IJCSA                                         ISSN 0972-9038
         INTERNATIONAL JOURNAL OF COMPUTER SCIENCE & APPLICATIONS
 

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Year 2004: Volume I Issue I


CONTENTS
     Paper Title:- Prime Implicates of First Order Formulas
       Author Name:- Manoj K. Raut and Arindama Singh
       Topic:- Logic
       URL:-

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       Abstract:-

This paper extends the notion of prime implicates to first order logic formulas without equality which are assumed to be in Skolem Conjunctive Normal Form. Using the extended notions of consensus and subsumption it is shown that the consensus-subsumption algorithm for com-puting prime implicates well known for propositional formulas can be conditionally lifted to first order formulas.



       Paper Title:- On-Line Fault Detection Techniques for Technical Systems: A Survey
       Author Name:- C. Angeli & A. Chatzinikolaou
       Topic:- Fault Detection
       URL:-

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       Abstract:-

On-line fault detection and isolation techniques have been developed for automated processes during the last few years. These methods include numerical methods, artificial intelligence methods or combinations of the two methodologies. This paper includes a reference to recent research work on numerical methods, an extensive presentation of artificial intelligence methods used for the fault detection process in technical systems and relevant survey material. Special reference is made to the on-line expert systems development where specific resent research work is illustrated.



       Paper Title:- Using Meta-Learning to Support Data Mining
       Author Name:- Ricardo Vilalta, Christophe Giraud-Carrier, Pavel Brazdil, Carlos Soares
       Topic:- Datamining
       URL:-

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       Abstract:-

Current data mining tools are characterized by a plethora of algorithms but a lack of guidelines to select the right method according to the nature of the problem under analysis. Producing such guidelines is a primary goal by the field of meta-learning; the research objective is to understand the interaction between the mechanism of learning and the concrete contexts in which that mechanism is applicable. The field of meta- learning has seen continuous growth in the past years with interesting new developments in the construction of practical model-selection assistants, task-adaptive learners, and a solid conceptual framework. In this paper, we give an overview of different techniques necessary to build meta- learning systems. We begin by describing an idealized meta-learning architecture comprising a variety of relevant component techniques. We then look at how each technique has been studied and implemented by previous research. In addition, we show how meta-learning has already been identified as an important component in real-world applications.



       Paper Title:- Direct-Proportional Length-Based DNA Computing for Shortest Path Problem
       Author Name:- Zuwairie Ibrahim, Yusei Tsuboi, Osamu Ono, Marzuki Khalid
       Topic:- BioComputing
       URL:-

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       Abstract:-

Deoxyribonucleic Acid or DNA computing has emerged as an interdisciplinary field that draws together chemistry, molecular biology, computer science, and mathematics. From the DNA computing point of view, it has been proven that it is possible to solve weighted graph problems by exploiting some characteristics of DNA such as length, concentration, and melting temperature. In this paper, we present an alternative direct-proportional length-based DNA computing approach whereby the cost of each path is encoded by the length of the oligonucleotides in a proportional way. The advantage is such that, after the hybridization and ligation reactions, gel electrophoresis can be performed to separate the respective DNA duplex according to their length which directly decodes the results. In addition to this advantage, the reliability of the proposed approach can be enhanced as only the general and well-known bio-molecular laboratory operations are employed during the computation.


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