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IAES International Journal of Artificial Intelligence (IJ-AI)
Published by Institute of Advanced Engineering and Science
ISSN : 20894872     EISSN : 22528938     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Engineering
IAES International Journal of Artificial Intelligence (IJ-AI) publishes articles in the field of artificial intelligence (AI). The scope covers all artificial intelligence area and its application in the following topics: neural networks; fuzzy logic; simulated biological evolution algorithms (like genetic algorithm, ant colony optimization, etc); reasoning and evolution; intelligence applications; computer vision and speech understanding; multimedia and cognitive informatics, data mining and machine learning tools, heuristic and AI planning strategies and tools, computational theories of learning; technology and computing (like particle swarm optimization); intelligent system architectures; knowledge representation; bioinformatics; natural language processing; multiagent systems; etc.
Arjuna Subject : -
Articles 5 Documents
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Search results for , issue "Vol 5, No 2: June 2016" : 5 Documents clear
Development of an Efficient Face Recognition System Based on Linear and Nonlinear Algorithms Araoluwa Simileolu Filani; Adebayo Olusola Adetunmbi
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 5, No 2: June 2016
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (756.397 KB) | DOI: 10.11591/ijai.v5.i2.pp80-88

Abstract

This paper presents appearance based methods for face recognition using linear and nonlinear techniques. The linear algorithms used are Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA). The two nonlinear methods used are the Kernel Principal Components Analysis (KPCA) and Kernel Fisher Analysis (KFA). The linear dimensional reduction projection methods encode pattern information based on second order dependencies. The nonlinear methods are used to handle relationships among three or more pixels. In the final stage, Mahalinobis Cosine (MAHCOS) metric is used to define the similarity measure between two images after they have passed through the corresponding dimensional reduction techniques. The experiment showed that LDA and KFA have the highest performance of 93.33 % from the CMC and ROC results when used with Gabor wavelets. The overall result using 400 images of AT&T database showed that the performance of the linear and nonlinear algorithms can be affected by the number of classes of the images, preprocessing of images, and the number of face images of the test sets used for recognition.
Automatic Exudates Detection in Diabetic Retinopathy Images H. Faouzi; Mohamed Fakir
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 5, No 2: June 2016
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (509.133 KB) | DOI: 10.11591/ijai.v5.i2.pp45-54

Abstract

Diabetic Retinopathy (DR) refers to the presence of typical retinal micro vascular lesions in persons with diabetics. When the disease is at the early state, a prompt diagnosis may help in preventing irreversible damages to the diabetic eye. If the exudates are closer to macula, then the situation is critical. Early detection can potentially reduce the risk of blind.  This paper proposes tool for the early detection of Diabetic Retinopathy using edge detection, algorithm kmeans in segmentation phase, invariant moments (Hu and Affine) and descriptor GIST in extraction phase. In the recognition phase, neural network is adopted. All tests are applied on database DIARETDB1.
Effective Analysis of Lung Infection using Fuzzy Rules Navneet Walia; Harsukhpreet Singh; Anurag Sharma
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 5, No 2: June 2016
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (357.388 KB) | DOI: 10.11591/ijai.v5.i2.pp55-63

Abstract

Soft Computing is conglomerate of methodologies which works together and provides an ability to make a decision from reliable data or expert’s experience. Nowadays different types of soft computing techniques such as neural network, fuzzy logic, genetic algorithm and hybrid system are largely used in medical areas. In this paper, an algorithm for analysis of lung infection is presented. The main focus is to develop system architecture to find probable disease stage patient may have. Severity level of disease is determined by using rule base method. The algorithm uses an output of Rulebase entered by the user to determine a level of infection.Soft Computing is conglomerate of methodologies which works together and provides an ability to make decision from reliable data or expert’s experience. Nowadays different types of soft computing techniques such as neural network, fuzzy logic, genetic algorithm and hybrid system are largely used in medical areas. In this paper, algorithm for analysis of lung infection is presented. The main focus is to develop system architecture to find probable disease stage patient may have. Severity level of disease is determined by using rule base method. The algorithm uses output of Rulebase entered by user to determine level of infection.
An SVD based Real Coded Genetic Algorithm for Graph Clustering Parthajit Roy; Jyotsna Kumar Mandal
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 5, No 2: June 2016
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (698.175 KB) | DOI: 10.11591/ijai.v5.i2.pp64-71

Abstract

This paper proposes a novel graph clustering model based on genetic algorithm using a random point bipartite graph. The model uses random points distributed uniformly in the data space and the measurement of distance from these points to the test points have been considered as proximity. Random points and test points create an adjacency matrix. To create a similarity matrix, correlation coefficients are computed from the given bipartite graph. The eigenvectors of the singular value decomposition of the weighted similarity matrix are considered and the same are passed to an elitist GA model for identifying the cluster centers. The model has been tasted with the standard datasets and the performance has been compared with existing standard algorithms.
Rule Based and Expectation Maximization algorithm for Arabic-English Hybrid Machine Translation Arwa Hatem Alqudsi; Nazlia Omar; Rabha W. Ibrahim
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 5, No 2: June 2016
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (527.192 KB) | DOI: 10.11591/ijai.v5.i2.pp72-79

Abstract

It is practically impossible for pure machine translation approach to process all of translation problems; however, Rule Based Machine Translation and Statistical Machine translation (RBMT and SMT) use different architectures for performing translation task. Lexical analyser and syntactic analyser are solved by Rule Based and some amount of ambiguity is left to be solved by Expectation–Maximization (EM) algorithm, which is an iterative statistic algorithm for finding maximum likelihood. In this paper we have proposed an integrated Hybrid Machine Translation (HMT) system. The goal is to combine the best properties of each approach. Initially, Arabic text is keyed into RBMT; then the output will be edited by EM algorithm to generate the final translation of English text. As we have seen in previous works, the performance and enhancement of EM algorithm, the key of EM algorithm performance is the ability to accurately transform a frequency from one language to another. Results showing that, as proved by BLEU system, the proposed method can substantially outperform standard Rule Based approach and EM algorithm in terms of frequency and accuracy. The results of this study have been showed that the score of HMT system is higher than SMT system in all cases. When combining two approaches, HMT outperformed SMT in Bleu score.

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