The problem of optimal placement of elements of electrical and electronic circuits is considered. The minimum weighted length of the connections is selected as the criterion. The scheme is defined by a matrix of connections. We consider a fixed set of element positions and a distance matrix based on an orthogonal metric. This problem is a variant of the general mathematical model, called the quadratic assignment problem. The geometric limitation of the problem is that no more than one element is placed in one cell. Combinatorial analogs of the Gauss-Seidel method, the genetic algorithm, and the corresponding hybrid methods for solving the quadratic assignment problem with optimal placement of electronic equipment elements are developed and implemented on a computer. A series of computational experiments was conducted, which showed satisfactory computational qualities of the proposed methods. The proposed computational method, which is a combinatorial analog of the method of coordinate descent and one of the variants of the general approach based on paired permutations, is characterized by the best computational qualities among the methods studied in the article. According to well-known studies, the genetic algorithm is obviously no worse than the Monte Carlo method. The research conducted in the article shows that the method of penalty functions in the problem of placement and for the case of a genetic algorithm is ineffective. Therefore, it is of interest to consider permutations without repetitions as individuals of the population. This circumstance is taken into account at the stages of selection and mutation: at these stages, the standard calculations according to the genetic algorithm are supplemented by the procedure of paired rearrangements of genes in the chromosome. The article provides a detailed description of the program for the implementation of the genetic method on a computer.

The process of marking multi-attribute experimental data for subsequent use by means of data mining in problems of detection and classification of rare anomalous events of computer systems (CS) is considered. The labeling process is carried out using three methods: manual preprocessing, statistical analysis and cluster analysis. Among the attributes of the metric type, the authors identified two macrogroups: “integral attributes” and “impulse attributes”. It is shown that the combination of statistical and cluster analysis methods increases the accuracy of detecting anomalous events in the CS, and also allows the selection of attributes according to their information significance. The expediency of manual preprocessing of data before clustering is shown by the example of dividing attributes into macrogroups, analyzing the density distribution using violin plot and removing the trend component using the method difference stationary series. With the help of construction of violin diagrams (Violin plot) for the attribute of the “integral” macrogroup, the distribution of states of the CS is shown. It is shown that the removal of the trend component by the DS-series method, normalization and reduction to absolute values allows more accurate marking of anomalous outliers, but this is not always acceptable. The interpretation of the clustering results performed for each normalized attribute shows that the normal values for all attributes are concentrated around zero values. The result of labeling experimental data is attribute-labeled data, where each attribute at the current time is assigned one of two states: abnormal or normal.

Ways of forming a precision time scale

Mohammed O.A.A. (2020) Development of approaches to ensure reliable emergency communications in emergencies. T-Comm

Management model in social and economic systems

Quality of service parameters estimation becomes even more valuable when using cloud compute services. Mathematical model of described cloud-deployed web application in terms of Processor Sharing (PS) policy for mono-service traffic type proposed in this research. This model has Poisson distribution of the incoming requests flow with intensity ?. Requests awaiting in queue, queue length is considered to be unlimited and all requests should be served. Request in this system is HTTP request with a special payload in JSON format. The size of this payload is different for each request but it lies in a narrow band of values (bytes or decades of bytes). A model of cloud compute cluster was built. Characteristics of relative serving efficiency and relative bandwidth of a single requests flow was calculated using this model for different amount of resource provided for processing of a single request. The dependency of these characteristics from cluster load coefficient is demonstrated in charts. Some conclusions on cloud cluster QoS parameters behavior after the change of input requests flow size. Proposed model helps estimating quality of service parameters and adopting the infrastructure to increased or decreased number of requests from customers and could be used for architecting, deploying and administrating web services.

The paper is dedicated to the overview of the autonomous ship onboard control system functionality. The paper is dedicated to autonomous maritime navigation, i.e. to planning a safe and optimal route for an autonomous ship amid the absence of crew on board and to handling an autonomous ship when underway, ensuring seaworthiness and route correctness. Moreover, the paper describes communications of several autonomous ships and autonomous and ordinary ships to infer a collective decision on how to pass safely through a particular area. Since it is expected that autonomous ships are going to be equipped with dozens of sensors and detectors, the paper describes remote monitoring of an autonomous ship when underway. Since an autonomous ship highly depends on its onboard control system, the paper also pays attention to the robustness of the system. The paper suggests evolutionary computations as a solution for the route planning problem because this approach enables to perform multicriteria optimization of a set of solutions simultaneously. For autonomous ship handling and seaworthiness control, the paper suggests machine learning techniques because these techniques can solve problems in case of uncertainty and the environmental mutability. For inter-ship communications, the paper suggests distributed consensus algorithms, widely used in parallel and distributed computation systems. To ensure the onboard control system robustness, the paper suggests the actor approach that represents that the entire software system consists of a set of elementary agents communicating in the distributed computational environment.

The construction and analysis of call-center model in

Minimizing signal distortions at the most optimal choice of digital conversion method. T-Comm

Рассматривается системотехнический этап проектирования приемного СВЧ-модуля радиолокационного назначения.Проведено сравнение результатов моделирования и расчетов, полученных с помощью двух различных программ -программного комплекса структурного синтеза, анализа и параметрической оптимизации (RF Systems Designer) и пакета VSS программы AWR DE.Отличительной особенностью программного комплекса RF Systems Designer является наличие возможности автоматического синтеза и параметрической оптимизации структурных схем линейного тракта.В работе рассматривается два различных метода проектирования линейных трактов.Первым методом проектирования является инженерный эмпирический метод с использованием современных САПР.Второй метод проектирования основан на применении описываемого программного комплекса.Целью работы является подтверждение корректности реализованных в программном комплексе алгоритмов структурного синтеза, параметрической оптимизации и принятия решения, математических моделей, соотношений и формул путем сравнения результатов