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Détails du magazine
Format
Magazine
eISSN
2449-6499
Première publication
30 Dec 2014
Période de publication
4 fois par an
Langues
Anglais

Chercher

Volume 3 (2013): Edition 4 (October 2013)

Détails du magazine
Format
Magazine
eISSN
2449-6499
Première publication
30 Dec 2014
Période de publication
4 fois par an
Langues
Anglais

Chercher

5 Articles
Accès libre

A Survey of old and New Results for the Test Error Estimation of a Classifier

Publié en ligne: 30 Dec 2014
Pages: 229 - 242

Résumé

Abstract

The estimation of the generalization error of a trained classifier by means of a test set is one of the oldest problems in pattern recognition and machine learning. Despite this problem has been addressed for several decades, it seems that the last word has not been written yet, because new proposals continue to appear in the literature. Our objective is to survey and compare old and new techniques, in terms of quality of the estimation, easiness of use, and rigorousness of the approach, so to understand if the new proposals represent an effective improvement on old ones.

Accès libre

Application of Artificial Neural Network and Genetic Algorithm to Healthcarewaste Prediction

Publié en ligne: 30 Dec 2014
Pages: 243 - 250

Résumé

Abstract

Prompt and proper management of healthcare waste is critical to minimize the negative impact on the environment. Improving the prediction accuracy of the healthcare waste generated in hospitals is essential and advantageous in effective waste management. This study aims at developing a model to predict the amount of healthcare waste. For this purpose, three models based on artificial neural network (ANN), multiple linear regression (MLR), and combination of ANN and genetic algorithm (ANN-GA) are applied to predict the waste of 50 hospitals in Iran. In order to improve the performance of ANN for prediction, GA is applied to find the optimal initial weights in the ANN. The performance of the three models is evaluated by mean squared errors. The obtained results have shown that GA has significant impact on optimizing initial weights and improving the performance of ANN.

Accès libre

B-Tree Algorithm Complexity Analysis to Evaluate the Feasibility of its Application in the University Course Timetabling Problem

Publié en ligne: 30 Dec 2014
Pages: 251 - 263

Résumé

Abstract

This paper presents a comparative analysis of complexity between the B-TREE and the Binary Search Algorithms, both theoretically and experimentally, to evaluate their efficiency in finding overlap of classes for students and teachers in the University Course Timetabling Problem (UCTP). According to the theory, B-TREE Search complexity is lower than Binary Search. The performed experimental tests showed the B-TREE Search Algorithm is more efficient than Binary Search, but only using a dataset larger than 75 students per classroom.

Accès libre

A Novel Approach for Automatic Detection and Classification of Suspicious Lesions in Breast Ultrasound Images

Publié en ligne: 30 Dec 2014
Pages: 265 - 276

Résumé

Abstract

In this research, a new method for automatic detection and classification of suspected breast cancer lesions using ultrasound images is proposed. In this fully automated method, de-noising using fuzzy logic and correlation among ultrasound images taken from different angles is used. Feature selection using combination of sequential backward search, sequential forward search and distance-based methods is obtained. A new segmentation method based on automatic selection of seed points and region growing is proposed and classification of lesions into two malignant and benign classes using combination of AdaBoost, Artificial Neural Network and Fuzzy Support Vector Machine classifiers and majority voting is implemented.

Accès libre

Dimensionality Reduction of Dynamic Mesh Animations Using HO-SVD

Publié en ligne: 30 Dec 2014
Pages: 277 - 289

Résumé

Abstract

This work presents an analysis of Higher Order Singular Value Decomposition (HOSVD) applied to reduction of dimensionality of 3D mesh animations. Compression error is measured using three metrics (MSE, Hausdorff, MSDM). Results are compared with a method based on Principal Component Analysis (PCA) and presented on a set of animations with typical mesh deformations.

5 Articles
Accès libre

A Survey of old and New Results for the Test Error Estimation of a Classifier

Publié en ligne: 30 Dec 2014
Pages: 229 - 242

Résumé

Abstract

The estimation of the generalization error of a trained classifier by means of a test set is one of the oldest problems in pattern recognition and machine learning. Despite this problem has been addressed for several decades, it seems that the last word has not been written yet, because new proposals continue to appear in the literature. Our objective is to survey and compare old and new techniques, in terms of quality of the estimation, easiness of use, and rigorousness of the approach, so to understand if the new proposals represent an effective improvement on old ones.

Accès libre

Application of Artificial Neural Network and Genetic Algorithm to Healthcarewaste Prediction

Publié en ligne: 30 Dec 2014
Pages: 243 - 250

Résumé

Abstract

Prompt and proper management of healthcare waste is critical to minimize the negative impact on the environment. Improving the prediction accuracy of the healthcare waste generated in hospitals is essential and advantageous in effective waste management. This study aims at developing a model to predict the amount of healthcare waste. For this purpose, three models based on artificial neural network (ANN), multiple linear regression (MLR), and combination of ANN and genetic algorithm (ANN-GA) are applied to predict the waste of 50 hospitals in Iran. In order to improve the performance of ANN for prediction, GA is applied to find the optimal initial weights in the ANN. The performance of the three models is evaluated by mean squared errors. The obtained results have shown that GA has significant impact on optimizing initial weights and improving the performance of ANN.

Accès libre

B-Tree Algorithm Complexity Analysis to Evaluate the Feasibility of its Application in the University Course Timetabling Problem

Publié en ligne: 30 Dec 2014
Pages: 251 - 263

Résumé

Abstract

This paper presents a comparative analysis of complexity between the B-TREE and the Binary Search Algorithms, both theoretically and experimentally, to evaluate their efficiency in finding overlap of classes for students and teachers in the University Course Timetabling Problem (UCTP). According to the theory, B-TREE Search complexity is lower than Binary Search. The performed experimental tests showed the B-TREE Search Algorithm is more efficient than Binary Search, but only using a dataset larger than 75 students per classroom.

Accès libre

A Novel Approach for Automatic Detection and Classification of Suspicious Lesions in Breast Ultrasound Images

Publié en ligne: 30 Dec 2014
Pages: 265 - 276

Résumé

Abstract

In this research, a new method for automatic detection and classification of suspected breast cancer lesions using ultrasound images is proposed. In this fully automated method, de-noising using fuzzy logic and correlation among ultrasound images taken from different angles is used. Feature selection using combination of sequential backward search, sequential forward search and distance-based methods is obtained. A new segmentation method based on automatic selection of seed points and region growing is proposed and classification of lesions into two malignant and benign classes using combination of AdaBoost, Artificial Neural Network and Fuzzy Support Vector Machine classifiers and majority voting is implemented.

Accès libre

Dimensionality Reduction of Dynamic Mesh Animations Using HO-SVD

Publié en ligne: 30 Dec 2014
Pages: 277 - 289

Résumé

Abstract

This work presents an analysis of Higher Order Singular Value Decomposition (HOSVD) applied to reduction of dimensionality of 3D mesh animations. Compression error is measured using three metrics (MSE, Hausdorff, MSDM). Results are compared with a method based on Principal Component Analysis (PCA) and presented on a set of animations with typical mesh deformations.

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