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}
This paper provides a way of skin detection in outdoor image based on multiple color space. The clustering is good in the color space YCgCr. Firstly, skin colors are projected in the color space CgCr and the fitting of distribution is carried through in order to wipe off a part of non skin color and gain the intersected image as the result of the first detection. Experimental results indicate that this fitting of distribution can have a good effect on reducing a mass of processing pixels of non skin color. Secondly, skin colors extracted in the first detection are projected in the color space GB in order to further wipe off part of the remaining non skin colors that are not reduced in the first detection by the fitting of distribution. Lastly, the relationships among the three components of every pixel of skin colors and non skin colors in the color space HSL are observed and the percentage of pixels corresponding to a certain relationship is calculated, so part of the non skin color can be further reduced based on the differences we find according to the observed relationship. Experimental results indicate that this algorithm has a good recognition effect and small amount of computation, it can be used in skin color detection in simple environment.
{"title":"Skin Color Analysis and Segmentation in Complex Outdoor Background","authors":"Hui Zhu, N. Mastorakis, X. Zhuang","doi":"10.1109/MCSI.2014.37","DOIUrl":"https://doi.org/10.1109/MCSI.2014.37","url":null,"abstract":"This paper provides a way of skin detection in outdoor image based on multiple color space. The clustering is good in the color space YCgCr. Firstly, skin colors are projected in the color space CgCr and the fitting of distribution is carried through in order to wipe off a part of non skin color and gain the intersected image as the result of the first detection. Experimental results indicate that this fitting of distribution can have a good effect on reducing a mass of processing pixels of non skin color. Secondly, skin colors extracted in the first detection are projected in the color space GB in order to further wipe off part of the remaining non skin colors that are not reduced in the first detection by the fitting of distribution. Lastly, the relationships among the three components of every pixel of skin colors and non skin colors in the color space HSL are observed and the percentage of pixels corresponding to a certain relationship is calculated, so part of the non skin color can be further reduced based on the differences we find according to the observed relationship. Experimental results indicate that this algorithm has a good recognition effect and small amount of computation, it can be used in skin color detection in simple environment.","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":"114378586","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}
Milan Schomig, David Neuhauser, Ralf Seidler, H. M. Bucker
In the design of fast arithmetic circuits, the two's complement number representation can be alternatively replaced by a signed digit number representation. Compared to standard full adders used in two's complement arithmetic, signed digit adder cells offer the potential for improved performance. Designing an efficient signed digit adder cell leads to the problem of analyzing 2 to the power of 44 truth tables originating from different signed digit encodings. Since different digit encodings can produce identical truth tables, it is favorable to reduce this large number of truth tables by identifying identical ones. We introduce a novel approach for the solution of this problem using the MapReduce programming model. We take a step towards solving this problem using three different implementations of MapReduce (Hadoop, Disco, and MR-MPI) and compare their performance on an Opteron-based cluster using up to 64 physical cores.
{"title":"Benchmarking Different MapReduce Implementations for Computer-Aided Hardware Development","authors":"Milan Schomig, David Neuhauser, Ralf Seidler, H. M. Bucker","doi":"10.1109/MCSI.2014.57","DOIUrl":"https://doi.org/10.1109/MCSI.2014.57","url":null,"abstract":"In the design of fast arithmetic circuits, the two's complement number representation can be alternatively replaced by a signed digit number representation. Compared to standard full adders used in two's complement arithmetic, signed digit adder cells offer the potential for improved performance. Designing an efficient signed digit adder cell leads to the problem of analyzing 2 to the power of 44 truth tables originating from different signed digit encodings. Since different digit encodings can produce identical truth tables, it is favorable to reduce this large number of truth tables by identifying identical ones. We introduce a novel approach for the solution of this problem using the MapReduce programming model. We take a step towards solving this problem using three different implementations of MapReduce (Hadoop, Disco, and MR-MPI) and compare their performance on an Opteron-based cluster using up to 64 physical cores.","PeriodicalId":202841,"journal":{"name":"2014 International Conference on Mathematics and Computers in Sciences and in Industry","volume":"53 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":"122247644","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}
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}
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}
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}
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}
Pavlos Kosmides, Chara Remoundou, K. Demestichas, Ioannis V. Loumiotis, Evgenia F. Adamopoulou, M. Theologou
Location-Based Social media have evolved rapidly during the last decade. Most Social Networks provide a plethora of venues and points of interest, while at the same time, users are able to declare their presence in specific locations (a process often referred to as "check-ins"), to provide ratings about the visited places or even suggest them to their friends. Location recommendations depending on users' needs have been a subject of interest for many researchers, while location prediction schemes have been developed in order to provide user's possible future location. In this paper, we present a method for predicting a user's location based on machine learning techniques. The dataset we used was based on input from a well-known Location-Based Social Network. Prediction results can be used in order to make appropriate suggestions for venues or points of interests to users, based on their interests and social connections. We propose a Probabilistic Neural Network and confirm its superior performance against two other types of neural networks.
{"title":"A Location Recommender System for Location-Based Social Networks","authors":"Pavlos Kosmides, Chara Remoundou, K. Demestichas, Ioannis V. Loumiotis, Evgenia F. Adamopoulou, M. Theologou","doi":"10.1109/MCSI.2014.39","DOIUrl":"https://doi.org/10.1109/MCSI.2014.39","url":null,"abstract":"Location-Based Social media have evolved rapidly during the last decade. Most Social Networks provide a plethora of venues and points of interest, while at the same time, users are able to declare their presence in specific locations (a process often referred to as \"check-ins\"), to provide ratings about the visited places or even suggest them to their friends. Location recommendations depending on users' needs have been a subject of interest for many researchers, while location prediction schemes have been developed in order to provide user's possible future location. In this paper, we present a method for predicting a user's location based on machine learning techniques. The dataset we used was based on input from a well-known Location-Based Social Network. Prediction results can be used in order to make appropriate suggestions for venues or points of interests to users, based on their interests and social connections. We propose a Probabilistic Neural Network and confirm its superior performance against two other types of neural networks.","PeriodicalId":202841,"journal":{"name":"2014 International Conference on Mathematics and Computers in Sciences and in Industry","volume":"92 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":"126320734","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：