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第三十八届中国控制会议

作者： Liangming Chen Long Jin Yuhe Li Mei Liu Bolin Liao Chenfu Yi Zhongbo Sun School of Information Science and Engineering Lanzhou University Guangdong Provincial Engineering Technology Research Center for Sports Assistive Device Guangzhou Sport University College of Information Science and Engineering Jishou University College of Mathematics and Computer Science Gannan Normal University Department of Control Engineering Changchun University of Technology

Traditional gradient-based neural networks may fall into local minima, and because these networks involve with lengthy iteration process, they are not fast enough. By the generalized-inverse method, the least squares solution with the smallest2-norm can be obtained. For traditional neural networks based on generalized-inverse method, the weights from the hidden layer to the output layer and the biases are generated by a random approach;the weights from the hidden layer to the output layer are calculated with the aid of generalized-inverse method. In triple generalized-inverse neural network(TGINN) proposed in this paper, all the weight matrixes from one layer to another are calculated with the aid of generalized-inverse method, as well as for biases of neurons in the hidden layer. Comparison experiments between TGINN and other models are carried out, and the experimental results illustrate the superiority of the proposed TGINN.

关键词： Neural network computer-aided diagnosis Generalized-inverse method Flat foot

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Target tracking based on KCF combining with spatio-temporal context learning

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International Journal of Performability engineering 2018年第2期14卷 386-395页

作者： Wang, Aili Yang, Zhennan Chen, Yushi Iwahori, Yuji Higher Education Key Lab for Measure and Control Technology and Instrumentations of Heilongjiang Harbin University of Science and Technology Harbin150080 China School of Electronics and Information Engineering Harbin Institute of Technology Harbin150001 China Dept of Computer Science Chubu University Aichi Japan

Most target tracking is based on a lot of samples training to build the model of the target, which is then carried on the tracking processing. This will need to choose a lot of tracked target samples for learning and training. However, there are all kinds of deformation of the training samples, including variety of light and scale, and so on, causing the long computation time, high computational complexity, and less robustness. The traditional kernel correlation filtering (KCF) tracking is through online learning of the first frame in the target vide. It then uses cyclic matrix to strengthen samples robustness, reducing the complexity of the calculation and time. But, the traditional KCF nuclear is unsatisfactory used for complex scenarios and quick treatment. In this paper, under the framework of the KCF, the target context information is introduced to make the tracking have better robustness and a better effect to deal with complex scenarios. © 2018 Totem Publisher, Inc. All rights reserved.

关键词： Target tracking

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A Study on the Differences of Attitude Learning and Learning Behavior Sequences for University computer MOOC+ SPOC Course

A Study on the Differences of Attitude Learning and Learning...

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International Conference on computer Science & Education (ICCSE)

作者： Zhao Changhua Mi Chunqiao School of Computer Science and Engineering Huaihua University Huaihua P. R. China Key Laboratory of Wuling-Mountain Health Big Data Intelligent Processing and Application in Hunan Province Universities Huaihua P. R. China Key Laboratory of Intelligent Control Technology for Wuling-Mountain Ecological Agriculture in Hunan Province Huaihua P. R. China

ISBN: (数字)9781728172675

ISBN: (纸本)9781728172682

The outbreak of COVID-19 make University computer MOOC+SPOC course face opportunities and challenges. There are some problems in MOOC+SPOC course teaching, such as learners' curiosity decreasing, lack of accomplishment and etc. In order to deal with these problems, this study explores the correlation and differences in the learning behavior sequences of learners with different attitudes to high happiness, medium happiness, and low happiness. Through the learners' comments on University computer MOOC+SPOC course, the learner's attitude information is tapped. By analyzing learning behavior sequences, this study finds out the degree of learning behavior change of learners with different attitudes. The result of this study can improve the existing University computer MOOC+SPOC instructional design and promote the learning mode to move towards intelligent personalized adaptive learning.

关键词： Interviews Electronic learning Data analysis Encoding Correlation

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A Study on Tuning Methods of Linear Active Disturbance Rejection control for a Class of Thermal Processes

A Study on Tuning Methods of Linear Active Disturbance Rejec...

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International Conference on Information Science and control engineering (ICISCE)

作者： Bo Li Li Wang Rui Zhao Shuang Zhang Ming Sun Inner Mongolia Branch Thermal Power Technology Research Institute China Datang Corporation Science and Technology Research Institute Co. Ltd Huhhot China Thermal Power Technology Research Institute China Datang Corporation Science and Technology Research Institute Co. Ltd Beijing China School of Control and Computer Engineering North China Electric Power University Baoding China

Active disturbance rejection controllers have been applied in a certain range in industrial processes. Aiming at the control difficulties of a class of large inertia and large delay thermal processes in thermal power plant, this paper studies two second-order linear ADRC parameter setting methods, and discusses their control effects and applicability. Based on the known process model, one method is to transform model into the form of $K/(Ts+1)^{n}$, and then based on the given maximum sensitivity function, the controller parameter tuning formula is obtained through the asymptote of the Nyquist curve; the other is to transform model into the form of $Ke^{-\tau s}/(Ts+1)$, and then the controller parameters are designed with this approximate model. Taking the superheated steam temperature system of a 330MW thermal power unit as the controlled object, the simulation study was performed by LADRC. The calculation of the control efficiency index and the integration index of ITAE and ISE is carried out from the three aspects, which are set-point tracking, robust performance and noise test. The control effect and scope of application of the two empirical setting formulas are analyzed and the valuable guidance is given.

关键词： Temperature sensors Robust control Sensitivity Process control Transforms Robustness Temperature control

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Towards better surgical instrument segmentation in endoscopic vision: multi-angle feature aggregation and contour supervision

arXiv

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arXiv 2020年

作者： Qin, Fangbo Lin, Shan Li, Yangming Bly, Randall A. Moe, Kris S. Hannaford, Blake Research Center of Precision Sensing and Control Institute of Automation Chinese Academy of Sciences Beijing100190 China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing101408 China SeattleWA98195-2500 United States Department of Otolaryngology-Head & Neck Surgery UW Seattle United States Department of Electrical Computer and Telecommunications Engineering Technology Rochester Institute of Technology United States

—Accurate and real-time surgical instrument segmentation is important in the endoscopic vision of robot-assisted surgery, and significant challenges are posed by frequent instrument-tissue contacts and continuous change of observation perspective. For these challenging tasks more and more deep neural networks (DNN) models are designed in recent years. We are motivated to propose a general embeddable approach to improve these current DNN segmentation models without increasing the model parameter number. Firstly, observing the limited rotation-invariance performance of DNN, we proposed the Multi-Angle Feature Aggregation (MAFA) method, leveraging active image rotation to gain richer visual cues and make the prediction more robust to instrument orientation changes. Secondly, in the end-to-end training stage, the auxiliary contour supervision is utilized to guide the model to learn the boundary awareness, so that the contour shape of segmentation mask is more precise. The effectiveness of the proposed methods is validated with ablation experiments conducted on novel Sinus-Surgery datasets. Copyright © 2020, The Authors. All rights reserved.

关键词： Deep neural networks

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SoccerNet 2023 Challenges Results

arXiv

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arXiv 2023年

作者： Cioppa, Anthony Giancola, Silvio Somers, Vladimir Magera, Floriane Zhou, Xin Mkhallati, Hassan Deliège, Adrien Held, Jan Hinojosa, Carlos Mansourian, Amir M. Miralles, Pierre Barnich, Olivier De Vleeschouwer, Christophe Alahi, Alexandre Ghanem, Bernard Van Droogenbroeck, Marc Kamal, Abdullah Maglo, Adrien Clapés, Albert Abdelaziz, Amr Xarles, Artur Orcesi, Astrid Scott, Atom Liu, Bin Lim, Byoungkwon Chen, Chen Deuser, Fabian Yan, Feng Yu, Fufu Shitrit, Gal Wang, Guanshuo Choi, Gyusik Kim, Hankyul Guo, Hao Fahrudin, Hasby Koguchi, Hidenari Ardö, Håkan Salah, Ibrahim Yerushalmy, Ido Muhammad, Iftikar Uchida, Ikuma Be'ery, Ishay Rabarisoa, Jaonary Lee, Jeongae Fu, Jiajun Yin, Jianqin Xu, Jinghang Nang, Jongho Denize, Julien Li, Junjie Zhang, Junpei Kim, Juntae Synowiec, Kamil Kobayashi, Kenji Zhang, Kexin Habel, Konrad Nakajima, Kota Jiao, Licheng Ma, Lin Wang, Lizhi Wang, Luping Li, Menglong Zhou, Mengying Nasr, Mohamed Abdelwahed, Mohamed Liashuha, Mykola Falaleev, Nikolay Oswald, Norbert Jia, Qiong Pham, Quoc-Cuong Song, Ran Hérault, Romain Peng, Rui Chen, Ruilong Liu, Ruixuan Baikulov, Ruslan Fukushima, Ryuto Escalera, Sergio Lee, Seungcheon Chen, Shimin Ding, Shouhong Someya, Taiga Moeslund, Thomas B. Li, Tianjiao Shen, Wei Zhang, Wei Li, Wei Dai, Wei Luo, Weixin Zhao, Wending Zhang, Wenjie Yang, Xinquan Ma, Yanbiao Joo, Yeeun Zeng, Yingsen Gan, Yiyang Zhu, Yongqiang Zhong, Yujie Ruan, Zheng Li, Zhiheng Huang, Zhijian Meng, Ziyu Belgium Saudi Arabia Sportradar Norway UCLouvain Belgium EPFL Switzerland EVS Broadcast Equipment Belgium Baidu Research United States Belgium Sharif University of Technology Iran Footovision France Zewail City of Science Technology and Innovation Egypt Université Paris-Saclay CEA France Universitat de Barcelona Spain Computer Vision Center Spain Nagoya University Japan Research Center for Applied Mathematics and Machine Intelligence Zhejiang Lab China AIBrain United States OPPO Research Institute China Germany Meituan China Tencent Youtu Lab China Amazon Prime Video Sport United States Sogang University Korea Republic of The University of Tokyo Japan Spiideo Sweden University of Tsukuba Japan School of Artificial Intelligence Beijing University of Posts and Telecommunications China Normandie Univ INSA Rouen LITIS France Shanghai Jiao Tong University China Key Laboratory of Intelligent Perception and Image Understanding The Ministry of Education Xidian University China NASK - National Research Institute Poland Robo Space China Tongji University China Sportlight Technology United Kingdom School of Control Science and Engineering Shandong University China lRomul Russia Aalborg University Denmark Turing AI Cultures GmbH Germany Information Systems Technology and Design Singapore University of Technology and Design Singapore Sun Yat-sen University China

The SoccerNet 2023 challenges were the third annual video understanding challenges organized by the SoccerNet team. For this third edition, the challenges were composed of seven vision-based tasks split into three main themes. The first theme, broadcast video understanding, is composed of three high-level tasks related to describing events occurring in the video broadcasts: (1) action spotting, focusing on retrieving all timestamps related to global actions in soccer, (2) ball action spotting, focusing on retrieving all timestamps related to the soccer ball change of state, and (3) dense video captioning, focusing on describing the broadcast with natural language and anchored timestamps. The second theme, field understanding, relates to the single task of (4) camera calibration, focusing on retrieving the intrinsic and extrinsic camera parameters from images. The third and last theme, player understanding, is composed of three low-level tasks related to extracting information about the players: (5) re-identification, focusing on retrieving the same players across multiple views, (6) multiple object tracking, focusing on tracking players and the ball through unedited video streams, and (7) jersey number recognition, focusing on recognizing the jersey number of players from tracklets. Compared to the previous editions of the SoccerNet challenges, tasks (2-3-7) are novel, including new annotations and data, task (4) was enhanced with more data and annotations, and task (6) now focuses on end-to-end approaches. More information on the tasks, challenges, and leader-boards are available on https://***. Baselines and development kits can be found on https://***/SoccerNet. © 2023, CC BY.

关键词： computer vision

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A Hierarchical Bidirectional LSTM Sequence Model for Extractive Text Summarization in Electric Power Systems

A Hierarchical Bidirectional LSTM Sequence Model for Extract...

引用

International Symposium on Computational Intelligence and Design, ISCID

作者： Wei Jiang Yunfeng Zou Ting Zhao Qiang Zhang Yinglong Ma State Grid Corporation of China Beijing China Marketing Service Center of State Grid Jiangsu Electric Power Co. Ltd Global Energy Interconnection Research Institute Co. Ltd Artificial Intelligence on Electric Power System State Grid Corporation Joint Laboratory Beijing China School of Control and Computer Engineering North China Electric Power University Beijing China

ISBN: (数字)9781728184463

ISBN: (纸本)9781728184470

With the increasing volume of documents in electric power systems, it is urgent and necessary for electric power systems managers to efficiently analyze the massive documents and make reasonable decisions by capturing the main points of the document as quickly as possible. The text summarization technique provides a feasible way to efficiently analyze and obtain the main contents residing in the document. In this paper, we present a Hierarchical Bidirectional Long Term Short Memory Sequence model for extractive text summarization in electric power systems in order to efficiently and accurately summarize electric power documents and obtain a summary of the document. Our model is divided into four layers including the embedding layer, the word layer, the sentence layer, and the classification layer in a hierarchical manner. The related experiments were made based on the electric power data set that contains more than 2000 electrical papers, in comparison with the existing approaches based on the CRF, CNN, and RNN models. The experimental results show that the performance based on our approach is superior to the three approaches against the three performance indexes ROUGE-1, ROUGE-2, and ROUGE-L.

关键词： Power systems Feature extraction Mathematical model Logic gates Task analysis Data mining Bit error rate

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Research on collaborative frequency regulation control strategy of wind farm based on decentralized exit 8

Research on collaborative frequency regulation control strat...

引用

8th Renewable Power Generation Conference, RPG 2019

作者： Ren, Y.H. Song, P. Wang, X.S. Shi, R.F. School of Control and Computer Engineering North China Electric Power University Beijing102206 China State Grid Jibei Electric Power Research Institute North China Electric Power Research Institute Co.Ltd. Beijing100045 China Grid-connected Operation Technology for Wind-Solar Storage Hybrid System State Grid Corporation Key Laboratory Beijing100045 China

ISBN: (纸本)9781839531255

When the wind turbine adopts the rotor inertia control to participate in grid frequency regulation, it is easy to cause the second frequency drop, which will be more serious when applied to the wind farm. To solve this problem, the influence of wind speed on the unit's ultimate support time under the constant power support mode is analyzed quantitatively and wind turbine recovery time is defined. The functional relationship between the unit's support time and recovery time suitable for engineering application is given. A wind farm frequency regulation optimization model aiming at the longest supporting time of all units in the whole station is established, and the wind farm coordinated frequency regulation control strategy based on decentralized exit is proposed, taking full account of capacity differences of units under different working conditions. Simulation examples show that the real-time coordination of the exit of the wind turbine frequency regulation can effectively alleviate the secondary frequency drop problem of a wind farm. © 2019 Institution of engineering and Technology. All rights reserved.

关键词： Wind turbines

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Automatic Support of the Generation and Maintenance of Assurance Cases 4th

Automatic Support of the Generation and Maintenance of Assur...

引用

4th International Symposium on Dependable Software engineering: Theories, Tools, and Applications, SETTA 2018

作者： Lin, Chung-Ling Shen, Wuwei Yue, Tao Li, Guangyuan Department of Computer Science Western Michigan University Kalamazoo United States Simula Research Laboratory University of Oslo Oslo Norway State Key Laboratory of Computer Science Institute of Software Beijing China China School of Computer and Control Engineering UCAS Beijing China

ISBN: (纸本)9783319999326

One of the challenges in developing safety critical systems is to ensure software assurance which encompasses quality attributes such as reliability and security as well as functionality and performance. An assurance case, which lays out an argumentation-structure with supporting evidence to claim that software assurance in a system is achieved, is increasingly considered as an important means to gain confidence that a system has achieved acceptable safety when checking with emerging standards and national guidelines. However, the complexity of modern safety critical applications hinders the automatic integration of heterogeneous artifacts into an assurance case during a development process such as a V-model, let alone the automatic support of system evolution. In this paper, we present a novel framework to automatically generate assurance cases via safety patterns and further support the maintenance of them during a system’s evolution. The application of safety patterns not only enables reusability of previously successful argument structures but also directs the support of assurance maintenance caused by common types of modifications in safety critical domains. The framework is implemented as a prototypical tool built using Model Driven Architecture (MDA). We evaluated the framework with two case studies featuring two criteria and the preliminary experimental results not only show that the framework is useful in evaluation of safety critical systems but also reveal how different types of modification can affect a structure of an assurance case. © 2018, Springer Nature Switzerland AG.

关键词： Reusability

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Analysis of Harmonics Detection and their Filtration by using Active Band Pass Filter for Domestic Appliances

Analysis of Harmonics Detection and their Filtration by usin...

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IEEE International Conference on Automation Science and engineering (CASE)

作者： Ehtisham Lodhi Zeeshan Lodhi Zhu Fenghua Gang Xiong Feiyue Wang Waheed ur Rehman Tariku Sinshaw The SKL for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China Department of Electrical and Computer Engineering COMSATS University Islamabad Abbottabad Campus Pakistan Guangdong Engineering Research Center of 3D Printing and Intelligent Manufacturing Cloud Computing Center Chinese Academy of Sciences Dongguan Guangdong China Beijing Engineering Research Center of Intellectual System and Technology Chinese Academy of Sciences Beijing China College of Mechanical Engineering and Applied Electronics Technologies Beijing University of Technology Beijing China

ISBN: (数字)9781728169040

ISBN: (纸本)9781728169057

In modern era, one of the rising power quality (PQ) concern is harmonics distortion (HD). The HD is usually produced by increase in the utilization of nonlinear user loads at domestic level. It not only spoils the PQ but also have harmful effects on electrical appliances. So, this paper presents a new approach to mitigate the HD in home appliances rapidly by utilizing the active band pass filter (ABPF). The fast Fourier transform (FFT) technique is employed for the detection of harmonics in appliances. The band pass filter dramatically affects the response time of active filter. The suggested control methodology is capable to eliminate harmonics from distorted input voltage waveform and provides a pure sinusoidal waveform. The prototype of this model is also implemented. Experimental results along with simulation show that the proposed model is quite effective in eliminating HD despite load variations and also useful to compensate the reactive power in electronic home appliances. Hence, this technique is cost effective for domestic users with high quality performance in all aspects.

关键词： Power harmonic filters Harmonic analysis Band-pass filters Harmonic distortion Home appliances

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