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Array P systems with parallel rewriting and tables of context-free rules

Journal of Computational and Theoretical Nanoscience 2016年第6期13卷 3636-3642页

作者： Pan, Linqiang Song, Bosheng Isawasan, Pradeep Subramanian, K.G. School of Electric and Information Engineering Zhengzhou University of Light Industry Zhengzhou Henan450002 China Key Laboratory of Image Information Processing and Intelligent Control School of Automation Huazhong University of Science and Technology Wuhan Hubei430074 China 32 Jalan Anson Penang10400 Malaysia Department of Mathematics and Computer Science Faculty of Science Liverpool Hope University LiverpoolL16 9JD United Kingdom

The two areas of picture languages and membrane computing were linked by array-rewriting P system in which array objects and context-free array-rewriting rules are used in order to generate picture languages. While rewriting arrays in the array-rewriting P system is in a sequential manner, parallel array P system (PAP) involves rewriting of arrays in the regions in parallel in order to generate picture languages. A variant of PAP, known as tabled array P system (TPAP), uses sets of context-free array-rewriting rules, called tables of rules. Generative power of TPAP in comparison with PAP and certain other kinds of picture array generating mechanisms are investigated. Copyright © 2016 American Scientific Publishers. All rights reserved.

关键词： Context free languages

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Asymmetry in cross-hippocampal connectivity in unilateral mesial temporal lobe epilepsy

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EPILEPSY RESEARCH 2015年 118卷 14-21页

作者： Li, Hong Fan, Wenliang Yang, Jie Song, Shuyan Liu, Yuan Lei, Ping Shrestha, Lochan Mella, Grace Chen, Wei Xu, Haibo Huazhong Univ Sci & Technol Tongji Med Coll Union Hosp Dept Radiol Wuhan 430022 Peoples R China Massachusetts Gen Hosp Dept Commun Sci & Disorders Inst Hlth Profess Boston MA 02114 USA Huazhong Univ Sci & Technol Educ Minist China Key Lab Image Proc & Intelligent Control Sch Life Sci & Technol Wuhan 430074 Peoples R China Tongji Univ Tonsil Hosp Dept Radiol Sch Med Shanghai Peoples R China First Peoples Hosp Yibin Radiol & Med Imaging Ctr Sichuan 644000 Peoples R China Wuhan Univ Zhongnan Hosp Dept Radiol Wuhan 430071 Peoples R China

Mesial temporal lobe epilepsy (mTLE) is mostly characterized by hippocampal sclerosis (HS) changes. Although considerable progress has been made in understanding the altered functional network of mTLE patients, whether one side of the abnormal hippocampal (HP) structure will affect the other healthy side of the hippocampal network is still unclear. Here, we used a seed-based method to explore the commonly alterative hippocampal network in mTLE patients by comparing the bilateral hippocampal network of unilateral mTLE patients with healthy control participants. We observed that both sides of the hippocampal network in unilateral mTLE patients were changed independent of the affected or "healthy" side, which may suggest a common plasticity network for both sides of hippocampal sclerosis mesial temporal lobe epilepsy patients. Furthermore, using the HP as the ROT, we found that the functional connectivity of the intra-HP in the left mTLE-HS group was moderately positively correlated with the duration of the disease, while a strong negative correlation between functional connectivity of the intra-HP and duration were detected in the right mTLE-HS group, which suggested that it was easier for the right HP than the left HP to communicate with the contralateral HP according to the progression of mTLE disease because the hippocampus plays different roles in the communication and compensatory mechanism associated with the contralateral side of the hemisphere. We hope that this potential relevance may help us to better characterize mTLE with hippocampal sclerosis and ultimately assist in providing a better diagnosis and more accurate invasive treatments of mTLE. (C) 2015 Elsevier B.V. All rights reserved.

关键词： Mesial temporal lobe epilepsy Hippocampal network Resting state functional connectivity Brain plasticity

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Understanding the Robustness of 3D Object Detection with Bird’s-Eye-View Representations in Autonomous Driving

arXiv

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arXiv 2023年

作者： Zhu, Zijian Zhang, Yichi Chen, Hai Dong, Yinpeng Zhao, Shu Ding, Wenbo Zhong, Jiachen Zheng, Shibao Institute of Image Communication and Network Engineering Shanghai Jiao Tong University China Dept. of Comp. Sci. and Tech. Institute for AI THBI Lab BNRist Center Tsinghua University China Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education School of Computer Science and Technology Anhui University Information Materials and Intelligent Sensing Laboratory of Anhui Province China SAIC Motor AI Lab China Zhongguancun Laboratory China

3D object detection is an essential perception task in autonomous driving to understand the environments. The Bird’s-Eye-View (BEV) representations have significantly improved the performance of 3D detectors with camera inputs on popular benchmarks. However, there still lacks a systematic understanding of the robustness of these vision-dependent BEV models, which is closely related to the safety of autonomous driving systems. In this paper, we evaluate the natural and adversarial robustness of various representative models under extensive settings, to fully understand their behaviors influenced by explicit BEV features compared with those without BEV. In addition to the classic settings, we propose a 3D consistent patch attack by applying adversarial patches in the 3D space to guarantee the spatiotemporal consistency, which is more realistic for the scenario of autonomous driving. With substantial experiments, we draw several findings: 1) BEV models tend to be more stable than previous methods under different natural conditions and common corruptions due to the expressive spatial representations;2) BEV models are more vulnerable to adversarial noises, mainly caused by the redundant BEV features;3) Camera-LiDAR fusion models have superior performance under different settings with multi-modal inputs, but BEV fusion model is still vulnerable to adversarial noises of both point cloud and image. These findings alert the safety issue in the applications of BEV detectors and could facilitate the development of more robust models. Code available at https: //***/zzj403/BEV_Robust. Copyright © 2023, The Authors. All rights reserved.

关键词： Birds

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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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Stability of homogeneous positive systems with time-varying delays

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AUTOMATICA 2023年第1期152卷

作者： Xiao, Qiang Huang, Zhenkun Zeng, Zhigang Huang, Tingwen Lewis, Frank L. Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Wuhan Peoples R China Huazhong Univ Sci & Technol Key Lab Image Proc & Intelligent Control Wuhan Peoples R China Jimei Univ Sch Sci Xiamen Peoples R China Texas A&M Univ Qatar Doha Qatar Univ Texas Arlington UTA Res Inst Ft Worth TX USA

Stability analysis of positive linear systems has been well-developed, while attention to positive homogeneous nonlinear systems is notably less paid. This note deepens and extends some previous results on stability of homogeneous systems with bounded time-varying delays. Based on positivity property, exponential stability of a class of delayed homogeneous system with degree confined to an interval is studied, and its state boundary is further investigated in any fixed time, which is more precise than the former result in some cases. Additionally, finite-time stability is obtained for a delay-free homogeneous system and an explicit boundary is presented. (c) 2023 Published by Elsevier Ltd.

关键词： Positive system Homogeneous system Exponential stability Boundedness Time delay

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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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A Novel Nonconvex Low-Rank Tensor Completion Approach for Traffic Sensor Data Recovery From Incomplete Measurements

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IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT 2023年 72卷 1页

作者： Chen, Xiaobo Wang, Kaiyuan Li, Zuoyong Zhang, Yu Ye, Qiaolin Shandong Technol & Business Univ Sch Comp Sci & Technol Yantai 264005 Shandong Peoples R China Jiangsu Key Lab Image & Video Understanding Social Nanjing 210094 Peoples R China Minjiang Univ Coll Comp & Control Engn Fujian Prov Key Lab Informat Proc & Intelligent Co Fuzhou 350121 Peoples R China Lehigh Univ Dept Bioengn Bethlehem PA 18015 USA Nanjing Forestry Univ Coll Informat Sci & Technol Nanjing 210037 Peoples R China

Complete traffic sensor data are considered to be one of the critical ingredients for intelligent transportation systems (ITSs). However, traffic measurements prevalently suffer from inevitable and ubiquitous missing values (MVs). Current missing data completion algorithms are difficult to leverage the global low-rank property and the fine-grained spatial-temporal structure simultaneously. To circumvent this problem, this work presents a novel collaborative nonconvex low-rank spatial-temporal data tensor completion model that can take full advantage of the inherent spatial-temporal characteristics of traffic measurement data. First, the tensor Schatten p-norm, as an effective nonconvex surrogate of rank function, is used to exploit the global multidimensional correlation of traffic data. Then, we present an elastic net self-representation method and utilize an autoregression model in order to simultaneously capture the self-similarity and the temporal continuity of traffic data acquired in the same sensor network. By integrating the above elements in a unified nonconvex learning model, our method can explore the inherent structure of traffic data from the viewpoints of both global multidimensional correlation and fine-grained spatial and temporal dependency. Then, in view of the general framework of the alternating directions method of multipliers (ADMMs), an efficient iterative algorithm is designed to solve our model. Besides, to optimize the parameter combination of the model, a Bayesian optimization (BO)-based parameter selection algorithm is developed, which avoids manual parameter adjustment. Extensive experiments and analyses on two real-world traffic datasets are carried out. The results demonstrate the advantages of our model under diverse missing patterns and missing ratios.

关键词： Alternating directions method of multipliers (ADMMs) low-rank tensor completion (LRTC) spatial-temporal correlation traffic sensor networks

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Reduced-order interval observer based consensus for MASs with time-varying interval uncertainties

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AUTOMATICA 2022年 135卷 109989-109989页

作者： Wang, Xiaoling Wang, Xiaofan Su, Housheng Lam, James Nanjing Univ Posts & Telecommun Coll Automat & AI Nanjing 210023 Peoples R China Jiangsu Engn Lab IOT Intelligent Robots IOTRobot Nanjing 210023 Peoples R China Shanghai Univ Dept Automat Shanghai 200072 Peoples R China Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Image Proc & Intelligent Control Key Lab Educ Minist China Luoyu Rd 1037 Wuhan 430074 Peoples R China Univ Hong Kong Dept Mech Engn Pokfulam Rd Hong Kong Peoples R China

In this paper, the consensus problem of a continuous-time uncertain multi-agent system (MAS) with time-varying interval uncertainties in the system matrix and unknown initial states is investigated via output feedback. Relating only to the interval bounds on the uncertainties, a reduced-order framer, which includes two Luenberger-like observers, is first derived. Then, a distributed control algorithm relying only on the information of the framers associated with each agent and its neighbors is proposed. It is shown that the control algorithm can render the reduced-order framer to be an exponential reduced-order interval observer, and simultaneously drive the uncertain MAS to reach robust consensus exponentially. Finally, numerical simulations for a large-scale MAS are used to verify the theoretical results. (c) 2021 Elsevier Ltd. All rights reserved.

关键词： Consensus Interval observer Multi-agent system Reduced-order observer Uncertain system

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Pattern phase transitions of self-propelled particles: gases, crystals, liquids, and mills

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NEW JOURNAL OF PHYSICS 2016年第10期18卷 103005-103005页

作者： Cheng, Zhao Chen, Zhiyong Vicsek, Tamas Chen, Duxin Zhang, Hai-Tao Huazhong Univ Sci & Technol Sch Automat Key Lab Image Proc & Intelligent Control Wuhan 430074 Peoples R China Huazhong Univ Sci & Technol State Key Lab Digital Mfg Equipment & Technol Wuhan 430074 Peoples R China Dartmouth Coll Thayer Sch Engn Hanover NH 03755 USA Univ Newcastle Sch Elect Engn & Comp Sci Callaghan NSW 2308 Australia Eotvos Lorand Univ Dept Biol Phys Pazmany Petersetany 1A H-1117 Budapest Hungary

To understand the collective behaviors of biological swarms, flocks, and colonies, we investigated the non-equilibrium dynamic patterns of self-propelled particle systems using statistical mechanics methods and H-stability analysis of Hamiltonian systems. By varying the individual vision range, we observed phase transitions between four phases, i.e., gas, crystal, liquid, and mill-liquid coexistence patterns. In addition, by varying the inter-particle force, we detected three distinct milling sub-phases, i.e., ring, annulus, and disk. Based on the coherent analysis for collective motions, one may predict the stability and adjust the morphology of the phases of self-propelled particles, which has promising potential applications in natural self-propelled particles and artificial multi-agent systems.

关键词： Vicsek model collective motions complex networks

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image Fuzzy Edge Information Segmentation Based on Computer Vision and Machine Learning

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JOURNAL OF GRID COMPUTING 2023年第4期21卷 56-56页

作者： Luo, Tianye Li, Shijun Li, Ji Guo, Jie Feng, Ruilong Mu, Ye Hu, Tianli Sun, Yu Guo, Ying Gong, He Jilin Agr Univ Coll Informat Technol Changchun 130118 Jilin Peoples R China Wuzhou Univ Guangxi Key Lab Machine Vis & Intelligent Control Wuzhou 543002 Guangxi Peoples R China Wuzhou Univ Guangxi Coll & Univ Key Lab Image Proc & Intellige Wuzhou 543002 Guangxi Peoples R China Jilin Agr Univ Jilin Prov Agr Internet Things Technol Collaborat Changchun 130118 Jilin Peoples R China Jilin Agr Univ Jilin Prov Intelligent Environm Engn Res Ctr Changchun 130118 Jilin Peoples R China Jilin Agr Univ Jilin Prov Informat Technol & Intelligent Agr Engn Changchun 130118 Jilin Peoples R China

image segmentation is a key problem in the field of machine vision. Its core goal is to separate the target and background in the region of interest from the image and directly affect the accuracy of subsequent operations such as target recognition and image understanding. In the past decades, there have been many good image segmentation algorithms. In recent years, the deep learning method represented by deep learning has made great progress in the field of image segmentation. In this paper, some commonly used image segmentation algorithms based on machine learning were reviewed, and their theoretical and experimental studies were carried out. In this paper, the application prospect of machine learning in image segmentation was prospected. The existing image segmentation methods are mainly divided into the following categories: threshold-based segmentation methods, region-based segmentation methods, edge-based segmentation methods, and segmentation methods based on specific theories. In recent years, with the rapid progress of computer vision technology, the requirements for the accuracy of object image edge information segmentation have become increasingly high. The main reason for image segmentation is to better obtain object information. However, due to interference conditions such as lighting and noise, image blurry edge information segmentation has become the most difficult point in the development of computer vision technology. In the comparative experiment of algorithms, the results showed that in the training set, the response time of Deep Neural Network (DNN) algorithm, Cluster Analysis (CA) algorithm, and Support Vector Machine (SVM) algorithm was 13.72 s, 16.88 s and 17.29 s when the number of samples was 150. In the test set, when the sample number was 50, the recognition rate of DNN algorithm was 93.7%;the recognition rate of CA algorithm was 87.9%;the recognition rate of SVM algorithm was 84.3%. Therefore, the research of image fuzzy edge information

关键词： Blurred Edges image Segmentation Machine Learning Computer Vision Deep Neural Network Cluster Analysis

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