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International Symposium on Autonomous Decentralized Systems (ISADAS)

作者： Jinhui Zhu Yinong Chen Mei Zhang Qiang Chen Ying Guo Huaqing Min Zhilie Chen School of Software Engineering South China University of Technology Guangzhou China School of Computing Informatics and Decision Systems Engineering Arizona State University Tempe USA School of Automation Science and Control Engineering South China University of Technology Guangzhou China College of computer & information science Southwest University Chongqing China School of Information Science and Technology Qingdao University of Science and Technology Qingdao China EVOC Intelligent Technology Company Limited Shen zhen China

ISBN: (数字)9781728116723

ISBN: (纸本)9781728116730

Information processing of guide dog robot requires expensive computing resources to meet real-time performance. We propose an edge computing framework based on Intel Up-Squared board and neural compute stick. Image processing and real-time control are performed on the framework. In addition, the voice recognition and commanding are also implemented, which are processed on Amazon cloud service. Vision, speech, and control services are integrated by ASU VIPLE (Visual IoT/Robotics Programming Language Environment). A prototype is developed, which implements the guide dog's obstacle avoidance, traffic sign recognition and following, and voice interaction with human.

关键词： Dogs Mobile robots Robot sensing systems Wheelchairs Edge computing Cameras

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A differentially k-anonymity-based location privacy-preserving for mobile crowdsourcing systems

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Procedia computer Science 2018年 129卷 28-34页

作者： Yingjie Wang Zhipeng Cai Zhongyang Chi Xiangrong Tong Lijie Li School of Computer Science and Engineering South China University of Technology Guangzhou 510006 China School of Computer and Control Engineering Yantai University Yantai 264005 China Department of Computer Science Georgia State University Atlanta 30303 USA College of Computer Science and Technology Harbin Engineering University Harbin 150001 China

With the rapid development of mobile devices, the problem privacy leaking has become an important research focus in the field of mobile crowdsourcing. In order to guarantee the security and truthfulness of mobile crowdsourcing, this paper proposes a differentially k -anonymity location privacy-preserving for mobile crowdsourcing. Through combining k-anonymity and differential privacy-preserving, the differentially k -anonymity-based location privacy-preserving is proposed in order to prevent workers’ location information from being leaked. Through comparison experiments, the effectiveness, adaptation and flexibility of the proposed differentially k -anonymity-based location privacy-preserving is verified. The differentially k -anonymity-based location privacy-preserving can inspire workers to participate crowd tasks, and protect workers’ location privacy effectively.

关键词： Mobile crowdsourcing location privacy-preserving k -anonymity differential privacy

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A method of registering virtual objects in monocular augmented reality system 13th

A method of registering virtual objects in monocular augment...

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13th Conference on Image and Graphics Technologies and Applications, IGTA 2018

作者： Wu, Zeye Wang, Pengrui Che, Wujun Institute of Automation Chinese Academy of Sciences Beijing100190 China School of Computer and Control Engineering University of Chinese Academy of Sciences Beijing100049 China AICFVE of Beijing Film Academy Beijing100088 China

ISBN: (纸本)9789811317019

A flexible novel method of registering virtual objects in monocular AR system is presented in this paper. Monocular AR systems use SLAM-related techniques to obtain the camera pose, of which the translation component is on a random scale. We add a scale calibration process to acquire the scale factor from the SLAM map to the real world and provide a closed-form solution of the transformation between two coordinate systems with different scales. We also describe the framework of an AR system based on our method with implementation. The proposed system can easily initialize virtual objects’ position, orientation and size by using a known reference in the real scene and the reference is no longer needed in the later process. Our method is flexible, simple to set up and easy to control. The results show the proposed method can apply to real-time interactive AR applications. © Springer Nature Singapore Pte Ltd., 2018.

关键词： Augmented reality

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Dynamic Prediction of NOx Emissions Based on Factor Analysis and NARX Neural Network

Dynamic Prediction of NOx Emissions Based on Factor Analysis...

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Chinese Automation Congress (CAC)

作者： Chuanyu Tan Yan Bai Xinli Li School of Control and Computer Engineering North China Electric Power University Beijing China

NOx emissions of thermal power plants are closely related to the environment. It is very important to research on the prediction of NOx emissions. However, most of the current models are static and did not take into account the impact of the previous data. Boiler combustion is a process with large delay, and NOx generation also goes through a certain process, so we cannot just focus on the data at the current moment. In this paper, the dynamic prediction model of NOx emissions combining factor analysis and NARX dynamic neural network is proposed. The common factors that play the important roles in NOx formation are extracted based on the factor analysis method. It can eliminate the collinearity of the original data and reduce the complexity of modeling. The factor score matrix of common factors is used as the input of the NARX neural network, and a dynamic model is established, taking full account of the influence of various operating parameters and output parameters on the NOx emission at the previous moment. The simulation results show the effective and feasible of the model in NOx emissions prediction.

关键词： Biological neural networks Predictive models Boilers Combustion Data models Analytical models

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Loop Invariant Generation for Non-monotone Loop Structures

Loop Invariant Generation for Non-monotone Loop Structures

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IEEE Annual International computer Software and Applications Conference (COMPSAC)

作者： Chunyan Hou Jinsong Wang Chen Chen Kai Shi School of Computer Science and Engineering Tianjin University of Technology Tianjin China College of Computer and Control Engineering Nankai University Tianjin China

ISBN: (纸本)9781538626672

A key problem in any automatic software verification system is the inference of loop invariants. When analyzing program structures involving disjunctive semantics, abstract interpretation has the problem of precision loss. Thus, some techniques were proposed to decompose such loop structures into a semantically equivalent sequence of loops with conjunctive semantics whose invariants can be generated by abstract interpretation directly. However, these works assumed that the iteration processes of nested branches are separate without consideration of non-monotone loop structures where those interweave with each other. In order to solve this problem, we present a novel static analysis technique for non-monotone loops. It analyzes loop convergence condition and traces the transfer between nested branches of finite non-monotone loops. With analytical results, it generates the loop invariants with precise semantics. Meanwhile, it takes advantage of cyclical nature of result expressions to restrict search space and accelerate computation procedure. Finally, experimental results show the potential of our approach, which is also helpful for reasoning about certain program security properties.

关键词： Convergence Semantics Software Static analysis Acceleration Security Standards

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Network Parameter Generation for One-Shot Object Detection

Network Parameter Generation for One-Shot Object Detection

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IEEE International Conference on Unmanned Systems (ICUS)

作者： Kang Wang Jiajia Zhao Yang Wang Shuigeng Zhou Shanghai Key Lab of Intelligent Information Processing and School of Computer Science Fudan University Shanghai China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing Electro-Mechanical Engineer Institute Beijing China School of Information Engineering Nanchang University China

ISBN: (纸本)9781728137933

Recent object detection models have achieved satisfactory performance by deep learning with large-scale annotated datasets. However, these models often perform poorly when the training examples are not sufficient enough, especially for one-shot object detection where there is only one training example of each target class. In this paper, we propose a network parameter generation framework for effective one-shot object detection. By leveraging the semantic relationship between the source-domain and the target-domain (new classes), our framework can generate network parameters for the new classes directly. Furthermore, we develop two implementation schemes for this framework: weighting-based parameter generation and regression-based parameter generation. These two schemes use different information to construct the relationship and transfer knowledge from the source-domain to the target-domain. Experiments on the PASCAL-OSCD benchmark show that our methods can significantly boost the performance of one-shot object detection.

关键词： Object detection Detectors Head Training Feature extraction Task analysis Training data

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A procedure to generate discrete MIMO closed-loop benchmark via LFT with application to state space identification 15

A procedure to generate discrete MIMO closed-loop benchmark ...

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15th International Conference on Informatics in control, Automation and Robotics, ICINCO 2018

作者： Puerto Acosta, Jorge A. Bottura, Celso P. Intelligent Systems and Control Laboratory School of Electrical and Computer Engineering University of Campinas/UNICAMP Cidade Universitria Zeferino Vaz Av. Albert Einstein 400 Campinas/SPCEP 13083-852 Brazil

ISBN: (纸本)9789897583216

In this paper we use the conformal transformation known as linear fractional transformation (LFT), with the purpose of generating a discrete multivariable closed-loop benchmark from continuous multivariable closed-loop control system, having in mind state space identification. To reach this objective we propose a procedure based on the general framework representation (GFR) and on the multi input multi output (MIMO) LFT bilin-ear discretization process. We first use the LFT tool to obtain the continuous joint control-output (augmented) system form for representing the canonical closed-loop continuous system. Afterwards, we discretize the augmented continuous closed-loop system in order to obtain an augmented discrete model, then, we calculate the discrete plant and controller in the state space form. An application to the multivariable control of a continuous chemical reactor is presented and also we use the discrete benchmark generated to identify a state space model an example of the potential of the our proposal. Copyright © 2018 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved

关键词： Closed loop control systems

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Condensate Throttling Based Coordinated System Optimization with Improved Simplex Method for an 1000-MW USC Power Unit

Condensate Throttling Based Coordinated System Optimization ...

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Chinese Automation Congress (CAC)

作者： Liangyu Ma Qianqian Li Fan Li Peiyao Zhang School of Control and Computer Engineering North China Electric Power University Baoding China

In order to absorb more new energy power sources, regional load dispatch center puts up very high requirement for the operation flexibility, load fast-following and deep peak load regulation ability of an ultra-supercritical (USC) power unit. Therefore, it is very significant to adopt advanced control strategies to optimize the Coordinated control System (CCS). In this work, the load prediction neural network model considering `condensate throttling' and the main steam pressure prediction model are developed by taking a 1000MW ultra-supercritical power unit as the object investigated. Based on the established models, a classic optimization theory-improved simplex method is selected as the CCS optimization algorithm. An intelligent coordination optimization scheme with condensate throttling is designed, and the real-time optimization program is developed with MATLAB software. Detailed simulation tests are carried out in the full-scope simulator of the 1000MW power unit. Simulation results indicate that the proposed scheme can effectively improve the coordinated control quality with faster load response, less main steam pressure fluctuation during dynamic load-changing process.

关键词： Load modeling Predictive models Valves Optimization Turbines Data models Reflection

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The Numerical Simulation and Experimental Research on Combustion Process in 660MW Boiler

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IOP Conference Series: Earth and Environmental Science 2020年第1期526卷

作者： Lei Yu Hui Tian Zhen Chang School of Control and Computer Engineering North China Electric Power University Beijing 102206 China Patent Examination Cooperation Sichuan Center of the Patent Office Chengdu 610000 China

In order to solve the problems of thermal insulation and ash prevention of the furnace combustion layer temperature detection devices installed on the boiler furnace, FLUENT software is used to numerically simulate the actual combustion process in the furnace of 660 MW power plant boiler, and the combustion status of each layer in the furnace is analyzed and studied. And then, according to the results of data simulation the thermal insulation and ash prevention technology implementation of the furnace combustion temperature detection devices is guided. The installation operation test results show that the furnace combustion temperature detection devices work within the range of instrument allowed −20°C~85°C temperature, which can obtain the direct, rapid, real-time furnace combustion temperature data that provides a valuable source of data for further optimization control of boiler combustion process.

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Solar Photovoltaic Power Prediction Based on Similar Day Approach 36

Solar Photovoltaic Power Prediction Based on Similar Day App...

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第36届中国控制会议

作者： Xu Zhang Bo Jiang Xiaoning Zhang Fang Fang Zhengping Gao Tao Feng The School of Control and Computer Engineering North China Electric Power University

ISBN: (纸本)9781538629185

The output power of photovoltaic(PV) power generation system is related to solar irradiance,temperature,humidity and other meteorological *** output powers in the similar days,which are much alike in meteorological conditions and social activities,will be more likely *** this paper,a prediction algorithm combining the time series and similar day is proposed to predict the power output of a PV *** this algorithm,the meteorological conditions of target days are predicted by the time series analysis,and the subjective weight and the entropy weight method are used to select the similar *** that,the target day's power output will be forecasted by tuning the weights of similar days' power *** on the actual data collected from an experimental system,the accuracy of prediction method is verified.

关键词： Photovoltaic(PV) power prediction similar days time series analysis

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