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6th International Conference on Frontiers of intelligent Computing: Theory and Applications, FICTA-2017

作者： Goel, Akanksha Khandelwal, Divanshu Mundhra, Jayant Tiwari, Ritu Robotics and Intelligent System Design Lab ABV-IIITM Gwalior Gwalior India

ISBN: (纸本)9789811075650

When one wants to read something, it is tough to decide the just perfect one book that one would want to read. And, given such a system is conceived and the reader can find the book he/she wishes to read, how does he/she decide where to buy that book from? Again, there are a plethora of vendors selling the same book at different prices. Thus, this paper proposes a dynamic recommendation system by extracting the relevant data from different E-portals and applying Hybrid Filtering Approach (collaborative and content-based filtering) on the collected data to recommend the books. This system makes use of user-based collaborative filtering approach using cosine similarity rule and is optimized with bee algorithm, and the results are refined by applying natural language processing on the reviews. The paper also intends to solve cold start problem by extracting available user preferences from Facebook API. © Springer Nature Singapore Pte Ltd. 2018.

关键词： Recommender systems

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Finger Movement Regression with Myoelectric Signal and Deep Neural Network

Finger Movement Regression with Myoelectric Signal and Deep ...

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2019 International Conference on Computer Science, Information Technology, and Electrical Engineering, ICOMITEE 2019

作者： Anam, Khairul Swasono, Dwiretno Istiyadi Muttaqin, Aris Zainul Hanggara, Faruq Sandi University of Jember Department of Electrical Engineering Jember Indonesia University of Jember Department of Computer Engineering Jember Indonesia University of Jember Department of Mechanical Engineering Jember Indonesia University of Jember Intelligent System and Robotics Lab Jember Indonesia

ISBN: (纸本)9781728134369

Research on electromyographic (EMG) signals is intensively carried out to help disabled people to control prosthetic hands. Neural Networks have been widely used in research on the classification of finger movements using EMG. The study of a classification system generally still works on a limited number of movements, even though the human body, especially fingers, has a nearly unlimited combination of movements to help do daily activities. To overcome this, a proportional control system is needed. In its recent development, research on myoelectric control using EMG devices is still in a laboratory environment. Hence, the results obtained in a clinical setting are often different. However, along with technological developments, the emergence of affordable and wearable commercial EMG devices such as Myo Armband, has encouraged this study to develop control systems of prosthetic fingers using regression. One of many options available is neural networks that have been widely used in various fields. By estimating each joint with a different neural network, the result shows the predicted is fitted to the actual angle with R2 as high as 99%. © 2019 IEEE.

关键词： Deep neural networks

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Learning-based adaptive estimation for AOA target tracking with non-gaussian white noise

Learning-based adaptive estimation for AOA target tracking w...

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2019 IEEE International Conference on robotics and Biomimetics, ROBIO 2019

作者： Xu, Sheng Ou, Yongsheng Wu, Xinyu Shenzhen Institutes of Advanced Technology CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems China Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen China

ISBN: (纸本)9781728163215

In angle-of-arrival (AOA) target tracking, the target states are estimated using the noisy angular measurements. The non-Gaussian measurement noise is common in practical applications and will decrease the estimation accuracy significantly. This paper is to reduce the negative impacts of the non-Gaussian white noise (NGWN), which is modeled by multiple mixture Gaussian white noises, and guarantee the estimation accuracy. A learning-based adaptive extended Kalman filter (EKF) for AOA target tracking is developed in the NGWN environment. In the proposed method, the extreme learning machine (ELM) using a three-layer neural network is applied to identify the characters of measurement noise at each sampling time. Consequence, the EKF will consider the noise characters by the trained ELM, and make the corresponding real-time adjustments to improve the tracking performance. The effectiveness of the proposed method is verified by simulation examples. © 2019 IEEE.

关键词： Target tracking

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Comprehensive Analysis for the Effect of Thermal Barrier Coating Porosity on Ultrasonic Longitudinal Wave Velocity 6th

Comprehensive Analysis for the Effect of Thermal Barrier Coa...

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6th International Conference on Life system Modeling and Simulation, LSMS 2020, and 6th International Conference on intelligent Computing for Sustainable Energy and Environment, ICSEE 2020

作者： Zhang, Shuxiao Ma, Zhiyuan Lin, Li Feng, Wei Shenzhen Key Laboratory of Smart Sensing and Intelligent Systems Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China NDT & E Laboratory Dalian University of Technology Dalian116000 China Guangdong Ultrasonic Nondestructive Testing Engineering Technology Research Center Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China Shenzhen College of Advanced Technology University of Chinese Academy of Sciences Shenzhen China Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China

ISBN: (纸本)9789813363779

According to SEM photos of ZrO2 coatings prepared by plasma spraying, 24 physical models with different porosities were constructed, and ultrasonic testing was simulated by finite-difference time-domain method, and the change of longitudinal wave velocity under porosities was analyzed according to the ultrasonic reflection coefficient amplitude spectroscopy. The simulation shows that the longitudinal wave velocity and porosity of the coating show a linear correlation given that the pore morphology and distribution state are unchanged. The simulation is verified by experiments, and it is found that the experiments and the simulation are in good agreement. This research work has important value for the determination of longitudinal wave velocity of thermal barrier coating in ultrasonic testing. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Thermal barrier coatings

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Single focused-beam acoustical tweezers: Trapping cells in 3‐D

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The Journal of the Acoustical Society of America 2023年第4_SUPPLEMENT期154卷 A263-A263页

作者： Zhixiong Gong Shiyu Li Zhichao Ma Key Lab. of Marine Intelligent Equipment and System State Key Lab. of Ocean Eng. School of Naval Architecture Ocean and Civil Eng. Shanghai Jiao Tong Univ. Dongchuan Rd. #800 Minhang District Shanghai 200240 China zhixiong.gong@*** Key Lab. of Marine Intelligent Equipment and System State Key Lab. of Ocean Eng. School of Naval Architecture Ocean and Civil Eng. Shanghai Jiao Tong Univ. Shanghai China Inst. of Medical Robotics School of Biomedical Eng. Shanghai Jiao Tong Univ. Shanghai China

Single focused beams have shown great potential in acoustofluidics and medical ultrasound because of their large pressure gradient and acoustic-thermal effect, such as acoustical tweezers and high-intensity focused ultrasound (HIFU) technique. However, the three-dimensional trapping of typical cells is still challenging since cells in water have a positive acoustic contrast factor and will be repulsive from the focus [Gong and Baudoin, Phys. Rev. Applied 18, 044033 (2022)]. In this work, to reverse this positive acoustic contrast factor into negative, we propose to use a cell-friendly medium (made of iodixanol with water) [Augustsson et al., Nat. Commun. 7, 11556 (2016)]. This enables a single focused beam to selectively trap and control cells in 3‐D, and more importantly, keeps the manipulated cells with good viability. This work will extend the applications of acoustical tweezers, which may be beneficial to single cell analysis, cellular phenotyping, precise assembly of different cells in tissue engineering, and controlled drug delivery.

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An Improved UAV Path Optimization Algorithm for Target Accurately and Quickly Localization

An Improved UAV Path Optimization Algorithm for Target Accur...

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International Conference on Informative and Cybernetics for Computational Social systems (ICCSS)

作者： Rui Liang Kai Wu Sheng Xu Tiantian Xu Xiaoyi Ma Lianyu Fu City West Power Supply Branch State Grid Tianjin Electric Power Company Tianjin China Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Shenzhen China Guangdong-Hong Kong-Macao Joint Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institute of Advanced Technology Shenzhen China State Grid Tianjin Information & Telecommunication Company Tianjin China

ISBN: (纸本)9781665402460

Angle-of-arrival (AOA) target localization using the unmanned aerial vehicle (UAV) has been widely applied in many practical applications. To localize an invasive target quickly and accurately, both the estimation and UAV path optimization algorithms are required. This paper focuses on developing a path optimization method to improve the target estimation performance. Firstly, the problem formulation of AOA target localization is introduced. Secondly, the classical pseudolinear Kalman filter (PLKF) and the gradient-based path optimization are presented. Thirdly, we analyze the problems that existed in the previous methods and propose an improved gradient-descent path optimization algorithm combined with a simple grid search method. Finally, the simulation examples verify the effectiveness of the proposed methods.

关键词： Location awareness Adaptation models Three-dimensional displays Target tracking Search methods Estimation Optimization methods

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Stairs Reconstruction with 3D Point Cloud for Gait Generation of Lower Limb Exoskeleton Robot

Stairs Reconstruction with 3D Point Cloud for Gait Generatio...

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IEEE International Conference on robotics and Biomimetics

作者： Yachun Feng Linqing Xia Yong He Can Wang Zefeng Yan Xinyu Wu Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences

With the aging of the population, a considerable number of elderly persons suffer from walking disability. Lower limb exoskeleton robots have been proved to be effective in rehabilitation training and walking assistance. Though significant advancement has been made in the last decade, lacking the ability of adapting to complex terrain is one of the main challenges that restrict the wide application of exoskeleton robots. Thus we focus on the environmental perception and corresponding gait pattern generation of lower limb assistant exoskeleton. In this paper, we introduce a method to generate gait of exoskeleton walking on a stair, which applies the L-0 minimization-based acquisition and reconstruction of stairs information through 3D Point Cloud. The results of experiments show that our method can precisely measure the physical dimension information of stairs.

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Movement Control and Attitude Adjustment of Climbing Robot on Flexible Surfaces

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IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS 2018年第3期65卷 2618-2628页

作者： Wu, Xinyu Liu, Jia Zhou, Yimin Lv, Qin Hu, Chaofang CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems and Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen China CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems and Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen China CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems and Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen China CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems and Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen China School of Electrical and Information Engineering Tianjin University Tianjin China

In this paper, a series of control algorithms have been designed for the climbing cloth robot, "Clothbot" to climb vertically. The developed algorithm consists of three parts: a sliding mode control with integral action (SMC with integral action), a linear quadratic regulator, and dead reckoning for semi-autonomous navigation. First, the SMC with integral action is developed for high-precision position tracking and speed tracking of the permanent magnet direct current (PMDC) motor installed on the robot. The error between the expected velocity and the actual velocity of the PMDC motor is adopted to design the sliding surface. In order to compensate the fluctuation of the load torque due to the varied friction during climbing, an observer is formulated to estimate the load torque in real-time. Second, the LQR is employed for attitude adjustment by an active torque so as to prevent the robot from falling or being jammed during the movement. Third, due to the onboard-limited energy, the robot is just equippedwith semi-autonomous navigation named dead reckoning carrying on primary localization and primary path planning. Experiments are performed to verify the efficacy of the proposed control algorithms.

关键词： Climbing robot flexible surface linear quadratic regulator load observer sliding mode control with integral action

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Quantitative Analysis of Mechanical-Cytoskeletal Coupling in Human Corneal Cells across Myopia Severity Levels∗

Biophysical reports

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Biophysical reports 2025年第3期5卷 100213页

作者： Geng Junyuan Lu Yue Li Shuangcheng Wang Yan Zhao Xin Institute of Optometry and Vision Science Nankai University Tianjin 300350 China Institute of Robotics and Automatic Information System and the Tianjin Key Laboratory of Intelligent Robotic Nankai University Tianjin 300350 China. Electronic address: junyuangeng@***. Institute of Robotics and Automatic Information System and the Tianjin Key Laboratory of Intelligent Robotic Nankai University Tianjin 300350 China. School of Medicine Nankai University Tianjin 300350 China Clinical College of Ophthalmology Tianjin Medical University Tianjin 300350 China. Clinical College of Ophthalmology Tianjin Medical University Tianjin 300350 China Tianjin Eye Hospital Tianjin Key Lab of Ophthalmology and Visual Science Tianjin Eye Institute Nankai University Affiliated Eye Hospital Tianjin 300350 China Nankai Eye Institute Nankai University Tianjin 300350 China. Electronic address: wangyan7143@***.

Myopia is a prevalent refractive eye disorder closely associated with alterations in corneal biomechanical properties. As fundamental units of corneal tissue, corneal cells significantly influence myopia progression through their nanomechanical characteristics. However, the biophysical mechanisms underlying this process, particularly in human corneal cells, remain unclear. This study investigates the coupling between mechanical properties and cytoskeletal morphology in human corneal cells across varying myopia severity levels. Utilizing atomic force microscopy (AFM), the Young's modulus and adhesion properties of corneal cells obtained from patients with low, moderate, and high myopia were assessed. Additionally, the cytoskeletal morphological variations were quantified by calculating the fractal dimension from AFM topography images. Experimental results reveal that with increasing myopia severity, corneal cells exhibit decreased stiffness, increased adhesion, and reduced regularity and stability of the cytoskeletal network. These evidences highlight a coupling relationship between biomechanical properties and cytoskeletal morphology in human corneal cells during myopia development at the cellular scale, offering significant insights into the pathogenesis of myopia and potential avenues for innovative preventive strategies.

关键词： atomic force microscopy cytoskeletal morphology human corneal cells mechanical properties myopia

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Abnormal Data Cleaning for Wind Turbines by Image Segmentation Based on Active Shape Model and Class Uncertainty

SSRN

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SSRN 2022年

作者： Liang, Guoyuan Su, Yahao Wu, Xinyu Ma, Jiajun Long, Huan Song, Zhe Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Guangdong Province Shenzhen China Guangdong Provincial Key Laboratory of Computer Vision and Virtual Reality Technology Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Guangdong Province Shenzhen China Guangdong-Hong Kong-Macao Joint Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Guangdong Province Shenzhen China School of Electrical Engineering Southeast University Jiang Su Province Nanjing China School of Business Nanjing University Jiang Su Province Nanjing China

Wind power curve describes the relationship between wind speed and output power of wind turbine, which may be contaminated due to various unexpected factors. Following the idea of image segmentation in our previous work, in this paper, we propose a novel image-based abnormal data cleaning algorithm aiming to provide high quality data for wind power curve modeling and relevant applications. For image binarization, a multiscale space is built to determine the optimal scale at which the most stable as well as informative shape representations are extracted. The Active Shape Model is utilized to model the power curve shape and generate a set of segmentation candidates for filtering abnormal data. To measure the cost of each candidate, the Class Uncertainty map based on dual feature images is built. And eventually the optimal segmentation boundary is determined by the optimization in the energy space. A series of comparative experiments conducted over the real-world datasets of 37 wind turbines have validated the superior performance of the proposed algorithm. © 2022, The Authors. All rights reserved.

关键词： Wind power

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