Development of Algorithm for Calculating Data Packet Transmission Delay in Software-Defined Networks

The relevance of this type of network is associated with the development and improvement of protocols, methods, and tools to verify routing policies and algorithmic models describing various aspects of SDN, which determined the purpose of this study. The main purpose of this work is to develop specialized methods to estimate the maximum end-to-end delay during packet transmission using SDN infrastructure. The methods of network calculus theory are used to build a model for estimating the maximum transmission delay of a data packet. The basis for this theory is obtaining deterministic evaluations by analyzing the best and worst-case scenarios for individual parts of the network and then optimally combining the best ones. It was found that the developed method of theoretical evaluation demonstrates high accuracy. Consequently, it is shown that the developed algorithm can estimate SND performance. It is possible to conclude the configuration optimality of elements in the network by comparing the different possible configurations. Furthermore, the proposed algorithm for calculating the upper estimate for packet transmission delay can reduce network maintenance costs by detecting inconsistencies between network equipment settings and requirements. The scientific novelty of these results is that it became possible to calculate the achievable upper data delay in polynomial time even in the case of arbitrary tree topologies, but not only when the network handlers are located in tandem. Doi: 10.28991/ESJ-2022-06-05-010 Full Text: PD

Trainable Regularization in Dense Image Matching Problems

This study examines the development of specialized models designed to solve image-matching problems. The purpose of this research is to develop a technique based on energy tensor aggregation for dense image matching. This task is relevant within the framework of computer systems since image comparison makes it possible to solve current problems such as reconstructing a three-dimensional model of an object, creating a panorama scene, ensuring object recognition, etc. This paper examines in detail the key features of the image matching process based on the use of binocular stereo reconstruction and the features of calculating energies during this process, and establishes the main parts of the proposed method in the form of diagrams and formulas. This research develops a machine learning model that provides solutions to image matching problems for real data using parallel programming tools. A detailed description of the architecture of the convolutional recurrent neural network that underlies this method is given. Appropriate computational experiments were conducted to compare the results obtained with the methods proposed in the scientific literature. The method discussed in this article is characterized by better efficiency, both in terms of the speed of work execution and the number of possible errors. Doi: 10.28991/HIJ-2023-04-03-011 Full Text: PD

Forming the Architecture of a Multi-Layered Model of Physical Data Storage for Complex Telemedicine Systems

The relevance of this research is determined by the need to study the issues of improving data storage technologies for complex telemedicine systems. The objective is to create a multi-layered data storage model for complex telemedicine systems to ensure the most complete use of their capacity and the timely expansion of existing storage. The research is conducted on the basis of an analysis of existing opportunities and problems in the field of data storage technologies. An analysis of the main features of the development of data storage technologies revealed that the existing models have no detailed description of the recording and physical storage of data bits, which is necessary for describing the storage process. Different architectures are reviewed, and their strengths and weaknesses are discussed. Within the framework of a demonstration experiment using the Kohonen neural network apparatus as a tool for solving the problem of placing objects in accordance with the required parameters, it is shown that the proposed storage system resource management model is operable and allows solving the problem of rational use of physical resources. As a result, a multilevel model of data storage is proposed, which combines the levels of storage process organization and technology. The distinguishing feature of this method is the comparison of storage organization levels, data media, and characteristics of physical storage and stored files. Doi: 10.28991/HIJ-2023-04-04-09 Full Text: PD

A Fuzzy Approach to the Synthesis of Cognitive Maps for Modeling Decision Making in Complex Systems

The object of this study is fuzzy cognitive modeling as a means of studying semistructured socio-economic systems. The features of constructing cognitive maps, providing the ability to choose management decisions in complex semistructured socio-economic systems, are described. It is shown that further improvement of technologies necessary for developing decision support systems and their practical use is still relevant. This work aimed to improve the accuracy of cognitive modeling of semistructured systems based on a fuzzy cognitive map of structuring nonformalized situations (MSNS) with the evaluation of root-mean-square error (RMSE) and mean average squared error (MASE) coefficients. In order to achieve the goal, the following main methods were used: systems analysis methods, fuzzy logic and fuzzy sets theory postulates, theory of integral wavelet transform, correlation and autocorrelation analyses. As a result, a new methodology for constructing MSNS was proposed—a map of structuring nonformalized situations that combines the positive properties of previous fuzzy cognitive maps. The solution of modeling problems based on this methodology should increase the reliability and quality of analysis and modeling of semistructured systems and processes under uncertainty. The analysis using open datasets proved that compared to the classical ARIMA, SVR, MLP, and Fuzzy time series models, our proposed model provides better performance in terms of MASE and RMSE metrics, which confirms its advantage. Thus, it is advisable to use our proposed algorithm in the future as a mathematical basis for developing software tools for the analysis and modeling of problems in semistructured systems and processes. Doi: 10.28991/ESJ-2022-06-02-012 Full Text: PD

Development and Algorithmization of a Method for Analyzing the Degree of Uniqueness of Personal Medical Data

The purpose of this investigation is to develop a method for quantitative assessment of the uniqueness of personal medical data (PMD) to improve their protection in medical information systems (MIS). The relevance of the goal is due to the fact that impersonal PMD can form unique combinations that are potentially of interest to intruders and threaten to reveal the patient's identity and medical confidentiality. Existing approaches were analyzed, and a new method for quantifying the degree of uniqueness of PMD was proposed. A weakness in existing approaches is the assumption that an attacker will use exact matching to identify people. The novelty of the method proposed in this paper lies in the fact that it is not limited to this hypothesis, although it has its limitations: it is not applicable to small samples. The developed method for determining the PMD uniqueness coefficient is based on the assumption of a multidimensional distribution of features, characterized by a covariance matrix, and a normal distribution, which provides the most reliable reflection of the existing relationships between features when analyzing large data samples. The results obtained in computational experiments show that efficiency is no worse than that of focus groups of specialized experts. Doi: 10.28991/HIJ-2023-04-01-09 Full Text: PD

Cluster Data Analysis with a Fuzzy Equivalence Relation to Substantiate a Medical Diagnosis

This study aims to develop a methodology for the justification of medical diagnostic decisions based on the clustering of large volumes of statistical information stored in decision support systems. This aim is relevant since the analyzed medical data are often incomplete and inaccurate, negatively affecting the correctness of medical diagnosis and the subsequent choice of the most effective treatment actions. Clustering is an effective mathematical tool for selecting useful information under conditions of initial data uncertainty. The analysis showed that the most appropriate algorithm to solve the problem is based on fuzzy clustering and fuzzy equivalence relation. The methods of the present study are based on the use of this algorithm forming the technique of analyzing large volumes of medical data due to prepare a rationale for making medical diagnostic decisions. The proposed methodology involves the sequential implementation of the following procedures: preliminary data preparation, selecting the purpose of cluster data analysis, determining the form of results presentation, data normalization, selection of criteria for assessing the quality of the solution, application of fuzzy data clustering, evaluation of the sample, results and their use in further work. Fuzzy clustering quality evaluation criteria include partition coefficient, entropy separation criterion, separation efficiency ratio, and cluster power criterion. The novelty of the results of this article is related to the fact that the proposed methodology makes it possible to work with clusters of arbitrary shape and missing centers, which is impossible when using universal algorithms. Doi: 10.28991/esj-2021-01305 Full Text: PD

Influence of Cutting Speed during the Turning of Inconel 718 on Oxidation Wear Pattern on the Zr-ZrN-(Zr,Mo,Al)N Composite Nanostructured Coating

The properties and oxidation wear patterns in the composite nanostructured coating of Zr-ZrN-(Zr,Mo,Al)N were studied during the turning of Inconel 718 alloy at the cutting speeds of vc = 125 and 200 m/min. The hardness of the coating, its elastic modulus, and critical fracture load during the scratch testing were determined. The study focused on the tribological properties of the Zr-ZrN-(Zr,Mo,Al)N coating at temperatures of 400–900 °C paired with an insert made of Inconel 718, which exhibited a certain advantage over the reference coatings of Zr-ZrN and Ti-TiN-(Ti,Cr,Al)N of similar thickness. The coating of Zr-ZrN-(Zr,Mo,Al)N provided for the longest tool life at the cutting speed of vc = 125 m/min (the tool life was four times longer in comparison with that of the uncoated tool and 15% longer in comparison with that of the Ti-TiN-(Ti,Cr,Al)N-coated tool) and at the cutting speed of vc = 200 m/min (the tool life was 2.5 times longer in comparison with that of the uncoated tool and 75% longer in comparison with that of the Ti-TiN-(Ti,Cr,Al)N-coated tool). While at the cutting speed of vc = 125 m/min, the surface coating layers exhibit only partial oxidation of the external layers (to a depth not exceeding 250 nm), with mostly preserved cubic nitride phases, and then the cutting speed of vc = 200 m/min leads to almost complete oxidation (to the depth of at least 500 nm), however, with a partially preserved nanolayered structure of the coating

Specific Application Features of Ti-TiN-(Ti,Cr,Al)N, Zr-ZrN-(Zr,Mo,Al)N, and ZrHf-(Zr,Hf)N-(Zr,Hf,Cr,Mo,Al)N Multilayered Nanocomposite Coatings in End Milling of the Inconel 718 Nickel-Chromium Alloy

This article discusses the specific application features of end mills with Ti-TiN-(Ti,Cr,Al)N, Zr-ZrN-(Zr,Mo,Al)N, and ZrHf-(Zr,Hf)N-(Zr,Hf,Cr,Mo,Al)N multilayer nanocomposite coatings during the machining of the Inconel 718 nickel–chromium alloy. The hardness, fracture resistance during scratch testing, structure, and phase composition of the coatings were studied. The tribological properties of the samples were compared at temperatures of 400–900 °C. Tests were conducted to study the wear resistance of the coated end mills during the milling of the Inconel 718 alloy. The wear mechanism of the end mills was studied. It was found that in comparison with the other coatings, the Zr-ZrN-(Zr,Mo,Al)N coating had the highest hardness and the lowest value of the adhesion component of the coefficient of friction at high temperatures. However, the Zr-ZrN-(Zr,Mo,Al)N coating exhibited good resistance to cracking and oxidation during the milling of the Inconel 718 alloy. Based on the above, the Zr-ZrN-(Zr,Mo,Al)N coating can be considered a good choice as a wear-resistant coating for the end milling of the Inconel 718 alloy