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IEEE/RSJ International Conference on Intelligent Robots and systems (IROS)

作者： Chenhao Liu Jingang Yi Long He Yijun Zhang Xiufeng Zhang Tao Liu State Key Laboratory of Fluid Power and Mechatronic Systems School of Mechanical Engineering Zhejiang University Hangzhou China Department of Mechanical and Aerospace Engineering Rutgers University Piscataway NJ USA Zhiyuan Research Institute Hangzhou China Department of Orthopedics The First Affiliated Hospital Zhejiang University School of Medicine Hangzhou China Key Laboratory of Rehabilitation Technical Aids Technology and System of the Ministry of Civil Affairs National Research Center for Rehabilitation Technical Aids Beijing China

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

The human foot arch plays a significant role in bearing weight, keeping balance, and walking efficiently. In this study, we present a pneumatic arch support insole (PASI) and a foot arch stiffness-based dynamic plantar support control to reduce the metabolic cost of walking. We first obtain the foot arch quasi-stiffness estimation over the gait phase by conducting multiple subject experiments. The design and modeling of the PASI and foot-insole interactions are then discussed. A model predictive control scheme is presented to dynamically regulate the foot arch stiffness over the gait phase by using the active PASI. We validate the system experimentally and conduct multi-subject walking tests. The results show that dynamic plantar support control of the foot arch stiffness reduces the metabolic cost by 7.99% compared to regular walking. In contrast, passive support without dynamic regulation increases the metabolic cost by 6.60%. The new pneumatic insoles and dynamic support method demonstrate promising potential for everyday and medical applications.

关键词： Legged locomotion Biomedical equipment Costs Estimation Medical services Regulation Intelligent robots Foot Predictive control

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A Smart Droplet Microfluidic system for Single-Cell Selective Lysis and Real-Time Sorting Based on Micro-Injection and Image Recognition

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SSRN 2023年

作者： Yu, Zhihang Jin, Jing Chen, Siyuan Shui, Lingling Chen, Huaying Shi, Liuyong Zhu, Yonggang Center for Microflows and Nanoflows School of Mechanical Engineering and Automation Harbin Institute of Technology Shenzhen518055 China Joint International Laboratory of Optofluidic Technology and System National Center for International Research on Green Optoelectronics School of Information and Optoelectronic Science and Engineering South China Normal University Guangzhou510006 China Mechanical and Electrical Engineering College Hainan University Haikou570228 China

Single-cell analysis has important implications for understanding the specificity of cells. To analyze the specificity of rare cells in complex biological samples such as blood and biopsies, selective lysis of single cells is pivotal but difficult. Microfluidics, particularly droplet microfluidics, has emerged as a promising tool for single-cell analysis. In this paper, we present a smart droplet microfluidic system that allows for single-cell selective lysis and real-time sorting, aided by the techniques of micro-injection and image recognition. A custom droplet and single-cell recognition program based on Python is proposed, which can also coordinate the operation of various parts of the microfluidic system. We have systematically investigated the effects of voltage and injection pressure applied to the oil-water interface on droplet micro-injection. An efficient and selective droplet injection scheme with the image feedback has been demonstrated. The droplet injection efficiency is found to increase dramatically from 2.5% to about 100%. Furthermore, we have proved that cell lysis solution can be selectively injected into target single-cell droplets. Then these droplets are shifted into the sorting area, with the sorting efficiency for K562 cells reaching up to 73%. The system function is finally explored by introducing complex cell samples, namely K562 cells and HUVECs, with a success rate of 75.2% in treating K562 cells as targets. This system enables automated single-cell selective lysis without the need for manual handling and sheds new light on the cooperation with other detection techniques for a broad range of single-cell analysis. © 2023, The Authors. All rights reserved.

关键词： Microfluidics

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Optimal condition-based maintenance decisions for group-replacement multi-component repairable system

Optimal condition-based maintenance decisions for group-repl...

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14th International Conference on Quality, Reliability, Risk, Maintenance, and Safety engineering (QR2MSE 2024)

作者： Yankai Qin Chao Shang Xiangyu Li Xiaohong Zhang Yuangeng Luo Miao Zhang CCTEG Taiyuan Research Institute Co Ltd Taiyuan People's Republic of China Department of Automation Tsinghua University Beijing People's Republic of China School of Mechanical and Transportation Engineering Taiyuan University of Technology Taiyuan People's Republic of China Division of Industrial and System Engineering Taiyuan University of Science and Technology Taiyuan People's Republic of China

ISBN: (数字)9781837241958

Multi-component replacement repairable systems refer to systems wherein all critical components are replaced in batches after a given production cycle, while defective parts are taken offline for maintenance before being reused as the system continues to operate. This paper focuses on multi-component replacement repairable systems composed of multiple identical components, defining a grouped replacement and offline condition-based maintenance strategy. The concept of maintenance degree is introduced to indicate the extent of maintenance on a component, and a model is constructed where maintenance effects, costs, and durations are determined by this degree of maintenance. By analyzing the state transition characteristics of the system operating under alternating conditions of operational and replacement components, a steady-state probability model of system degradation is derived. Considering factors such as maintenance time, cost, and effectiveness, an average cost rate model within a finite time frame is established to determine the optimal system replacement period, preventive maintenance thresholds, and degree of maintenance. The correctness and effectiveness of the strategy and model are verified using a seven-roll continuous hot-rolling system as a case study, along with an analysis of parameter sensitivity.

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Metalized plastic current collectors: Bridge to high energy density reconciling high safety for lithium-ion batteries

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Journal of Energy Storage 2025年 125卷

作者： Lu, Xianhang Hao, Ming Fu, Yunhe Xie, Mingming Su, Shaokang Hu, Yuxiang Bian, Xin Xie, Yuanhua Ba, Yaoshuai Zhao, Xinying Du, Xuefeng Chen, Zhengwei Ba, Dechun Liu, Kun School of Mechanical Engineering and Automation Northeastern University Shenyang110819 China Vacuum Science and Aerospace Engineering Research Center Northeastern University Shenyang110819 China Key Laboratory of Advanced Functional Materials College of Materials Science and Engineering Beijing University of Technology Beijing100124 China Institute of Fluid Engineering Zhejiang University Hangzhou310027 China School of Equipment Engineering Shenyang Ligong University Shenyang110159 China Co. Ltd. Shenyang110122 China

The energy density of mainstream lithium-ion batteries (LIBs) has nearly reached theoretical limits due to the growing demand for new energy vehicles. However, the LIBs continue to struggle with meeting the requirements of applications. Increasing energy density typically involves raising the nickel content and charging cut-off voltage, these strategies can compromise the structural stability of cathode and the electrochemical stability of electrolyte, thereby increasing the risk of battery fires. The challenge of balancing high energy density with high safety remains a significant barrier to the development of LIBs. The metalized plastic current collector (MPCC), with its sandwich-like structure composed of "conductive layer-support layer-conductive layer", offers a potential solution. The MPCCs' low thermal deformation temperature and plasticity mismatch with electrode materials allow it to disrupt continuous short-circuit states in extreme conditions, preventing explosions. Additionally, the MPCCs could pull "flameproof, lightweight, thinning, and low-cost" all together, making it a feasible route for large-scale production to co-enhance energy density and safety of LIBs. Currently, on the eve of scaling and standardization, the new structure of MPCCs poses new challenges, particularly in the preparation process and equipment. This review delves into the structure, performance, application, and preparation status of MPCCs. It highlights the explosion-proof mechanism, process route, and coating equipment, summarizes the key challenges in MPCCs' application and preparation while exploring the prospects in next-generation battery systems. Additionally, the review discusses the modification strategies for MPCCs and provides an outlook on their scalability and future integration with advanced battery systems. © 2025 Elsevier Ltd

关键词： Lithium-ion batteries

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A Real-time Framework of Multi-Camera Vehicle Tracking system

A Real-time Framework of Multi-Camera Vehicle Tracking Syste...

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2024 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2024

作者： Zhuang, Hanyang Chen, Xingyuan Lan, Jianglin Wang, Ying Lu, Zhaoxuan Wang, Chunxiang Yang, Ming University of Michigan Shanghai Jiao Tong University Joint Institute Shanghai Jiao Tong University Shanghai200240 China University of Glasgow James Watt School of Engineering GlasgowG12 8QQ United Kingdom Shanghai Jiao Tong University School of Mechanical Engineering Shanghai200040 China Shanghai Intelligent and Connected Vehicle R and D Center Co. LTD Shanghai201400 China Shanghai Jiao Tong University Department of Automation Shanghai200240 China Ministry of Education of China Key Laboratory of System Control and Information Processing Shanghai200240 China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai200240 China

ISBN: (纸本)9798350372601

Multi-camera vehicle tracking (MCVT) system is a key technology to build an intelligent city and intelligent transportation system. The MCVT system utilizes roadside monitoring devices and computing platforms to achieve city-level road traffic perception at a finer scale by tracking each vehicle on the road to obtain the trajectory. The existing MCVT system mainly focuses on dealing with the algorithm modules separately, without studying the real-time performance and system architecture of the entire pipeline. However, in real-world applications, many of the tricks in improving evaluation metrics are not applicable since there is endless traffic flow running all the time. Therefore, this paper proposes a real-time framework of the MCVT system to streamline all the algorithm modules with proper data flow. Firstly, a multi-threaded multi-vehicle tracking (MVT) module is developed to detect vehicles in each camera. Re-identification is implemented during MVT to provide the feature for tracking in the same camera and across different cameras. Then, after the vehicle leaves the camera field of view, the feature of vehicle trajectory is calculated by averaging the feature at each frame. Meanwhile, a background thread runs continuously to match the incoming feature of vehicle trajectory with past features by conducting a topology searching method. In the end, the vehicle trajectories with well-matched features are considered to be the same vehicle. The entire pipeline has been validated on two different datasets, the precision is 0.64 in the CityFlow dataset which uses 6 cameras simultaneously. In the customized dataset, the same method can still reach real-time when using 16 cameras at the same time with smaller network modules. © 2024 IEEE.

关键词： Vehicle locating systems

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Special Issue: Challenges and Opportunities in Computing research to Enable Next-Generation engineering Applications

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Journal of Computing and Information Science in engineering 2023年第6期23卷 060301页

作者： Allen, Janet K. Esfahani, Ehsan Gupta, S.K. Gurumoorthy, Balan He, Bin Liu, Ying Michopoulos, John G. Panchal, Jitesh H. Purwar, Anurag Wärmefjord, Kristina School of Industrial and Systems Engineering University of Oklahoma NormanOK73019 United States Department of Mechanical and Aerospace Engineering University at Buffalo BuffaloNY14260 United States Department of Aerospace and Mechanical Engineering Viterbi School of Engineering University of Southern California Los AngelesCA90089 United States Department of Mechanical Engineering Indian Institute of Science Bangalore Karnataka560012 India School of Mechatronic Engineering and Automation Shanghai University Shanghai200444 China Department of Mechanical Engineering School of Engineering Cardiff University CardiffCF24 3AA United Kingdom Naval Research Laboratory WashingtonDC20375 United States School of Mechanical Engineering Purdue University West LafayetteIN47907 United States Department of Mechanical Engineering State University of New York Stony BrookNY11794-2300 United States Industrial and Materials Science Department Chalmers University of Technology GöteborgSE-41296 Sweden

Recent advances in computing and information science such as artificial intelligence (AI), machine learning (ML), edge computing, cloud computing, metacomputing, and quantum computing are creating new computing paradigms. These advances are providing new opportunities for new research and application development. For instance, the adoption of Industry 4.0 enabled by AI/ML is fundamentally changing how products are designed, manufactured, maintained, and recycled. It enables consideration of all aspects of the product life cycle and realizing sustainable designs and helps us in achieving carbon neutrality. Intelligent machines such as robots and autonomous vehicles are revolutionizing human–machine interactions and increasing digitalization in the manufacturing and transportation industries. It is important for the Journal of Computing and Information Science in engineering (JCISE) community to identify challenges and opportunities in these emerging areas and inspire new researchers to join the field and become a part of the community. This Special Issue consists of 19 position papers that span a wide variety of topics of interest to the JCISE community. These position papers identify challenges and opportunities, outline new areas of research, and point out new applications that will be enabled by advances in this field.

关键词： engineering systems and industry applications

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Imbalanced Data Generation and Fusion for In-Situ Monitoring of Laser Powder Bed Fusion

SSRN

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SSRN 2022年

作者： Li, Jingchang Cao, Longchao Liu, Huaping Zhou, Qi Zhang, Xiangdong Li, Menglei School of Aerospace Engineering Huazhong University of Science & Technology Wuhan430074 China School of Mechanical Engineering & Automation Wuhan Textile University Wuhan430200 China Wuhan Second Ship Design and Research Institute Wuhan430064 China

As one of the popular metal additive manufacturing (AM) techniques, laser powder bed fusion (LPBF) can produce near net shape products with complex geometries. Unfortunately, the LPBF technology still largely suffer from poor part consistency and process repeatability. This has driven significant research efforts combining process sensing and data-driven models to perform in-situ monitoring for ensuring part quality. However, the collected sensing datasets in actual applications may be imbalanced and making it challenging for in-situ monitoring. In this paper, we propose an imbalanced data generation and fusion approach to achieve in-situ quality monitoring with imbalanced datasets in the LPBF process. Three imbalanced datasets of layer-wise images, acoustic emission (AE) signals, and photodiode signals are first collected and created by the developed multi-sensor in-situ monitoring system. Then, a Generative Adversarial Network (GAN)-based data generation model is proposed to generate high-quality samples of the minority classes. Finally, a deep learning (DL)-based multi-sensor fusion method is established to fuse the three augmented balanced datasets. Results show that the generated high-quality samples can significantly improve the model performance, and the proposed DL-based multi-sensor fusion model outperforms the single-sensor-based quality classification models, providing a possible way for imbalanced quality monitoring in the LPBF process. © 2022, The Authors. All rights reserved.

关键词： 3D printers

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Riemannian Online Optimistic Algorithms with Dynamic Regret

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IEEE Transactions on Automatic Control 2025年

作者： Wang, Xi Yuan, Deming Hong, Yiguang Hu, Zihao Wang, Lei Shi, Guodong University of New South Wales School of Electrical Engineering & Telecommunications SydneyNSW2052 Australia Nanjing University of Science and Technology School of Automation Nanjing210094 China Tongji University Shanghai Research Institute for Intelligent Autonomous Systems Shanghai201210 China Hong Kong University of Science and Technology Department of Mathematics Hong Kong Zhejiang University College of Control Science and Engineering Zhejiang 310058 China The University of Sydney Australian Center for Robotics School of Aerospace Mechanical and Mechatronic Engineering NSW2006 Australia

In this paper, we consider Riemannian online convex optimization with dynamic regret, which involves minimizing the cumulative loss difference between a learner's decisions and a sequence of adaptive decisions across dynamic environments over time on Riemannian manifolds. First, we propose Riemannian Online Optimistic Gradient Descent (R-OOGD), which extends the classical optimistic algorithms to Riemannian manifolds, requiring one gradient inquiry per round. We then propose Riemannian Adaptive Online Optimistic Gradient Descent (R-AOOGD) by incorporating the meta-expert framework into R-OOGD. We analyze the dynamic regret of R-OOGD and R-AOOGD in terms of the regularity of the sequence of cost functions and comparators. The dynamic regret bound matches the results in Euclidean space and with a scale adjustment of O(1+κ D2/√1-KD2) related to the sectional curvature lower bound κ, sectional curvature upper bound and feasible set diameter. Finally, we provide numerical experiments to illustrate the performance of the proposed algorithms. © 1963-2012 IEEE.

关键词： Optimization algorithms

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Novel Truncated-rank Graph-structured and Tree-guided Sparse Linear Mixed Models for Variable Selection on Genome-wide Association Studies

Novel Truncated-rank Graph-structured and Tree-guided Sparse...

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2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024

作者： Liu, Xiang Liu, Xueling Diao, Jing Zheng, Mengyao Li, Jihe Xie, Yongyi Lai, Kang Geng, Xiao Song, Yijun Jiang, Linshan National University of Singapore School of Computing Singapore National University Health System Group Technology Office Singapore Peking University School Hospital of Stomatology National Center for Stomatology National Clinical Research Center for Oral Diseases Department of Preventive Dentistry China Harvard University Harvard T.H. Chan School of Public Health United States Peking University School of Software and Microelectronics China Tongji University Shanghai Skin Disease Hospital Institute of Dermatology School of Medicine China Nanyang Technological University School of Mechanical & Aerospace Engineering Singapore Peking University Third Hospital Engineering Research Center of Bone and Joint Precision Medicine Ministry of Education Orthopaedic Department China Zhejiang University of Finance & Economics Dongfang College China National University of Singapore Institute of Data Science Singapore

ISBN: (纸本)9798350386226

Variable selection for genome-wide association studies is a key focus for bioinformatics researchers in high-performance computing. The rapid growth of biological and biomedical data demands has led to high-dimensional, heterogeneous datasets characterized by non-i.i.d. properties and numerous response variables, often resulting in false negatives or positives in recovered results. Traditional methods, when nalively applied, yield suboptimal performance due to confounding factors. To account for the complex interdependencies in heterogeneous data and enhance the practical outcomes of genome-wide association studies, we introduce two methods, TGsLMM and TTsLMM, which balance effects between response and explanatory variables for subpopulation inference. Our unified framework performs sparse variable selection using graph-structured or tree-guided structures in a low-rank linear mixed model. Additionally, we extend our approach to high-dimensional datasets and adaptively select the covariance structure for genomic data. Extensive experiments on synthetic and three real-world datasets emphasize the robustness and effectiveness of our proposed methods, achieving the highest ROC area compared to baselines and superior results for future potential. © 2024 IEEE.

关键词： Confounding factors genome-wide association study mixed model variable selection

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A model for universal spatial variations of temperature fluctuations inturbulent Rayleigh-Bénard convection

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Theoretical & Applied Mechanics Letters 2021年第2期11卷 102-104页

作者： Xiaozhou He Eberhard Bodenschatz Guenter Ahlers School of Mechanical Engineering and Automation Harbin Institute of TechnologyShenzhen 518055China Max Planck Institute for Dynamics and Self Organization D-37073 GöttingenGermany International Collaboration for Turbulence Research Institute for Nonlinear Dynamics University of GöttingenD-37073 GöttingenGermany Laboratory of Atomic and Solid-State Physics and Sibley School of Mechanical and Aerospace Engineering Cornell UniversityIthacaNY 14853USA Department of Physics University of CaliforniaSanta BarbaraCA 93106USA

We propose a theoretical model for spatial variations of the temperature varianceσ2(z,r)(z is the dis-tance from the sample bottom and r the radial coordinate)in turbulent Rayleigh-Bénard convection(RBC).Adapting the“attached-eddy”modelofshearflowtothe plumesofRBC,wederivedanequationforσ2 which is based on the universal scaling of the normalized RBC temperature *** equation in-cludes both logarithmic and power-law dependences on z/λth,whereλth is the thermal boundary layer *** equation parameters depend on r and the Prandtl number Pr,but have only an extremelyweak dependence on the Rayleigh number Ra Thus our model provides a near-universal equation for thetemperature variance profile in turbulent RBC.

关键词： Rayleigh-Bénard convection Temperature variance profile Attached-eddy Law of wall

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