{"title":"Pivot-Free Block Matrix Inversion","authors":"S. Watt","doi":"10.1109/SYNASC.2006.61","DOIUrl":"https://doi.org/10.1109/SYNASC.2006.61","url":null,"abstract":"We present a pivot-free deterministic algorithm for the inversion of block matrices. The method is based on the Moore-Penrose inverse and is applicable over certain general classes of rings. This improves on previous methods that required at least one invertible on-diagonal block, and that otherwise required row- or column-based pivoting, disrupting the block structure. Our method is applicable to any invertible matrix and does not require any particular blocks to invertible. This is achieved at the cost of two additional specialized matrix multiplications and, in some cases, requires the inversion to be performed in an extended ring","PeriodicalId":309740,"journal":{"name":"2006 Eighth International Symposium on Symbolic and Numeric Algorithms for Scientific Computing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2006-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132038285","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}
{"title":"Restraint Order Component Model Execution","authors":"A. Vescan","doi":"10.1109/SYNASC.2006.66","DOIUrl":"https://doi.org/10.1109/SYNASC.2006.66","url":null,"abstract":"In this paper we discuss a way of composing a system from components and two different execution approaches of the obtained solutions. Secondly, we argue that the selection of the accurate model that best represents the user requirements supposes semantic involvement by the user. We illustrate the synergy of model construction and model execution by giving a real life example. The integration of an automatic composition model has validated our approach as a simple but powerful tool for customizing software to support client-specific requirements","PeriodicalId":309740,"journal":{"name":"2006 Eighth International Symposium on Symbolic and Numeric Algorithms for Scientific Computing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2006-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133566923","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}
{"title":"Providing High Data Availability in MedioGRID","authors":"Adrian Colesa, I. Ignat, Radu Opris","doi":"10.1109/SYNASC.2006.65","DOIUrl":"https://doi.org/10.1109/SYNASC.2006.65","url":null,"abstract":"High data availability is an important requirement for any data provider system. Replication is the main approach used to improve data availability, which is an inherent method for any distributed infrastructure including grids. The Globus toolkit provides specialized tools and services for data replication in grid, though it is not so simple to know how to deploy, configure and make them work efficiently together in order to obtain the desired level of data availability. Based on our experiments with these tools, we designed an architecture of a data replication management system for the MedioGrid project. Our solution automates the replication process between data storage nodes in the system. We implemented and tested a prototype of our architecture","PeriodicalId":309740,"journal":{"name":"2006 Eighth International Symposium on Symbolic and Numeric Algorithms for Scientific Computing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2006-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125053213","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}
{"title":"Clouds Mask Algorithm","authors":"Floricica Parauan, Mihaela Ordean, A. Diamandi","doi":"10.1109/SYNASC.2006.22","DOIUrl":"https://doi.org/10.1109/SYNASC.2006.22","url":null,"abstract":"The article exemplifies a way to identify the nature of a pixel up to different constants and indicators. An algorithm is described for clouds mask and pseudocode for snow respective ice detection. We present also the experimental results. In previous research we found different approaches of these algorithms but each of them attacks differently the subject","PeriodicalId":309740,"journal":{"name":"2006 Eighth International Symposium on Symbolic and Numeric Algorithms for Scientific Computing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2006-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129639100","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}
{"title":"A Parallel Algorithm for Rendering Huge Terrain Surfaces","authors":"Norbert Somosi, D. Petcu","doi":"10.1109/SYNASC.2006.8","DOIUrl":"https://doi.org/10.1109/SYNASC.2006.8","url":null,"abstract":"In this short report we present an efficient way for real time parallel rendering of complex terrain models. We describe a hybrid algorithm that combines the parallel sort last and the sequential GeoMipMapping rendering algorithms. Tests on a cluster of workstations are also reported","PeriodicalId":309740,"journal":{"name":"2006 Eighth International Symposium on Symbolic and Numeric Algorithms for Scientific Computing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2006-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130817478","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}
{"title":"Evolutionary Support Vector Regression Machines","authors":"R. Stoean, D. Dumitrescu, M. Preuss, C. Stoean","doi":"10.1109/SYNASC.2006.39","DOIUrl":"https://doi.org/10.1109/SYNASC.2006.39","url":null,"abstract":"Evolutionary support vector machines (ESVMs) are a novel technique that assimilates the learning engine of the state-of-the-art support vector machines (SVMs) but evolves the coefficients of the decision function by means of evolutionary algorithms (EAs). The new method has accomplished the purpose for which it has been initially developed, that of a simpler alternative to the canonical SVM approach for solving the optimization component of training. ESVMs, as SVMs, are natural tools for primary application to classification. However, since the latter had been further on extended to also handle regression, it is the scope of this paper to present the corresponding evolutionary paradigm. In particular, we consider the hybridization with the classical epsi-support vector regression (epsi-SVR) introduced by Vapnik and the subsequent evolution of the coefficients of the regression hyperplane. epsi-evolutionary support regression (epsi-ESVR) is validated on the Boston housing benchmark problem and the obtained results demonstrate the promise of ESVMs also as concerns regression","PeriodicalId":309740,"journal":{"name":"2006 Eighth International Symposium on Symbolic and Numeric Algorithms for Scientific Computing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2006-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127199719","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}
{"title":"A New k-means Based Clustering Algorithm in Aspect Mining","authors":"G. Czibula, G. Moldovan","doi":"10.1109/SYNASC.2006.5","DOIUrl":"https://doi.org/10.1109/SYNASC.2006.5","url":null,"abstract":"Clustering is a division of data into groups of similar objects. Aspect mining is a process that tries to identify cross-cutting concerns in existing software systems. The goal is to refactor the existing systems to use aspect oriented programming, in order to make them easier to maintain and to evolve. This paper aims at presenting a new k-means based clustering algorithm used in aspect mining. Clustering is used in order to identify crosscutting concerns. We propose some quality measures in order to evaluate the results both from the clustering point of view and the aspect mining point of view, and we also report two case studies","PeriodicalId":309740,"journal":{"name":"2006 Eighth International Symposium on Symbolic and Numeric Algorithms for Scientific Computing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2006-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114367932","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}
{"title":"Tuning Evolutionary Algorithm Performance Using Nature Inspired Heuristics","authors":"A. Abraham","doi":"10.1109/SYNASC.2006.78","DOIUrl":"https://doi.org/10.1109/SYNASC.2006.78","url":null,"abstract":"Summary form only given. Evolutionary algorithms have become an important problem solving methodology among many researchers working in the area of computational intelligence. The population based collective learning process; self adaptation and robustness are some of the key features of evolutionary algorithm when compared to other global optimization techniques. Due to its simplicity, evolutionary algorithms have been widely accepted for solving several important practical applications in engineering, business, commerce etc. However, experimental evidence had indicated cases where evolutionary algorithms are inefficient at fine tuning solutions, but better at finding global basins of attraction. The efficiency of evolutionary training can be improved significantly by hybridization of some search procedures or incorporating some heuristics into the evolution process. In this talk, we will review how particle swarm optimization algorithm and bacterial foraging algorithm could be used to optimize the performance of evolutionary algorithms. The performance of the hybridized algorithms will be illustrated using some benchmark problems","PeriodicalId":309740,"journal":{"name":"2006 Eighth International Symposium on Symbolic and Numeric Algorithms for Scientific Computing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2006-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116072318","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}
{"title":"Adventures of a Logician-Engineer: A Journey through Logic, Engineering, Medicine, Biology, and Statistics","authors":"L. Wong","doi":"10.1109/SYNASC.2006.14","DOIUrl":"https://doi.org/10.1109/SYNASC.2006.14","url":null,"abstract":"Summary form only given. Whenever a programmer writes a loop, or a mathematician does a proof by induction, an invariant is involved. The discovery and understanding of invariants often underlies problem solving in many domains. The author discusses his search for powerful invariants over the past decade. This search was/is motivated by a broad spectrum of problems: understanding query languages, engineering data integration systems, optimizing disease treatments, recognizing DNA feature sites, and discovering reliable patterns","PeriodicalId":309740,"journal":{"name":"2006 Eighth International Symposium on Symbolic and Numeric Algorithms for Scientific Computing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2006-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121902051","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}
{"title":"The Confluence Property for Petri Nets and its Applications","authors":"I. Leahu, F. Ţiplea","doi":"10.1109/SYNASC.2006.71","DOIUrl":"https://doi.org/10.1109/SYNASC.2006.71","url":null,"abstract":"A Petri net is confluent if its firing relation is confluent, i.e., for any two reachable markings there exists a marking reachable from both of them. We prove that confluence is a decidable property for Petri nets and it is preserved by asynchronous parallel composition. Applications to Petri net structural transformations and term rewriting systems are then pointed out","PeriodicalId":309740,"journal":{"name":"2006 Eighth International Symposium on Symbolic and Numeric Algorithms for Scientific Computing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2006-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130167866","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}