MULTI-AGENT WORKFLOW
"AN APPROACH BASED ON THE ONTOLOGY OF SERVICE"
MAAMAR KHATER, ZAKARIA ELBERRICHI and MIMOUN MALKIDepartmen, of Computer ScienceUniversity of Sidi Bel Abbes, Algeria.
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ABSTRACT
The introduction of the technology of agents into the field of Workflow, makes it possible to offer more flexibility and adaptability to workflow systems, this is due to the characteristics of the agents and in particular the intelligent agents. This article explores the two technologies (workflow and agent) and the various forms of integration of agents in workflow management systems, and discusses the benefit of this integration. An approach "Agent-Based Workflow" based on the ontology of service is also given.
Keywords: Workflow, Software Agents, Multi-Agent Systems, Agent-Based Workflow, Agent- Enhanced Workflow, service ontology.
GENETIC ALGORITHM FOR COMPRESSING SOUND DATA
DR. MOHAMMED A. F. AL-HUSAINYDepartment of Computer Information Systems, Faculty of Sciences and Information Technology
Al-Zaytoonah University of Jordan
Amman-Jordan
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ABSTRACT
The principal objective of this research is an adoption of the Genetic Algorithm (GA) for studying it firstly, and
to stop over the facilities which are introduced from the genetic algorithm.The candidate field for applying the facilities
of the genetic algorithm is the data compression field, because researchers took great interest in this field in the recent
years. This research uses the facilities of the genetic algorithm for the enhancement of the performance of one of the
popular compression method, Vector Quantization (VQ) method is selected in this work. After studying this method, new
proposed algorithm for mixing the (GA) with this method was constructed and then the required programs for testing this algorithm was written. A good enhancement was recorded for the performance of the (VQ) method when mixed with the (GA). The proposed algorithm was tested by applying it on some sound data files. Some fidelity measures are calculated to evaluate the performance of the new proposed algorithm.
KEYWORDS: Vector Quantization, Crossover Operation, Mutation Operation, Clustering.