vol. 01, no. 03http://sedici.unlp.edu.ar:80/handle/10915/3722014-12-19T22:35:20Z2014-12-19T22:35:20ZDiscriminative power of the receptors activated by k-contiguous bits ruleWierzchon, Slawomir T.http://sedici.unlp.edu.ar:80/handle/10915/94002013-10-17T12:02:29Z2000-01-01T00:00:00ZArticulo
Journal of Computer Science & Technology; no. 3
The paper provides a brief introduction into a relatively new discipline: artificial immune systems (AIS). These are computer systems exploiting the natural immune system (or NIS for brevity) metaphor: protect an organism against invaders. Hence, a natural field of applications of AIS is computer security. But the notion of invader can be extended further: for instance a fault occurring in a system disturbs patterns of its regular functioning. Thus fault, or anomaly detection is another field of applications. It is convenient to represent the information about normal and abnormal functioning of a system in binary form (e.g. computer programs/viruses are binary files). Now the problem can be stated as follows: given a set of self patterns representing normal behaviour of a system under considerations find a set of detectors (i.e, antibodies, or more precisely, receptors) identifying all non self strings corresponding to abnormal states of the system. A new algorithm for generating antibody strings is presented. Its interesting property is that it allows to find in advance the number of of strings which cannot be detected by an "ideal" receptors repertoire.
2000-01-01T00:00:00ZThe paper provides a brief introduction into a relatively new discipline: artificial immune systems (AIS). These are computer systems exploiting the natural immune system (or NIS for brevity) metaphor: protect an organism against invaders. Hence, a natural field of applications of AIS is computer security. But the notion of invader can be extended further: for instance a fault occurring in a system disturbs patterns of its regular functioning. Thus fault, or anomaly detection is another field of applications. It is convenient to represent the information about normal and abnormal functioning of a system in binary form (e.g. computer programs/viruses are binary files). Now the problem can be stated as follows: given a set of self patterns representing normal behaviour of a system under considerations find a set of detectors (i.e, antibodies, or more precisely, receptors) identifying all non self strings corresponding to abnormal states of the system. A new algorithm for generating antibody strings is presented. Its interesting property is that it allows to find in advance the number of of strings which cannot be detected by an "ideal" receptors repertoire.Introductory techniques for 3-D computer vision. Emmanuele Trucco - Alessandro Verri. Prentice Hall, 1998Sanz, Cecilia Verónicahttp://sedici.unlp.edu.ar:80/handle/10915/94032013-10-17T12:02:29Z2000-01-01T00:00:00ZRevision
Journal of Computer Science & Technology; no. 3
This book is an applied introduction to the problems and solutions of modern computer vision. It offers a collection of selected, well-tested methods (theory and algorithms), aiming to balance difficulty and applicability. It can be considered a starting point to understand and investigate the literature of computer vision, including conferences, journals, and Internet sites.
2000-01-01T00:00:00ZThis book is an applied introduction to the problems and solutions of modern computer vision. It offers a collection of selected, well-tested methods (theory and algorithms), aiming to balance difficulty and applicability. It can be considered a starting point to understand and investigate the literature of computer vision, including conferences, journals, and Internet sites.Multiagent systems: a modern approach to distributed artificial intelligence. Edited by Gerhard Weiss, MIT Press, 1999Simari, Guillermo Ricardohttp://sedici.unlp.edu.ar:80/handle/10915/94022013-10-17T12:02:29Z2000-01-01T00:00:00ZRevision
Journal of Computer Science & Technology; no. 3
Multiagent Systems is the title of a collection of papers dedicated to surveying specific themes of Multiagent Systems (MAS) and Distributed Artificial Intelligence (DAI). All of them authored by leading researchers of this dynamic multidisciplinary field.
2000-01-01T00:00:00ZMultiagent Systems is the title of a collection of papers dedicated to surveying specific themes of Multiagent Systems (MAS) and Distributed Artificial Intelligence (DAI). All of them authored by leading researchers of this dynamic multidisciplinary field.Parallel programming: techniques and applications using networked workstations and parallel computers. Barry Wilkinson, C. Michael AllenTinetti, Fernando Gustavohttp://sedici.unlp.edu.ar:80/handle/10915/94012013-10-17T12:02:29Z2000-01-01T00:00:00ZRevision
Journal of Computer Science & Technology; no. 3
This book makes a clear presentation of the traditional topics included in a course of undergraduate parallel programming. As explained by the authors, it was developed from their own experience in classrooms, introducing their students to parallel programming. It can be used almost directly to teach basic parallel programming
2000-01-01T00:00:00ZThis book makes a clear presentation of the traditional topics included in a course of undergraduate parallel programming. As explained by the authors, it was developed from their own experience in classrooms, introducing their students to parallel programming. It can be used almost directly to teach basic parallel programmingCrowding under diverse distance criteria for niche formation in multimodal optimizationFernandez, NataliaAlfonso, HugoGallard, Raúl Hectorhttp://sedici.unlp.edu.ar:80/handle/10915/93992013-10-17T12:02:29Z2000-01-01T00:00:00ZArticulo
Journal of Computer Science & Technology; no. 3
Niche formation allows evolutionary algorithms to be used when the location and maintenance of multiple solutions appertaining to diverse areas of the phenotypic space is required. Consequently the application field can be extended to multiobjective optimization, simulation of complex systems and multimodal function optimization. In this later case a conventional evolutionary algorithm tends to group the final population around the fittest individual. Thus, other areas of interest in the search process are lost. Niching methods permits the maintenance of solutions located around these areas of interest. This contribution briefly describe problems preventing niche formation in conventional genetic algorithms, a crowding method for niche formation and analysis of results when optimizing two multimodal functions.
2000-01-01T00:00:00ZNiche formation allows evolutionary algorithms to be used when the location and maintenance of multiple solutions appertaining to diverse areas of the phenotypic space is required. Consequently the application field can be extended to multiobjective optimization, simulation of complex systems and multimodal function optimization. In this later case a conventional evolutionary algorithm tends to group the final population around the fittest individual. Thus, other areas of interest in the search process are lost. Niching methods permits the maintenance of solutions located around these areas of interest. This contribution briefly describe problems preventing niche formation in conventional genetic algorithms, a crowding method for niche formation and analysis of results when optimizing two multimodal functions.A hierarchical triangulation for multiresolution terrain modelsAbásolo Guerrero, María JoséDe Giusti, Armando EduardoBlat Gimeno, Josephttp://sedici.unlp.edu.ar:80/handle/10915/93982013-10-17T12:02:29Z2000-01-01T00:00:00ZArticulo
Journal of Computer Science & Technology; no. 3
Interactive visualisation of triangulated terrain surfaces is still a problem for virtual reality systems. A polygonal model of very large terrain data requires a large number of triangles. The main problems are the representation rendering efficiency and the transmission over networks. The major challenge is to simplify a model while preserving its appearance. A multiresolution model represents different levels of detail of an object. We can choose the preferable level of detail according to the position of the observer to improve rendering and we can make a progressive transmission of the different levels. We propose a multiresolution triangulation scheme that eliminates the restrictions of the restricted quadtree triangulation and obtains better results.
2000-01-01T00:00:00ZInteractive visualisation of triangulated terrain surfaces is still a problem for virtual reality systems. A polygonal model of very large terrain data requires a large number of triangles. The main problems are the representation rendering efficiency and the transmission over networks. The major challenge is to simplify a model while preserving its appearance. A multiresolution model represents different levels of detail of an object. We can choose the preferable level of detail according to the position of the observer to improve rendering and we can make a progressive transmission of the different levels. We propose a multiresolution triangulation scheme that eliminates the restrictions of the restricted quadtree triangulation and obtains better results.A genetic approach using direct representation of solution for parallel task scheduling problemEsquivel, Susana CeciliaGatica, Claudia R.Gallard, Raúl Hectorhttp://sedici.unlp.edu.ar:80/handle/10915/93972013-10-17T12:02:29Z2000-01-01T00:00:00ZArticulo
Journal of Computer Science & Technology; no. 3
Evolutionary computation (EC) has been recently recognized as a research field, which studies a new type of algorithms: Evolutionary Algorithms (EAs). These algorithms process populations of solutions as opposed to most traditional approaches which improve a single solution. All these algorithms share common features: reproduction, random variation, competition and selection of individuals. During our research it was evident that some components of EAs should be re-examined. Hence, specific topics such as multiple crossovers per couple and its enhancements, multiplicity of parents and crossovers and their application to single and multiple criteria optimization problems, adaptability, and parallel genetic algorithms, were proposed and investigated carefully. This paper show the most relevant and recent enhancements on recombination for a genetic-algorithm-based EA and migration control strategies for parallel genetic algorithms. Details of implementation and results are discussed.
2000-01-01T00:00:00ZEvolutionary computation (EC) has been recently recognized as a research field, which studies a new type of algorithms: Evolutionary Algorithms (EAs). These algorithms process populations of solutions as opposed to most traditional approaches which improve a single solution. All these algorithms share common features: reproduction, random variation, competition and selection of individuals. During our research it was evident that some components of EAs should be re-examined. Hence, specific topics such as multiple crossovers per couple and its enhancements, multiplicity of parents and crossovers and their application to single and multiple criteria optimization problems, adaptability, and parallel genetic algorithms, were proposed and investigated carefully. This paper show the most relevant and recent enhancements on recombination for a genetic-algorithm-based EA and migration control strategies for parallel genetic algorithms. Details of implementation and results are discussed.The collective computing modelGonzalez, Jesús AlbertoLeón, CoromotoPiccoli, María FabianaPrintista, Alicia MarcelaRoda García, José LuisRodríguez, CasianoSande, Francisco dehttp://sedici.unlp.edu.ar:80/handle/10915/93962014-10-22T19:03:48Z2000-01-01T00:00:00ZArticulo
Journal of Computer Science & Technology; no. 3
The parallel computing model used in this paper, the Collective Computing Model (CCM), is a variant of the well-known Bulk Synchronous Parallel (BSP) model. The synchronicity imposed by the BSP model restricts the set of available algorithms and prevents the overlapping of computation and communication. Other models, like the LogP model, allow asynchronous computing and overlapping but depend on the use of specific libraries. The CCM describes a system exploited through a standard software platform providing facilities for group creation, collective operations and remote memory operations. Based in the BSP model, two kinds of supersteps are considered: Division supersteps and Normal supersteps. The structure of divisions produced by the Division Functions and the partnership relation among processors give place to communication patterns among processors that are topologically similar to a hypercube. We have named the resulting structures Dynamic Polytopes To illustrate these concepts, the Fast Fourier Transform Algorithm is used. Computational results prove the accuracy of the model in four different parallel computers: a Parsytec Power PC, a Cray T3E, a Silicon Graphics Origin 2000 and a Digital Alpha Server.
2000-01-01T00:00:00ZThe parallel computing model used in this paper, the Collective Computing Model (CCM), is a variant of the well-known Bulk Synchronous Parallel (BSP) model. The synchronicity imposed by the BSP model restricts the set of available algorithms and prevents the overlapping of computation and communication. Other models, like the LogP model, allow asynchronous computing and overlapping but depend on the use of specific libraries. The CCM describes a system exploited through a standard software platform providing facilities for group creation, collective operations and remote memory operations. Based in the BSP model, two kinds of supersteps are considered: Division supersteps and Normal supersteps. The structure of divisions produced by the Division Functions and the partnership relation among processors give place to communication patterns among processors that are topologically similar to a hypercube. We have named the resulting structures Dynamic Polytopes To illustrate these concepts, the Fast Fourier Transform Algorithm is used. Computational results prove the accuracy of the model in four different parallel computers: a Parsytec Power PC, a Cray T3E, a Silicon Graphics Origin 2000 and a Digital Alpha Server.Model evolution and system evolutionPons, ClaudiaBaum, Gabriel AlfredoKutsche, Ralf-Detlefhttp://sedici.unlp.edu.ar:80/handle/10915/93952013-10-17T12:02:29Z2000-01-01T00:00:00ZArticulo
Journal of Computer Science & Technology; no. 3
In this paper we define an evolution mechanism with formal semantics using the metamodeling methodology [Geisler et al.98] based on dynamic logic. A remarkable feature of the metamodeling methodology is the ability to define the relation of intentional and extensional entities within one level, allowing not only for the description of structural relations among the modeling entities, but also for a formal definition of structural
constraints and dynamic semantics of the modeled entities. While dynamic semantics on the extensional level means run-time behavior, dynamic semantics on intentional level describes model evolution in the system life cycle.
2000-01-01T00:00:00ZIn this paper we define an evolution mechanism with formal semantics using the metamodeling methodology [Geisler et al.98] based on dynamic logic. A remarkable feature of the metamodeling methodology is the ability to define the relation of intentional and extensional entities within one level, allowing not only for the description of structural relations among the modeling entities, but also for a formal definition of structural
constraints and dynamic semantics of the modeled entities. While dynamic semantics on the extensional level means run-time behavior, dynamic semantics on intentional level describes model evolution in the system life cycle.