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MEC International Conference on Big Data and Smart City (ICBDSC)

作者： Jiang Zhong Weili Guo Zhenhua Wang Key Laboratory of Dependable Service Computing in Cyber-Physical Society Chongqing University Chongqing city China College of Computer Science Chongqing University Chongqing city China

To avoid unpredictable losses because of network failure, the reliability of the network needs to be evaluated in some application scenarios. This paper start the network failure prediction research upon 14 months' network alarm logs we collected. The logs are of one Metropolitan area network. The research method is shown as below: firstly, construct features to represent network characteristics by the means of the feature construction method which is based on two levels time windows; secondly, select optimal parameter combination to create the feature files through multiple experiments; thirdly, design and build adaptive failure prediction model according to classification learning methods. Numbers of experiments show that accuracy of predicting whether the network failure takes place in 6 hours is up to 70%, is better than the prediction result of Weibull distribution model obviously; the results of classification prediction for network equipment failure are slightly better than the prediction method on the basis of Weibull distribution. Preliminary research results show that most network failures can be predicted through analyzing previous network running logs and the method proposed in this paper is verified to be with good prediction effect. This method can detect failures in practical application on early stage and reduce unnecessary economic losses.

关键词： Predictive models Adaptation models Data models Data mining Big data Smart cities

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Robust Adaptive Control of Nonlinear Systems with Asymmetric Non-smooth Saturation

Robust Adaptive Control of Nonlinear Systems with Asymmetric...

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第28届中国控制与决策会议

作者： Xuehai Tu Junfeng Lai Kai Zhao Institute of Smart System and Renewable Energy School of AutomationChongqing University The Key Laboratory of Dependable Service Computing in Cyber Physical Society of Ministry of Education Chongqing Universit

ISBN: (纸本)9781467397155

In this paper,the robust adaptive control is proposed for a class of parametric uncertain nonhnear system with asymmetric non-smooth input *** introducing a well-defined smooth function,a robust adaptive control algorithms are developed to deal with the problem of asymmetric non-smooth *** most of the existing control schemes for the uncertain nonhnear system,which requires an assumption that the control gain is an unknown constant,the developed controller only needs that the control gain is a bounded and unknown time-varying *** this work,the robust adaptive controller can guarantee global uniform boundedness of the closed-loop system signals as rigorously proved by Lyapunov analysis.A simulation results is presented to illustrate the effectiveness of the proposed adaptive control technique.

关键词： Robust Adaptive Control Asymmetric Non-Smooth Saturation Uniformly Bounded

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Shilling attack detection in recommender systems via selecting patterns analysis

Shilling attack detection in recommender systems via selecti...

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作者： Li, Wentao Gao, Min Li, Hua Zeng, Jun Xiong, Qingyu Hirokawa, Sachio Key Laboratory of Dependable Service Computing in Cyber Physical Society Chongqing University Ministry of Education Chongqing400044 China School of Software Engineering Chongqing University Chongqing400044 China College of Computer Science Chongqing University Chongqing400044 China Research Institute for Information Technology Kyushu University Fukuoka-shi812-8581 Japan

Collaborative filtering (CF) has been widely used in recommender systems to generate personalized recommendations. However, recommender systems using CF are vulnerable to shilling attacks, in which attackers inject fake profiles to manipulate recommendation results. Thus, shilling attacks pose a threat to the credibility of recommender systems. Previous studies mainly derive features from characteristics of item ratings in user profiles to detect attackers, but the methods suffer from low accuracy when attackers adopt new rating patterns. To overcome this drawback, we derive features from properties of item popularity in user profiles, which are determined by users' different selecting patterns. This feature extraction method is based on the prior knowledge that attackers select items to rate with man-made rules while normal users do this according to their inner preferences. Then, machine learning classification approaches are exploited to make use of these features to detect and remove attackers. Experiment results on the MovieLens dataset and Amazon review dataset show that our proposed method improves detection performance. In addition, the results justify the practical value of features derived from selecting patterns. © 2016 The Institute of Electronics, Information and Communication Engineers.

关键词： Feature extraction

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Simulation and Experiment Study of Non-Destructive Testing Using EMA/EC Dual Probe

Simulation and Experiment Study of Non-Destructive Testing U...

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2016 IEEE Far East NDT New Technology & Application Forum

作者： Niu Zhi OUYANG Qi Shen Zhixi Zhang Xinlan Zhang Tianfeng The Key Laboratory of Dependable Service Computing in Cyber Physical Society of Ministry of Education Chongqing University College of Automation Chongqing University College of Computer Science and Engineering Chongqing University of Technology

It is of some advantages for non-destructive testing surface and internal flaws using EC/EMA dual *** fusion detection principle of EMA/EC is emulated by finite element *** to EC,the current eddy field distribution focused on skin and coil impedance variation induced by eddy field is studied by theory and experiment method,and aimed to EMAT,the propagation characteristics of the ultrasonic wave excited by EMAT is analyzed by Multiphysics Comsol simulation *** simulation and experiment results showed that it is effective methods for non-destructive testing surface and internal flaw of the tested object using EC/EMA fusion detection method.

关键词： EMAT ECT Sensor Fusion NDT&E

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A component recommender for bug reports using Discriminative Probability Latent Semantic Analysis

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Information and Software Technology 2016年 73卷 37-51页

作者： Meng Yan Xiaohong Zhang Dan Yang Ling Xu Jeffrey D. Kymer School of Software Engineering Chongqing University Chongqing 401331 PR China State Key laboratory of Coal Mine Disaster Dynamics and Control Chongqing 400044 PR China Key Laboratory of Dependable Service Computing in Cyber Physical Society Ministry of Education Chongqing 400044 PR China

Context The component field in a bug report provides important location information required by developers during bug fixes. Research has shown that incorrect component assignment for a bug report often causes problems and delays in bug fixes. A topic model technique, Latent Dirichlet Allocation (LDA), has been developed to create a component recommender for bug reports. Objective We seek to investigate a better way to use topic modeling in creating a component recommender. Method This paper presents a component recommender by using the proposed Discriminative Probability Latent Semantic Analysis (DPLSA) model and Jensen–Shannon divergence (DPLSA-JS). The proposed DPLSA model provides a novel method to initialize the word distributions for different topics. It uses the past assigned bug reports from the same component in the model training step. This results in a correlation between the learned topics and the components. Results We evaluate the proposed approach over five open source projects , Mylyn, Gcc, Platform, Bugzilla and Firefox. The results show that the proposed approach on average outperforms the LDA-KL method by 30.08%, 19.60% and 14.13% for recall @1, recall @3 and recall @5, outperforms the LDA-SVM method by 31.56%, 17.80% and 8.78% for recall @1, recall @3 and recall @5, respectively. Conclusion Our method discovers that using comments in the DPLSA-JS recommender does not always make a contribution to the performance. The vocabulary size does matter in DPLSA-JS. Different projects need to adaptively set the vocabulary size according to an experimental method. In addition, the correspondence between the learned topics and components in DPLSA increases the discriminative power of the topics which is useful for the recommendation task.

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How to High-Efficiently Acquire Activity Pattern in Smart Environment

How to High-Efficiently Acquire Activity Pattern in Smart En...

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

作者： Chengliang Wang Fei Ma Yunpeng Wang Debraj De Sajal K. Das Key Laboratory of Dependable Service Computing in Cyber Physical Society Ministry of Education College of Computer Science Chongqing University Chongqing China Missouri University of Science & Technology Missouri USA

ISBN: (纸本)9781509039371

The application of Smart Environment plays an important role in the development of advanced science and technology and therefore more and more attention. And activity recognition is the basis of Smart Environment, which reflects the intelligence of Smart Environment. However, there are two difficult and important problems which limiting the popularization of Smart Environment existing: high costs and difficulties in obtaining activity pattern. In order to overcome these problems and obtain activity pattern more effectively and efficiently, a framework for activity pattern transfer is proposed in this paper. There are two parts of activity pattern transfer: (i) Trajectory transfer, establishing the relationship on trajectories of template environment and new environment. (ii) Trigger duration transfer, transferring the trigger duration from template environment to new environment. There are four core algorithms of activity recognition based on transfer learning after pretreatment: candidate path set generation algorithm (CTSG), similarity computing algorithm (SC), trajectory mapping algorithm (TM) and trigger duration transfer algorithm (TDT). A lot of experiments had been done in the end to verify the efficiency of activity pattern transfer in simulation environment. And the experiments present the methods good time consuming performance and effectiveness.

关键词： Trajectory Intelligent sensors Electronic mail Layout

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Design and implementation of human resource information systems based on MVC a case study vocational education in iraq

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International Journal of u- and e- service, Science and Technology 2016年第11期9卷 15-26页

作者： Tariq, Omar Sang, Jun Gulzar, Kanza Key Laboratory of Dependable Service Computing in Cyber Physical Society of Ministry of Education Chongqing University Chongqing400044 China School of Software Engineering Chongqing University Chongqing401331 China

The qualities of human resources development systems are considered as inputs of economic and social growth. The importance of these systems is increased according to gradual transformation towards knowledge of trade and business in the most societies. Technical and professional education that aim to prepare employees at various basic levels such as labor and intermediate levels for technicians is of primary importance. In this paper the Human-Resource Information Systems in the Directorate of Vocational Education can be seen as an example of a complex system. Therefore, the paper considers HRIS as a case study for which a software system has been developed taking the Requirement Engineering approach into account. Thereafter, HRIS is designed using object oriented analysis and design methodology along with J2EE platform and a few auxiliary technologies like framework Spring helpful in implementation of MVC design pattern and Hibernate facilitating connecting process with a database. A System uses an efficient database Oracle 10g Release 2. © 2016 SERSC.

关键词： Design

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Temperature Monitoring Based on Image Processing for Intelligent Microwave Heating 27

Temperature Monitoring Based on Image Processing for Intelli...

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第27届中国控制与决策会议

作者： CUI Liyan GAO Min XIONG Qingyu WEN Junhao XIE Ning School of Software Engineering Chongqing University Key Laboratory of Dependable Service Computing in Cyber Physical Society Ministry of Education

ISBN: (纸本)9781479970186

Microwave,as a clean and efficient energy,can solve growing levels of pollution and energy *** In the process of industrial production,the use of high-power microwave will cause hot spots,thermal runaway,or even *** we need to achieve intelligent control of microwave,to ensure the safe and efficient use of microwave *** temperature information is the basis for intelligent control,and there are many methods to monitor temperature in microwave oven,for example,optical fiber and infrared temperature measurement and ultrasonic *** these methods suffer from high attrition rate locality,or difficulty in installation *** solve the problems,we propose a temperature monitoring approach using image processing and colorimetric *** evaluate the proposed approach,we established a microwave heating system with camera and fiber,developed temperature measurement software to monitor temperature,and visualized the temperature field for the heating object in the microwave *** experiments show that the proposed approach is non-contact with low cost,easy to installation,and accurate on the reconstruction of temperature field.

关键词： Temperature Monitoring Image Processing Microwave Heating Curve Fitting

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Automatically classifying software changes via discriminative topic model: Supporting multi-category and cross-project

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Journal of Systems and Software 2016年 113卷 296-308页

作者： Meng Yan Ying Fu Xiaohong Zhang Dan Yang Ling Xu Jeffrey D. Kymer School of Software Engineering Chongqing University Huxi Town Shapingba Chongqing 401331 PR China Key Laboratory of Dependable Service Computing in Cyber Physical Society Ministry of Education Chongqing 400044 PR China State Key laboratory of Coal Mine Disaster Dynamics and Control Chongqing 400044 PR China

Accurate classification of software changes as corrective, adaptive and perfective can enhance software decision making activities. However, a major challenge which remains is how to automatically classify multi-category changes. This paper presents a discriminative Probability Latent Semantic Analysis (DPLSA) model with a novel initialization method which initializes the word distributions for different topics using labeled samples. This method creates a one-to-one correspondence between the discovered topics and the change categories. As a result, the discriminative semantic representation of the software change messages whose largest topic entry directly corresponds to the category label of the change message which is directly used to perform single-category and multi-category change classification. In the evaluation on five open source projects, the experimental results show that the proposed approach achieves a more accurate performance than the four baseline methods. Especially with the multi-category classification task which improves the recall rate. Moreover, the different projects share the same vocabulary and the estimated model so that DPLSA is well applicable to cross-project software change message analysis.

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Optimization method for trajectory combination in surveillance video synopsis based on genetic algorithm

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Journal of Ambient Intelligence and Humanized computing 2015年第5期6卷 623-633页

作者： Xu, Ling Liu, Hailin Yan, Xinhua Liao, Shengping Zhang, Xiaohong School of Software Engineering Chongqing University Chongqing401331 China Key Laboratory of Dependable Service Computing Cyber Physical Society Ministry of Education Chongqing400044 China

With the dramatic increasing of surveillance video data, it is required that the synopses extracted from video data be quickly explored. Video synopsis is a technology for quick browsing of a video by compressing object trajectories. However, extracting and rearranging the detected object trajectories is one of the difficult issues in generating video synopsis. In this paper, a method is proposed which used for solving the optimization problem of trajectory combination in generating video synopses. The method utilizes the temporal combination ways of trajectories to deal with the optimization problem of motion trajectory combination under the idea of genetic algorithm (GA). Experiment results show that combination of the trajectories based on GA is better than simulated annealing both in information loss and time consumption. Besides,GA is easier to be manipulated by computers. © 2015, Springer-Verlag Berlin Heidelberg.

关键词： Genetic algorithms

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