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arXiv 2019年

作者： Tzvetanov, Tzvetomir Anhui Province Key Laboratory of Affective Computing Advanced Intelligent Machine School of Computer Science and Information Engineering Hefei University of Technology Hefei China

In a recent publication (Tzvetanov (2018), bioRxiv 465807), I made an extensive analysis with computational modelling and psychophysics of the simple experimental design of Dr. *** (Tadin, Lappin, Gilroy and Blake (2003), Nature, 424:312-315) about motion perception changes in humans due to size and contrast of the stimulus. This publication sparked from strong claims made in Schallmo et al. (2018) (eLife, 7:e30334) about two important points: (1) "divisive normalization", not inhibitory and excitatory mechanisms, creates the observed psychophysical results and (2) drug-enhanced inhibition showed perceptual outcomes that hint to "weaker suppression" (i.e. inhibition) not stronger "suppression". Schallmo & Murray (2018, bioRxiv, 495291) presented concerns about my extensive publication, specifically about the parts where I directly analysed some of their methods, results and claims. Here, I show that their concerns do not provide clear answers to my specific points and further do not mention other major critiques of data interpretation and modelling of this experimental design. Therefore, I maintain all my claims that were elaborated in details in my first publication (Tzvetanov, 2018, bioRxiv 465807): the specific ones that analyse the results of their and other studies, but also the more broad modelling that is applicable to any study using the simple experimental design of Dr. ***. Copyright © 2019, The Authors. All rights reserved.

关键词： Statistics

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Robust Tensor Principal Component Analysis Based on F-norm

Robust Tensor Principal Component Analysis Based on F-norm

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IEEE International Conference on Mechatronics and Automation

作者： Weimin Ge Jinxiang Li Xiaofeng Wang National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Tianjin University of Technology Binshui Xidao 391 Xiqing District Tianjin China Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control Tianjin University of Technology Binshui Xidao 391 Xiqing District Tianjin China

ISBN: (数字)9781728164168

ISBN: (纸本)9781728164175

Tensor principal component analysis (TPCA) has been widely used to extract appearance features of colour objects or colour scenes presented in tensor form. Using L 1 -norm as the distance metric, the existing TPCA-L 1 with its greedy (TPCA-L 1 -G) and non-greedy (TPCA-L 1 -NG) algorithms were proposed to reduce the sensitivity to outliers. The two algorithms, however, only derived TPCA solution in a form of two-dimensional matrix without actually extending them to the tensor subspaces and without performing experimental verification for tensor data. Simultaneously, the spatial correlations between pixels of the raw tensor data cannot be effectively preserved. To solve the problems, a robust tensor principal component analysis algorithm based on F-norm distance metric is proposed in this paper, which not only preserves the spatial structure of the raw data, but also reduces the sensitivity to outliers in tensor data. Experiments on reconstruction error and classification rate show that the proposed algorithm is effective and superior to other tensor algorithms in performances.

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An Incremental Feature Extraction Method for Weld Surface Defect Recognition

An Incremental Feature Extraction Method for Weld Surface De...

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IEEE International Conference on Mechatronics and Automation

作者： Jun Liu Keguang Ren Xiaofeng Wang Weimin Ge National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Tianjin University of Technology Binshui Xidao 391 Xiqing District Tianjin China Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control Tianjin University of Technology Binshui Xidao 391 Xiqing District Tianjin China

ISBN: (数字)9781728164168

ISBN: (纸本)9781728164175

To meet the requirements of online feature extraction for weld defect recognition, an Incremental 2DPCA algorithm (I2DPCA) without estimating the covariance matrix of weld surface images is firstly proposed. A set of weld features with multiple orthogonal principal components can be obtained by a recursive estimation method, instead of the eigenvalue decomposition method or the singular value decomposition method. The computational complexity will be greatly reduced and the online feature extraction speed will be improved. To extract more structure features and reduce the dimension of weld images, an Incremental row-column Bidirectional PCA (IBDPCA) algorithm is presented based on I2DPCA, which preserves the weld features in the horizontal and vertical directions of weld images, and realizes the incremental feature extraction and data dimensionality reduction in the row and column directions. Finally, a series of comparative experiments are performed on the collected weld defect dataset. The results show that the proposed algorithm is superior to other PCA algorithms in convergence rate, classification rate, and complexity. The convergence rate is more than 99%, the classification rate can reach 96%, which can meet the online feature extraction requirements for weld defect recognition.

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Improved Simulated Annealing Genetic Algorithm based Low power mapping for 3D NoC 2

Improved Simulated Annealing Genetic Algorithm based Low pow...

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2018 2nd International Conference on Electronic Information Technology and Computer Engineering (EITCE 2018)

作者： Hanna He Fang Fang Wei Wang Hefei University of Technology School of Computer Science and Information Engineering Anhui Province Key Laboratory of Affective Computing and Advanced Intelligent Machine

Mapping of IP(Intellectual Property) cores onto NoC(Network-on-Chip) architectures is a key step in NoCbased designs. Energy is the key parameter to measure the designs. Therefore, we propose an Improved Simulated Annealing Genetic Alogrithm, abbreviated as ISAGA. The algorithm combines the parallelism of Genetic Algorithm(GA) and the local search ability of Simulated Annealing(SA). We improve the initial population selection of GA to get the lower power consumption mapping scheme. The experimental results show that compared with the GA, ISAGA has good convergence and can search the optimal solution quickly, which can effectively reduce the power consumption of the system. In the case of 124 IP cores, the average power consumption of the ISAGA is reduced by 32.0% compared with the GA.

关键词： NTD Improved Simulated Annealing Genetic Algorithm based Low power mapping for 3D NoC

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Selection of fundamental period components of vibration modeling for non-faulty planetary gearboxes

Selection of fundamental period components of vibration mode...

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Prognostics and System Health Management Conference (PHM-Qingdao)

作者： Xinguang Ma Li Zhan Jie Liu Lin Zhang Jun Liu Mian Zhang Nuclear Power Institute of China Chengdu China Tianjin Key Laboratory of the Design and Intelligent Control of the Advanced Mechanical System Tianjin University of Technology China

Planetary gearboxes are `hearts' of transmission train among heavy industrials. The health condition of planetary gearboxes is the key to maintain reliable operation of industrial and promote harmonious social development. Frequency spectrum analysis of vibration measurements is a popular way for condition assessing. As prior guidance for spectrum analyzing, phenomenological modeling emerges as a simple and effective mathematical description of the vibration measurements referring to the sensor. A reasonable model of a non-faulty planetary gearbox is the essential work, either in understanding the motion behavior, or in condition monitoring and even for fault diagnosis. In this paper, traditional models are reexamined and investigated: we found the contradicting results from two classical references on the selection of fundamental period components when constructing models. The rationality of the traditional models is mathematically and experimentally studied, the more reasonable one is indicated.

关键词： Vibrations Fault diagnosis Analytical models Vibration measurement Frequency measurement Mathematical model Spectral analysis

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Finite Element Analysis of Series Elastic Actuator for Exoskeleton Robot Joint

Finite Element Analysis of Series Elastic Actuator for Exosk...

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IEEE International Conference on Mechatronics and Automation

作者： Pengyu Xi Weimin Ge Sen Zhang Zhili Zhang Teresa Zielinska Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology Tianjin China National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Tianjin University of Technology Intelligent Manufacturing College Tianjin Sino-German University of Applied Science Tianjin China Institute of Aeronautics and Applied Mechanics Warsaw University of Technology Warsaw Poland

ISBN: (数字)9781728164168

ISBN: (纸本)9781728164175

The finite element simulation for the joints of an exoskeleton robot is conducted in this paper. Using software OpenSim to simulate the normal walking gait of the human body, the motion angle and moment of the human hip, knee and ankle joints are obtained. Using the obtained data as the input parameters in the finite element simulation of the simulation software Ls-dyna, the strain diagrams and contact force curves of the circular roller and cam disk were obtained. In this study, three commonly used materials are selected: alloy steel, ductile iron and hard aluminum alloy. Finally, the effects of different materials on the key components of the series elastic actuator are studied.

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Image Super-resolution Reconstruction Based on Deep Residual Network

Image Super-resolution Reconstruction Based on Deep Residual...

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2018 2nd International Conference on Artificial Intelligence: Technologies and Applications（ICAITA2018）

作者： Bin Sun Jian Lu Xiaopeng Wei Laboratory of Advanced Design and Intelligent Computing Dalian University

Having powerful ability to learn and represent features, deep convolutional neural networks(CNN) can get better results in image super-resolution reconstruction. However, deep networks also exist some problems. For example, the gradient will gradually vanish through the network, which makes the training difficult to converge. To address these problems, this paper presents a deep network model that is suitable for superresolution reconstruction. By applying residual network modules, the model realizes the transmission of information across one or more layers. This residual network structure can not only avoid the loss of effective information in the network, but also speed up the training convergence. Compared with the previous classical methods, the proposed model converges faster, and the subjective and objective evaluations have been improved to a certain extent.

关键词： super-resolution reconstruction deep learning residual network

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Manipulator of robust fuzzy adaptive compensation control 3

Manipulator of robust fuzzy adaptive compensation control

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3rd Asia-Pacific Conference on intelligent Robot Systems, ACIRS 2018

作者： Yangjian, Wang Xiaofei, Chen Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineeringline Binshui Xidao 391 Tianjin China

ISBN: (纸本)9781538672266

Dynamics system for reconfigurable manipulator of uncertainty, based on the fuzzy adaptive algorithm is proposed to approach the system control law from adaptation to friction and external disturbance, the compensation control of the reconfigurable robot arm. At the same time in order to improve the control law of compensation precision and anti-interference performance, reduce the approximation error of the algorithm and the robust items added in the control law. By Lyapunov stability theory proves that the proposed fuzzy adaptive robust fuzzy control law and the adaptive control law can be in reconfigurable manipulator dynamics contained in friction and the external disturbance to ensure the stability of the system. Last three do f reconfigurable robot arm as an example to design a reconfigurable robotic arm controller, the simulation results show that the algorithm has good trajectory tracking performance, and proves the feasibility and effectiveness of the algorithm. © 2018 IEEE.

关键词： Friction

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Adaptive Handover Decision Inspired By Biological Mechanism in Vehicle Ad-hoc Networks

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Computers, Materials & Continua 2019年第9期61卷 1117-1128页

作者： Xuting Duan Jingyi Wei Daxin Tian Jianshan Zhou Haiying Xia Xin Li Kunxian Zheng Beijing Advanced Innovation Center for Big Data and Brain Computing Beijing100191China Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems&SafetyControl Beijing100191China School of Transportation Science and Engineering Beihang UniversityBeijing100191China Department of Engineering and Design University of SussexBrightonBN19RHUK Research Institute of Highway Ministry Transport Beijing100088China Department of Computer Science and Technology Tsinghua UniversityHaidian DistrictBeijing100088China

In vehicle ad-hoc networks(VANETs),the proliferation of wireless communication will give rise to the heterogeneous access environment where network selection becomes *** by the self-adaptive paradigm of cellular attractors,this paper regards an individual communication as a cell,so that we can apply the revised attractor selection model to induce each connected *** at improving the Quality of Service(QoS),we presented the bio-inspired handover decision-making *** addition,we employ the Technique for Order Preference by Similarity to an Ideal Solution(TOPSIS)for any vehicle to choose an access *** paper proposes a novel framework where the bio-inspired mechanism is combined with *** a dynamic and random mobility environment,our method achieves the coordination of performance of heterogeneous networks by guaranteeing the efficient utilization and fair distribution of network resources in a global *** experimental results confirm that the proposed method performs better when compared with conventional schemes.

关键词： Revised attraction selection model TOPSIS VANETs QoS

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intelligent non-invasive elderly fall monitoring by designing software defined radio frequency sensing system

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Digital Communications and Networks 2024年

作者： Adeel Akram Muhammad Bilal Khan Najah Abed Abu Ali Qixing Zhang Awais Ahmad Muhammad Shahid Iqbal Syed Atif Moqurrab Laboratory for Intelligent Sensing and Computing Institute of Advanced Technology University of Science and Technology of China Hefei 230031 Anhui China State Key Laboratory of Fire Science University of Science and Technology of China Hefei 230026 Anhui China College of IT United Arab Emirates University Al-Ain 15551 United Arab Emirates Department of Electrical and Computer Engineering COMSATS University Islamabad Attock 43600 Pakistan College of Computer and Information Sciences Imam Muhammad Ibn Saud Islamic University (IMSIU) Riyadh 11432 Kingdom of Saudi Arabia Department of Computer Science and Information Technology Women University of AJ&K Bagh Pakistan School of Computing Gachon University 1342 Seongnam-daero Sujeong-gu Seongnam-si 13120 Korea

The global increase in life expectancy poses challenges related to the safety and well-being of the elderly population, especially in relation to falls. While falls can lead to significant cognitive impairments, timely intervention can mitigate their adverse effects. In this context, the need for non-invasive, efficient monitoring systems becomes paramount. Although wearable sensors have gained traction for monitoring health activities, they may cause discomfort during prolonged use, especially for the elderly. To address this issue, we present an intelligent, non-invasive Software-Defined Radio Frequency (SDRF) sensing system, tailored red for monitoring elderly people's falls during routine activities. Harnessing the power of deep learning and machine learning, our system processes the Wireless Channel State Information (WCSI) generated during regular and fall activities. By employing sophisticated signal processing techniques, the system captures unique patterns that distinguish falls from normal activities. In addition, we use statistical features to streamline data processing, thereby optimizing the computational efficiency of the system. Our experiments, conducted for a typical home environment while using treadmill, demonstrate the robustness of the system. The results show high classification accuracies of 92.5%, 95.1%, and 99.8% for three Artificial Intelligence (AI) algorithms. Notably, the SDRF-based approach offers flexibility, cost-effectiveness, and adaptability through software modifications, circumventing the need for hardware overhaul. This research attempts to bridge the gap in RF-based sensing for elderly fall monitoring, providing a solution that combines the benefits of non-invasiveness with the precision of deep learning and machine learning.

关键词： AI Elderly falls intelligent learning SDRF WCSI

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