Volumen 04 | Número 02http://sedici.unlp.edu.ar:80/handle/10915/3802024-03-19T09:39:47Z2024-03-19T09:39:47ZParallel Computing in Local Area NetworksTinetti, Fernando Gustavohttp://sedici.unlp.edu.ar:80/handle/10915/94922019-06-19T04:02:40Z2004-01-01T00:00:00ZRevision
Journal of Computer Science & Technology; ol. 4, no. 2
In this thesis, parallel computing on installed local area networks (LAN) is focused, analyzing problems and possible solutions taking into account the main factors of computing and communications. More specifically, LAN are characterized as parallel computers in the context of linear algebra applications, proposing parallelization guidelines which are: specific for parallel computing on LAN, and simple enough to be applied to a wide range of problems
2004-01-01T00:00:00ZIn this thesis, parallel computing on installed local area networks (LAN) is focused, analyzing problems and possible solutions taking into account the main factors of computing and communications. More specifically, LAN are characterized as parallel computers in the context of linear algebra applications, proposing parallelization guidelines which are: specific for parallel computing on LAN, and simple enough to be applied to a wide range of problemsRedes Neuronales Artificiales. Un Enfoque Práctico: P. Isasi Viñuela, I. M. Galván. Pearson Educación, 2004. ISBN 84-205-4025-0Lanzarini, Laura Cristinahttp://sedici.unlp.edu.ar:80/handle/10915/94912019-06-19T04:02:38Z2004-01-01T00:00:00ZRevision
Journal of Computer Science & Technology; vol. 4, no. 2
Artificial Neural Networks belong to the sub-symbolic branch of Artificial Intelligence since they allow to find the solution of a problem without the need of knowing the algorithm necessary to solve it. This turns them into a tool based on an approach completely different from that used by conventional Computing.
Artificial neural networks (ANN) have been inspired in how the brain works and in the way its cells relate to each other. Technological advances provide ever-greater resources to represent really complex structures, perform computations at high speed and in parallel. This has indeed motivated research on this kind of tool.
2004-01-01T00:00:00ZArtificial Neural Networks belong to the sub-symbolic branch of Artificial Intelligence since they allow to find the solution of a problem without the need of knowing the algorithm necessary to solve it. This turns them into a tool based on an approach completely different from that used by conventional Computing.
Artificial neural networks (ANN) have been inspired in how the brain works and in the way its cells relate to each other. Technological advances provide ever-greater resources to represent really complex structures, perform computations at high speed and in parallel. This has indeed motivated research on this kind of tool.Design and Development of a Platform for Internet-based Collaborative Product DevelopmentZhang, KuiZhou, Jianzhonghttp://sedici.unlp.edu.ar:80/handle/10915/94902019-06-19T04:02:37Z2004-01-01T00:00:00ZArticulo
Journal of Computer Science & Technology; vol. 4, no. 2
In order to accomplish collaborative product development in the area of engineering, a work platform is needed to support all-sided collaborative work by the different development partners at geographically different locations. The platform is established on the basis of a three-tier architecture which provides four advantages over Client/Sever model. First of all, it can improve the capability and scalability of the development system. Secondly it can enhance the functional reliability. Thirdly it can transfer main management works to application servers to reduce the overall expenses. Finally it can increase the feasibility and development efficiency. In a typical Collaborative Product Development (CPD) scenario, design work is always over emphasized, while expert supervision is paid little attention. So, it is necessary to build the CPD platform for design and evaluation by Computer-Supported Cooperative Work (CSCW) technology and the Internet technology. This paper introduces the system functions, benefits and further challenges. Then key technologies, such as concurrency control mechanism, shared whiteboard collaborative control strategy, are analyzed in detail. It is proved that the system helps to enhance the product development efficiency.
2004-01-01T00:00:00ZIn order to accomplish collaborative product development in the area of engineering, a work platform is needed to support all-sided collaborative work by the different development partners at geographically different locations. The platform is established on the basis of a three-tier architecture which provides four advantages over Client/Sever model. First of all, it can improve the capability and scalability of the development system. Secondly it can enhance the functional reliability. Thirdly it can transfer main management works to application servers to reduce the overall expenses. Finally it can increase the feasibility and development efficiency. In a typical Collaborative Product Development (CPD) scenario, design work is always over emphasized, while expert supervision is paid little attention. So, it is necessary to build the CPD platform for design and evaluation by Computer-Supported Cooperative Work (CSCW) technology and the Internet technology. This paper introduces the system functions, benefits and further challenges. Then key technologies, such as concurrency control mechanism, shared whiteboard collaborative control strategy, are analyzed in detail. It is proved that the system helps to enhance the product development efficiency.Knowledge Insertion: an Efficient Approach to Reduce Search Effort in Evolutionary SchedulingPandolfi, DanielLasso, Marta GracielaSan Pedro, María Eugenia deVillagra, AndreaGallard, Raúl Hectorhttp://sedici.unlp.edu.ar:80/handle/10915/94892019-06-19T04:02:33Z2004-08-01T00:00:00ZArticulo
Journal of Computer Science & Technology; vol. 4, no. 2
Evolutionary algorithms (EAs) are merely blind search algorithms, which only make use of the relative fitness of solutions, but completely ignore the nature of the problem. Their performance can be improved by using new multirecombinative approaches, which provide a good balance between exploration and exploitation. Even though in difficult problems with large search spaces a considerable number of evaluations are required to arrive to near-optimal solutions. On the other hand specialized heuristics are based on some specific features of the problem, and the solution obtained can include some features of optimal solutions. If we insert in the evolutionary algorithm the problem specific knowledge embedded in good solutions (seeds), coming from some other heuristic or from the evolutionary process itself, we can expect that the algorithm will be guided to promising subspaces avoiding a large search. This work shows alternative ways to insert knowledge in the search process by means of the inherent information carried by solutions coming from that specialised heuristic or gathered by the evolutionary process itself. To show the efficiency of this approach, the present paper compares the performance of multirecombined evolutionary algorithms with and without knowledge insertion when applied to selected instances of the Average Tardiness Problem in a single machine environment.
2004-08-01T00:00:00ZEvolutionary algorithms (EAs) are merely blind search algorithms, which only make use of the relative fitness of solutions, but completely ignore the nature of the problem. Their performance can be improved by using new multirecombinative approaches, which provide a good balance between exploration and exploitation. Even though in difficult problems with large search spaces a considerable number of evaluations are required to arrive to near-optimal solutions. On the other hand specialized heuristics are based on some specific features of the problem, and the solution obtained can include some features of optimal solutions. If we insert in the evolutionary algorithm the problem specific knowledge embedded in good solutions (seeds), coming from some other heuristic or from the evolutionary process itself, we can expect that the algorithm will be guided to promising subspaces avoiding a large search. This work shows alternative ways to insert knowledge in the search process by means of the inherent information carried by solutions coming from that specialised heuristic or gathered by the evolutionary process itself. To show the efficiency of this approach, the present paper compares the performance of multirecombined evolutionary algorithms with and without knowledge insertion when applied to selected instances of the Average Tardiness Problem in a single machine environment.Design of distance courses in a web learning environment (WebLIDI)Sanz, Cecilia VerónicaZangara, María AlejandraGonzález, Alejandro HéctorDe Giusti, Armando EduardoIbañez, Eduardohttp://sedici.unlp.edu.ar:80/handle/10915/94882019-06-19T04:02:28Z2004-08-01T00:00:00ZArticulo
Journal of Computer Science & Technology; vol. 4, no. 2
This paper presents some of the aspects related to the multidisciplinary research process initiated in III LIDI for the development of a learning environment focused on the WEB (WebLIDI). It attempts to gather, in a work group, the technology working logic and the basic notions about teaching and learning. This project not only aims at developing a distance course design methodology, but also at the possibility of applying it through the WebLIDI environment - based on the principles connected to the pedagogical and technological variables involved in teaching and learning instances. Some of the decisions taken throughout this process are here presented in detail, ranging from general information of a course to content structuring and evaluation possibilities. Also, the current state of the development - expected to be used experimentally as from the second semester of 2003- is specified.
2004-08-01T00:00:00ZThis paper presents some of the aspects related to the multidisciplinary research process initiated in III LIDI for the development of a learning environment focused on the WEB (WebLIDI). It attempts to gather, in a work group, the technology working logic and the basic notions about teaching and learning. This project not only aims at developing a distance course design methodology, but also at the possibility of applying it through the WebLIDI environment - based on the principles connected to the pedagogical and technological variables involved in teaching and learning instances. Some of the decisions taken throughout this process are here presented in detail, ranging from general information of a course to content structuring and evaluation possibilities. Also, the current state of the development - expected to be used experimentally as from the second semester of 2003- is specified.Implementing agents for a collaborative online learning environmentAzevedo, Hilton José Silva deScalabrin, Edson EmílioFaria, Marcio de PaulaManfroi, Fairushttp://sedici.unlp.edu.ar:80/handle/10915/94872019-06-16T04:04:57Z2004-01-01T00:00:00ZArticulo
Journal of Computer Science & Technology; vol. 4, no. 2
This paper discusses the main lines used to model intelligent agents that will operate in a Collaborative Online Learning Environment-COLE. The aim of COLE is to evaluate the contribution that Information Technology and Multiagent Systems can bring to the discussion about new adult learning processes. The work hypothesis is that online environments can better handle the huge mass of data related to human interactions in social learning processes than the face-to-face educational ones. Acquiring and managing expanded sets of data has been an obstacle to implement educational practices that consider students in broader dimensions, far beyond content assessment. Elements of the Social Learning Theory, specifically concepts from the Communities of Practice base COLE implementation. A brief description of Project Based Learning - PBL and portfolios (here conceptual maps) give elements to understand the project approach. The SAAS method, used to identify the agents is described. Use cases related to the "Librarian Agent" and the "Portfolio Agent" are presented and windows related to the "portfolio" and "active reading annotation" services illustrate the work.
2004-01-01T00:00:00ZThis paper discusses the main lines used to model intelligent agents that will operate in a Collaborative Online Learning Environment-COLE. The aim of COLE is to evaluate the contribution that Information Technology and Multiagent Systems can bring to the discussion about new adult learning processes. The work hypothesis is that online environments can better handle the huge mass of data related to human interactions in social learning processes than the face-to-face educational ones. Acquiring and managing expanded sets of data has been an obstacle to implement educational practices that consider students in broader dimensions, far beyond content assessment. Elements of the Social Learning Theory, specifically concepts from the Communities of Practice base COLE implementation. A brief description of Project Based Learning - PBL and portfolios (here conceptual maps) give elements to understand the project approach. The SAAS method, used to identify the agents is described. Use cases related to the "Librarian Agent" and the "Portfolio Agent" are presented and windows related to the "portfolio" and "active reading annotation" services illustrate the work.Teaching fundamentals of computing theory: a constructivist approachChesñevar, Carlos IvánMaguitman, Ana GabrielaGonzález, María PaulaCobo, María Laurahttp://sedici.unlp.edu.ar:80/handle/10915/94862019-06-16T04:04:54Z2004-08-01T00:00:00ZArticulo
Journal of Computer Science & Technology; vol. 4, no. 2
A Fundamentals of Computing Theory course involves different topics that are core to the Computer Science curricula and whose level of abstraction makes them difficult both to teach and to learn. Such difficulty stems from the complexity of the abstract notions involved and the required mathematical background. Surveys conducted among our students showed that many of them were applying some theoretical concepts mechanically rather than developing significant learning. This paper shows a number of didactic strategies that we introduced in the Fundamentals of Computing Theory curricula to cope with the above problem. The proposed strategies were based on a stronger use of technology and a constructivist approach. The final goal was to promote more significant learning of the course topics.
2004-08-01T00:00:00ZA Fundamentals of Computing Theory course involves different topics that are core to the Computer Science curricula and whose level of abstraction makes them difficult both to teach and to learn. Such difficulty stems from the complexity of the abstract notions involved and the required mathematical background. Surveys conducted among our students showed that many of them were applying some theoretical concepts mechanically rather than developing significant learning. This paper shows a number of didactic strategies that we introduced in the Fundamentals of Computing Theory curricula to cope with the above problem. The proposed strategies were based on a stronger use of technology and a constructivist approach. The final goal was to promote more significant learning of the course topics.Learning by generation in computer science educationKerren, Andreashttp://sedici.unlp.edu.ar:80/handle/10915/94852019-06-16T04:04:53Z2004-08-01T00:00:00ZArticulo
Journal of Computer Science & Technology; vol. 4, no. 2
The use of generic and generative methods for the development and application of interactive educational software is a relatively unexplored area in industry and education. Advantages of generic and generative techniques are, among other things, the high degree of reusability of systems parts and the reduction of development costs. Furthermore, generative methods can be used for the development or realization of novel learning models. In this paper, we discuss such a learning model that propagates a new way of explorative learning in computer science education with the help of generators. A realization of this model represents the educational software GANIFA on the theory of generating finite automata from regular expressions. In addition to the educational system's description, we present an evaluation of this system.
2004-08-01T00:00:00ZThe use of generic and generative methods for the development and application of interactive educational software is a relatively unexplored area in industry and education. Advantages of generic and generative techniques are, among other things, the high degree of reusability of systems parts and the reduction of development costs. Furthermore, generative methods can be used for the development or realization of novel learning models. In this paper, we discuss such a learning model that propagates a new way of explorative learning in computer science education with the help of generators. A realization of this model represents the educational software GANIFA on the theory of generating finite automata from regular expressions. In addition to the educational system's description, we present an evaluation of this system.