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INDONESIA
International Journal of Intelligent Systems and Applications in Engineering
Published by Ismail SARITAS
ISSN : 21476799     EISSN : -     DOI : -
Core Subject : Science,
Computer Science & IT
International Journal of Intelligent Systems and Applications in Engineering (IJISAE) is an international and interdisciplinary journal for both invited and contributed peer reviewed articles that intelligent systems and applications in engineering at all levels. The journal publishes a broad range of papers covering theory and practice in order to facilitate future efforts of individuals and groups involved in the field. IJISAE, a peer-reviewed double-blind refereed journal, publishes original papers featuring innovative and practical technologies related to the design and development of intelligent systems in engineering. Its coverage also includes papers on intelligent systems applications in areas such as nanotechnology, renewable energy, medicine engineering, Aeronautics and Astronautics, mechatronics, industrial manufacturing, bioengineering, agriculture, services, intelligence based automation and appliances, medical robots and robotic rehabilitations, space exploration and etc.
Arjuna Subject : -
Articles 4 Documents
 1 
Search results for , issue " Vol 3, No 3 (2015)" : 4 Documents clear
Lossless Text Compression Technique with LSB Technique to Hide Secret Message inside an Image (CLSB) Dagez, Hanan Ettaher
International Journal of Intelligent Systems and Applications in Engineering Vol 3, No 3 (2015)
Publisher : Advanced Technology and Science (ATScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18201/ijisae.61154

Abstract

Abstract— This paper presents CLSB algorithm to improve and increase the security ofhiding message inside an image by using Least Significant Bit (LSB) method. This research attempts to improve the way has been introduced in [1], where they use digital images to hide Secret Text files. This method is working by distributing data (BMP image format) randomly without use any table to store the path of hiding data. CLSB propose new method to reduce size of dictionary index. Therefore, the main objective of this research is to develop a new method to increase the security by adding a secret key to decode and improve the quality by using LZW method to reduce the size of text file before hiding. Results proved and has also presented in this paper.   Abstract— This paper presents CLSB algorithm to improve and increase the security ofhiding message inside an image by using Least Significant Bit (LSB) method. This research attempts to improve the way has been introduced in [1], where they use digital images to hide Secret Text files. This method is working by distributing data (BMP image format) randomly without use any table to store the path of hiding data. CLSB propose new method to reduce size of dictionary index. Therefore, the main objective of this research is to develop a new method to increase the security by adding a secret key to decode and improve the quality by using LZW method to reduce the size of text file before hiding. Results proved and has also presented in this paper.   
Application of global thresholding in bread porosity evaluation Bosakova-Ardenska, Atanaska
International Journal of Intelligent Systems and Applications in Engineering Vol 3, No 3 (2015)
Publisher : Advanced Technology and Science (ATScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18201/ijisae.30637

Abstract

The white bread is one of most popular food in Bulgaria. Its quality is defined by standards and control is also standardized. The white bread has four groups of quality parameters - organoleptic, physicochemical, chemical contaminants and microbiological. This paper presents one research over white bread porosity which is one of physicochemical parameters. By standard evaluation of bread porosity is time expensive procedure. Current research proposes one fast computer based approach for white bread porosity evaluation. In experiments are used three brands white breads. The images of breads are binarized with four known algorithms and coefficient of diversity (ratio of white pixels and all image pixels) for resulting binary images is calculated. This coefficient corresponds with bread porosity. Experimental results show that one of these algorithms – Vector Median Thresholding, is appropriate for bread porosity evaluation.
A Modified Flower Pollination Algorithm for Fractional Programming Problems metwalli, mohamed Abdel-Baset; hezam, ibrahim
International Journal of Intelligent Systems and Applications in Engineering Vol 3, No 3 (2015)
Publisher : Advanced Technology and Science (ATScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18201/ijisae.56680

Abstract

Flower pollination algorithm is a new nature-inspired algorithm, based on the characteristics of flowering plants. In this paper, a new method is developed chaos-based Flower Pollination Algorithm (CFPA) to solve Fractional Programming Problems (FPPs). The proposed algorithm is tested using several ROP benchmarks. The test aims to prove the capability of the CFPA to solve any type of FPPs. The solution results employing the CFPA algorithm are compared with a number of exact and metaheuristic solution methods used for handling FPPs. Numerical examples are given to show the feasibility, effectiveness, and robustness of the proposed algorithm. The results obtained using CFPA indicated the superiority of the proposed technique among others in computational time.
Neural Boundary Conditions in Optic Guides Özkan-Bakbak, Pınar
International Journal of Intelligent Systems and Applications in Engineering Vol 3, No 3 (2015)
Publisher : Advanced Technology and Science (ATScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18201/ijisae.04354

Abstract

In this study, the boundary coefficients of Transverse Electric (TE) and Transverse Magnetic (TM) modes at a planar slab optic guides are modeled by Neural Networks (NN). After modal analysis, train and test files are prepared for NN. Multi-Layer Perceptron (MLP) and Radial Basis Function (RBF) neural networks are performed and compared with each other. NNs are expected to be capable of modeling optical fiber technology in industry based on the same approaches as a result of this study.

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