Complex application deployment and management over multiple heterogeneous PaaS platform is one of the key problems that have emerged with the cloud technology revolution. Presently, vendor lock-in has become a major PaaS technology challenge. Multi-Cloud PaaS Architecture (MCPA) has been recently proposed research project, intended to resolve complexity and interoperability challenges. MCPA offers flexible tools and services for seamless adaptive multi-cloud management of complex application modules over the heterogeneous PaaS cloud. In this research study, the authors have outlined motivation and objectives of the MCPA projects. MCPA positioned with respect to related cloud initiatives and its initial design and infrastructure has also been discussed. The Initial results show that the use of MCPA in PaaS cloud can improve portability and mitigate lock-in problem.
{"title":"Multi-cloud PaaS Architecture (MCPA): A Solution to Cloud Lock-In","authors":"R. Yasrab, Naijie Gu","doi":"10.1109/ICISCE.2016.108","DOIUrl":"https://doi.org/10.1109/ICISCE.2016.108","url":null,"abstract":"Complex application deployment and management over multiple heterogeneous PaaS platform is one of the key problems that have emerged with the cloud technology revolution. Presently, vendor lock-in has become a major PaaS technology challenge. Multi-Cloud PaaS Architecture (MCPA) has been recently proposed research project, intended to resolve complexity and interoperability challenges. MCPA offers flexible tools and services for seamless adaptive multi-cloud management of complex application modules over the heterogeneous PaaS cloud. In this research study, the authors have outlined motivation and objectives of the MCPA projects. MCPA positioned with respect to related cloud initiatives and its initial design and infrastructure has also been discussed. The Initial results show that the use of MCPA in PaaS cloud can improve portability and mitigate lock-in problem.","PeriodicalId":6882,"journal":{"name":"2016 3rd International Conference on Information Science and Control Engineering (ICISCE)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84376513","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Optical flow estimation is one of the important domains in computer vision. HS algorithm based on variational method is a classical optical flow estimation method, which can get consecutive smooth optical flow field in motion segmentation domain. But it usually takes a lot of time to calculate the HS model. In this paper, how HS algorithm gets optical flow field is analyzed firstly, and then a simplified HS algorithm is proposed, which does not need complex computation. Finally, Experiments demonstrate the validity and efficiency of the proposed method.
{"title":"A Simplified HS Algorithm in Optical Flow Estimation","authors":"Wei Wei-bo, Liu Bowen, Pan Zhenkuan, Wang Zhi","doi":"10.1109/ICISCE.2016.32","DOIUrl":"https://doi.org/10.1109/ICISCE.2016.32","url":null,"abstract":"Optical flow estimation is one of the important domains in computer vision. HS algorithm based on variational method is a classical optical flow estimation method, which can get consecutive smooth optical flow field in motion segmentation domain. But it usually takes a lot of time to calculate the HS model. In this paper, how HS algorithm gets optical flow field is analyzed firstly, and then a simplified HS algorithm is proposed, which does not need complex computation. Finally, Experiments demonstrate the validity and efficiency of the proposed method.","PeriodicalId":6882,"journal":{"name":"2016 3rd International Conference on Information Science and Control Engineering (ICISCE)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84479954","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ruomeng Jiang, S. Malik, Yingyun Sun, Jianliang Zhong
Small isolated power systems are generally located in remote areas which are rather far away from the power grid. Renewable energy such as wind power is introduced into small isolated power systems directly to reduce power generation cost and increase the economy. However, it brings challenges on the operation and control of small isolated power system. To insure the economy and stability of small isolated power systems, this paper puts forward a small isolated power system unit commitment model with state-controllable wind power. Wind turbines are regarded as state-controllable and discrete-regulated random power sources in the proposed model to reduce the operation risk of power system. Furthermore, based on scenario analysis, the model is solved with L-shaped algorithm which decouples discrete variables and continuous variables while decoupling of deterministic and random variables is used to decrease calculation burden of the problem. Finally, the case analysis indicates the feasibility and validity of the proposed model.
{"title":"A Small Isolated Power System SCUC Model with State-Controllable Wind Power","authors":"Ruomeng Jiang, S. Malik, Yingyun Sun, Jianliang Zhong","doi":"10.1109/ICISCE.2016.174","DOIUrl":"https://doi.org/10.1109/ICISCE.2016.174","url":null,"abstract":"Small isolated power systems are generally located in remote areas which are rather far away from the power grid. Renewable energy such as wind power is introduced into small isolated power systems directly to reduce power generation cost and increase the economy. However, it brings challenges on the operation and control of small isolated power system. To insure the economy and stability of small isolated power systems, this paper puts forward a small isolated power system unit commitment model with state-controllable wind power. Wind turbines are regarded as state-controllable and discrete-regulated random power sources in the proposed model to reduce the operation risk of power system. Furthermore, based on scenario analysis, the model is solved with L-shaped algorithm which decouples discrete variables and continuous variables while decoupling of deterministic and random variables is used to decrease calculation burden of the problem. Finally, the case analysis indicates the feasibility and validity of the proposed model.","PeriodicalId":6882,"journal":{"name":"2016 3rd International Conference on Information Science and Control Engineering (ICISCE)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83784951","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Production safety is concerned continuously in coalmine, especially the gas safety is a key issue in the working management of coal production. With the development of information technology, a large volume of data should collected from sensors deployed in coalmine. Therefore, it is necessary to forecast gas concentration or evaluate the gas safety in the key point, for example, the underground working face, when there are some faults in the sensing system or the data communication system. In this paper, on the one hand, we adopt Support Vector Regression (SVR) to predict gas concentration with the data from other sensors which are running well, on the other hand, we classify the gas concentration data into two class signed to totally safe or a bit high by applying the model constructed by C-Support Vector Classification (SVC) or one-class Support Vector Machine (SVM). Furthermore, Particle Swarm Optimization (PSO) algorithm and Genetic Algorithm (GA) are employed to optimize the parameters of the model. The performances of the models are compared and analyzed in the paper, and the experimental results show that the proposed methods are effective and feasible for processing the gas concentration.
{"title":"Coalmine Gas Concentration Analysis Based on Support Vector Machine","authors":"L. Kun, Ling-Kai Yang, Mei-Ling Zhang, Cheng Jian","doi":"10.1109/ICISCE.2016.64","DOIUrl":"https://doi.org/10.1109/ICISCE.2016.64","url":null,"abstract":"Production safety is concerned continuously in coalmine, especially the gas safety is a key issue in the working management of coal production. With the development of information technology, a large volume of data should collected from sensors deployed in coalmine. Therefore, it is necessary to forecast gas concentration or evaluate the gas safety in the key point, for example, the underground working face, when there are some faults in the sensing system or the data communication system. In this paper, on the one hand, we adopt Support Vector Regression (SVR) to predict gas concentration with the data from other sensors which are running well, on the other hand, we classify the gas concentration data into two class signed to totally safe or a bit high by applying the model constructed by C-Support Vector Classification (SVC) or one-class Support Vector Machine (SVM). Furthermore, Particle Swarm Optimization (PSO) algorithm and Genetic Algorithm (GA) are employed to optimize the parameters of the model. The performances of the models are compared and analyzed in the paper, and the experimental results show that the proposed methods are effective and feasible for processing the gas concentration.","PeriodicalId":6882,"journal":{"name":"2016 3rd International Conference on Information Science and Control Engineering (ICISCE)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83904797","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
It is one of the most frequently stated problems for solid oxide fuel cell (SOFC) system with rated load that output voltage should be kept constant under the fuel utilization rate constraint. Dual-mode predictive control is one of the most popular approaches in process control due to its outstanding advantages such as handling constraints and ensuring close-loop stability. Based on the identified model at the rated load operating point, a dual-mode predictive controller was designed for the SOFC system. However, steady state error was unavoidable in the output because of the identification error. To this end, an integral term was introduced into the augmented model. Simulation results show that the proposed dual-mode predictive controller with integral action in this paper can eliminate the steady-state error under the fuel utilization rate constraint.
{"title":"Dual-Mode Predictive Control of Solid Oxide Fuel Cell","authors":"Han Miaomiao, Zhou Baozhong","doi":"10.1109/ICISCE.2016.207","DOIUrl":"https://doi.org/10.1109/ICISCE.2016.207","url":null,"abstract":"It is one of the most frequently stated problems for solid oxide fuel cell (SOFC) system with rated load that output voltage should be kept constant under the fuel utilization rate constraint. Dual-mode predictive control is one of the most popular approaches in process control due to its outstanding advantages such as handling constraints and ensuring close-loop stability. Based on the identified model at the rated load operating point, a dual-mode predictive controller was designed for the SOFC system. However, steady state error was unavoidable in the output because of the identification error. To this end, an integral term was introduced into the augmented model. Simulation results show that the proposed dual-mode predictive controller with integral action in this paper can eliminate the steady-state error under the fuel utilization rate constraint.","PeriodicalId":6882,"journal":{"name":"2016 3rd International Conference on Information Science and Control Engineering (ICISCE)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88363922","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Because the traditional aircraft trajectory prediction methods are difficult to solve the complex trajectory fitting function and the accuracy of predicted trajectory is not high enough, aircraft trajectory prediction based on genetic programming is proposed in this paper. First of all, aircraft flight trajectory data is normalized processing. And then the reasonable set of function and fitting evaluation standard are established. Finally the flight trajectory is predicted by using genetic programming algorithm. The simulation results show that the prediction accuracy of this algorithm is fairly high, and fitting trajectory using this algorithm accords with the actual flight trajectory.
{"title":"Aircraft Trajectory Prediction Based on Genetic Programming","authors":"Caikun Zhang, Chuang Shi, Wenfu Liu, Xuan Zhang","doi":"10.1109/ICISCE.2016.44","DOIUrl":"https://doi.org/10.1109/ICISCE.2016.44","url":null,"abstract":"Because the traditional aircraft trajectory prediction methods are difficult to solve the complex trajectory fitting function and the accuracy of predicted trajectory is not high enough, aircraft trajectory prediction based on genetic programming is proposed in this paper. First of all, aircraft flight trajectory data is normalized processing. And then the reasonable set of function and fitting evaluation standard are established. Finally the flight trajectory is predicted by using genetic programming algorithm. The simulation results show that the prediction accuracy of this algorithm is fairly high, and fitting trajectory using this algorithm accords with the actual flight trajectory.","PeriodicalId":6882,"journal":{"name":"2016 3rd International Conference on Information Science and Control Engineering (ICISCE)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86111159","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper deals with the design of fuzzy observer for discrete time nonlinear system represented by Takagi Sugeno with measurable premise variables. The proposed observer design approach is based on fuzzy lyapunov function. The convergence conditions of the fuzzy observer are achieved in terms of Liner Matrix Inequalities (LMI). Finally, an example is given to illustrate the proposed result.
{"title":"Observer Design of Discrete Time T-S Fuzzy Systems with Measurable Premise Variables Based on Fuzzy Lyapunov Function Approach","authors":"M. Rizk, M. Tayel, Walied M. Saed","doi":"10.1109/ICISCE.2016.219","DOIUrl":"https://doi.org/10.1109/ICISCE.2016.219","url":null,"abstract":"This paper deals with the design of fuzzy observer for discrete time nonlinear system represented by Takagi Sugeno with measurable premise variables. The proposed observer design approach is based on fuzzy lyapunov function. The convergence conditions of the fuzzy observer are achieved in terms of Liner Matrix Inequalities (LMI). Finally, an example is given to illustrate the proposed result.","PeriodicalId":6882,"journal":{"name":"2016 3rd International Conference on Information Science and Control Engineering (ICISCE)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74967607","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In order to solve the problems that grid connected inverters cannot share power accurately in different line impedance. A new control method for grid connected inverters is presented in this paper. The new control method combines adaptive droop coefficient droop control with fuzzy PID control. The system consists of two sets of three-phase inverters which are controlled by current voltage dual-loop, an improved droop loop and fuzzy PID controller. The adaptive droop coefficient droop control can overcome the system cannot share power accurately in different line impedance, and the fuzzy PID controller can improve the system response speed and reduce system.waveform distortion. Simulation results show the good performance of the scheme.
{"title":"A New Control Method for Inverters Parallel Operation in Microgrid","authors":"Wenge Tong","doi":"10.1109/ICISCE.2016.169","DOIUrl":"https://doi.org/10.1109/ICISCE.2016.169","url":null,"abstract":"In order to solve the problems that grid connected inverters cannot share power accurately in different line impedance. A new control method for grid connected inverters is presented in this paper. The new control method combines adaptive droop coefficient droop control with fuzzy PID control. The system consists of two sets of three-phase inverters which are controlled by current voltage dual-loop, an improved droop loop and fuzzy PID controller. The adaptive droop coefficient droop control can overcome the system cannot share power accurately in different line impedance, and the fuzzy PID controller can improve the system response speed and reduce system.waveform distortion. Simulation results show the good performance of the scheme.","PeriodicalId":6882,"journal":{"name":"2016 3rd International Conference on Information Science and Control Engineering (ICISCE)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79413848","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Chaoran Yang, Dayu Xiao, Yueyang Teng, Zixiang Wei, Jinliang Yang, Yan Kang
In recent years, with the rapid ascension of the whole medical level, people have a higher demand for medical CT equipment, not just emphasizing the inspection speed and high image quality problem. Traditional CT equipment has a complex structure, with big weight, high cost, large space, hardly moving problems. Traditional CT equipment depends on power supply and has a high demand for working environment. The development of Mobile CT technology can effectively solve above problems. It is suitable for the integration operating room, bedside or ambulance. Mobile CT equipment has a vital significance that replaced large-scale medical equipment to treat the injured people at the first time in sudden natural disasters, such as frequent earthquake, mud-rock flow. This paper systematically expounds the concept and development of the mobile CT, introduces the domestic and foreign mobile CT practical application of various kinds of medical department. Mobile CT has a very important auxiliary function. Finally, the article looks forward to the future mobile CT technology.
{"title":"The Overview of Mobile CT","authors":"Chaoran Yang, Dayu Xiao, Yueyang Teng, Zixiang Wei, Jinliang Yang, Yan Kang","doi":"10.1109/ICISCE.2016.307","DOIUrl":"https://doi.org/10.1109/ICISCE.2016.307","url":null,"abstract":"In recent years, with the rapid ascension of the whole medical level, people have a higher demand for medical CT equipment, not just emphasizing the inspection speed and high image quality problem. Traditional CT equipment has a complex structure, with big weight, high cost, large space, hardly moving problems. Traditional CT equipment depends on power supply and has a high demand for working environment. The development of Mobile CT technology can effectively solve above problems. It is suitable for the integration operating room, bedside or ambulance. Mobile CT equipment has a vital significance that replaced large-scale medical equipment to treat the injured people at the first time in sudden natural disasters, such as frequent earthquake, mud-rock flow. This paper systematically expounds the concept and development of the mobile CT, introduces the domestic and foreign mobile CT practical application of various kinds of medical department. Mobile CT has a very important auxiliary function. Finally, the article looks forward to the future mobile CT technology.","PeriodicalId":6882,"journal":{"name":"2016 3rd International Conference on Information Science and Control Engineering (ICISCE)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80596474","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The paper presents a method to predict disulfide bond structure based on sample selection and Classifiers Fusion Technology. Firstly, the codes of the selected protein sequence are used as the input data of RBF neural network. Then the different sizes of the information windows were selected to construct the prediction models of disulfide bond. At last, the final prediction will be obtain from fusing different forecasting models. The result of above simulation experiments shows that the prediction model based on classifier fusion technology can greatly increase prediction accuracy of the structure of protein disulfide bond.
{"title":"An Improved Prediction Method of Protein Disulfide Bond","authors":"Pengfei Sun, Yunhong Ding","doi":"10.1109/ICISCE.2016.183","DOIUrl":"https://doi.org/10.1109/ICISCE.2016.183","url":null,"abstract":"The paper presents a method to predict disulfide bond structure based on sample selection and Classifiers Fusion Technology. Firstly, the codes of the selected protein sequence are used as the input data of RBF neural network. Then the different sizes of the information windows were selected to construct the prediction models of disulfide bond. At last, the final prediction will be obtain from fusing different forecasting models. The result of above simulation experiments shows that the prediction model based on classifier fusion technology can greatly increase prediction accuracy of the structure of protein disulfide bond.","PeriodicalId":6882,"journal":{"name":"2016 3rd International Conference on Information Science and Control Engineering (ICISCE)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77886659","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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