International Journal on Soft Computing ( IJSC ): September 2022

Microarray is a useful technique for measuring expression data of thousands or more of genes simultaneously. One of challenges in classification of cancer using high-dimensional gene expression data is to select a minimal number of relevant genes which can maximize classification accuracy. Because of the distinct characteristics inherent to specific cancerous gene expression profiles, developing flexible and robust gene identification methods is extremely fundamental. Many gene selection methods as well as their corresponding classifiers have been proposed. In the proposed method, a single gene with high classdiscrimination capability is selected and classification rules are generated for cancer based on gene expression profiles. The method first computes importance factor of each gene of experimental cancer dataset by counting number of linguistic terms (defined in terms of different discreet quantity) with high class discrimination capability according to their depended degree of classes. Then initial important genes are selected according to high importance factor of each gene and form initial reduct. Then traditional kmeans clustering algorithm is applied on each selected gene of initial reduct and compute missclassification errors of individual genes. The final reduct is formed by selecting most important genes with respect to less miss-classification errors. Then a classifier is constructed based on decision rules induced by selected important genes (single) from training dataset to classify cancerous and non-cancerous samples of experimental test dataset. The proposed method test on four publicly available cancerous gene expression test dataset. In most of cases, accurate classifications outcomes are obtained by just using important (single) genes that are highly correlated with the pathogenesis cancer are identified. Also to prove the robustness of proposed method compares the outcomes (correctly classified instances) with some existing well known classifiers.

KEYWORDS

Microarray cancer data, K-means algorithm, Gene selection, Classification Rule, Cancer sample identification, Gene reducts.

Original Source URL: https://airccse.org/journal/ijsc/papers/3312ijsc06.pdf

https://airccse.org/journal/ijsc/current2012.html

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Submission System: http://coneco2009.com/submissions/imagination/home.html

Monday, 19 September 2022

Submit Your Research Articles...!!! November Issue!!!

International Journal on Soft Computing ( IJSC )

ISSN: 2229 - 6735 [Online] ; 2229 - 7103 [Print]

https://airccse.org/journal/ijsc/ijsc.html

Submission Deadline : October 01, 2022

Paper Submission URL - http://coneco2009.com/submissions/imagination/home.html

#softcomputing #chaostheory #bioinformatics #robotics #machinelearning #FuzzyLogic

Friday, 16 September 2022

Current Issue

August 2022, Volume 13, Number 3

Introduction of a Novel Anomalous Sound Detection Methodology

Xiao Tan and S M Yiu, University of Hong Kong, Hong Kong

ABSTRACT

This paper is to introduce a novel semi-supervised methodology, the enhanced incremental principal component analysis (“IPCA”) based deep convolutional neural network autoencoder (“DCNN-AE) for Anomalous Sound Detection (“ASD”) with high accuracy and computing efficiency. This hybrid methodology is to adopt Enhanced IPCA to reduce the dimensionality and then to use DCNN-AE to extract the features of the sample sound and detect the anomality. In this project, 228 sets of normal sounds and 100 sets of anomaly sounds of same machine are used for the experiments. And the sound files of machines (stepper motors) for the experiments are collected from a plant site. 50 random test cases are executed to evaluate the performance of the algorithm with AUC, PAUC, F measure and Accuracy Score. IPCA Based DCNN-AE shows high accuracy with the average AUC of 0.815793282, comparing with that of Kmeans++ of 0.499545351, of Incremental PCA based DBSCAN clustering of 0.636348073, of Incremental based PCA based One-class SVM of 0.506749433 and of DCGAN of 0.716528104. From the perspective of computing efficiency, because of the dimensions-reduction by the IPCA layer, the average execution time of the new methodology is 15 minutes in the CPU computing module of 2.3 GHz quad-core processors, comparing with that of DCGAN with 90 minutes in GPU computing module of 4 to 8 kernels.

KEYWORDS

Internet of things (“IoT”), Anomalous Sound Detection (“ASD”), Audio Frames, Deep learning, Deep Convolutional Neural Network, Autoencoder.

Original Source URL: https://aircconline.com/ijsc/V13N3/13322ijsc01.pdf

https://airccse.org/journal/ijsc/current2022.html

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ijscjournal@yahoo.com or ijsc@aircconline.com

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Thursday, 15 September 2022

12th International Conference on Artificial Intelligence, Soft Computing and Applications (AIAA 2022)

December 23 ~ 24, 2022, Sydney, Australia

Webpage URL: https://cndc2022.org/aiaa/index

Submission Deadline: September 17, 2022

Here's where you can reach us: aiaa@cndc2022.org (or) aiaaconference@yahoo.com

Submission URL:

https://cndc2022.org/submission/index.php

Wednesday, 14 September 2022

Submit Your Research Articles...!!! November Issue!!!

International Journal on Soft Computing ( IJSC )

ISSN: 2229 - 6735 [Online] ; 2229 - 7103 [Print]

https://airccse.org/journal/ijsc/ijsc.html

Submission Deadline: September 18, 2022

Wikicfp: http://wikicfp.com/cfp/servlet/event.showcfp?eventid=145683

Paper Submission URL - http://coneco2009.com/submissions/imagination/home.html

#softcomputing #chaostheory #bioinformatics #robotics #machinelearning #FuzzyLogic

Monday, 12 September 2022

Call for Papers...!!!

International Journal on Soft Computing (IJSC)

ISSN: 2229 - 6735 [Online]; 2229 - 7103 [Print]

https://airccse.org/journal/ijsc/ijsc.html

Submission Deadline: September 18, 2022

Contact Us
Here's where you can reach us: ijscjournal@yahoo.com or ijsc@aircconline.com 

Submission System 
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#softcomputing #neuralnetworks #FuzzyLogic #wavelet #nanotechnology #Machinelearning #chaostheory #bioinformatics

Friday, 9 September 2022

Call for Research Papers!

3rd International Conference on Machine Learning Techniques and NLP (MLNLP 2022)

September 24 ~ 25, 2022, Toronto, Canada

https://csity2022.org/mlnlp/index

Submission Deadline: September 10, 2022(Final Call)

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mlnlp@csity2022.org or mlnlpconference@yahoo.com

Submission System: https://csity2022.org/submission/index.php

#NLP #machinelearning #ontology #SemanticWeb #informationretrival #AI

Tuesday, 6 September 2022