Accepted Papers

  • Management of Saltwater Intrusion in Coastal Aquifers by Ant Colony Algorithm
    Mehdi Nezhad Naderi1, Masoud Reza Hessami Kermani2 and Gholam-Abbas Barani2 1Islamic Azad University,Tonekabon, Iran,2Shahid Bahonar University,Kerman, Iran

    Population growth in coastal areas is caused increasing of indiscriminate pumping from coastal wells and spread of saltwater intrusion into wells. In this paper, Because of huge, rupture and local minimum in search space, Ant colony algorithm has been used for finding optimal solutions. When well exposed to salt water is off and taken out of operation. As result the optimal amount of pumping and position of each of the wells were obtained with this in mind that the maximum net profit and Saltwater tackle situations is affected by exploitation wells are some distance away of each wells. The results show that Ant colony algorithm can effectively and efficiently be used to obtain nearly global solutions to this groundwater management problem. The computational effort needed to determine the optimal solution increases with complexity of the problem. The computational time required for the solution of management model increases with the complexity of the problem. The optimum solution is not solved for values of less than 10 /day thus problem has high local solutions.

    Stefano Cherubinand Giovanni Agosta ,Informazione e Bioningegneria – Politecnico di Milano, Milano, Italy

    In recent years, customized precision has emerged as a promising approach to improve power/performance trade-offs that are nowadays a major roadblock on the path towards exascale in High Perfomance Computing.In this work we explore customized precision by replacing double precision floating point computations with single precision or fixed point arithmetic. We dynamically perform an exploration of the possible solutions during the early phase of the application lifetime. We evaluate the effect of our solution on a subset of the PolyBench/C benchmark suite, where we observe a speedup on 3 out of 6 benchmarks, while keeping the error within manageable levels. We further explore the parametrization of the exploration policy, showing the impact of different ways of staging the exploration on the performance.

    Felipe Lima Duarte, Angélica Félix de Castro and Paulo Gabriel Gadelha Queiroz, UFERSA, Mossoró - RN, Brazil

    A System of Systems (SoS) is a class of system composed of a set or arrangement of independent systems that together provide unique functionality for the end user. Due to its complexity, the Requirement Engineering (RE) process needs to undergo adaptations to fit the development of this type of system. In this context, the objective of this work is to propose a approach for the development of SoS, called REAP-SoS. The main characteristic of the REAP-SoS is the derivation of the individual missions and requirements of the constituent systems based on the general SoS assignments. In addition, the approach is also able to derive the requirements of the constituent systems of SoS. To validate the approach, a case study on a SoS urban traffic control and monitoring was performed

  • An Ontology Matching Problem Based on Refined Similarity Measures
    Allaoua Refoufi and Achref Benarab, University of Setif, Algeria

    Ontology matching is the process that identifies correspondences between similar concepts in two different ontologies of the same domain of discourse to solve knowledge heterogeneous problems. We propose an automatic similarity based matching algorithm that exploits almost all types of entities descriptions as well as their relations to effectively compute the correspondences between the two to be matched ontologies. The iterative algorithm computes each measure of similarity separately and then aggregates them in a linear combination to compose the final similarity score. The measures used deal with linguistic, semantic, and structural as well as many other measures to gain efficiency. We also include a new similarity measure based on dynamic programming in conjunction with known measures to refine the similarity process. Finally, we provide comparative experimental results in support of our method on several wellknown ontology benchmarks recommended by the OAEI1. The results obtained are shown to be quite superior compared to the state-of-the-art ontology matching systems.