Genetic algorithm for the efficient selection of disyllabic word lists used in Mandarin speech discrimination tests

2005 ◽  
Vol 43 (5) ◽  
pp. 648-657 ◽  
Author(s):  
P. -C. Li ◽  
Y. -Y. Chiang ◽  
K. -S. Tsai ◽  
S. -T. Young
Keyword(s):  
Genetic Algorithm ◽  
Speech Discrimination ◽  
Speech Discrimination Tests ◽  
Word Lists ◽  
Disyllabic Word ◽  
Efficient Selection ◽  
Selection Of

A Comparison of the NU-6 and W-22 Speech Discrimination Tests for Assessing Sensorineural Hearing Loss

1979 ◽  
Vol 44 (4) ◽  
pp. 522-527 ◽  
Author(s):  
Daniel J. Orchik ◽  
Karen M. Krygier ◽  
Betty P. Cutts
Keyword(s):  
Hearing Loss ◽  
Sensorineural Hearing Loss ◽  
Sensorineural Hearing ◽  
Clinical Use ◽  
Speech Discrimination ◽  
Sensation Level ◽  
Speech Discrimination Tests ◽  
Word Lists

The Auditec recordings of the CID W-22 and NU-6 word lists were administered to 30 adults having sensorineural hearing losses. Speech discrimination scores for both tests were obtained at 16, 24, and 32 dB sensation level. Results suggest that both tests differentiate sensorineural-impaired subjects from normal listeners, although scores were significantly better for the W-22 word lists at all sensation levels. Implications for the clinical use of these measures are discussed.

Feature selection of the armature winding broken coils in synchronous motor using genetic algorithm and mahalanobis distance

2012 ◽  
Vol 57 (3) ◽  
pp. 829-835 ◽  
Author(s):  
Z. Głowacz ◽  
J. Kozik
Keyword(s):  
Genetic Algorithm ◽  
Feature Selection ◽  
Mahalanobis Distance ◽  
Distance Measure ◽  
Synchronous Motor ◽  
Medical Diagnostics ◽  
Motor Current ◽  
Feature Spaces ◽  
Multidimensional Feature Spaces ◽  
Selection Of

The paper describes a procedure for automatic selection of symptoms accompanying the break in the synchronous motor armature winding coils. This procedure, called the feature selection, leads to choosing from a full set of features describing the problem, such a subset that would allow the best distinguishing between healthy and damaged states. As the features the spectra components amplitudes of the motor current signals were used. The full spectra of current signals are considered as the multidimensional feature spaces and their subspaces are tested. Particular subspaces are chosen with the aid of genetic algorithm and their goodness is tested using Mahalanobis distance measure. The algorithm searches for such a subspaces for which this distance is the greatest. The algorithm is very efficient and, as it was confirmed by research, leads to good results. The proposed technique is successfully applied in many other fields of science and technology, including medical diagnostics.

scholarly journals Selection of Scholarship Recipient by Implementing Genetic Algorithm and Fuzzy Logic

2021 ◽  
Vol 1933 (1) ◽  
pp. 012069
Author(s):  
Yohanssen Pratama ◽  
Monalisa Pasaribu ◽  
Joni Nababan ◽  
Dayani Sihombing ◽  
Dicky Gultom
Keyword(s):  
Genetic Algorithm ◽  
Fuzzy Logic ◽  
Selection Of

scholarly journals Network Analysis Based on Unique Spectral Features Enables an Efficient Selection of Genomically Diverse Operational Isolation Units

2021 ◽  
Vol 9 (2) ◽  
pp. 416
Author(s):  
Charles Dumolin ◽  
Charlotte Peeters ◽  
Evelien De Canck ◽  
Nico Boon ◽  
Peter Vandamme
Keyword(s):  
Network Analysis ◽  
Hierarchical Clustering ◽  
Mass Spectra ◽  
Spectral Features ◽  
Maldi Tof ◽  
Maldi Tof Mass Spectra ◽  
Diversity Studies ◽  
Technical Sample ◽  
Efficient Selection ◽  
Selection Of

Culturomics-based bacterial diversity studies benefit from the implementation of MALDI-TOF MS to remove genomically redundant isolates from isolate collections. We previously introduced SPeDE, a novel tool designed to dereplicate spectral datasets at an infraspecific level into operational isolation units (OIUs) based on unique spectral features. However, biological and technical variation may result in methodology-induced differences in MALDI-TOF mass spectra and hence provoke the detection of genomically redundant OIUs. In the present study, we used three datasets to analyze to which extent hierarchical clustering and network analysis allowed to eliminate redundant OIUs obtained through biological and technical sample variation and to describe the diversity within a set of spectra obtained from 134 unknown soil isolates. Overall, network analysis based on unique spectral features in MALDI-TOF mass spectra enabled a superior selection of genomically diverse OIUs compared to hierarchical clustering analysis and provided a better understanding of the inter-OIU relationships.

Efficient selection of feature sets possessing high coefficients of determination based on incremental determinations

2003 ◽  
Vol 83 (4) ◽  
pp. 695-712 ◽  
Author(s):  
Ronaldo F. Hashimoto ◽  
Edward.R. Dougherty ◽  
Marcel Brun ◽  
Zheng-Zheng Zhou ◽  
Michael L. Bittner ◽  
...  
Keyword(s):  
Feature Sets ◽  
Efficient Selection ◽  
Selection Of
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