The 2013 International Conference on Information Science
and Cloud Computing
December 7-8, 2013, Guangzhou, China
Conference
Sponsor
Co-Sponsor
Program
Supportors
The 2013 International Conference on Information Science and Cloud Computing
第三届信息科学与云计算国际学术会议
The 2013 International Conference on Information Science and Cloud Computing
第三届信息科学与云计算国际学术会议
会议日程安排表 Conference Program
12 月 6 日
6th December p.m.
周五 Friday p.m.
签到
12 月 7 日
7th December a.m.
周六 Saturday a.m.
Registration
签到，领取会议材料
3 楼耀光厅
Register, Approach
Yaoguang Hall on the 3rd floor
开幕式
3 楼耀光厅
Opening Ceremony
Yaoguang Hall on the 3rd floor
大会嘉宾演讲
3 楼耀光厅
Keynote Speech
Yaoguang Hall on the 3rd floor
茶歇
3 楼休息区
07:30—09:00
09:00—09:30
09:30—10:10
10:10—10:30
Tea Break
resting area on the 3rd floor
大会嘉宾演讲
3 楼耀光厅
Keynote Speech
Yaoguang Hall on the 3rd floor
大会嘉宾演讲
3 楼耀光厅
Keynote Speeches
Yaoguang Hall on the 3rd floor
集体照
大门
Collective photography
The door
10:30—11:10
11:10—11:50
11:50—12:00
午餐
12:00—13:30
Lunch
12 月 7 日
7th December p.m.
2 楼金桂轩酒家大厅
The lobby in Jinguixuan restaurant on
the 2nd floor
周六 Saturday p.m.
分会场报告
3 楼会议室
Technical Sessions
The meeting room on the 3rd floor
茶歇
3 楼休息区
Tea Break
Resting area on the 3rd floor
分会场报告
3 楼会议室
Technical Sessions
The meeting room on the 3rd floor
13:30—15:00
15:00—15:30
15:30—17:30
晚宴
17:30—20:00
Banquet
12 月 8 日
8th December a.m.
2 楼金桂轩酒家 39 号贵宾厅
No.39 VIP room in Jinguixuan
restaurant on the 2nd floor
周日 Sunday a.m.
The 2013 International Conference on Information Science and Cloud Computing
第三届信息科学与云计算国际学术会议
分会场报告
3 楼会议室
Technical Sessions
The meeting room on the 3rd floor
茶歇
3 楼休息区
Tea Break
Resting area on the 3rd floor
分会场报告
3 楼会议室
Technical Sessions
The meeting room on the 3rd floor
08:00—10:00
10:00—10:30
10:30—12:00
午餐
12:00—13:30
Lunch
12 月 8 日
8th December p.m.
2 楼金桂轩酒家 15 号贵宾厅
No.15 VIP room in Jinguixuan
restaurant on the 2nd floor
周日 Sunday p.m.
分会场报告
3 楼会议室
Technical Sessions
The meeting room on the 3rd floor
茶歇
3 楼休息区
Tea Break
Resting area on the 3rd floor
分会场报告
3 楼会议室
Technical Sessions
The meeting room on the 3rd floor
13:30—15:00
15:00—15:30
15:30—17:30
晚宴
17:30—20:00
Banquet
2 楼金桂轩酒家 39 号贵宾厅
No.39 VIP room in Jinguixuan
restaurant on the 2nd floor
The 2013 International Conference on Information Science and Cloud Computing
第三届信息科学与云计算国际学术会议
大会嘉宾介绍
Keynote Speakers Resume
Dr. Christian K. Hansen
Eastern Washington University
2014 President of the IEEE Reliability Society
E-mail: [email protected]
Bio：
Dr. Christian K. Hansen is Professor and Associate Dean of Computing and Engineering
Sciences at Eastern Washington University (EWU) and 2014 President of the IEEE Reliability Society.
He is been with EWU since 1993 and served a variety of academic and administrative leadership
positions. Prior to his current leadership position, he served as department chair for eight years. He has
been active in the reliability profession for over 25 years and published broadly on a variety of
engineering applications, mostly related to reliability modeling and failure data analysis for complex
electronic systems. Over the past two decades he has been active with the IEEE Reliability Society and
has served in leadership positions that include vice-president of publications, treasurer and president
elect. Dr. Hansen is a graduate of the Technical University of Denmark with degrees in Electrical
Engineering (MS, 1988) and Statistics (PhD, 1991).
Title:
Big Data in the Big Picture – Challenges and Projections for the Future
The 2013 International Conference on Information Science and Cloud Computing
第三届信息科学与云计算国际学术会议
Prof. Hong Shen
School of Computer Science, The University of Adelaide,
North Terrace, Adelaide, Australia
Bio：
Hong Shen is Professor (Chair) of Computer Science in the University of Adelaide, Australia,
and currently also a "Thousand Talents" professor in Sun Yat-Sen University, China. He received the
B.Eng.degree from Beijing University of Science and Technology, M.Eng.degree from University of
Science and Technology of China, Ph.Lic.and Ph.D. degrees from Abo Akademi University, Finland,
all in Computer Science. He was Professor and Chair of the Computer Networks Laboratory in Japan
Advanced Institute of Science and Technology(JAIST) during 2001-2006, and Professor (Chair) of
Compute Science at Griffith University, Australia, where he taught 9 years since 1992.With main
research interests in parallel and distributed computing,algorithms, data mining, privacy preserving
computing, high performance networks and multimedia systems, he has published more than 300
papers including over 100 papers in international journals such as a variety of IEEE and ACM
transactions. Prof. Shen received many honours/awards including China National Endowed Expert of
"Thousand Talents", Chinese Academy of Sciences "Hundred Talents", National Education
Commission Science and Technology Progress Award,and Chinese Academy of Sciences Natural
Sciences Award. He served on the editorial board of numerous journals (incl.IEEE TC and IEEE TPDS)
and chaired several conferences.
Title:
Smart Cloud Computing: Challenges and Opportunities
The 2013 International Conference on Information Science and Cloud Computing
第三届信息科学与云计算国际学术会议
Tatsuhiro Tsuchiya
Graduate School of Information Science and Technology
Osaka University, Japan
Bio:
Tatsuhiro Tsuchiya received his M.E. and Ph.D degrees in engineering from Osaka University in
1995 and 1998, respectively. He is currently a professor at the Graduate School of Information Science
and Technology at Osaka University. His research interests are in the areas of dependable computing
and verification and testing.
He is a member of the program committees of 34th International
Conference on Distributed Computing Systems (ICDCS 2014), 33rd International Symposium on
Reliable Distributed Systems (SRDS 2014), and 7th International Conference on Software Testing,
Verification and Validation (ICST 2014).
Title:
On Transfer of Distributed Computing Theory to Cloud Computing Practice
The 2013 International Conference on Information Science and Cloud Computing
第三届信息科学与云计算国际学术会议
分会场报告 Technical Sessions
分会场报告 A1：信息理论（12月7日13:30--17:30）
Technical Sessions A1: Information Theory (December 7th p.m. 13:30--17:30)
Session A1
Presentation Topic
Presenters
Research on the Effect of the Adjustable Parameter Applied to
Information Theoretic Criteria based Spectrum Sensing Method
Tingting Liu
P107
A Location Privacy-Preserving Protocol Based on Homomorphic
Encryption and Key Agreement
Xiaoling Zhu
P181
The Anti-Phishing Technology Based on E-mail Extraction and
Analysis
Fu Xue
P193
Mafeng Zhu
P247
An Improvement of the Slotted CSMA/CA Algorithm with
Multi-level Priority Strategy and Service Differentiation
Mechanisms
P255
The Security Testing Case Research of Protocol Implementation
Lei Zhang
P256
Efficient Identity-based Encryption from Lattice
Dongmei Chen
P268
Unambiguous Synchronization Technique for BOC Signals
Jiamin Qi
A Method of Computing Iceberg Cube Based on
Non-antimonotonic Constraint
Yuntian Feng
P307
P333
Mining Spam Accounts with User Influence
Kan Chen
The Research and Simulation of the Satellite Network Routing
Algorithm based on Game Theory
Rongyan Qiao
P100
Performance Simulation and Optimization of Agricultural
Supply Chains
Jing Chen
P188
H-KD: a Novel Query Structure for Multi-dimensional
Awareness Information
Xiao Sun
P244
Alexander S.
Belenky
P366
Games with Connected Player Strategies for Analyzing the
Competitiveness of a Railroad Company in a Cargo
Transportation Marketplace
The 2013 International Conference on Information Science and Cloud Computing
第三届信息科学与云计算国际学术会议
分会场报告 B1：云科学（12月7日13:30--17:30）
Technical Sessions B1: Cloud Science (December 7th p.m. 13:30--17:30)
Session B1
Presentation Topic
Presenters
C132
The Attack on Mona: Secure Multi-Owner Data Sharing for
Dynamic Groups in the Cloud
Zhongma Zhu
C136
An Energy-Saving Virtual-machine Scheduling Algorithm of
Cloud Computing System
Ruo Du
P133
A Parallel Domain Decomposition FDTD Algorithm Based on
Cloud Computing
Xiaohu Liu
P141
Research on Multi-tenant PaaS Cloud Security on Java Platform
Xiaoming Liu
P142
New Features Acquisition of Text with Cloud-LDA Model
Fanli He
P197
Survey of Cloud Messaging Push Notification Service
Na Li
P262
Towards Real-time Federate Cloud for Large Group Company
Lixin Du
On the Availability of Replicated Data Managed by
Yuuki Ueda
P319
Hierarchical Voting
P327
Cloud Model: Detect Unsupervised Communities in Social
Tagging Networks
Hongbo Gao
P335
A Cloud-based Platform for Watching Same Content on
Three-Screen TV Continuously in Smart Home
Noel Crespi
P109
Online Resource Monitoring Model in Cloud TV
Chao Xu
P187
Cloud Scenes Generation Based on the Improved Random
Midpoint Displacement Method
Dongsheng
Yang
P365
An Environment Recognition Algorithm Based on Weighted
Cloud Classifier
Yang Zhao
The 2013 International Conference on Information Science and Cloud Computing
第三届信息科学与云计算国际学术会议
分会场报告 C1：嵌入式系统（12月7日13:30—17:30）
Technical Sessions C1: Embedded Systems (December 7th p.m. 13:30—17:30)
Session C1
Presentation Topic
Presenters
C107
The Design and Implementation of Sigma Delta ADC
Digital Decimation Filter
Jie Cao
P081
The Design and Implementation of a Mobile Learning
Platform Based on Android
Wei Sonng
P212
The Asymptotic Properties of Quasi-maximum Likelihood
Estimator for Spatial Error Panel Data Model
Lixia Wen
P291
Intelligent Optimization on Power Values for Inverse
Distance Weighting
Zhanglin Li
P199
The Speedup Model for Manycore Processor
P245
A Case of Chip Multithreading Architecture with Resource
Unit Manager
Juan Fang
P189
Partition Strategies for C Source Programs to Support
CPU+GPU Coordination Computing
Ding Yao
P122
A Method for Star Extraction of the Air-borne Star Sensor
during the Daytime
Xiang Zhang
P162
An Implementation of Montgomery Modular Multiplication
on FPGAs
Xinkai Yan
P287
System Reliability-Aware Energy Optimization for
Network-on-Chip with Voltage-Frequency Islands
Jianxian Zhang
P108
Study on Virtual-Measure Kalman Filter Algorithm in Radar
Networking
Wenbo Zhao
P349
Research and Implementation of Data Collection Protocol
for Wireless Sensor Networks
Xiaohong Wang
P314
C# blueprint Action Pattern
Nan Ye
Peng Gao
The 2013 International Conference on Information Science and Cloud Computing
第三届信息科学与云计算国际学术会议
分会场报告 D1：系统分析（12月7日13:30--17:30）
Technical Sessions D1: Systems Analysis (December 7th p.m. 13:30--17:30)
Session D1
Presentation Topic
Presenters
C137
A Dynamics Model of Opinion Information System
Jin Du
The Design and Implementation of a Process-based Printing
Order Management System
Huiling Ma
P177
Energy-Efficient Task Allocation for VFI-based Real-Time
Multi-Core Systems
Xiaodong Wu
P288
P323
Educational Geographic Information System Based on WebGIS
Mingyi Duan
P350
Research and Design of the Clock Synchronization for the
Bridge Health Monitoring System Based on Wireless Sensor
Network
Mingqiang
Song
C141
Implementation of Resource Management System Based on
Open Source Computing Platform Eucalyptus
Jianmin He
P303
Analysis on the Impact of Cloud Computing for Management
Information System
Xiaojing Wang
P305
Storage Space Reclaim Based on cluster Bitmap in the New
Technology File System
Chanying Qi
P320
Research on Optimum Model for the Best Link of Expert System
Chen Guo
P132
An Energy-saving Algorithm in Networked Embedded System
Based on Critical Tasks Served First Strategy
Bing Xue
P331
Study on Virtual Assembly System Based on Kinect
Somatosensory Interaction
Hongjian Liao
P137
A New Model Language for Cyber Physical Systems
Mingxing Liu
P144
A College Teaching Building Lighting Control System Based
On Power Line Carrier
Haochen Wang
The 2013 International Conference on Information Science and Cloud Computing
第三届信息科学与云计算国际学术会议
分会场报告 A2：数据挖掘（12月8日08:00--12:00）
Technical Sessions A2: Data Mining (December 8th a.m. 08:00--12:00)
Session A2
Presentation Topic
Presenters
P121
Operation Performance Evaluation and Optimization Based on
SUPER-SBM DEA Model in Railway Industry in China
Zhongdong Li
P161
Hadoop Cellular Automata for Identifying Rumor in Social
Networks
Hui Zhang
P168
A Method Based on Random Search Algorithm for Unequal
Circle Packing Problem
Ying Shang
P226
Using Bidirectional Search to Compute Optimal Shortest Paths
over Multi-Weight Graphs
Hui Ma
P273
Simulation Research on Diffusion of Agricultural Science and
Technology for Peasant
Li Ma
P275
A Three-stage Clustering Framework based on Multiple Feature
Combination for Chinese Person Name Disambiguation
Fei Wang
P286
Arc-length Constraint-Based Surface Deformation Using EnergyMinimum Optimization
Huanyu Yang
P302
A New Method of Optimization Based on Arc Search
P316
Research on Digital Museum of Yunnan Ethnic Minorities’
Resources Based on Network
Jun Wang
Lei Wang
P334
Factors Affecting Small and Medium-Sized Enterprise’s
Information Technology Absorptive Capability: An Empirical
Study of Jilin Province in China
P357
Preserving Social Network Privacy Using Edge Vector
Perturbation
Lihui Lan
P261
Effective Data Exchange in Parallel Computing
P373
Study on E-commerce Service Supply Chain Coordination Based
on Contract Theory
Xin Pan
Hui Ma
Fatao Wang
The 2013 International Conference on Information Science and Cloud Computing
第三届信息科学与云计算国际学术会议
分会场报告 B2：控制理论（12月8日08:00—12:00）
Technical Sessions B2: Control Theory (December 8th a.m. 08:00—12:00)
Session B2
C151
Presentation Topic
A Instant-Based
Qur’an Memorizer Application Interface
Presenters
Zameer Ahmed
Adhoni
P067
Attention Rate of Attribute Items: On the Combination of ABAC
Rules
Xinmao Gai
P087
ASCMS: an Accurate Self-Modifying Code Cache Management
Strategy in Binary Translation
Wenqi Wang
P172
The Model of Population Projection by Delay Differential Equation
with Two Lags
Liqiang Fan
P176
Strategies for Improving Accuracy of Structural Variation
Prediction using Read Pairs
Jingyang Gao
P239
A Weighted Association Rules Mining Algorithm with Fuzzy
Quantitative Constraints
Qibing Lu
P251
Predicting the Subcellular Localization of Proteins with Multiple
Sites Based on N-terminal Signals
Xumi Qu
P264
Solving Fuzzy Nonlinear Systems—A Class of Defuzzification in
the Fuzzy Control
Meizhen Jia
P341
A Kind of Quadratic System Decoupling Method Based on Similar
Transformation Solution
Shujuan Wang
P371
A Clustering-based QoS Prediction Approach for Web Service Sele
ction
Xuejie Zhang
P342
Fuzzy Logic-based Fault Diagnosis of Simply Supported Bridge
Using Modal Frequency as Input Variable
Yubo Jiao
P369
Topological Analysis of a Complex Trust Network
Xiangling Kuang
P071
Numerical Research of a Economic Model Based on Topological
Horseshoes Theory
Guangqun Chen
C114
Study on Image Encryption Algorithm Based on Chaotic Theory
Qiu Zhang
The 2013 International Conference on Information Science and Cloud Computing
第三届信息科学与云计算国际学术会议
分会场报告 C2：结构设计（12月8日08:00—12:00）
Technical Sessions C2: Architecture Design (December 8th a.m. 08:00—12:00)
Session C2
Presentation Topic
Presenters
P018
Method of Architecture Core Data Optimization Design Based
on DM2
Xiaoxue Zhang
P276
CloudFlame: Cyberinfrastructure for Combustion Research
Gokop L.Goteng
P328
Image Zooming Method with Hierarchical Structure
Lanfei Zhao
P265
Multiple Feature Fusion Protein Tertiary Structure Prediction
Wenzheng Bao
P295
An Algorithm for Delay-Reliability in Communication
Networks Based on Probabilistic User Equilibrium Model
Zhao Liu
Yue Cao
P266
A Study on User Adoption of Cloud Storage Service in China:
A Revised Unified Theory of Acceptance and Use of
Technology Model
P129
An Improved Collaborative Filtering Model Considering Item
Similarity
Yefei Zha
P362
Bigraph-based Modeling and Tracing for the Food Chain
System
Xue Li
P241
Design and Development of Air Traffic Management Safety
Database Analysis System
Lixin Wang
P336
Design of the Multi-level Inventory Control Model and
Solution algorithm for the Spare Parts
Yu Cao
Yi Liu
P364
The Design and Implementation of Knowledge Processing and
Decision-making Model Based on Multi-class in Agricultural
Expert System
P047
Musical Instrument Recognition Based on the Bionic Auditory
Model
Xiaoxue Zhang
The 2013 International Conference on Information Science and Cloud Computing
第三届信息科学与云计算国际学术会议
分会场报告 D2：机器学习（12月8日08:00—12:00）
Technical Sessions D2: Machine Learning (December 8th a.m. 08:00—12:00)
Session D2
Presentation Topic
Presenters
P169
Neural Network Based Algorithm for Generalized Eigenvalue
Problem
Bo Yu
P130
The Improved Particle Filter Algorithm Based on Weight
Optimization
Jun Zhu
P196
Multi-resolution Image Fusion Algorithm Based on Gradient and
Texture Features
Junyong Ma
P140
Recognition Methods of Housing Vacancy Based on Digital
Image Processing
Wei Yao
P194
A New Face Recognition Method Based on the Energy Image of
Facial Contour
Fei Zhai
P202
A Ship Recognition Method based on Affinity Propagation
P201
A New Approach for Text Location Based on SUSAN and SVM
P359
A New Approach of Face Identification in Line Drawings
P206
An Improved Super-Resolution Reconstruction Algorithm Based
on Regularization
Shuang Wang
P225
An Improved Forecasting Algorithm for Spare Parts of Short Life
Cycle Products Based on EMD-SVM
Yeliang Fan
P026
Technology of Fuzzy Chinese-Geocoding Method
P149
An Improved Genetic Algorithm based on Local Modularity for
Community Detection in Complex Network
Rui Li
P289
Performance Comparisons of Evolutionary Algorithms for
Walking Gait Optimization
Hong Jiang
Weiya Guo
Chuan Wang
Weikun Sun
Zhen Sun
The 2013 International Conference on Information Science and Cloud Computing
第三届信息科学与云计算国际学术会议
分会场报告 A3：模式识别（12月8日13:30—17:30）
Technical Sessions A3: Pattern Recognition (December 8th p.m. 13:30—17:30)
Session A3
Presentation Topic
Presenters
P051
Research on the Storage Method of Raster Image Based on File
Directory
Chao Wang
P079
Zero-Watermark Scheme for 2D Vector Drawings Based on
Mapping
Hua Zhao
P084
Markers Registration in Image-Guided Surgery
P112
Research on Web Mapping of Vector Nautical Charts Based on
HTML5
Mingyang Pan
P120
Driver’s Seat Belt Detection in Crossroad Based on Gradient
Orientation
Cao Liu
P209
Hand Tracking Algorithm Based
on SuperPixels Feature
Zhenhuan Zhou
Zhiqin Zhang
P146
A Multi-Level Grid Partition Method for Enterprises
Distribution Data
Zhang Zhang
P171
Simulation of Fabric in 2D Virtual Scene Based on Mesh Model
Xiaona Fan
P278
A Median Filtering Algorithm Based on Selected Point in
Digital Image
Yan Liang
P230
A Model of Visual Attention for Natural Image Retrieval
Guanghai Liu
P232
Research on Spatial Frequency Motivated Gray Level Image
Fusion Based on Improved PCNN
Nianyi Wang
P293
A New Subpixel Imaging Method for Image Super Resolution
P166
Bag of Visual Words for Cows’Basic Activity Recognition
Jihong Wang
Changji Wen
The 2013 International Conference on Information Science and Cloud Computing
第三届信息科学与云计算国际学术会议
分会场报告 B3：人工智能（12月8日13:30--17:30）
Technical Sessions B3: Artificial Intelligent (December 8th p.m. 13:30--17:30)
Session B3
Presentation Topic
Presenters
P041
Fast Adaptive Bilateral Filtering with Fixed Parameters for
Sharpness Enhancement and Noise Reduction
Yuanzhong Shu
P061
Revealing Research Themes and Their Evolutionary Trends
Using Bibliometric Data Based on Strategic Diagrams
Hongqi Han
P138
Enhanced Film Grain Noise Removal for High Fidelity Video
Coding
Inseong Hwang
P143
Establish Expert System of Transformer Fault Diagnosis Based
on Dissolved Gas in Oil
Wenjing Zhang
P164
A Steered Molecular Dynamics Method for Receptor-ligand
Unbinding Based on Genetic Algorithm
Junfeng Gu
P258
Research of Terrain 3D Visualization Method based on IDL and
ArcEngine
Bin Yang
P292
Super-Resolution Employing an Efficient Nonlocal Prior
Shuai Chen
P321
Research on the Evidence Optimization Method Based on the
Expert System
Chen Guo
P340
The universal approximation capabilities of 2pi-periodic
approximate identity neural networks
Saeed Panahian
Fard
P354
Research on XML Keyword Query Method Based on Semantic
Shan Tian
P363
A Process-oriented Ontology-based Knowledge Model
Yanhong Zhao
P351
Cluster Analysis on the Flow Velocity for the Sea Route
Monitorin
Yanling Zhang
P046
Application of Unscented Kalman Filter for Flying Target
Tracking
Honglei Yan
The 2013 International Conference on Information Science and Cloud Computing
第三届信息科学与云计算国际学术会议
分会场报告 C3：算法理论（12月8日13:30--17:30）
Technical Sessions C3: Algorithm Theory (December 8th p.m. 13:30--17:30)
Session C3
Presentation Topic
Presenters
C149
Analyzing on the Failure Mode of BFNNs’ learning and its
Improving Algorithm
Shuiming Zhong
P089
Maize Embryo Image Acquisition and Variety Identification
Based on OTSU and K-means Clustering Algorithm
Wenjing Zhang
P184
A Lifecycle Analysis of the Revision Behavior of Featured
Articles on Wikipedia
Xinyi Li
P186
Collaborative Filtering Recommendation Algorithm Based on
Users of Maximum Similar Clique
Zhaoyang Zhou
P205
NBA All-Star Lineup Prediction Based on Neural Networks
Bigui Ji
P238
Algorithm Research about Textual Case Retrieval Based on
Topic Words
Lei Tang
Han Li
P347
Research of Clustering Algorithm based on Information
Entropy and Frequency Sensitive Discrepancy Metric in
Anomaly Detection
P008
A Motion Planning Algorithm Based on Uncertainty
Prediction
Tianyuan Gu
P380
A Data Compression Algorithm for the Sea Route Monitoring
with Wireless Sensor Network
Wei Huangfu
P159
Dividing for Combination: A Bootstrapping Sentiment
Classification Framework for Micro-blogs
Songxian Xie
P035
Software Analysis of Internet Bots using a Model Checker
Shin-ya Nishizaki
P045
Multi-use Conditional Proxy Re-encryption
Lequn Mo
P217
The Credit Risk Prediction of the Small and Medium-Sized
Enterprises based on GA-v-SVR
Xiangdong Liu
The 2013 International Conference on Information Science and Cloud Computing
第三届信息科学与云计算国际学术会议
分会场报告 D3：优化理论（12月8日13:30--17:30）
Technical Sessions D3: Optimization Theory (December 8th p.m. 13:30--17:30)
Session D3
Presentation Topic
Presenters
P096
Commodity Futures Price Prediction and Trading Strategies
a Signal Noise difference Approach
Jinhao Zheng
P221
Application of FAHP Approach to Assess Service Quality
Yong Li
P260
Commercial Bank Stress Tests Based on Credit Risk
Xue Zhang
P263
Realization of Multi-port SDRAM Controller in LXI Data
Acquisition System
Yanqin Zhang
P300
Quality Evaluation for Anxi Tieguanyin Tea Based on
Electronic Nose and PCA-LDA Method
Fufang Li
P309
Improvement of the Data Mining Algorithm of Rough Set under
the Framework of Map/Reduce
Qiong Liu
P352
Optimal Constellation Mapping for Pulse Amplitude
Modulation Based Vertical Physical-Layer Network Coding
Fengyue Gao
P267
Present Situation and Prospect of Data Warehouse Architecture
under the Background of Big Data
Lihua Sun
P277
Comprehensive Credit Evaluation Model of Electricity
Customer Based on the Changing Trend of Credit
Sitong Cao
C121
An Improved Path Planning for Mobile Robots
Feng Zhou
P101
Optimal Web Service Composition Based on
Context-awareness and Genetic Algorithm
Yuan Yuan
P088
Optimization for the Locations of Urban E-commerce
Distribution Network Based on a Genetic Algorithm
Aihua Xiang
P009
An Improved Association Rules Mining Algorithm Based on
Power Set and Hadoop
Weibin Guo
The 2013 International Conference on Information Science and Cloud Computing
第三届信息科学与云计算国际学术会议
会议地点及交通 Conference Location and Traffic
会议地点：广州大学学术交流中心
Conference Location: Academic Exchange Center Guangzhou University
地址：广州市白云区解放北桂花路 23 号
Address: No.23 Jie Fang Beilu, Baiyun District, Guangzhou
住宿地点：1、广州大学学术交流中心
2、广州流花宾馆
Hotel Location: 1, Academic Exchange Center Guangzhou University
2, Guangzhou Liuhua Hotel
用餐地点：广州市益高饮食有限公司金桂轩酒家
Dining Place: Guangzhou Jinguixuan Restaurant
交通方式 Traffic:
广州白云机场（30 公里）：步行至白云机场 B 区国内到达厅站，乘坐机场快线 1 号线, 在中央
海航酒店站下车，步行至广州大学学术交流中心。出租车约 78 元。
Guangzhou Baiyun International Airport (30 kilometers): Walk to Baiyun Airport area B, domestic
arrival hall station, take the airport express line 1, get off at the Central Hotel station, and walk to
Academic Exchange Center Guangzhou University. It takes about 78 Yuan by taxi.
广州火车站（1 公里）：步行约 15 分钟至广州大学学术交流中心。出租车约 10 元。
Guangzhou Railway Station (1 km) : Walk about 15 minutes to the Academic Exchange Center
Guangzhou University. It takes about 10 Yuan by taxi.
广州火车东站（10 公里）：步行至东站汽车客运站，乘坐 32 路(或 298 路, 60 路), 在广园客
运站下车，换乘 481 路, 在广州大学总站(桂花岗校区)站下车，步行至广州大学学术交流中心。
出租车约 27 元。
Guangzhou Railway East Station (10 km): Walk to Guangzhou East Coach terminal, take bus 32 (or
298 road, 60 road), get off at Guangyuan Coach Station and change to the 481 road, get off in the
station of Guangzhou university (Guihuagang Campus), and walk to Academic Exchange Center
Guangzhou University. It takes about 27 Yuan by taxi.
广州火车南站（21 公里）：步行至广州南站，乘坐地铁 2 号线(嘉禾望岗方向), 在越秀公园站
下车(B2 口出)，步行至广州大学学术交流中心。出租车约 70 元。
Guangzhou Railway South Station (21 km) : Walk to Guangzhou south station, take the subway line
2 (Jiahewanggang direction), get off at the Yuexiu Park station(B2 Exit), and walk to Academic
Exchange Center Guangzhou University. It takes about 70 Yuan by taxi.
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第三届信息科学与云计算国际学术会议
广州火车北站（30 公里）：步行至花都客运站，乘坐广花东站线，在广园客运站下车，换乘 481
路, 在广州大学总站(桂花岗校区)站下车，步行至广州大学学术交流中心。出租车约 96 元。
Guangzhou Railway North Station (30 kilometers) : Walk to Guangzhou Huadu Coach Station, take
Guanghua station line, get off at Guangyuan Coach Station and change to the 481 road, get off in the
station of Guangzhou university (Guihuagang Campus), and walk to Academic Exchange Center
Guangzhou University. It takes about 96 Yuan by taxi.
广州汽车站（2.5 公里）：步行至站南路站，乘坐商务专线 3 路, 在桂花岗站下车，步行至广州
大学学术交流中心。出租车约 10 元。
Passenger Transport Station of Guangzhou (2.5 km) : Walk to Zhannan Road station, take bus
business line 3, get off at Guihuagang station, and walk to Academic Exchange Center Guangzhou
University. It takes about 10 Yuan by taxi.
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附录 Appendix
C107 The Design and Implementation of Sigma Delta ADC Digital Decimation Filter
Authors: Cao Jie, Yujun Liu, Bingshu Jiang, Xiaozhi Liu
Abstract. This paper presents a novel implementation of Sigma Delta digital decimation filter with low
power and hardware efficient but high performance. The digital decimation filter consists of a modified
Cascaded integrator-comb (CIC) decimation filter, one stage compensate filter and one stage half-band
filter. The multi-stage signal processing, poly-phase technology and CSD code are used to design the
filter. The decimation filter is designed and simulated by Simulink Matlab and modelsim6.5. The
hardware realization of the decimation filter is obtained by FPGA Xilinx technology. Compared to the
traditional digital decimation filter, the proposed method has a power reduction of 44% and a hardware
saving of 65%.
Keywords: Digital decimation filter; CIC filter; CSD code
C108 The Research of Embedded Software Reliability Modeling Analysis Based on AADL
Authors: Tian Chuan, Yujun Liu, Li Xin,Qingling Duan
Abstract. This paper proposes an analysis method of embedded and distributed software reliability
modeling based on AADL. By using the key information in AADL structural model, AADL fault model
is established, to describe the fault behavior of computer distributed software. On this basis, the
reliability analysis is carried through the sensitivity analysis method. We analyze the reliability of the
system, which can help designers to find out the key modules that affect the reliability of the system in
the early stages of development and provides a strategic decision foundation to enhance the system
reliability.
Keywords: Embedded simulation; AADL; Reliability Modeling
C114 Research on Image Encryption Algorithm Based on Chaotic Theory
Authors: Qiu Zhang
Abstract. With the rapid development of high-tech such as cloud technology, information security has
become more critical than before. So the cryptography has a very important significance as key
technology in information security. In recently, some new cryptography theory has attracted more and
more attention at the background of research on algorithm efficiency and security has become the
current hot research field. Chaotic algorithm is very suitable for stream cipher encryption not only its
sensitivity to initial conditions for time series generated but also its complex structure is difficult to
analyze and forecast. At the same time, it can provide smart pseudo random sequence with excellent
randomness, correlation and complexity. Therefore, this paper mainly studies about the image
encryption algorithm based on chaotic theory.
Keywords: information security; chaotic theory; image encryption
C118 Application of SOA and Web Service in Implementing Heterogeneous System Integration
Authors: Yilan Yang
Abstract. Large enterprises tend to have heterogeneous systems, namely the formation of “islands of
information”, that makes information interaction and interoperability very difficult. Application of
integrated development based on service-oriented architecture, which does not change the underlying
architecture of enterprise applications, is a good solution to the aforementioned problems. This paper
proposes a scheme to integrate heterogeneous resources based on SOA and Web Service, builds
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inter-departmental business systems to conduct feasibility analysis and to verity theoretical basis with
interoperability, cross-industry interconnection and data sharing as benchmarks.
Keywords: heterogeneous system; protocol conversion; SOA architecture layer
C121 A Improved Path Planning For the Mobile Robots
Authors: Zhou Feng
Abstract. Path planning is one of the most important technologies in the navigation of the mobile
robot, which should meet the optimization and real-time requests. A based on Rapidly-exploring
Random Tree (RRT) and Particle Swarm Optimizer (PSO) for path planning of the robot is proposed.
First the grid method is built to describe the working space of the mobile robot, then the
Rapidly-exploring Random Tree algorithm is used to obtain the global navigation path, and the Particle
Swarm Optimizer algorithm is adopted to get the better path. Computer experiment results demonstrate
that this novel algorithm can plan an optimal path rapidly in a cluttered environment. The successful
obstacle avoidance is achieved, and the model is robust and performs reliably.
Keywords: robot, path planning, rapidly-exploring random tree, particle swarm optimizer
C132 The Attack on Mona: Secure Multi-Owner Data Sharing for Dynamic Groups in the Cloud
Authors: Zhongma Zhu, Zemin Jiang, Rui Jiang
Abstract. With the characters of low maintenance and little management cost, cloud computing
provides an effective and economical approach for data sharing in the cloud among group members.
However, since the cloud is untrustworthy, we must provide security guarantees for the sharing data.
Unfortunately, because of the frequent change of the membership, sharing data while providing
privacy-preserving is still a challenging issue. Recently, Liu et al presented a secure multi-owner data
sharing scheme, named Mona, which was claimed that any cloud user could anonymously share data
with others through leveraging group signature and dynamic broadcast encryption techniques.
Meanwhile, the scheme could achieve fine-grained access control, which means that not only the group
members could use the sharing data resource at any time, but also the new users were able to use the
sharing data immediately after their revocations and the revoked users will not be incapable of using
the sharing data again once they are revoked. However, through our security analysis, the Mona
scheme still has some security vulnerabilities. It will easily suffer from the collusion attack, which can
lead to the revoked users getting the sharing data and disclosing other legitimate members’ secrets. In
addition, there is another security shortage in the user registration phase, which is how to protect the
private key when distributing it in the unsecure communication channels. This kind of attack can also
lead to disclosing the user’s secret data.
Keywords: access control; privacy-preserving; cloud computing; collusion attack
C136 An Energy-Saving Virtual-machine Scheduling Algorithm of Cloud Computing System
Authors: Wu Kehe, Du Ruo, Chen Long, Yan Su
Abstract. Even virtual machines has been widely used as the unit to allocate the processor time or
storage spaces by the providers of Cloud Computing systems, the energy consumption pattern of virtual
machines in Cloud Computing system is not clear enough yet now. In this paper, we built an energy
consumption model of the Cloud Computing system, by using statistical method we can estimate the
energy consumption of a virtual machine in a small range of errors in 3%-6%. Then, based on the
model, we proposed a virtual machine scheduling algorithm to improve the energy efficiency of the
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system. First, we set a threshold value of energy consumption for each server in the system, and by
analyzing these work plans submitted by each virtual machine, we tested whether the threshold will
been exceeded or not. Then, by migrate one/several chosen virtual machines to other physical servers
in the system we can reduce the energy consumption of the whole system. Our evaluation shows that
the proposed scheduling algorithm can effectively implement energy-saving goals without significant
decline of the Quality of Services.
Keywords: component; cloud computing; energy consumption efficiency;energy consumption model;
virtual machine scheduling; energy-saving.
C137 A dynamics model of opinion information system
Authors: Du Jin, Du Yanhui
Abstract. With the rapid development of the Internet, BBS, instant messaging, twitter, micro-blog has
become an important channel for people to express their will and exchange information. With the help
of the free, open and efficient network platform, opinion information can more directly, more truly
reflect public opinion in all aspect of life, also become real-time mapping barometer of the social
public opinion. On the other sight, the online public opinion transmit information to form a system
which can be affect by many factor as the government, the traditional media, the netizens and the
network media. Therefore, by the use of advanced information technology to deal with the opinion
information, we analysis the related factors of relationship between them by dynamic evolution rule,
and make a reasonable experiment. All of these can lay the groundwork for future scientific research.
Keywords: opinion information system; dynamic model; public opinion
C141 Implementation of Resource Management System Based on Open Source Computing Platform
Eucalyptus
Authors: Jian-min He, Wei-jie Cao, Rui Min
Abstract. In order to improve the efficiency and convenience of resource management in cloud
computing, the mechanisms of virtual machine deployment and the model of resource management are
discussed in this paper. By analyzing the architecture of IaaS cloud computing platform and the
mechanisms of resource management in cloud computing, the authors develop a cloud computing
resource management system (CCRMS) based on open source software Eucalyptus and Xen, to meet
the needs of users to create three kinds of different system images: Linux virtual desktop image, Web
service image and database service image. The created images are tested in the experimental
environment and the testing results show that the CCRMS is able to effectively manage the resources
and improve the efficiency of management in cloud computing.
Keywords: cloud computing; resource management; IaaS; Xen; Eucalyptus; virtual machine
C149 Analyzing on the failure mode of BFNNs’ learning and its improving algorithm
Authors: Shuiming Zhong, Yinghua Lv
Abstract. In order to improve the learning mechanism of BFNNs, the paper firstly analyzes the failure
mode of BFNNs trained by SBALR, which takes the form of a local cycle. And then by mean of the
sensitivity theory, a disturbance learning algorithm is developed to make the BFNNs that suffer from
learning failure to escape the local cycle. The new algorithm aims to keep the existing learning
performance as much as possible. Experimental results demonstrate the new algorithm’s effectiveness
both on learning effect and learning efficiency.
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Keywords: Learning, binary feedforward neural networks, local cycle, sensitivity
C151 A Instant-Based Qur’an Memorizer Application Interface
Authors: Zameer Ahmed Adhoni, Husam Al Hamad
Abstract. In this paper, we describe an Instant-Based Qur’an Memorizer Application Interface, which
aims at providing a unifying framework for building Qur’an memorizer application.
It includes all
features for memorizing the Qur’an, and it is feasible to be used in latest handsets. Its unique feature of
instant creation gives the user to memorize any Surah or Ayah from the Qur’an. We describe the core
components and design patterns of the proposed memorizer with emphasis on key design criteria.
These criteria aim at providing the necessary scalability and performance on the one hand, and quality
assurance of the Qur’an text on the other.
Keywords: Qur’an, Memorizer
P5 The research of trusted technology under cloud environment
Authors: Lou Ying-hong, Wang Wen-lin
Abstract. In the current cloud environments, there are some problems of information in security and
reliability. In order to establish more flexible and adaptable security mechanism, combining the cloud
and credible is a major research direction in the field of security today. In this paper we studied some
credible technology in cloud computing environment and a new reverse cloud generation algorithms is
proposed. The expected value and hyper entropy of subjective cloud is used to evaluate the reputation
of trust objects, and provide a basis for trust decisions online trading.
Keywords: trusted cloud; subjective trust; cloud model; evaluate information security; cloud security
P7 Multi-Objective TT&C Mission Planning Technique for On-Orbit Service
Authors: LI Jing, GU Xiao-song, YE Gang-qian
Abstract. The multi-objective TT&C (Tracking, Telemetry and Command) mission planning
technique is researched based on the background of both ground-based and space-based TT&C mission
to the OOS (On-Orbit Service) type of “one-station to multi-objective”. Firstly, the characteristics and
constraint condition of OOS TT&C mission are analyzed. Secondly, the space-based and ground-based
TT&C mission planning models are established. Finally, using typical OOS mission as an example, the
method of TT&C resource planning is simulated for ground-based multi-objective and ISL
(Inter-Satellite Link). The optimized design of TT&C events, optimization scheduling of TT&C
resources and automatic implementation strategies of TT&C operations are included to the TT&C
mission in this paper.
The research results show: the ground-based TT&C resource can be saved by
using of space-based TT&C resource. The technical reference can be provided for the implementation
of future spacecraft OOS by the research results.
Keywords: on-orbit service; multi-objective TT&C; mixed integer programming; mission planning;
resources scheduling
P8 A Motion Planning Algorithm Based on Uncertainty Prediction
Authors: Gu Tianyuan, Song Kepu, Miao Changxiu
Abstract. Considering the remarkable influence by uncertainty on a rapidly moving robot, a new
motion planning algorithm is proposed. Firstly, an actual state-based trajectory uncertainty prediction
method suitable for multiple blind areas is presented, which can effectively predict the deviation
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between actual trajectories to come and the planned trajectory. On this basis, the rapidly-exploring
random trees algorithm is introduced to implement the motion planning under uncertainty. Simulations
demonstrated the feasibility of the algorithm. This motion planning algorithm can effectively solve the
speed robot navigating through complex environment with multiple blind regions.
Keywords: motion planning; uncertainty prediction; blind region; RRT
P9 An Improved Association Rules Mining Algorithm Based on Power Set and Hadoop
Authors: Weijun Mao, Weibin Guo
Abstract. The association rules mining plays an important role in data mining. As the rapid growth of
datasets, the computation time and required memory increase seriously. Cloud computing provides
efficient and cheap solutions to analyze and implement the association rules mining algorithms in
parallel. In this paper, we propose an improved association mining algorithm based on power set and
MapReduce programming model, which can process massive datasets with a cluster of machines on
Hadoop platform. The experimental results show that the proposed algorithm can achieve higher
efficiency in the association rules mining.
Keywords: Data mining; Association rules mining; Cloud computing; MapReduce; Power set
P18 Method of architecture core data optimization design based on DM2
Authors: ZHANG Xiaoxue, LUO Aimin, LUO Xueshan
Abstract. Based on the complexity in military information systems architecture design, we proposed
the concepts of architecture optimization design. After analyzed application of logical data meta-model
(DM2) in building architecture data and products, we built a framework of architecture optimization
design. Combined with the building sequence and designing guidelines of architecture data and
products, we proposed architecture core data optimization design process. After analyzing the main
contents of taking architecture optimization design, the goals and the guidelines of building
mathematical models of architecture core data optimization design are put forward. Finally, we took
the optimization design of activity data as an example, built the corresponding mathematical model,
and illustrated relative optimization method. Architecture core data optimization design method affords
a realizable approach of making architecture design solutions more quantitatively, scientifically, and
automatically.
Keywords: Military information systems; architecture; data meta-model; optimization design
P20 Entropy-based model for measuring risk of requirement changes
Authors: YANG Yu, ZHOU Hua, LIU Jun-hui, FENG Yun
Abstract. Software projects face a common problem is the requirement uncertainty and frequent
requirement changes
[1]
. The risk of requirement changes is considerable risk in software project
management. Information entropy can effectively measure subsystem’s degree of uniformity. This
paper proposes a quantitative risk measurement model that could be used to measure risk posed by
requirement changes. The more uniform requirement impact on software project, the smaller the risk,
otherwise the key requirement changes will have a significant impact on the project. This paper
discusses the rationality of the model and gives an instance of this model. The model requires data can
be obtained from enterprise. Experiments show that the model is scientific and rational. It can serve as
a reference for requirement management.
Keywords: risk measure;information entropy;requirement change;software engineering
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P26 Research on Technology of Fuzzy Chinese-Geocoding Method
Authors: Sun Zhen, Qiu A-gen, Zhao Jie, Zhang Fu-hao, Zhao Yangyang, Wang Liang
Abstract. Using fuzzy mathematics principle, this paper, introduced the concept of address elements,
proposed a fuzzy Chinese-geocoding method. On the one hand, through the address elements
identification mechanism, it improved the segmentation accuracy and solved the problem that address
elements are not standard. On the other hand, by calculating the MI indicator it determined the best
matching result. In addition through quality control module, it got the error results and re-matched
them. Based on the theoretical research of fuzzy Chinese-geocoding method, this paper realized the
fuzzy Chinese-geocoding system, and did experiment in Harbin, evaluating it both from matching rate
and positional error.
Keywords: address element; fuzzy Chinese-geocoding; matching rate
P35 Software Analysis of Internet Bots using a Model Checker
Authors: Eri Koike, Shin-ya Nishizaki
Abstract. Internet bots are software agents which perform automated tasks. Recently, Twitter bots
have become popular and are widely used. However, in order to reduce the load onthe Twitter server,
one can only make alimited number of connections to the server. You therefore have to design a
Twitter bot considering the total number of connections. Model Checking is a technique for verifying
automatically whether a model satisfies a given specification. A number of model checkers have been
developed, such as SPIN and UPPAAL. In this paper, we study how to apply model checking to
analysis of load provided by a bot on the Twitter server. We give a model of a Twitter bot for the
UPPAAL model checker. The bot is actually implemented on the Google App Engine. We analyze the
dynamic features of the model with respect to restriction of communication with the Twitter server,
using the UPPAAL model checker. Finally, we discuss the future direction of our work.
Keywords: component; Software Analysis; Internet Bot; Model Checking
P41 Fast Adaptive Bilateral Filtering with Fixed Parameters for Sharpness Enhancement and Noise
Reduction
Authors: Yuanzhong Shu, Ye Chen and Yannan Su
Abstract. In this paper, based on Chaudhury’s fast O(1) bilateral filtering (FBF) and the shift-variant
technique, we present a fast adaptive bilateral filtering (FABF) for sharpness enhancement and noise
removal with good computational efficiency. FABF sharpens an image by increasing the slope of the
edges without producing overshoot or undershoot. Compared with FBF, FABF-restored images are
significantly sharper. Compared with adaptive bilateral filter (ABF), FABF shows a similar
performance in terms of noise removal and sharpness enhancement, while the execution time of FABF
is substantially shorter than that of ABF.
Keywords: bilateral filter, raised cosine kernel, shift-variant technique, sharpness enhancement, noise
removal
P45 Multi-use Conditional Proxy Re-Encryption
Authors: LeQun Mo, GuoXiang Yao
Abstract. This paper presents the first multi-use conditional proxy re-encryption scheme based on
ECC, which is motivated by the following scenario in mail systems: Alice can delegated her decryption
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rights to Bob for the encrypted mails send to her, which contain a specific wordand satisfythe condition
set on the proxy by Alice, and Bob also can delegated the right to others just like Alice through the
proxy, as the condition set by him is satisfied, and so on if required. Furthermore, asanimportant part
for fulfilling our main goal, a new method to obtain the partial re-encryption keys is proposed, and the
security of our schemes is provensecure against chosen ciphertext attacks in the random oracle model.
Keywords: liptic Curve; Contional Proxy Re-encryption; Multi-usability; Chosen Ciphertext Security
P46 Application of Unscented Kalman Filter for Flying Target Tracking
Authors: YAN Hong-lei, HUANG Geng-hua, WANG Hai-wei, SHU Rong
Abstract. According to the nonlinear maneuvering characteristics of flying targets, unscented Kalman
filter is used to achieve a two-dimensional trajectory tracking and predicting in the coordinate of
camera view field. By calculating the target centroid position in the imaging focal plane, the third-order
constant acceleration motion model of two-dimensional is established. Because of the nonlinear
characteristics of flying targets, unscented transform sampling is used to update the states matrix. It`s
not need to solve the complicated Jacobian matrix which cannot be avoided in the ordinary extended
Kalman filtering. Unscented Kalman filter is used to update the target prediction matrix, and the next
state of the target prediction matrix is used to be the trajectory prediction value. Model simulation and
data processing results show that the algorithm brings a great convenience for real-time processing
platform at the coordinate of camera view field.
Keywords: Unscented Kalman Filter; nonlinear filtering; Target Tracking; simulation analyses
P47 Musical instrument recognition based on the bionic auditory model
Authors: Lin Zhang, Shan Wang, Lianming Wang, Yiyuan Zhang
Abstract. We present a bionic auditory system for musical instrument recognition. This system is
designed based on the physiological structures of the human auditory system that are essential to sound
source recognition, such as the basilar membrane and inner hair cells in the cochlea of the inner ear,
cochlear nucleus, and the auditory cortex. A large solo database consisting of 243 acoustic and
synthetic solo tones over the full pitch ranges of seven different instruments (guitar, harp, horn, piano,
saxophone, trumpet, and violin) is used to encompass different sound possibilities of each instrument.
The gammatone model, the Meddis model, and posteroventral cochlear nucleus (PVCN) model are
constructed to imitate the basilar membrane, the inner hair cells, and the cochlear nucleus, respectively.
By using 33%/67% splits between training and test data, a self-organizing mapping neural network
(SOMNN) based on the function of auditory cortex is established to classify the instruments. The
instruments are recognized with an overall success rate of over 75%. This bionic auditory system
indicates high efficiency and high accuracy in musical instrument recognition.
Keywords: Bionic Auditory Model; Musical Instrument Recognition;
Self- organizing Mapping
Neural Network
P51 Research on the Storage Method of Raster Image Based on File Directory
Authors: WANG Chao, GUO Chang-guo, LIU Dong-hong, LIU Yu-jun
Abstract. In order to increase the efficiency of raster image storage, a block file directory tree (BFDT)
framework is introduced in this paper as a new index structure of raster blocks. Through changing the
container of raster blocks from the database to the file system, and depends on the file system’s storage
advantage of high efficiency, the BFDT framework improves the storage method used by GeoRaster.
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The BFDT framework is designed to have a quad-tree structure，and implemented based on the open
source database management system—Ingres. For verification, some comparative experiments of raster
image storage are conducted. The experimental results prove that the performance of the BFDT
framework is more efficient than GeoRaster. Therefore the BFDT framework can effectively solve the
storage problem of massive raster image data.
Keywords: raster image; file directory; block storage; GeoRaster; block file; BFDT framework;
quad-tree; Ingres
P59 Parameters Optimization of PID Based on Improved Particle-Swarm-Optimization
Authors: Xinming Fan, Jianzhong Cao,Hongtao Yang,Xiaokun Dong, Chen Liu, Zhendong Gong,
Qingquan Wu
Abstract. Because the PID parameters settings obtained by classical method fail to achieve the best
control performances, this paper we propose an improved particle swarm optimization (IPSO)
algorithm with inertial weight changes non-linearly and border buffer. Unlikely the original PSO,
firstly, the inertial weight changes non-linearly instead of linearly. Secondly, we provide a border
buffer to the slopping-over particles, making them to fall in the explored space of optima to enhance
the diversity of the particle swarm. The simulation experiments shows that the system whose
parameters are optimized by IPSO has better performances, meanwhile, it proves the effectiveness of
the improved particle swarm optimization.
Keywords: Particle Swarm Optimization; PID controller ;parameters tuning;System simulation.
P61 Revealing research themes and their evolutionary trends using bibliometric data based on strategic
diagrams
Authors：Hongqi HAN, Jie GUI, Shuo XU
Abstract. The paper aims to use strategic diagram technique to detect research themes and reveal their
evolutionary trends in a scientific field using bibliometric data under practical application. Keywords
are selected not only from author-provided and machine-indexed keywords, but also extracted from the
full text so as to eliminate the “indexer effect”. The keywords are then clustered to detect research
themes, which are classified into four categories in a strategic diagram to reveal the research situations
according to their strategic positions. Moreover, the strategic diagrams based on analysis of temporal
dynamics are used to find out the thematic evolution through the similarity index to detect similar
themes of adjacent phases, and the provenance and influence indexes to evaluate interactions of similar
themes. Experimental results showed that the method is effective and useful in revealing research
themes and their evolutionary trends in a scientific field.
Keywords: Theme detection; Thematic evolution; Strategic diagram; Co-word analysis
P67 Attention Rate of Attribute Items: On the Combination of ABAC Rules
Authors: Xinmao Gai, Mingfei Wang, Mingyang Wang
Abstract. In order to solve the problem with conflicts between two Attribute-based Access Control
(ABAC) rules, a method for combining rules from different policies is proposed in this paper. By the
definitions of attention rate of attribute items, which reveals the inherence of an access control
rule/policy while the attention rate of attribute items of a policy can be obtained from those of the rules,
and priority rate of an access request, which reflects the security goal of the system, the concepts of
𝛼 −applicable rule and 𝛼 −applicable policy are defined and the conflicts between rules are divided
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into two categories: irrelevant rules conflict and relevant rules conflict. Finally, methods for eliminating
both of the two types of conflicts are introduced.
Keywords: attribute-based access control; attention rate; priority rate; rule conflict
P71 Numerical Research of an Economic Model Based on Topological Horseshoes Theory
Authors: Guangqun Chen, Xiaorong Hu, Lijuan Chen
Abstract. Recently, research for complex dynamical behavior of financial or economic systems by
means of nonlinear theory and method has become a new hot spot. In this paper, we firstly optimizing
the parameter of system using method of Lyapunov Exponent, and then transform the model to the
Poincaré map by choosing proper Poincaré plane, finally, finding two different types of topological
horseshoe with expanding in one direction in the phase space of the corresponding the Poincare map. It
is not only found strictly that the topological horseshoe exists widely in the economic model, but also
verifies strictly the chaos in math to reveal the dynamical principle of chaos.
Keywords: economic model; chaos; topological horseshoes; Poincaré map; numerical computation
P79 Zero-Watermark Scheme for 2D Vector Drawings Based on Mapping
Authors: Zhao Hua, Du Shoujian, Zhang Daozhen
Abstract. This paper proposed a zero-watermark scheme for 2D vector drawings based on mapping
which few researches have been conducted on till now. In our scheme, The watermark is not embedded
into but built or picked up from the original vector drawings by mapping the most two important
characters the length ratio and angle to a dot picture which can also be saved in a vector format.
Experimental results demonstrate that the proposed scheme is lossless and robust enough against the
ordinary attacks such as rotate, scale, transplant (RST) as well as their combinations, even cropping
and adding attacks with higher accuracy and computation efficiency and moreover it has a distinctively
visual effect. Generally it shows better performances than the previous ones and is faithful enough for
the authentication.
Keywords: 2D Vector Drawings; Zero-Watermark; Mapping
P81 The design and implementation of a mobile learning platform Based on Android
Authors: Song Wei
Abstract. In order to solve the problem of mobile learning, the design and implementation of a mobile
learning system based on Android operating system is introduced in this paper. Mobile learning brings
us to new impressions of whenever and wherever there is a possible study through effective
combination of digital learning and mobile computing technology. Mobile learning is regarded as a
kind of indispensable learning tool in the future. There are many functions on the platform such as user
management, course selection, course download, online tutorials and online test functions and so on.
The learner can, whenever and wherever possible, learn by intelligent mobile phone, panel computers
or other portable devices. Anyone can open course resources and use them in a convenient way. The
platform has good operability and a very optimistic future business-wise, and it provides us a better
solution for easy mobile learning.
Keywords: Android; 3G; Internet of things; mobile learning
P84 Comparison and Assessment of Different Image Registration Algorithms Based on ITK
Authors: Zhou Zhenhuan
Abstract. A lot of image registration algorithms are proposed in recent year, among these algorithms,
which one is better or faster than the other can be only validated by experiments. In this paper,
ITK(Insight Segmentation and Registration Toolkit) is used for verifying different algorithms as a
framework. ITK framework requires the following components: a fixed image, a moving image, a
transform, a metric, an interpolator and an optimizer. Dozens of classical algorithms are tested under
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the same conditions and their experimental results are demonstrated with different metrics,
interpolators or optimizers. By comparison of registration time and accuracy, those practical and useful
algorithms are selected for developing software in image analysis. These kinds of experiments are very
valuable for software engineering, they can shorten the cycle of software development and greatly
reduce the development costs.
Keywords: image registration; ITK; algorithms comparison; registration framework
P87 ASCMS: an Accurate Self-Modifying Code Cache Management Strategy in Binary Translation
Authors: Anzhan Liu, Wenqi Wang
Abstract. Self-modifying code poses potential problems in binary translation. When the original
source code had written by itself, the translated code block from source code must be retranslated.
Self-modifying code must be accurately emulated by the runtime.
To improve the translation
efficiency of self-modifying code, this paper design and realize a new policy named ASCMS for
self-modifying code cache management. The ASCMS provides a precise positioning to a translated
block, not to a trace or the whole code cache. Through the simulation experiments, The ASCMS has
3.95 times increase to self-modifying code in binary translation.
Keywords: self-modify code; binary translation; code cache management; ASCMS
P88 Optimization for the locations of urban e-commerce distribution network based on a genetic
algorithm
Authors: Aihua Xiang, Dong Wang
Abstract. A mathematical model and a genetic algorithm are proposed to solve a logistics network
optimization problem. Combined with the characteristics of urban logistics and e-commerce, the sum
of transportation costs, construction costs and maintenance costs are considered in the model to
describe the total logistics cost in the network. Since the model is a NP problem, the genetic algorithm
is used to solve it. At last, an example is applied for the model validation. From the analysis of the
result, it is clear that the mathematical model can effectively solve the logistics network optimization
problem and the genetic algorithm is appropriate integer programming algorithm.
Keywords: logistics network optimization; urban e-commerce distribution; genetic algorithm
P89 The Maize Embryo Image Acquisition and Variety Identification Based on OTSU and K-means
Clustering Algorithm
Authors: Donglai Ma, Hong Cheng, Wenjing Zhang
Abstract. In order to evaluate the feasibility of maize variety identification with the embryo
characteristics, the paper selected four maize varieties, and scanned 70 images of each variety. It first
used OSTU algorithm to segment the embryo images from the whole maize grain image. Then, it
extracted six characteristic parameters of embryo from the embryo image, with connected component
labeling and multi-object contour extraction algorithm. Finally, it identified the maize varieties with the
six kinds of embryo’s characteristic parameters, using the k-means clustering algorithm. With these
methods, the variety identification rates of the four maize varieties, including 280 test samples, are all
more than 94.12%. The experimental results demonstrate the effectiveness of maize variety
identification based on embryo morphology characteristics.
Keywords: variety identification; embryo characteristic; k-means cluster; maize
P96 Commodity Futures Price Prediction and Trading Strategies-- a Signal Noise difference Approach
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Authors: Zheng Jinhao, Peng Shoukang
Abstract. This paper introduces the signal noise difference method and applies this method into the
commodity futures price prediction. Based on the prediction rules mined from the data of 25 potential
prediction indicators of SHFE CU, a corresponding transaction strategy is established. And we use the
market data from 2009 to 2013 to test our transaction strategy, which obtains a result of 147.85%
annual yield. In addition, several improvements are discussed to optimize this model.
Keywords: data mining; signal noise difference; price prediction; SHFE CU
P98 Model Driven Programming in Data Preprocessor Design
Authors: Dangwei Liang, Feiyue Ye, Hao Shi, Dong Xiao
Abstract. As business data’s complexity and diversity in software systems, data pre-processor has
become an indispensable part of software. However the common data preprocessor has some
shortcomings: poor structure flexibility, difficult of extension and maintenance, poor data processing
ability, long development cycle and other shortcomings. To solve these problems, this paper proposes a
general data pre-processor design method based on model driven architecture. Using the ideas of model
driven architecture, with the aid of modeling tools and modeling language, preprocessor demand model
is established firstly, and then based on this model, establish the preprocessor platform independent
model, and finally translate into preprocessor code. The method applied to the design of the data
preprocessor in the billing system, verify its validity and it can be easily applied to the design of other
kinds of data preprocessor.
Keywords: Data Preprocessor; Model Driven Architecture; Platform Independent Model; Software
Modeling
P100 The Research and Simulation of the Satellite Network Routing Algorithm based on Game Theory
Authors: Rongyan Qiao, Xinguo Zhao
Abstract. According to the characteristics of the finite energy of the satellite network nodes, in order to
solve the problem of some nodes losing lots of energies because of uneven network flow, this paper
proposes a game model of routing algorithm based on ‘the mechanism of price’, and the model of
Bayesian-Nash equilibrium strategy is resolved. The results of the simulation verified illustrates that
the algorithm have a certain role in reducing network transmission ‘hot spots’ and improving the use
rate of nodes and fairly using the network resources, etc.
Keywords: Satellite network; Game theory; Bayesian-Nash equilibrium strategy
P101 Optimal Web Service Composition Based on Context-awareness and Genetic Algorithm
Authors: Yuan Yuan, Xiuguo Zhang, Wenxi Sun
Abstract. This paper presents a Web service composition method which supports the associations of
services in order to improve the success rate of Web service composition and the quality of the
composite service. Firstly, a context-aware web service composition model is built and this paper
introduces the concept of service-correlation matrix which means presenting the context of service
components in the form of matrix and dynamically updating the matrix with context-awareness
technology. Secondly, this paper introduces genetic algorithm into web service composition.
Experimental results indicate that the method in this paper effectively reduces the deviation between
the theoretical value and the practical value of the context properties of the composite web services
which are significantly associated with others.
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Keywords: Context-aware; Service-correlation; Service Composition; Genetic Algorithm
P107 Research on the Effect of the Adjustable Parameter Applied to Information Theoretic Criteria
based Spectrum Sensing Method
Authors: Tingting Liu, Jian Zhang, Zhiming Wang
Abstract. Cognitive radio is now emerging as a popular technology to end the spectrum scarcity.
Cognitive radio includes some essential components such as spectrum sensing, power allocation,
interference controlling and dynamic spectrum access in which spectrum sensing is the foremost. Blind
sensing method attracts much attention for its easiness to implement and the few requirements for prior
knowledge. The Information Theoretic Criteria (ITC) based spectrum sensing method is a promising
blind sensing technology that can reliably sense the activity of primary user with few prior information.
However, it cannot agilely set the false alarm probability which is usually required in communication
systems. In this paper, a research on the effect of the adjustable parameter is carried out. The validity of
this method is established by simulation in several scenarios with different numbers of sampling
samples and receiving antennas. The simulation results show that the adjustable parameter can change
the false alarm probability according to the requirement of the system and also the sensing method with
an adjustable parameter can overcome the noise uncertainty.
Keywords: Spectrum Sensing; Energy detection; Information Theoretic Criteria
P108 Study on Virtual-Measure Kalman Filter Algorithm in Radar Networking
Authors: ZHAO Wen-bo, DING Hai-long
Abstract. Using Kalman filter algorithm (KFA) in tracking target in radar networking system (RNS),
measure-value of target in networked radar (NR) polar coordinate system has the nonlinear relation
with state-value of target in fusion center rectangular coordinate system of RNS. The nonlinear relation
does not satisfy linear requirement of KFA application. So this paper virtualizes fusion center
rectangular coordinate system as the measure coordinate system of KFA. Through this way, original
nonlinear relation is simplified as a linear form. By means of modeling noise of virtual measure
coordinates, and constructing the initialization strategy, KFA can be used to solve the problem of state
estimation in RNS. The simulating verification shows that virtual-measure KFA proposed in this paper
is more precise than extended KFA (EKFA) used for state estimation in RNS.
Keywords: Radar Network; Kalman Filter; statistical characteristic;
initialization strategy
P109 Online Resource Monitoring Model in Cloud TV
Authors: Chao Xu, Xuewen Zeng, Zhichuan Guo
Abstract. In order to solve the problem of the user experience degradation caused by the resource
competition among the applications in cloud TV, we present an approach of online resource monitoring
model (ORMM), which is applied in the television service engine (TVSE) framework. Firstly, specific
to the shared resource and the exclusive resource, an appropriate resource usage sampling method
using system calls and service arbiter is introduced, which simultaneously monitors all types of the
system resources. Secondly, to support the most important interactive video application, a Hidden
Markov Model based application anomaly detection algorithm using the slide window is designed in
consideration of the state transition of the interactive video application. Finally, based on the testing in
Android cloud TV, a performance evaluation illustrates the parameters selection of the model, and the
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detection precision of our algorithm is superior to other popular anomaly detection algorithms about
20%.
Keywords: Cloud TV; resource monitoring; anomaly detection; Hidden Markov Model
P112 Research on Web Mapping of Vector Nautical Charts Based on HTML5
Authors: PAN Mingyang, PANG Bobo ,LI Chao, WANG Deqiang, MIN Donglong, ZHAO Depeng
Abstract. According to the issues encountered by traditional web chart technologies, the paper,
following the boom of HTML5, did a research into web mapping of vector nautical charts based on
HTML5. The research mainly includes: 1) System architecture for the HTML5 based web chart
application, in which HTML5, CSS and Javascript are used to build and style the client Web chart
pages, and Node.js is used to construct the server-side to provide both HTTP and WebSocket services;
2) Organization of vector chart data to obtain more efficiency of data network transmission and data
procession, for which original S-57 charts are converted into Shapefiles and a Javascript framework is
designed to read and parse the Shapefiles for the client; 3) Vector nautical charts display on Web page,
for which a Javascript display framework and rendering functions for chart points, lines and areas
symbols are designed based on HTML5 Canvas. An application of web chart based vessel tracking is
tested further to verify the proposed methods. The results showed that HTML5 is suitable to develop
web vector chart applications, although there are several problems waiting to be solved such as can’t
comply with S-52 display standard completely.
Keywords: HTML5 Canvas; Web mapping; Vector nautical charts; Shapefile; S-57; S-52
P114 Research on runoff predicting based on wavelet neural network conjunction model
Authors: Fanping Zhang, Huichao Dai, Deshan Tang, Yixiang Sun,
Abstract. A new hybrid model that combines wavelet and artificial neural network(ANN) called the
wavelet wavelet neural network(WNN) model is proposed and applied for runoff time series prediction.
In this paper, BP network is selected as the neural network, the Morlet wavelet is chosen as the hidden
excitation function of precipitation model, the MATLAB is used to write WNN prediction program and
the the model is trained and tested by the year runoff time series of Tangnaihai Station located in
Yellow River upper stream from 1956 to 2008. The hybrid model (WNN) was compared with the back
propagation artificial neural network (BPANN) model. The performance of forecasting accuracy of the
WNN model is relatively high comparing the traditional approach. The hybrid model (WNN) is a
reliable and practical method for runoff prediction.
Keywords: runoff prediction; time series; wavelet analysis; Morlet wavelet; artificial neural network
P120 Driver’s Seat Belt Detection in Crossroad Based on Gradient Orientation
Authors: Dian Yu, Hong Zheng, Cao Liu
Abstract. Seat belt detection is one of an important detecting function and is widely needed in the field
of intelligent transportation system. However, research for which is still limited in terms of the
increasing requirements at present. In this paper, one algorithm for detecting vehicle seat belts on road
is proposed. And a type of feature based on gradient orientation is employed to describe and detect seat
belts, according to the method discussed in this paper. After the image pre-processing, the front
window location and the human face detecting, this feature is finally extracted in the selected region
and the conclusion is given by counting the seat belt feature in the area that close to the right side of the
detected human face area. Another approach is also designed in case that the human face detection
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fails. Tests on high-definition vehicle images show that proposed algorithm is capable of extracting
belt-feature under difference circumstances and it is also effective to tell whether the driver has
fastened its seat belt.
Keywords: Seat Belt Detection; Pixel Gradient Orientation; Human Face Detection
P121 On Operation Performance Evaluation and Optimization Based on SUPER-SBM DEA Model in
Railway Industry in China
Authors: Li Zhongdong
Abstract. Taking railway industry in China for example, SUPER-SBM DEA model of existing
uncontrollable factors are adopted to analyze and evaluate the operation performance in 30 provinces in
China. Based on detailed analysis of railway industry operation features, Optimization of related slack
variables is analyzed. Suggestions are put forward as follows: current railway transportation capacity
should be reasonably used; input factors should be reasonably collocated; input capital should be
accumulated through various channels.
Keywords：SUPER-SBM model; Railway operation performance; Uncontrollable factors
P122 A Method for Star Extraction of the Air-borne Star Sensor during the Daytime
Authors: ZHANG Xiang, CHEN Pu, LU Zhidong
Abstract. This paper proposes a new approach to star image denoising, recognizing and centroiding for
the airborne application, especially during the daytime. To extend attitude determination of aircraft to
daytime, one prerequisite is to precisely obtain the centroid of the target star. To date, there has not
been an adequate analytical model and experimental method to solve this problem effectively.
Generally, three main problems of degraded images lie in the low signal-to-noise ratio, high intensity of
the background and distorted star shape. To clearly validate the given method on star recognition, we
focused on the static environment, without the severe distortion and motion blur. To demonstrate the
proposed approach, an experiment was conducted with a camera and host computer. Specifically, it
consisted of the star image acquisition, image processing and star recognition. Due to the denoising
process, the noise component was eliminated effectively. Besides, by the connected region analysis and
minimal area screening, the star pattern can be completely isolated. On top of that, the percentage of
recognition amounted to 86.7% and the centroid precision was within 1/10 pixel. The experimental
results demonstrate the potential of the proposed approach to the star recognition and extraction, during
the daytime for airborne application.
Keywords: star sensor; star extraction; wavelet de-noising
P128 Study on Prediction System for Disaster of Water-inrush From Coal Floor
Authors: Demin Liu, Huiqing Lian, Fei Li ,Linshen Gao
Abstract. Mine hydrogeology conditions are very complex in china, especially in North China type
coal mine. When the coal is being mined, it is seriously threatened by Ordovician karst water with high
pressure. Water inrush accidents often happen in North China type coal mine which has become an
important factor affecting the safety in production of coal mine. Taking Dong Shan coal mine as an
example, the paper has analyzed principle of water-inrush from coal floor of the mine by Summary of
mine water inrush in the coal mine. Early-warning indexes of water inrush which include water
temperature, water pressure, stress and strain were built. Structure of prediction system for
water-inrush disaster was designed, and the hardware and software of the system were developed.
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Industrial test for the prediction system was done in 51523 face. Practice shows that the prediction
system could monitor Early-warning indexes of water inrush in real time, and according to the early
warning indexes to distinguish the mine water inrush risk which can provide the foresight of the
information for preventing water inrush disaster.
Keywords: Northern China Coalfield; water inrush from coal floor; early warning system; remote
monitoring and control
P129 An improved Collaborative Filtering Model Considering Item Similarity
Authors: Yeifei Zha, Yuqing Zhai
Abstract. Because of its simplicity and effectiveness, collaborative filtering (CF) became one of the
most successful recommendation algorithms. User-based CF is one classic method of CF algorithms. In
order to solve the problem that common rating items are often too few to be used to effectively
calculate the similarity of two users in user-based CF, we proposed an improved collaborative filtering
model with item similarity called ISCF in this paper. In ISCF model, the similarity of items was
considered in user-based collaborative filtering, which contributes to alleviate the problem of data
sparsity and therefore calculate the similarity of user. Experimental results illustrate that our approach
ISCF outperforms the average method and user-based CF. Compared with user-based CF, the average
improvement in the percentage of ISCF at MAE and RMSE are 21.9% and 17.7%, respectively. In
addition, our approach ISCF can predict more items than user-based CF, and the average improvement
in the percentage of ISCF at prediction diversity is 33.86%.
Keywords: collaborative filtering; recommender system; user-based CF; item similarity
P130 The Improved Particle Filter Algorithm Based on Weight Optimization
Authors: Jun Zhu, Xiaolong Wang, Qiansheng Fang
Abstract. Particle filter algorithm is to achieve recursive Bayesian filter through the simulation method
of non-parameter Monte Carlo, It based on sequential importance sampling ,and can not avoid particle
degeneration problem, a way to overcome the particle degradation is re-sampling, However sample
impoverishment will appear in the process of re-sampling, This paper proposes an improved particle
filter method based on optimized weight, the method solves the particle impoverishment problem to a
certain extent; The simulation results show that, the improved particle filter algorithm proposed in the
paper can effectively improve the estimation precision of particle filter algorithm.
Keywords: Particle filter; re-sampling; particle impoverishment; weights optimization
P132 An Energy-saving Algorithm in Networked Embedded System Based on Critical Tasks Served
First Strategy
Authors: Xue Bing Zhao Zhigang Wang Lu, Zhu Xiaoli
Abstract. Lots of collaborative applications that contain a number of dependent tasks run in networked
embedded system, such as wireless sensor network, Cyber-Physical-System and so on. For the reasons
that deadlines of some collaborative applications are not so hard usually and lifetime of whole system
depends on energy dissipation, it is meaningful to figure out a good strategy for balancing delay with
system energy dissipation. Considering this issue, our research focuses on trying to minimize total
system energy dissipation for extending lifetime of whole system, on the premise that delay of finish
time is acceptable. In this paper, we point out which tasks are critical among independent tasks from
the perspective of energy-saving and propose BESF (Biggest Energy Span First) algorithm thatfirst
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allocates the task with biggest energy span. Actually, BESF algorithm references BEATA algorithm,
however, BESF could not only further decrease energy-consumption of whole system comparing with
existing related algorithms, like BEATA, GEATA,but also still ensure that the finish time is tolerable.
Experimental results show that in most situations, BESF algorithm is able to save more energy
comparing with existing algorithms.
Keywords: heterogeneousnetworkedembedded system; BEATA algorithm; energy consumption; task
allocation
P133 A Parallel Domain Decomposition FDTD Algorithm Based on Cloud Computing
Authors: Haiming Lin, Xiaohu Liu, Kangyu Jia, Wei Fu
Abstract. This paper presents a parallel domain decomposition finite difference time domain
(DD-FDTD) algorithm based on MapReduce architectural pattern in a Hadoop cloud computing cluster.
The algorithm is implemented on a 6-nodes Hadoop laboratory test cloud computing cluster to compute
the electromagnetic fields of lightning in the downtown area in Shanghai city, PR China. The speedup
ratio under different numbers of computational subdomains is evaluated. It shows that the maximum
speedup ratio of the algorithm implemented on our Hadoop cluster is about 2.4, which will increase
with the scale of the mesh model and the nodes of the Hadoop cluster.
Keywords: Cloud computing; MapReduce; Hadoop; FDTD method; Domain Decomposition method;
Electromagnetic Fields of Lightning
P134 A Simple Way For The Detail Component Design of Aircraft Wings
Authors: Liu Guochun, Zhou Tao
Abstract. Due to the lack of the wings detail design progress and the limitation of ordinary detail
design ways for the complicated design of wings, while a new wing detail design process was proposed
based on traditional wing structural design approach. The process involves taking loads on initial
proofing structure, structural design, FEM (Finite Element Methods) analysis, etc. According to the
wing structural characteristics, it makes the reaction forces as the input loads for the detail design. The
detail components are designed based on the new design process which meets to all the design
requirements. It shows that the new design process is feasible and available.
Keywords: wing structure; FEM analysis; detail design; component design
P137 A New Model Language for Cyber Physical Systems
Authors: Liu Mingxing, Ma Wubin, Dengsu, Huang Hongbin
Abstract. Cyber Physical Systems are an emerging discipline that integrates computation and physical
processes. With the computation field developed maturely, the major challenges of the implementation
of CPSs are the informational abstraction of physical processes and the feedback control on physical
processes. The aim of this paper is to provide a description methodology of the physical entity control
part, which we named CPSs Hyper Control Markup Language (CPSsHCML). Through the analysis of
TV control part, which is an important physical entity in smart home that is a typical CPSs, the
classification of CPSs Hyper Control is obtained in following four aspects: Function Switch (FS),
Discrete Enumerative (DE), Continuous Interval (CI) and Angle Direction (AD). Our work focuses on
the definition and description of the attribute fields of global properties and the four CPSs Hyper
Controls. In addition, an application of CPSsHCML, which we mentioned above, Sony KLV-40F300A
TV in smart home, is provided to show that the prospects of CPSsHCML are promising. Furthermore,
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some important research challenges and suggestions in future are outlined in brief.
Keywords: Cyber Physical Systems; Hyper Control Markup Language; Smart Home
P138 Enhanced Film Grain Noise Removal for High Fidelity Video Coding
Authors: Inseong Hwang, Jinwoo Jeong, Jangwon Choi, YoonsikChoe
Abstract. In this paper, we propose a novel technique for film grain noise removal, which can be
adopted in high fidelity video coding. Film grain noise enhances the natural appearance of high fidelity
video, therefore it is should be preserved. However, film grain noise is a burden to typical video
compression systems because it has relatively large energy level in the high frequency region. In order
to improve the coding performance while preserving film grain noise, the noise removal and synthesis
process is used. We propose a film grain noise removal technology in the pre-processing step. In
pre-processing step, film grain noise is removed by using temporal, spatial and inter-color correlation.
Specially, color image denoisng using inter color prediction provides good denoising performance in
noise concentrated B plane because film grain noise has inter-color correlation in the RGB domain.
The results show that the coding gain of denoised video is higher than for previous works,while the
visual quality of the final reconstructed video is well preserved.
Keywords: Film grain noise; video denoising; inter-color correlation;bilateral filter; high fidelity video
coding
P140 Study on Recognition methods of housing vacancy based on digital image processing
Authors: Wei Yao, Guifa Teng, Hui Li
Abstract. At present, China real estate industry for several years has undergone the tremendous changes,
accompanying the various rumors on haunted house are often mentioned. Housing vacancy rate statistics
community is complicated. Because it is not the same like the census to census operations and can only
use the indirect method of investigation, which makes findings unreasonable. For example, someone has
multiple housing and has a live recording; the use of water, point still does not reflect the real vacancy
rate. Therefore, whether it is water, electricity meters, gas and other methods are incorrect. Due to the
lack of sophisticated statistical techniques, the number of vacant housing so far is still an open question.
Studies of housing vacancy rate based on digital image processing are a new subject. This paper presents
a kind of the image threshold segmentation by image correction, the relationship between the mass
center coordinate of windows, finally get the black light rate method, using matlab and VC joint
programming to achieve statistical black light rate and finally obtain the housing vacancy rate system.
Simultaneously compared with the common methods of the water meter and electric meter checking of
statistical vacancy rate, verified the validity of the method.
Keywords: image recognition; housing vacancy rate; image correction
P141 Research on Multi-tenant PaaS Cloud Security on Java Platform
Authors: Jia Chang-yun, Zhu Min, Liu Xiao-ming
Abstract. This paper focuses on the potential security risk embedded in the model of multi-tenant
sharing virtual machine service. Also the characteristics of current Java virtual machine standard model
and the typical problems that may be encountered under the multi-tenant circumstances will be further
discussed. Additionally, major solutions to the above problems of Java application server, including
MVM, I-JVM and improved OSGI model, will be deeply analyzed in this paper. Through introduction
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to the GAE of commercial multi-tenant PaaS platform, this paper presents a clear and precise
discussion and clarification to the solutions of security problems on the platform of multi-tenant PaaS.
Keywords: Java; PaaS cloud; security; Multi-tenant
P142 New Features Acquisition of Text with Cloud-LDA Model
Authors: Maoyuan Zhang, Fanli He, Shuiyin Chen
Abstract. This paper probes into how to improve Information Retrieval by changing the feature
distribution of the text. It introduces Cloud Model theory into Latent Dirichlet Allocation (LDA) Model
and build a new feature selection system. LDA Model is used to mine the underlying topical structure.
Each topic is associated with a multinomial distribution over words which are semantic related. But
there is doubt that themes are relevant with each other in the light of semantics. Based on LDA model
presented probability distribution of vocabulary in text, the new system with Cloud Model theory can
automatically simulate feature set whose contribution degree is high in the text. Results show this
feature set has less features but higher classification accuracy, thus obviously better than currently
popular feature selection methods. If the query is matched to words with high contribution degree, the
more these words are, the more relevant the article searched out is with the query. NTCIR-5 (the 5th
NII Test Collection for IR Systems) collections of Experiment on SLIR (Single Language IR) show
that this method achieves an obvious improvement compared with some other methods in IR.
Keywords: Information Retrieval, feature, Cloud Model, LDA model
P143 Establish expert system of transformer fault diagnosis based on dissolved gas in oil
Authors: Donglai Ma, Wenjing Zhang, Wei Yao
Abstract. In order to avoid economic loss caused by transformer fault, it needs to monitor the
transformer status in real-time, discovery and handle the transformer fault timely.
Using association
rule analysis method to mine fault information of transformer, analyze the reliability between the
transformer fault and characteristics, revealing the correlation degree of them. Based on the analysis of
transformer fault, it put forwards to represent knowledge with production method based on rules, build
knowledge database using decision rules, and construct the basic expert system model, which lays the
foundation for intelligent diagnosis of transformer. The model uses dissolved gas in oil, electrical
parameters etc. as fault judgment, evaluate transformer condition, and enrich the knowledge base of
expert system with the evaluation results.
Keywords: Dissolved Gases Analysis, transformer; knowledge base; Expert system, Association rules
P144 A College Teaching Building Lighting Control System Based On Power Line Carrier
Authors: Yanming Huo, Haochen Wang, Xiaoying Zuo, Zhimin Cui
Abstract. With the university enrolment increasing, the registered students are becoming more and
more. Almost all the universities are in the state of saturation. This leads to a big trial for the strength of
the building. In the process of using the teaching buildings, lights are used more frequently and
massively. Meanwhile because of the poor management and the students’ lack of saving up electricity, a
lot of energy is wasted, at the same time resulting in the pollution for the environment. In order to keep
pace with the idea of a low-carbon life, and to provide convenience for the students’ study, this essay
introduces a new light-control system with artificial intelligence. This system can control all the lights
by knowing the distribution of the students, the light intensity, the total number of the students, even
the number in each classroom. Each sensor connects with each other by Power Line Carrier. This can
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greatly reduce the waste of the energy and the cost of building this system.
Keywords: The teaching building; Power line carrier; SCM STC89C52
P146 A Multi-Level Grid Partition Method for Enterprises Distribution Data
Authors: Zhang Zhang, Yang Yang Zhao, Li Juan Duan, A Gen Qiu, Fu Hao Zhang, Kun Wang Tao
Abstract. In order to use enterprises distribution data effectively and maximize their social and
economic value, a multi-level grid partition method for enterprise distribution data is proposed which
divides the voluminous data into reasonable size. This method uses the provinces or municipalities of
nationwide as coarsest division, then a quad-tree is constructed to partition the points of enterprises
according to their location. Each node in the quad-tree has a limit of points, when the number of points
in a node beyond the limit, the node is divided into four nodes with roughly the same number of points
in each quadrant. This process proceeds recursively until no node contain points more than the limit.
Enterprise distribution data of Harbin is used in experiments to test the feasibility and effectiveness of
this method, the results of the experiments show that enterprises distribution data were divided rapidly
and accurately to the grid, which improve the applicability of the data and the convenience of data
integration.
Keywords: mutil-grid; the national organization code;spatial information; quad-tree; grid divition
P149 An Improved Genetic Algorithm based on Local Modularity for Community Detection in
Complex Network
Authors: Yang Xinwu, Li Rui
Abstract. Community detection has been an issue in complex network research. In the paper,
according to the definition of weak community, we firstly propose a local modularity and then design a
new more efficient mutation operator based on local modularity. The mutation operator selects the
neighbor node that can best embody the definition of weak community structures as mutated result,
which makes the mutated candidate solution closer to the optimal solution. Furthermore, to accelerate
the emergence of the optimal solution, the roulette selection is integrated into a uniform crossover
operator. On the basis of above works, an improved Genetic Algorithm based on the local modularity
(IGALM) is presented for Community detection.The proposed algorithm is tested and compared to
other algorithms on both computer-generated network and real-world networks. The comparative
experimental results reflect that the new algorithm is feasible and effective in small and large scale
complex networks.
Keywords: complex network; community detecting; genetic algorithm;
local modularity
P159 Dividing for Combination: A Bootstrapping Sentiment Classification Framework for Micro-blogs
Authors: Songxian Xie, Ting Wang
Abstract. There are many challenges for sentiment classification of user-generated content (UGC) on
social media platforms such as micro-blogs. Context dependence, which has been the most challenging
problem, is focused on in this paper, and a novel semi-supervised framework is proposed to address the
problem. By dividing the feature space of sentiment classification into two parts including the general
features and the context features, a general classifier and a context classifier are learned separately in
the two partial feature spaces, and a semi-supervised framework is developed to combine the general
classifier and context classifier into a bootstrapping classifier. Experimental results show that both the
general classifier and context classifier outperform traditional lexicon-based classifier, and the
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combined bootstrapping classifier outperforms supervised classifier upper bound. The proposed
semi-supervised framework is flexible and effective in solving the context dependent problem of
sentiment classification for micro-blogs without the need of labeled data.
Keywords: sentiment classification; idioms; context dependence; classifier; social media
P161 Hadoop Cellular Automata for Identifying Rumor in Social Networks
Authors: Hui Zhang, Ji Li, Yueliang Xiao, Hui Zhang, Ji Li, Yueliang Xiao
Abstract. Rumors are unavoidable in social networks and spreading through social networks. In this
paper, we introduce three roles, which are rumor maker, accomplice and innocent, into social networks.
Rumor makers are people who distribute rumors in social networks. In order to propagate rumor as
more people as possible, rumor maker cannot achieve this goal without others’ help. So that
accomplices are people who help rumor maker spread rumors. Innocent are people who do not share
help for rumors spreading. We introduce an extended cellular automata algorithm, i.e. Hadoop Cellular
Automata (HCA), to simulate people’s tweeting activity in social networks. We deploy our
experiments on an open source platform, Hadoop. Our result shows that Hadoop Cellular Automata is a
liner algorithm. Also HCA can simulate people’s tweeting activity very well and can pick out rumors
easily in social networks.
Keywords: social networks; cellular automata; rumor spreading
P162 An Implementation of Montgomery Modular Multiplication on FPGAs
Authors: Xinkai Yan, Guiming Wu, Dong Wu, Fang Zheng, Xianghui Xie
Abstract. Modular multiplication is one of the most important operations in the public key
cryptographic algorithms. In order to design a high-performance modular multiplier, we present a novel
hybrid Montgomery modular multiplier over GF(p) on FPGAs, which employs Karatsuba and Knuth
multiplication algorithms in different levels to implement large integer multiplication. A 9-stage
pipeline full-word multiplier is proposed for the 256-bit multiplication with 4-level recursion. The
performance of our modular multiplier is improved through optimizing the pipeline and reducing
carry-chain latency of the modular adder. On the average, our modular multiplier can perform one
256-bit modular multiplication in 3 cycles. We can integrate 13 modular multipliers on a Xilinx
Virtex-6 V6VSX475T FPGA. The experimental results show that the throughput of 856.9 million
modular multiplications per second can be achieved and the hybrid Montgomery modular multiplier
has an outstanding performance in the situations which need plenty of continuous multiplications.
Keywords: Hybrid; Montgomery modular multiplication; Elliptic curve cryptography (ECC)
P164 A steered molecular dynamics method for receptor-ligand unbinding based on genetic algorithm
Authors: Junfeng Gu, Xicheng Wang, Yingying Yang
Abstract. Steered molecular dynamics (SMD) method provides a new tool to investigate the
structure-activity relationship, but its application is restricted severely when the real dissociation
pathway is tortuous. In this paper, a self-adaptive SMD method is designed for protein-ligand and
protein-protein unbinding. During the unbinding process, the pulling direction varies automatically
with a specified genetic algorithm to find the pathway which can be passed through with minimum
force, so the rupture force of the unbinding process can be minimized and a rational dissociation
pathway can be found for the receptor-ligand complex. For evaluating the efficiency of the proposed
method, several representative protein-ligand complexes and protein-protein complexes are simulated
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to pull the ligands away from the receptors. Compared with the conventional SMD, the new SMD
scheme gains different dissociation pathways, and these new pathways generally have smaller rupture
force and lower energy barrier.
Keywords: Genetic algorithm; Steered molecular dynamics; Receptor-ligand;
Dissociation pathway;
Optimization
P166 Bag of Visual Words for Cows’Basic Activity Recognition
Authors: Wen Changji，Zhao Xin，Zhou Cuijuan，Chen Xueying，Guo Qing
Abstract. The manual intervention before the birth dates is very important to reduce the dystocia rate
and enhance the survival rate of calves effectively. Information acquisition of the cows’ basic sowactivity modes and regulars is one of judgments of manual intervention critical points. Now, the
mainstream way has limitations that external sensors are used to obtain information by attaching to the
specific positions. So, we proposed a method for recognizing the cows’ basic sow-activities by using
bag of visual words under the video monitoring in this paper. Firstly, this method detected the
remarkable areas of the cow activities in the videos by using spatial-temporal interest points. Secondly,
it clustered the quantitative features into visual words and then constructed the visual dictionary for
describing the activities. Finally, it used the nearest neighbor classification for the activity classification
and recognition. This method was tested in different experimental setting for recognizing the typical
basic sow-activities such as walking, lying and look-backing. One was tested on 90 groups of videos
under given visual angles and the other on 30 groups of videos under the random perspective. The
experiment results show that the method proposed in this paper achieve satisfactory accuracy of cows’
basic sow-activity recognition.
Keywords: Basic activity recognition; Bag of Visual words; Spatial-temporal interest point; Cows
P168 A Method Based on Random Search Algorithm for Unequal Circle Packing Problem
Authors: Shang Ying, Chu Jizheng
Abstract. We propose a random search algorithm to resolve the problem of packing circles into a
rectangular container. With our method, all the circles are put into a large space randomly; and then by
introducing the bow shift area, the searching space can be reduced and the local optimal solution can be
list. By moving, turning and other disturbance methods, it will achieve the global optimization in the
whole area. We designed exactly software to verify our algorithm. With our approach, the best optimal
layout is irrelevant with the initial layout and the position of the biggest circle.
Keywords: Circle cutting and packing, NPC, Optimization Algorithm, SA Packing Problem, Random
Search.
P169 Neural Network Based Algorithm for Generalized Eigenvalue Problem
Authors: Hang Tan, Guoren Yang, Bo Yu, Xuesong Liang, Ying Tang
Abstract. The present paper introduces a neural network based on approach for the generalized
eigenvalue problem Ax   Bx , where n-by-n matrices A and B are real-valued, B is non-singular, and
B 1 A is an orthogonal matrix whose determinant is equal to 1. The generalized eigenvalues that have
the largest or smallest absolute value of principal argument, as well as the corresponding eigenvectors
that may be n-dimensional complex vectors, i.e., 2n-dimensional real vectors, can be extracted by using
our proposed algorithm that is essentially based on an ordinary differential equation of order n.
Experimental results demonstrated the effectiveness of the proposed algorithm.
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Keywords: Special orthogonal matrix; Generalized eigenvalue; Generalized eigenvector; Neural
network
P171 Simulation of Fabric in 2D Virtual Scene Based on Mesh Model
Authors: Xiaona Fan, Senlin Zhang, Zhen Fan, Zhaoqi Chen
Abstract. A fabric simulation system of 2D virtual scene is researched and implemented in this paper.
The system not only simulates the folds and transformations of the scene realistically but also allows
replacement and modification of fabric. The finite element mesh algorithm is used to model the virtual
scene. In order to avert deformations of texture mapping, the cubic polynomial interpolation algorithm
is proposed in this paper. It can overcome the low-pass characteristic of the bilinear interpolation
algorithm by eliminating the jags generated from texture mapping. To make the scene simulation more
stereo, this paper utilizes the intensity based fusion algorithm, which retains the original scene’s
intensity. The experimental results show that the two-dimensional fabric scene simulation system is
accurate and realistic, and has rapid time response.
Keywords: Bilinear interpolation; Texture mapping; Cubic polynomial interpolation; Intensity fusion;
Scene simulation
P172 The Model of Population Projection by Delay Differential Equation with Two Lags
Authors: Liqiang Fan
Abstract. In order to give the more reasonable models of population projections, delay differential
equations with two lags were considered. By analysing the relative growth rate of population, the
growth function of population which determined by the maximum age and minimum age of new
mothers might be more suitable. Because of the model does not have analytic solution, numerical
method gives the result of the delay differential equation, and the population of America and
population in the world test the rationality of the model. The result of the model agrees with the actual
when give the appropriate parameters and some reasonable assumptions.
Keywords: logistic equation; lag; relative growth rate; fitting; numerical method
P174 The reliability analysis of embedded systems
Authors: Zhongzheng You
Abstract. This article starts with the introduction of the essence of the reliability of embedded system.
By introducing some characteristics of embedded system such as failure rate, reliability and mean time
to failure to analyze the reliability of embedded system, and set up the model of a single system, series
system and parallel system. The models founded were simulated with Simulink software. Finally, the
results of the simulation and the example validations indicate that series-parallel hybrid structure is
very necessary in order to improve the reliability of embedded system and make the system has a long
service life.
Keywords: Embedded system; Reliability; Mean time to failure; Failure rate; Model; The reliability
function; Structure
P176 Strategies for Improving Accuracy of Structural Variation Prediction using Read Pairs
Authors: Jingyang Gao, Rui Guan, Fei Qi
Abstract. A substantial number of sequencing-based methods for discovering structural variation have
recently sprung up, among which technologies utilizing read pairs have made significant progress in
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providing high accuracy. Based on in-depth analysis of the state-of-the-art computational methods for
identifying structural variation with read pairs, strategies for improving accuracy of structural variation
prediction are summarized and classified into several categories, such as conservative mapping,
clustering, distribution-based strategies and so on. Specific elaboration and concrete comparison of the
strategies are carried on. It should be a future trend to develop an approach that is organic combination
of multi-class strategies for structural variation detection.
Keywords: structural variation; genome sequencing; read pairs; computational methods
P177 The Design and Implementation of a Process-based Printing Order Management System
Authors: Ma Huiling, Zhang Yongbin
Abstract. In order to solve the problem of isolated order information among production processes,
which leads to the information cannot be transferred timely and shared effectively, a system of
information tracking is presented in this paper. The BPMN (Business Process Model and Notation)
specification is adopted to establish order process model. The model can be used to describe the
company's core business and the order information transmission process with the process-oriented
thinking. Then Web standard-JSF (JavaServer Faces) is introduced to develop the system. The
operation results show that order information can be transferred timely, fast, accurately, which avoids
the delays or inaccuracies caused by manual operation. Meanwhile the managers can follow the tracks
of the order progress at all times and provide clients with advice. The process-based order management
system improved the information management ability of the printing enterprise and laid foundation for
the realization of informatization enterprise-wide.
Keywords: Order management; Printing process; BPMN; informatization
P181 A Location Privacy-Preserving Protocol Based on Homomorphic Encryption and Key Agreement
Authors: Xiaoling Zhu, Yang Lu, Xiaojuan Zhu, Shuwei Qiu
Abstract. Location-based services (LBS) bring so much convenience to our daily life. However they
have incurred serious location privacy problems. k-anonymity is the one of most popular
privacy-preserving methods. The method relying on a trusted third party (TTP) might cause the TTP to
become a performance bottleneck. So TTP-free protocols are proposed. But existing TTP-free
protocols cannot resist attacks from multiple users colluding with a LBS provider. To solve the
problems, this paper proposes a novel location privacy-preserving protocol. The protocol uses key
agreement to construct the perturbations which can be removed on the whole. The perturbations are
used to disguise real locations; meanwhile, they do not affect LBS service quality. With the help of
homomorphic encryption, the LBS provider can compute the centroid of a companion set while it does
not know the locations of the members in the set. The analysis shows that the protocol can resist
location privacy attacks from insiders and outsiders, especially from multiple users colluding with the
LBS provider. The protocol achieves high service quality while providing strong location privacy
protection for LBS.
Keywords: location-based services; location privacy; k-anonymity; homomorphic encryption; key
agreement
P184 A Lifecycle Analysis of the Revision Behavior of Featured Articles on Wikipedia
Authors: Xinyi Li, Zhunchen Luo, Kunyuan Pang, Ting Wang
Abstract. Wikipedia is the largest online encyclopedia. Its openness allows anyone to edit an article,
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making articles vary greatly in quality. As only a small proportion of articles are assessed manually, the
automatic evaluation of quality has become a highly active research field. Among the factors that affect
quality, revision action is the direct factor. In this paper, we conduct a lifecycle analysis of the revision
action of featured articles—the best work on Wikipedia, to find out the revision behavior patterns.
Using a fine-grained approach, we parse revision actions into insert, delete and replace actions to study
their performance in different phases of the lifecycle. Our results reveal that featured articles have
distinct revision behavior over different phases. The contribution of the research is to show the
correlation between revision behavior and the evolution of quality, which can help us understand what
is behind the evolution of articles and can be used to assist quality evaluation.
Keywords: Wikipedia; featured article; revision behavior; lifecycle analysis
P186 Collaborative Filtering Recommendation Algorithm Based on Users of Maximum Similar Clique
Authors: Zhou Zhaoyang, He Yanju
Abstract. In order to improve the performance of Collaborative filtering (CF), a new method of
producing the nearest neighbor for active user is proposed in this paper. Inspired by the conformist of
E-commerce consumers, we build the user model of maximum similar clique and we use it to improve
the method of producing the nearest neighbors for target users. A collaborative filtering
recommendation algorithm MCQ-CF based on user model is present. The experiment results show that
the algorithm MCQ-CF has good performance for accuracy and stability.
Keywords: collaborative filtering; conformist; similar clique; recommendation system
P187 Cloud Scenes Generation Based on the Improved Random Midpoint Displacement Method
Authors: Yang Dongsheng, Yang Kaipei
Abstract. In order to generate more rational and more diversity natural cloud scene, the improved
random midpoint displacement method is proposed in this paper. We found that the cloud scenes
generated by the traditional random midpoint displacement method were simple and similar through
simulation analysis. The limitation of traditional random midpoint displacement method was caused by
unreasonable method of generating random numbers. So the improved random midpoint displacement
method uses a new method to generate random numbers. In improved method, the normalized function
was used and the difference between average value and maximum and minimum value was taken into
account. According to a large number of simulations, the law of that parameters of improved method
influence the cloud scenes was given and the qualification about parameters of improved method was
presented. Simulation results show that the cloudy scenes by improved method are more rational and
more diversity.
Keywords: cloud; scene generation; midpoint displacement method; improved
P188 Performance Simulation and Optimization of Agricultural Supply Chains
Authors: Jing Chen, Haihong Yu
Abstract. Agricultural supply chains management is getting increasing focused in recent years, among
academics as well as practitioners. In this paper, we present a supply chain simulation study for a real
case, with the agricultural manufacture and distribution systems of cooperative-centered in concern.
We evaluated the key performance indicator of the whole supply chains by building and simulating 3
present models of agricultural distribution systems. The design alternatives differed in terms of the
level of integration and synchronisation between supply chain stages. By adjusting the combination of
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parameters we specifically optimized the models quantitatively. This article provides a flexible
simulation technique which could be widely used in the management system of agricultural circulation
and efficiency improving of Chinese agricultural supply chains.
Keywords: supply chains of agriculture; simulation; performance evaluation;model optimization.
P189 Partition Strategies for C Source Programs to Support CPU+GPU Coordination Computing
Authors: Yao Ding, Zeng Guo-sun, Ding Chun-ling
Abstract. GPGPU technology provides a new effective way for achieving high performance
heterogeneous computing. However, how to restructure traditional programs is the key to use GPGPU
technology under CPU+GPU heterogeneous environment. This paper studies the partition strategies for
C source programs to support CPU+GPU coordination computing. By analyzing characteristics of c
source programs in memory access, arithmetic density, control flow structure and data parallelism,
while considering the difference between CPU and GPU hardware, some strategies and algorithms for
partitioning the target programs are presented. Finally, some experiments are conducted by using some
typical programs to verify the effectiveness of proposed strategies and algorithms.
Keywords: GPGPU; coordination computing; C source programs; partition strategies
P193 Research of the Anti-Phishing Technology based on E-mail Extraction and Analysis
Authors: Yanhui Du, Fu Xue
Abstract. In this paper, an anti-phishing technique based on e-mail extraction and analysis is proposed.
The technique approached with phishing email, the channel phishing attack transmits, distinguish
phishing emails and extract the suspicious URL from the e-mail for further analysis.
Upon arrival, a protected list is build according to those third parties most vulnerable to phishers in
order to filter those confusing advertising spam in China and a neural network based model is proposed
in order to detecting phishing messages from an e-mail stream.
In this anti-phishing technique, email stream captured by our honey pot subsystem from the Internet is
parsed into a MIME email firstly; various feathers are extracted from the email and outputted into
feather vectors. The feature vectors will be self-organized by ART2 neural network one by one and
classified into corresponding categories. Link URLs in the suspected emails’ messages will be
extracted for further detection in phishing site subsystem.
Experiment using collected emails shows a good performance aiming at detecting phishing emails in
China while foreign method performs badly in distinguishing phishing emails from spam.
Keywords: ART2 Neural Networks, E-mail Extraction, Anti-phishing
P194 A new face recognition method based on the energy image of facial contour
Authors: Yang Xinwu, Zhai Fei, Ma Zhuang
Abstract. In order to further improve the effectiveness and enhance practicability of face recognition
under guaranteeing the recognition accuracy, this paper proposes a new method of face recognition
based on the energy image of facial contour. First, image binaryzation and edge detection method are
used to extract the facial contour, then the energy image of facial contour of training samples are
obtained; second, matrix logic "and" operation is adopted to calculate the similarity between a test
sample and the energy image of facial contour of each class; finally, the test sample is classified
according to the similarity criteria. The method is based on a kind of similarity match, so it can make
good use of two-dimensional structure information of face images; moreover, it adopts matrix logic
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"and" operation in classification instead of solving the eigenvalue problem and calculating the
Euclidean distance of traditional classification algorithm, which can reduces the computational
complexity dramatically. Finally, the contrast experiment with principal component analysis and
sparsity preserving projections shows that the proposed method is more effective and stable on the Yale
face database.
Keywords: face recognition; similarity; faceial contour extraction;
energy image of facial contour
P196 Multi-resolution Image Fusion Algorithm Based on Gradient and Texture Features
Authors: Junyong Ma, Shengwei Zhang, Caibing Yue,
Abstract. A multi-resolution image fusion algorithm based on gradient and texture features is proposed.
After each level of Gaussian Pyramid being separately filtered by texture-extracting filters and edge
gradient filters, a series of texture and edge images including the texture information of original image
are generated. This provides more comprehensive information measurement for further fusion. Infrared
and visible images are fused utilizing the proposed image fusion method, and the fusion results are
compared with several traditional fusion method. Experiment results and image fusion quality
assessment show that the proposed fusion method demonstrates more superiority.
Keywords: Image Fusion; Texture Feature; Gradient Feature
P197 Survey of Cloud Messaging Push Notification Service
Authors: Na Li, Yanhui Du, Guangxuan Chen
Abstract. Cloud messaging push notification services are key features of pervasive mobile applications
where invocations occur asynchronously and it is important that the mobile users are notified in a
timely fashion of the available services. This article summarizes Push technology evolution including
key techniques, features and architectures. It presents four kinds of push notifications such as Google
Cloud Messaging, Apple Push Notification service, Microsoft Push Notification service and Blackberry
Push service. It also analyses these four push notification approaches. In addition, it proposes a QESM
to evaluate and select the most appropriate push mechanisms.
Keywords: push notification services; cloud computing; survey
P199 The Speedup Model for Manycore Processor
Authors: Nan Ye, Ziyu Hao, Xianghui Xie
Abstract. Integrating a large number of simple cores on thechip to provide the desired performance
and throughput, microprocessor has entered the manycore era. In order to fully extract the ability of the
manycore processor, we propose speedup models for manycore architecture in this paper. Under the
assumption of Hill-Marty model, we deduce our formulas based on Gustafson’s Law and Sun-Ni’s Law.
Then, compared with the Hill-Marty model, wetheoretically analyse the best allocation under the given
resources. Furthermore, we apply the conclusions of our models to evaluate current manycore
processors and predict future architecture. Our results show that manycore architecture can be capable
of extensive scalability and be beneficial to promote the performance, especially
heterogeneous one.
By using simple analytical models, we provide a better understanding of architecture design and our
work complement existing studies.
Keywords:speedup model, manycore architecure, Gustafson’s Law, Sun-Ni’s Law
P201 A New Approach for Text Location Based on SUSAN and SVM
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Authors: Wang Chuan, Zhou Yi-min
Abstract. In order to extract text parts from images, this paper proposes a new approach that combines
edge detection, heuristic knowledge and SVM. Firstly, SUSAN algorithm with an adaptive threshold is
used to extract the edge information from gray images, and the binary edge images are obtained;
Secondly, the heuristic knowledge is used to filter the text candidate areas obtained by edge dilation,
and the positions of the text candidate areas in the binary image apply to the gray image; Finally use
statistics of gray level co-occurrence matrix as SVM’s inputs to construct SVM which is used to verify
the text areas further. The experimental results show that the proposed approach can effectively locate
the text areas with high accurate and extraction ratios.
Keywords: text location; edge detection; SUSAN operator; SVM
P202 A Ship Recognition Method based on Affinity Propagation
Authors: Weiya Guo, Xuezhi Xia
Abstract. Accurate target classification is the keystone of sea battlefield’s ship targets recognition.
Aiming at the deficiencies of supervised and unsupervised classified methods, we present a novel
scheme called semi-supervised ship target recognition based on affinity propagation (AP). In order to
circumvent the problem of choosing initial points, the method introduces affinity propagation
clustering to construct classification model simply and effectively. Based on the idea of
semi-supervised learning, a few restrictions of labelled flows and priori manifold distribution of
sampled space are abstracted. Also, manifold similarity is defined. Henceforth, the semi-supervised
method can not only largely reduce the complexity of marking sampled flows, but also nicely improve
the performance of the classified. Theoretical analysis and experimental results show that that the
proposed method is robust and can get better than KNN or SVM or HDR method. With the
acquirement of high recognition rate in the battlefield’s ship targets on the sea, undoubtedly, this
approach is a feasible and efficient method.
Keywords: ship recognition; semi-supervised learning; affinity propagation (AP) clustering; manifold
similarity
P205 NBA All-Star Lineup Prediction Based on Neural Networks
Authors: Bigui Ji, Ji Li
Abstract. In this paper we examined the use of Neural Networks as a tool to predict the starting and
reserve lineup of All-Star game, in the National Basketball Association, from all the candidates.
Statistics of data from season 2008-09 to 2012-13 were collected and used to train a verity of Neural
Networks such as feed-forward, radial basis and generalized regression Neural Networks. Fusion of the
neural networks was also examined by using AdaBoost ensemble learning algorithm. Further, we have
explored which features set input to the neural network was the most useful ones for prediction. And an
excellent prediction scheme was proposed to improve the forecast accuracy. By using AdaBoost and
the proposed scheme, the accuracy of our prediction of the starting lineup is up to 91.7%, the reserve
lineup 73.3%.
Keywords: All-Star prediction; Neural Networks; AdaBoost
P206 An Improved Super-Resolution Reconstruction Algorithm Based on Regularization
Authors: Shuang Wang, Bingliang Hu, Xiaokun Dong ,Xingtao Yan
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Abstract. The traditional regularized super-resolution (SR) algorithms can reconstruct the
high-resolution (HR) image to some extent. But the high frequency information of the image will lose
seriously and the edges and details will become blurred. This paper presents an improved regularized
SR algorithm. Firstly, a new interpolation algorithm is used to obtain the initial value of the HR image.
Secondly, the trilateral filter is adopted as the regularization term to preserve the edge and details.
Finally, the steepest descent method is taken as the iterative algorithm to gain the optimum solution.
Simulated experiments are presented including the comparison with some existing reconstruction
algorithms. Those results show that the proposed algorithm performs better than others. Furthermore,
the edges and details of the image are well preserved.
Keywords: super-resolution reconstruction; regularization; trilateral filter; steepest descent method.
P209 Hand Tracking Algorithm Based on SuperPixels Feature
Authors: Zhang Zhiqin, Huang Fei
Abstract. There have been considerable research efforts to use the hand as an input device for HCI in
recent years. Hand tracking is the most important procedure for HCI, it is essential of tracking stability
and efficiency for hand manipulation. This paper proposed a novel hand tracking algorithm which can
track a hand stable and is real time, and the proposed algorithm can work on normal CCD cameral. Our
algorithm is based on mean-shift and we improved it to fit for robust hand tracking by using super pixel
cluster, integrated GIH and skin color mask, the skin color mask was extracted using online learning.
The proposed improved algorithm can track hand reliably even in clutter environments comparing to
the existing traditional algorithms.
Keywords: HCI, super pixels, hand tracking, online learning, monocular, mean shift
P210 Granular Based Dijkstra algorithm For Solving Uncertain Shortest Path Problem
Authors: Assem Ahmed Alsawy, Hesham Ahmed Hefny
Abstract. shortest path problem got a lot of attention from many researchers; the distances between the
nodes can be represented by different types of uncertain numbers such as: interval numbers, fuzzy
numbers, rough numbers and also some of them can be classical real numbers. These heterogeneous
types of numbers are forming a challenge in calculation the shortest path. This paper proposes a
Unified Granular Number (UGN) that we call, G- Number to act as a general form for any uncertain
granular number. G- Number represents higher level of abstract that hold only common properties of
different types of uncertain granular numbers while ignoring some particular properties which are not
necessary to be considered in such higher abstract level. The main benefit of using such a proposed Gnumber is the ability to represent all types of granular numbers using unified formality that greatly
simplifies arithmetic operations.
P212 The Asymptotic Properties of Quasi-maximum Likelihood Estimator for Spatial Error Panel Data
Model
Authors: Chunhong Li，Lixia Wen
Abstract. The spatial panel data model is commonly used in practice. In order to explore the property
of the parameter estimator for the spatial error panel data model with fixed effects, the quasi-maximum
likelihood estimator for the model is provided in this paper. And two theorems on the asymptotic
properties of the estimator are proposed and proved. For illustration, the associated simulation is
employed to verify the effectiveness of the proposed strategies. Empirical results show that when the
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number of the spatial units is large and the number of the time series is finite, the estimator is consistent
and asymptotically normal.
In conclusion, it is an estimator with good performance.
Keywords: spatial error panel data model; quasi-maximum likelihood estimator; consistency
asymptotic normality; simulation studies.
P217 The Credit Risk Prediction of the Small and Medium-Sized Enterprises based on GA-v-SVR
Authors: Wei Wang, Xiangdong Liu, Si Chen
Abstract. Making the science assessment and prediction of the credit risk of the small and
medium-sized enterprises (SME) is a significant part of risk management of commercial bank. This
paper first integrates Genetic Algorithm (GA) with v-SVR model, creates the credit prediction model,
GA-v-SVR, and then builds the SME credit risk indicator system. Using principal component analysis
method screens out the major factors of credit risk, it then considers those factors as the input indexes,
and chooses credit default as the output indicator. The model is employed to train the first group
sample, and the rules of credit risk recognition are obtained. Finally, we utilize these rules to predict
the credit of the second group sample, and acquire a rather accurate result so that can prove the
feasibility and validity of the model established by this paper.
Keywords: support vector machine; genetic algorithm; credit risk; small and medium-sized enterprises
P221 Application of FAHP Approach to Assess Service Quality
Authors: Yong Li, Zhi-Kun Zhang
Abstract. Service quality has become an important topic because of its apparent relationship to
customer loyalty, reduced cost and retention, and it is widely taken as a driver of firm marketing and
financial performance. In order to remain competitive in developing markets, improving the service
quality is a key strategy for firms. As service satisfaction of dealers directly impacts production sales,
firms are especially concerned with increasing and maintaining the service quality, as well as
identifying why service satisfaction decline. This paper proposed an approach within the Fuzzy
Analytic Hierarchy Process (FAHP) framework with specific service quality elements based on
SERVQUAL for tackling the imprecision and uncertainty of service satisfaction assessments during
service process, where the decision-makers’ comparison judgments are represented as fuzzy triangular
numbers. Finally, results of the study demonstrate the feasibility of the proposed FAHP-based
algorithm in effectively selecting the assessment outcomes. So, through collect data to judge the result
by FAHP, considerable value for the firms to improve its’ service quality could be obtained.
Keywords: Service quality; Service satisfaction; SERVQUAL; Fuzzy linguistic scale; Fuzzy analytic
hierarchy process (FAHP)
P225 An Improved Forecasting Algorithm for Spare Parts of Short Life Cycle Products Based on
EMD-SVM
Authors: Jie Li, Yeliang Fan, Yong Xu, Huiran Feng
Abstract. Demand of spare parts of short life cycle products has great random fluctuation and short life
cycle. Traditional forecasting methods have low forecasting accuracy which leads to understock or
overstock of spare parts. Considering such situation an improved forecasting method based on
Empirical Mode Decomposition and Support Vector Machine (IEMD-SVM) is proposed. By replacing
the Cubic Spline Interpolation in the standard EMD with Piecewise Cubic Hermite Interpolation, the
overshoots and undershoots problems caused by great volatility of data are solved. Experiments with
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459 real data sets show that the IEMD-SVM forecasting method has a better forecasting result than
traditional forecasting methods which provides better decision supports for enterprise inventory
management.
Keywords: component; short life cycle products, spare parts demand, forecasting, Empirical Mode
Decomposition, Support Vector Machine
P226 Using Bidirectional Search to Compute Optimal Shortest Paths over Multi-Weight Graphs
Authors: Hui Ma, Ruishi Liang
Abstract. Computing the shortest path between two vertices in a given graph finds out vast
applications. Currently most state-of-the-art research studies the shortest path computation problem in
single-weight graphs, i.e., each edge in the graph has only one weight. In some applications, there are
multiple weights on an edge, and those weights need to be considered when computing the shortest
path. However, the sub-path property that any sub-path on a shortest path is also a shortest path, is
violated in multi-weight graphs, and hence those state-of-the-arts could not be directly applied. This
paper proposes a Bidirectional Best-First Search (BBFS) method with heuristic optimizations to find an
optimal shortest path in multi-weight graphs. Experiments show that compared to the single search
Best-First Search (BFS), BBFS has higher performance. Meanwhile, BBFS has high accuracy
especially for long paths search.
Keywords: shortest path; multi-weight graph; long path; bidirectional search
P229 Application of 3D Sampling Trajectory in EVDRS Algorithm
Authors: Zhongyuan Mou, Jie Yang, Jieru Chi
Abstract. In order to solve the reconstructed image problem with poor image quality and long data
scan time, 3D-EVDRS algorithm is proposed in this paper. By using 3D sampling trajectory in EVDRS
algorithm, 3D-EVDRS algorithm can rationally solve the reconstructed image problem with poor
image quality and long data scan time. For illustration, the medical diagnosis spine data is utilized to
show the feasibility of the 3D-EVDRS algorithm in solving the reconstructed image problem with poor
image quality and long data scan time. Experiments show that 3D-EVDRS algorithm will be used as an
efficient algorithm in solving the reconstructed image problem with poor image quality and long data
scan time. 3D-EVDRS algorithm can effectively solve the problem with image quality and imaging
speed and thus a class of the reconstructed image problem with poor image quality and long data scan
time are solved.
Keywords: 3D sampling trajectory; EVDRS algorithm; MRI; image reconstruction; 3D-EVDRS
technique
P230 A model of visual attention for natural image retrieval
Authors: Guang-Hai Liu, Deng-Ping Fan
Abstract. in this paper, we propose a simple, yet very powerful visual attention model to encode color,
orientation and saliency information and spatial layout as natural image features for content-based
image retrieval, where the image representation is so called saliency textons histogram. Experimental
results indicate that the performances of our algorithm are better than that of multi-texton histogram
and Gabor filter method significantly. The saliency textons histogram has the good discrimination
power of color, edge features and spatial layout. Furthermore, the proposed visual attention model can
simulate the human visual mechanism to some extent.
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Keywords: Visual attention; Saliency model; Saliency textons histogram.
P232 Research on Spatial Frequency Motivated Gray Level Image Fusion Based on Improved PCNN
Authors: Nianyi Wang, Yide Ma, Weilan Wang
Abstract. SCM is an improved PCNN model compared to traditional PCNN model. It decreased
computation complexity and is much less time consuming than PCNN. It accords with Weber–Fechner
law and possesses the advantages of both PCNN and ICM. In this paper, we proposed a SCM based
image fusion method. Firstly, spatial frequency is considered as the gradient features of images to
motivate SCM networks. And then we provided a new method to select pixels from source images and
generate the final fused image. In order to verify the effectiveness of the proposed method, we
compared it with other five methods under four image fusion effect evaluation indices. The
experimental results show that the proposed approach is an effective fusion method. Robustness test
experiments verify that our method can be used in noisy image processing field.
Keywords: image fusion; spiking cortical model (SCM); spatial frequency; robustness test; pulse
coupled neural network (PCNN)
P235 A Hybrid Artificial Bee Colony Algorithm Combined With Simulated Annealing Algorithm for
Traveling Salesman Problem
Authors: Shi Pei, Jia Su-ling
Abstract. In order to solve travelling salesman problem (TSP), a hybrid artificial bee colony algorithm
combined with simulated annealing algorithm (HABC-SA) is presented for TSP. This algorithm gives a
discrete coding method for food source position. Crossover and mutation operators in genetic algorithm
are introduced into the new algorithm to do local search. Simulated annealing idea is applied in this
hybrid artificial bee colony algorithm to increase the diversity of food sources. The proposed algorithm
is tested on benchmark problems,
and results show that this algorithm can avoid pre-maturity and
advance constringency for TSP.
Keywords: artificial bee colony algorithm (ABC); travelling salesman problem (TSP); simulated
annealing idea.
P238 Study on Textual Case Retrieval Algorithm Based on Topic Words
Authors: Lei Tang, Ying Wang, Yi Zhu, Kunwang Tao, Yong Feng, Ying Guan
Abstract. Several shortages of Boolean retrieval, ignoring the semantic relations between words and
unable to rank the retrieval results in order of importance, are found by analyzing the essence of
traditional text retrieval, in view of which an improvement of algorithm optimization based on topic
words is proposed. Through enriching topic words to structure keywords library, the semantic distance
and similarity of keywords are calculated on the basis of semantic retrieval framework. The improved
algorithm is applied in the disaster case retrieval system at last, which retrieval results are then
analyzed to detect performance. It is observed that the improved algorithm has a better improvement in
retrieval both precision rate and recall rate.
Keywords: Boolean retrieval; topic words; semantic distance; improved algorithm; precision rate;
recall rate
P239 A Weighted Association Rules Mining Algorithm with Fuzzy Quantitative Constraints
Authors: LU Qi-bing, SHENG Bu-yun
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Abstract. Along with production process automation and development of new products, manufacturing
information in large quantity, contains more dimensions, in order to mine useful information from the
manufacturing database, monitor and control manufacturing process effectively. A weighted
association rules mining algorithm with fuzzy quantitative constraints (FQC-wed Apriori algorithm) is
proposed in this paper. First, find association rules after database mining. Then, mine fuzzy association
rules with fuzzy query. Last, find frequent itemsets with the improved weighted association rules
algorithm. Manufacturing process information can be mined and effectiveness of the mining algorithm
can be evaluated. The algorithm is applied to manufacturing process information mining in
discrete manufacturing industry.
Keywords: data mining, association rules algorithm, weighted support, fuzzy association
P241 Design and Development of Air Traffic Management Safety Database Analysis System
Authors: Wang Lixin, Liu Yi
Abstract. With the rapid development of civil aviation, air traffic management system plays a more
important role in ensuring aviation safety, and hence there is an urgent need to use information
technology to improve analysis level and efficiency of aviation safety information. In this paper, an air
traffic management safety database analysis system is developed. It can not only store basic
information of safety events by entering data directly or acquiring data from other sources, but also
quantify and classify the incidents according to human factor analysis, defense failure analysis and
organization factor analysis of SHELL model so as to achieve in-depth analysis of the safety
information. In the development of the system, B/S mode, MySQL database, Java language and Struts
2 + Spring + Hibernate framework are adopted. Via flexible user role and permission mechanism it
could ensure a safe and ordered access to safety data. Moreover, considering importance and
complexity of data acquisition, this module is deployed on cloud computing platform as a service,
which could improve data acquiring efficiency and also lay a foundation for follow-up data mining of
ATC safety data. The system could provide a quantitative decision support for ATC safety information
management.
Keywords: air traffic management; database; cloud computing; civil aviation safety
P244 H-KD: a novel query structure for multi-dimensional awareness information
Authors: Hong Tang, Xiao Sun, Guofeng Zhao
Abstract. With the development of Internet, network applications based on awareness information
appear increasingly in future Internet, such as context-based routing, content delivery and personalized
content recommendation. The full use of awareness information to support those applications makes
the fast query of information to be a critical issue. This paper adopts the strategy of “divide-conquer” to
propose an effective two-layer data structure named H-KD to search diverse, multi-attribute and
massive awareness information. As the first layer structure, Hash Tree organizes the service ID that
identifies the type of awareness while the second layer is composed of KD Trees to deal with the
specific instances of information. The results of simulation with the real data sets show that H-KD is
more efficient and scalable than KD Tree especially when used in the partial query and the range
query.
Keywords: future Internet; awareness information query; KD Tree; Hash Tree
P245 A Case of Chip Multithreading Architecture with Resource Unit Manager
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Authors: Juan Fang, Zhenxi Pan, Lu Yu, Sitong Liu
Abstract. In order to improve the overall throughput of processors, to increase thread-level parallelism
(TLP) and instruction-level parallelism (ILP) intra and inter cores, and ensure the scalability of
multi-core systems, can a novel mechanism chip multithreading with resource unit manager
(RUM-CMT) be used, which is presented in this paper. By introducing the efficiency difference of
resource utilization among threads, such as, the condition of dynamically resource allocation to CMT
architecture and add an absorption barrier for all threads to make their reserved resources far away
from hidden hunger. For verify the applicability of RUM-CMT, a 4 cores with 2 threads processor and
a 4 cores with 4 threads processor are simulated based on GEMS & simics simulator. And this limited
study shows RUM-CMT can increase performance by 29.79%, and an improve success committed
instructions per squash instructions by 31.15% and fairness attains 6.25% improvements over static
partition on 4 cores with 4 threads processor. The 4 cores with 2 threads also attains passable enhance.
So RUM-CMT can accurately and concise reallocate resource according to phase turning in the
running of applications, improve resource utilization, mining the ILP and TLP in applications. In other
words, RUM-CMT improves the controllability of threads, reduces invalid losses and improves system
efficiency, and it is a suitable solution for multicore, multithreaded architecture.
Keywords: Dynamic partition; Register Unit Manager; simultaneous multithreading
P247 An Improvement of the Slotted CSMA/CA Algorithm with Multi-level Priority Strategy and
Service Differentiation Mechanisms
Authors: Lin ZHOU, Mafeng ZHU, Kaixia PAN, Liping LEI, Congbin ZHUO
Abstract. It is the fact that IEEE 802.15.4 protocol does not support any service of priority scheduling
mechanism and there are some shortages existing in the slotted CSMA/CA algorithm. In view of the
different types of priority and the defects of the original CSMA/CA algorithm, a kind of CSMA/CA
algorithm with multi-level priority strategy and service differentiation mechanisms is proposed in this
paper. What’s more, different BE and CW are used to provide multilevel differentiated service for
devices in sensor network. Four types of priority are assumed, there are high, medium, low and normal
priority and they are assigned depend on current state of the network by CSMA/CA algorithm. In the
end, it is proved that the proposed algorithm performs better than the original one in the aspects of the
throughput, network delay and the probability of successfully access to channel using network
simulator OPNET.
Keywords: the Slotted CSMA/CA; multi-level priority strategy; service differentiation mechanism;
OPNET
P251 Predicting the Subcellular Localization of Proteins with Multiple Sites Based on N-terminal
Signals
Authors: Xumi Qu, Yuehui Chen, Shanping Qiao,
Abstract. Subcellular localization of proteins is an important attribute in molecular cell biology and
proteomics, and closely related to its functions, signal transduction and biological process. In recent
years, great progress has been made in the research field of protein subcellular localization prediction.
However, some shortcomings still exist in the prediction methods. Such as the extracted features
information is not complete enough to achieve a higher prediction accuracy rate, some important
protein information and the correlation of the amino acid sequence are usually ignored and so on. Some
proteins can simultaneously exist or move between two or more different subcellular locations, but
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were considered to have only one location. In this study, we divide a protein sequence into two parts
according to its N-terminal sorting signals and extract their pseudo amino acid composition features
respectively. And then we use the multi-label KNN, abbreviated as ML-KNN to deal with the proteins
which have both single location and multiple locations. The results are satisfied by Jack Knife test.
Keywords: subcellular localization; pseudo amino acid composition; N-terminal sorting signals;
ML-KNN
P253 A graph-based method for Detecting Text in natural scene images
Authors: Li Rong
Abstract. Detecting texts in camera-captured images is a challenging task. In this paper we present a
graph based method for detecting texts in camera captured images. We first extract connected
components by an adaptive method. Then we construct a graph whose vertices correspond to connected
components. There also have two special vertices called terminals: source s (text) and sink t (non-text).
We find four nearest neighbor CCs of a CC, and add edges in the graph between the corresponding
vertex of the CC and vertex of its neighboring CC. Energy function of the graph is defined so that its
minimum is corresponding to an optimized partition of vertices into source and sink. Parameters of the
energy function are determined by trial. Maximum flow/minimum cut method is used to minimize
energy function and get an optimized partition of the connected components into source(text) and
sink(non-text). Experiment results show that the method can diminish many false alarms which in the
result of output of SVM classifier alone and attains very high precision.
Keywords: text detection; graph cut; camera captured images; natural scene images; conditional
random field
P255 The Security Testing Case Research of Protocol Implementation
Authors: Lei Zhang, Jing An, Chunlan You, Guangxuan Chen•
Abstract. As the underlying design of security protection technology, security protocol played an
indispensable role in the protection of data storage and transmission of the network and information
system. This paper analyzed the existing method for generating test cases based on the security testing
research of protocol implementation according to the three key steps, formal description of the protocol
model, the generation of test sequence and the description of test cases. This paper also provides
reference for the research of new method to generate test cases.
Keywords: protocol implementation; security testing; test cases
P256 Efficient Identity-based Encryption from Lattice
Authors: Chen Huiyan, Chen Dongmei, Zhang Yanshuo
Abstract. At present, most of identity based encryption (IBE) schemes from lattice originate from the
results of Gentry et.al.[11], and regard each identity as a bit string with equal length and then assign a
matrix to each bit of identity string. Consequently, they are considerably less efficient. In this paper, we
present an efficient IBE from standard learning with errors problem and process identities as one chunk
for performance. This paper gives a proof that our IBE is IND-sID-CCA secure in the standard model.
Meanwhile, we also show that our IBE construction is also IND-ID-CCA secure by the technique i.e.,
imposing additional restrictions on the identities, presented by D. Boneh and X. Boyen in [3].
Keyword: lattice, identity based encryption, learning with errors (LWE) problem, selective-identity
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P258 Research of terrain 3D visualization method based on IDL and ArcEngine
Authors: Bin YANG, Jin-sheng WANG, Xiu-mei GU, De-zheng GAO
Abstract. It is a very hot research topic in GIS, virtual reality, computer graphics, digital
photogrammetry and other fields which should be researched on 3D terrain visualization. There is also
an important part of the digital earth strategy in many fields in order to resolve some comprehensive
problems. Trying to take advantage of IDL data processing and graphic display function and
ArcEngine spatial analysis function, in the Visual C # 2005 under the environment of hybrid
programming mechanism, using of component design and development of integrated development
technologies analysis of terrain visualization application operating environment. It should realize the
3D digital terrain expression and spatial analysis function. The results show that the IDL and
ArcEngine integrated development method applied to the 3D terrain visualization analysis software
platform developed operability and extension force with strong, both in terms of space efficiency and
image data analysis , development costs advantages.
Keywords: 3D visualization; formatting; Digital terrain; IDL; ArcEngine; Integrated development.
P260 Commercial Bank Stress Tests Based on Credit Risk
Authors: Weiqing Wang, Xue Zhang, Xiangdong Liu
Abstract. Based on the History-Based Stressed PD model which is derived from Merton theory and
IRB model which is derived from Basel New Capital Accord, this paper selects six commercial banks
to conduct the empirical research of credit risk stress testing. The result indicates that the value-at-risk
calculated by IRM model is much higher than History-Based Stressed PD model, because the former is
completely based on the theoretical model while the latter takes into consideration of the historical and
realistic significance. In practice, this paper suggests to comprehensively consider the measuring
results of two models to formulate risk control measures.
Keywords: stressing test; credit exposure; History-Based Stressed PD model; IRM model
P261 Effective Data Exchange in Parallel Computing
Authors: Hui Ma, Yongqi Li
Abstract. How to efficiently transfer data among parallel threads is a research hotspot. A common data
structure of transferring data among parallel threads is queue. Some writer threads write data into one
side of the queue, and reader threads read data from the other side of the queue. Run in parallel
environments, some sources, such as shared variables, are critical resources, which require atomic
operation. One naive way to guarantee the correctness is to impose a lock on critical resources.
However, lock is a heavy system mechanism, and is of low efficiency. In this paper, a highly effective
single-in-single-out lock-free queue is devised by utilizing some important hardware properties and
techniques, such as thread-local variables, fast modulo operations and cache-line padding, etc. A
single-in-multi-out lock-free queue and a multi-in-multi-out lock-free queue are also proposed.
Experimental results in the end show the effectiveness of our methods.
Keywords: data exchange; parallel computing
P262 Towards Real-time Federate Cloud for Large Group Company
Authors: Lixin Du, Wei He
Abstract. How to improve the utilization of IT facilities is a major problem for enterprises which have
many real-time control systems. We think that improving or rebuilding legacy applications using cloud
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computing ideology is more suitable than building new cloud platform for these traditional real-time
companies. In this paper, we propose a federate cloud (FC) architecture for large group company
having many subsidiaries with similar real-time applications based on centric model.
In the FC
architecture, a sub cloud is constructed for applications in each subsidiary and all the sub clouds are
connected together by cloud bus. We discuss the detailed mechanism for the FC architecture, including
construction of
the FC component, the real-time cloud storage strategies and cloud service scheduling
algorithm. Experiment results show that our method can improve the utilization of IT facilities
effectively.
Keywords: cloud computing; real-time storage; service scheduling; federate cloud
P263 Realization of Multi-port SDRAM Controller in
LXI Data Acquisition System
Authors: Jianmin Wang, Yanqin Zhang, Jinhu Zhou, Peng Jia, Xunjun He
Abstract. Currently, the LXI data acquisition system often requires high speed, large capacity memory,
but the internal storage resource of FPGA is not sufficient to meet the requirements. In order to solve
above problems, a SDRAM controller is proposed in this paper, where the Multiple FIFO based on the
on-chip resources of FPGA serves as the read and write cache to realize the multiple functional
modules performing the read/write operation in LXI acquisition system by the design of priority
algorithm and reasonable controlling the access of SDRAM from external device. At the same time, the
SDRAM can still communicate at high frequency by the suitable time limitation. The simulation results
show that the proposed SDRAM controller can not only realize reading and writing data, and but also
its operating frequency is able to meet the requirements of functional modules.
Keywords: SDRAM; muli-port; arbitration; FPGA
P264 Solving Fuzzy Nonlinear Systems—A Class of Defuzzification in the Fuzzy Control
Authors: Jia Meizhen, Peng Xiaohua
Abstract. In order to achieve defuzzification, converts fuzzy quantity to accurate quantity in fuzzy
control, researching about solving fuzzy nonlinear systems. Parameters transform method combines
with homotopy method are introduced in this paper. The parameters transform method transforms a
class of general fuzzy nonlinear systems and full fuzzy nonlinear systems into numerical nonlinear
systems. Then, one can get solutions of the numerical nonlinear systems based on the homotopy
method. It is feasible to choose any appropriate initial value when using homotopy method, avoiding
the hard work of selecting appropriate initial values. The numerical experiments approve this method is
a useful defuzzification at last. It is easer to accomplish defuzzification by solving the two fuzzy
nonlinear systems. In this way, a class of fuzzy control can be established based on the defuzzification.
Keywords: defuzzification; fuzzy control; fuzzy nonlinear systems; parameters transform method; the
homotopy method
P265 Multiple Feature Fusion Protein Tertiary Structure Prediction
Authors: Wenzheng Bao, Yuehui Chen, Yiming Chen
Abstract. Predicting protein tertiary structure from its primary amino acid sequence is a challenging
mission for bioinformatics. In this paper we put forward a novel approach for predicting the tertiary
structure of protein and construct an Error Correcting Output Codes(ECOC) classification model on the
basis of Particle swarm optimization(PSO) and neural network(NN).Three feature extraction methods,
which are Amino Acid Composition, Amino Acid Frequency and Hydrophobic Amino Acid
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Combination, respectively, are employed to extract the features of protein sequences. To evaluate the
efficiency of the proposed method we choose a benchmark protein sequence dataset (640 dataset) as
the test data set. The final results show that our method is efficient for protein structure prediction.
Keywords:Tertiary structure of protein; ECOC classification models; Particle swarm optimization;
neural network
P266 A Study on User Adoption of Cloud Storage Service in China: A Revised Unified Theory of
Acceptance and Use of Technology Model
Authors: Yue Cao, Xinhua Bi, Lei Wang
Abstract. Cloud services have been basically popularized in Europe and US, but in China especially in
enterprise market the promotion of cloud services is quite difficult, it is necessary to explore the factors
influencing the adoption of cloud services. Based on the revised Unified Theory of Acceptance and
Use of Technology (UTAUT) model, we described a theoretical framework that incorporates the
unique characteristics of cloud storage service to evaluating the adoption of cloud storage service in
China. Results of empirical study showed that perceived risk, personal innovativeness, performance
expectancy, effort expectancy and social influence had significant effects on adoption intention, and
adoption intention and facilitating conditions had significant effects on adoption behavior.
Keywords: cloud storage service; user adoption; unified theory of acceptance and use of technology
(UTAUT)
P267 Present Situation and Prospect of Data Warehouse Architecture under the Background of Big
Data
Authors: Sun Lihua, Hu Mu, Ren Kaiyin, Ren Mingming
Abstract. Compared with the traditional data warehouse applications, the big data analysis is
characterized by its large data size and complex query analysis. In order to design the data warehouse
architecture suitable for the big data analysis, this paper analyzes and summarizes the current
mainstream implementation platform-parallel database, MapReduce and the hybrid architecture based
on the above-mentioned two architectures. Moreover, it presents respectively their advantages and
disadvantages and describes various researches of and the author’s efforts on the big data analysis to
make prospects for the future study.
Keywords: big data; data warehouse; large scale; MapReduce; parallel database; deep analysis
P268 Unambiguous Synchronization Technique for BOC signals
Authors: Jiamin Qi, Zhenbo Li, Jiapin Chen, Ling Mao
Abstract. In order to deal with the tracking ambiguity for binary offset carrier (BOC) modulated
signals, a new tracking technique is proposed. The idea of the proposed new tracking loop is to
combine a single peak correlation function. Through subtracting two cross-correlation, a single positive
peak correlation function could be obtained. For different BOC signals, the new proposed method
adopts symmetrical equivalent pulse width modulated symbols of the auxiliary signal. The theoretical
formulas of the proposed acquisition technique is computed and simulated. The performance results
show that the proposed new technique could solve the ambiguity completely, although there is some
degradation in acquisition.
Keywords: GNSS; BOC modulation; unambiguous acquisition; detection
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P273 Simulation research on diffusion of agricultural science and technology for peasant
Authors: MA Li, CHU Xia-ling, HUANG Xiu-jie, XIONG Rui-quan, LI Huan-huan, LIN Qun
Abstract. [Purpose] In order to solve problems like Chinese farmers’ weak economic strength, low
ability for receiving technology, and low efficiency of agricultural science and technology diffusion,
the diffusion of agricultural science and technology among farmers is simulated and analyzed. [Method]
By using complex network theory and Netlogo software, the spread of agricultural science and
technology is simulated. [Results] Results show that the higher the “network-density” and
“disseminator” are, the faster the agricultural science and technology diffuses; the more the “explorer”
and “intensity” are, the faster the agricultural science and technology diffuses, but when the number of
“explorer” and “intensity” reaches a certain level, agricultural science and technology diffusion enters a
platform stage; the bigger the “cost” is, the smaller the “revenue” is, the larger the technical potential
difference is, the more the time full coverage of agricultural science and technology consumes;
“environment” factor is not sensitive to the technology diffusion. [Conclusions] Agricultural science
and technology diffusion model and simulation established by using the theory and method of complex
network, can provide a reference for the improvement of agricultural technology diffusion system
and diffusion method.
Keywords: peasant; own characteristics; Netlogo; agricultural science and technology; simulation
P275 A Three-stage Clustering Framework based on Multiple Feature Combination for Chinese Person
Name Disambiguation
Authors: Fei Wang, Yi Yang, Zhaocai Ma, Lian Li
Abstract. To solve name ambiguity problems and improve the performance of person name
disambiguation, we propose a three-stage clustering algorithm in the paper. In the first stage,
organizations and locations (OLs)are used to cluster documents about the same person，therefore some
texts with more resemblance will be assigned to one category. This stage is simply document clustering
based on the similarity of OLs. In the second stage, the clustered documents are used as a new data
source from which some novel features (like co-author names) are extracted. We used these new
extracted features to make additional clustering between documents. Meanwhile, a method was
proposed to solve name ambiguity problems by using social networks construction based on the
relationships among co-authors. In the third stage, webpages are further clusteredusing content-based
hierarchical agglomerative clustering (HAC) algorithm, then analyzing the useful content including
title and abstract and keywords (TAKs) to disambiguate the ambiguous names. Experimental results
show that our three-stage clustering algorithm can availably enhance the performance of person name
disambiguation.
Keywords: personnamedisambiguation;social networks;hierarchical agglomerative clustering
P276 CloudFlame: Cyberinfrastructure for Combustion Research
Authors: Gokop L. Goteng, Naveena Nettyam, S. Mani Sarathy
Abstract. Combustion experiments and chemical kinetics simulations generate huge data that is
computationally and data intensive. A cloud-based cyberinfrastructure known as CloudFlame is
implemented to improve the computational efficiency, scalability and availability of data for
combustion research.
The architecture consists of an application layer, a communication layer and
distributed cloud servers running in a mix environment of Windows, Macintosh and Linux systems.
The application layer runs software such as CHEMKIN modeling application. The communication
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layer provides secure transfer/archive of kinetic, thermodynamic, transport and gas surface data using
private/public keys between clients and cloud servers. A robust XML schema based on the Process
Informatics Model (PrIMe) combined with a workflow methodology for digitizing; verifying and
uploading data from scientific graphs/tables to PrIMe is implemented for chemical molecular structures
of compounds. The outcome of using this system by combustion researchers at King Abdullah
University of Science and Technology (KAUST) Clean Combustion Research Center and its
collaborating partners indicated a significant improvement in efficiency in terms of speed of chemical
kinetics and accuracy in searching for the right chemical kinetic data.
Keywords: CloudFlame, cyberinfrastructure, simulation, modeling, database, kinetics, combustion.
P277 Comprehensive Credit Evaluation Model of Electricity Customer Based on the Changing Trend
of Credit
Authors: Wenyong Du, Cheng Zhou, Bin Zheng, Chao Gao, Weiwei Kong, Sitong Cao
Abstract. In order to solve the credit quantification and scoring problem, this paper did some research
on credit evaluation model of electricity customers. The credit was divided into 5 first-grade indicators
and 15 second-grade indicators. The paper quantified these indicators and evaluated their weights by
utilizing Analytic Hierarchy Process model. The indicators were scored by utilizing exponential
scoring. According to the weight and scores of each indicator, we calculated the month credit values of
the last 12 months. Through these month credit values and their changing trend, the comprehensive
credit was calculated. We used a customer sample data to verify and analyze the model. The
experimental result shows that the model can evaluate credit indicators reasonably and effectively.
Thus, the credit quantification and scoring problem is solved.
Keywords:
credit evaluation; credit scoring; Analytic Hierarchy Process; exponential scoring;
changing trend of credit
P278 A Median Filtering Algorithm Based on Selected Point in Digital Image
Authors: Yan Liang, Yan Gao
Abstract. In this paper an algorithm of median filtering based on selected point is introduced, and it
improved the obscured phenomenon of the median filtering image. The algorithm based on the notion
of pixel tags, find the contaminated pixels in the sub-image area. And median filter the pixels only.
Experimental results show that the effect of the filtered image is ideal, and it has the advantages of
faster processing and little damage on the image.
Keywords: median filtering; Selected Point; Image Process
P286 Arc-length Constraint-Based Surface Deformation Using Energy- Minimum Optimization
Authors: Huanyu YANG, Kuangrong HAO, Yongsheng DING
Abstract. Deformation of 3D objects is an important problem in many application domains, such as
geometric modeling, computer graphics and computer-aided design. In this paper, we propose a
method for deformation of 3D objects with arc-length constraints. We convert the curve into the
polyline. Then we build the energy function of the polyline. Based on the minimum energy curve
method, the curve on the mesh is deformed with arc-length constraints and multi-points constraints.
The test results show that the proposed method has good performance. Compared to the other method,
shape preserving of the curve is better. Finally, we use this method for the deformation of the 3D
mannequin model.
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Keywords: component; Arc-length constraints, Deformation of 3D objects, Energy-Minimum
Optimization
P287 System Reliability-Aware Energy Optimization for Network-on-Chip with Voltage-Frequency
Islands
Authors: Jianxian Zhang，Duan Zhou, Yintang Yang
Abstract. In this paper, a novel energy optimization algorithm for Network-on-Chip (NoC) based on
voltage-frequency islands (VFIs) is proposed under the system reliability constraints. The proposed
algorithm mainly includes the three processes of VFI partitioning, assignment and task mapping to
reduce the energy consumption. A system reliability-aware mapping algorithm is proposed which
employs a hybrid algorithm based on quantum-behaved particle swarm optimization and
multi-neighborhood simulated annealing strategy. The optimum particles upon QPSO are further
optimized by annealing operation mentioned above. Besides, the catastrophic operation is executed to
enlarge the search scope and avoid getting into the local optimum. It minimizes the communication
energy consumption of NoC system on the condition of meeting system reliability constraints.
Experimental results show that the proposed algorithm is quite effective in optimizing energy
consumption of NoC with voltage-frequency islands under system reliability constraints.
Keywords: Network-on-Chip; Voltage-frequency Islands; System Reliability; Mapping
P288 Energy-Efficient Task Allocation for VFI-based Real-Time Multi-Core Systems
Authors: Xiaodong Wu, Jian-jun Han
Abstract. Chip Multiprocessor (CMP) has become computing engine for a wide spectrum of
applications due to its higher throughput and better energy efficiency. The problem of optimal
task-to-core allocation with the minimum energy consumption has been proven to be NP-hard. In order
to solve the energy-efficient real-time task mapping in the voltage-frequency islands (VFI) based
multicore system, we propose a heuristics EEGA (Energy-Efficient and Genetic Algorithm) to address
the problem. During the iteration process of the algorithm, the energy consumption of the processor can
be gradually optimized by the selection, crossover and mutation operators. Experimental results show
that when compared with other energy-efficient mapping algorithms, our proposed approach can gain
better performance with regard to the energy efficiency and schedulability ratio.
Keywords: energy-efficient; multi-core, voltage-frequency island; real-time system; task allocation;
dynamic voltage and frequency scaling
P289 Performance Comparisons of Evolutionary Algorithms for Walking Gait Optimization
Authors: Chaohong CAI, Hong JIANG
Abstract. To investigate the performance of different evolutionary algorithms on walking gait
optimization, we designed an optimization framework. There are four bio-inspired methods in the
framework, which include Genetic Algorithm (GA), Covariance Matrix Adaption Evolution Strategy
(CMA-ES), Particle Swarm Optimization (PSO) and Differential Evolution (DE). In the learning
process of each method, we employed three learning tasks to optimize the walking gait, which are
aiming at generating a gait with higher speed, stability and flexibility respectively. We analysed the
gaits optimized by each four method separately. According to the comparison of these results, it
indicates that DE performs better than the other three algorithms. The comparison also shows that the
gaits learned by CMA-ES and PSO are acceptable, but there exist drawbacks compared to DE. And
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among these methods, GA presents weak performance on gait optimization.
Keywords: CMA-ES, PSO, DE, Humanoid Robotics, Gait Optimization
P291 Intelligent optimization on power values for inverse distance weighting
Authors: LI Zhang-lin, GAO Jian-ying
Abstract. As a typical spatial interpolation method in geoscience and geographic data processing,
inverse distance weighting (IDW) method has a long-time standing problem which is how to choose
the best power value while calculating. For the issue, this text proposes an alternative way based on
enumeration and cross validation. By orderly analyzing and estimating the effectiveness of every
possible power value through cross-validation, this method can intelligently find the proper power
value. Additionally, a practical application procedure with a real dataset by the proposed method is
carried out as a typical case study, from which the calculation result is obviously superior to
conventional method. Thus, it is not difficult to conclude that both theoretical analysis and practical
application can show the validity and practicability of the proposed method.
Keywords: Inverse distance weighting; Power value; Spatial interpolation; Reserve estimation
P292 Super-Resolution Employing an Efficient Nonlocal Prior
Authors: Shuai Chen, Bin Chen, Yide He
Abstract. In this paper, we propose a novel approach for multiframe super-resolution reconstruction by
incorporating non-local prior in the maximum a posteriori (MAP) formulation. This prior expresses
that recovered images tend to exhibit repetitive structures. Due to the enormous amount of weight
calculations, the original non-local prior algorithm has a high computational cost. Techniques of weight
symmetry, moving averaging filter, limited search window are adopted to speed up non-local filter.
Meanwhile, Non-Linear Conjugated Gradient (NLCG) method is used to solve simultaneously the
high-resolution (HR) image of optimization process and non-local prior adapted to the HR image.
Experimental results on extensive synthetic and realistic images demonstrate the superiority of the
proposed algorithm to representative algorithms both quantitatively and qualitatively.
Keywords: non-local prior; non-local means; moving average filter; non-linear conjugated gradient;
MAP; super-resolution
P293 A new subpixel imaging method for image super resolution
Authors: Jihong Wang, Zuofeng Zhou, Jian Zhang, Jianzhong Cao, Qingquan Wu, Xinming Fan,
Zhendong Gong, Bing Zhao
Abstract. The subpixel imaging technique for image super resolution can get a higher resolution image
from two low resolution images which are observed from two linear array CCDs staggered half pixel
both along the flight direction and perpendicular direction.
In this paper, an adaptive weight
interpolation method which considers the Euclidean distance information from two low resolution
images for different size interpolation window is proposed. Compared with the traditional interpolation
method, the experiment results show the effectiveness of the proposed method.
Keywords: subpixel imaging, weighted interpolation, super resolution
P295 An algorithm for Delay-Reliability in communication networks based on probabilistic user
equilibrium model
Authors: Zhao Liu, Ning Huang, Dongpeng Li
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Abstract. In order to make a better performance analysis and reliability evaluation of communication
networks, a new definition of Delay-Reliability in communication networks, an algorithm to calculate
approximate solutions of the Delay-Reliability in communication networks, and a delay failure model
in communication networks are presented in this paper. Inspired by the road resistance function in
transportation networks, we analyze similarities and differences between communication networks and
transportation networks, and use OPNET simulation to build a new delay failure model in
communication networks. Based on probabilistic user equilibrium model and our delay failure model,
in stochastic-flow networks, we use discrete random variables to characterize delay in a single link and
the link’s degraded conditions to propose a new definition of Delay-Reliability in communication
networks and its corresponding approximate algorithm. The approximate algorithm is especially useful
and practical in large scale backbone network engineering due to its major computational advantage.
For illustration, an example is given to show that our definition, algorithm and delay failure model can
make a reasonable performance analysis and reliability evaluation of communication networks.
Keywords: delay; reliability; performance analysis; stochastic-flow network; probabilistic user
equilibrium; OPNET
P300 Quality Evaluation for Anxi Tieguanyin Tea Based on Electronic Nose and PCA-LDA Method
Authors: Hongxiu Liu, Dehan Luo, Fufang Li, Guowen Xie
Abstract. Tea is conventionally tested by human sensory panel called Tea Tasters, who assign quality
scores to different tea samples. This paper reports a method of the reliable measurement and correct
classification of Anxi Tieguanyin tea in Fujian province based on a kind of electronic nose
(E-nose):PEN3(Portable Electronic Nose Version 3.0). With the help of the E-nose, we analyze various
grades of different kinds of tea samples by using the popular method of separation, like PCA and LDA.
Experiments show that the method proposed in this paper has outstanding performance and high
efficiency.
Keywords: Electronic Nose;
Tieguanyin Tea; Tea Quality Evaluation; PCA; LDA
P302 A new method of optimization based on arc search
Authors: Xin Pan, Weikun Sun
Abstract. In order to efficiently solve the unconstrained optimization problem in which the objective
function is very nonlinear, an innovative framework of optimization which is different from line search
framework is proposed in this paper. This new method determines the step-length first with
nonmonotone line search technique, and generates a two dimensional subspace spanned by the
steepest-descent direction and an auxiliary vector. In this subspace, a circle with the current point as its
center and with step-length as it radius is constructed.
On this circle, the minimizer of the objective
function as the next iterative point can be calculated with arc search, and the search direction can be
generated with the minimizer and the current point. The variation of gradient of the objective function
in the search direction is used for determining the step-length of the next step. The global convergence
of this new algorithm is proved in this paper under some mild assumptions. Numerical tests illustrate
that this new algorithm is more efficient than conjugate gradient direction. The arc search improves the
efficiency of the iterative process. This new algorithm requires only the storage of three vectors such
that it is suitable for large scale problems.
Keywords: optimization; large scale problems; nonmonotone line search; arc search
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P303 Analysis on the Impact of Cloud Computing for Management Information System
Authors: Xiaojing Wang
Abstract. First of all, the concept of cloud computing and the present situation of management
information system are to be introduced. This is followed by an analysis of the impact of cloud
computing on MIS from the MIS development, operation and maintenance, as well as data security
aspects. The conclusion was that MIS development mode comprised of mashup, development
methodology oriented workflow, operation and maintenance is simple, service-oriented with
on-demand billing, resource cost minimalised, data security constrained. This paper can guide
enterprises to carry out MIS strategy planning and construction in the cloud, improving the efficiency
of MIS development and the probability of success, so as to enhance the core competitiveness of
enterprises.
Keywords: Management Information System, Cloud Computing, Mashup, Oriented Workflow, Data
Security
P305 Storage Space Reclaim Based on cluster Bitmap in the New Technology File System
Authors: Chanying Qi, Zhanhuai Li, Xiao Zhang, Huifeng Wang
Abstract. Thin provisioning is widely used to improve the utilization ratio of storage space in the
storage area network (SAN) environment. However, most of file systems only use the logical volume
offered by iSCSI protocol and does not support automatic reclaiming the space of thin provisioning.
The most major problem is that block-level storage device is difficult to perceive the release behavior
of the host application storage space. In order to solve the problem, we implement thin provisioning
iSCSI storage service system (ThinPro iSCSI Server) to reclaim the space in the NTFS file system. By
analyzing the chart structure about cluster bitmap, the prototype can identify the released space in the
NTFS file system automatically and efficiently. It uses flexible reclaim strategy to improve the
performing in the reclaim process, which can alleviate the influence of extra I/Os. By confirming the
data consistency before reclaiming the free space, it can avoid the data inconsistent problem and make
the method practically and robustly. Empirical results show that the method can delay the time of the
capacity warning and reclaim free space effectively. Moreover, it can improve the utilization rate of
storage greatly.
Keywords: thin-provisioning; SAN; reclaiming storage; NTFS file system; coherence
P307 A Method of Computing Iceberg Cube Based on Non-antimonotonic Constraint
Authors: Yuntian Feng, Hongjun Zhang ,Wenning Hao, Gang Chen
Abstract. To compute iceberg cube based on non-antimonotonic constraint, we propose a modified
Star-Cubing method by means of converting constraint by top-k. It uses a method of top-k to convert a
constraint to an antimonotonic constraint and carries out the star-reduction in the base cuboid table,
thus reduces the cost of the shared dimension pruning in Star-Cubing. Experimental results show that
the method could compute iceberg cube based on non-antimonotonic constraint availably and improve
the efficiency of computation method at the same time.
Keywords: top-k; Star-Cubing; star-reduction; shared dimension pruning
P309 Improvement of the data mining algorithm of Rough set under the framework of Map/Reduce
Authors: Wang Ying, Liu Ji-qing, Liu Qiong
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Abstract. In order to solve the problem that there is shortage of space and computing power of the
traditional spatial data mining algorithm during the processing for massive spatial data information, a
combination of Rough set and distributed framework is used in the processing of spatial data mining. In
this paper, parallel improvement is taken to the algorithm of traditional Rough set for spatial data
mining based on the basic theory of rough set and the Map/Reduce framework, which is efficient and
cheap. Then, a spatial data example is utilized to show the feasibility of the improved parallel
algorithm. Empirical results show that the improved parallel algorithm of Rough set for spatial data
mining can not only effectively improve the efficiency of the algorithm but also meet the need of
people to deal with massive spatial data which is hardly to the algorithm of traditional Rough set.
Improved Rough set parallel algorithm for spatial data mining can effectively solve the problem of
shortage for massive spatial data storage and computing power mining.
Keywords: Spatial data mining；Rough Set；Map/Reduce；Parallelization
P314 C# blueprint Action Pattern
Authors: Peng Gao, Jianbin Liu
Abstract. Software pattern is the solution of some fixed issues in software development. And it
improves the development efficiency. This paper raised the concept of C# blueprint pattern based on a
wealth of program model examples. And the formalized definition framework of C# blueprint action
pattern is summed up. The framework defines the rules of structure, semantics and so on. At last,
examples are raised to explain the C# blueprint action pattern. The raise of C# blueprint provides rapid
solutions to C# program modeling and improves the development and maintains efficiency of C#
program.
Keywords: C# blueprint; action mode; abstract syntax; MDA; formal framework
P316 Research on Digital Museum of Yunnan ethnic minorities’ resources based on Network
Authors: Jun Wang, Rong-kan Fan, Jian-hou Gan
Abstract. [Purpose] In order to solve the problem that Yunnan ethnic minorities’ resources don’t
obtain good publicity because of some restrictions such as time and geographical region. [Method] This
paper puts forward an efficient technique of comprehensive application of current three kinds of main
development technology to establish digital museum of Yunnan ethnic minorities’ resources, including
multimedia database, website, 3D object display system and virtual showroom.[Results] We
established multimedia database of Yunnan ethnic minorities’ resources, digital museum website of
Yunnan ethnic minorities’ resources, and 3D object display prototype system of Yunnan ethnic
minorities’ resources. It is especially significant to establish Digital Museum of Yunnan ethnic
minorities’ resources based on network for the protection and wide spread of Yunnan ethnic minorities’
resources.
Keywords: component; network; ethnic minorities’ resources; digital museum
P319 On the Availability of Replicated Data Managed by Hierarchical Voting
Authors: Yuuki Ueda, Hideharu Kojima, Tatsuhiro Tsuchiya
Abstract. Cloud services often depend on a mechanism that provides a reliable data storage that is
resilient to failures. Majority voting and hierarchical voting, an extension of majority voting, are both
used to implement such a mechanism in an unreliable network. For example, Apache ZooKeeper
adopts both of the two methods. This work considers the question whether or not hierarchical voting
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with two levels indeed improves data availability compared to majority voting. The simulation results
obtained so far suggest that hierarchical voting is unlikely to increase data availability.
Keywords: replication; majority voting; hierarchical voting; split-brain problem
P320 Research on Optimum Model for the Best Link of Expert System
Authors: Chen Guo, Jia-man Ma, Yue-fan Liu
Abstract. According to the observation of known facts, researcher finds all performances which are
conform to the observation of cognitive to associate with form knowledge base, and then build an
initial network model. Based on this model, we complete the mutual uncertainty constraint by using the
new achieve probability and effect probability between evidences and adjacent nodes. And on this basis,
using the drive method which satisfied competition threshold, keeping reasoning to the high level, until
find an object conclusion meets the expectation. The confirming result makes the best assuming
evidence become the centre of focus from competition. It decides the orientation of evidence which is
priority to be chosen, and give a high efficiency solution for choosing deterministic target by rapid
positioning and accurate selection.
Keywords: expert system; uncertainty; the best link
P321 Research on the Evidence Optimization Method Based on the Expert System
Authors: Chen Guo, Ming Huang, Xu Liang
Abstract. The research purpose of this paper is hope to quick select the evidence center, which
satisfied the object conclusion, from many uncertain observational evidences, effective position and
rapid inference. So in the process of first sampling, need to establish the sample center. This paper
established 4 collections of records, using the threshold algorithm based on competition to reason and
refine layer by layer, exclude the uncertainty disturbances, and find the optimal link existed in optimal
state. The optimal link determined the selection center of evidence reasoning object, provided the core
of evidence for subsequent optimization, achieved the objective of rapid position and accurate
inference.
Keywords: expert system; evidence optimization; uncertainty; optimized link
P322 Differential Evolution with Clustering Cooperative Coevolution for high-dimensional problems
Authors: Shuzhen Wan
Abstract. Evolutionary algorithms has been applied successfully to many optimization problems in
recent years. However, their performance will deteriorate when applied to complex high-dimensional
problems. A clustering-cooperative coevolution scheme was introduced into DE algorithm to tackle the
high-dimensional problems. In the scheme, the clustering method has been employed to decompose the
problem, which works well with the cooperative coevolution. The proposed algorithm is evaluated by
MPB and CEC09 benchmark functions with expanded dimension. The results show clearly that our
proposed algorithm is effective and efficient for dynamic high-dimensional optimization problems.
Keywords: Differential Evolution; clustering cooperative coevolution; high-dimensional optimization
problem
P323 Educational Geographic Information System Based on WebGIS
Authors: Mingyi Duan, Yajun Yang, Haibo Yang, Fang Zhao
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Abstract. Educational GIS (EDUGIS) based on Web is an important part of educational modernization
construction. In order to visually display and dynamically query the educational geographic
information, and give statistical analysis for educational spatial information and educational resource,
in this paper, the framework and functional structure of EDUGIS is designed based on MapServer, an
open source WebGIS platform. After the analysis of the organization structure of Ajax technology, by
combining the framework of open source platform MapServer and open-source database
PostGIS/PostgreSQL software, EDUGIS based on Web is realized. The research results show that the
EDUGIS is effective and useful for providing a timely, scientific and effective decision-making
support for educational body and education sector.
Keywords: WebGIS; Educational Geographic Information System; Ajax
P327 Cloud Model: Detect Unsupervised Communities in Social Tagging Networks
Authors: Hongbo Gao, Jing Jiang, Li Zhang, Deyi Li
Abstract. In the big data era, detecting unsupervised communities in a given dataset, analyzing the
evolution of the unsupervised communities, tracing the interests of users is very important. For instance,
we can capture user’s interest and provide him the personalized information. In order to detect
unsupervised communities in social tagging networks, this paper use similarity cloud properties of
cloud model to solve the different community analysis, classification, and describe the evolutions of
unsupervised communities quantitatively and users’ dynamic interests in unsupervised communities
problems. Cloud model is used in this paper. By introducing similarity cloud properties of cloud model,
cloud model can detect the unsupervised unsupervised communities, describe the evolutions of
unsupervised communities quantitatively, and users’ dynamic interests in unsupervised communities.
For illustration, the proposed model is applied to Del.icio.us dataset to detect unsupervised
communities and one month is used as time slice to study the evolutions of the unsupervised
communities. Empirical results show that unsupervised community in social tagging in network, using
Similarity cloud properties of cloud model can effectively detect different unsupervised communities,
and describe the evolutions of unsupervised communities quantitatively. Similarity cloud properties
based cloud model can effectively detect unsupervised community in social tagging network, and
quantitatively describe the evolutions of the community and community user’ dynamic interest. Hence,
CBUCD model is an efficient solution for detecting unsupervised community and analyzing evolutions.
Keywords: Cloud Model; Social Tagging; Unsupervised Community; Social Network.
P328 Image Zooming Method with Hierarchical Structure
Authors: Xiao Yi-han, Pang Yong-jie, Zhao Lan-fei
Abstract. Since the enlarged images which were calculated by traditional linear interpolation and
nonlinear algorithms are disturbed by blur and fuzzy edge, this paper proposes a new image zooming
algorithm with hierarchical structure. It employed the retinex model to decompose image into low
frequency layer and high frequency layer. The mirror signals which were introduced by up-sampling
course were filtered by low pass filter to reconstruct the low frequency layer. The heat equation was
adopted to reconstruct the high frequency layer with edge-preserving ability. The zooming images were
obtained by merging layers at last. Experimental results show that this algorithm improves the defects
of linear interpolation and nonlinear algorithms, the generated images via our algorithm possess
preferable visual effect.
Keywords: image zooming; linear interpolation; retinex; the heat equation
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P331 Study on Virtual Assembly System Based on Kinect Somatosensory Interaction
Authors: Hongjian Liao, XiaoLi Long
Abstract. To improve the efficiency of interaction and user experience in desktop-based Virtual
Assembly System (VAS), this paper proposed to establish low-cost but strong immerse virtual
assembly experiment system using Kinect and Unity3D engine. For the purpose of employing body
motion, gesture and voice to accomplish interaction tasks, establishing assembly model data, hand
gesture recognition and changing virtual assembly scene view by body motion were three key issues,
so “treelike hierarchy modeling”, “gesture semantics extension” and “multidimensional head tracking”
methods were proposed accordingly, and the implementation process was discussed. A Speed Reducer
Virtual Assembly System (SRVAS) was designed and realized by these methods, and practical results
show that the method of gesture recognition has a good accuracy and robustness, and is almost
unaffected by light and complex background. Kinect somatosensory interaction can improve
interaction efficiency and enhance user immersion with low-cost in 3D virtual system.
Keywords: somatosensory interaction; Kinect; virtual assembly system; gesture recognition; user
experience
P333 Mining Spam Accounts with User Influence
Authors: Kan Chen, Peidong Zhu, Yueshan Xiong
Abstract. As the increasing development of online social networks (OSNs), spammers’ attentions have
been attracted from the traditional email field. Nowadays, advertisements, deception messages, illegal
contents are prevalent in all kinds of ONSs. They’re propagated from one to another arbitrarily,
polluting the Internet environment, and what’s more, resulting in a great many of security problems.
Some previous works have been proposed to detect spammers according to user properties. The
problem is that in order to prevent from being detected, spammers are likely to pretend to be normal,
and what’s more, some normal users also engage into spam spreading for financial benefits, making
detection more difficult. In this paper, we solve the detection problem from the view of user influence.
The basic of our work is that since spammers pretend to be normal, their influences should keep step
with their normal behaviors. But when a spam campaign is launched, usually in order to influent others,
a great many of spammers engaged into propagation, the original poster’s influence would get a sudden
increase, making him outstanding from the others. In this way, we can distinguish the original
spammers and supervise from the root of the propagation tree. Our work is experimented on real data
gathered from Weibo and shows inspiring results.
Keywords: spam detection; user influence; online social network
P334 Factors Affecting Small and Medium-Sized Enterprise’s Information Technology Absorptive
Capability: An Empirical Study of Jilin Province in China
Authors: Lei Wang, Xinhua Bi, Yue Cao, Meiling Gu
Abstract. [Purpose] In order to find out the key factors affecting the Information Technology (IT)
absorptive capability of Small and Medium-sized Enterprises (SMEs), an empirical study is conducted
in this paper. [Method] Based on the three-dimensional structure and the influence model of IT
absorptive capability proposed by Cuiling Yu, and combined with the characteristics of SMEs, this
paper proposes a new model of influence factors, and meanwhile makes an empirical study on the
SMEs in Jilin province. [Results] Empirical results shows that IT consulting, IT infrastructure and
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government support have significantly impacts on the three-dimension of SMEs’ IT absorptive
capability. [Conclusions]
On the one hand, the paper reveals how the regions and industries as
control variables influence the IT absorptive capacity of SMEs; on the other hand, the paper reveals
that IT consulting has a special effect on IT absorptive capacity of SMEs.
Keywords: information technolgoy; big data; absorptive capability; small and medium-sized enterprise;
influential factors
P335 A Cloud-based Platform for Watching Same Content on Three-Screen TV Continuously in Smart
Home
Authors: Ehsan Ahvar, Gyu Myoung Lee and Noel Crespi
Abstract. Watching Same Content on Three-Screen TV Continuously (WSC3STVC) has been
considered as one of the representative services in smart homes recently. This service offers content
mobility among multiple kinds of screens based on user position in home. Quality of Experience (QoE)
and service implementation cost are two important challenges for supporting WSC3STVC service. To
the best of our knowledge, there is no visible attempt to design a comprehensive platform for
supporting this service in smart homes. Benefiting from cloud computing, peer-to-peer (P2P) network,
clustering and H.264 SVC transcoding, this paper proposes a QoE-aware and cost-effective platform
for supporting WSC3STVC service in smart home. The strong points of the proposed platform are
transcoding in cloud instead of Home GateWay (HGW) for decreasing HGW cost, content switching
inside HGW for reducing service delay, using a cloud-managed P2P network for improving bandwidth
between cloud and homes and also clustering homes for reducing transfer delay between homes.
Keywords: cloud-based; smart home; three screen TV
P336 Design of the Multi-level Inventory Control Model and Solution algorithm for the Spare Parts
Authors: CAO Yu, WANG Tiening, XU Shengliang, ZHU Yu
Abstract. The inventory control model based on the multi-objective programming of the spare parts is
set up. The algorithm of particle swarm optimization (PSO) is designed and improved to solve the
inventory control multi-objective programming model. Aiming at the question of the particle deviates
from the solution space and the prematurity problem in the searching course, the regain mechanism and
interference mechanism are build up to improve the classical PSO, and the switching mechanism from
the Cartesian space to the discrete space of inventory control model is established, and then the
optimized solution algorithm based on the improved PSO is presented. At last, the simulation
experiments of inventory control are made to validate the multi-objective programming model. It lays
the foundation for design and realization of simulation and optimization of the spare parts inventory
control.
Keywords: inventory control; the spare part; Multi-objective Programming; Particle Swarm
Optimization
P338 A research of massive distributed high voltage electrical online monitoring data management
platform based on cloud storage
Authors: Du Wenzhao, Zhao Linan
Abstract. High voltage electrical online monitoring can make us easily to get operating data of the
high-voltage electrical equipment in real time. And it is important to analyze these monitoring data,
because the result of the analysis can help us to know the healthy status of these devices, especially
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prompt us to concern the possible failures. Thus it is necessary to manage these monitoring data in a
proper way. In this research the authors analyzed the characteristic of the monitoring data and needs of
the monitoring data management. Based on the analysis the authors proposed to achieve the efficient
management of the massive distributed line monitoring data through the cloud storage platform. And
the cloud store platform is a three-tier architecture, the bottom is the substation level which is used to
storge the data of
the substation, and the middle is the regional level which is used to storage the data
of all the region, the top is the grid level, which is used to manage all monitoring data.
Keywords: component; high-voltage electrical; online monitoring data; cloud storage
P340 The universal approximation capabilities of 2pi-periodic approximate identity neural networks
Authors: Saeed Panahian Fard, Zarita Zainuddin
Abstract. A fundamental theoretical aspect of artificial neural networks is related to the investigation
of the universal approximation capability of a new type of a three-layer feedforward neural networks.
In this study, we present four theorems concerning the universal approximation capabilities of a
three-layer feedforward 2pi-periodic approximate identity neural networks. Using 2pi-periodic
approximate identity, we prove two theorems which show the universal approximation capability of a
threelayer feedforward 2pi-periodic approximate identity neural networks in the space of continuous
2pi-periodic functions. The proofs of these theorems are based on the convolution linear operators and
the theory of _-net. Using 2pi-periodic approximate identity again, we also prove another two theorems
which show the universal approximation capability of these networks in the space of pth-order
Lebesgue integrable 2pi-periodic functions.
Keywords: 2pi-periodic approximate identity, 2pi-periodic approximate identity neural networks,
continuous 2pi-periodic functions, pth-order Lebesgue integrable 2pi-periodic functions, Universal
approximation, Generalized Minkowski inequality.
P341 A Kind of Quadratic System Decoupling Method Based on Similar Transformation Solution
Authors: Wang Shujuan, Shen Jihong, Zhou Ying, Wang Chen
Abstract. The structure preserving decoupling method for quadratic system is proposed based on
similar transformation in this paper. Firstly, the problem to find two decoupling transformation is
converted to the problem to find one similar transformation. Secondly, the coefficient matrices of
decoupled system are identified according to the spectral information of original system. At last, based
on theoretical derivation the similar transformations are given by solving linear singular equation
numerically. The numerical experiments show feasibility of the method, and this paper shows a new
point for quadratic system decoupling researches.
Keywords: quadratic system; Lancaster structure; structure preserving; system decoupling; Kronecker
product
P342 Fuzzy logic-based fault diagnosis of simply supported bridge using modal frequency as input
variable
Authors: Yongchun Cheng, Hongbin Guo, Xianqiang Wang, Yubo Jiao
Abstract. Fault diagnosis of bridge is critical to guarantee the safe operation of structure. A fuzzy
logic-based damage detection method is proposed in this paper to identify the single and multiple
damages of bridge. Modal frequency is adopted as input parameter, while the damage severity is output
one. Gauss and Bell functions are used as membership functions for input and output parameters,
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respectively. The fuzzy rule base is established according to suitable acquisition method. Numerical
simulation for a simply supported bridge is used to verify the feasibility of the proposed method. The
results reveal that the established fuzzy system possesses favorable memory, inference and anti-noise
abilities. Its antinoise level is favorable. The fuzzy logic method is feasible for fault diagnosis of bridge
structure with single and multiple
damaged locations under noise effect.
Keywords: simply supported bridge; fault diagnosis; fuzzy logic; numerical simulation
P347 Research of Clustering Algorithm based on Information Entropy and Frequency Sensitive
Discrepancy Metric in Anomaly Detection
Authors: LI Han, WU Qiuxin
Abstract. Anomaly detection is a method to detect intrusion behaviors including system or users’
non-normal behavior and unauthorized use of computer resources. Clustering analysis is an
unsupervised method to group data set into multiple clusters. Using clustering algorithm to detect
anomaly behavior has good scalability and adaptability. This paper mainly focuses on improving
k-means clustering algorithm, and uses it to detect the abnormal records. Our goal is to increase the DR
value and decrease the FAR value in anomaly detection by calculating appropriate value of parameters
and improving the clustering algorithm. In our IE&FSDM algorithm, the initial cluster centers can be
calculated by the minimum standard information entropy of records. In testing phase, discrepancy metric
is introduced to help calculate exact number of clusters in testing data set. Using the results of initial
cluster centers calculated in the pre-phase, IE&FSDM compute the actual clusters by converging
cluster centers and obtains the actual cluster centers according to the frequency sensitive discrepancy
metric. Then comply with the improved k-means algorithm, iterative calculate until divide all network
records into different clusters, and then the normal and abnormal behaviors are classified. Experiment
based on KDD CUP1999 dataset is implemented to test the performance of IE&FSDM algorithm.
Results show that IE&FSDM has a higher detection rate and a lower false alarm rate, and achieves the
expectant goal.
Keywords: k-menas; Clustering Analysis; Anomaly Detection; Information Entropy; Discrepancy
Metric
P349 Research and Implementation of data collection protocol for wireless sensor networks
Authors: Xongke Xu, Xiaohong Wang, Mingqiang Song, Teng Feng, Liang Dai, Xiangjun He
Abstract: Wireless Sensor Network is a new self-organization and multi-hop network which deploys a
lot of nodes communicating with each other wirelessly, so the design of a appropriate routing protocol
for wireless sensor networks is essential. In this script, the performances of many classical route
strategies are introduced and analyzed. In order to test the LEACH and LEACH-C algorithm’s
performance, the NS2 (Network Simulator Version 2) is used to realize the simulation of the LEACH
and LEACH-C algorithm in three different scenarios and analyze the results from three angles. The
result shows that, in condition that the SINK node is not far from the deployed sensors, no matter the
nodes are randomly deployed or deployed in linear, LEACH-C performs much better than LEACH. In
the opposite condition, LEACH will perform better than LEACH-C except in the data throughput.
Keywords: wireless sensor network; routing protocol; LEACH; LEACH-C; NS2
P350 Research and design of the clock synchronization for the bridge health monitoring system based
on Wireless Sensor Network
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第三届信息科学与云计算国际学术会议
Authors: Hongke Xu, Mingqiang Song, Xiaohong Wang , JiaYu Yang, Enmao Quan
Abstract. This paper constructs a bridge health monitoring system based on Wireless Sensor Network.
In order to detect and obtain the bridge’s status information, we have studied the clock synchronization
problem between the sensor nodes in wireless sensor network of the bridge health monitoring system.
The clock synchronization simulation verifies the design of asymmetrical clock synchronization
algorithm in the wireless sensor of the bridge health monitoring system is valid and reliable. The
simulation results show that this clock synchronization algorithm can realize the clock synchronization
and be able to monitor real-time bridge conditions.
Keywords: bridge health monitoring system;wireless sensor network (WSN);asymmetric type of
adaptive algorithm; the clock synchronization algorithm
P351 Cluster Analysis on the Flow Velocity for the Sea Route Monitoring
Authors: Yanling Zhang , Shujuan Wang, Xiaodong Peng , Zhiqiang He, Chunjiang Zhang, Wei
Huangfu
Abstract. Due to the importance of the marine resources, the limited sea routes are valuable to the
marine transportation. With sensors deployed under the sea, the data of flow velocity are obtained via
wireless communications. Based on the real historical data collected from Qinhuangdao port, which is
one of the most important ports in the North China, the rules is attempted to be revealed with the data
mining methods. By cluster analysis on the historical data, we classifies the days into P-days and
F-days. In different kinds of days, the characteristics of the flow velocity under the water are different.
It is a novel analysis of the data for the sea route monitoring. Although it is only a preliminary
exploration in this field, the results is helpful to the safety and efficiently scheduling of the sea routes.
Keywords: flow velocity, cluster analysis, change rules, voyagers’ sailing
P352 Optimal Constellation Mapping for Pulse Amplitude Modulation Based Vertical Physical-Layer
Network Coding
Authors: Youyun Xu, Fengyue Gao, Kui Xu, Jianfeng Zhang
Abstract. This paper discusses the denoise-and-forward (DNF) problem in two-way relay channel
(TWRC). A pulse amplitude modulation (PAM) based vertical physical-layer network coding (VPNC)
scheme is proposed and the optimal constellation mapping is studied to minimize the bit error rate
(BER) and symbol error rate (SER) performance. Compared with the existing PNC scheme in which
the relay superimposes two users’ signals of the same constellation, two users in the proposed VPNC
scheme transmit PAM signals with vertical constellation and the relay superimposes two signals of
vertical constellation. The closedform BER and SER expressions of the proposed VPNC scheme are
also derived in this paper. Simulation results agree well with the theoretical analyses. Meanwhile,
simulation results show that the proposed VPNC scheme outperforms the conventional PNC scheme on
the SER and BER performance and optimal constellation mapping can obtain a about 1dB performance
gain.
Keyword: Physical-layer network coding; denoise-andforward; two-way relay channel; vertical
constellation mapping.
P354 Research on XML keyword query method based on semantic
Authors: Guofeng Zhao, Shan Tian
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第三届信息科学与云计算国际学术会议
Abstract. In this paper, we study the problem of effective keyword search over XML documents,
Keyword search for smallest lowest common ancestor(SLCA) in XML data has recently been proposed
as a meaningful way to identify interesting data nodes in XML data where their subtrees contain an
input set of keywords. XML retrieval technology has been concerned widely by information retrieval
researchers. XML data contains rich semantic information, but most of query methods can’t make full
use of the semantic information. There will be missed case if there is no enough semantic information.
This paper proposed a new XML keyword query algorithm based on semantic(SKSA) to solve the
question above. The algorithm takes full use of the node semantic information based on structural
semantic. The same or similar results will be returned to users if there is no the keyword in XML
document, which avoids the missed case. The test experiment result on the real XML data sets shows
that SKSA has higher recall rate, and can match the user’s query intention better.
Keywords: XML; keyword search; semantic; synonyms; WordNet
P357 Preserving Social Network Privacy Using Edge Vector Perturbation
Authors: Lihui LAN, Lijun TIAN
Abstract. Social network applications have become popular. The researchers can benefit through
social network analysis, but it raises serious privacy concerns for the individual involved in social
network. Some techniques have been proposed for protecting personal privacy. However, the existing
methods tend to focus on un-weighted social network for anonymizing nodes and structure information
or weighted social networks for annoymizing edge weight. We propose an edge vector perturbation
method to preserve structural properties and edge weights for weighted social networks. First, we
construct edge vector or edge space of the original weighted social network. Second, we calculate edge
betweenness and assign weights to elements in edge vector. Third, we construct release candidate set
by the weighted Euclidean distance. We leverage the notions of edge vector and edge space in
S
weighted social network. Given a social network G , we adopt two methods to build original edge
vector E _ Vec (G ) . Select from some edge vectors from  ( K n ) as publication candidate set of
S
S
E _ Vec (G ) . To ensure effectiveness of the released dataset, we use Euclidean distance between the
vectors as metrics of the similarity. We execute experiments on datasets to study publication utility and
quality. Our method can be applied to a typical perturbation algorithm to achieve better preservation of
the utility of its output.
Keywords: social network; privacy preservation; edge vector; candidate set; Euclidean distance
P359 A New Approach of Face Identification in Line Drawings
Authors: Weikun Sun, Xin Pan
Abstract: Face identification is the key step for reconstruction of a three dimensional object from a
single two-dimensional line drawing depicting it. Many methods have been presented to solve this
problem, and none of them considered the convexity of cycle polygon. In this paper we propose a new
approach of face identification in line drawings, which combines together graph theory and convex
property of polygons. With considering the convexity, we can overcome the difficulty of non-convex
cycle polygons and our algorithm can deal with 3D solids of over 10,000 potential faces with efficiency.
A couple of examples are provided in the end to show that our approach can handle some complex 3D
reconstructions.
Keywords: face identification; line drawing; graph theory; convexity
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P362 Bigraph-based Modeling and Tracing for the Food Chain System
Authors: Xue Li , Xiaoyuan Liu, Ying
Zhao, Xiaodong Peng, Wei Huangfu, Zhongshan Zhang
Abstract. Food chain is one of the most complex, dynamic and essential systems in the world. It is
fundamental to reveal the characteristics and build the behavior model of such a huge system in order
to keep the food chain safe, secure and efficient. A novel bigraph-based food chain model is introduced
to express the various one-to-one, one-to-many and many-to-many relations in the food chains, which
also offers a traceable capacity to seek both the mid procedures and the roots for food safety issues.
The modeling and tracing for the food chain system are discussed then verified with an implementation
including database storage and web service, which is implicational for the future applications in the
traceable food chain systems.
Keywords: food chain; bigraph; traceability; modeling; traceable food chain system.
P363 A process-oriented ontology-based knowledge model
Authors: Yanhong Zhao, Hongqi Li, Liping Zhu, Fengqi Tan and Ying Wang
Abstract. With the rapid growth of knowledge resources, the production departments in the field of oil
and gas exploration and development produce daily a great volume of result documents. Meanwhile, a
large part of knowledge is stored in the experts’ brain as experience. How to spend less effort finding
knowledge meeting users' need and how to make effective use of the expertise to avoid knowledge loss
become more and more important. This paper adopts a knowledge model which is composed by
process model and ontology model in the subject of Well Site Deployment. In this knowledge model,
the process model provides the detailed operation flow and data flow, the ontology model provides the
evaluating standards and the operating standards. We build a web-based knowledge service platform
based on this knowledge model, through which knowledge can be shared between experts and
non-experts. Furthermore, users can reuse the knowledge and trace the existing work results of well site
deployment and development by the platform. All of these can help the final users to improve the
efficiency of decision making.
Keywords: Knowledge service; Process model; Ontology; Knowledge model
P364 The design and implementation of Knowledge Processing and Decision-making Model Based on
Multi-class in Agricultural Expert System
Authors: LIU Yi, XU Ke, SONG Junde, Xin Liao, ZHAO Yuwen
Abstract. This paper introduces the current status of the knowledge processing and decision-making of
expert system, and proposes a knowledge processing and decision-making model based on
class-frames-production rules and case base in order to solve the problem of large quantity and many
types of knowledge in agricultural expert system. We design the knowledge processing process and
reasoning and decision-making process of the model. And finally we take the pests problem of
Lu-cotton 11th as an example, introduce the work steps of the model, and verify the feasibility of the
model.
Keywords: knowledge processing；decision-making；agricultural expert system
P365 An Environment Recognition Algorithm Based on Weighted Cloud Classifier
Authors: Zhao Yang, Liu Hongya
Abstract. Environment recognition is a necessary prerequisite for behavioral decision and intelligent
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control of intelligent vehicle. In order to improve the surrounding environment recognition ability of
intelligent vehicles, a weighted cloud classifier is constructed to recognize the content of image
captured by vehicle camera. By researching the image texture characters, several cloud classifiers are
trained based on first and second order statistical characteristics of texture to identify image content
preliminarily. Then cloud models are combined with adaboost algorithm to construct a weighted cloud
classifier. Experiment results show that through weight optimization, the weighted classifier can realize
multi-target recognition, and achieve good results in the recognition of vehicle, road, lane line and
other targets. The weighted cloud classifier will play an important role in improving the environment
recognition and behavioral decision capacity of intelligent vehicle.
Keywords: Recognition; Cloud model; Classifier; Weighted optimization
P366 Games with connected player strategies for analyzing the competitiveness of a railroad company
in a cargo transportation marketplace
Authors: Alexander S. Belenky, Alexandra I. Yunusova
Abstract. The competitiveness of a railroad company in a marketplace of cargo transportation in a
region of a country is analyzed with the use of two mathematical models in the form of two-person
games in which all the feasible player strategies are connected, i.e., cannot be chosen by the players
independently, and the set of these connected strategies is a polyhedron described by a system of
compatible linear inequalities. The first model is used to analyze the case in which the railroad
company competes with all the other cargo carriers that offer their services in the region, for instance,
with tracking companies, whereas the second model helps find potential profitable coalitions of the
company with some of these carriers in an attempt to enlarge the company’s fair share of the market as
much as possible on account of providing a “door-to-door” service for clients that need to move high
volumes of cargo over long distances.
Keywords: Coalitions, competitiveness, equilibrium, games, polyhedron, quadratic optimization
problems, railroad company, transportation tariffs
P369 Topological Analysis of a Complex Trust Network
Authors: KUANG Xiangling, HUANG Guangqiu
Abstract. In view of the problem that the current trust models only are simulated in a simple network
or a small-scale network, ignoring the macroscopic properties of trusted network, a complex trust
network is built by using complex network approach and some important topological properties of the
network are quantitative analyzed from macrospector perspective. First a trust model is built with
complex network approach, and then several topological properties, such as node degree, cumulative
degree distribution, k- core, network clustering coefficient, network average path length, and
betweenness are analyzed by using the actual large-scale network data. These properties indicate that
the complex trust network is a small-world network with scale-free characteristic. At last the practical
value of these indicators is analyzed.
Keywords: complex network; trust network; topological properties
P371 A Clustering-based QoS Prediction Approach for Web Service Selection
Authors: Zhang Xuejie, Wang Zhijian, Lv Xin, Qi Rongzhi
Abstract. With the increasing number of Web services, recommendation and selection of the optimal
Web services has become one of the most important challenges in the service computing field. The
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goal of consumers is to discover and use services which lead to them experiencing the highest quality.
Existing approaches to quality evaluation mostly assume a consumer's primary goal as being
optimization of performance, so that consumers are unable to effectively identify and engage with
providers who deliver services that will best meet their needs. In order to solve this problem, we
propose a clustering-based QoS prediction framework for Web services. In our framework, we employ
the k-means clustering algorithm. We determinate the similarity between consumers based on their
expectations. In terms of the relationship between their expectations and the rating of the services, we
predict the rating of a service used to select desirable services. At last, the experiment shows that the
approach achieves better prediction.
Keywords: web service; QoS prediction; clustering; expectation
P373 Study on e-commerce service supply chain coordination based on contract theory
Authors: Fatao WANG
Abstract. In order to solve e-tailing service integrator's go-ods and logistics service coordination
problem, this paper designs a supply chain model which consists of a product supplier, an e-retailer and
a logistics service provider. The purpose of this model is to analyze the effectiveness of three types of
supply chain contracts within the e-commerce logistics service supply chain. This article will analyze
wholesale price contracts, revenue sharing contracts and quantity flexibility contracts. The models
under three types of contracts are constructed to analyze the optimal decisions. In addition, the article
will explain why managers in the e-commerce industry should adopt these supply chain contract
approaches to increase revenues. The models described in the study could be seamlessly utilized by
e-retailers and logistics service providers to maximize their revenues and profits. The results show that
this model can coordinate the e-commerce logistics service supply chain by adjusting contract
parameters and improve the profits of the members.
Keywords: service supply chain; e-commerce; modeling; coordination
P380 A Data Compression Algorithm for the Sea Route Monitoring with Wireless Sensor Network
Authors: Yang Li, Shanni Xi, Chunjiang Zhang, Wei Huangfu, Zhongshan Zhang
Abstract. The wireless sensor network plays a significant role in monitoring the environment near the
harbour in order to inform the ships nearby out of dangers and optimize the utilization of limited sea
routes. Based on the historical data collected by the buoys with sensing capacities, a novel data
compression algorithm named PCVQ is introduced to lower the budget of wireless communication
subject to the constrains of data precision. The principal components of the sensing data are analysed.
With such principal components and statistical of historical data, the optimal codebook is acquired by
the technology of vector quantization. The on-line data are decomposed with the historical principal
component coefficients, and then compressed according to the optimal codebook. The PCVQ algorithm
is verified with the practical data in Qinhuangdao Port of China, which is a novel exploration in the sea
route monitoring.
Keywords: wireless sensor network, sea route monitoring, data compression, principal component
analysis