Keywords: syntax analysis, legal papers, bottom-up parsing, token concatenation, text analysis, natural language, semantic network, algorithm
The need to automate the decision-making process on legal issues in various fields of human activity determines the relevance of this work. In this regard, this article is aimed at disclosing an approach to organizing the process of parsing texts in natural language for the automatic construction of a semantic network corresponding to the given input documents. The subject area is the field of legal information. The approach proposed by the authors opens up wide possibilities for the semantic analysis of legal documents and their comparison with each other. The article discusses the organization of the process of bottom-up parsing natural language texts for the further automatic building a semantic network. The authors propose the text parsing algorithm. Its results are applicable for the further formation of the knowledge base on the available texts of legal documents. Semantic networks are supposed to be used as a model for representing knowledge, which opens up broad prospects for the automation of legal information processing. In addition to solving the problems of making decisions on legal issues that are often encountered in practice, the considered approach will automate the solution of such a time-consuming task as the automation of the legal examination of regulatory legal acts. The implementation of this procedure is necessary in order for the adopted regulatory legal acts to comply with the principles of admissibility and legality of their inclusion in the current system of law.
Keywords: syntax analysis, legal papers, bottom-up parsing, token concatenation, text analysis, natural language, semantic network, algorithm
Currently, orthopedic surgeons do not have information about what loads on the bone-implant regenerate system are permissible at the stage of regeneration and do not lead to the destruction of the newly formed bone tissue. The general approach to the construction of computer models of complex structural formations of the musculoskeletal system is considered on the example of reconstruction of the ulna in a fracture, of a foot in an ankle fracture and varus deformity of the toe and pathology of the cervical spine. An approach to the construction of meaningful models has been substantiated, the possibility of a personalized approach in the construction of CT and MRI geometric computer models of biological objects in the Mimics program, which allows converting the object into the Solidworks program, has been illustrated, and the calculations of stresses, displacements and deformations in the considered models in the SolidWorks Simulation program have been performed. Since there are no studies in the available literature for all considered biological objects with implants, a comparative analysis of the calculation results was carried out for the most complex of the considered models - the cervical spine is normal. The constructed models can be used for biomechanical assessment of the state of the structures of the musculoskeletal system at different stages of reconstruction.
Keywords: computer model, content model, reconstruction, ulna, foot, cervical spine, fracture, varus deformity, stress, displacement
Infocommunication networks provide the base structure for analysis, processing and transmission of information. Main principles networking and infocommunication networks technologies is independent from type of destination. Therefore, infocommunication networks can be used for dual-use (civil and military purposes). In any case, traffic distribution analysis of infocommunication networks allows to estimate a quality of service of information streams for providing such properties of special-use infocommunication networks as: timeliness of information delivery, promptness, sustainability and continuity of communication. Application of different types of modelling to traffic distribution analysis provides ample opportunities for estimation of infocommunication networks projects under development that it increases the level of practical feasibility of these projects. In this work the tensor analysis of networks is used for modelling of traffic distribution in special-use infocommunication network. The investigated object is the multilevel infocommunication network with several levels: the level of gathering information, the aggregation level, the level of preliminary processing, the level of information centers. The mesh and node tensor models are used for the estimation of mean delay of networks routes. The joint application of two methods of tensor modelling allows to formalize the process of estimation mean delay for set of network routes. In result, the routes with maximal mean delay were determined for infocommunication network of special-use and the conclusion was made about necessity of optimization of traffic distribution to reduce time delay.
Keywords: traffic distribution, infocommunication networks, tensor analysis of networks, special-use network, mean time delay
At present, the introduction of computer networks with dynamic topology is becoming a ubiquitous phenomenon. In everyday life, we often encounter them without knowing it. Mobile, road, sea and air dynamic networks are everywhere, and their distinctive feature is the constant change in the structure due to the constant updating of the end nodes in the network. Due to such a wide spread in these networks, there are a sufficient number of security threats both at the hardware level and at the software level. Such threats cannot be ignored. In this regard, this paper is devoted to the consideration of the main threats of security breaches at the software and network levels in networks with dynamic topology and the problems that arise when training a deep neural network to detect these threats. The analysis of the problems of training deep neural networks is carried out and the method of their elimination is proposed using the studied methods of solving such problems. As a result of the practical implementation of the technique, it is possible to obtain a properly trained neural network that will effectively detect security threats in real time.
Keywords: computer network, dynamic topology, neural network, security threats, deep learning
the study of new types of electric machines with improved electromechanical characteristics requires a huge amount of calculations, while the analysis of the optimal ratio of certain parameters is a multi-criteria task, which does not always have the only correct solution that satisfies all the tasks set. The relatively recent appearance and application in actuators of new types of small-sized electric machines based on windings with complex geometry of the active part excludes the possibility of classical planar modeling, but three-dimensional modeling requires significant computational and time resources. in this regard, this study is devoted to the analysis of the possibility of using discrete modeling of complex objects with the possibility of optimizing the properties of the object under study. in the course of the study, an analysis of the structural design of the modeling object was carried out, followed by the formation of an array of discrete models. The formation of this type of modeling was justified based on the condition of the absence of sharp structural and structural changes in the object under study. the simulation was performed in the ANSYS environment by generating a script file in the APDL language. the results of the study demonstrate the possibility of carrying out this kind of modeling in relation to the rhomboid brushless direct current motor with the possibility of optimization according to a certain criterion. although the presented model has a number of assumptions and is not yet fully capable of replacing three-dimensional modeling, the materials of the article are of practical value for software developers aimed at analyzing the physical state of electrical machines.
Keywords: BLDC, winding, diamond shape, discrete modeling, three-dimensional modeling, aPDL
A significant growth of the number of information sources requires an appropriate increase for the channel and communication links capacity. However, with consideration of the physical and geographical conditions of the Russian Federation, it is can not be always possible to develop a terrestrial communication infrastructure. If the terminal devices are located at a significantly distance from the fixed telecommunication network, it is advisable to use broadband radio systems to transmit the required amount of information. Currently, high speed Ka/Q-band satellite systems are being created in Russia and around the world using geostationary communication satellites. These systems serve wide areas, providing subscribes with broadband access services to remote information and telecommunication resources. This is achieved through the use of multibeam antennas, which provides a high effective isotropic radiated power and quality factor of the satellite receiving antennas in extended coverage areas, and thus creates conditions for the use of relatively simple subscribers terminals. Besides, one of the ways to increase the capacity of radio links for various purposes is to use spectrally efficient digital transmission methods. Thus, DVB-S2 channels, used in the forward satellite links use amplitude phase shift keying (APSK). In this paper we obtain a mathematical expressions for calculating error probability of an uncoded 16APSK and 32APSK signals. The analytical results are interpreted in terms of the signal-to-noise ratio (Es/N0), which allows forecasting the quality of radio channel for data transmition and forward satellite link availability of high-speed satellite communication systems.
Keywords: amplitude phase shift keying, constellation diagram, signal detection, error probability, radiocommunication
Having half a century of experience in the design and operation of marine nuclear power plants, when designing new installations, the struggle is for increased resource characteristics of equipment and, in particular, the resource of the reactor core. To achieve the desired result, a deep analysis of all physical and chemical processes occurring in the main equipment of the reactor plant is carried out. An important role in this work is played by the study of transient thermohydraulic processes. Such processes are inertial and introduce oscillatory perturbations of the first order of smallness into the system. It is also important to investigate systems for dynamic stability. This aspect of the study is important not only for ship installations with their inherent maneuverability, but also for large-scale power units. Analysis and research of mathematical models is a difficult process, because even for the simplest two-circuit installation, such a model will consist of several nonlinear differential equations. In this case, it is advisable to use either numerical methods or simplified mathematical models. To study the transient thermal-hydraulic processes in this work, an experimental stand FT-100 was used, which is a model of a two-circuit installation. Several nominal operation modes were implemented. The results obtained are checked for agreement with the simplest mathematical model, and can serve as a starting point for further calculation of the installation parameters. Also, the value of the obtained data array lies in the possibility of verifying the calculated codes of dynamics and automatic control systems. These codes are a valuable tool in design, and obtaining new experimental data helps to increase the accuracy of the calculation.
Keywords: transient processes, dynamic characteristics, model of a nuclear plant, experimental modeling
The danger of the spread of the COVID virus disease is due to propagation of the exhaled virus cloud in the natural conditions of human habitation. Modeling the spread of a viral cloud of airborne droplets makes it possible to assess the conditions for limiting its spread. Mathematical tools and software modeling tools are used to obtain a dynamic picture of the spread of the virus cloud. The results of software modeling of SARS-COV-2 virus spread in air in the form of aerosol saliva particles <5 microns formed by infected person breathing are presented. The comparative sizes of aerosol particles of the exhaled air-drop mixture and smoke particles in the air are given. A conclusion is made about the thermodynamic convection process of aerosol cloud propagation in the air. The software model is developed on the basis of the Laplace equation with zero boundary conditions and initial conditions – an instantaneous source in the center of the volume. The simulation is carried out and conclusions are drawn about the influence of temperature on the flash attenuation. Assumptions are made about the need to use an absorbing material to reduce the flash attenuation time. From theoretical and practical points of view, it is determined that the process of SARS-COV-2 propagation in the air is caused by diffusion and convection process of the air-drop mixture flow in the air. Such a flow is similar to the spread of smoke and fog in the air. The study takes into account physical phenomena such as diffusion and convection in the air.
Keywords: SARS-COV-2, software modeling of diffusion, airborne propagation, virus, convective diffusion
Oncological diseases are widespread at present time. Mathematical modeling for these diseases provides an answer to the question of a person's expectancy of life depending on a certain therapy. The paper provides a brief analysis of the functional load of cancer stem cells in the general system of the cancer cell population. This analysis includes consideration under conditions of an immune response and external influence (chemotherapy). The neoplasm growth modeling and the immune response to the disease, a model of the growth of a neoplasm during immune response and chemotherapy are proposed taking into account the approaches outlined in the literature. Mathematical models of neoplasms based on the positions of the clonal concept (Burnet's theory), which take into account the growth of cancer (dividing) cells, the response of the immune system, and drug therapy, these models are described by the Cauchy problem for a system of ordinary differential equations. The dynamics of tumor growth are determined based on the model. The model of disease stages is based on the distribution of the main parameters that determine the kinetics growth of the dividing cells population. An estimate is given of the average time to reach four stages of the disease and the duration of remission after the end of treatment using a statistical approach. The obtained theoretical results are compared with the data of the Russian Population Cancer Registry.
Keywords: mathematical modeling, steady state, sustainability, neoplasm, chemotherapy
In the context of digital and technological challenges, changes in relations between market participants, modified types of information security threats arise, the sources of which are innovative financial services and their combinations. Such types appear due to the recent trend of transforming traditional service models into financial ecosystems, essential in the financial sector's evolution. In the context of information / cyber security risk, the product of the financial ecosystem should be defined as an architecturally complete information and communication technology that meets the needs of the organization's client with the presence of predefined and implemented useful properties. The transformation of information security risk factors inevitably affects the need to revise approaches to risk assessment, focusing on information security specialists on digital financial services - products of financial ecosystems. The task of assessing the information / cybersecurity risk of a product of a financial ecosystem is not so much predicting the future state of the product itself or the financial ecosystem, but deliberate management within the framework of the implementation of specific scenarios. The research topic is devoted to describing certain aspects of the new model of information security risk management in the development of financial ecosystems. The problems of using the classical model of information / cyber security risk analysis are considered. A risk assessment method is proposed that takes into account the peculiarities of the heterogeneous environment of financial ecosystems and the dynamics of risk factors.
Keywords: ecosystem, transformation, information security, cybersecurity, information security risks, key risk indicators, digital profile, financial ecosystem, digital technologies
In order to determine the optimal algorithm and methods for assessing damage in the event of the implementation of information security threats in special-purpose communication networks, the existing approaches to solving this problem are considered and analyzed. The quality of threat recognition by the adaptive recognition system can be assessed in the form of prevented damage during the implementation of a conflict impact on the communication system. For this, it is advisable to use a standard model for the implementation of threats of conflict impact on the communication network, based on a four-stage strategy of conflict interaction. Using the expression obtained in the work, it is possible to assess the quality of threat recognition by the adaptive recognition system in the form of prevented damage during the implementation of the conflict impact on the communication network. An assessment of the reaction time of a complex of countermeasures to the implementation of threats to information security of a special-purpose communication network in the context of the implementation of centralized and decentralized control has been carried out. The resulting family of dependencies, for specific networks and given technical means, makes it possible to estimate the time parameters of the proposed adaptive routing algorithms, or, according to the specified requirements for control efficiency, form requirements for the performance of technical means of the control system. From the given dependencies it follows that for the considered computational procedures of routing algorithms, the decentralized control method for most types of structures is preferable according to the criterion response time, regardless of the performance of technical means. However, there are such structural characteristics of networks for which the advantage of one or another routing algorithm depends on the ratio of the performance of the technical means of the control system.
Keywords: countering information security threats, special purpose communication networks, an integrated approach, information security threats, damage assessment
Modern forms of education in higher educational institutions determine the increased load on the servers of higher educational institutions. This is especially true for video conferencing systems implemented on the basis of the University's information infrastructure. To improve the reliability and stability of these systems, it is necessary to analyze the load distribution on the system as a whole and its individual components in accordance with the existing schedule. The main task of the article is to predict the load peaks, which are determined by the graph, but also depend on a number of random factors. The article proposes a dynamic model that simulates the formation of the load on the servers of the video conferencing system depending on the available schedule of classes, taking into account random factors. The solution of the problem of modeling and predicting the behavior of a dynamic system is based on the use of the stochastic apparatus of Petri nets with priorities. As an additional mechanism for ensuring the adequacy of the model, the time intervals of Petri net transitions are determined, within which they can be active, which allows you to link the functioning of the entire network with real time intervals in the class schedule. The adequacy of the proposed model is proved by the correspondence of the predicted load servers distribution based on the results computational experiment to real video conferencing system data
Keywords: video conferencing system, petri net, server load, stochastic modeling, random factors
Informational training system contains visual, generalized, structured material on mechanical stability, accidents and ecological-biological peculiarities of the main types used in landscaping in the city of Donetsk: taxonomic position, biology and ecology, biogeography, representation in the city of Donetsk, the mechanical resistance and the accident rate, wind resistance, root system, different properties of wood, critical age in the city of Donetsk, the presence of the saw cut/core in xiloteca, recommendations for landscapers, landscaping concepts, publications, photographs. The informational training system allows to the researcher to quickly and visually get acquainted with the ecological and biological features of tree species used in gardening in the city of Donetsk, learn how to assess the general condition of the tree and use this knowledge in the future when conducting monitoring environmental and dendrological studies. This information system summarizes the results of russian and international research on the ecological and biological characteristics of the presented species and supplements them with growth characteristics, physical and mechanical properties of wood, mechanical resistance to dynamic (wind) and static (icing, snow sticking, etc.) loads in a large industrial city. The information system contributes to the implementation of the presented results in the educational process (as a methodological guide for students and postgraduates of biological universities), monitoring studies of the state of the environment and assessing the accident rate of woody plants by «Zelenstroy» services, as well as by employees of the city environmental management.
Keywords: database, mechanical stability, accident rate, ecological and biological features of species, woody plants in the urban environment
The paper presents an overview of modern methods for monitoring of the state of structural elements of power transmission lines (PTL) by processing images in the infrared, ultraviolet and visible spectra. Methods for recognizing of the main structural elements of power transmission lines and detecting the most characteristic defects for them, based on the determination of distinctive structural features (color, shape, borders, brightness gradient and texture), are considered. Insulators, wires, supports and fittings are considered as the main elements of power transmission lines. The analysis of the efficiency of the considered methods and approaches was performed based on the comparison of the metrics presented in the source data: values of the proportion of correct recognitions (accuracy), accuracy (precision) and recall (recall). Particularly relevant is the analysis of methods for monitoring structural elements of power transmission lines based on images obtained not only in the visible, but also in the ultraviolet and infrared spectra. Methods for image processing in the visible spectrum are based on deep and machine learning algorithms. The ultraviolet spectrum (UV) is used to detect corona discharges on wires and insulators. Imaging in the infrared spectrum (IR) enables to identify defects in power transmission lines that cannot be revealed in images in the visible spectrum, for example, hotspots. As a result of the analysis, the methods for detecting power line defects with the highest efficiency for the visible spectrum were considered: GVN, HOG + SVM, SSD, Grab cut, cascading CNN, LBP-HF + SVM, DMNN, VGG-19, LBP + ULBP, YOLO v3, DELM + LRF, SVM, Faster R-CNN, CNN, stereo vision + PLAMEC. The detection method with the highest efficiency for the IR spectrum is "Otsu + Threshold Processing", and the SVR method shows the highest efficiency for the UV spectrum.
Keywords: unmanned aerial vehicle, inspection of high-voltage power lines, fault detection, defect detection, spectral image analysis
The problem of identifying the state of a technical system based on signals coming from it is considered, each state corresponds to a class of signals with certain properties, which is relevant in the field of pattern recognition, technical diagnostics and other areas of science and technology. To solve it, the belonging of the incoming signal to one of the selected classes is determined. To describe a random signal and mathematical representation of classes, a Markov model of a random process is used, on the basis of which an optimal signal classification algorithm with a given reliability has been developed. Values (decisive statistics) are obtained, according to which a decision is made about the belonging of a sample of samples of the received signal to the corresponding class and which allow us to estimate the "distance" between the classes (their models). Their study allows one to evaluate the capabilities and efficiency of signal classification algorithms, as well as the properties of a set of classes by their Markov models. With the use of information theory, the properties of decisive statistics are investigated, their probabilistic characteristics are determined. Using the concepts of entropy and information divergence (Kullback-Leibler distance), estimates of the mean value and variance of the decision statistics are obtained. Estimates of the duration of the classification procedure are obtained. An example of calculation is given. The research results can be used to determine the state of technical devices (engines, turbines, etc.) based on incoming signals from sensors placed on them, when classifying radio signals in radio monitoring systems and other scientific and technical applications.
Keywords: signal, classification, markov model, entropy, information divergence
The main approach to solving problems in programming courses often consists of writing and testing individual parts of an algorithm written in a particular language. Students make several attempts to submit the problem to the testing system, each of these attempts reflecting an individual solution state. Usually, to determine the student performance, the average number of submissions to pass the solution or focusing on time taken to complete the problem correctly is calculated. Such metrics are usually not robust, because the time to correct individual errors significantly affects the total time to solve the problem. Also, these metrics do not reflect what the student does not understand in the theoretical aspect. This article proposes a metric based on the probabilistic distance between an observed student solution and a correct solution. As part of the experiment, a group of students solved problems in an online programming environment. Their submissions were evaluated against a model of the algorithmic component necessary for a correct solution. A Markov Model was used to generate problem state graph, connecting program states. The proposed metric of the probabilistic distance to solution was applied to the graph to determine the distances from each solution to the nearest correct ones. The results showed that this metric is useful in determining the distance if the path to the correct solution was typical and consistent with the studied theoretical material. The article provides details of the implementation of the metric of probabilistic distances to the solution and a plan for further research based on current observations.
Keywords: intelligent tutoring system, programming courses, automatic feedback, educational data mining, learning analytics
The article deals with the problem of management in network organizational systems within the framework of implementing a modern leadership strategy. The classification order of the objects included in the system allows the use of structural transformation mechanisms according to the position in achieving the goal determined by the control center. The objects taking the leading positions are united into the top classes. This makes it possible for the management centre to allocate targeted resource support to the objects featured with an advanced development trend. To ensure the stability of such a trend for the forecast calendar periods, an intra-object distribution of resource provision is carried out between priority management channels and responsibility centres in the expenditure of the allocated funds. The main components of information support used for making management decisions are presented. The authors offer a multi-stage algorithm for controlling the intra-object distribution of resource provision, based on the expert assessment methods and the application of an optimization approach premised on Boolean programming problems. The stages are integrated into a single structural scheme providing the formation of management decisions on the optimal distribution of the target resources between management channels, responsibility centres and economic classification items.
Keywords: management, organizational system, structural transformation, classification ordering, expert assessment, forecasting, optimization
This article discusses the relevance of developing educational mechanisms in the learning process and in the game. The main stages of the game, the types of quests, player control features are considered. The main scripts and objects that help to assimilate the material are analyzed. An attached scheme for the interaction of game objects and game characters. Reasonable time limits for one test task are given, as well as the main parameters for obtaining the final grade based on the results of B_total. Based on the assessment system, an algorithm is proposed for the student knowledge assessment system, fixing the main stages of the testing system. Based on the algorithm, an educational game is proposed with the aim of setting out historical references about ancient Ireland and testing the player’s knowledge with the help of implemented game mechanics. In addition, various approaches to assessing effectiveness are considered, and in the case of the introduction of an educational game in an educational institution, the following factors are taken into account: increased involvement, time for mastering the material, and information assimilation. At the end of the article, a conclusion is drawn on the effectiveness of the use of educational games.
Keywords: assessment, assessment, mathematical model, algorithm, game mechanics in training, game creation
In this paper, the aim of the study is to increase the speed and the number of solutions in intelligent systems based on genetic algorithms aimed at solving the problem of structural and parametric synthesis of large discrete systems with a given behavior. algorithm directly in the process of solving the problem of structural-parametric synthesis. Management can be carried out on the basis of data on the state of individuals in the population. In the work, as a methodology, it is proposed using the mathematical apparatus of artificial neural networks and genetic algorithms, adapted to the problem being solved using the theory of Petri nets. The proposed approach, united by one mathematical apparatus of Petri nets, allows one to model: the process of recognizing the state of a population, the procedure of structural-parametric synthesis of large discrete systems with a given behavior, as well as control of the genetic algorithm in order to correct the trajectory of the population movement, prevent attenuation and premature convergence. The article proposes the results of computational experiments that have shown the effectiveness of the developed models and methods in solving the problem of structural-parametric synthesis of large discrete systems with a given behavior based on static intercomponent connections.
Keywords: artificial neural networks, genetic algorithm, intelligent information systems, theory of Petri nets, structural-parametric synthesis, gPGPU technology
Currently, there is a growing interest in dynamical systems of non-integer order. The development of the theory of fractional powers has aroused interest in the use of non-integer orders in control and regulation problems, in which the object of regulation and the controller are described by models of non-integer orders. Fractional order calculus offers flexible numerical capabilities that can be applied in the design of control systems. However, before the results of theoretical research can be transferred to industrial installations, it is important to study the effects of fractional flow controllers using laboratory experiments and simulations. This article discusses the concept of a fractional PID controller that includes an integrator and a non-integer order differentiator, and analyzes its behavior and characteristics. Practical aspects of setting up and implementing fractional order controllers for the paper web weight control system using FOMCON (a set of MATLAB tools for identifying and managing fractional order systems) are considered. The paper presents an example of implementation of PID controllers of fractional order for the control system of the pressure device of a paper machine (BDM). The results of modeling using classical PID controllers and using PID controllers with fractional powers are presented.
Keywords: mathematical modeling, paper machine (PM), fractional calculus, fOMCON, pI-controller, pID-controller, design of control systems, automatic control, mATLAB tools
Мodern software is quite widely presented in various spheres of life in our country. The software is characterized by many features. If we compare the stated characteristics of software of computing complexes from different producers, the most of the elements of comparison, especially quantitative characteristics, are turned out to be quite close to each other, and the objects of comparison are almost identical. There is an urgent task to select the best object from several identical ones for further researches. This is especially actual if the comparison of the quantitative characteristics of the software does not produce the desired results. Then the problem should be solved with the help of experts to evaluate the qualitative characteristics and using the appropriate mathematical methods that justifies the scientific meaning of the chosen approach. In this work, high-quality software metrics are proposed to investigate . In particular, one of the qualitative characteristics of the software that can be evaluated by users without much difficulty is practicality. To study the characteristics and metrics of practicality, the work proposes to use expert and statistical procedures, which are combined in the expert statistical method. Questions of organization of expert survey for assessment of practical characteristics are covered, method of statistical processing of expert data is presented, procedure of selection and analysis of mathematical model of complex indicator of software practicality quality is investigated. The further development of the ideas set out in this article will be the development of software for expert and statistical procedures in assessing the quality metrics of software.
Keywords: practicality, software of computing complexes, expert and statistical method, quality metric, complex quality indicator
Software has already become an integral part of the life of any society. In the modern world, the functioning of any complex systems and complexes means interaction with the corresponding software. To solve this complex problem in one department manufacturers sometimes offer identical software options for computing complexes. Since the selection of optimal software involves considerable financial costs, the problem cannot be effectively solved without the involvement of experts in this field. In addition, the views of experts operating the software using a scientific approach are not currently taken into account, especially when assessing qualitative metrics that characterize its practicality. In this work, it is proposed to consider an alternative approach to assessing the quality characteristics of software during its operation and choosing the optimal software product from a certain set of analogues, based on the study of expert data. To solve this problem, the work proposes a method of forming a group of experts, presents an alternative method of assessing the consistency of expert opinions based on a metric coefficient, presents a method of forming a system of qualitative indicators of software based on the sign criterion, presents an algorithm for evaluating the quality of software of computer systems based on the analysis of expert data. The development of software for the implementation of the presented algorithm will be the development of the ideas set in this article.
Keywords: software of computing complexes, quality assessment, quality characteristics, consistency of expert opinions, integrated quality indicator
The article shows the relevance of the problem of specialization of senior students on the example of bachelors of the training direction 10.03.01 "Information security" and its specificity. Every year, technical areas of training are becoming more and more popular among applicants, while about 30% of applicants to universities in the Russian Federation do not cite a conscious choice of an engineering profession as the reason for their choice of technical areas. The results of surveys and focus groups among graduates of the studied specialty showed that the majority of them do not continue to work in their specialty. Data are presented that indicate the need for the selection of methods based on the analysis of the psychological properties of a person in order to orient senior students to the most suitable specialization for them in terms of not only their professional competencies, but also psychological characteristics of the personality in order to avoid the syndrome of professional burnout. For this purpose, a methodology was selected and described to identify the most suitable specialization for a student and software that implements the methodology in the form of a web application for students and university staff, as well as the results of testing its applicability in one of the Russian universities.
Keywords: information security, education, personality, specialization, professional burnout, automation of career guidance
When constructing regression models, the problem of choosing a structural specification is paramount. To date, a great variety of such specifications have been developed. This paper provides a brief description of the following forms of relationship between variables: linear regression, linear elementary regression, linear multiplicative regression, Leontief production function, and index regression. Due to the mixing of linear and piecewise linear regressions, a new specification has been formulated - linear non-elementary regression, in which regressors are both input variables and binary operations of all possible combinations of their pairs. It is shown that the assignment of specific values to certain parameters of such models makes them quasilinear, which makes it possible to estimate them using the ordinary least squares. Areas of definition of these parameters are established. An algorithm for approximate estimation of linear non-elementary regressions using the ordinary least squares is developed. The operation of the algorithm is demonstrated by the example of modeling electricity consumption in the Irkutsk region. The quality of the constructed linear non-elementary regression by the coefficient of determination turned out to be higher than that of the previously obtained models. It is shown that in linear non-elementary regressions, the nature of the influence of input variables on the output changes over time.
Keywords: regression model, leontief production function, linear non-elementary regression, ordinary least squares, electricity consumption
Despite the emergence of new modern medicines, mortality rates from essential hypertension remain high. This problem is since a combination of several groups of medicines is required to effectively treat this disease. The aim of this study is to develop models for the automated selection of medicines for the treatment of hypertension based on the individual characteristics of the patient, as well as to assess the effectiveness of the prescribed treatment based on the available clinical indicators of patients and the proposed combination of drugs. The original dataset contains depersonalized information on 262 patients of the cardiological hospital for 66 clinical parameters. Six groups of drugs were considered: BAB, I-ACE\ARA, CCB of the nifedipine group, CCC of the verapamil group, diuretics, centrally acting medicines. Machine learning techniques have been used to identify determinants that contribute to the success of drug treatment for hypertension in each sample of patients. During the study, to achieve this goal, several machine learning models were built to solve classification and regression problems. The highest accuracy was shown by the gradient boosting models XGBOOST for the classification problem and CATBOOST for the regression problem. Based on the results of the study, it can be concluded which clinical indicators are most significant for effective treatment with each of the medicines under consideration.
Keywords: machine learning, gradient boosting, decision trees, random forest, arterial hypertension, arterial pressure
This article examines and describes the process of constructing an algorithm of actions - a scenario for searching, detecting and extinguishing a fire in a forest with unmanned aerial vehicles, developed at the initial stage when designing the operation of heterogeneous unmanned aerial systems in an automatic mode in order to optimize the solution of an urgent problem aimed at preserving flora and fauna, by the forces and means of the Ministry of the Russian Federation for Civil Defense, Emergencies and Elimination of the Consequences of Natural Disasters. The developed scenario makes it possible to achieve the solution of this problem by the forces of a heterogeneous unmanned aircraft system. Based on the experience of units armed with and actively operating unmanned aerial vehicles, limitations for the considered simplified scenario have been developed and described. This scenario was investigated using a mathematical apparatus, namely, a multicriteria optimization problem was built, which allows calculating the optimal number of unmanned aerial vehicles used, the total time for examining and extinguishing a fire, and the cost costs associated with trees in areas of fire that have not been extinguished.
Keywords: unmanned aerial vehicles, unmanned aviation systems, operation restrictions, scenarios for the use of unmanned aerial vehicles, multi-criteria optimization problem
Cloud computing is a powerful computing technology that provides flexible services to the user anywhere. Resource management and task planning are the most important perspectives of cloud computing. One of the main challenges of cloud computing was scheduling tasks. Typically, task planning and resource management in the cloud is a complex optimization task while considering quality of service requirements. Huge work within task planning focuses only on issues of deadlines and cost optimization, and avoids the importance of availability, reliability, and reliability. The main goal of this study is to develop an optimized algorithm for efficient resource allocation and planning in a cloud environment. This study uses the PSO and R-factor algorithm. The main purpose of the PSO algorithm is to have tasks scheduled on virtual machines to reduce latency and system throughput. PSO is a method generated by the social and collective behavior of swarms of living things in nature, and in which particles search for a problem space to predict a near-optimal or optimal solution. A hybrid algorithm has been developed that combines PSO and R-factor in order to reduce processing time, make the gap and the cost of performing the task at the same time. The results of tests and simulations show that the proposed method is more effective than previously common approaches.
Keywords: сloud computing, resource allocation, particle swarm algorithm, task management, modeling
The design of a column for contacting gas or vapor with a liquid has been developed, which allows increasing productivity by improving the surface of contact between phases. Previously known and recently developed designs of mass transfer columns do not meet the requirements for achieving the required technical result. This is due to the small area of creation of the phase contact surface, which leads to insufficient mass transfer on the surface of the liquid layer formed between the elements of the column trays, which reduces productivity. Therefore, it is proposed to carry out an axisymmetric annular multi-row installation of S-shaped elements with a vertical partition around the circumference with the same gap between adjacent rings, which will increase the surface area of the phase contact between the flowing liquid and the rising gas (vapor), and will contribute to the intensification of heat and mass transfer processes , will increase performance. To confirm the claimed technical result, comparative calculations were carried out on a computer according to the developed program, with known designs of plates with tunnel caps of the TST type for column apparatus with a diameter of (400-3000 mm). The design of the contacting column developed and the previously known standard bubble cap trays were simulated. Numerical modeling showed that the installation of S-shaped elements with vertical partitions around the circumference, axisymmetrically with the same gap between adjacent rings, in the gaps between which the overflow devices, which are tubes with a spray device, are evenly located, make it possible to increase the surface area of the phase contact between the flowing liquid and rising steam by 65%, and also allows to provide an increased rate of heat and mass transfer on the tray.
Keywords: mass transfer columns, contact devices, numerical modeling, trays, trays with S-shaped elements
The purpose of the study is to develop a method for the formation of criterion assessments of morphological features of technical systems based on the analysis of trends identified in the patent array. One of the common ways to generate new technical solutions or improve the functional structure of a technical system is the procedure of morphological synthesis. To evaluate a new synthesized technical solution, an urgent approach is the use of criterion assessments of its constituent morphological features (technical functions of system elements). As a result of the application of methods for extracting technical functions in the DGH format ("Action" - "Object" - "Restriction") from Russian-language patents and in the SAO format ("Subject" - "Action" - "Object"), a term document is formed from English-language patents. the matrix. The content of the term-document matrix is modernized on the basis of the developed algorithm for comparing technical functions, using statistical analysis of the patent array using Word2Vec technology (identifying contextual synonyms). A method for the formation of criterion estimates of technical functions based on patent trends identified by clustering a patent array based on a term document matrix has been developed. A method for determining the criteria-based assessment of the significance of a technical function in the future time period by means of forecasting time series based on the ARIMA method has been formed.
Keywords: morphological analysis, dGH, sAO, patents, fact extraction, trend, aRIMA
The problem of synthesis of a statistical algorithm constructed in a subclass of discrete-continuous random processes designed to predict and detect the beginning of a DDos attack by analyzing changes in the intensity of received traffic is considered. To analyze and identify threats to the security of computer networks, there are monitoring systems that focus on analyzing traffic, packets, and protocols. All of these systems are vulnerable. Almost all levels of the object's OSI model, which is defined as any type of server or selected applications, are subject to attack, but the first sign of an attack is abnormal behavior of input traffic. Promising techniques to ensure safety of the COP include methods based on the detection of the deviation by the change of probabilistic data parameters. Their essence is to determine changes in the statistical characteristics of data flows. The developed algorithm allows not only detecting a network security threat, but also.
Keywords: computer network, security threat, discrete-continuous random processes, security monitoring, recurrent algorithm