Zeszyty czasopisma

Tom 12 (2022): Zeszyt 3 (July 2022)

Tom 12 (2022): Zeszyt 2 (April 2022)

Tom 12 (2022): Zeszyt 1 (January 2022)

Tom 11 (2021): Zeszyt 4 (October 2021)

Tom 11 (2021): Zeszyt 3 (July 2021)

Tom 11 (2021): Zeszyt 2 (April 2021)

Tom 11 (2021): Zeszyt 1 (January 2021)

Tom 10 (2020): Zeszyt 4 (October 2020)

Tom 10 (2020): Zeszyt 3 (July 2020)

Tom 10 (2020): Zeszyt 2 (April 2020)

Tom 10 (2020): Zeszyt 1 (January 2020)

Tom 9 (2019): Zeszyt 4 (October 2019)

Tom 9 (2019): Zeszyt 3 (July 2019)

Tom 9 (2019): Zeszyt 2 (April 2019)

Tom 9 (2019): Zeszyt 1 (January 2019)

Tom 8 (2018): Zeszyt 4 (October 2018)

Tom 8 (2018): Zeszyt 3 (July 2018)

Tom 8 (2018): Zeszyt 2 (April 2018)

Tom 8 (2018): Zeszyt 1 (January 2018)

Tom 7 (2017): Zeszyt 4 (October 2017)

Tom 7 (2017): Zeszyt 3 (July 2017)

Tom 7 (2017): Zeszyt 2 (April 2017)

Tom 7 (2017): Zeszyt 1 (January 2017)

Tom 6 (2016): Zeszyt 4 (October 2016)

Tom 6 (2016): Zeszyt 3 (July 2016)

Tom 6 (2016): Zeszyt 2 (April 2016)

Tom 6 (2016): Zeszyt 1 (January 2016)

Tom 5 (2015): Zeszyt 4 (October 2015)

Tom 5 (2015): Zeszyt 3 (July 2015)

Tom 5 (2015): Zeszyt 2 (April 2015)

Tom 5 (2015): Zeszyt 1 (January 2015)

Tom 4 (2014): Zeszyt 4 (October 2014)

Tom 4 (2014): Zeszyt 3 (July 2014)

Tom 4 (2014): Zeszyt 2 (April 2014)

Tom 4 (2014): Zeszyt 1 (January 2014)

Tom 3 (2013): Zeszyt 4 (October 2013)

Tom 3 (2013): Zeszyt 3 (July 2013)

Tom 3 (2013): Zeszyt 2 (April 2013)

Tom 3 (2013): Zeszyt 1 (January 2013)

Informacje o czasopiśmie
Format
Czasopismo
eISSN
2449-6499
Pierwsze wydanie
30 Dec 2014
Częstotliwość wydawania
4 razy w roku
Języki
Angielski

Wyszukiwanie

Tom 3 (2013): Zeszyt 4 (October 2013)

Informacje o czasopiśmie
Format
Czasopismo
eISSN
2449-6499
Pierwsze wydanie
30 Dec 2014
Częstotliwość wydawania
4 razy w roku
Języki
Angielski

Wyszukiwanie

5 Artykułów
Otwarty dostęp

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

Data publikacji: 30 Dec 2014
Zakres stron: 229 - 242

Abstrakt

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.

Otwarty dostęp

Application of Artificial Neural Network and Genetic Algorithm to Healthcarewaste Prediction

Data publikacji: 30 Dec 2014
Zakres stron: 243 - 250

Abstrakt

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.

Otwarty dostęp

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

Data publikacji: 30 Dec 2014
Zakres stron: 251 - 263

Abstrakt

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.

Otwarty dostęp

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

Data publikacji: 30 Dec 2014
Zakres stron: 265 - 276

Abstrakt

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.

Otwarty dostęp

Dimensionality Reduction of Dynamic Mesh Animations Using HO-SVD

Data publikacji: 30 Dec 2014
Zakres stron: 277 - 289

Abstrakt

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 Artykułów
Otwarty dostęp

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

Data publikacji: 30 Dec 2014
Zakres stron: 229 - 242

Abstrakt

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.

Otwarty dostęp

Application of Artificial Neural Network and Genetic Algorithm to Healthcarewaste Prediction

Data publikacji: 30 Dec 2014
Zakres stron: 243 - 250

Abstrakt

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.

Otwarty dostęp

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

Data publikacji: 30 Dec 2014
Zakres stron: 251 - 263

Abstrakt

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.

Otwarty dostęp

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

Data publikacji: 30 Dec 2014
Zakres stron: 265 - 276

Abstrakt

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.

Otwarty dostęp

Dimensionality Reduction of Dynamic Mesh Animations Using HO-SVD

Data publikacji: 30 Dec 2014
Zakres stron: 277 - 289

Abstrakt

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.

Zaplanuj zdalną konferencję ze Sciendo