Кафедра "Комп'ютерна інженерія та програмування"

Постійне посилання колекціїhttps://repository.kpi.kharkov.ua/handle/KhPI-Press/1095

Офіційний сайт кафедри https://web.kpi.kharkov.ua/cep

Від 26 листопада 2021 року кафедра має назву – "Комп’ютерна інженерія та програмування"; попередні назви – “Обчислювальна техніка та програмування”, “Електронні обчислювальні машини”, первісна назва – кафедра “Математичні та лічильно-вирішальні прилади та пристрої”.

Кафедра “Математичні та лічильно-вирішальні прилади та пристрої” заснована 1 вересня 1961 року. Організатором та її першим завідувачем був професор Віктор Георгійович Васильєв.

Кафедра входить до складу Навчально-наукового інституту комп'ютерних наук та інформаційних технологій Національного технічного університету "Харківський політехнічний інститут". Перший випуск – 24 інженери, підготовлених кафедрою, відбувся в 1964 році. З тих пір кафедрою підготовлено понад 4 тисячі фахівців, зокрема близько 500 для 50 країн світу.

У складі науково-педагогічного колективу кафедри працюють: 11 докторів технічних наук, 21 кандидат технічних наук, 1 – економічних, 1 – фізико-математичних, 1 – педагогічних, 1 доктор філософії; 9 співробітників мають звання професора, 14 – доцента, 2 – старшого наукового співробітника.

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Methodological instructions for practical work on the course "Signal and Image Processing"
(Національний технічний університет "Харківський політехнічний інститут", 2024) Povoroznyuk, O. A.; Filatova, A. E.
This edition provides methodological instructions for practical works 1-9, which include mathematical basics of signal processing (Fourier transforms, convolutions, z-transform) and image processing (twodimensional Fourier transform, element-by-element transforms, digital filtering and wavelet transforms). Theoretical information and calculations are accompanied by examples. Intended for students of all undergraduate majors in Computer Engineering 123.
Developing an informational model of instrumental examination
(2019) Filatova, A. E.; Povoroznyuk, A. I.; Gavrylenko, Svitlana; Fahs, Mohamad
This document presents the development of an informational model of instrumental examination of a patient using the data flow diagrams (DFD). The developed informational model of the instrumental examination is presented in the form of a context diagram, its decomposition, and the decomposition of the subsystems «Registration and analysis of biomedical signals and images with locally concentrated features» and «Diagnostics». Taking into account the proposed information model, UML diagrams of the activity of the biomedical decision support system based on morphological analysis of biomedical signals and images with locally concentrated features, of the module for morphological analysis of an electrocardiogram, and of the module for improving the quality of visualization of biological objects on radiological images based on the IMRI method are developed.
Web-application ''online-diagnost''
(ФОП Тарасенко В. П., 2020) Makhsudov, Fazliddin; Filatova, A. E.
Evaluating the Effectiveness of Electrocardiological Study Using Cardiological Decision Support Systems
(2020) Filatova, A. E.; Skarga-Bandurova, Inna; Brezhniev, Eugene; Fahs, Mohamad
This work is devoted to evaluating the effectiveness of the electrocardiological study process without using and using cardiological decision support systems. To assess the effectiveness, analytical expressions of the probabilistic-time characteristics of the developed structural model of the electrocardiological study process are used. An analysis of the time characteristics of the model is performed when different initial conditions are set for three different types of electrocardiological studies: the study is conducted for the first time, the study is repeated as a result of screening, the study is repeated after treatment. The work shows that the use of cardiological decision support systems based on the developed methods for analyzing biomedical signals with locally concentrated features reduced the average time required for the electrocardiological study of each of the considered types.
Method of automatic determination of the heart’s electrical axis in cardiological decision support systems
(Одеський національний політехнічний університет, 2021) Filatova, A. E.; Fahs, Mohamad
The work is devoted to solving the scientific and practical problem of automating the heart’s electrical axis calculation to im-prove the quality of morphological analysis of biomedical signals with locally concentrated features in cardiological decision support systems, which in turn reduces the likelihood of medical errors. The work shows that existing methods for in the determining the electrical axis of the heart require morphological analysis of an electrocardiogram. The method is based on determining the integral signal in the frontal plane from all limb leads, taking into account the lead angle in the hexaxial reference system. In graphic form in polar coordinates, the integral electrocardiological signal is a figure, predominantly elongated along the axis, the direction’n of which corresponds to the heart’s electrical axis. The position of the heart’s electrical axis is calculated as the angle between the axis of standard lead I and the vector, the end of which is at the center of mass of the locus of the points the farthest away from the reference point. Cluster analysis is used to find the most distant points from the reference point. The proposed method for of calculating the heart’s electrical axis makes it possible not to carry out a preliminary morphological analysis of an electrocardiogram. To implement the method proposed in the article, a program was written in the Matlab language, which is connected as a dynamic link library to the cardiological decision support system “TREDEX telephone” operating as part of the medical diagnostic complex “TREDEX” manu-factured by “Company TREDEX” LLC, Kharkiv. Verification of the results was carried out using a database of electrocardiograms, which were recorded using a transtelephone digital 12-channel electrocardiological complex “Telecard”, which is part of the medical diagnostic complex “TREDEX”, and deciphered by cardiologists of the communal non-profit enterprise of the Kharkiv Regional Council “Center for Emergency Medical aid and disaster medicine”. Comparison of the results of calculating the heart’s electrical axis according to electrocardiograms by a doctor and automatically using the proposed method showed that in the overwhelming majority of cases the decisions made coincide. At the same time, cardiologists make mistakes, and errors are made during automatic calculation using the proposed method. The paper explains the reasons for these errors.
Application of probabilistic-time graphs for evaluating the effectiveness of the electrocardiological study process
(Одеський національний політехнічний університет, 2020) Filatova, A. E.; Povoroznyuk, A. I.; Fahs, Mohamad
This work is devoted to the development of a structural model of the patient’s electrocardiological study process based on graph theory, probability theory and the method of generating functions. The developed structural model is presented in the form of a probabilistic-time graph, in which nine main states and an uncertainty state (a set of states that do not lead to the goal) are identified, as well as the probabilistic-time characteristics of the arcs of transitions from one graph state to another. The following are identified as the main states characterizing the process to complete an electrocardiological study: the beginning of the study; indications were defined; morphological analysis of biomedical signals with locally concentrated features was performed; pathological changes were identified; comparison with previous electrocardiological studies was performed; dynamics evaluation was completed; evaluation of treatment effectiveness was completed; diagnostic decision was made; recommendations were issued (the end of the electrocardiological study). For the proposed model of the electrocardiological study process by the Mason method, there are obtained analytical expressions for the generating functions of the entire graph, as well as the part of the graph that characterizes the successful completion of the electrocardiological study. Using the indicated generating functions, analytical expressions were obtained to calculate the average transit time of an electrocardiological study and the probability of successful completion of this process. To get all analytic expressions, a program was written in the Matlab language. The developed structural model of an electrocardiological study in the form of a probabilistic-time graph made it possible to identify the main states and determine the criteria for the effectiveness of the process in terms of average time and the probability of a successful study.
Development of alternative diagnostic feature system in the cardiology decision support systems
(Технологический центр, 2016) Povoroznyuk, A. I.; Filatova, A. E.
The trend towards an increase in the production of Ukrainian digital electrocardiographic telemetry systems such as transtelephonic digital 12-channel electrocardiograph complex "Telecard" identified the need to create intelligent automated cardiac decision support systems. The basis of these systems is the morphologic analysis of electrocardiograms, which represent biomedical signals with locally concentrated features. The system of alternative diagnostic features based on the method proposed by the authors of the morphological analysis of biomedical signals with locally concentrated features to provide additional graphical information in the diagnosis of one of the most common cardiac arrhythmias - ventricular arrhythmia is developed. Representation of the electrocardiogram in two-dimensional space of alternative features, as well as hodograph is proposed. Differences between the ECG-hodographs for normal ECG and ECG with different arrhythmias of right and left ventricles, as well as multifocal ventricular arrhythmia are analyzed. It was found that a graphical representation of an electrocardiogram in the alternative feature space allows the physician to visually perform the classification of different types of ventricular arrhythmia, which in combination with the classical analysis of ECG on the time axis increases the reliability of diagnostics.
Research and automation of restaurant business
(Національний технічний університет "Харківський політехнічний інститут", 2017) Kurinnyi, R. I.; Filatova, A. E.
Design of non-linear filter in the problem of structural identification of biomedical signals with locally concentrated properties
(2013) Povoroznyuk, A. I.; Filatova, A. E.; Myrgorod, Yuri
In this paper we propose a generalized method of structural identification of biomedical signals with locally concentrated properties using a digital non-linear filter. The experimental verification of the detecting function was performed by using different ways to describe the model of the desired class of structural elements.
Development of method of matched morphological filtering of biomedical signals and images
(Allerton Press, 2019) Povoroznyuk, A. I.; Filatova, A. E.; Zakovorotniy, A. Yu.; Shehna, Kh.
Formalized approach to the analysis of biomedical signals and images with locally concentrated features is developed on the basis of matched morphological filtering taking into account the useful signal models that allowed generalizing the existing methods of digital processing and analysis of biomedical signals and images with locally concentrated features. The proposed matched morphological filter has been adapted to solve such problems as localization of the searched structural elements on biomedical signals with locally concentrated features, estimation of the irregular background aimed at the visualization quality improving of biological objects on X-ray biomedical images, pathologic structures selection on mammogram. The efficiency of the proposed methods of matched morphological filtration of biomedical signals and images with locally concentrated features is proved by experiments.