In the framework of the drift-diffusion model of carrier transport in the bulk of III–V typesemiconductors, under external action of strong constant electric and magnetic fields orthogonallyoriented relative to each other, a new principle for applying the discovered effects is proposed, whichtake into account the nonlinearities of the output parameters of the working chip, which leads to thepossibility creation of new semiconductor structures controlled by a magnetic field (SSCMF). Previously,the diffusion component of the output current density was not taken into account as a separateeffect arising under the orthogonal action of strong electric and magnetic components, which was atfirst time considered in this paper. It is shown that this component is a part of the inductive transverseoutput current and can be considered as an independent effect. The proposed practical applicationis based on the classical relations that describe the component spatial representation of the effectivemass energy dependence and the parameters of the kinetic equations for the carriers drift andheating in the bulk of highly mobile III–V type semiconductors structures. (The energy dependence ofthe reciprocal effective mass value was obtained under the assumption that this parameter becomesheavier in the framework of the two-valley representation. However, the mechanism of such increasingis not considered in detail, but is taken into account as a result of expansion in a Taylor series.)At the same time, some new phenomena were also hypothetically discovered: a diffusion detectoreffect and a transverse induction effect controlled by a magnetic field, similar in its manifestation tothe Gunn effect observed in this direction. The results obtained open the prospect for creating fundamentallynew frequency-converting devices based on the above SSCMF, such as autodyne-type converters(mixers), one of the designs of which is also proposed in this work in a waveguide version. Inthe case of experimental confirmation of the discovered effects, which can be investigated using theblock diagram of the measuring setup proposed in the work, we can conclude that there are promisingnew applications of magnetically controlled semiconductor structures. In addition, equipmentdevelopers will be interested in the possibility of using the magnetic field orientation angle to controlthe output parameters of such structures as part of converters

The article is devoted to solving the scientific problem of decision support for the preventionand elimination of emergencies’ consequences based on solving the problem of structuring information.The relevance of this task is due to the need to develop theoretical foundations for optimizingthe risk of adverse effects on human health and the environment in connection with emergencies.The authors give definitions to the main terms of the studied subject area. A formalizedstatement of the problem to be solved is presented. A detailed emergencies’ classification with adescription of the presented classes’ features is given. The system of rules for decision support inemergencies should have a multi-level hierarchy, which allows for the construction of variousdecision-making trajectories on a top-down basis. The most suitable model for building such an informationspace is an ontological structure that provides the creation of the necessary multi-levelhierarchy, taking into account all the parameters and criteria that affect the development of the situation.The main elements of this ontological model are entities and relationships between them, thepresence of which at the upper level of decomposition will indicate the risk of an emergency, and ateach lower level it will expand the taxonomy of a detailed description of emergencies’ possible situationsand the necessary actions to prevent or eliminate them consequences. The processing of thisontological model of rules is implemented on the basis of the structuring information fuzzy methodproposed by the authors in emergencies, which differs from known analogs by the use of a new generalizedcriterion for optimizing the choice of decision support alternatives. The originality of theoptimization formulation of the structuring problem lies in the assessment of the information elementscontextual binding to a certain class of emergency situations, interdisciplinary, taking into accountthe presence of many links between subject areas, as well as taking into account the decrease in thelevel of information efficiency about the course of emergencies over time.

Due to the rapid development of the sphere of trade, the means of automatic control of thework of employees providing services to customers are gaining particular popularity. At the moment,there are many modern approaches, methods and algorithms for automatically trackingbuyers and sellers in the store. Modern companies are trying to solve this problem in differentways: counting visitors, monitoring devices, various neural network solutions, and so on. Afterreviewing the solutions with the necessary functionality, the main disadvantages were identified,such as, for example, high cost, inconvenience in use, and so on. As a result, the authors set agoal: to improve the quality of tracking the movement of employees / customers through the developmentof automated means and methods of movement control, inter-chamber tracking and identificationof the individual. The article describes a method for automatic recognition and tracking ofemployees of stores and firms. The method is based on a cascade of neural networks and algorithmsthat allow recognizing customers and employees in uniform, as well as evaluating thequality of employees' work and customer satisfaction by voice. As the results of the research, thisarticle presents models and methods for classifying customers and sellers by uniform, methods fordetermining the level of interaction between sellers and customers based on algorithms for determiningthe satisfaction of visitors and customers by voice and face, and algorithms for determiningthe quality of employees' work. The developed methods can improve the efficiency of employees, aswell as increase the quality of services provided. Based on the results of the work, testing wascarried out and a conclusion was made about the satisfactory performance of the presented methodsand algorithms.

The use of filters matched to radio signals is quite common in radar, which helps to improverange resolution, as well as in communication systems and many other radio engineering systems,allowing you to increase the output signal-to-noise ratio (SNR). Designing digital devices on fieldprogrammable gate array (FPGA) allows us to configure them quite flexibly and create prototypesof radio engineering systems for further implementation of DSP algorithms, on applicationspecificintegrated circuits (ASIC ), GPU, CPU, etc. FPGA digital devices are most used in lowpower mobile systems, while ASICs show the highest performance with high development costs.In this work, special attention is paid to the design and implementation of a filter matched to acomplex chirp signal in the frequency domain on an FPGA using the Xilinx System Generator forDSP library of Matlab/Simulink. The results of the hardware-software model operation are presentedin paper both for a single point object and for three point objects with different sampleddelays. The dependence of the output on the input SNR for a linear and quadratic envelope detectoris shown. The analytical curve SNROUT(SNRIN) is compared with the curve obtained using thedeveloped hardware-software model implemented on the FPGA. The paper shows the benefits ofusing Xilinx System Generator for rapid prototyping of DSPs on FPGAs, and it provides an analysisof the used FPGA resources for the developed matched filter.

To improve the quality of manufactured products, it is necessary to improve all technologicalprocesses, which requires increasing the accuracy of the entire measuring path as a whole.For this it is necessary to carefully analyze systematic, random and fluctuating errors in the measurementchannel and take all measures to reduce them. Digital filtering or averaging of intermediatemeasurements (observations) according to certain rules is a radical means of improving theaccuracy of measurements performed. The aim of this work is to compare the quality of suppressionof near-real noise interference using the eight most well-known averaging methods. A model of the measurement path and a general block diagram for modeling the measurement process on acomputer under the influence of random interference are proposed for eight averaging algorithms.As a criterion for evaluating the quality of averaging methods, the ratios of absolute error variancesand mean square deviations before the computing device and after applying the specified averagingalgorithm are taken. Based on the simulation results, the following conclusions are made. 1. All averagingalgorithms provide suppression of random error components of complex interference to thelevel of 40–60 dB. Three algorithms are the best: arithmetic mean AR, a-truncated mean AU5 and atenderizedmean AB5, which provide for the suppression of 5 % of anomalous results. With an increasein the number of observations, the suppression coefficients increase proportionally. 2. Thesampling time must be a multiple of the duration of the 50 Hz AC mains period (20 ms). The optimalnumber of observations (measurements) is 100–128; with 128 measurements, the division operationis reduced to a simple shift, and the averaging result can be obtained in 1–2 μs. 3. When experimentallyapplying the AR averaging method for filtering a highly noisy measurement signal in a communicationline with a length of 800 m, a decrease in the spread of ADC output codes was observedfrom ± 3.5 % to ± 0.1 % after filtering (AR, 64 measurements in 40 ms).

Time series with seasonal variability is widely used to describe processes in variousfields, such as trade, analysis of financial markets, forecasting of passenger air transportation,and description of climatic changes. Recently, this approach has been widely used to describetechnological processes as well. In this regard, applying predictive models in control systems ofcomplex technical objects has become possible. Machine learning methods can be effectivelyused to build predictive models of series of this type. In this case, only historical data accumulatedover several periods of seasonal observation is used as input data for constructing theforecast. Knowledge of other parameters, as a rule, is not required. The article considers creatinga predictive time series model with seasonal variability, describing a technological process,the inlet flow of a wastewater treatment plant being chosen as a model. The general methodologyof model building, requirements for the input data sets, and algorithms of preprocessing toform samples used for model training and testing are described. Classical methods (SARIMA,Holt-Winters Exponential Smoothing, ETS), as well as new algorithms (Facebook Prophet,XGBoost, Long Short Term Memory), were used to build the predictive model. The implementationof the algorithms is done in the Python language, and recommendations for the use of existinglibraries and functions of this language are given in the work. The comparative analysis ofthe accuracy of the obtained models is given on the calculation of a set of statistical metri cs.Analysis of methods performance is also carried out since the time it takes to create a modeland get a forecast plays an important role when running the model in real production conditions.The best method for solving the set task for application in real-time control systems waschosen based on the sum of estimates. In conclusion, recommendations for improving forecastaccuracy were given, and future research directions were outlined.

The purpose of this article is to analyze the current state of research in the field of fuzzymulticriteria optimization methods, as well as the development of aggregation operators and algorithmsusing fuzzy multicriteria group decision-making using an intuitionistic attitude of linguisticpreferences. The most well-known fuzzy methods of multicriteria optimization are presented:ELECTRE, PROMETHEE, VIKOR, TOPSIS, AHP, ANP, MACBETH, DEMATEL, Shoke integraland DEA, their features, applications and the most cited articles are considered. Most real optimizationproblems may have conflicting goals. The method of fuzzy multi-purpose decision-makingFMODM is also presented for situations where there are inaccuracies and uncertainty in somegoals and variables on which they depend; methods of fuzzy multi-purpose linear programmingFMOLP, fuzzy multi-objective target programming FMOGP and fuzzy heuristic decision-makingmethods. The problem of fuzzy multicriteria group decision-making during evacuation with anintuitive relation of linguistic preferences is considered. It is noted that fuzzy logic methods areparticularly suitable for making evacuation decisions when there is little data, knowledge ofcause-and-effect relationships is inaccurate, and observations and criteria can be expressed inlinguistic qualitative terms. The main stages of group making the best decision among alternativesin a fuzzy environment are presented: combining expert assessments; obtaining a final assessmentfor each alternative represented by a linguistic variable; ranking alternatives; group making themost preferred decision. An approach to group decision-making with an intuitive preference relationshipbased on aggregation procedures is proposed. The group model of decision-making andthe concept of fuzzy group decision and linguistic variables used in predicting an emergency situationand planning evacuation are considered. It is noted that the well-known operators of orderedweighted averaging OWA, LOWA do not take into account the weights of experts. The Low operatoris defined, which allows taking into account the weight values of experts, as well as an approachto determining a fuzzy group solution of aFCS as a type 2 set. Algorithms for determininga fuzzy group multicriteria solution based on aFCS are presented

The aim of the study is to improve the efficiency of high-level design of robotic systems in termsof management of computing and diagnostics of on-board computer software. Three problems areconsidered: assignment, scheduling and diagnostics. The first problem, the assignment task, is todetermine the necessary resources and build the distribution of program modules among the onboardcomputer processors in accordance with a given criterion. The article presents a mathematicalformulation of the problem, algorithms are given, and the presence of areas of effective dominance ofalgorithms depending on the selected criterion is shown. The second problem, the scheduling problem,is to determine the sequence of tasks in multi-channel systems in accordance with a given criterion.A mathematical formulation of the problem is given, algorithms and the results of their studyare given. A feature of the scheduling algorithms under consideration is the use of a unified approach,namely the concept of the dominance relation between processors and the construction ofsolvable classes of systems. The third problem is software diagnostics. The complexity of the task ofdiagnosing computer systems is determined not only by their high dimensionality, but also by themultiplicity of causes of violations. The source of violations of the computing process can be bothhardware failures and errors in the organization of calculations made by developers. The article usesa hierarchical approach, in this case, the components of the system, connected by an inclusion relation,are arranged in accordance with the level of complexity in such a way that the model of higherlevelcomponents is represented by a composition of lower-level models. For each level, own diagnostictools are synthesized, focused on failures of information links between the components of theprevious level. The article proposes an approach to test diagnostics using a network dynamic model,which involves the introduction of redundancy in order to simplify the diagnostic experiment andreduce the complexity of its preparation. This approach allows you to automatically synthesize diagnostictools and detect violations in the addressing of information exchanges when the software ofrobotic systems works as intended. Approbation of the algorithms under consideration was carriedout using software developed by the author at the stage of designing on-board systems at JSC «Concern«Central Research Institute «Elektropribor».

The effectiveness of the use of autonomous mobile robots largely depends on the motion controlsystem. For a crew car, the question of selecting the optimal driving speed is decided by the driver. Thespeed of movement of autonomous robots, especially over very rough terrain, is significantly lower andthis is caused by the operation of an autonomous control system. In tracked chassis, one of the componentsof speed is known to have such a property as agility, which characterizes the controllability of avehicle under specified conditions. The aim of the study is to increase the efficiency of automatic controlsystems (ACS) for the movement of ground-based robotic systems for military purposes (RTK VN) on thecourse based on the application of the method of two-circuit systems equivalent to combined. The use ofautomatic control systems equivalent to combined systems makes it possible to increase the accuracy ofautomatic control systems by reducing the value of the dynamic error, that is, achieving error invariancewithout violating the stability of the system. The objective of the study is to experimentally determinethe dependences of the steady-state value of the error of reproducing the angle of the course withconstant and linear input influences in single-circuit and double-circuit automatic motion controlsystems of the RTK. In the course of the work, it was proposed to draw up structural diagrams ofautomatic traffic control systems of the RTK VN along the course angle, based on structural diagramsto develop models for conducting experimental studies of the proposed approach by computermodeling methods. In the course of the study, it is proposed to analyze the accuracy of reproducingthe angle of the course based on the data obtained as a result of modeling. As part of the ongoingwork, the task of building motion control systems for autonomous mobile tracked vehicles and robotsis considered. A model of the automatic motion control system of tracked RTCs is proposed based onthe application of the method of two-circuit systems equivalent to combined ones. The simulationresults confirm the efficiency of the proposed approach and show that it is possible to obtain improvedindicators of the functioning of the control system in terms of accuracy and efficiency.The method proposed in the article allows us to solve the problem of improving the efficiency of theRTK motion control system along the course angle in offline mode.