Integrated circuits, systems on a chip are the key links in various industrial systems and state defense systems. The emergence of counterfeit integrated circuits, problems of piracy, overproduction, unauthorized interference in the design of microcircuit, hardware Trojans require the development of methods and means of their timely detection. Trojans can be introduced into the integrated circuits structure both on the development stage and during the production process, including the stages of specification, design, verification and manufacturing. The inclusion of additional elements in the integrated circuits structure jeopardizes the functional suitability and reliability of the system as a whole. For the purpose of hardware protection of projects, the methods of hardware coding are currently used.

The paper discusses the features and reliability of logical coding of combinational circuits. An algorithm for cracking the code of combinational circuits is proposed, based on the description of encoded structure by the resolution function and reducing the problem to SAT CNF. The initial data for decoding the structure of a digital device is the structural implementation of encoded circuit, obtained, for example, by reverse engineering (prototype design), as well as an activated physical sample of an integrated circuit, when into protected from unauthorized access memory the correct key value is loaded. This sample can be used as a black box model. The main idea of breaking a key is to solve a problem without research on a large interval of values of input and output variables.

The urgency of the problem of memory testing of modern computing systems is shown. Mathematical models describing the faulty states of storage devices and the methods used for their detection are investigated. The concept of address sequences (pA) with an even repetition of addresses is introduced, which are the basis of the basic element included in the structure of the new transparent march tests March _pA_1 and March _pA_2. Algorithms for the formation of such sequences and examples of their implementations are given. The maximum diagnostic ability of new tests is shown for the case of the simplest faults, such as constant (SAF) and transition faults (TF), as well as for complex pattern sensitive faults (PNPSFk). There is a significantly lower time complexity of the March_pA_1 and March_pA_2 tests compared to classical transparent tests, which is achieved at the expense of less time spent on obtaining a reference signature. New distance metrics are introduced to quantitatively compare the effectiveness of the applied pA address sequences in a single implementation of the March_pA_1 and March_pA_2 tests. The basis of new metrics is the distance D(A(j), pA) determined by the difference between the indices of repeated addresses A(j) in the sequence pA. The properties of new characteristics of the pA sequences are investigated and their applicability is evaluated for choosing the optimal test pA sequences that ensure the high efficiency of new transparent tests. Examples of calculating distance metrics are given and the dependence of the effectiveness of new tests on the numerical values of the distance metrics is shown. As well as in the case of classical transparent tests, multiple applications of new March_pA_1 and March_pA_2 tests are considered. The characteristic V(pA) is introduced, which is numerically equal to the number of different values of the distance D(A(j), pA) of addresses A(j) of the sequence pA. The validity of analytical estimates is experimentally shown and high efficiency of fault detection by the tests March_pA_1 and March_pA_2 is confirmed by the example of coupling faults for p = 2.

In the problems of data flows analysis, the problems of statistical decision making on parameters of observed data flows are important. For their solution it is proposed to use sequential statistical decision rules. The rules are constructed for three models of observation flows: sequence of independent homogeneous observations; sequence of observations forming a time series with a trend; sequence of dependent observations forming a homogeneous Markov chain. For each case the situation is considered, where the model describes the observed stochastic data with a distortion. "Outliers" ("contamination") are used as the admissible distortions that adequately describe the majority of situations appear in practice. For such situations the families of sequential decision rules are proposed, and robust decision rules are constructed that allow to reduce influence of distortion to the efficiency characteristics. The results of computer experiments are given to illustrate the constructed decision rules.

The analytical solution of boundary value problem describing the process of penetration of low-frequency magnetic field through thin-walled cylindrical screen with cylindrical inclusion is constructed by use of approximate boundary conditions. The source of the field is a thin thread of infinitely small length with an infinitely small cross-section where current circulates. Thread is located in a plane which is perpendicular to axis of cylindrical screen, in outer region with respect to a screen. Initially the potential of initial magnetic field is represented as spherical harmonic functions, then using addition theorems connecting spherical and cylindrical harmonic functions, it became as cylindrical harmonic functions superposition. Secondary potentials of magnetic field are also presented as superposition of cylindrical harmonic functions in three-dimensional space. It is shown that the solution of formulated boundary value problem is reduced to the solution of linear algebraic equations system for coefficients included in the representation of secondary fields. The influence of some aspects of the problem on the value of the screening coefficient of an external magnetic field when passing through a cylindrical copper screen in the presence of a cylindrical inclusion is studied numerically. Calculation results are presented in graphs form. Obtained results can be used to shield technical devices and biological objects against the effects of magnetic fields to provide ecological surrounding of operating electrical installations and devices.

The paper concerns the problem of improving energy efficiency and the quality of air temperature automatic control in industrial greenhouses. The article proposes a method based on the principle of disturbance compensation using weather forecast data. The plant dynamic model structure is described by the linear 1st order aperiodic link with delay both for the control circuit and for the disturbance circuit. To solve the problem of time delays in the plant mathematical model it is suggested along with the use of outside temperature sensor signal to take into account the weather forecast data for the outdoor temperature changes over the specific forthcoming interval of time. It allows the controller to generate appropriate compensation control signal in advance. The block diagram of the automatic control system of the greenhouse temperature is given. Theoretical mathematical expressions for the regulation algorithm and analysis of regulation quality are obtained and the results of numerical modeling of the temperature control process are presented. The proposed automatic control method can be used to regulate the air temperature in buildings with high requirements for microclimate parameters.

A method for the simulation of reduced frequency resolution of the ear in patients with sensorineural hearing loss is proposed. The method is based upon the ability to adjust it according to the audiogram of a concrete person by frame-by-frame signal processing in the frequency domain. Simulation of the effect of the reduced frequency resolution of the ear is achieved by processing the components of amplitude spectrum of the original sound signal by the "smearing" function. The "smearing" function is formed from the amplitude-frequency characteristics of the auditory filters, which bandwidth is determined by the audiogram of the deaf person. The proposed method is implemented in the MATLAB. An experimental study of the effect of the reduced frequency resolution of the ear using the speech intelligibility test was conducted. The experiment involved 15 people who listened the records processed by the proposed method with various settings and noise conditions. Experimental data have shown that reduced frequency resolution of the ear leads to the deterioration in speech intelligibility, especially in the presence of background noise. Based on the answers of the participants of the experiment, the confusion tables of sounds were compiled, reflecting the fact of indistinguishability of sounds similar in frequency, that confirms the correctness of the proposed method.

In machine learning, the input data is often given in different dimensions. As a result of the scientific papers review, it is shown that the initial data described in different types of scales and units of measurement should be converted into a single representation by normalization or standardization. The difference between these operations is shown. The paper systematizes the basic operations presented in these scales, as well as the main variants of the function normalization. A new scale of parts is suggested and examples of the data normalization for correct analysis are given. Analysis of publications has shown that there is no universal method of data normalization, but normalization of the initial data makes it possible to increase the accuracy of their classification. It is better to perform data clustering by methods using distance functions after converting all features into a single scale. The results of classification and clustering by different methods can be compared with different scoring functions, which often have different ranges of values. To select the most accurate function, it is reasonable to normalize several functions and to compare their estimates on a single scale. The rules for separating features of tree-like classifiers are invariant to scales of quantitative features. Only comparison operation is used. Perhaps due to this property, the random forest classifier, as a result of numerous experiments, is recognized as one of the best classifiers in the analysis of data of different nature.

There are three main families of inference algorithms in first-order logic: direct inference and its application to deductive databases and production systems; backward inference procedures and logic programming systems; theorem proving systems based on the resolution method. When solving specific problems, the most effective algorithms are those that allow you to cover all the facts and axioms and must be taken into account in the process of inference. An example is considered in which it is necessary to prove the guilt of a person in murder. On the basis of statements, a knowledge base is formed from expressions, with the help of which an expression of first-order logic is compiled and proved using direct logical inference. The proof of the reasoning obtained in direct inference using the proof tree is given. However, direct inference provides for the implementation of all admissible stages of logical inference based on all known facts. The article also considers a method based on the resolution when implementing the reverse inference, taking into account the expression obtained in the direct inference. This expression is converted into a conjunctive normal formula using the laws of Boolean algebra and is proved by the elimination of events using the conjunction operation.

The need of the creation of information system with specialized services which allow scientists and specialists to perform thematic processing of Earth remote sensing data, changing the data processing parameters in a certain way, and independently analyze the information received is shown.

To achieve the goal of rapid provision of information, the development of specialized information system is considered on the example of the creation of the software package for the dissemination of operational space information, as well as a software package for predicting the yield of grain crops.

The structure of the software package for the dissemination of operational space information is shown. The technical and functional characteristics of the separate components of the package are given. The relations of the subsystems of the package are shown during data receiving, processing, analyzing and providing information to interested specialists and researchers. Attention is drawn to the possibilities of wide application of the software package for the dissemination of operational space information for solving scientific and applied problems in various fields of knowledge.

The practical application of vegetation indexes in the analysis of operational space information is shown. The data of the practical results of forecasting of the grain crops development, as well as the quantitative indicators of satellites sessions are presented. The possibility of further improvement and development of the created information system is shown.