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IET International Conference on Information science and Control engineering

作者： Rong Ding Xu Liu Weilong Cui Yadong Wang State Key Laboratory of Software Development Environment School of Computer Science and Engineering Beihang University Beijing 100191 China|c|

ISBN: (纸本)9781629939254

Foreground detection is an important and challenging task in the traffic surveillance applications, especially at urban intersections. A very common solution for foreground detection with static cameras is background subtraction. When the background is modeled, learning rate is an important parameter and is difficult to select. Difficulties of background updating usually come from complex physical scenarios such as sudden illumination changes and occlusion. Conventional background modeling algorithms usually use the same learning rate for the entire frame or sequence and are not able to match the environment changes adaptively. Although some improvements with adaptive learning rate have been achieved, they are still not appropriate for complex traffic intersection scene. This paper addresses the problem of background subtraction at busy intersection and proposes a new method for vision-based foreground detection. It assigns a learning rate adaptively for each pixel according to the information collected by the infrastructure-based networked system, also called a Cyber-Physical System (CPS). Our goal is to provide a simple and efficient solution to improve the robustness and accuracy of intersection foreground detection. We test our approach in urban traffic intersection and the experimental results show that the new method has a promising future.

关键词： Foreground detection Background subtraction Intersection Adaptive learning rate Cyber-physical systems

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Welcome Message from the Chairs

Welcome Message from the Chairs

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Asia International Conference on Modeling & Simulation

作者： David Al-Dabass Jasmy Yunus Dayu Giriantari Zuwairie Ibrahim Satya Kumar Department of Computer Science and Engineering The University of Aizu Japan State Key Lab of Software Development Environment Beihang University China

Asia Modelling Symposium 2012 (AMS2012), the sixth Asia international conference on mathematical modelling and computer simulation, received submissions from over 20 countries. The conference program committee had a very challenging task of choosing high quality submissions. Each paper was peer reviewed by several independent referees of the program committee and, based on the recommendation of the reviewers, 43 papers were finally accepted. The papers offer stimulating insights into emerging modelling and simulation techniques for intelligent and hybrid intelligent systems and systems that employ intelligent methodologies.

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Content Addressable Storage Optimization for Desktop Virtualization Based Disaster Backup Storage System

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China Communications 2012年第7期9卷 1-13页

作者： Ruan Li Xiao Lim in Zhu Mingfa State Key Laboratory of Software Development Environment Beijing 100191 P. R. China School of Computer Science and Engineering Beihang University Beijing 100191 P. R. China

This paper proposes a content addres sable storage optimization method, VDeskCAS, for desktop virtualization storage based disaster backup storage system. The method implements a blocklevel storage optimization, by employing the algorithms of chunking image file into blocks, the blockffmger calculation and the block dedup li cation. A File system in Use Space （FUSE） based storage process for VDeskCAS is also introduced which optimizes current direct storage to suit our content addressable storage. An interface level modification makes our system easy to extend. Experiments on virtual desktop image files and normal files verify the effectiveness of our method and above 60% storage volume decrease is a chieved for Red Hat Enterprise Linux image files. key words： disaster backup; desktop virtualization; storage optimization; content addressable storage

关键词： disaster backup desktop virtualization storage optimization content addressable storage

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USO- a new Slope One algorithm based on modified user similarity

USO- a new Slope One algorithm based on modified user simila...

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International Conference on Information Management, Innovation Management and Industrial engineering, ICIII

作者： Mingtao Sun Hui Zhang Shiyu Song Kejia Wu State Key Software Development Environment Laboratory Beihang University Beijing China School of Computer Science and Engineering Beihang University Beijing China

ISBN: (纸本)9781467319324

Recommendation algorithm based on collab.rative filtering strategy has achieved great success in the field of personalized recommendation, However, based on collab.rative filtering recommendation algorithm complexity is too high, over-fitting problem, the recommended accuracy requirements lead to the algorithm difficult to achieve in practical applications. Slope One algorithm greatly simplifies the complex process of collab.rative filtering algorithm, dramatically reducing the recommended system and maintenance difficulty, but at the same time recommended the accuracy will decline. Recommended in order to take into account the recommendation algorithm of low complexity and high accuracy, the authors propose the improved algorithm based on the correct user similarity Slope One - USO algorithm The inspection results show that the algorithm can effectively improve the accuracy of the recommendation of the slope-one algorithm.

关键词： Educational institutions Accuracy

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Context-based requirement modeling for self-adaptive service software

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Journal of Computational Information Systems 2012年第24期8卷 10131-10140页

作者： Liu, Wei Feng, Zaiwen School of Computer Science and Engineering Hubei Key Laboratory of Intelligence Robot Wuhan Institute of Technology Wuhan 430073 China State Key Lab. of Software Engineering Wuhan University Wuhan 430072 China

Service-oriented self-adaptation software (SoSAS) utilizes services as fundamental elements for developing applications that have the capability to autonomously modify their behavior at run-time in response to changes in their environment. While a few techniques have been developed to support the modeling and analysis of requirements for self-adaptive systems, limited attention has been paid to the description of service requirements and uncertainty in requirements of SoSAS. In this paper, we propose a context-based requirement representing and modeling framework as a fundamental of self-adaptation evolution. We introduce a context snapshot model to represent uncertainty in requirement with domain knowledge;goal-oriented context requirement to model user requirements and process-oriented context requirement to model service requirements;and finally, propose means-c-end analysis to relate user and service requirement with context condition. We illustrate and evaluate our approach through three scenarios of city intelligent traffic domain in the support tool ConUSER. © 2011 by Binary Information Press.

关键词： Uncertainty analysis

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Model-driven tenant development for PaaS-based SaaS

Model-driven tenant development for PaaS-based SaaS

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IEEE International Conference on Cloud Computing Technology and science (CloudCom)

作者： Wei-Tek Tsai Wu Li Babak Esmaeili Wenjun Wu Department of Computer Science and Technology INLIST Tsinghua University Beijing China School of Computing Informatics and Decision Systems Engineering Arizona State University Tempe AZ USA State Key Laboratory of Software Development Environment Beihang University Beijing China

This paper proposes key SaaS (software-as-a-Service) design strategies for those SaaS systems that run on top of a commercial PaaS (Platform-as-a-Service) system such as GAE (Google App Engine)[1]. Specifically, this paper proposes a model-based approach for customization, multi-tenancy architecture, scalab.lity, and redundancy & recovery techniques for GAE. The ACDATER (Actors, Conditions, Data, Actions, Timing, Events, and Relationship) model is used for various features, and then automated code generation is used to generate code based on the model specified. Simulation can be performed to ensure correctness before deployment.

关键词： software as a service Databases Computational modeling Scalab.lity Reliability Data models

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R-calculus without the cut rule

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science China(Information sciences) 2011年第12期54卷 2550-2563页

作者： LUO Jie & LI Wei state key lab.ratory of software development environment, school of computer science and engineering, Beihang University, Beijing 100191, China 1. State Key Laboratory of Software Development Environment School of Computer Science and Engineering Beihang University Beijing 100191 China

R-calculus is an inference system for deducing all possible changes when a theory is refuted by the facts. In this paper, we try to eliminate the cut rule in R-calculus by modifying the existing rules and by introducing new rules. The result is the R-calculus without the cut rule, which still preserves the reachability, soundness and completeness as R-calculus does. R-calculus without the cut rule is a formal inference system of logical connective symbols and quantifier symbols solely. It can serve as the theoretical foundation of the automation of revision calculus.

关键词： revision R-calculus cut rule

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Energy prediction for MapReduce workloads

Energy prediction for MapReduce workloads

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9th IEEE Int. Conf. on Dependable, Autonomic and Secure Comput., DASC 2011, incl. 9th Int. Conf. on Pervasive Intelligence and Computing, PICom 2011, 9th Int. Symp. on Embedded Computing, EmbeddedCom 2011, 1st Int. Conf. on Cloud and Green Comput.CGC

作者： Li, Wenjun Yang, Hailong Luan, Zhongzhi Qian, Depei State Key Laboratory of Software Development Environment School of Computer Science and Engineering Beihang University Beijing China

ISBN: (纸本)9780769546124

Energy efficiency of data centers has attracted wide research attention with growing concern for power consumption and heat dissipation. Map Reduce as an efficient programming model for data-intensive computing is increasingly popular among industrial companies and academic organizations. As Map Reduce is developed specifically to process large-scale data analysis, its impact on energy efficiency of data centers has not been well scrutinized. Recently some energy conserving strategies have been proposed to reduce the overall power consumption of Map Reduce clusters. The fundamental ideas of previous work can be summarized as scaling down working nodes and reducing execution time. However, there are few researches on energy prediction for Map Reduce workloads, which can offer guide for cluster administrator to make power budget or schedule workloads to clusters with different power budget, and be useful for monitoring workloads' energy consumption. In this paper, we identify several workload metrics that have strong correlations with energy consumption. We use multivariate linear regression to analyze these metrics, and then construct a prediction model. Regression diagnosis is performed intensively to optimize the prediction model. After applying to the Word Count and Sort workloads with various input size, we find our prediction model is highly accurate with 0.12% and 0.15% inaccuracy compared to the observed energy consumption in the best and worst cases. © 2011 IEEE.

关键词： MapReduce

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Accelerate GMSK demodulation using GPU

Accelerate GMSK demodulation using GPU

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2011 International Conference on System science, engineering Design and Manufacturing Informatization, ICSEM 2011

作者： Gao, Xiaopeng Dong, Deping State Key Laboratory of Software Development Environment School of Computer Science Engineering Beihang University Beijing China

ISBN: (纸本)9781457702471

Gaussian Filtered Minimum Shift keying(GMSK) is used extensively in radio communication field nowadays;as frequency of radio signals increases, traditional technology such as DSP and FPGA can't satisfy the real-time requirement due to its complexity and compute-intensive. The development of modern GPU makes this possible. In this paper, a Gaussian Filtered Minimum Shift keying (GMSK) demodulation was implemented using CUDA on GPU. Since the demodulation process was largely executed on the GPU, the method can take full advantage of massive computational power of modern graphics hardware. The experiment results show that our GPU based GMSK implementation can gain nearly 20x speedups compared with the serial algorithm. © 2011 IEEE.

关键词： Demodulation

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Safety mechanism of RTOS on multi-core processor

Safety mechanism of RTOS on multi-core processor

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2011 International Conference on System science, engineering Design and Manufacturing Informatization, ICSEM 2011

作者： Wu, Jiangtao Long, Xiang Wang, Lei State Key Laboratory of Software Development Environment School of Computer Science and Engineering Beihang University Beijing China

ISBN: (纸本)9781457702471

In safety critical area, even the slightest error of the operating system could lead to a significant property damage or casualties. As a result, the safety of the RTOS (Real Time Operating System) must be improved. Rushby etc. have done lots of research on safety kernel. Multi-core processor is developing rapidly. This paper presents that the safety of real time system can be improved with a multi-core processor running a main operating system and a separated safety kernel. In addition, this paper gives a simple implementation and verifies its feasibility on MPC8641D. © 2011 IEEE.

关键词： Real time systems

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