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2018 International Conference on Modeling, Simulation and Analysis(ICMSA 2018)

作者： Xing-long XIONG Feng-tian XU Zi-bo ZHUANG Xing CHEN Civil Aviation Meteorological Technology Research Institute Tianjin Key Laboratory of Intelligent Signal and Image Processing Civil Aviation University of China

Lanzhou Zhongchuan Airport is one of the Northwest's largest aviation hubs,and it is greatly affected by the wind *** to the low-lying terrain of the airport and the terraced terrain,the wind field around the airport is closely related to its *** paper set up the digital elevation model of the terrain near the runway with an area of 6 KM*6 KM*2 KM,and wind field numerical simulation is solved by Fluent *** wind speed and pressure distribution characteristics of the simulated wind field are obtained by iterative *** the method of horizontal plane at mountain area,the local influence of topographic factors on the wind field is *** results show that when the wind flows through the surrounding mountain area,due to the ups and downs of the mountain,the wind speed has a big difference in different height layers,and it is easy to cause crosswind shear,which has an impact on the flight *** results have important reference value for the research and low-level wind shear forming factors of wind field caused by complex terrain,and it is of great significance to deeply understand the mechanism of wind shear.

关键词： Numerical simulation Complex terrain Wind shear Fluent

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The Design of Multi-mode Examinees Identity Verification System for Colleges and Universities

The Design of Multi-mode Examinees Identity Verification Sys...

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2018 International Conference on Computer Modeling, Simulation and Algorithm（CMSA2018）

作者： Jia Chen Cong Chen Guangxi Colleges and Universities Key Laboratory of Image Processing and Intelligent Information System Wuzhou University Guangxi Colleges and Universities Key Laboratory of Professional Software Technology Wuzhou University

With the rapid development of information management in colleges and universities, traditional eyeobserving verification methods cannot satisfy today's requirement for examination management any more. Examinees' identities need to be verified more effectively and accurately. In recent years, biometric recognition has been becoming an essential component of effective person identification solutions because biometric identifiers intrinsically represent individuals' bodily identity. In this paper, we present a multi-mode verification system that not only takes advantage of biometric recognition to improve efficiency and accuracy, but also incorporates eye-observing verification to deal with the case when biometric recognition fails. Accordingly, an original portable verification device was designed to implement this multi-mode verification system. Our experiment shows that this verification system can meet the practical requirement of examination management in colleges and universities.

关键词： identity verification multi-mode verification comprehensive judgment original verification device

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Attention to refine through multi-scales for semantic segmentation

arXiv

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arXiv 2018年

作者： Yang, Shiqi Peng, Gang Key Laboratory of Ministry of Education for Image Processing and Intelligence Control School of Automation Huazhong University of Science and Technology Wuhan China

This paper proposes a novel attention model for semantic segmentation, which aggregates multi-scale and context features to refine prediction. Specifically, the skeleton convolutional neural network framework takes in multiple different scales inputs, by which means the CNN can get representations in different scales. The proposed attention model will handle the features from different scale streams respectively and integrate them. Then location attention branch of the model learns to softly weight the multi-scale features at each pixel location. More- over, we add an recalibrating branch, parallel to where location attention comes out, to recalibrate the score map per class. We achieve quite com- petitive results on PASCAL VOC 2012 and ADE20K datasets, which surpass baseline and related works. Copyright © 2018, The Authors. All rights reserved.

关键词： Semantic Segmentation

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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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Correction to: A method of VR‑EEG scene cognitive rehabilitation training

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Health information science and systems 2021年第1期9卷 7页

作者： Wenjun Tan Yang Xu Pan Liu Chunyan Liu Yujin Li Yanrui Du Chao Chen Yuping Wang Yanchun Zhang Key Laboratory of Intelligent Computing in Medical Image Ministry of Education Northeastern University Shenyang 110189 China. Cyberspace Institute of Advanced Technology Guangzhou University Guangzhou 510006 China. Department of Neurology Xuanwu Hospital Capital Medical University Beijing 100053 China. Key Laboratory of Complex System Control Theory and Application Tianjin University of Technology Tianjin 300384 China. Institute for Sustainable Industries and Liveable Cities Victoria University Melbourne VIC 8001 Australia.

[This corrects the article DOI: 10.1007/s13755-020-00132-6.].

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Proximity Effect Aware Detailed Placement in Electron Beam Lithography 2

Proximity Effect Aware Detailed Placement in Electron Beam L...

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2nd International Conference on Electronic Information Technology and Computer Engineering, EITCE 2018

作者： Chen, Yuhang Huang, Zhipeng Chen, Xiongfeng Chen, Jianli Zhu, Wenxing College of Mathematics and Computer Science Fuzhou University Fuzhou350108 China Center for Discrete Mathematics and Theoretical Computer Science Fuzhou University Fuzhou350108 China Fujian Key Laboratory of Information Processing and Intelligent Control Minjiang University Fuzhou350108 China

Proximity effect is one of the most tremendous consequences that produces unacceptable exposures during electron beam lithography (EBL), and thus distorting the layout pattern. In this paper, we propose the first work which considers the proximity effect during layout stage. We first give an accurate evaluation scheme to estimate the proximity effect by fast Gauss transform. Then, we devote a proximity effect aware detailed placement objective function to simultaneously consider wirelength, density and proximity effect. Furthermore, cell swapping and cell matching based methods are used to optimize the objective function such that there is no overlap among cells. Compared with a state-of-the-art work, experimental result shows that our algorithm can efficiently reduce the proximity variations and maintain high wirelength quality at a reasonable runtime. © The Authors, published by EDP Sciences, 2018.

关键词： Electron beam lithography

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A video coloring method based on CNN and feature point tracking 1st

A video coloring method based on CNN and feature point track...

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1st International Conference on Smart Vehicular Technology, Transportation, Communication and Applications, VTCA 2017

作者： Guan, George Zhang, Fuquan Ding, Gangyi Niu, Meng Xu, Lin School of Software Beijing Institute of Technology Beijing100081 China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Minjiang University Fuzhou350121 China Innovative Information Industry Research Institute Fujian Normal University Fuzhou350300 China

ISBN: (纸本)9783319707297

Black and white films were the main form of human culture records before. Colorization of those films is creative. At present, Colorization of black and white films is still handmade which is expensive and time consuming. In this paper, a framework based on CNN and particle filter tracking algorithm is proposed, which can color black and white video and try to solve the problem of dynamic frame based on context correlation. At the same time, the objective function of CNN structure and particle filter tracking are optimized. The result of colorization on videos is satisfactory. © Springer International Publishing AG 2018.

关键词： Monte Carlo methods

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Identification and Prediction of key Nucleotide Sites Using Machine Learning in Bioinformatics: A Brief Overview

Identification and Prediction of Key Nucleotide Sites Using ...

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

作者： Jianhua Cai Leyi Wei Kun Zeng Guobao Xiao Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Minjiang University Fuzhou P.R. China College of Mathematics and Computer Science Fuzhou University Fuzhou P.R. China College of Intelligence and Computing Tianjin University Tianjin P.R. China

ISBN: (数字)9781728143286

ISBN: (纸本)9781728143293

Nowadays, the burgeon of machine learning has promoted its wide application in various fields. In Bioinformatics, machine learning computational method has become an indispensable part. Its efficiency and simplicity break the expensive and inefficient barriers of previous experimental methods. This article briefly reviews the application and development of machine learning in identifying and predicting key nucleotide sites (such as 6mA, 5mC, 4mC, etc.) in DNA or RNA. Among them, supervised learning is one of the main methods to this work. Its wide application has provided great convenience for the development of identification and prediction of key nucleotides in Bioinformatics.

关键词： Bioinformatics Feature extraction Machine learning Predictive models Computational modeling DNA Prediction algorithms

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A multi-objective particle swarm optimization for multiple knapsack problem with strong constraints

A multi-objective particle swarm optimization for multiple k...

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IEEE Conference on Industrial Electronics and Applications (ICIEA)

作者： Xuan Ma Ying Yan Qing Liu Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of Technology Xi'an City China

Aiming at the characteristics of strong constraints of multiple knapsack problem (MKP), a method based on multi-objective particle swarm optimization is proposed in this paper. We take constraint violation as an optimal objective to avoid the troublesome of dealing with unfeasible solutions unsatisfied constraints. For updating effectively the external archive, the degree of constraint violation and the crowding degree of non-dominated particle in Pareto front are taken as two criteria. To decrease the probability of algorithm converging to a pseudo Pareto front, a mutation operator is designed. The experimental results of solving a number of MKP instances demonstrate that the proposed algorithm performs better to the MKP instances with strong constraints.

关键词： Optimization Sociology Statistics Particle swarm optimization Heuristic algorithms Complex systems control systems

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Modeling and simulation of MHD melt convection and heat transfer in CZ crystal growth

Modeling and simulation of MHD melt convection and heat tran...

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Chinese Automation Congress

作者： Ni Zhang Ding Liu Weichao Huang National and Local Joint Engineering Shaanxi key Laboratory of Complex System Control and Intelligent Information Processing Xi'an China

This paper presents an axisymmetric swirl incompressible thermal lattice Boltzmann model to study the magnetohydrodynamics (MHD) melt flow and heat transfer at high Grashof number and high Reynolds number under external magnetic field in Czochralski (CZ) crystal growth process. The model is built based on the double distribution function lattice Boltzmann equation (DDF-LBE) and is verified by benchmark problem. By using the proposed model, the evolution relationship of melt flow, temperature is constructed under the combined effects of Lorenz force, rotating inertia force and thermal buoyancy force. Furthermore, the flow patterns and the temperature distribution of silicon melt under different magnetic field strengths are simulated. The simulation results show that with the increase of magnetic field strength, the melt velocity is reduced, which suppresses the melt convection and is beneficial for suppressing the fluctuation of melt. And the temperature gradient below the crystal growth interface increases in the case of crystal rotation, which is helpful to increase the crystallization rate. The combination of Cusp magnetic field, crucible rotation and crystal rotation can be used as an effective method in the production of high-quality crystal.

关键词： Modeling Computer simulation Crystal growth Lattice boltzmann method

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