IJARAI Volume 1 Issue 5

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Paper 1: A genetic algorithm approach for scheduling of resources in well-services companies

Abstract: In this paper, two examples of resources scheduling in well-services companies are solved by means of genetic algorithms: resources for call solving, people scheduling. The results demonstrate that the genetic algorithm approach can provide acceptable solutions to this type of call solving for scheduling in well-services companies. The suggested approach could be easily extended to various resource scheduling areas: process scheduling, transportation scheduling.

Author 1: Adrian Brezulianu
Author 2: Lucian Fira
Author 3: Monica Fira

Keywords: Genetic algorithm; optimization; well-services.

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Paper 2: An improvement direction for filter selection techniques using information theory measures and quadratic optimization

Abstract: Filter selection techniques are known for their simplicity and efficiency. However this kind of methods doesn’t take into consideration the features inter-redundancy. Consequently the un-removed redundant features remain in the final classification model, giving lower generalization performance. In this paper we propose to use a mathematical optimization method that reduces inter-features redundancy and maximize relevance between each feature and the target variable.

Author 1: Waad Bouaguel
Author 2: Ghazi Bel Mufti

Keywords: Feature selection; mRMR; Quadratic mutual information ; filter.

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Paper 3: A Comparative Study on different AI Techniques towards Performance Evaluation in RRM(Radar Resource Management)

Abstract: The multifunction radar (MFR) has to make a decision as to which functions are to be performed first or which must be degraded or even not done at all when there are not enough resources to be allocated. The process of making these decisions and determining their allocation as a function of time is known as Radar Resource Management (RRM). The RRM has two basic issues: task prioritization and task scheduling. The task prioritization is an important factor in the task scheduler. The other factor is the required scheduling time, which is decided by the environment, the target scenario and the performance requirements of radar functions. The required scheduling time could be improved by using advanced algorithm [1, 6].

Author 1: Madhusudhan H S
Author 2: Khalid Nazim S.A

Keywords: Radar; RRM (Radar Resource Management); Artificial Intelligence (AI); Neural Network (NN); Fuzzy Logic (FL).

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Paper 4: Integrated Information System of Monitoring and Management for Heart Centers

Abstract: The integrated information system presented in this paper is focused on increasing the quality of the medical services offered to the patients by rendering the activities more efficient and by corroborating the family doctors and the cardiologists’ efforts. In order to accomplish the mentioned objectives we propose implementing an integrated information system by means of which the integrated management of the medical data will be done. In addition, it has been offered a collaborative instrument, patient oriented, that it will be used both by the family doctor and by the specialist doctor.

Author 1: Adrian Brezulianu
Author 2: Monica Fira

Keywords: ECG; Monitoring; Management; Integrated Information System.

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Paper 6: Introduction of the weight edition errors in the Levenshtein distance

Abstract: In this paper, we present a new approach dedicated to correcting the spelling errors of the Arabic language. This approach corrects typographical errors like inserting, deleting, and permutation. Our method is inspired from the Levenshtein algorithm, and allows a finer and better scheduling than Levenshtein. The results obtained are very satisfactory and encouraging, which shows the interest of our new approach.

Author 1: Gueddah Hicham
Author 2: Yousfi Abdallah
Author 3: Belkasmi Mostapha

Keywords: component;spelling errors; correction; Levenshtein distance; weight edition error.

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