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Intent Pattern Recognition of Lower-limb Motion Based on Mechanical Sensors

IEEE/CAA Journal of Automatica Sinica 2017年第4期4卷 651-660页

作者： Zuojun Liu Wei Lin Yanli Geng Peng Yang School of Control Science and Engineering Hebei University of Technology Engineering Research Center of Intelligent Rehabilitation Ministry of Education Department of Electrical Engineering and Computer Science Case Western Reserve University Hebei University of Technology

Based on the regularity nature of lower-limb motion,an intent pattern recognition approach for above-knee prosthesis is proposed in this paper. To remedy the defects of recognizer based on electromyogram(EMG), we develop a pure mechanical sensor architecture for intent pattern recognition of lower-limb motion. The sensor system is composed of an accelerometer, a gyroscope mounted on the prosthetic socket, and two pressure sensors mounted under the sole. To compensate the delay in the control of prosthesis, the signals in the stance phase are used to predict the terrain and speed in the swing phase. Specifically, the intent pattern recognizer utilizes intraclass correlation coefficient(ICC) according to the Cartesian product of walking speed and terrain. Moreover, the sensor data are fused via DempsterShafer's theory. And hidden Markov model(HMM) is used to recognize the realtime motion state with the reference of the prior step. The proposed method can infer the prosthesis user's intent of walking on different terrain, which includes level ground,stair ascent, stair descent, up and down ramp. The experiments demonstrate that the intent pattern recognizer is capable of identifying five typical terrain-modes with the rate of 95.8%. The outcome of this investigation is expected to substantially improve the control performance of powered above-knee prosthesis.

关键词： Above-knee prosthesis hidden Markov model(HMM) intra-class correlation coefficient(ICC) intent pattern recognition sensor fusion

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Medical Knowledge Graph:Data Sources,Construction,Reasoning,and Applications

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Big Data Mining and Analytics 2023年第2期6卷 201-217页

作者： Xuehong Wu Junwen Duan Yi Pan Min Li Computer Science and Engineering Central South UniversityChangsha 410083China School of Computer Science Hunan First Normal UniversityChangsha 410006China School of Computer Science and Engineering Central South UniversityChangsha 410083China Computer Science and Control Engineering Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen 518000China

Medical knowledge graphs(MKGs)are the basis for intelligent health care,and they have been in use in a variety of intelligent medical ***,understanding the research and application development of MKGs will be crucial for future relevant research in the biomedical *** this end,we offer an in-depth review of MKG in this *** research begins with the examination of four types of medical information sources,knowledge graph creation methodologies,and six major themes for MKG ***,three popular models of reasoning from the viewpoint of knowledge reasoning are discussed.A reasoning implementation path(RIP)is proposed as a means of expressing the reasoning procedures for *** addition,we explore intelligent medical applications based on RIP and MKG and classify them into nine major ***,we summarize the current state of MKG research based on more than 130 publications and future challenges and opportunities.

关键词： medical knowledge graph knowledge graph construction knowledge reasoning intelligent medical applications intelligent healthcare

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NONLINEAR control WITH END-POINT ACCELERATION FEEDBACK FOR A 2-LINK FLEXIBLE MANIPULATOR - EXPERIMENTAL RESULTS

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JOURNAL OF ROBOTIC SYSTEMS 1993年第4期10卷 505-530页

作者： KHORRAMI, F JAIN, S Control/Robotics Research Laboratory School of Electrical Engineering & Computer Science Polytechnic University Brooklyn NY 11201

Experimental results for end-point positioning of multi-link flexible manipulators through end-point acceleration feedback are presented in this article. The advocated controllers are implemented on a two-link flexible arm developed at the control/Robotics Research Laboratory at Polytechnic University. The advocated approach in this article is based on a two-stage control design. The first stage is a nonlinear O(1) feedback linearizing controller corresponding to the rigid body motion of the manipulator. Because this scheme does not utilize any feedback from the end-point motion, significant vibrations are induced at the end effector. To this effect, and to enhance the robustness of the closed-loop dynamics to parameter variations, the inner loop is augmented with an outer loop based on a linear output LQR design that utilizes an end-point acceleration feedback. The forearm of the manipulator is significantly more flexible as compared with the upper arm. Experimental and simulation results validate the fact that the end-effector performance is significantly better with the proposed O(1) feedback linearizing control as compared with the linear independent joint PD control. In addition, the nonlinear control offers other advantages in terms of smaller and smoother actuator torques and reducing the effects of nonlinearities. Close conformation between simulation and experimental results validates the accuracy of the model.

关键词： Manipulators

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Minimum Epsilon-Kernel Computation for Large-Scale Data Processing

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Journal of computer science & Technology 2022年第6期37卷 1398-1411页

作者： Hong-Jie Guo Jian-Zhong Li Hong Gao School of Computer Science and Technology Harbin Institute of TechnologyHarbin 150001China Faculty of Computer Science and Control Engineering Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen 518000China

Kernel is a kind of data summary which is elaborately extracted from a large *** a problem,the solution obtained from the kernel is an approximate version of the solution obtained from the whole dataset with a provable approximate *** is widely used in geometric optimization,clustering,and approximate query processing,etc.,for scaling them up to massive *** this paper,we focus on the minimumε-kernel(MK)computation that asks for a kernel of the smallest size for large-scale data *** the open problem presented by Wang et *** whether the minimumε-coreset(MC)problem and the MK problem can be reduced to each other,we first formalize the MK problem and analyze its *** to the NP-hardness of the MK problem in three or higher dimensions,an approximate algorithm,namely Set Cover-Based Minimumε-Kernel algorithm(SCMK),is developed to solve *** prove that the MC problem and the MK problem can be Turing-reduced to each ***,we discuss the update of MK under insertion and deletion operations,***,a randomized algorithm,called the Randomized Algorithm of Set Cover-Based Minimumε-Kernel algorithm(RA-SCMK),is utilized to further reduce the complexity of *** efficiency and effectiveness of SCMK and RA-SCMK are verified by experimental results on real-world and synthetic *** show that the kernel sizes of SCMK are 2x and 17.6x smaller than those of an ANN-based method on real-world and synthetic datasets,*** speedup ratio of SCMK over the ANN-based method is 5.67 on synthetic ***-SCMK runs up to three times faster than SCMK on synthetic datasets.

关键词： approximate query processing kernel large-scale dataset NP-hard

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Energy characteristics of coal damage deformation under triaxial compression

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Bulletin of engineering Geology and the Environment 2025年第6期84卷 1-15页

作者： Zhang, Yao Li, Bobo Wang, Bin Ren, Chonghong Xu, Jiang College of Mining Guizhou University Guiyang550025 China Department of Computer Science Guizhou Police College Guiyang550005 China Guizhou Key Laboratory of Comprehensive Utilization of Non-Metallic Mineral Resources Guiyang550025 China National & Local Joint Laboratory of Engineering for Effective Utilization of Regional Mineral Resources From Karst Areas Guizhou University Guiyang550025 China State Key Laboratory of Coal Mine Disaster Dynamics and Control Chongqing University Chongqing400044 China

With respect to underground engineering, activities involving the mining of mineral resources, coal is found in a complex environment, in which temperature, gas, and external loads combine. In order to explore damage deformation, including energy transformation mechanisms in coal under different failure conditions, a triaxial compression test at different temperatures, and at different gas pressures was carried out by using triaxial servo-controlled seepage equipment of thermo-fluid–solid coupling. Based on this test, when the influence of thermal damage is examined, the whole damage change equation of coal under different temperatures and external loads might be obtained. Moreover, a damage constitutive model for coal at different temperatures, and under different gas pressures was established by considering the degradation of coal’s mechanical properties caused by gas pressure and temperature. Furthermore, concerning the whole process relating to coal’s deformation and destruction under complex stress, an unstable phenomenon driven by energy, including energy’s build-up, and dispersal that shows coal damage and instability is exhibited. Therefore, a mathematical expression of energy, based on damage and deformation of coal rock, that examined the effects of temperature and gas pressure, has been obtained in this paper. The results revealed the various stage characteristics in the deformation and disintegration process that were, basically, similar under different temperatures and gas pressures. Temperature and gas pressure possess a greater impact on coal’s mechanical properties than other factors. Secondly, a damage constitutive model for coal under different temperatures and gas pressures was established in order to consider the degradation of coal’s mechanical properties caused by temperature and gas pressure. In addition, by considering the influence of temperature and gas pressure, the mathematical expression of energy dissipation, based on coal damage and de

关键词： Compression testing

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Sensitivity limitations in nonlinear feedback control

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SYSTEMS & control LETTERS 1996年第4期27卷 249-254页

作者： Seron, MM Goodwin, GC Centre for Industrial Control Science Department of Electrical and Computer Engineering University of Newcastle Newcastle NSW 2308 Australia

In this paper we define nonlinear sensitivity and complementary sensitivity operators of a feedback control loop and show that they satisfy a complementarity constraint. We then consider the case of general nonlinear open-loop operators that give rise to nonlinear sensitivities that are Lipschitz operators on some Banach space. Under these conditions, we obtain lower bounds on the Lipschitz constants of both operators for open-loop nonminimum phase and unstable nonlinear systems. These results parallel those known in linear control theory on the H-infinity norms of S and T. We finally point to the relevance of the defined nonlinear sensitivities in robustness issues.

关键词： nonlinear feedback systems complementarity sensitivity limitations Lipschitz operators robustness

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Improved taboo search algorithm for designing DNA sequences

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Progress in Natural science:Materials International 2008年第5期18卷 623-627页

作者： Kai Zhang a, Jin Xu a,b, Xiutang Geng a, Jianhua Xiao a, Linqiang Pana, a The Key Laboratory of Image Processing and Intelligent control, Department of control science and engineering, Huazhong University of science and Technology, Wuhan 430074, China b School of Electronic engineering and computer science, Peking University, Beijing 100871, China The Key Laboratory of Image Processing and Intelligent Control Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan 430074 China School of Electronic Engineering and Computer Science Peking University Beijing 100871 China

The design of DNA sequences is one of the most practical and important research topics in DNA computing. We adopt taboo search algorithm and improve the method for the systematic design of equal-length DNA sequences, which can satisfy certain combinatorial and thermodynamic constraints. Using taboo search algorithm, our method can avoid trapping into local optimization and can nd a set of good DNA sequences satisfying required constraints.

关键词： DNA computing Taboo search algorithm DNA sequence design

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Mobile Crowdsourcing Task Allocation Based on Dynamic Self-Attention GANs

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computers, Materials & Continua 2024年第4期79卷 607-622页

作者： Kai Wei Song Yu Qingxian Pan School of Computer and Control Engineering Yantai UniversityYantai264005China School of Computer and Information Science Southwest UniversityChongqing400715China

Crowdsourcing technology is widely recognized for its effectiveness in task scheduling and resource *** traditional methods for task allocation can help reduce costs and improve efficiency,they may encounter challenges when dealing with abnormal data flow nodes,leading to decreased allocation accuracy and *** address these issues,this study proposes a novel two-part invalid detection task allocation *** the first step,an anomaly detection model is developed using a dynamic self-attentive GAN to identify anomalous *** to the baseline method,the model achieves an approximately 4%increase in the F1 value on the public *** the second step of the framework,task allocation modeling is performed using a twopart graph matching *** phase introduces a P-queue KM algorithm that implements a more efficient optimization *** allocation efficiency is improved by approximately 23.83%compared to the baseline *** results confirm the effectiveness of the proposed framework in detecting abnormal data nodes,enhancing allocation precision,and achieving efficient allocation.

关键词： Mobile crowdsourcing task allocation anomaly detection GAN attention mechanisms

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Robust Text Detection in Natural Scenes Using Text Geometry and Visual Appearance

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International Journal of Automation and computing 2014年第5期11卷 480-488页

作者： Sheng-Ye Yan Xin-Xing Xu Qing-Shan Liu School of Information and Control Nanjing University of Information Science and Technology School of Computer Engineering Nanyang Technological University

This paper proposes a new two-phase approach to robust text detection by integrating the visual appearance and the geometric reasoning rules. In the first phase, geometric rules are used to achieve a higher recall rate. Specifically, a robust stroke width transform(RSWT) feature is proposed to better recover the stroke width by additionally considering the cross of two strokes and the continuousness of the letter border. In the second phase, a classification scheme based on visual appearance features is used to reject the false alarms while keeping the recall rate. To learn a better classifier from multiple visual appearance features, a novel classification method called double soft multiple kernel learning(DS-MKL) is proposed. DS-MKL is motivated by a novel kernel margin perspective for multiple kernel learning and can effectively suppress the influence of noisy base kernels. Comprehensive experiments on the benchmark ICDAR2005 competition dataset demonstrate the effectiveness of the proposed two-phase text detection approach over the state-of-the-art approaches by a performance gain up to 4.4% in terms of F-measure.

关键词： Text detection geometric rule stroke width transform (SWT) support vector machine (SVM) multiple kernel learning (MKL)

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MEET: A Million-Scale Dataset for Fine-Grained Geospatial Scene Classification with Zoom-Free Remote Sensing Imagery

arXiv

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arXiv 2025年

作者： Li, Yansheng Wu, Yuning Cheng, Gong Tao, Chao Dang, Bo Wang, Yu Zhang, Jiahao Zhang, Chuge Liu, Yiting Tang, Xu Ma, Jiayi Zhang, Yongjun Information and computing science from Shandong University Weihai China Pattern recognition and intelligent system from the Huazhong University of Science and Technology Wuhan China Computer science and technology from Wuhan University Wuhan China Xidian University Xi’an China Pattern recognition and intelligent systems from Northwestern Polytechnical University Xi’an China School of Mathematics and Statistics Huazhong University of Science and Technology Wuhan China Institute for Pattern Recognition and Artificial Intelligence Huazhong China University of Science and Technology Remote sensing science and technology from Wuhan University Wuhan China School of Remote Sensing and Information Engineering Wuhan University Wuhan China Electronic circuit and system from Xidian University Xi’an China University of Colorado at Boulder BoulderCO United States Control science and engineering from the Huazhong University of Science and Technology Wuhan China Geodesy and photography from Wuhan University Wuhan China

Accurate fine-grained geospatial scene classification using remote sensing imagery is essential for a wide range of applications. However, existing approaches often rely on manually zooming remote sensing images at different scales to create typical scene samples. This approach fails to adequately support the fixed-resolution image interpretation requirements in real-world scenarios. To address this limitation, we introduce the Million-scale finE-grained geospatial scEne classification dataseT (MEET), which contains over 1.03 million zoom-free remote sensing scene samples, manually annotated into 80 fine-grained categories. In MEET, each scene sample follows a scene-in-scene layout, where the central scene serves as the reference, and auxiliary scenes provide crucial spatial context for fine-grained classification. Moreover, to tackle the emerging challenge of scene-in-scene classification, we present the Context-Aware Transformer (CAT), a model specifically designed for this task, which adaptively fuses spatial context to accurately classify the scene samples. CAT adaptively fuses spatial context to accurately classify the scene samples by learning attentional features that capture the relationships between the center and auxiliary scenes. Based on MEET, we establish a comprehensive benchmark for fine-grained geospatial scene classification, evaluating CAT against 11 competitive baselines. The results demonstrate that CAT significantly outperforms these baselines, achieving a 1.88% higher balanced accuracy (BA) with the Swin-Large backbone, and a notable 7.87% improvement with the Swin-Huge backbone. Further experiments validate the effectiveness of each module in CAT and show the practical applicability of CAT in the urban functional zone mapping. The source code and dataset will be publicly available at https://***/project/***. Copyright © 2025, The Authors. All rights reserved.

关键词： Image classification

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