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2019 6th International Conference on Advanced Composite Materials and Manufacturing Engineering, ACMME 2019

作者： Xiong, Xin Huang, Li Tian, Jinrong Infrastructure and Logistics Management Wuhan University of Science and Technology Wuhan Hubei430081 China College of Computer Science and Technology Wuhan University of Science and Technology Wuhan Hubei430081 China Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan University of Science and Technology Wuhan Hubei430081 China Key Laboratory of Metallurgical Equipment and Control Technology Ministry of Education Wuhan University of Science and Technology Wuhan Hubei430081 China

The phenomenon of cracks on the surface of buildings is widespread. The existence of cracks affects the normal use of buildings, shortening the service life, seriously damaging the structure of buildings, resulting in safety accidents. Therefore, regular detection and reinforcement of cracks on the surface of buildings is a necessary link to ensure safety. At present, the detection of building surface cracks is mainly carried out by manpower with means of equipment assisted. However, there are some problems in manpower detection, such as high manpower consumption, low *** paper presents a method of detecting and inspecting cracks on building surface based on image processing technology in machine vision, which includes image gray transformation, image denoising etc. Curve fitting and least square method are used to obtain crack parameters, so as to improve the inspecting efficiency and realize the automation of building surface inspection. © Published under licence by IOP Publishing Ltd.

关键词： Curve fitting

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Evaluation and application of shallow buried tunnel construction safety based on combined empowerment-multidimensional cloud model

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IOP Conference Series: Earth and Environmental Science 2021年第1期791卷

作者： Shang Liu Jie Song Run Xu Changyong Zhang Guoqiang Zhong Chao Wang Shandong Provincial Communications Planning and Design Institute Group Co. LTD Shandong Jinan China Shandong Province highway traffic safety big data engineering laboratory Shandong Jinan China Key Laboratory of tunnel information construction and intelligent control transportation industry Shandong Jinan China

In order to study the influence of various factors on the construction safety of shallow buried tunnels, a multifactor evaluation model consisting of 9 indicators, such as tunnel size, the buried depth, surrounding rock condition and construction management, is established from the perspective of '4M1E' by combining the characteristics of shallow buried tunnel construction by borehole-blasting method. It combines the advantages of subjective weighting method AHP and objective weighting method CRITIC, and determines the comprehensive weight values through the combined weighting method, which is used to improve the weight assignment of multi-dimensional normal cloud model, and evaluates the stability of the surrounding rock at the entrance and exit of the shallow buried tunnel based on the concepts of expectation, entropy and super entropy of the cloud model. And then it accurately obtains the construction safety of the entrance and exit of the shallow buried tunnel, and the evaluation results have scientific guidance for the control of construction risks.

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Privacy-preserving medical treatment system through nondeterministic finite automata

arXiv

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arXiv 2020年

作者： Yang, Yang Deng, Robert H. Liu, Ximeng Wu, Yongdong Weng, Jian Zheng, Xianghan Rong, Chunming School of Information Systems Singapore Management University Singapore College of Mathematics and Computer Science Fuzhou University Fujian China State Key Laboratory of Integrated Services Networks Xidian University Guangdong Provincial Key Laboratory of Data Security and Privacy Protection Guangzhou China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Minjiang University Fuzhou China School of Information Systems Singapore Management University Singapore Singapore Department of Computer Science Jinan University Guangdong China College of Mathematics and Computer Science Fuzhou University Fujian China Department of Electronic Engineering and Computer Science University of Stavanger Norway MingByte Technology Qingdao China

In this paper, we propose a privacy-preserving medical treatment system using nondeterministic finite automata (NFA), hereafter referred to as P-Med, designed for the remote medical environment. P-Med makes use of the nondeterministic transition characteristic of NFA to flexibly represent the medical model, which includes illness states, treatment methods and state transitions caused by exerting different treatment methods. A medical model is encrypted and outsourced to the cloud to deliver telemedicine services. Using P-Med, patient-centric diagnosis and treatment can be made on-the-fly while protecting the confidentiality of a patient's illness states and treatment recommendation results. Moreover, a new privacy-preserving NFA evaluation method is given in P-Med to get a confidential match result for the evaluation of an encrypted NFA and an encrypted data set, which avoids the cumbersome inner state transition determination. We demonstrate that P-Med realizes treatment procedure recommendation without privacy leakage to unauthorized parties. We conduct extensive experiments and analyses to evaluate efficiency. Copyright © 2020, The Authors. All rights reserved.

关键词： Diseases

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Multi-view ontology alignment visualization (MOAV): A human-cognition based ontology alignment visualization technique

Journal of Network Intelligence

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Journal of Network Intelligence 2020年第4期5卷 198-210页

作者： Chen, Jie Zhang, Jie Xue, Xingsi Huang, Yikun Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of Technology No.33 Xueyuan Road University Town Minhou FuzhouFujian350118 China School of Computer Science and Engineering Yulin Normal University No.299 Education Middle Road Yulin CityGuanxi Province537000 China Fujian Provincial Key Laboratory of Big Data Mining and Applications Intelligent Information Processing Research Center Fujian University of Technology No.33 Xueyuan Road University Town Minhou FuzhouFujian350118 China Guangxi Key Laboratory of Automatic Detecting Technology and Instruments Guilin University of Electronic Technology No.1 Jinji Road Guangxi Guilin541004 China Department of Information Technology Concord University College Fujian Normal University No.68 Xueyuan Road University Town Minhou FuzhouFujian350117 China

To further improve the quality of ontology alignment, it is necessary for an ontology matcher to introduce a user’s knowledge into its automatic matching process, which yields the development of interactive ontology matching techniques. Since validating problematic entity correspondences is a difficult cognition task, user interaction based on Ontology Alignment Visualization (OAV) has become the critical component of an interactive ontology matcher, which directly affects the quality of validating result and the efficiency of validating process. The existing OAV tools are mainly developed based on their designers’ subjective feelings and experiences, which do not take into consideration the law of human cognition. To improve the efficiency of the ontology alignment validating process, in this paper, a Multi-view OAV (MOAV) is proposed, which synthetically utilizes the human cognitive theory-information visualization and human-computer inter-action. The experiment utilizes the Ontology Alignment Evaluation Initiative (OAEI)’s benchmark to test the performance of our proposal, and the experimental results show that MOAV can effectively improve a user’s validating efficiency. © 2020, Taiwan Ubiquitous information. All rights reserved.

关键词： Visualization

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Research on Saturation of PMSM System Regulator for Electric Vehicle

Research on Saturation of PMSM System Regulator for Electric...

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Chinese Automation Congress (CAC)

作者： Shengmin Li Zeling Zhang Dan Zhao Siyu Guo Key Laboratory of Shaanxi Province for Complex System Control and Intelligent Information Processing Xi'an China

The saturation phenomenon often happens to the regulator in the start-up procedure of electric vehicles. And the dynamic and static performance of the motor will be worse while this phenomenon lasts longer. In this paper, firstly we will analyze the causes of this phenomenon, and then propose an effective method to solve the regulator saturation. Based on traditional double-loop vector control, this method increased the voltage cut-off negative feedback and combined the state feedback linearization to realize the dynamic decoupling between currents and solve the current regulator saturation problem which happens during start-up procedure. Finally, the feasibility and effectiveness of the proposed method were verified by simulation experiments, and the comprehensive performance of the motor, including speed range, speed tracking performance and dynamic response, was improved.

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Weighted Feature Pyramid Networks for Object Detection

Weighted Feature Pyramid Networks for Object Detection

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IEEE International Conference on Big data and Cloud Computing (BdCloud)

作者： Xiaohan Li Taotao Lai Shuaiyu Wang Quan Chen Changcai Yang Riqing Chen Jinxun Lin Fu Zheng Digital Fujian Institute of Big Data for Agriculture and Forestry College of Computer and information Sciences Fujian Agriculture and Forestry University Fuzhou China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control College of Computer and Control Engineering Minjiang University Fuzhou China Fu Jian Shu Bo Xun Information Technology Co. Ltd

ISBN: (数字)9781728143286

ISBN: (纸本)9781728143293

Feature Pyramid Networks (FPN) is a popular feature extraction. However, FPN and its variants do not investigate the influence of resolution information and semantic information in the object detection. Thus, FPN and its variants cannot detect some objects on challenging images. In this paper, based on FPN, we propose to use gaussian kernel function to assign different weight values to semantic information and resolution information for different images in the object detection. The proposed method, is called a Weighted Feature Pyramid Network (WFPN), and shows significant improvement over the traditional feature pyramids in several applications. Using WFPN in Faster R-CNN system, the proposed method achieves better performance on the PASCAL detection benchmark.

关键词： Feature extraction Kernel Object detection Agriculture Forestry Semantics Big data

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Model Identification and Internal Model control for 3D Printer

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IOP Conference Series: Materials Science and Engineering 2020年第1期740卷

作者： Ruidong Xie Yingmin Yi Haichuan Yang Key Lab of Manufacturing Equipment of Shaanxi Province Xi'an University of Technology Xi'an 710048 China Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of Technology Xi'an 710048 China

A 3D printer system for selective laser sintering technology is used to establish a mathematical model of the relationship between laser power and temperature by using the recursive least squares method. Based on this model, the internal model control method is used to design the controller to realize the actual 3D printer. Temperature control, simulation analysis of internal model control and traditional PID control effects. The experimental results show that the feasibility, accuracy and internal model control of the recursive least squares identification model are fast, easy to implement, robust, and only one adjustable parameter, easy to adjust.

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The estimation of the laser point temperature based on CNN (Convolutional Neural Network)

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IOP Conference Series: Materials Science and Engineering 2020年第1期740卷

作者： Yingmin Yi Ruidong Xie Haichuan Yang Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of Technology Xi'an 710048 China Key Lab of Manufacturing Equipment of Shaanxi Province Xi'an University of Technology Xi'an 710048 China

For the requirements of the laser temperature in additive manufacturing, there is a high precision and high heat need in the industry. The method is proposed to estimate the temperature of laser point, which is based on CNN. In this method, a model of CNN is carried out. The collected laser thermal radiation images are used to train the model. Image recognition and isotherm estimation can be obtained by the trained model. The conclusion can be verified by the experiment. The isotherm and temperature of the laser can be measured efficiently in this method.

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A Power Optimization control Method Based on IMC for 3D Printer

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Journal of Physics: Conference Series 2020年第1期1654卷

作者： Ruidong Xie Haichuan Yang Yingmin Yi Key Lab of Manufacturing Equipment of Shaanxi Province Xi'an University of Technology Xi'an 710048 China Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of Technology Xi'an 710048 China

Aiming at the effect of selective laser sintering technology used in 3D printing, the recursive least squares method was applied to fitting a control system model for quantification the relationship between laser power and corresponding temperature in this paper. The internal model control method is considered based on the establishing model. The controller is put into the actual 3D printing power control system for controlling the laser power. In the experiment, both internal model controller and the PID controller for the 3D printer are researched and deployed for comparing the their effects in the paper. The experimental result illustrates that the IMC based on the recursive least squares method is of effectiveness.

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A Detection and Identification Method Based on CNN for Laser Point Thermal Radiation

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Journal of Physics: Conference Series 2020年第1期1654卷

作者： Haichuan Yang Ruidong Xie Yingmin Yi Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of Technology Xi'an 710048 China Key Lab of Manufacturing Equipment of Shaanxi Province Xi'an University of Technology Xi'an 710048 China

Aiming at the high demands of temperature and precision in the aspect of additive manufacturing, a method based on CNN was proposed for estimating measurement. The network was trained through the collected laser thermal radiation images for image recognition and isotherm estimation after modeling a CNN. The experimental conclusion verifies that the isotherm detection and temperature estimation of the laser point can be efficiently implemented in proposed method.

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