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IAENG International Journal of Computer Science 2021年第2期48卷 1-8页

作者： Zheng, Qingchun Zhang, Zhidong Liu, Jingna Zhu, Peihao Ma, Wenpeng Professor in the Key Laboratory of Advanced Mechatronic System Design and Intelligent Control Tianjin University of Technology Tianjin300384 China Postgraduate student in the Key Laboratory of Advanced Mechatronic System Design and Intelligent Control Tianjin University of Technology Tianjin300384 China A Lecturer in the Key Laboratory of Advanced Mechatronic System Design and Intelligent Control Tianjin University of Technology Tianjin300384 China An Assistant Professor in the Key Laboratory of Advanced Mechatronic System Design and Intelligent Control Tianjin University of Technology Tianjin300384 China

The dust removal technology of welding seam image has important practical significance for promoting the development of weld instance segmentation and target tracking. In this paper, we propose a welding seam image dust removal algorithm based on fusion of dual-scale dark channel and bright channel, which is to solve the problem that the color distortion and halo effect of dark channel prior image restoration algorithm in weld depth of field sudden change area and bright region. Firstly, the results of the minimum filtering of two scale windows are adaptively weighted and fused to obtain the fused dark channel. Secondly, the dark channel prior and the bright channel prior fusion strategy is adopted to obtain the fused atmospheric light to make the rough transmittance estimation more accurate. Finally, the weighted guided filtering is combined with up-sampling and down-sampling to optimize the rough transmittance, and the weld image is restored by combining the atmospheric scattering model. The experimental results indicate that our algorithm can restore the color and edge details of welding seam images and effectively suppress the halo effect. The objective comparison with several typical algorithms proves the feasibility and superiority of the proposed algorithm. © 2021. All Rights Reserved.

关键词： Image reconstruction

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Research on vision detection technology based on photometric calibration

Research on vision detection technology based on photometric...

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2021 IEEE International Conference on Computer Science, Electronic Information Engineering and intelligent Control Technology, CEI 2021

作者： Sun, Guoqing Zhou, Haibo Li, Chenming Zhao, Yijiao Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control Tianjin300384 China National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Tianjin300384 China

ISBN: (纸本)9780738146492

The camera is affected by illumination changes and vignetting effect during the shooting process, resulting in the lack of brightness information, which affects the accuracy of target detection. In order to reduce the impact of illumination changes and vignetting effect on image quality, obtain images closer to the real scene, and improve the accuracy of target detection, this paper conducts photometric calibration on the image from two aspects: the calibration of CRF (Camera Response Function) and the compensation function of vignetting effect. This paper first uses the N-degree polynomial model to construct the camera response function, proposes a functional model of vignetting compensation based on the position of the pixel point, and finally combines the first two experimental results and conducts experimental verification on the data set before and after the photometric calibration on different algorithms of target detection. The experimental results show that the application of photometric calibration in the field of machine vision can improve the adaptability of machine vision to illumination changes and vignetting effect to a certain extent. The self-made data set is trained and tested, when IoU is 0.7, the mAP calculated by the test set after photometric calibration is improved by 2.3% compared with the original data set. © 2021 IEEE.

关键词： Computer vision

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Wireless Acoustic Sensor Networks and Edge computing for Rapid Acoustic Monitoring

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IEEE/CAA Journal of Automatica Sinica 2019年第1期6卷 64-74页

作者： Zhengguo Sheng Saskia Pfersich Alice Eldridge Jianshan Zhou Daxin Tian Victor C.M.Leung the Department of Engineering and Design University of Sussex Infineon Technologies AG the Department of Music University of Sussex Beijing Advanced Innovation Center for Big Data and Brain Computing (BDBC) Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems & Safety ControlSchool of Transportation Science and EngineeringBeihang University the Department of Electrical and Computer Engineering The University of British Columbia

Passive acoustic monitoring is emerging as a promising solution to the urgent, global need for new biodiversity assessment methods. The ecological relevance of the soundscape is increasingly recognised, and the affordability of robust hardware for remote audio recording is stimulating international interest in the potential for acoustic methods for biodiversity *** scale of the data involved requires automated methods,however, the development of acoustic sensor networks capable of sampling the soundscape across time and space and relaying the data to an accessible storage location remains a significant technical challenge, with power management at its core. Recording and transmitting large quantities of audio data is power intensive,hampering long-term deployment in remote, off-grid locations of key ecological interest. Rather than transmitting heavy audio data, in this paper, we propose a low-cost and energy efficient wireless acoustic sensor network integrated with edge computing structure for remote acoustic monitoring and in situ *** and computation of acoustic indices are carried out directly on edge devices built from low noise primo condenser microphones and Teensy microcontrollers, using internal FFT hardware support. Resultant indices are transmitted over a ZigBee-based wireless mesh network to a destination *** tests of audio quality, indices computation and power consumption demonstrate acoustic equivalence and significant power savings over current solutions.

关键词： Acoustic sensor networks edge computing energy efficiency

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Multi-view Weighted Kernel Fuzzy Clustering Algorithm Based on the Collaboration of Visible and Hidden Views 15th

Multi-view Weighted Kernel Fuzzy Clustering Algorithm Based ...

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15th CCF Conference on Computer Supported Cooperative Work and Social computing, Chinese CSCW 2020

作者： Tang, Yiming Xia, Bowen Ren, Fuji Song, Xiaocheng Li, Hongmang Wu, Wenbin Anhui Province Key Laboratory of Affective Computing and Advanced Intelligent Machine Hefei University of Technology Hefei230601 China School of Computer and Information Hefei University of Technology Hefei230601 China

ISBN: (纸本)9789811625398

With the development of media technology, data types that cluster analysis needs to face become more and more complicated. One of the more typical problems is the clustering of multi-view data sets. Existing clustering methods are difficult to handle such data well. To remedy this deficiency, a multi-view weighted kernel fuzzy clustering method with collaborative evident and concealed views (MV-Co-KFCM) is put forward. To begin with, the hidden shared information is extracted from several different views of the data set by means of non-negative matrix factorization, then applied to this iterative process of clustering. This not only takes advantage of the difference information in distinct views, but also utilizes the consistency knowledge in distinct views. This pre-processing algorithm of extracting hidden information from multiple views (EHI-MV) is obtained. Furthermore, in order to coordinate different views during the iteration, a weight is distributed. In addition, so as to regulate the weight adaptively, shannon entropy regularization term is also introduced. Entropy can be maximized as far as possible by minimizing the objective function, thus MV-Co-KFCM algorithm is proposed. Facing 5 multi-view databases and comparing with 6 current leading algorithms, it is found that the algorithm which we put forward is more excellent as for 5 clustering validity indexes. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Fuzzy clustering

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EKIGCN: External Knowledge Injected Graph Convolutional Networks for Aspect-based Sentiment Analysis 9

EKIGCN: External Knowledge Injected Graph Convolutional Netw...

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9th IEEE International Conference on Cloud computing and Intelligence Systems, CCIS 2023

作者： Shi, Xuefeng Hu, Min Ren, Fuji Shi, Piao Hefei University of Technology Anhui Province Key Laboratory of Affective Computing and Advanced Intelligent Machine Hefei230000 China University of Electronic Science and Technology of China Sichuan Chengdu611731 China

ISBN: (纸本)9798350304428

Aspect-based sentiment analysis (ABSA) is a challenging subtask in the natural language processing community, which aims to determine the sentiment polarity about the corresponding specific aspect terms. In existing works, external knowledge has been proven effective to improve the ABSA tasks' performance. However, it is still essential to study further to find a universal method for ABSA tasks. Therefore, we propose an external knowledge-injected graph convolutional network (EKIGCN) to enhance the sentiment representation with commonsense. Specifically, Sentic Net is leveraged to provide external knowledge to construct an affective dependency graph. In order to fully exploit the effectiveness of affective knowledge, a shallow mutual interaction is utilized to fuse the learned contextual representation and the graph. Besides, to make EKIGCN sensitive to aspect terms, an aspect-aware multi-head attention module is also employed to enhance the corresponding relations between aspect and contextual words. Extensive experiments are conducted on three popular datasets to validate the effectiveness of our proposed model, and the results outperform the mentioned state-of-the-art methods in ABSA tasks. © 2023 IEEE.

关键词： Sentiment analysis

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Neural network for heterogeneous annotations

Neural network for heterogeneous annotations

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2016 Conference on Empirical Methods in Natural Language Processing, EMNLP 2016

作者： Chen, Hongshen Zhang, Yue Liu, Qun Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences China University of Chinese Academy of Sciences China Singapore University of Technology and Design Singapore ADAPT Centre School of Computing Dublin City University Ireland

ISBN: (纸本)9781945626258

Multiple treebanks annotated under heterogeneous standards give rise to the research question of best utilizing multiple resources for improving statistical models. Prior research has focused on discrete models, leveraging stacking and multi-view learning to address the problem. In this paper, we empirically investigate heterogeneous annotations using neural network models, building a neural network counterpart to discrete stacking and multi-view learning, respectively, finding that neural models have their unique advantages thanks to the freedom from manual feature engineering. Neural model achieves not only better accuracy improvements, but also an order of magnitude faster speed compared to its discrete baseline, adding little time cost compared to a neural model trained on a single treebank. © 2016 Association for Computational Linguistics

关键词： Forestry

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A micro-genetic algorithm for DNA encoding sequences design

A micro-genetic algorithm for DNA encoding sequences design

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IEEE International Conference on Control Science and Systems Engineering (CCSSE)

作者： Xinmei Peng Xuedong Zheng Bin Wang Changjun Zhou Qiang Zhang Key Laboratory of Advanced Design and Intelligent Computing Ministry of Education Dalian University Dalian P. R. China

ISBN: (纸本)9781467398732

Aiming at DNA encoding sequences design, a micro-genetic algorithm (MGA) is proposed by introducing a sharing function based on similarity and H-measure of DNA sequences. In the algorithm, six design criteria are adopted and four genetic operators are applied. Compared with the previous results, the algorithm can get better DNA sequences and improve the computational efficiency.

关键词： DNA Encoding Algorithm design and analysis Sociology Statistics DNA computing

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Research on Three Main Lightweight Approaches for Automotive Body Engineering Considering Materials, Structural Performances and Costs

Research on Three Main Lightweight Approaches for Automotive...

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SAE 2015 World Congress and Exhibition

作者： Lei, Fei Chen, Xin Xie, Xiao Ping Zhu, Jing State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body Joint Center for Intelligent New Energy Vehicle College of Mechanical and Vehicle Engineering Hunan University Changsha410082 China

Lightweight automotive body can be obtained by developing new body constructions, using lightweight materials and structural optimizations, etc. Usually, lighter materials and structural optimizations are main aspects considered in lightweight automotive body engineering. In fact, material costs and manufacturability play more important roles than others in lightweight design. Three lightweight design approaches are considered. The first approach of lightweight design is to replace steels with lighter materials using equal rigidity design method. The second approach is a single objective optimization of mass reduction with materials selection and cost penalty. The third approach is a multi-objective optimization of mass reduction and cost reduction using multi-material concept. These three approaches are applied to an automotive body design problem considering the side impact. Different optimization methods are used to obtain different results. design aspects, such as sizes of components, types of materials and costs can be optimized. Type of lightweight optimization is then a choice of manufacturer's concern. Copyright © 2015 SAE International.

关键词： Cost engineering

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Optimization design of Close-top Mill Housing Based on Agent Model and NSGA-Ⅱ Algorithm

Optimization design of Close-top Mill Housing Based on Agent...

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2015 5th International Conference on Information Engineering for Mechanics and Materials(ICIMM 2015)

作者： Yanjun Shi Xianchao Wang Xiaojun Zheng School of Mechanical Engineering Dalian University of Technology Key Laboratory of Advanced Design and Intelligent Computing Ministry of Education of Dalian University

Conventional engineering optimization design technology is often computational expense and highly time cost, thus we need to take approximation technique to speed up the design process and reduce design cost. We herein would introduce the close-top mill housing optimization model, take Optimal Latin Hypercube Sampling（OLHS） experimental design strategies to determine the sample, analyse the difference among EBF, RBF, Kriging surrogate model, introduce NSGA-II algorithm briefly and study the performance of method based on surrogate model and optimization algorithm.

关键词： EBF-NN RBF-NN Kriging NSGA-II Mill housing Surrogate models

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design and Implementation of Ideological and Political Education Evaluation System

Design and Implementation of Ideological and Political Educa...

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2018计算机科学与工程技术国际研讨会

作者： Zhenyuan Lv Changjun Zhou Chunye Zhou Key Laboratory of Advanced Design and Intelligent Computing (Dalian University) Ministry of Education School of Politics and Law Shangrao Normal University

With the development of informatization, in order to improve office efficiency and manage students more effectively, universities have produced many management systems, such as library management systems and educational management systems. These systems mostly manage student information and other information in an integrated manner. The refinement of each module, due to the large number of colleges and universities, graduates and enrolls a large number of students every year, and the archiving of students' ideological and political courses and students' ideological and political evaluation is quite complicated. Some college management systems may only provide ideological and political courses. Course information and student test scores did not specifically manage the student's ideological and political education assessment and assess the student's psychological activities based on the student's daily performance, nor did they provide detailed course scheduling information for specific ideological and political related courses. Therefore, colleges and universities should also implement detailed information management for students' ideological and political education methods, which can improve management efficiency and reduce unnecessary human resources. The management system is developed by the Java[1-3]development language through Myeclipise as a development tool. The mysql database is used as the background to realize the information management of the ideological and political education of college students. It can promote the detailed management of all aspects of students' information management. Service school as well as students. And the machine learning algorithm is added. Through the previous students' data, the classification model is trained by Logistic regression algorithm to evaluate the students' ideological and political good condition.

关键词： design and Implementation of Ideological and Political Education Evaluation System

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