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Dnipropetrovsk, Ukraine

The National Mining University , colloquially known in Ukrainian as NGU is located in Dnipropetrovsk, the third most populous city in Ukraine. It was founded in 1899 as the Yekaterinoslav Higher Mining School. The task of the university then was to provide the mining industry with highly qualified specialists, a goal that has continued to direct the university's leadership right up to the present day, although in recent years its academic offer has developed beyond the confines of mining-related subjects. Currently, its structure consists of nine faculties . During the Soviet era, NGU was one of the country's top specialised institutions of higher education. It is ranked as one of Ukraine's best universities in many rankings and today attracts a large number of foreign students.The National Mining University is one of the leading establishments of higher education in Ukraine. According to the ratings of UNESCO it achieved 6th position among the 200 Top universities in Ukraine in 2009. Wikipedia.


Korkhin A.S.,National Mining University
Cybernetics and Systems Analysis | Year: 2013

The paper considers the methods to evaluate regression parameters under indefinite a priori information of two types: fuzzy and stochastic. Fuzzy a priori information is assumed to be formulated on the basis of fuzzy notions of the model designer. Stochastic a priori information is systems of equations, which are linear in regression parameters and whose right-hand sides are random variables. Regression parameters may both be constant and vary in time. A classification of the evaluation methods using indefinite a priori information is proposed and used to generalize well-known methods. An evaluation method is developed, which combines the fuzzy and stochastic a priori information about regression parameters. © 2013 Springer Science+Business Media New York.


Pivovarova I.,National Mining University
Journal of Engineering and Applied Sciences | Year: 2014

In this study, the method of estimating the spatial uniformity of hydrological characteristics and the subsequent zoning of the studied territory by means of GIS applications are described. A new algorithm is proposed for estimating the uniformity of spatially distributed data depending on the differentiation of spatial-correlation functions of the studied characteristics. Mathematical calculation algorithm was implemented using object-oriented C++programming language. Prospects of researches in the creation of information model of the territory, reflecting the spatial structure, the status and relationships between its separate elements with the purpose of optimization of nature management and making decisions about the management of natural objects are outlined. © Medwell Journals, 2014.


Kolluru B.,National Mining University
Journal of integrative bioinformatics | Year: 2011

In this paper we illustrate the usage of text mining workflows to automatically extract instances of microorganisms and their habitats from free text; these entries can then be curated and added to different databases. To this end, we use a Conditional Random Field (CRF) based classifier, as part of the workflows, to extract the mention of microorganisms, habitats and the inter-relation between organisms and their habitats. Results indicate a good performance for extraction of microorganisms and the relation extraction aspects of the task (with a precision of over 80%), while habitat recognition is only moderate (a precision of about 65%). We also conjecture that pdf-to-text conversion can be quite noisy and this implicitly affects any sentence-based relation extraction algorithms.


Lubenets M.O.,National Mining University
Naukovyi Visnyk Natsionalnoho Hirnychoho Universytetu | Year: 2016

Purpose: Experimental determination of the dependence of the force and the coefficient of friction of the flexible body on the normal reaction between bodies while sliding over the fixed block. Methodology: The frictional properties of the friction pair "flexible body-block" was determined by means of the test bench with different forces applied to the ends of the flexible body. Then according to Euler's Solution the experimental dependence of the force and the friction coefficient on the normal reaction between the bodies was developed and compared with the accumulated data of the theory and practice. Findings: Experimental dependence of the force and the coefficient of friction of the flexible body on the normal reaction between bodies while sliding over the fixed block was established. Originality: For the first time, the two-parameter linear dependence of the friction force and inversely proportional dependence of the coefficient of friction of the flexible body on the normal reaction between bodies while sliding over the fixed block were obtained experimentally. This corresponds to Coulomb's law of friction between two solid bodies, new solution of Euler's classical problem of flexible body sliding over the fixed block, and practice data. Practical value: Research results can be used in mechanical engineering while designing and operating transport vehicles with a flexible traction body as well as in research and education. © Lubenets M.O., 2016.


Nawaz R.,National Mining University
BMC bioinformatics | Year: 2013

Negation occurs frequently in scientific literature, especially in biomedical literature. It has previously been reported that around 13% of sentences found in biomedical research articles contain negation. Historically, the main motivation for identifying negated events has been to ensure their exclusion from lists of extracted interactions. However, recently, there has been a growing interest in negative results, which has resulted in negation detection being identified as a key challenge in biomedical relation extraction. In this article, we focus on the problem of identifying negated bio-events, given gold standard event annotations. We have conducted a detailed analysis of three open access bio-event corpora containing negation information (i.e., GENIA Event, BioInfer and BioNLP'09 ST), and have identified the main types of negated bio-events. We have analysed the key aspects of a machine learning solution to the problem of detecting negated events, including selection of negation cues, feature engineering and the choice of learning algorithm. Combining the best solutions for each aspect of the problem, we propose a novel framework for the identification of negated bio-events. We have evaluated our system on each of the three open access corpora mentioned above. The performance of the system significantly surpasses the best results previously reported on the BioNLP'09 ST corpus, and achieves even better results on the GENIA Event and BioInfer corpora, both of which contain more varied and complex events. Recently, in the field of biomedical text mining, the development and enhancement of event-based systems has received significant interest. The ability to identify negated events is a key performance element for these systems. We have conducted the first detailed study on the analysis and identification of negated bio-events. Our proposed framework can be integrated with state-of-the-art event extraction systems. The resulting systems will be able to extract bio-events with attached polarities from textual documents, which can serve as the foundation for more elaborate systems that are able to detect mutually contradicting bio-events.

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