Kherson National Technical University

About: Kherson National Technical University is a education organization based out in Kherson, Ukraine. It is known for research contribution in the topics: Decision support system & Cluster analysis. The organization has 263 authors who have published 263 publications receiving 812 citations.

An Evaluation of the Information Technology of Gene Expression Profiles Processing Stability for Different Levels of Noise Components

Abstract: This paper presents the results of research concerning the evaluation of stability of information technology of gene expression profiles processing with the use of gene expression profiles, which contain different levels of noise components. The information technology is presented as a structural block-chart, which contains all stages of the studied data processing. The hybrid model of objective clustering based on the SOTA algorithm and the technology of gene regulatory networks reconstruction have been investigated to evaluate the stability to the level of the noise components. The results of the simulation have shown that the hybrid model of the objective clustering has high level of stability to noise components and vice versa, the technology of gene regulatory networks reconstruction is rather sensitive to the level of noise component. The obtained results indicate the importance of gene expression profiles preprocessing at the early stage of the gene regulatory network reconstruction in order to remove background noise and non-informative genes in terms of the used criteria.

Forest Fire-Fighting Monitoring System Based on UAV Team and Remote Sensing

Abstract: This work presents a monitoring system for tactical forest fire-fighting operations based on a team of unmanned aerial vehicles and remote sensing techniques. Functions and missions of the system, as well as its architecture, are considered. Image processing and remote sensing algorithms are presented, a way for data integration into a fire-spreading model in a real-time forest fire response decision support system is proposed. The combination of automatic monitoring and remote sensing techniques with an approximate fire-spreading model can provide required credibility and efficiency of fire prediction and response.

Criterial analysis of gene expression sequences to create the objective clustering inductive technology

Abstract: The paper presents the researches to determine the effectiveness of different criteria to estimate the complex biology objects clustering quality. The gene expression sequences of cancer patients were used as experimental data. The degree of the studied objects similarity was estimated by the comparison of the gene expression sequences profile using different metrics to estimate the objects proximity. The studies have shown that the best separating ability is obtained by using the correlation metric proximity of objects. Herewith the use of the CH criterion (Calinski-Harabasz) allows to get the most objective objects clustering by using simulated data. The presented research is focused mainly on the inductive model of the objective clustering, where the objects clustering is carried out concurrently on the two equal power subsets. In this case, the final decision about the objects grouping is accepted using the two subsets basing both on the internal clustering quality criteria estimating and the minimum value of the external criterion of clustering similarity.

A Fuzzy Model for Gene Expression Profiles Reducing Based on the Complex Use of Statistical Criteria and Shannon Entropy

Abstract: The paper presents the technology of gene expression profiles reducing based on the complex use of fuzzy logic methods, statistical criteria and Shannon entropy. Simulation of the reducing process has been performed with the use of gene expression profiles of lung cancer patients. The variance and the average absolute value were changed within the defined range from the minimum to the maximum value, and Shannon entropy from the maximum to the minimum value during the simulation process. 311 gene expression profiles from 7129 were removed as non-informativity during simulation process. The structural block diagram of the step-by-step data processing in order to remove non-informativity gene expression profiles has been proposed as the simulation results.

Objective Clustering Inductive Technology of Gene Expression Sequences Features

Abstract: Technology of high dimensional data features objective clustering based on the methods of complex systems inductive modeling is presented in the paper. Architecture of the objective clustering inductive technology as a block diagram of step-by-step implementation of the objects clustering procedure was developed. Method of criterial evaluation of complex data clustering results using two equal power data subsets is proposed. Degree of clustering objectivity evaluates on the basis of complex use of internal and external criteria. Researches on the simulation results of the proposed technology based on the SOTA self-organizing clustering algorithm using the gene expression data obtained by DNA microarray analysis of patients with lung cancer GEOD-68571 Array Express database, the datasets “Compound” and “Aggregation” of the Computing School of the Eastern Finland University and the data “seeds” are presented.