Decision support methods are developed for the problems in applied optics in which it is necessary to make decisions about image quality and its compliance with the requirements that are determined by its further use. The choice of the calibrated theoretical image on which correctness of carrying out of settlement work is checked is discussed. An algorithm according to which the obtained numerical image is improved is given. The paper identifies the disadvantages of machine vision systems, such as defects in system elements, system debugging, noise, unsuccessful experimental scheme that reduce the quality of the experimental image. To establish the relationship between the causes and consequences of defects, a table with the causes of the defects formation in the diffraction pattern according to the scheme of Ishikawa is builded. The quality and ways to improve the experimental image are established using a Pareto diagram. Improvement occurs iteratively and allows to improve gradually the image quality to the maximum possible value in the experimental scheme. Two stages of decision-making are introduced - the first determines the perfection of the experimental image, and the second its acceptability as the main result of the work according to experts’ opinion. The completeness of the alternatives in the analysis is given by the recommendations for further action, and the magnitude of the error due to a combination of two methods: Pareto diagram and experts opinion does not exceed 5 %.

The creation of a very heat resistant cover for returnable orbiters and for hypersonic flying aircrafts is an actual problem in modern science and technics. Therefore, computer modelling and investigations molecular structure of various multicomponent compounds are important tasks. In the paper, based on the computer model the molecular structure and a very heat resistant of carbonitride hafnium Hf6C3N2 have been investigated by using of the semiempirical quantum mechanical method PM3. Some mechanical, electrical, optical and thermodynamic parameters of this material have been researched. Debye temperature and melting temperature have been calculated. The found theoretical value of melting temperature of carbonitride hafnium Hf6C3N2 is approximated to obtained experimental results. The block diagram of carried out investigations has been presented. The results of investigations indicate that these materials can be applied as a very heat resistant cover for hypersonic flight vehicles and returnable orbiter.

Study subject. The article discusses methods for determining the distance to objects and their geometric parameters using the vision systems. The goal is a comparative analysis of the quality indicators of the most used methods for determining the distance and geometric parameters of the object. The following task is to analyze and experimentally study the quality indicators of methods for determining the distance and geometric parameters of the object; to assess the efficiency of monocular and stereoscopic systems in laboratory conditions. Used methods: statistical modeling, laboratory field tests. The obtained results: a comparative analysis of the efficiency of the known methods for determining the distance and geometric parameters of the object. The quality indicators estimates of the studied methods for determining the distance and geometric parameters are obtained. Conclusions: the algorithms for the implementation of the investigated methods for determining the distance and geometric object parameters, used in stereoscopic and monocular vision systems, have been implemented; experimental results have been obtained that allow a comparative analysis of their effectiveness. The software products modeling the considered methods, operating in real time in the Python environment, are obtained.

The subject of research discussed in the paper is indicators of a critical network performance. The research target is a model of nonlinear elements of a critical network. The research objective is creation of a model for nonlinear elements of computer network (CN) telecommunications facilities of a critical system providing the desired parameters of QoS. The paper fulfills the following tasks: analysis of the main factors causing impaired service quality in CN; creation of a model for a small nonlinearity impact on forming free oscillations by generating a relevant motion equation; analysis of oscillator free motion presented in the form of the Duffing equation; working out a general integral of the Duffing equation as applied to a stiff system. The research methods used are: the foundations of the theory of computer systems and networks and the nonlinear differential equations theory. The results obtained are as follows: the main factors presumably causing impaired network services of forensic systems are analyzed; it was found that one of the main causes is the telecommunications component of CN, which possesses a number of critical parameters, including lack of stability and robustness of data signal frequency; numerical simulation of the findings was performed. Conclusions: a formula was devised to define the relationship between the free oscillation frequency and the oscillation system energy with reference to nonlinearity which takes into account the parameters of the oscillation system initial state at startup; nonlinearity of the oscillation system of a self-oscillator has a significant impact on accuracy and stability of its output oscillation frequencies; it was determined that for equivalent nonlinearity parameter values k>0.1 there is a considerable mismatch between the reference signal and the actual signal transmitted in the network, which can cause a large deterioration of QoS; further research should be aimed at development of hardware-software tools making it possible to reduce the impact of small nonlinearities of telecommunications equipment elements of critical networks on quality of performance

Solving the problems of analysis and synthesis of closed digital systems for stabilization of movable objects is associated with significant difficulties. One of the possible ways to solve the problem is the transition from a mathematical model of a continual-discrete closed stabilization system to an approximate mathematical model of a discrete closed system using infinite matrix series containing the own matrix and the control matrix of the continuous part of the system, as well as the quantization period of the discrete part. Using the example of a closed digital stabilization system for a space stage of a solid-propellant carrier rocket flying in an airless space with a marching engine turned on, the problem of constructing stability regions of a closed digital stabilization system in the plane of variable parameters of a digital stabilizer was solved and a comparative analysis of these regions was carried out for various numbers of members of matrix series taken into account and different values of the digital stabilizer quantization period

The implementation of tools for assessing decisions making is an urgent and demanded task at the current stage of information technology development. Decision-making support systems (DMSS) are perspective tools for it. The paper proposes a mathematical tool for construction a DMSS. DMSS construction involves the analysis of the available observation or measurement results and the development of a strategy for checking the initial parameters in the form of a fuzzy decision tree or production rules. The proposed tool is based on cumulative information estimates (information and entropy) for fuzzy data sets. The use of fuzzy data is a most fully consistent with human nature. It can be explained, that in practice people often use subjective sensations and a priori knowledge than precise probabilistic criteria. Therefore, using fuzzy logic and considering the degree of possibility as a fuzzy measure, experts are able to describe real data with sufficient accuracy. The relationship of the proposed total information estimates is investigated in the paper. The paper provides examples which demonstrating the practical application of the proposed mathematical tool. The authors plan to present the results of experimental investigations of the proposed approach and its comparison with other known methods and algorithms in a next work. These results will be obtained on a wide range of formalized data stored in the well-known UCI Machine Learning Repository. As compared methods and algorithms, we are going to choose algorithms for constructing fuzzy decision trees based on Luca de Termini entropy, Naive-Bayesian classification, algorithms for decision trees induction - C4.5, CART and the method of nearest neighbours.

The subject matter of this paper is a research of issues related to the variability management at the stage of domain analysis (DA) in the full life cycle (FLC) of software products line (SPL). The main goal of this research work is the elaboration of a new knowledge-based information technology to support a variability management in DA as a most complex and weak-formalized stage in FLC of SPL. In order to reach this goal the following tasks were formulated and resolved: to analyze the variability issues in FLC on the example of the modern agile-development approach - in the Scrum-methodology; to study how the methods of knowledge handling can be used to support some users and domain-experts activities within the DA phase with respect to software variability modeling; to make the motivated choice of the suitable CASE-tools to elaborate an appropriate IT solution to support the knowledge-oriented approach to DA; to present this IT-solution in a structured form, to consider some its implementation issues, and to discuss the first testing results. The methods used in this research are: domain-driven design approach to software development, repertory grids method and ontologies for expert’s knowledge handling, IDEF0 notation for specification of the proposed IT solution, feature-oriented domain analysis (FODA) for variability modeling. Conclusions: the results of this research shown that the special attention has to be paid to the DA in a FLC, especially with usage of knowledge-based methods. To perform this process in an effective way the repertory grids method is motivated chosen and analyzed. To support the usage of this method in DA the proposal is made to elaborate the special IT-solution using some already available CASE-tools. The essentials functionality features of two such systems: GridSuite and SOVA (Semantical and Ontological Variability Analysis) are considered, and basing on this result, the integrated IT-solution is elaborated and presented in form of the IDEF0 diagram. Finally, the main technological facets of these tools installation are studied and tested, and the test-case to show the possibility to generate the FODA-variability model for the “Smart-Home” application domain is provided

In the task of finding the features of digital images, it is relevant to determine solutions that provide high processing speed. In the article experimental studies of the application of differential invariants based on the partial image model as a linear combination of B-splines that are close to the average interpolation. Such a model retains the properties of the Gaussian model in the frequency domain, but has less computational complexity, which allows us to better investigate its asymptotic properties and the properties of the corresponding partial derivatives used in the construction of differential invariants. The issue of differences in gradient magnitude, Lapsasian, Hessian determinant, and curvature of the scaling curve during image processing was studied, and the masks of low-frequency filters and operator masks were minimized based on differences of smoothing operators. It has been experimentally proved that smoothing of digital images and reduction of their linear sizes allows to formalize the process of feature selection on the basis of analysis of probability distributions of introduced differential invariants. The suggested approach may be recommended when searching for similar objects containing different images. The approach considered in the work has a low computational complexity, which makes it possible to recommend it for use in systems with a low computation speed, in particular for systems operating on single-board computers.

The subject matter of the paper is the redundant structures of complex systems (RCS), in particular, safety control systems for nuclear power plants, power grids, aerospace systems, and other critical application complexes (CAP). The goal is to develop and study models of reliability (availability) of such RCS taking into account the means of information processing and communications of the CAP. The tasks to be solved are: 1) to form a set of RCS based on majority voting according to the "2oo3" principle and redundancy according to the "1oo2" principle of information and communication processing facilities with serial-parallel and bridge connections of elements; 2) to develop reliability block diagrams (RBD), mathematical (analytical) models of reliability of RCS with cascade redundancy "2oo3" and "1oo2"; 3) to study these models and determine the dependences of the probabilities of failure-free operation of various RCSs on time, the failure rates of information processing and communication facilities, voting elements, 1oo2 elements; 4) formulate recommendations for the selection of RCS types depending on the values of input parameters and requirements for systems. For this, the methods of set theory, probability theory, combinatorial analysis were used. The following results were obtained. A set of RCSs with various options for redundancy and connection of layers "2oo3" have been proposed. The corresponding RBDs and mathematical models of reliability have been developed and researched, and recommendations have been formulated for their use depending on the input parameters. Conclusions. The scientific novelty of the obtained models is as follows: they provide an analytical assessment for the RCS with various variants of the 2oo3 and 1oo2 cascades, taking into account the information processing and communication facilities of the CAP.

The subject matter of the article is the logistics support for the state defense forces. The goal of the study is the finding out a logistics support model that allows to obtain quantitative estimates of the required number of weapons ensured a given level of combat readiness and support the serviceability of troops, as well as optimal management of procurement, repair and modernization of weapons over time. The tasks to be solved are: to present the process of logistics support of the state defense forces group using the queuing model; to compile a state graph of a sample of weapons and military equipment; to compose a equations system describing the average number of weapons and military equipment samples in different states during their operation in the troops; by solving the differential equations system to obtain the dependences of the main logistics support system’s parameters in time. General scientific and special methods of scientific knowledge are used. The following resultswere obtained: The logistics support of the state defense forces group is presented as a queuing model, the parameters of which are determined by statistical data from the troops. A model of queuing is proposed to describe the logistics support process for the state defense forces group. In the model, the transitions of the sample of weapons from one state to another are carried out with intensities, µ or ? depend?s on the influence of the external environment and management. Within the framework of the proposed model, a differential equations system is obtained describes the average numbers of weapons samples in different states during their operation in the army. The obtained differential system solution corresponding the model is a quantitative estimate of the required number of weapons needed to ensure a given level of combat readiness and serviceability of state defense forces troops, as well as optimal management of procurement, repair and modernization of weapons over certain time.

The subject of research is image normalization based on key points analysis. The purpose is development of mathematical models and their software implementation for normalization of image geometric transformations based on the analysis of SIFT, SURF, ORB, BRISK, KAZE, AKAZE descriptors; the model application for comparative analysis of descriptors based on expert assessments of normalization quality, time costs and other indicators; construction and usage in experiments the own dataset with 100 real image pairs which contains scenes of five types: buildings, plane images outside, plane images inside, natural and artificial textures; making conclusions about the performance of the considered descriptors to solve the normalization problem. Such methods are applied: SIFT, SURF, ORB, BRISK, KAZE, AKAZE descriptors for describing key points, the Nearest Neighbor Distance Ratio method or symmetric method for search of corresponding pairs of key points from different images, the RANSAC method for rejecting false correspondences and obtaining a homography matrix, similarity measures, software modeling. The results obtained: experimental normalization results by SIFT, SURF, ORB, BRISK, KAZE, AKAZE descriptors for 100 real pairs of own dataset (normalized images, their overlaps, quantitative descriptor evaluation, precision and recall estimation, time costs estimation, expert quality assessment, conversion of all indicator values to an 8-point rating scale); summary diagrams and conclusions about advantages and weaknesses of the compared descriptors; recommendations about the most-suitable-algorithm selection for solving normalization problem in specific cases.

The subject of the research is the methods of digital processing of halftone medical images with locally concentrated features. The object of the research is the process of morphological analysis of digital mammograms in the design of decision support systems in medicine. The aim of this work is to develop methods and technologies for detecting of diagnostically significant characteristics of digital mammograms based on their morphological analysis, taking into account fractal dimensions. The objective of the study is to improve the quality of mammographic examinations of patients in the design of decision support systems in medicine by developing specialized methods for morphological analysis of digital mammograms (highlighting diagnostically significant elements amid noises), based on taking into account the features of the images in the form of useful signal models, in particular, fractal dimension models. Research methods: a method for calculating the fractal dimension of two-dimensional halftone images specified on a discrete set, methods of object-oriented programming, methods of statistical analysis. As a result of the research, the following results were obtained: based on the analysis of known methods of digital image processing, a limited area of their application in processing mammograms was shown and the urgency of developing specialized methods of morphological analysis based on taking into account the features of the considered images in the form of useful signal models, in particular, fractal dimension models. A method and an algorithm for the implementation of morphological analysis of digital mammograms, taking into account their fractal dimension, have been developed. The software implementation of the method was performed using the MatLab math package and testing on real mammograms was completed. Mammograms without obvious pathologies and mammograms which having pathological structures of various types (tumors, intraductal formations and microcalcifications) were processed. The fractal dimension of the entire image and selected fragments was calculated. Conclusions. The results of the research showed that the fractal dimension of the entire image does not give statistically significant results on the presence or absence of pathologies, but if we calculate the fractal dimension on the selected fragments, then the results are very different. We can trace the pattern that the more obvious pathologies on a fragment, the greater the fractal dimension. Further research is aimed at developing a method for classifying digital mammograms taking into account their fractal dimensions.

The subject matter of the article is the processes of automated construction of explanations on the operation of an intelligent system for use in the human-computer interface. The goal is to develop a dynamic model of explanation for the human-computer interface using temporal knowledge about the process of functioning of the intelligent system. Temporal knowledge makes it possible to set possible sequences of decision-making actions in an intelligent system based on the known temporal order for pairs of such actions. Tasks: to develop an approach to constructing explanations for the operation of an intelligent system based on the use of temporal knowledge; development of a three-aspect model of explanations using temporal knowledge. The approaches used are: approaches to the construction of knowledge representation based on temporal dependencies, approaches to the construction of chatbot answers using rules, as well as with their automatic generation. The following results are obtained. The structuring of aspects of explanation taking into account the possibilities of their description with the help of temporal knowledge is performed; a temporal approach to constructing an explanation is proposed; a dynamic explanation model using temporal rules has been developed. Conclusions. The scientific novelty of the results is as follows. A temporal approach to constructing explanations for the operation of an intelligent system is proposed. The approach describes explanation as a process consisting of a temporally ordered sequence of facts. The order of time for pairs of facts is determined by temporal rules. Such rules may define the explanation process with varying degrees of detail over time, depending on the request for clarification. Detailed explanations reflect the subject area model and include the basic and alternative sequences of actions performed by the intelligent system. The explanation of the basic patterns of the intelligent system makes it possible to interpret the limitations that affect the obtained solution. The explanation of the system as a whole provides an implicit reflection of the key causal relationships, which allows you to get a simplified interpretation of the results of the intelligent system. A dynamic model of describing explanations based on temporal knowledge for use in the human-computer interface is proposed. The model takes into account the description of actions in the subject area, the patterns of these actions, as well as generalized causal relationships between such patterns. The model provides an opportunity to present the dynamics of the process of functioning of the intelligent system with the required level of detail, as well as change the level of detail to clarify the explanation at the request of the user.

The threat to information security for the air navigation service providers represents a potential violation of information security of the information infrastructure elements in the air traffic management system such as communications, navigation and surveillance equipment, and the information and telecommunication systems. Typically, a threat results from the presence of vulnerable components in the protection of information technology as part of air navigation service providers’ activity. Most of the approaches and techniques of international aviation organizations and best-practices of air navigation service providers are focused on developing risk methods and models regarding aviation safety. A well-known problem with aviation safety risk assessment is that it does not take into account the information and cyber security threats. The subject of the article is exploration of methods and models for risk assessment of air navigation service providers. The purpose is the development of model of functional hazard assessment and set of information security requirements for air navigation service providers. The proposed model of functional hazard assessment differs from the known by detailing of information security sphere. The software model of functional hazard assessment was developed via MATLAB Fuzzy Logic Toolbox. Practical significance is that the obtained results allow air navigation service providers to make better decisions regarding management systems maturity improvement.

The subject of research in the article is the models and methods of resources load forecasting in cloud computing systems using the mathematical apparatus of neural networks. The aim of the work is increasing the efficiency of computing systems resources usage (such as RAM, disk space, CPU, network) by developing methods of resources load forecasting. The article addresses the followingtasks: development of an integrated approach to the problems of resources load forecasting within cloud computing systems, which includes the synthesis of a combining forecasting neural network; development of a forecasting neural network model based on Elman neural network; development of a method for training a neural network based on an artificial immunity algorithm; evaluation of the effectiveness of the developed method. To solve the set tasks, the approaches and methods of artificial neural and immune systems were used, as well as methods of theoretical research, which are based on the scientific provisions of the theory of artificial intelligence, statistic, functional and systemic analyzes. The following results were obtained: on the basis of the analysis of resources load forecasting methods in cloud computing systems, the main results of the methods were revealed, the advantages and disadvantages were demonstrated. On the basis of the research results analysis, the necessity of improving analytical methods for forecasting the load has been proved. The method of computing resources load forecasting in cloud computing systems has been improved, which makes it possible to obtain more accurate assessment results and prevent overloads in cloud computing systems. The results obtained are confirmed by the experiments carried out using the means of the infrastructure of private infrastructure services. Conclusions: improved the resources load forecasting method based on the mathematical apparatus of artificial neural networks to improve the efficiency of their usage.