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2020 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2020

作者： Hu, Rui Cai, Jiaming Zheng, Wangjie Yang, Yang Shen, Hong-Bin Shanghai Jiao Tong University Key Lab. of Shanghai Education Commission for Intelligent Interaction and Cognitive Engineering Department of Computer Science and Engineering Shanghai200240 China Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China Shanghai Jiao Tong University Department of Bioinformatics and Biostatistics Shanghai200240 China

ISBN: (纸本)9781728162157

Cryo-electron microscopy (cryo-EM) has become a mainstream technology for solving spatial structures of biomacromolecules, while the processing of cryo-EM images is a very challenging task. One of the great challenges is the high noise in the images. A common method is to cluster the images with close projecting angles to get mean images, which are used for 3D reconstruction. However, due to the extremely low signal-to-noise-ratio, common clustering methods often fail to obtain high-quality mean images, leading to poorly reconstructed structures. In this study, we present a new unsupervised learning framework, called NiuEM, to discriminate images captured from different angles and yield cluster-mean images. NiuEM first generates pseudo-lab.ls and then exploits both contrastive loss and cross-entropy loss for training convolutional layers to learn feature representations. Moreover, the pseudo-lab.ls are updated iteratively to enhance the reliability of lab.ls. We assess the performance of NiuEM on four data sets via both visualized and quantitative experiments. Especially, two kinds of metrics are adopted to measure the performance, regarding the clustering quality and the resolution of reconstructed 3D models, respectively. The experimental results show that NiuEM achieves very competitive clustering accuracy in the comparison with the state-of-the-art image clustering methods. Moreover, the cluster mean images yielded by NiuEM lead to better initial 3D models compared with the mainstream reconstruction tools. © 2020 IEEE.

关键词： Image reconstruction

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Orthogonal Waveform Design of MIMO Radar Based on Niche Genetic Algorithm

Orthogonal Waveform Design of MIMO Radar Based on Niche Gene...

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IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC)

作者： Bingnan PEI Tengda Pei Haosheng ZHANG Fujian Key Lab. Of Modern Communication and BeiDou Positioning Technology Quanzhou University of Information Engineering Quanzhou China Dalian Key Laboratory of Environmental Perception and Intelligent Control Dalian University Dalian China

ISBN: (数字)9781728172026

ISBN: (纸本)9781728172033

In order to optimize the orthogonal design of MIMO radar waveform, an improved algorithm based on niche genetic algorithm is proposed. The algorithm is able to eliminate individuals with similar structures in the population or data, maintain a certain distance between individuals, and effectively hold the diversity of them It thus eliminates the phenomenon of premature convergence, strengthens the global search ability of the algorithm, and improves its convergence speed. It is shown that the algorithm has both the advantages of overall search ability of genetic algorithm and the ability of the niche genetic algorithm to discover multiple optimal solutions. Simulation was given to show that the algorithm was cable to reduce the side-lobe of the auto-correlation function of the orthogonal polyphase code and the peak value of the cross-correlation function of the code with good performance of autocorrelation and cross-correlation obtained

关键词： Correlation Optimization MIMO radar Genetic algorithms Encoding Simulation Interference

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Research on Fast Error Calibration Methods for Flexible Measuring Arm

Research on Fast Error Calibration Methods for Flexible Meas...

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2019 International Conference on Artificial Intelligence and Advanced Manufacturing, AIAM 2019

作者： Zhao, Xinhua Zhao, Lei Ji, Liangping Zhang, Jiaxing School of Mechanical Engineering Tianjin University of Technology Tianjin Key Lab. for Adv. Mechatronic Syst. Des. and Intelligent Control Sch. of Mech. Engineering Tianjin Univ. of Technol. Tianjin China National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Tianjin University of Technology Tianjin China

ISBN: (纸本)9781728146911

Based on the structure of the joint coordinate measuring machine, the error calibration of the flexible measuring arm is systematically and deeply researched. The straightness error data of the two linear guide rails are obtained by measuring the high-precision square box. Then, the slope of the straightness error curve is obtained by least squares method, and the verticality error can be also calculated. The parallelism error for two rotation axes can be calibrated by test a precision flat. Its result can be quickly compute based on the sampling data. The proposing calibration methods have low cost, easy operation, high efficiency and small environmental restrictions than external calibration by expensive instruments. The experiment has proved the validity and feasibility of the above method. © 2019 IEEE.

关键词： Errors

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Biological and physical properties of a modification silicone liner 4

Biological and physical properties of a modification silicon...

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2020 4th International Conference on Material Science and Technology, ICMST 2020

作者： Gu, Huiru Luan, Huiqin Mo, Zhongjun Song, Iang Fan, Yubo Key Laboratory for Biomechanics and Mechanobiology of Ministry of Education School of Biological Science and Medical Engineering Beihang University Beijing100191 China Key Laboratory of Intelligent Control and Rehabilitation Technology of the Ministry of Civil Affairs National Research Center for Rehabilitation Technical Aids Beijing100176 China Beijing Key Laboratory of Rehabilitation Technical Aids for Old-Age Disability Beijing100176 China Key Lab. of Rehab. Tech. Aids Anal. and Identification of the Min. of Civ. Aff. Beijing100176 China

Silicone liners provide comfortability for amputees, meanwhile effectively protecting their skin surface and subcutaneous tissue. Silicone liners used in prosthetics are mainly used for filling, cushioning, and suspending a receiving cavity. At present, biological and mechanical properties of silicone liners in prosthetic cavity remain unclear, and the price is expensive for amputees. We improve the silicone material preparation process to reduce the price as well as to ensure the mechanics and biosafety of the material. Characterization of silicone liner surface, cellular toxicity of silicone liner, bacterial adhesion on the surface of silicone liner, and mechanical properties were evaluated and compared among commercial materials (sample A and B) and our improved silicone liner material (sample C). The water contact, the macroscopic surface and the calculated mechanical parameters have no significant differences among the three types samples. The extract of three types silicone liner have no cytotoxicity reactivity. Samples C markedly reduced the adhesion of E. coli compared with sample A. The improved silicone material preparation process ensured the biological and mechanical properties and reduced the price of these silicone liners, thereby increasing their potential as silicone liners of prosthetics cavity. © 2020 Institute of Physics Publishing. All rights reserved.

关键词： Silicones

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Incorporating Hidden Layer representation into Adversarial Attacks and Defences

arXiv

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arXiv 2020年

作者： Shen, Haojing Chen, Sihong Wang, Ran Wang, Xizhao Big Data Institute College of Computer Science and Software Engineering Guangdong Key Lab. of Intelligent Information Processing Shenzhen University Guangdong Shenzhen518060 China The College of Mathematics and Statistics Shenzhen University Shenzhen518060 China The Shenzhen Key Laboratory of Advanced Machine Learning and Applications Shenzhen University Shenzhen518060 China

In this paper, we propose a defence strategy to improves adversarial robustness incorporating hidden layer representation. The key of this defence strategy aims to compress or filter input’s information including adversarial perturbation. And this defence strategy can be regarded as an activation function which can be applied any kind of neural networks. We also prove theoretically the effectiveness of this defense strategy under certain conditions. Besides, incorporating hidden layer representation we propose three types of adversarial attacks to generate three types of adversarial examples, respectively. The experiments show that our defence method can significantly improve the adversarial robustness of deep neural networks which achieves the state-of-the-art performance even though we do not adopt adversarial training. © 2020, CC BY.

关键词： Deep neural networks

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A study on the uncertainty of convolutional layers in deep neural networks

arXiv

引用

arXiv 2020年

作者： Shen, Haojing Chen, Sihong Wang, Ran Big Data Institute College of Computer Science and Software Engineering Guangdong Key Lab. of Intelligent Information Processing Shenzhen University ShenzhenGuangdong518060 China College of Mathematics and Statistics Shenzhen University Shenzhen518060 China Shenzhen Key Laboratory of Advanced Machine Learning and Applications Shenzhen University Shenzhen518060 China

This paper shows a Min-Max property existing in the connection weights of the convolutional layers in a neural network structure, i.e., the LeNet. Specifically, the Min-Max property means that, during the back propagation-based training for LeNet, the weights of the convolutional layers will become far away from their centers of intervals, i.e., decreasing to their minimum or increasing to their maximum. From the perspective of uncertainty, we demonstrate that the Min-Max property corresponds to minimizing the fuzziness of the model parameters through a simplified formulation of convolution. It is experimentally confirmed that the model with the Min-Max property has a stronger adversarial robustness, thus this property can be incorporated into the design of loss function. This paper points out a changing tendency of uncertainty in the convolutional layers of LeNet structure, and gives some insights to the interpretability of convolution. © 2020, CC-BY.

关键词： Convolution

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A Review of Generalized Zero-Shot Learning Methods

arXiv

引用

arXiv 2020年

作者： Pourpanah, Farhad Abdar, Moloud Luo, Yuxuan Zhou, Xinlei Wang, Ran Lim, Chee Peng Wang, Xi-Zhao Jonathan Wu, Q.M. The Centre for Computer Vision and Deep Learning Department of Electrical and Computer Engineering University of Windsor WindsorONN9B 3P4 Canada Deakin University Australia The Department of Computer Science City University of Hong Kong Hong Kong The College of Mathematics and Statistics Shenzhen Key Lab. of Advanced Machine Learning and Applications Shenzhen University Shenzhen518060 China The College of Computer Science and Software Engineering Guangdong Key Lab. of Intelligent Information Processing Shenzhen University Shenzhen518060 China

Generalized zero-shot learning (GZSL) aims to train a model for classifying data samples under the condition that some output classes are unknown during supervised learning. To address this challenging task, GZSL leverages semantic information of the seen (source) and unseen (target) classes to bridge the gap between both seen and unseen classes. Since its introduction, many GZSL models have been formulated. In this review paper, we present a comprehensive review on GZSL. Firstly, we provide an overview of GZSL including the problems and challenges. Then, we introduce a hierarchical categorization for the GZSL methods and discuss the representative methods in each category. In addition, we discuss the availab.e benchmark data sets and applications of GZSL, along with a discussion on the research gaps and directions for future investigations. Copyright © 2020, The Authors. All rights reserved.

关键词： Zero-shot learning

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Formation control for multiple agents with local measurements: Continuous-time and sampled-data-based cases

arXiv

引用

arXiv 2019年

作者： Wang, Chen Li, Shuai Xia, Weiguo Sun, Jinan Xie, Guangming National Engineering Research Center for Software Engineering Peking University Beijing100871 China Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education School of Control Science and Engineering Dalian University of Technology Dalian116024 China State Key Laboratory of Turbulence and Complex Systems Intelligent Biomimetic Design Lab College of Engineering Peking University Beijing100871 China

We study the formation control problem for a group of mobile agents in a plane, in which each agent is modeled as a kinematic point and can only use the local measurements in its local frame. The agents are required to maintain a geometric pattern while keeping a desired distance to a static/moving target. The prescribed formation is a general one which can be any geometric pattern, and the neighboring relationship of the N-agent system only has the requirement of containing a directed spanning tree. To solve the formation control problem, a distributed controller is proposed based on the idea of decoupled design. One merit of the controller is that it only uses each agent's local measurements in its local frame, so that a practical issue that the lack of a global coordinate frame or a common reference direction for real multi-robot systems is successfully solved. Considering another practical issue of real robotic applications that sampled data is desirable instead of continuous-time signals, the sampled-data based controller is developed. Theoretical analysis of the convergence to the desired formation is provided for the multiagent system under both the continuous-time controller with a static/moving target and the sampled-data based one with a static target. Numerical simulations are given to show the effectiveness and performance of the controllers. Copyright © 2019, The Authors. All rights reserved.

关键词： Multi agent systems

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Erratum to “Entropy-based fuzzy support vector machine for imbalanced datasets” [Knowl.-Based Syst. 115 (2017) 87–99]

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Knowledge-Based Systems 2020年 192卷

作者： Salim Rezvani Xizhao Wang Big Data Institute College of Computer Science and Software Engineering Guangdong Key Lab. of Intelligent Information Processing Shenzhen University Shenzhen 518060 Guangdong China

In this note, we show that the calculation of statistics X F 2 and F F in sections 4.5 and 4.6 of the paper (Fan et al., 2017) is not correct. Also, based on the calculation of Critical Difference (CD) of Bonferroni–Dunn test, we show that the conclusion on ”significantly outperforming the compared algorithms”, drawn by the authors using the P -value test, is not convincing.

关键词： Information entropy fuzzy support vector machine Bonferroni–Dunn test Friedman test

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Strip wrinkling detection based on feature extraction and sparse representation

引用

International Journal of Wireless and Mobile Computing 2017年第1期12卷 36-40页

作者： Wang, Wenhao Chen, Xiong Pan, Yuqi Intelligent Control Research Lab. Department of Electronic Engineering Fudan University Shanghai200433 China

Strip wrinkling is a kind of adverse phenomenon occurring during strip steel production. It is necessary to detect strip wrinkling promptly for production lines, most of which rely on manual survey for detection until now. To provide a better condition for wrinkling detection, this paper introduces a feature-based image processing method. Feature extraction, dictionary learning and sparse representation are included in this method. Draped surface of wrinkling strip is suitable for SIFT technique extracting features of wrinkles. The extracted features will be collected by dictionary learning. For every original strip image, detecting wrinkles may be realised by assessing which dictionary its features incline to. At this stage, the assessment is implemented by sparse representation. The proposed method has been tested in a strip steel production line and the performance showed its applicability. Copyright © 2017 Inderscience Enterprises Ltd.

关键词： Feature extraction

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