In this paper the consensus problem is considered for multi-agent systems having an independent agent and fixed topology.
研究了具有独立主体和固定拓扑结构的多智能体系统的一致性问题。
{"title":"Multi-agent Linear Dynamical Systems, Analyzing the Consensus Problem","authors":"M. I. García-Planas","doi":"10.1109/MCSI.2014.20","DOIUrl":"https://doi.org/10.1109/MCSI.2014.20","url":null,"abstract":"In this paper the consensus problem is considered for multi-agent systems having an independent agent and fixed topology.","PeriodicalId":202841,"journal":{"name":"2014 International Conference on Mathematics and Computers in Sciences and in Industry","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115511454","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 statistical nature of numerous problems in mathematics, physics and engineering have led to the development of methods for generating random data for a given distribution. Ancient methods include, dice, coin flipping and shuffling of cards. Today, various pseudo, quasi and true random generators (RNGs) are being proposed for their improved properties. In this work, test metrics for goodness-of-fit and randomness are reviewed. The method of uniform sampling (MUS) is modified for improving the randomness without harming the goodness-of-fit qualities. The test results illustrate that very high goodness-of-fit can be obtained even when the number of observed samples is as small as 10.
{"title":"True Random Number Generation of very High Goodness-of-Fit and Randomness Qualities","authors":"S. G. Tanyer","doi":"10.1109/MCSI.2014.47","DOIUrl":"https://doi.org/10.1109/MCSI.2014.47","url":null,"abstract":"The statistical nature of numerous problems in mathematics, physics and engineering have led to the development of methods for generating random data for a given distribution. Ancient methods include, dice, coin flipping and shuffling of cards. Today, various pseudo, quasi and true random generators (RNGs) are being proposed for their improved properties. In this work, test metrics for goodness-of-fit and randomness are reviewed. The method of uniform sampling (MUS) is modified for improving the randomness without harming the goodness-of-fit qualities. The test results illustrate that very high goodness-of-fit can be obtained even when the number of observed samples is as small as 10.","PeriodicalId":202841,"journal":{"name":"2014 International Conference on Mathematics and Computers in Sciences and in Industry","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114986248","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 work is an extension of very recently developed decomposition method for matrices. That method has been called "Tridiagonal Matrix Enhanced Multivariance Product Representation, or briefly, TMEMPR. Here, in this work our ultimate goal has been taken as the decomposition of a univariate linear integral operator. Instead of this task we focus on a bivariate function since the kernel of such an operator is a bivariate function. After having a well developed theory it is just a matter of simple translation what we are going to obtain into linear integral operator's decomposition. The main skeleton of the issue has been constructed in this presentation.
{"title":"Tridiagonal Kernel Enhanced Multivariance Products Representation (TKEMPR) for Univariate Integral Operator Kernels","authors":"A. Okan, M. Demiralp","doi":"10.1109/MCSI.2014.26","DOIUrl":"https://doi.org/10.1109/MCSI.2014.26","url":null,"abstract":"This work is an extension of very recently developed decomposition method for matrices. That method has been called \"Tridiagonal Matrix Enhanced Multivariance Product Representation, or briefly, TMEMPR. Here, in this work our ultimate goal has been taken as the decomposition of a univariate linear integral operator. Instead of this task we focus on a bivariate function since the kernel of such an operator is a bivariate function. After having a well developed theory it is just a matter of simple translation what we are going to obtain into linear integral operator's decomposition. The main skeleton of the issue has been constructed in this presentation.","PeriodicalId":202841,"journal":{"name":"2014 International Conference on Mathematics and Computers in Sciences and in Industry","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124951209","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}
M. Karova, I. Penev, Gergana Todorova, M. Todorova
The paper presents a Genetic Algorithms technique, used to optimize project schedule created in Microsoft Project. The proposed model is called OPTPROJECT. The proposed application is simple and at the same time general enough for optimization of projects, where the high cost activities have to be performed last (at the end of the project). It can be used to manage both small and large projects.
{"title":"Genetic Algorithm for Managing Project Activities System","authors":"M. Karova, I. Penev, Gergana Todorova, M. Todorova","doi":"10.1109/MCSI.2014.46","DOIUrl":"https://doi.org/10.1109/MCSI.2014.46","url":null,"abstract":"The paper presents a Genetic Algorithms technique, used to optimize project schedule created in Microsoft Project. The proposed model is called OPTPROJECT. The proposed application is simple and at the same time general enough for optimization of projects, where the high cost activities have to be performed last (at the end of the project). It can be used to manage both small and large projects.","PeriodicalId":202841,"journal":{"name":"2014 International Conference on Mathematics and Computers in Sciences and in Industry","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128842633","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 novel design of a 8-bit decision module that forms the heart of a dynamic CMOS incrementer-cum-decrementer circuit is presented in this work. The new 8-bit decision module is designed on the basis of identifying least significant zero bit (LSZB) in the binary input stream contrary to identification of least significant one bit (LSOB), as is the case with existing approaches, to perform increment-cum-decrement operations. Further, an original cascading architecture has been proposed for building larger size incrementers-cum-decrementers based on the LSZB principle. SPICE simulations reveal that a 32-bit incrementer-cum-decrementer implemented using the proposed LSZB principle dissipates 58.6% less power than its counterpart designs based on the LSOB approach.
{"title":"Dynamic CMOS Incrementers-cum-Decrementers Based on Least Significant Zero Bit Principle","authors":"P. Balasubramanian, N. Mastorakis","doi":"10.1109/MCSI.2014.27","DOIUrl":"https://doi.org/10.1109/MCSI.2014.27","url":null,"abstract":"The novel design of a 8-bit decision module that forms the heart of a dynamic CMOS incrementer-cum-decrementer circuit is presented in this work. The new 8-bit decision module is designed on the basis of identifying least significant zero bit (LSZB) in the binary input stream contrary to identification of least significant one bit (LSOB), as is the case with existing approaches, to perform increment-cum-decrement operations. Further, an original cascading architecture has been proposed for building larger size incrementers-cum-decrementers based on the LSZB principle. SPICE simulations reveal that a 32-bit incrementer-cum-decrementer implemented using the proposed LSZB principle dissipates 58.6% less power than its counterpart designs based on the LSOB approach.","PeriodicalId":202841,"journal":{"name":"2014 International Conference on Mathematics and Computers in Sciences and in Industry","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126641866","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 this paper an implemented software system for identification of best fitting distribution of sample data is described. Some modifications and additions of the known statistical approaches are presented aiming the practical application of the distribution identification task. Additionally the cloud computing approach is applied in order to process the sample data series in parallel that makes significantly faster the implemented system.
{"title":"Statistical Distribution Identification with Cloud Based Module","authors":"Ventsislav Nikolov, Danko Naydenov, A. Antonov","doi":"10.1109/MCSI.2014.45","DOIUrl":"https://doi.org/10.1109/MCSI.2014.45","url":null,"abstract":"In this paper an implemented software system for identification of best fitting distribution of sample data is described. Some modifications and additions of the known statistical approaches are presented aiming the practical application of the distribution identification task. Additionally the cloud computing approach is applied in order to process the sample data series in parallel that makes significantly faster the implemented system.","PeriodicalId":202841,"journal":{"name":"2014 International Conference on Mathematics and Computers in Sciences and in Industry","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131343429","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}
There is increasing interest in wind energy investment by both public and private producers in Iran. However, the biggest challenge is the lack of up-to-date site specific data information on wind energy potential across the country. In this paper, the 10min period measured wind speed data for years 2002, 2003 at 10m, 30m and 40m heights were analyzed for Firoozkooh city in Iran County approximately 120km from Tehran. The wind speed distribution was modeled using the Weibull probability function, wind density and Monthly wind energy production are estimated. Results show that the monthly value of shape parameter (k) ranges from 1.1054 in October 2002 (h=40m) to 2.6847 in June 2002 (h=10m), while the monthly value of scale parameter (c) varies from 2.9083m/s in January 2002 (h=10m) to 9.4082m/s in June 2002 (h=40m). Values of 232.18 and 169.32w/m2 are estimated for annual mean power density at height of 30m for years 2002 and 2003 respectively and the wind class was found to be 2 which not being deemed suitable for large machines, although smaller wind turbines may be economical in this area where the value of the energy produced is higher.
{"title":"Assessment of Wind Energy Potential for City of Firoozkooh in Iran","authors":"Seyyed Mohsen Kamali, M. Manshadi","doi":"10.1109/MCSI.2014.41","DOIUrl":"https://doi.org/10.1109/MCSI.2014.41","url":null,"abstract":"There is increasing interest in wind energy investment by both public and private producers in Iran. However, the biggest challenge is the lack of up-to-date site specific data information on wind energy potential across the country. In this paper, the 10min period measured wind speed data for years 2002, 2003 at 10m, 30m and 40m heights were analyzed for Firoozkooh city in Iran County approximately 120km from Tehran. The wind speed distribution was modeled using the Weibull probability function, wind density and Monthly wind energy production are estimated. Results show that the monthly value of shape parameter (k) ranges from 1.1054 in October 2002 (h=40m) to 2.6847 in June 2002 (h=10m), while the monthly value of scale parameter (c) varies from 2.9083m/s in January 2002 (h=10m) to 9.4082m/s in June 2002 (h=40m). Values of 232.18 and 169.32w/m2 are estimated for annual mean power density at height of 30m for years 2002 and 2003 respectively and the wind class was found to be 2 which not being deemed suitable for large machines, although smaller wind turbines may be economical in this area where the value of the energy produced is higher.","PeriodicalId":202841,"journal":{"name":"2014 International Conference on Mathematics and Computers in Sciences and in Industry","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131508141","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}
C. Balasubramanyam, M. Ajay, Amogh B. Shetty, K. Spandana, K. Seetharamu
This paper deals with a 6-bar mechanism, which finds its application in a precision deep drawing press. The approach for the kinematic simulation is based on loop closure analysis, which has been performed to derive expressions for slider displacement. The results are consolidated using Artificial Neural Network (ANN). Genetic Algorithm (GA) is used for optimizing the dimensions of the mechanism, corresponding to the chosen objective function.
{"title":"Kinematic Analysis and Optimization of a 6 Bar Mechanism","authors":"C. Balasubramanyam, M. Ajay, Amogh B. Shetty, K. Spandana, K. Seetharamu","doi":"10.1109/MCSI.2014.44","DOIUrl":"https://doi.org/10.1109/MCSI.2014.44","url":null,"abstract":"This paper deals with a 6-bar mechanism, which finds its application in a precision deep drawing press. The approach for the kinematic simulation is based on loop closure analysis, which has been performed to derive expressions for slider displacement. The results are consolidated using Artificial Neural Network (ANN). Genetic Algorithm (GA) is used for optimizing the dimensions of the mechanism, corresponding to the chosen objective function.","PeriodicalId":202841,"journal":{"name":"2014 International Conference on Mathematics and Computers in Sciences and in Industry","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121661539","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 global optimization of a mathematical model determines the best parameters such that a target or cost function is minimized. Optimization problems arise in almost all scientific disciplines (operations research, life sciences, etc.). Only in a few exceptional cases, these problems can be solved analytically-exactly, so in practice numerical routines based on approximations have to be used. The routines return a result -- a so-called candidate of a global minimum. Unfortunately, the question whether the candidate represents the optimal solution, often remains unanswered. This article presents a simple-to-use, statistical analysis that determines and assesses the quality of such a result. This information is valuable and important -- especially for practical application.
{"title":"Statistical Analysis on Global Optimization","authors":"T. Ullrich, D. Fellner","doi":"10.1109/MCSI.2014.15","DOIUrl":"https://doi.org/10.1109/MCSI.2014.15","url":null,"abstract":"The global optimization of a mathematical model determines the best parameters such that a target or cost function is minimized. Optimization problems arise in almost all scientific disciplines (operations research, life sciences, etc.). Only in a few exceptional cases, these problems can be solved analytically-exactly, so in practice numerical routines based on approximations have to be used. The routines return a result -- a so-called candidate of a global minimum. Unfortunately, the question whether the candidate represents the optimal solution, often remains unanswered. This article presents a simple-to-use, statistical analysis that determines and assesses the quality of such a result. This information is valuable and important -- especially for practical application.","PeriodicalId":202841,"journal":{"name":"2014 International Conference on Mathematics and Computers in Sciences and in Industry","volume":"104 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124737937","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}
Mobile Communication System (MCS) is an important element for ensuring information support in crisis and in battle action. The transit network or the network of base stations is the basis of MCS. Checking a designed radio relay links is the basis for MCS planning. This verification is performed by checking line of sight between selected locations. But there can be other circumstances influenced deployment of transit nodes in battle area. Quality of road is one of criteria. Today, we can use the concept of risk mapping in choosing a sites or location of transit nodes or base stations. This concept can be successfully used in combination with geographical information system. There are devised a special GIS layers that express risk assessment for individual points of battle area. Location for transit nodes can be chosen according to quality of direct line of sight and level of risk. The article deals with the methodology of risk mapping for MCS planning.
{"title":"Risk Mapping for Mobile Communication","authors":"L. Lukás","doi":"10.1109/MCSI.2014.59","DOIUrl":"https://doi.org/10.1109/MCSI.2014.59","url":null,"abstract":"Mobile Communication System (MCS) is an important element for ensuring information support in crisis and in battle action. The transit network or the network of base stations is the basis of MCS. Checking a designed radio relay links is the basis for MCS planning. This verification is performed by checking line of sight between selected locations. But there can be other circumstances influenced deployment of transit nodes in battle area. Quality of road is one of criteria. Today, we can use the concept of risk mapping in choosing a sites or location of transit nodes or base stations. This concept can be successfully used in combination with geographical information system. There are devised a special GIS layers that express risk assessment for individual points of battle area. Location for transit nodes can be chosen according to quality of direct line of sight and level of risk. The article deals with the methodology of risk mapping for MCS planning.","PeriodicalId":202841,"journal":{"name":"2014 International Conference on Mathematics and Computers in Sciences and in Industry","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128340473","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：