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2nd International Conference on Biomedical and Intelligent Systems, IC-BIS 2023

作者： Tian, Chongxuan Zhang, Yanbing Zhang, Zhenlei An, Haoyuan Li, Wei Department of Biomedical Engineering Institute School of Control Science and Engineering Shandong University Shandong Jinan China

ISBN: (纸本)9781510666733

The development of deep learning has significantly altered computer vision and given rise to a wide range of pre-made training models. It is currently utilized often in medical pathology imaging. Histopathology image analysis with computer assistance can speed up diagnosis and increase precision. This study aims to address the issue of classifying images of central nervous system tumor pathology using a new deep learning network architecture (SPACH). Ultimately, our model had a classification accuracy of 92.5%. © 2023 SPIE.

关键词： Pathology

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Power and Voltage control Based on DC Offset Injection for Bipolar Low-voltage DC Distribution System

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Journal of Modern Power Systems and Clean Energy 2023年第5期11卷 1529-1539页

作者： Xinyi Kong Jianwen Zhang Jianqiao Zhou Jiajie Zang Jiacheng Wang Gang Shi Xu Cai key Laboratory of Control of Power Transmission and Conversion of Ministry of Education Department of Electrical EngineeringShanghai Jiao Tong UniversityShanghai 200240China School of Electronic and Electrical Engineering Shanghai University of Engineering ScienceShanghaiChina School of Mechatronic Systems Engineering Simon Fraser UniversitySurreyBCCanada

The bipolar low-voltage DC(LVDC) distribution system has become a prospective solution to better integration of renewables and improvement of system efficiency and reliability. However, it also faces the challenge of power and voltage imbalance between two poles. To solve this problem, an interface converter with bipolar asymmetrical operating capabilities is applied in this paper. The steady-state models of the bipolar LVDC distribution system equipped with this interface converter in the gridconnected mode and off-grid mode are analyzed. A control scheme based on DC offset injection at the secondary side of the interface converter is proposed, enabling the bipolar LVDC distribution system to realize the unbalanced power transfer between two poles in the grid-connected mode and maintain the inherentpole voltage balance in the off-grid mode. Furthermore, this paper also proposes a primary-side DC offset injection control scheme according to the analysis of the magnetic circuit model, which can eliminate the DC bias flux caused by the secondaryside DC offset. Thereby, the potential core magnetic saturation and overcurrent issues can be prevented, ensuring the safety of the interface converter and distribution system. Detailed simulations based on the proposed control scheme are conducted to validate the function of power and voltage balance under the operation conditions of different DC loads.

关键词： Bipolar low-voltage DC distribution system interface converter DC offset injection unbalanced power voltage balance

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Human action recognition using a convolutional neural network based on skeleton heatmaps from two-stage pose estimation

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Biomimetic Intelligence & Robotics 2022年第3期2卷 22-33页

作者： Ruiqi Sun Qin Zhang Chuang Luo Jiamin Guo Hui Chai School of Electrical Engineering University of JinanJinan 250022China School of Control Science and Engineering Shandong UniversityJinan 250061China

Human action recognition based on skeleton information has been extensively used in various areas,such as human-computer *** this paper,we extracted human skeleton data by constructing a two-stage human pose estimation model,which combined the improved single shot detector(SSD)algorithm with convolutional pose machines(CPM)to obtain human skeleton *** backbone of the SSD algorithm was replaced with ResNet,which can characterize images *** addition,we designed multiscale transformation rules for CPM to fuse the information of different scales and a convolutional neural network for the classification of the skeleton keypoints heatmaps to complete action *** and outdoor experiments were conducted on the Caster Moma mobile robot platform,and without an external remote control,the real-time movement of the robot was controlled by the leader through command actions.

关键词： Convolutional neural networks Human detection Human pose estimation Human action recognition

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A Resilient control Strategy in Connected Vehicles under Actuator Attacks 7

A Resilient Control Strategy in Connected Vehicles under Act...

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7th CAA International Conference on Vehicular control and Intelligence, CVCI 2023

作者： Li, Kai Wang, Yulei Chen, Hong Gao, Jinwu State Key Laboratory of Automotive Simulation and Control The Department of Control Science Jilin University Changchun China School of Electronics and Information Engineering Tongji University Shanghai China The Department of Control Science Jilin University School of Electronics and Information Engineering Tongji University Shanghai China

ISBN: (纸本)9798350340488

With the promotion of advanced communication technology, autonomous vehicle platoons (AVPs) develop rapidly due to their advantages in enhancing traffic efficiency, road safety and reducing fuel consumption. However, as cyber physical systems, AVPs are very vulnerable to malicious attacks. In this paper, we propose a novel resilient control scheme to detect and tolerate a malicious directional actuator attack in a distributed manner which destroys the feedback control system by reversing the direction of actuator. The scheme consists of a distributed trigger mechanism with a logic-based switching criterion to detect the directional actuator attacks, and a resilient and distributed triple-step control scheme to defend against the attacks. The proposed control scheme is applied on bidirectional (BD) topology. Both global asymptotic stability and string stability of the platoon system are strictly proved via Lyapunov's stability theory. Finally, simulation results are provided to show the effectiveness of the proposed approach. © 2023 IEEE.

关键词： Autonomous vehicle platoons Directional Actuator attacks Distributed control String stability

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A review of intelligent optimization for group scheduling problems in cellular manufacturing

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Frontiers of engineering Management 2023年第3期10卷 406-426页

作者： Yuting WANG Yuyan HAN Dunwei GONG Huan LI School of Computer Science Liaocheng UniversityLiaocheng 252059China School of Information and Control Engineering China University of Mining and TechnologyXuzhou 221116China

Given that group technology can reduce the changeover time of equipment,broaden the productivity,and enhance the flexibility of manufacturing,especially cellular manufacturing,group scheduling problems(GSPs)have elicited considerable attention in the academic and industry practical *** are two issues to be solved in GSPs:One is how to allocate groups into the production cells in view of major setup times between groups and the other is how to schedule jobs in each *** a number of studies on GSPs have been published,few integrated reviews have been conducted so far on considered problems with different constraints and their optimization *** this end,this study hopes to shorten the gap by reviewing the development of research and analyzing these *** literature is classified according to the number of objective functions,number of machines,and optimization *** classical mathematical models of single-machine,permutation,and distributed flowshop GSPs based on adjacent and position-based modeling methods,respectively,are also *** but not least,outlooks are given for outspread problems and problem algorithms for future research in the fields of group scheduling.

关键词： cellular manufacturing group scheduling flowshop literature review

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A Novel Time Diffusion Model for Industrial Time Series Data Generation 13

A Novel Time Diffusion Model for Industrial Time Series Data...

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13th IEEE Data Driven control and Learning Systems Conference, DDCLS 2024

作者： Zheng, Chen Jiang, Xiaoyu Song, Zhihuan Zhang, Xinmin Shen, Bingbing College of Control Science and Engineering Zhejiang University State Key Laboratory of Industrial Control Technology Hangzhou310027 China School of Mathematics Hangzhou Normal University Hangzhou311121 China

ISBN: (纸本)9798350361674

Given the intricate temporal correlations inherent in most process industry systems, temporal dynamic modeling methods based on time series data have demonstrated superior performance in the area of industrial data-driven modeling. However, due to constraints in data acquisition and maintenance methods, obtaining a substantial volume of high-quality and intact time series data from process industries is often challenging. To address this challenge, AI-Generated Content technologies (AIGC) can be employed to produce high-quality virtual data and ensure data sufficiency. This paper proposes a novel Time Diffusion Model (TDM) for the generation of industrial time series data. TDM introduces diffusion models to better capture the temporal correlations and data distributions of industrial time series data, enabling the generation of high-quality virtual time series data. This capability extends its applicability to time series data imputation and time series data augmentation tasks. The proposed TDM model is applied to the practical primary reformer process case. The experimental results substantiate that TDM can generate industrial time series data of high quality and effectively enhance the performance of industrial data-driven tasks. © 2024 IEEE.

关键词： Spatio-temporal data

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Recent advances in metal-free CDs/g-C_(3)N_(4) photocatalysts:Synthetic strategies,mechanism insight,and applications

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Journal of Materials science & Technology 2023年第19期150卷 11-26页

作者： Xingxing Yang Lina Sheng Yongli Ye Jiadi Sun Zaijun Li Xiao Ning Jin Cao Xiulan Sun State Key Laboratory of Food Science and Technology School of Food Science and TechnologyCollaborative Innovation Center of Food Safety and Quality ControlJiangnan UniversityWuxi 214122China Yixing Institute of Food and Biotechnology Co. LtdYixing 214200China School of Chemical and Material Engineering Jiangnan UniversityWuxi 214122China National Institutes for Food and Drug Control Beijing 100050China

Carbon dots/graphite carbon nitride(CDs/g-C_(3)N_(4)),a novel composite photocatalyst,has shown great po-tential for applications in energy regeneration and environmental remediation owing to its following advantages:metal-free,low cost,easily tunable,and excellent photocatalytic ***,we reviewed the development of synthetic strategies,photocatalytic enhancement mechanisms,and pho-tocatalytic applications of CDs/g-C_(3)N_(4) in this ***,the three composite strategies of CDs and g-C_(3)N_(4)-self-assembly,solvothermal,and calcination polymerization are outlined,and their advantages and disadvantages are described in ***,the photocatalytic enhancement mechanism of the com-posite strategies was elucidated according to the variation trends of CDs/g-C_(3)N_(4) band structure,electronic properties,light absorption range,and interfacial charge ***,the applications of CDs/g-C_(3)N_(4) in hydrogen evolution,pollutant degradation,CO_(2) reduction,and bacterial disinfection in recent years are reviewed ***,the current obstacles and future research directions of CDs/g-C_(3)N_(4) are discussed from the perspective of preparation technology and practical applications,respectively.

关键词： Photocatalysis Graphite carbon nitride Carbon dots Synthetic strategy Photocatalytic application

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Binding interaction of typical emerging contaminants on Gobiocypris rarus transthyretin:an in vitro and in silico study

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Frontiers of Environmental science & engineering 2024年第11期18卷 53-64页

作者： Xiangqiao Li Huihui Liu Songshan Zhao Peter Watson Xianhai Yang Jiangsu Key Laboratory of Chemical Pollution Control and Resources Reuse School of Environmental and Biological EngineeringNanjing University of Science and TechnologyNanjing 210094China Los Alamos National Laboratory New Mexico Los AlamosNM 87545USA

Emerging contaminants(ECs)have drawn global concern,and the endocrine disrupting chemicals is one of the highly interested ECs ***,numerous ECs lacks the basic information about whether they can disturb the endocrine related biomacromolecules or elicit endocrine related detrimental effects on *** this study,the potential binding affinity and underlying binding mechanism between 29 ECs from 7 chemical groups and Gobiocypris rarus transthyretin(CrmTTR)are investigated and probed using in vitro and in silico *** experimental results demonstrate that 14 selected ECs(11 disinfection byproducts,1 pharmaceuticals and personal care product,1 alkylphenol,1 perfluoroalkyl and polyfluoroalkyl substance)are potential CrmTTR *** CrmTTR binding affinity of three ECs(i.e.,2,6-diiodo-4-nitrophenol(logRP(T_(4))=0.678±0.198),2-bromo-6-chloro-4-nitrophenol(logRP(T_(4))=0.399±0.0908),tetrachloro-1,4-benzoquinone(logRP(T_(4))=0.272±0.0655))were higher than that of 3,3′,5,5′-tetraiodo-L-thyronine,highlighting that more work should be performed to reveal their potential endocrine related harmful effects on Gobiocypris *** docking results imply that hydrogen bond and hydrophobic interactions are the dominated non-covalent interactions between the active disruptors and *** optimum mechanism-based(for CrmTTR),and high throughput screening(for CrmTTR,little skate-TTR,seabream-TTR,and human-TTR)binary classification models are developed using three machine learning algorithms,and all the models have good classification *** facilitate the use of developed high throughput screening models,a tool named“TTR Profiler”is derived,which could be employed to determine whether a given substance is a potential CrmTTR,little skate-TTR,seabreamTTR,or human-TTR disruptor or not.

关键词： Endocrine disrupting effects Hormone transporter Endocrine disrupting chemicals Disinfection byproducts Classification model

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Multi-Task Learning for Alzheimer's Disease Diagnosis and Mini-Mental State Examination Score Prediction

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Big Data Mining and Analytics 2024年第3期7卷 828-842页

作者： Jin Liu Xu Tian Hanhe Lin Hong-Dong Li Yi Pan Hunan Provincial Key Lab on Bioinformatics School of Computer Science and EngineeringCentral South UniversityChangsha 410083China Xinjiang Engineering Research Center of Big Data and Intelligent Software School of SoftwareXinjiang UniversityUrumqi 830091China School of Science and Engineering University of DundeeDundeeDD14HNUK Faculty of Computer Science and Control Engineering Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen 518055China

Accurately diagnosing Alzheimer's disease is essential for improving elderly ***,accurate prediction of the mini-mental state examination score also can measure cognition impairment and track the progression of Alzheimer's ***,most of the existing methods perform Alzheimer's disease diagnosis and mini-mental state examination score prediction separately and ignore the relation between these two *** address this challenging problem,we propose a novel multi-task learning method,which uses feature interaction to explore the relationship between Alzheimer's disease diagnosis and minimental state examination score *** our proposed method,features from each task branch are firstly decoupled into candidate and non-candidate parts for ***,we propose feature sharing module to obtain shared features from candidate features and return shared features to task branches,which can promote the learning of each *** validate the effectiveness of our proposed method on multiple *** Alzheimer's disease neuroimaging initiative 1 dataset,the accuracy in diagnosis task and the root mean squared error in prediction task of our proposed method is 87.86%and 2.5,*** results show that our proposed method outperforms most state-of-the-art *** proposed method enables accurate Alzheimer's disease diagnosis and mini-mental state examination score ***,it can be used as a reference for the clinical diagnosis of Alzheimer's disease,and can also help doctors and patients track disease progression in a timely manner.

关键词： multi-task learning Alzheimer's disease diagnosis mini-mental state examination score prediction

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Obstacle detection and autonomous stair climbing of a miniature jumping robot

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Biomimetic Intelligence & Robotics 2023年第1期3卷 11-21页

作者： Yaning Zhang Jun Zhang Bohuai Chen Haoyun Chen Aiguo Song The State Key Laboratory of Bioelectronics Jiangsu Key Lab of Remote Measurement and ControlSchool of Instrument Science and EngineeringSoutheast UniversityNanjing 210096China

Miniature jumping robots(MJRs)have difficulty executing autonomous movements in unstructured environments with obstacles because of their limited perception and computing *** study investigates the obstacle detection and autonomous stair climbing methods for *** propose an obstacle detection method based on a combination of attitude and distance detections,as well as MJRs’motion.A MEMS inertial sensor collects the yaw angle of the robot,and a ranging sensor senses the distance between the robot and the obstacle to estimate the size of the *** also propose an autonomous stair climbing algorithm based on the obstacle detection *** robot can detect the height and width of stairs and its position relative to the stairs and then repeatedly jump to climb them step by ***,the height,width,and position are sent to a control terminal through a wireless sensor network to update the information regarding the MJR and stairs in a control ***,we conduct stair detection,modeling,and stair climbing experiments on the MJR and obtain acceptable precisions for autonomous obstacle ***,the proposed obstacle detection and stair climbing methods can enhance the locomotion capability of the MJR in environmental monitoring,search and rescue,etc.

关键词： Jumping robot Obstacle detection Obstacle modeling Active perception Autonomous stair climbing

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