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arXiv 2021年

作者： Wu, Dongrui Xu, Jiaxin Fang, Weili Zhang, Yi Yang, Liuqing Xu, Xiaodong Luo, Hanbin Yu, Xiang The Ministry of Education Key Laboratory of Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China Zhejiang Lab Hangzhou311121 China The School of Civil and Hydraulic Engineering Huazhong University of Science and Technology Wuhan430074 China The College of Public Administration Huazhong University of Science and Technology Wuhan430074 China The University of Michigan Ann ArborMI48109 United States The School of Management and Sino European Institute for Intellectual Property Huazhong University of Science and Technology Wuhan430074 China

Physiological computing uses human physiological data as system inputs in real time. It includes, or significantly overlaps with, brain-computer interfaces, affective computing, adaptive automation, health informatics, and physiological signal based biometrics. Physiological computing increases the communication bandwidth from the user to the computer, but is also subject to various types of adversarial attacks, in which the attacker deliberately manipulates the training and/or test examples to hijack the machine learning algorithm output, leading to possible user confusion, frustration, injury, or even death. However, the vulnerability of physiological computing systems has not been paid enough attention to, and there does not exist a comprehensive review on adversarial attacks to them. This paper fills this gap, by providing a systematic review on the main research areas of physiological computing, different types of adversarial attacks and their applications to physiological computing, and the corresponding defense strategies. We hope this review will attract more research interests on the vulnerability of physiological computing systems, and more importantly, defense strategies to make them more secure. Copyright © 2021, The Authors. All rights reserved.

关键词： Machine learning

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Modeling and simulation of temperature distribution for planar cross-flow solid oxide fuel cell

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Energy Procedia 2019年 158卷 1585-1590页

作者： Yuan-wu Xu Xiao-long Wu Hang You Tao Xue Dong-qi Zhao Jian-hua Jiang Zhong-hua Deng Xiao-wei Fu Li Xi School of Automation Key Laboratory of Education Ministry for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan 430074 China Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan University of Science and Technology Wuhan 430065 China Research Institute of Huazhong University of Science & Technology in Shenzhen Shenzhen 518057 China

Solid oxide fuel cell is a device that can convert chemical energy directly into electricity. Its advantages, such as high efficiency, low emission, quiet operation, fuel flexibility, bring about the broad application prospect. However, it is difficult to obtain the temperature distribution in the existing planar cross flow solid oxide fuel cell through the experiment. In this paper, a control orient two-dimensional differential equation model is established for a planar cross flow solid oxide fuel cell based on the finite node method, and an iterative algorithm for calculating the real time voltage of the fuel cell is proposed for the model. Based on the model, the temperature distribution of the fuel cell in the test and system configuration is simulated. The simulation results show that the model can reflect the thermoelectric characteristics of the planar cross flow solid oxide fuel cell, especially the temperature distribution of the fuel cell. The SOFC temperature distribution modeling in this paper is helpful for the development of temperature distribution observers and design related control methods in later studies.

关键词： modeling simulation temperature distribution planar cross flow solid oxide fuel cell

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Standby and Shutdown Cycles Modeling of SOFC Lifetime Prediction

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Energy Procedia 2019年 158卷 1573-1578页

作者： Wu Xiao-long Xu Yuanwu Xue Tao Zhao Dongqi Jiang Jianhua Deng Zhonghua Fu Xiaowei Li Xi School of Automation Key Laboratory of Education Ministry for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan 430074 China Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan University of Science and Technology Wuhan 430065 China Shenzhen Huazhong University of Science and Technology Research Institute Shenzhen 518057 China

In order to more accurately predict the impact of solid oxide fuel cells to stack life on standby and shutdown, this paper proposes a modeling method based on experimental data. Which is based on Elman neural network(NN). At the same time, a main factor is considered in the modeling process which is the effect of cooling rate on the stack. In the process of modeling, the most obvious cooling rate is used to modeling. There are two different influencing factors on classify, the training set and the verification set respectively. After the reliability of the model, the Solid Oxide Fuel cell (SOFC) stack life prediction is carried out. From the predict results and the experimental results, it is found that the prediction results are good and the high precision.

关键词： Solid Oxide Fuel Cell(SOFC) Stack useful lifetime predict Cooling speed Gas composition Cycle standby shutdown

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Reaching Non-Negative Edge Consensus of Networked Dynamical Systems

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IEEE TRANSACTIONS ON CYBERNETICS 2018年第9期48卷 2712-2722页

作者： Wang, Xiao Ling Su, Housheng Chen, Michael Z. Q. Wang, Xiao Fan Chen, Guanrong College of Automation Nanjing University of Posts and Telecommunications Nanjing China School of Automation Image Processing and Intelligent Control Key Laboratory of Education Ministry of China Huazhong University of Science and Technology Wuhan China School of Automation Nanjing University of Science and Technology Nanjing China Department of Automation Shanghai Jiao Tong University and Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai China Department of Electronic Engineering City University of Hong Kong Hong Kong

In this paper, the problem of non-negative edge consensus of undirected networked linear time-invariant systems is addressed by associating each edge of the network with a state variable, for which a distributed algorithm is constructed. Sufficient conditions referring only to the number of edges are derived for non-negative edge consensus of the networked systems. Subsequently, the linear programming method and a low-gain feedback technique are introduced to simplify the design of the feedback gain matrix for achieving the non-negative edge consensus. It is found that the low-gain feedback technique has a good effect on the non-negative edge consensus of the networked systems subject to input saturation. Numerical simulations are presented to verify the effectiveness of the theoretical results.

关键词： Distributed algorithm line graph low-gain feedback networked system non-negative edge consensus

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Development of an MEMS based biomimetic whisker sensor for tactile sensing

Development of an MEMS based biomimetic whisker sensor for t...

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IEEE International Conference on Cyborg and Bionic Systems (CBS)

作者： Zihou Wei Qing Shi Chang Li Shurui Yan Guanglu Jia Zhigang Zeng Qiang Huang Toshio Fukuda Key Laboratory of Biomimetic Robots and Systems Key Laboratory of Biomimetic Robots and Systems (Beijing Institute of Technology) Ministry of Education Beijing China Key Laboratory of Ministry of Education for Image Processing and Intelligent Control the School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China

ISBN: (数字)9781728150734

ISBN: (纸本)9781728150741

It has been demonstrated that biological whisker sensing system has excellent capacity to achieve the pattern recognition, and whisker sensor based robot tactile perception has caused widespread concern. However, most of current existed whisker sensors are too large in size, and are difficult to be integrated into a small robot. In this paper, we proposed a MEMS based biomimetic whisker sensor inspired by rats, which integrates four sensing units on a square silicon wafer with a side length of 6.8mm and makes it possible to be installed on a small robot with similar size to a real rat. Our sensor measure the bending moment at the root of the whisker based on the piezoresistive effect. We have explored the range of functions that whisker arrays can serve on and it is shown that our whisker sensor can determine obstacle distance, and is also capable of gathering surface information including shape and texture.

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Re-ID driven localization refinement for person search

arXiv

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arXiv 2019年

作者： Han, Chuchu Ye, Jiacheng Zhong, Yunshan Tan, Xin Zhang, Chi Gao, Changxin Sang, Nong Key Laboratory of Ministry of Education for Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Peking University Shanghai Jiao Tong University Megvii Technology

Person search aims at localizing and identifying a query person from a gallery of uncropped scene images. Different from person re-identification (re-ID), its performance also depends on the localization accuracy of a pedestrian detector. The state-of-the-art methods train the detector individually, and the detected bounding boxes may be suboptimal for the following re-ID task. To alleviate this issue, we propose a re-ID driven localization refinement framework for providing the refined detection boxes for person search. Specifically, we develop a differentiable ROI transform layer to effectively transform the bounding boxes from the original images. Thus, the box coordinates can be supervised by the re-ID training other than the original detection task. With this supervision, the detector can generate more reliable bounding boxes, and the downstream re-ID model can produce more discriminative embeddings based on the refined person localizations. Extensive experimental results on the widely used benchmarks demonstrate that our proposed method performs favorably against the state-of-the-art person search methods. Copyright © 2019, The Authors. All rights reserved.

关键词： Machine learning

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Fast and accurate single-image depth estimation on mobile devices, mobile AI 2021 challenge: Report

arXiv

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arXiv 2021年

作者： Ignatov, Andrey Malivenko, Grigory Plowman, David Shukla, Samarth Timofte, Radu Zhang, Ziyu Wang, Yicheng Huang, Zilong Luo, Guozhong Yu, Gang Fu, Bin Wang, Yiran Li, Xingyi Shi, Min Xian, Ke Cao, Zhiguo Du, Jin-Hua Wu, Pei-Lin Ge, Chao Yao, Jiaoyang Tu, Fangwen Li, Bo Yoo, Jung Eun Seo, Kwanggyoon Xu, Jialei Li, Zhenyu Liu, Xianming Jiang, Junjun Chen, Wei-Chi Joya, Shayan Fan, Huanhuan Kang, Zhaobing Li, Ang Feng, Tianpeng Liu, Yang Sheng, Chuannan Yin, Jian Benavides, Fausto T. Computer Vision Lab ETH Zurich Switzerland Ltd AI Witchlabs Switzerland Tencent GY-Lab China Key Laboratory of Image Processing and Intelligent Control Ministry of Education School of Artificial Intelligence and Automation Huazhong University of Science and Technology China Nanjing Artificial Intelligence Chip Research Institute of Automation Chinese Academy of Sciences China Black Sesame Technologies Inc. Singapore Singapore Visual Media Lab KAIST Korea Republic of Harbin Institute of Technology China Peng Cheng Laboratory China Multimedia and Computer Vision Laboratory National Cheng Kung University Taiwan Samsung Research UK United Kingdom OPPO Research Institute China ETH Zurich Switzerland

Depth estimation is an important computer vision problem with many practical applications to mobile devices. While many solutions have been proposed for this task, they are usually very computationally expensive and thus are not applicable for on-device inference. To address this problem, we introduce the first Mobile AI challenge, where the target is to develop an end-to-end deep learning-based depth estimation solutions that can demonstrate a nearly real-time performance on smartphones and IoT platforms. For this, the participants were provided with a new large-scale dataset containing RGB-depth image pairs obtained with a dedicated stereo ZED camera producing high-resolution depth maps for objects located at up to 50 meters. The runtime of all models was evaluated on the popular Raspberry Pi 4 platform with a mobile ARM-based Broadcom chipset. The proposed solutions can generate VGA resolution depth maps at up to 10 FPS on the Raspberry Pi 4 while achieving high fidelity results, and are compatible with any Android or Linux-based mobile devices. A detailed description of all models developed in the challenge is provided in this paper. Copyright © 2021, The Authors. All rights reserved.

关键词： Computer operating systems

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Predefined-time terminal sliding mode control of robot manipulators

arXiv

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arXiv 2020年

作者： Liang, Chang-Duo Ge, Ming-Feng Liu, Zhi-Wei Wang, Yan-Wu Karimi, Hamid Reza School of Mechanical Engineering and Electronic Information China University of Geosciences Wuhan430074 China School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China Key Laboratory of Image Processing and Intelligent Control Ministry of Education Huazhong University of Science and Technology Wuhan430074 China Department of Mechanical Engineering Politecnico di Milano Milan20156 Italy

In this paper, we present a new terminal sliding mode control to achieve predefined-time stability of robot manipulators. The proposed control is developed based on a novel predefined-time terminal sliding mode (PTSM) surface, on which the states are forced to reach the origin in a predefined time, i.e., the settling time is independent to the initial condition and can be explicitly user-defined via adjusting some specific parameters called the predefined-time parameters. It is also demonstrated that the proposed control can provide satisfactory steady-state performance in the case of both external disturbances and parametric uncertainties. Besides, we present a formal systemic analysis method to derive the sufficient conditions for guaranteeing the predefined-time convergence of the closed-loop system. Finally, the effectiveness and performance of the presented control scheme are illustrated through both theoretical comparisons and numerical simulations. Copyright © 2020, The Authors. All rights reserved.

关键词： Sliding mode control

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Finite-size scaling of geometric renormalization flows in complex networks

arXiv

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arXiv 2020年

作者： Chen, Dan Su, Housheng Wang, Xiaofan Pan, Gui-Jun Chen, Guanrong School of Artificial Intelligence and Automation Image Processing and Intelligent Control Key Laboratory of Education Ministry of China Huazhong University of Science and Technology Wuhan430074 China Department of Automation Shanghai University Shanghai200072 China Faculty of Physics and Electronic Science Hubei University Wuhan430062 China Department of Electrical Engineering City University of Hong Kong Hong Kong Hong Kong

Recently, the concept of geometric renormalization group provides a good approach for studying the structural symmetry and functional invariance of complex networks. Along this line, we systematically investigate the finite-size scaling of structural and dynamical observables in geometric renormalization flows of synthetic and real evolutionary networks. Our results show that these observables can be well characterized by a certain scaling function. Specifically, we show that the critical exponent implied by the scaling function is independent of these observables but only depends on the small-world properties of the network, namely, all networks located in the small-world phase have a uniform scaling exponent, while those located in the non-small-world phase and in their critical regions have another uniform scaling. More importantly, we perform extensive experiments on real evolutionary networks with small-world characteristics, and our results show that these observables also have uniform scaling in their geometric renormalization flows. Therefore, in a sense this exponent can be used as an effective measure for classifying universal small-world and non-small-world network models. © 2020, CC BY-SA.

关键词： Geometry

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Multi-task deep learning with dynamic programming for embryo early development stage classification from time-lapse videos

arXiv

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arXiv 2019年

作者： Liu, Zihan Huang, Bo Cui, Yuqi Xu, Yifan Zhang, Bo Zhu, Lixia Wang, Yang Jin, Lei Wu, Dongrui Key Laboratory of Ministry of Education for Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China Reproductive Medicine Center Huazhong University of Science and Technology Tongji Hospital Wuhan430074 China

Time-lapse is a technology used to record the development of embryos during in-vitro fertilization (IVF). Accurate classification of embryo early development stages can provide embryologists valuable information for assessing the embryo quality, and hence is critical to the success of IVF. This paper proposes a multi-task deep learning with dynamic programming (MTDL-DP) approach for this purpose. It first uses MTDL to pre-classify each frame in the time-lapse video to an embryo development stage, and then DP to optimize the stage sequence so that the stage number is monotonically non-decreasing, which usually holds in practice. Different MTDL frameworks, e.g., oneto-many, many-to-one, and many-to-many, are investigated. It is shown that the one-to-many MTDL framework achieved the best compromise between performance and computational cost. To our knowledge, this is the first study that applies MTDL to embryo early development stage classification from time-lapse videos. Copyright © 2019, The Authors. All rights reserved.

关键词： Deep learning

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