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3 Bio-Algorithms and Med-Systems

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Speaker identification based on artificial neural networks. Case study: the Polish vowel (pilot study)

Salapa K., Trawińska A., Roterman I., Tadeusiewicz R.

Bio-Algorithms and Med-Systems

2014

Vol. 10, no. 2

91--99

Current statistical methods and technologies used for speaker identification via dynamic formant frequency often involve classic multivariate analyses that must meet a number of criteria in order to be considered trustworthy. The authors propose more advanced classification techniques, including artificial neural networks. Owing to iterative learning algorithms, neural networks can be trained to detect highly complex, nonlinear relations hidden in input data. This study specifically considers feed-forward multilayer perceptron and radial basic function network models. The investigation involves an analysis of the Polish vowel (stressed or unstressed) in selected contexts described by the four lowest formant frequencies. Results indicate high accuracy of neural networks as a speaker identification tool reaching up to 100%. In addition, the authors have determined that the accuracy of classification is similar when based on a single context to when input data are aggregated over several different contexts.

Ab initio protein structure prediction – the hydrophobicity distribution analysis

Evangelista G., Minervini G., Polticelli F, Malawski M., Szepieniec T., Flis Ł., Prymula K., Kochańczyk M., Matczyńska E., Wiśniowski Z., Salapa K., Banach M., Roterman I.

Bio-Algorithms and Med-Systems

2011

Vol. 7, no. 2

5--12

The three-dimensional structures generated for 20 “never born proteins” (NBP – random amino acid sequence with no significant homology to existing proteins) using two different techniques: ROSETTA (called R in the paper) and “fuzzy oil drop” model (called S in the paper) were compared to estimate the accordance with the assumed model estimating the influence of an external force field on the final structure of the protein. Selected structures are those corresponding to the highest (10 proteins) and lowest (10 proteins) RMS-D values obtained measuring the similarity between the R and S structures. The R structures generated according to an internal force field (the individual inter-molecular interaction) including solvation effects were analyzed using the “fuzzy oil drop” model as target model. The second applied model “fuzzy oil drop” generated structures characterized by an ordered hydrophobic core structure. 13 of the 20 selected S structures appeared to be accordant with the “fuzzy oil drop” model while 6 out of the 20 structures appeared to be accordant with external force field for R structures which suggests a general interpretation of the influence of an external force field on the folding simulation.

Statistical pathways - a method of visualization statistical rules

Salapa K., Stanisz A.

Bio-Algorithms and Med-Systems

2009

Vol. 5, no. 9

127--131

The aim of this article is the application of flow charts in teaching statistics. It contains three exemplary diagrams concerning the most common tests such as independent one-sample, two-sample t-test and one-way analysis of variance. They present particular steps in process of selection the most relevant test. Hypothesis testing is a powerful tool in science because of the potential to explain causality. Unfortunately students have difficulties in recognition the correct test. Such diagrams could facilitate the understanding and studying statistical rules. All flowcharts presented in this paper have been prepared using the authoring tool called BIT Pathways.