Application of Improved Differential Evolution Algorithm in solving Container-packing problems

e-mail: yyxx207@163.com

Abstract—Blade is one of the most important components in devices such as generating equipments, aircraft engines and turbines. Its surface quality has important influence on the overall performance and working reliability of these devices. In this work, an automatic belt grinding system is designed to satisfy the growing demand for finish machining of blade with high-quality and high-efficiency. The belt grinding process of blade is firstly discussed and then, a self-adapting hybrid belt grinding machine tool is designed and analyzed. After that, grinding path on the blade is planned and motions of this machine tool when grinding the blade are calculated. At last, virtual prototype of this machine tool is built and the machining process when grinding blade is visualized. Simulation results indicate that the designed belt grinding system has very good performance when following complex surface and can be used in machining blade with complex surface.*

Keywords-turbine blade; belt grinding; free form surface; machine tool; grinding process

Sheave Wheel Stress Wireless Monitoring System Research of Mine Hoist

Wang Ying, Zhu Zhencai, Chen Guangzhu, Li Wei, Wang Zhongqiu

College of Mechanical and Electrical Engineering

China University of Mining and Technology

Xuzhou, China

ying.wang.paopao@gmail.com

Abstract—The fatal accidents of mine hoist, such as cage jam and rope slack, can’t be prevented effectively at present. In this paper, we propose a stress wireless monitoring system based on ZigBee communication technology in order to monitor the mine hoist by measuring the sheave wheel stress. First, we design. The system includes two parts: the data collector and controller, which monitor and transmit the real-time stress data to the computer; and the computer, which can realize the functions of data display, storage, analysis and output. The system is tested in Wangzhuang coal mine, Xuzhou, China. The validity and reliability of the system are proved. The system can be used as the data source of mine hoist’s fault diagnosis.

Keywords-sheave wheel; stress; monitoring system; mine hoist; fault diagnosis

Flight Control System of a Robotic Portable Unmanned Aerial Vehicle

Jinjun Rao, Tongyue Gao, Zhen Jiang and Zhenbang Gong

Department of Precision Mechanical Engineering

Shanghai University

Shanghai, China

jjrao, gty, zhjiang, zhbgong @shu.edu.cn

Abstract—Portable fixed-wing Unmanned Aerial Vehicles (PUAV) present enormous potential. In order to develop a robotic PUAV with significant levels of autonomy, the flight control system is studied. The platform is introduced and dynamics model is studied firstly. Then the infrastructure hardware and the architecture of the flight control system are detailed. As the core of the flight control system, the attitude controller using variable fuzzy controller is investigated, and a bilinear interpolation approach is presented to realize quick inference with low computation cost of the embedded micro processor. The flight simulation and experiment validates the performance of the flight control system of PUAV.

Keywords-Flight control system; portable unmanned aerial vehicles; variable universe fuzzy control; bilinear interpolation

Machine Vision-based Detection System of a Cleaning Robot

for Vertical Type Air-Conditioning Duct

Yi Cao, Huige Chen, Xinjun Yu, Haihe Zang, Xiujuan Li

School of Electrical Engineering

Henan University of Technology

Zhengzhou, China

e-mail: caoyioffice@yahoo.com.cn, chge1983@yahoo.com.cn

Abstract—As service robot, the cleaning robots for vertical type air-conditioning duct are studied in recent years. The detection system based on machine vision is a key component in the robot controller design. An effective method based on histogram similarity principle which is used in the machine vision is studied in the paper. Firstly, the configuration and workflow of the machine vision system is presented. Secondly, some key technologies based on the image histogram are studied. Finally, some experiments are carried out and the results illustrate in the paper. And the experiment results show the proposed method is useful and accurate.

Keywords-cleaning robot; machine vision; histogram similarity principle ;image histogram

APF Obstacle Avoidance in Polar Coordinates for Mobile Robot

Based on Laser Radar
YU Zhiqiang, GAO Meng，DENG Xiaoyan, DU Liqiang, HE Chaofeng, DI Jianhong, YANG Yong, SHI Yanhui, HU Liqiang

Shijiazhuang Railway Institute

Shijiazhuang 050043, Hebei Province, China

Yuzhiqiang38381@126.com, gaomeng@sjzri.edu.cn

Abstract—In order to improve the safety and the reliability of mobile robot, a method for the path planning and the obstacle avoidance is provided based on distance information that laser radar offers. The method used the improved artificial potential field (APF) and set up the real-time variation polar coordinates, whose centre was the place that the laser radar installed in. In the polar coordinates, the robot-to-obstacle relative distance was measured, the direction and the speed of robot were adjusted to avoid obstacles. The simulation results show that this method based on the distance information that laser radar provides can make mobile robot avoid obstacle reliably.

Keywords- laser radar; path planning; obstacle avoidance; polar coordinates; artificial potential field

NSS-AKmeans: An Agglomerative Fuzzy K-Means Clustering Method with Automatic Selection of Cluster Number

Yanfeng Zhang

Shenzhen Graduate School

Harbin Institute of Technology, HIT Campus at Xili University Town, Shenzhen, China

zhangyanfeng@hit.edu.cn

Xiaofei Xu

Department of Computer Science

Harbin Institute of Technology,

Harbin, China

xiaofei@hope.hit.edu.cn

Yunming Ye

Shenzhen Graduate School

Harbin Institute of Technology, HIT Campus at Xili University Town, Shenzhen, China

yeyunming@hit.edu.cn

Abstract—In this paper, we present a new Neighbor Sharing Selection based Agglomerative fuzzy K-means (NSS-AKmeans) algorithm for learning optimal number of clusters and generating better clustering results. The NSS-AKmeans can identify high density areas and determine initial cluster centers from these areas with a neighbor sharing selection method. To select initial cluster centers, we propose an agglomeration energy (AE) factor for representing global density relationship of objects, and a Neighbors Sharing Factor (NSF) for estimating local neighbor sharing relationship of objects. Then we use the Agglomerative Fuzzy k-means clustering algorithm to further merge these initial centers to obtain the preferred number of clusters and generate better clustering results. Experimental results on various data sets have shown that the NSS-AKmeans was very effective in automatically identifying the true cluster number as well as producing accurate clustering results.

Keywords- Neighbor Sharing Selection; agglomeration energy; Neighbors Sharing Factor; initial cluster centers; number of clusters

OFDM Baseband Modulation Technology

based on VHDL

Lin Lin

Graduate School of the Chinese Academy of Sciences

Changchun China; Beijing China

linlinat0218@yahoo.com.cn

Yan-feng Qiao

Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences

Changchun China

qiaoyf@ciomp.ac.cn

Wan-xin Su

Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences

Changchun China

swx123456@mail.jl.cn

Abstract—In order to improve the transmission velocity in mulitipath fading wireless channel, the high speed OFDM technology receives increasing attentions in mobile communication. Modulation programs are designed with VHDL based on the principle of OFDM in the paper. First, after OFDM fundamental is introduced; two main advantages are obtained via discussing spectrum utilization ratio of OFDM. Then, from the results of VHDL simulation, the realization of baseband operations, such as interleaver, subcarrier modulation, IFFT and adding CP, are presented. Finally, implemented programs are validated on the actual implement system. Experimental results indicate that setup time corresponding to transmission velocity is only 71.05µs and steady time is approximately 6 times as setup time, that is, not only achieving the high speed transmission, but also supplying adequate modulation time.

Keywords: OFDM; VHDL; Baseband Modulation

Multi-Mapping Based Ontology Merging System Design

Guanyu Li1, Zhenghai Luo2, Jianshuang Shao3

Faculty of Information Science and Technology, Dalian Maritime University,

Dalian, Liaoning, 116026, P.R. China

1 Email: rabitlee@163.com, 2 Email:luozhenghai1@126.com, 3 Email: jsshao1986@163.com

Abstract—It is found that ontology merging is the most effective way to solve the problem of ontology heterogeneity in distributed environment which can hinder the inter-operability of the services by using ontology to describe Web services and merged ontology can provide a good basis for the inter-operability of services. To solve this problem, firstly a framework for multi-mapping based ontology merging systems (MMOMS) is proposed, and the functions and working processes of its six composition modules are fully described. Secondly, the compound strategy to merge ontology mapping results is set forth in detail. Thirdly, 5 rules for ontology merging and 2 rules for conflict handling are given. Lastly, algorithms of ontology merging, attribute merging, relation merging, and super-class merging of MMOMS are designed formally. In terms of general performance, the experimental verification result reveals that the MMOMS works well in solving the problem of ontology heterogeneity in Semantic Web Services.

Keywords: Ontology Merging; Multi-Mapping; Semantic Web Service; Web Service Integration

Gear Tooth Profile Recognition System Based on Machine Vision

Inner Mongolia University of Science &Technology

IMUST

Bao Tou,China

Yan Hongbo

Inner Mongolia University of Science &Technology

Liu Yi

IMUST

e-mail:liuyihld@hotmail.com

Bao Tou,China

e-mail:nkdyanhongbo@163.com

Abstract: This paper presents a new type for detection of spiral bevel gears by using machine vision technology. It is a high efficiency, high precision and non-contact detection system. The concrete method is shown as follows: Cameras were calibrated with improved Tsai two-step method. Then, the two cameras in two different orientations taken gear images. After matching the two images robustly, using correspondence between image feature points and imaging geometry to solve the three-dimensional coordinates of feature points. Finally, recognize tooth profile in contrast deal tooth data.

Key Words: machine vision; spiral bevel gear; gear tooth profile ; recognize

Video smoke recognition based on optical flow

Yu Chunyu, Zhang Yongming, Fang Jun, Wang Jinjun

State key laboratory of fire science of USTC

Hefei 230027, Anhui province, China

Email: ycyu@mail.ustc.edu.cn

Abstract—A novel video smoke recognition method based on optical flow is presented. The result of optical flow is assumed to be an approximation of motion field. The method is proposed as following, first, moving pixels and regions in the video are determined by a background estimation method. Then, a pyramidal implementation of the Lucas Kanade feature tracker is proposed to calculate the optical flow of regions determined by the first step. And the average and variance of the corner points’ optical velocity are calculated which we call optical flow features and use to differentiate smoke from some other moving objects. Finally, examples consisting of features extracted from sequences of off-line videos are collected for the training of a discriminating model. A prototype of back-propagation neural networks is introduced for the discriminating model. Experiments show that the algorithm is significant for improving the accuracy of fire smoke detection and reducing false alarms.

Optimizing Grid Resource Allocation by Combining Fuzzy Clustering

with Application Preference

Dawei Sun

School of Information

Science & Engineering

Northeastern University

Shenyang, China

sundaweicn@163.com

Guiran Chang

Computing Center

Northeastern University

Shenyang, China

chang@neu.edu.cn

Lizhong Jin

School of Information

Science & Engineering

Northeastern University

Shenyang, China

jinlizhongneu@163.com

Xingwei Wang

School of Information

Science & Engineering

Northeastern University

Shenyang, China

wangxw@mail.neu.edu.cn

Abstract—Focusing on the problem of resource allocation under large-scale, distributed, autonomous, heterogeneous and dynamic environments in grid computing, a heuristic algorithm combining fuzzy clustering with application preference is proposed. Fuzzy clustering method is applied according to a group of features, which describe the user’s application preference, to realize reasonable pre-classification resource. Then a resource is chosen according to the synthetic evaluation value, which can make the user’s target utility maximized. There is no need to search every resource at each scheduling step. Therefore, the cost on choosing the resource to execute the current task is reduced significantly. Experimental results show that the bigger the target system, the more efficient the algorithm is, and the more satisfactorily the application preferences of users are met. Furthermore, since resources are classified by different application preferences, this method can also avoid heavy loads concentrating on only a few resources so as to improve load balance in grid environments.

Keywords-grid computing; application preference; fuzzy clustering; resource allocation; heterogeneous computing environment

Research and Design of the Financial Supervision and Management

System Based on Data Center

Jie Ling

Faculty of Computer

Guangdong University of Technology

Guangzhou, China

jling@gdut.edu.cn

Miao Wang

Faculty of Computer

Guangdong University of Technology

Guangzhou, China

wmjsj06@126.com

Zhaoxia Yang

College of Mathematics and Computational Science

Sun Yat-sen University

Guangzhou, China

Feng Chen

Guangzhou Financial Bureau

Guangzhou, China

Abstract—According to the circulation process of financial indicators flow, data flow, capital flow involved in financial supervision work, based on the financial data center, designs a five-story architecture for the system including monitoring and analysis of budget preparation, monitoring and analysis of budget adjustments, monitoring and analysis of budget implementation, monitoring and analysis of accounts and other financial monitoring software features and monitoring point, given the implementation method of supervision and management system.

Keywords-Financial Supervision, Financial Data Center, Budget, Data extraction, Data warehouse

A High-speed Method of CCD Image Data Storage System

Zhang Feng

Graduate School of the Chinese Academy of Sciences

Beijing, China

zhangfeng1186@163.com

Wu qinzhang,Ren guoqiang

The Institute of Optics and Electronics

The Chinese Academy of Sciences

Chengdu, China

Abstract—A high-speed, real-time method of CCD Image data storage system is introduced. It integrates data acquisition and storage into a single FPGA chip. A SATA controller is designed in VHDL based on the protocol SATA 2.6 and implemented by using the GTX in V5FX70 series FPGA. If several disks are combined to RAID, the CCD data can be stored into SATA disk parallelly with the virtue of high speed, real-time, stable and portable.

Keywords- CCD Image data; high-speed; real time; GTX;SATA

Prediction of short-term bus routes passage flow based on wavelet analysis

Zhao Shuzhi

Transportation Plan and Management Department

Transportation and Traffic College of Jilin University Changchun, China

e-mail:zhaosz@jlu.edu.cn

Ni Tonghe(Affiliation Author)

Transportation Plan and Management Department

Transportation and Traffic College of Jilin University Changchun, China

e-mail: nile1949@yahoo.com.cn

Abstract—It is the basis for higher levels of benefits that whether a Public transport enterprises can allocate reasonably. During the bus business operations, the phenomenon of peak lack and pling peak idle of vehicle resources, results in a lower quality of service, passenger satisfaction is not high. In this paper, wavelet analysis and neural network methods are used to study the distribution of passenger flow at various time slots of bus routes, put forward a prediction method of bus line passenger flow time, describe the distribution of passenger flow of time-line, predict passenger flow of the period of the bus lines, and the transport vehicle dynamics control and reasonable dispatch can be realized.

Keywords-wavelet analysis; bus routes; passenger flow; prediction

Application of Linear Frequency Modulation Pulse Compression in Air-coupled Ultrasonic Testing

WEI Dong, ZHOU Zhenggan and NI Xiansheng

Institute for Nondestructive Testing and Mechatronics Engineering

Beihang University

Beijing, 100191, CHINA

zzhenggan@buaa.edu.cn

Abstract - Effective signal processing technology should be used to improve signal-to-noise ratio in air-coupled ultrasonic testing, because of there is feeble signal and low signal-to-noise ratio. Pulse compression of linear frequency modulation could enhance system’s signal to noise ratio and distance resolution effectively. Principle of linear frequency modulation pulse compression is introduced, including of designing and accomplishing of matching filter. The relationship between pulse compression parameters and testing result is analyzed. The affect of exciting mode to ultrasonic signal and pulse compression to signal-to-noise ratio are researched by comparing experiment results. Air-coupled ultrasonic C-scan testing system based on pulse compression is accomplished, and the effectiveness of pulse compression method is testified by ultrasonic imaging results.

Directional Multiscale Edge Detection Using the Contourlet Transform

Shun-feng Ma, Geng-feng Zheng, Long-xu Jin, Shuang-li Han, Ran-feng Zhang

Institute of Optics, Fine Mechanics and Physics Chinese Academy of Sciences

Changchun, China

e-mail: jluer@hotmail.com

Shun-feng Ma, Geng-feng Zheng

Chinese Academy of Sciences

Beijing, China

e-mail: GF.Zheng83@gmail.com

Abstract—Wavelet multiresolution analysis allows us to detect edges at different scales, also to obtain other important aspects of the extracted edges. However, due to the usual two-dimensional tensor product, wavelet transform is not optimal for representing images. The main problem in edge detection using wavelet transform is that it can only capture point-singularities, and the extracted edges are not continuous. In order to solve that problem, we propose a new image edge detection method based on the contourlet transform. The directional multiresolution representation Contourlet takes advantages of the intrinsic geometrical structure of images, and is appropriate for the analysis of the image edges. Using the modulus maxima detection, an image edge detection method based on contourlet transform is proposed. To suppress the image noise effect on edge detection, the scale multiplication in contourlet domain is also proposed. Through real images experiments, the proposed edge detection method’s performance for the extracted edges is analyzed and compared with other two edge detection methods. The experiment result proves that the proposed edge detection method improves over wavelet-based techniques and Canny detector, and also works well for noisy images.

Keywords-wavelet; multiscale; edge detection; contourlet; modulus maxma; the scale multiplication

KNN Algorithm Improving Based on Cloud Model

Liu Yu

Beihang University

Beijing, China

liuyu8014@163.com

Chen Gui-Sheng

China Institute of Electronics Engineering

Beijing , China

uaicloud@gmail.com

Abstract-KNN algorithm is particularly sensitive to outliers and noise contained in the training data set. In this paper, we use the reverse cloud algorithm to map the training samples into clouds. Each attribute is mapped to a cloud vector. Reverse cloud algorithm is not sensitive to the noise on data sets and it can eliminate the impact of noise on classification effectively. By comparing the similarity of clouds in the cloud vector, we can calculate the attributes weights. For those attributes with a low weight of properties, we find out merger them to a new attribute which can generate more significant attribute weight than original ones. We present a new KNN algorithm based on Cloud Model and compare our algorithm with classic KNN algorithms and other well-known improved KNN algorithms using 10 data sets. Experiments show that our approach could achieve a better or at least a comparable classification accuracy with other algorithms.

Keywords- KNN; classification; attribute weight learning; similarity; Cloud Model.

Retrieval of Bare Surface Soil Moisture from AMSR-E Data

Nianlong Han

College of Resources Science and Technology

Beijing Normal University

Beijing, China

e-mail: nlhan@ires.cn

Shengbo Chen, Zijun Wang

College of GeoExploration Science and Technology,

Jilin UniversityChangchun, China

e-mail:chensb@jlu.edu.cn;

wzj08@mails.jlu.edu.cn

Abstract—Passive microwave plays an important role in soil moisture monitoring. In this study, a layered soil emission model has been built based on theory of radiative transfer, combined with the random rough surface, soil dielectric constant model and soil moisture algorithm.The soil moisture in different frequencies was simulated and the look-up table set was established between soil moisture and soil brightness temperature in the taklimakan desert study area. The look-up table set was used to retrieve the soil moisture from the study area’s brightness temperature observed by AMSR-E.The results of soil moisture retrieval were compared to the AMSR-E soil moisture data product and their rms errors were calculated for validation. The validation results suggest that there is a good agreement between retrieved and AMSR-E soil moisture in study area at certain frequencies, and the soil moisture has been retrieved to the highest accuracy at 6.9GHz, with H poarization. In conclusion, the soil moisture in this study area can be well reflected by the retrieval results.