tracking error converges to zero asymptotically in theory. Finally, experiment results are given to validate the proposed control method.

关键词： Torque Disturbance observers Sliding mode control Uncertainty Velocity control Mathematical model Upper bound

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MLN-net: A multi-source medical image segmentation method for clustered microcalcifications using multiple layer normalization

arXiv

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arXiv 2023年

作者： Wang, Ke Ye, Zanting Xie, Xiang Cui, Haidong Chen, Tao Liu, Banteng College of Information Science and Technology Zhejiang Shuren University Hangzhou China State Key Laboratory of Industrial Control Technology Zhejiang University Hangzhou China School of Computer Science and Artificial Intelligence Changzhou University Changzhou China School of Engineering Newcastle university Newcastle upon Tyne United Kingdom Breast Surgery First Affiliated Hospital Zhejiang University Hangzhou China The Second Affiliated Hospital School of Medicine Zhejiang University Hangzhou China

Accurate segmentation of clustered microcalcifications in mammography is crucial for the diagnosis and treatment of breast cancer. Despite exhibiting expert-level accuracy, recent deep learning advancements in medical image segmentation provide insufficient contribution to practical applications, due to the domain shift resulting from differences in patient postures, individual gland density, and imaging modalities of mammography etc. In this paper, a novel framework named MLN-net, which can accurately segment multi-source images using only single source images, is proposed for clustered microcalcification segmentation. We first propose a source domain image augmentation method to generate multi-source images, leading to improved generalization. And a structure of multiple layer normalization (LN) layers is used to construct the segmentation network, which can be found efficient for clustered microcalcification segmentation in different domains. Additionally, a branch selection strategy is designed for measuring the similarity of the source domain data and the target domain data. To validate the proposed MLN-net, extensive analyses including ablation experiments are performed, comparison of 12 baseline methods. MLN-net enhances segmentation quality of full-field digital mammography (FFDM) and digital breast tomosynthe (DBT) images from the FFDM-DBT dataset, which achieves the average Dice similarity coefficient (DSC) of 86.52% and the average Hausdorff distance (HD) of 20.49mm on the source domain DBT. And it outperforms the baseline models for the task in FFDM images from both the CBIS-DDSM and FFDM-DBT dataset, which achieves the average DSC of 50.78% and the average HD of 35.12mm on the source domain CBIS-DDSM. Extensive experiments validate the effectiveness of MLN-net in segmenting clustered microcalcifications from different domains and the its segmentation accuracy surpasses state-of-theart methods. Code will be available at https://***/yezanting/MLN-N

关键词： Mammography

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A PD- Type iterative learning algorithm for networked control systems with missing data 2019

A PD- Type iterative learning algorithm for networked contro...

引用

2019 International Conference on Artificial Intelligence and computer Science, AICS 2019

作者： Cheng, Xiaoyan Dong, Yahui Wang, Hongbin Wang, Qinzhao Key Lab of Industrial Computer Control Engineering of Hebei Province Yanshan University Qinhuangdao066004 China Weapon and Control Department Army Academy of Armored Forces Beijing100072 China

ISBN: (纸本)9781450371506

In this paper, a PD-type iterative learning control method is proposed for a class of nonlinear discrete networked control systems with measurement signal and control signal data dropouts. Proportional and differential items of the error signal are employed in this method to modify the current control signal, which takes full advantage of the historical error signals. The data dropout is described as a stochastic and independent Bernoulli process with a given probability. In addition, the zero-order holding method is introduced at the data receivers of the controller and actuator. Finally, the stability analysis and simulation results are performed to verify the convergence and effectiveness of the proposed method. © 2019 Association for Computing Machinery.

关键词： Networked control systems

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