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arXiv 2020年

作者： Zhu, Haiping Shan, Hongming Zhang, Yuheng Che, Lingfu Xu, Xiaoyang Zhang, Junping Shi, Jianbo Wang, Fei-Yue The Shanghai Key Laboratory of Intelligent Information Processing School of Computer Science Fudan University Shanghai200433 China The Institute of Science and Technology for Brain-inspired Intelligence MOE Frontiers Center for Brain Science Fudan University Shanghai200433 China The Shanghai Center for Brain Science and Brain-inspired Technology Shanghai201210 China The GRASP Laboratory University of Pennsylvania PhiladelphiaPA United States The State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China The Institute of Systems Engineering Macau University of Science and Technology 999078 China The University of Chinese Academy of Sciences Beijing100049 China

Image ordinal estimation is to predict the ordinal lab.l of a given image, which can be categorized as an ordinal regression problem. Recent methods formulate an ordinal regression problem as a series of binary classification problems. Such methods cannot ensure that the global ordinal relationship is preserved since the relationships among different binary classifiers are neglected. We propose a novel ordinal regression approach, termed Convolutional Ordinal Regression Forest or CORF, for image ordinal estimation, which can integrate ordinal regression and differentiable decision trees with a convolutional neural network for obtaining precise and stable global ordinal relationships. The advantages of the proposed CORF are twofold. First, instead of learning a series of binary classifiers independently, the proposed method aims at learning an ordinal distribution for ordinal regression by optimizing those binary classifiers simultaneously. Second, the differentiable decision trees in the proposed CORF can be trained together with the ordinal distribution in an end-to-end manner. The effectiveness of the proposed CORF is verified on two image ordinal estimation tasks, i.e. facial age estimation and image aesthetic assessment, showing significant improvements and better stability over the state-of-the-art ordinal regression methods. Copyright © 2020, The Authors. All rights reserved.

关键词： Decision trees

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Design and Implementation of RFID based Smart Shopping Booth 6

Design and Implementation of RFID based Smart Shopping Booth

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6th International Conference on Information Science and control Engineering (ICISCE)

作者： Lodhi, Ehtisham Zhu, Fenghua Lodhi, Zeeshan Saleem, Qasim Xiong, Gang Wang, FeiYue Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Beihang Univ Sch Automat Sci & Elect Engn Beijing 100191 Peoples R China COMSATS Univ Islamabad Dept Elect & Comp Engn Abbottabad Campus Abbottabad 22060 Pakistan Chinese Acad Sci Cloud Comp Ctr Dongguan 523808 Pakistan Chinese Acad Sci Beijing Engn Res Ctr Intelligent Syst & Technol Inst Automat Beijing 100190 Peoples R China

ISBN: (纸本)9781728157122

In this modern era, technology has advanced to such an extent to make our daily life more proficient and convenient. This paper presents the design and implementation of vending machine (VM) for students, which operates on radio frequency identification technology (RFID). Hence, it turns the VM into smart shopping booth (SSB). The SSB gives the access only through RFID card and vend different products according to the desire of student. The SSB is equipped with RFID reader and student identity card that holds the RFID tag. When the student identity card is scanned for verification and then after selecting the required products, will be dispensed off if a student has availab.e balance in his/her identity card and SMS will be sent to students about remaining balance in their cards by GSM technology. The programming for controller is done by using proton IDE language. The SSB is the customized idea of vending machine and it attempts to resolve various issues that appeared in coin/note based VM. The student identity card RFID based technology is a breakthrough towards a paperless and cashless environment. Moreover, it is very beneficial in saving the precious time of students due to fast paced life and also user friendly. RFID based SSB also improved the communication and sensing capabilities of VM. Hence, our suggested approach outperforms in all aspects.

关键词： component VM (Vending Machine) RFID (radio frequency identification technology) SSB (Smart Shopping Booth) GSM SMS Cashless

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An Image-based Automatic Calculation Algorithm for Bridge Crack Size

An Image-based Automatic Calculation Algorithm for Bridge Cr...

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Chinese Automation Congress (CAC)

作者： Wang, Qi Dong, Xisong Shen, Zhen Xiong, Gang Yan, Jun Niu, Lulu Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Beijing Univ Chem Technol Coll Informat Sci & Technol Beijing 102202 Peoples R China Chinese Acad Sci Beijing Engn Res Ctr Intelligent Syst & Technol Inst Automat Beijing 100190 Peoples R China Chinese Acad Sci Cloud Comp Ctr Dongguan 523808 Peoples R China Qingdao Acad Intelligent Ind Qingdao 266000 Peoples R China Univ Chinese Acad Sci Sch Artificial Intelligence Beijing 100039 Peoples R China

ISBN: (纸本)9781728140940

The crack is a serious disease of bridges and one of the important topics in the bridge detecting. Compared with the traditional manual methods for measuring crack size directly or indirectly, this paper proposes a new method based on Matlab.toolbox for digital calculation of crack images. After preprocessing and detecting the original image, some morphological operation like corrosion and expansion have been used in this paper to improve the calculation accuracy. Relying on the connected region calculation, the stepped line is introduced to approach the real crack and obtain the number of pixels in length and width. Then through some calculations, the true size of the crack can be converted from pixel values, which provides a good basis for determining its hazard level. At the end of this paper, experiment results verify the accuracy and practicability of the method, and this method can be used as a subsequent part of crack identification to obtain crack size information.

关键词： digital calculation crack size morphological operation stepped line approach

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A Quantitative Study of Factors Influence on Evacuation in Building Fire Emergencies

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IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL systems 2018年第2期5卷 544-552页

作者： Hu, Yuling Wang, Xiao Wang, Fei-Yue Beijing Univ Civil Engn & Architecture Beijing 100044 Peoples R China Beijing Key Lab Intelligent Proc Bldg Big Data Beijing 100044 Peoples R China Qingdao Acad Intelligent Ind Qingdao 266109 Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 10019 Peoples R China Natl Univ Def Technol Res Ctr Computat Expt & Parallel Syst Changsha 410073 Hunan Peoples R China

In order to decrease the casualties in fire disasters and to improve the efficiency of evacuation, exploring, and revealing the impact of influence factors on evacuation is of vital importance. This paper is focused on the influence of fire and human factors on evacuation processes directed by evacuation strategies in the building structure. Interactions between fire environment and evacuees are considered in a systematic view. Building artificial evacuation systems and performing computational experiments are the main research ways. A case is given to illustrate the research approach and quantitative results have been analyzed. The work in this paper can be used for optimizing occupant distribution and composition, estimating evacuation strategies, and ultimately for improving the evacuation efficiency.

关键词： Artificial evacuation systems building fire computational experiments evacuation strategies influence factor quantitative analysis

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Parallel intelligent systems for Integrated High-Speed Railway Operation control and Dynamic Scheduling

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IEEE TRANSACTIONS ON CYBERNETICS 2018年第12期48卷 3381-3389页

作者： Dong, Hairong Zhu, Hainan Li, Yidong Lv, Yisheng Gao, Shigen Zhang, Qi Ning, Bin Beijing Jiaotong Univ State Key Lab Rail Traff Control & Safety Beijing 100044 Peoples R China Beijing Jiaotong Univ Sch Comp & Informat Technol Beijing 100044 Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Qingdao Acad Intelligent Ind Parallel Traff Innovat Technol Ctr Qingdao 266109 Peoples R China China Acad Railway Sci Signal & Commun Res Inst Beijing 100081 Peoples R China

The information exchange gap between current operation control and dynamic scheduling in high-speed railway systems (HRSs) still exists, and this gap has hindered the further integrative improvement of HRSs. This paper aims to explore a feasible solution to bridging the information exchange gap for further improving the efficiency of HRSs, with the parallel intelligent systems for integrated HRS operation control and dynamic scheduling first analyzed and constructed using the ACP approach, that is, "artificial systems" (A), "computational experiments," (C) and "parallel execution" (P). Then, on the basis of the constructed parallel intelligent systems, experiments on several typical scenarios in HRSs are conducted to achieve a set of control and management strategies for actual HRSs. Experimental results show that a number of powerful tools provided by the proposed parallel intelligent systems can be utilized not only to study the current HRSs, but also to further undertake research on integrated operation control and dynamic scheduling for HRSs.

关键词： ACP approach high-speed railway system (HRS) integrated operation control and dynamic scheduling parallel intelligent system

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Modified Gram-Schmidt Method-Based Variable Projection Algorithm for Separable Nonlinear Models

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IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING systems 2019年第8期30卷 2410-2418页

作者： Chen, Guang-Yong Gan, Min Ding, Feng Chen, C. L. Philip Fuzhou Univ Coll Math & Comp Sci Fuzhou 350116 Fujian Peoples R China Fuzhou Univ Fujian Prov Key Lab Network Comp & Intelligent In Fuzhou 350116 Fujian Peoples R China Minist Educ Key Lab Spatial Data Min & Informat Sharing Fuzhou 350116 Fujian Peoples R China Fuzhou Univ Ctr Discrete Math & Theoret Comp Sci Fuzhou 350116 Fujian Peoples R China Qingdao Univ Sci & Technol Coll Automat & Elect Engn Qingdao 266042 Shandong Peoples R China Jiangnan Univ Sch Internet Things Engn Wuxi 214122 Jiangsu Peoples R China Univ Macau Fac Sci & Technol Dept Comp & Informat Sci Macau 99999 Peoples R China Dalian Maritime Univ Nav Coll Dalian 116026 Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100080 Peoples R China

Separable nonlinear models are very common in various research fields, such as machine learning and system identification. The variable projection (VP) approach is efficient for the optimization of such models. In this paper, we study various VP algorithms based on different matrix decompositions. Compared with the previous method, we use the analytical expression of the Jacobian matrix instead of finite differences. This improves the efficiency of the VP algorithms. In particular, based on the modified Gram-Schmidt (MGS) method, a more robust implementation of the VP algorithm is introduced for separable nonlinear least-squares problems. In numerical experiments, we compare the performance of five different implementations of the VP algorithm. Numerical results show the efficiency and robustness of the proposed MGS method-based VP algorithm.

关键词： Data fitting modified Gram-Schmidt (MGS) parameter estimation separable nonlinear least-squares problem variable projection (VP)

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M⁴CD: A Robust Change Detection Method for intelligent Visual Surveillance

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IEEE ACCESS 2018年 6卷 15505-15520页

作者： Wang, Kunfeng Gou, Chao Wang, Fei-Yue Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Qingdao Acad Intelligent Ind Innovat Ctr Parallel Vis Qingdao 266000 Peoples R China Natl Univ Def Technol Res Ctr Computat Expt & Parallel Sys Changsha 410073 Hunan Peoples R China

In this paper, we propose a robust change detection method for intelligent visual surveillance. This method, named (MCD)-C-4, includes three major steps. First, a sample-based background model that integrates color and texture cues is built and updated over time. Second, multiple heterogeneous features (including brightness variation, chromaticity variation, and texture variation) are extracted by comparing the input frame with the background model, and a multi-view learning strategy is designed to online estimate the probability distributions for both foreground and background. The three features are approximately conditionally independent, making multi-view learning feasible. Pixel-wise foreground posteriors are then estimated with Bayes rule. Finally, the Markov random field (MRF) optimization and heuristic postprocessing techniques are used sequentially to improve accuracy. In particular, a two-layer MRF model is constructed to represent pixel-based and superpixel-based contextual constraints compactly. Experimental results on the CDnet dataset indicate that (MCD)-C-4 is robust under complex environments and ranks among the top methods.

关键词： Change detection multimodal background multi-view learning conditional independence Markov random field

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An AI based High-speed Railway Automatic Train Operation System Analysis and Design

An AI based High-speed Railway Automatic Train Operation Sys...

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International Conference on intelligent Rail Transportation (ICIRT)

作者： Zhang, Miao Zhang, Qi Lv, Yisheng Sun, Wenzhe Wang, Haiteng China Acad Railway Sci Corp Ltd Ctr Natl Railway Intelligent Transportat Syst Eng Beijing Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing Peoples R China

ISBN: (纸本)9781538675281

Recent years, the research and application of High-Speed Railway (HSR) automatic train operation (ATO) system are under fast development, while the safety, energy efficiency and passenger comfort of ATO systems still need improvement. On the other hand, Artificial Intelligence (AI) technology, for example, Deep Learning, has been widely applied in automata industry such as robot control and driverless vehicle. In this paper, we propose a new idea of improving train control system performance with Al technologies such as Deep Reinforcement Learning and Imitation learning, and describe the system objective, structure and development process. The details of key processes such as establishment of Train Running Condition Evaluation Index, acquisition and processing of relevant big data, construction of Al based automatic train operation model and the program of simulation and experiment are presented in this paper, which provides a brand new and practical idea to the development of High-Speed Railway automatic train operation systems.

关键词： HSR ATO Artificial Intelligence Deep Reinforcement Learning Imitation Learning

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Privacy protection based on many-objective optimization algorithm

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CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE 2019年第20期31卷 e5342-e5342页

作者： Zhang, Jiangjiang Xue, Fei Cai, Xingjuan Cui, Zhihua Chang, Yu Zhang, Wensheng Li, Wuzhao Taiyuan Univ Sci & Technol Complex Syst & Computat Intelligence Lab Taiyuan 030024 Shanxi Peoples R China Beijing Wuzi Univ Sch Informat Beijing Peoples R China Chinese Acad Sci State Key Lab Intelligent Control & Management Co Inst Automat Beijing Peoples R China Jiaxing Vocat Tech Coll Jiaxing Peoples R China

It is difficult to protect users' privacy and to process private information due to the complexity and uncertainty of such information. To protect private information quickly and accurately, a many-objective optimization algorithm framework based on the hybrid elite selection strategy is proposed in this paper. First, a mating selection mechanism combined with the achievement scale function and angle information index is used to generate elite offspring of the internal population. Then, the balanceable fitness estimation method is employed to select and update the external archive. To test performance, the proposed algorithm is tested on many-objective optimization problems (MaOPs) and compared with five state-of-the-art algorithms. Experimental simulation results show that the proposed algorithm is more effective in solving MaOPs and can inspire development of a better privacy protection strategy.

关键词： achievement scalarizing function angle information index balanceable fitness estimation method many-objective optimization algorithm privacy protection

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From Parallel Plants to Smart Plants:intelligent control and management for Plant Growth

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IEEE/CAA Journal of Automatica Sinica 2017年第2期4卷 161-166页

作者： Mengzhen Kang Fei-Yue Wang State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences (SKL-MCCSCASIA) Qingdao Academy of Intelligent Industries Beijing Engineering Research Center of Intelligent Systems and Technology IEEE State Key Laboratory of Management and Control for Complex Systems (SKL-MCCS) Institute of AutomationChinese Academy of Sciences (CASIA) School of Computer and Control Engineering University of Chinese Academy of Sciences Research Center for Military Computational Experiments and Parallel Systems Technology National University of Defense Technology

Precision management of agricultural systems, aiming at optimizing profitability, productivity and sustainability, comprises a set of technologies including sensors, information systems, and informed management, etc. Expert systems are expected to aid farmers in plant management or environment control, but they are mostly based on the offline and static information, deviated from the actual situation. Parallel management, achieved by virtual/artificial agricultural system, computational experiment and parallel execution, provides a generic framework of solution for online decision support. In this paper, we present the three steps toward the parallel management of plant: growth description U+0028 the crop model U+0029, prediction, and prescription. This approach can update the expert system by adding learning ability and the adaption of knowledge database according to the descriptive and predictive model. The possibilities of passing the knowledge of experienced farmers to younger generation, as well as the application to the parallel breeding of plant through such system, are discussed. © 2017 Chinese Association of Automation.

关键词： Agriculture Artificial intelligence Decision support systems Expert systems Sustainable development

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