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International Journal of Electrical and Computer Engineering
ISSN : 20888708     EISSN : 27222578     DOI : -
International Journal of Electrical and Computer Engineering (IJECE, ISSN: 2088-8708, a SCOPUS indexed Journal, SNIP: 1.001; SJR: 0.296; CiteScore: 0.99; SJR & CiteScore Q2 on both of the Electrical & Electronics Engineering, and Computer Science) is the official publication of the Institute of Advanced Engineering and Science (IAES). The journal is open to submission from scholars and experts in the wide areas of electrical, electronics, instrumentation, control, telecommunication and computer engineering from the global world.
Articles 63 Documents
Search results for , issue "Vol 7, No 2: April 2017" : 63 Documents clear
An Improved Integrated Hash and Attributed based Encryption Model on High Dimensional Data in Cloud Environment Satheesh K S V A Kavuri; Gangadhara Rao Kancherla; Basaveswararao Bobba
International Journal of Electrical and Computer Engineering (IJECE) Vol 7, No 2: April 2017
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (607.896 KB) | DOI: 10.11591/ijece.v7i2.pp950-960

Abstract

Cloud computing is a distributed architecture where user can store their private, public or any application software components on it. Many cloud based privacy protection solutions have been implemented, however most of them only focus on limited data resources and storage format. Data confidentiality and inefficient data access methods are the major issues which block the cloud users to store their high dimensional data. With more and more cloud based applications are being available and stored on various cloud servers, a novel multi-user based privacy protection mechanism need to design and develop to improve the privacy protection on high dimensional data. In this paper, a novel integrity algorithm with attribute based encryption model was implemented to ensure confidentiality for high dimensional data security on cloud storage. The main objective of this model is to store, transmit and retrieve the high dimensional cloud data with low computational time and high security. Experimental results show that the proposed model has high data scalability, less computational time and low memory usage compared to traditional cloud based privacy protection models.
Parallel Genetic Algorithms for University Scheduling Problem Artan Berisha; Eliot Bytyçi; Ardeshir Tershnjaku
International Journal of Electrical and Computer Engineering (IJECE) Vol 7, No 2: April 2017
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1244.806 KB) | DOI: 10.11591/ijece.v7i2.pp1096-1102

Abstract

University scheduling timetabling problem, falls into NP hard problems. Re-searchers have tried with many techniques to find the most suitable and fastest way for solving the problem. With the emergence of multi-core systems, the parallel implementation was considered for finding the solution. Our approaches attempt to combine several techniques in two algorithms: coarse grained algorithm and multi thread tournament algorithm. The results obtained from two algorithms are compared, using an algorithm evaluation function. Considering execution time, the coarse grained algorithm performed twice better than the multi thread algorithm.
Evaluation of the Energy Performance of the Amougdoul Wind Farm, Morocco Asma Ezzaidi; Mustapha Elyaqouti; Lahoussine Bouhouch; Ahmed Ihlal
International Journal of Electrical and Computer Engineering (IJECE) Vol 7, No 2: April 2017
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (692.326 KB) | DOI: 10.11591/ijece.v7i2.pp692-705

Abstract

This paper is concerned with the assessment of the the performance of the Amougdoul wind farm. We have determined the Weibull parameters; namely the scale parameter, c (m/s) and shape parameter, k. After that, we have estimated energy output by a wind turbine using two techniques: the useful power calculation method and the method based on the modeling of the power curve, which is respectively 134.5 kW and 194.19 KW corresponding to 27% and 39% of the available wind energy, which confirm that the conversion efficiency does not exceed 40%.

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