Keywords: simulation, reconfigurable manufacturing system, complex structured object, software package, optimization, queuing system, anylogic
Currently, in the field of industrial production, there is a gradual transition to a new stage of development, called Industry 4.0. The basic concept was first presented at the 2011 Hannover exposition. The main process in an industrial plant according to the Industry 4.0 concept is the digital transformation of a physical manufacturing system into a reconfigurable digital one. Reconfigurable manufacturing systems are the latest advancement in production system development. The most important characteristics of reconfigurable manufacturing systems are the high adaptability of hardware and software components to respond to constantly changing market requirements for the type and quantity of products. The software package presented in this paper is intended for simulation of complex-structured systems. The application area of this package mainly includes reconfigurable manufacturing systems that provide the production of complex technical products with high constructive and quality indicators, comprising a wide range of components and parameters. The software package is based on a formalized description of the manufacturing system as a multichannel multiphase queuing system. At the same time, object simulation is based on typical models of working and assembly systems. The software package is developed in the object-oriented programming language JAVA using the AnyLogic simulation environment.
Keywords: simulation, reconfigurable manufacturing system, complex structured object, software package, optimization, queuing system, anylogic
Determination of the range of factors affecting the object of research is the most important task of medical research. Its solution is complicated by a large amount of diverse data, including extensive anamnestic information and data from clinical studies, often combined with a limited number of observed patients. This work is devoted to the comparison of the results obtained by various feature selection methods for the search for a set of predictors, on the basis of which a model with the best forecast quality was created, for solving the problem of binary classification of predicting the onset of pregnancy during in vitro fertilization (IVF). The data from the anamnesis of women, presented in binary form, were used as features. The sample consisted of 68 features and 689 objects. The signs were examined for the presence of cross-correlation, after which methods and algorithms were applied to search for a selection of significant factors: nonparametric criteria, interval estimate of the shares, Zcriterion for the difference of two shares, mutual information, RFECV, ADD-DELL, Relief algorithms, algorithms based on the permutation importance (Boruta, Permutation Importance, PIMP), feature selection algorithms using model feature importance (lasso, random forest). To compare the quality of the selected sets of features, various classifiers were built, their metric AUC and the complexity of the model were calculated. All models have high prediction quality (AUC above 95%). The best of them are based on features selected using nonparametric criteria, model selection (lasso regression), Boruta, Permutation Importance, RFECV and ReliefF algorithms. The optimal set of predictors is a set of 30 binary features obtained by the Boruta algorithm, due to the lower complexity of the model with a relatively high quality (AUC of the model 0.983). Significant signs includes: data about pregnancies in the anamnesis in general, ectopic and regressive pregnancies, independent and term childbirth, abortions up to 12 weeks; hypertension, ischemia, stroke, thrombosis, ulcers, obesity, diabetes mellitus in the immediate family; currently undergoing hormonal treatment not associated with the IVF procedure; allergies; harmful professional factors; normal duration and stability of the menstrual cycle without taking medication; hysteroscopy, laparoscopy and laparotomy; resection of any organ in the genitourinary system; is it the first IVF, the presence of any surgical interventions, diseases of the genitourinary system; the age and BMI of the patient; absence of chronic diseases; the presence of diffuse fibrocystic mastopathy, hypothyroidism.
Keywords: feature selection, binary classification problem, small data analysis, machine learning, assisted reproductive technologies
The paper deals with the application of the method of time series analysis to predict the cost of electricity and assess the state of insulation of power circuits of an electric locomotive. The proposed approach makes it possible, on a scientific basis, to plan the amount of funds allocated to pay for electricity, as well as to take timely measures aimed at restoring insulation and excluding the causes of fires that occur on locomotives. Time series analysis was carried out with the help of an application program that allows assessing the trend of changes in the indicators under consideration. A device for monitoring the state of insulation of power circuits of an electric locomotive is also proposed, in which the developed program for forecasting time series is implemented. Installing the device described in the work on the locomotive will allow timely assessing the current and predicted state of insulation, as well as taking timely measures to restore it. The urgency of the problem of diagnosing the state of insulation is due to the aging processes of fixed assets (machine tools and equipment) at industrial enterprises, which requires timely measures to restore the state of insulation of power electrical equipment. The application program is implemented in the MatLab package and is used to predict the cost of electricity. To expand the possibilities of using the application in other applications, the source code of the program was transformed into the code written in the high-level C language. The program obtained in this way is used in the PIC18F452 microcontroller to assess the state of the insulation of the power circuits of an electric locomotive.
Keywords: time series forecasting, singular spectral analysis method, singular decomposition, electricity cost, insulation condition
The article examines the characteristic changes in the staff activity in the conditions of digital transformation of organizational systems. It is shown that the changes are primarily related to the increasing role of the enterprise information system, which provides all types of interaction between the structural components of a new type of organization. With the functioning of the information system itself as a man-machine system, the importance of the effectiveness of staff activities increases. It is proposed to consider the process of staff performance management from the point of view of ensuring its adaptation to new labor functions in the conditions of digital transformation of organizational systems. The components of educational resources for basic and practice-oriented staff training are considered as management tools. The expediency of management decisions based on the optimization approach is proved. A sequence of tasks of reduction, aggregation-balance and resource optimization is formed, which allows you to choose a solution for a variety of thematic modules of preparation for performing labor functions in the conditions of digital transformation, taking into account balance and resource constraints. The resulting solution allows you to solve the task of managing the effectiveness of personnel activities, taking into account the types of activities and labor functions that differ significantly from the traditional ones.
Keywords: management, digital transformation, organizational system, optimization, educational resources
The problem of evaluating the quality of user interfaces of computer programs is considered. Indicators of the overal and relative information content of user interfaces are proposed, their mathematical model is developed, and analytical expressions for calculation are obtained. Most often, an indicator of the quality of user interfaces is understood as a function of the total time of elementary operations on its elements spent by the user to solve a specific task. Interface elements are understood as information interaction objects - input fields, icons, various types of lists, tables, and so on. Basic operations are understood as actions with them - finding, reaching, and managing. The entire set of elementary actions for solving a specific task is called the task profile. It is convenient to use time indicators to get generalized values of the interface quality indicator both in General and at each step of the profile (on the principle that the shorter the time or the number of operations, the better). But they answer the question "how much", not "why". Why, for example, can a task profile have a greater number of steps but a shorter execution time compared to a similar one? In General, interface elements make up a complex system with multidimensional relationships by belonging to a particular task, by importance, by frequency and method of use, and so on. Therefore, an attempt to randomly change the configuration of the monitor screen in order to optimize actions at a particular step may lead to changes in the time values at the remaining steps of the profile with unpredictable results. One of the ways to solve the problem of analyzing and/or optimizing interfaces is to develop quality indicators that operate on the characteristics of the overall layout of interfaces, in particular the number, size, and location of elements on the monitor screen. These indicators include the proposed indicators of overall and relative information content.
Keywords: computer program, user interface, analysis, quality indicator, indicator of overall information content, indicator of relative information content
The paper considers the issue of building a block hierarchy of software and information models that simulate the subject area in training systems, based on the principle from simple to complex, from elementary functions to more complex ones. This allows us to implement the principle of adaptability in training systems – the ability to manage the complexity of the training process depending on the competence of the trainee. An approach to the construction of a universal task constructor for training systems based on the representation of the training process in the form of changing a finite number of parameters of the training block by affecting it by the trainee is proposed. The training block in this setting is considered as a set of parameters of various types. A method for evaluating the training process is proposed, which involves checking the state of the block at the end of training, that is, checking whether the parameter values match the specified ones. It allows you to create flexible systems for evaluating knowledge. Correlation of certain parameters with the skills of the trainee allows automating the process of controlling the level of his subject competence and makes it possible to implement the principle of adaptability of training systems, which consists in a gradual increase in the complexity of the training process. A prototype of a universal task designer for training systems is presented. Its use significantly simplifies task editing, neglecting the use of programming environments.
Keywords: training, training, training process, training systems, simulator, task modeling
The article is devoted to evaluating the model of classification of images of bone marrow cells in the diagnosis of acute leukemia and minimal residual disease using a neural network. The experiment used a sample of 13 cell types: basophils, lymphocytes, monocytes, rod-shaped neutrophils, segmentonuclear neutrophils, eosinophils, lymphoblasts, myeloblasts, prolymphocytes, promyelocytes, normocytes, metamyelocytes, myelocytes. Images of bone marrow cells were obtained from preparations of the Laboratory of hematopoietic immunology of the N. N. Blokhin National medical research center of oncology. The description of cells was performed by twenty-six signs. Models of the used features are presented – the average values of the color components H, S of the color model HSB (H - color tone, S-saturation, B-brightness), morphological characteristics - area, shape coefficient, diameter, the ratio of the maximum distance from the center of mass to the edge of the object to the minimum; textural characteristics of the image area bounded by the cell contour for the spatial adjacency matrix - energy, moment of inertia, entropy, local uniformity, maximum probability for the color components R, G, B, and brightness value. Experimental tests of the classifier under consideration were carried out. The experimental sample contained 636 cells of thirteen different types. It was found that the use of the neural network model for the selected feature system provides 90% accuracy of classification of the studied cell types. The results obtained are of a preliminary nature. An increase in the training sample is required to increase the reliability of estimates in further studies, taking into account the cell types and variability of cell images.
Keywords: pattern recognition, image processing, microscopic analysis automation, acute leukemia diagnosis
Currently, special-purpose communications networks are widely used in government bodies, bodies that carry out the functions of the country's defense, state security and law enforcement. In connection with the features of the functioning of infocommunication systems and communication networks for special purposes, it must be borne in mind that they are deployed and provide management and interaction within the existing departmental and interdepartmental communication systems. The article proposes a model for the formation of a set of means to counter threats to information security in communication networks for special purposes. A description of such complexes is given, situations and grounds for their application are considered. Attention is drawn to the identification of common technological features of the formation of a set of means to counter threats to information security in communication networks for special purposes. To formulate requirements for complexes of means of counteracting threats to information security in communication networks for special purposes, a rule base has been compiled on the basis of which certain countermeasures will be selected. The authors modeled the functioning of a complex of countermeasures using the apparatus of linguistic variables and fuzzy expert systems. Based on the results obtained, requirements can be proposed for creating a set of means to counter threats to information security in special communication networks. The mathematical apparatus used in this article, based on the use of linguistic variables and fuzzy expert systems, can fully characterize the dependence of the effectiveness of countermeasures on the totality of implemented protective measures.
Keywords: countering threats to information security, special-purpose communications networks, integrated approach, fuzzy expert systems, security management
The article discusses current problems and tools for ensuring information security in network infrastructure. The author analyzes the current trends in information security breaches in 2018-2019, concludes about the relevance of countering threats related to unauthorized access to network resources and objects. A typical network infrastructure was analyzed, the main elements were identified: subjects, objects and access resources. The most important security elements are network and server hardware. The main sources of threats to network security violations are identified, a chain of threats to network security is compiled and described, the significance of threats is shown by sources of which are external and internal violators. An example of a network attack implementation scheme during exploitation of the BDU vulnerability: 2017-02494 is given. An approach to building network attack routes for an internal and external security intruder is proposed. It is shown that the network attack route represents the procedure for overcoming technical as well as logical devices containing security measures when implementing an attack on a network infrastructure object. An algorithm for constructing a network attack has been developed. The conclusion is drawn about the possibility of applying the approach to building a network attack route in the tasks of security monitoring, security assessment and planning of protective measures.
Keywords: vulnerability, network security, security event, attack vector, intruder
The article solves the problem of multi-aspect assessment of the quality of projects to ensure environmental safety of the complex of construction processes performed during the construction of buildings and structures. A system of quality criteria for projects of this type is formed, including one integral criterion and four complex criteria that characterize projects in terms of their relevance, feasibility, economic feasibility, realism, and twenty-six local criteria. All criteria meet the requirements of adequacy, completeness and sensitivity. They are systemic in nature and cover the main aspects of environmental safety of construction industries. Based on the use of multiplicative, additive, metric and dichotomous convolutions, formulas are written for evaluating the integral and complex quality criteria of projects to ensure the environmental safety of construction processes. An algorithm for multi-aspect assessment of the quality of projects of this type based on the use of these formulas is developed. The implementation of this algorithm in the practice of territorial environmental authorities will solve a number of topical issues, namely: to improve the quality of expertise of projects to ensure the environmental safety of construction processes; to encourage the introduction of digital technologies in the practice of organizing construction work; to unify legal, economic and technical mechanisms to encourage the introduction of "green" technologies in the work of construction organizations.
Keywords: construction, project, environmental safety, assessment, criterion, algorithm
Complex distributed systems are characterized by a large number of units and their constituent objects, geographically located at a considerable distance from each other. Therefore, when managing various aspects of their activities or functioning, analysis and processing of spatial information characterizing the location and relative position of subsystems and objects, as well as the space surrounding them, can significantly benefit. This article discusses one of the activities aimed at managing vulnerability by identifying and countering threats to public security in the territory of complex distributed systems with the help of video surveillance systems that provide information support to officials in organizing law enforcement activities. For a high-quality solution of these problems, the analysis and structuring of the necessary spatial and corresponding attribute information as part of the spatial information base and its processing as part of a comprehensive geographic information system were carried out. An approach to the formulation and solution of some problems on the placement of video surveillance equipment based on the set-theoretical description of its most important spatial characteristics is proposed. The solution to these problems can improve the quality of placement of video surveillance equipment and the necessary engineering infrastructure, taking into account the actual placement of both the cameras themselves and the observed objects, and taking into account obstacles. In turn, the high-quality placement of cameras will increase the efficiency of fixing the place and time of the incident and thereby allow quickly put forward the necessary forces and means to counter public safety threats, develop optimal extension routes, plan the areas of responsibility of the relevant services and plan the conduct of parry events in accordance with their location these threats.
Keywords: complex distributed systems, vulnerability, threat parry, video surveillance, visibility zones, spatial data, geographic information systems
The work offers methodological support for critical information infrastructure objects, which provides for the systematization of the basic steps for the formation of adaptive authentication algorithms, including using a biometric factor, which consists in checking the electroencephalogram of the access subject. The proposed approach eliminates the drawbacks of existing traditional authentication methods based on the use of explicit verification methods related to the fact that authentication characteristics are used to authenticate the user, which can be compromised by attackers. During the research, an authentication subsystem was implemented using the brain-computer interface. Despite the resistance to errors of the second kind, the insufficient results of the false access denial coefficient obtained at the stage of the experiment do not allow for the “seamless” implementation of such biometric authentication mechanisms in existing objects of critical information infrastructure. At the same time, the effectiveness of the adaptive mechanisms for checking the user profile formed on the basis of the approach proposed in the work indicates the possibility of their use on real objects using diverse factors and authentication criteria. Thus, in the framework of this article, one of the aspects of an integrated approach to ensure the security of the functioning of technological processes, as well as combating fraud and theft of information through the formation of adaptive authentication algorithms, was considered.
Keywords: authentication, electroencephalogram, neurointerface, critical information infrastructure, information security
Ensuring the functional safety of cyber-physical systems is a prerequisite for their implementation in areas in which reliable and predictable behavior of nodes of distributed cyberphysical control systems is a critical requirement. In the literature from the beginning of the 90s of the last century, within the framework of the theory of risk management, an approach to ensuring the functional safety of subject-centric systems is discussed. The conceptual basis of this approach is the provision on the inevitability of the presence of latent defects of different nature in complex technical systems, the activation conditions of which cannot be predicted. This implies the need to create barriers to the conversion of danger into an incident. The approach proposed in this paper to constructing a system of structural models based on the apparatus of conjugation schemes and truth tables of functional components should be considered from the perspective of information support for the formation of barriers. The basis of the approach to constructing structural models that allow performing a scenario analysis of the functional safety indicators of the nodes of cyber-physical systems is the apparatus of conjugation schemes and truth tables. It is shown that the proposed approach allows one to obtain models corresponding to Failure Tree Analysis, Root Cause Analysis, as well as a set of models obtained as part of the concept of profiles as particular solutions.
Keywords: functional safety, cyber-physical systems, reliability, information service, profile
The aim of the work is to improve the detection algorithms for remote control of a user session. Object of study - a system for detecting remote control of a user's computer. The subject of the study is data mining algorithms collected using tools and monitoring tools as part of the client side of the web application on the browser side, designed to analyze changes in the patterns of dynamic biometric features in the case of remote control. The approaches to detecting a remote connection are analyzed. The structure of the remote access detection system with a modern approach to the collection and analysis of the user environment in combination with machine learning methods has been developed. The experimental part of the work is based on an analysis of the user environment database, collected specifically for testing the software implementation of the developed algorithms. 16 different options for remote connection from an attacker to a user's device were considered. The obtained sample included 178 measurements with a different number of time intervals between intermediate points of the mouse cursor path. The highest efficiency was shown by the random forest classification algorithm with a group of features consisting of time intervals between mouse cursor movement events. The share of correct predictions was 93% on test data.
Keywords: intelligent analysis, user environment analysis, antifraud system, cyber fraud, remote access
The use of intelligent cameras and sensors, in combination with the human operator in video analytics systems, from which most of the analytical and visual load has been removed, allows you to increase the efficiency of video surveillance and, as a result, increase the safety and productivity of work in production as a whole. Analysis of the existing data processing methods in the video surveillance systems of industrial facility showed that the use of a non-contact method for analyzing person’s posture and actions in the camera’s field of vision is rare, but it can be critical in certain situations (person in overalls is in the camera’s field of view, but the system is on him does not respond, because he is not in the forbidden zone). The improvement of algorithms for the intellectual analysis of video data in the system for monitoring compliance with industrial safety rules (analysis of the type of dynamics and control "friend or foe") using neural network processing technologies is considered. Effectiveness evaluation of algorithms for analyzing full-scale video data software implementation showed the correctness of classification in 97% of cases. Effectiveness evaluation of the 5 subjects into two classes of “own” and “alien” classification was carried out by cross-validation and showed an accuracy of 99% on the test sample.
Keywords: video analytics, intelligent analysis, dynamics type recognition, neural network, classifier, pose determination
Scientific and technical progress has contributed to a rapid increase in the complexity of systems and their functions, which is especially characteristic of various fields of modern industry. Here, the cost of failure of equipment can be very high and sometimes lead to invaluable losses associated with the loss of life. Maintenance of such systems requires high material costs, but still does not exclude the possibility of failures. This indicates that the problem of ensuring the reliability of complex multiobject systems is still far from being solved. In this regard, the task of ensuring reliable operation of systems while minimizing the cost of their maintenance and maintenance is now in the first place. The solution of this problem is impossible without the development and implementation of intelligent systems that perform the functions of predictive analytics and predictive maintenance. This article proposes a hybrid neural network model for predicting failures of complex multi-object systems based on the classification approach, aimed at improving the operational reliability of equipment at minimal cost. The results of computational experiments confirming the high efficiency of the proposed solution are presented.
Keywords: forecasting failures, data-driven methods, deep neural networks, lstm, cnn
This paper considers the technological process of vulcanization of automobile tires from the point of view of a potentially dangerous process. Currently, technological processes are becoming more complex, evolving most of the time in conditions of uncertainty, incompleteness and indistinctness of information. One of the most common methods of process control today is still PID controllers, due to their ease of implementation, low cost and their satisfactory results in the control of linear systems. In order to adequately control potentially dangerous technological processes, it is necessary to develop new models and algorithms based on new intelligent approaches. One of the most promising approaches to process control is models based on fuzzy logic and fuzzy sets. The paper presents the General mathematical structure of the vulcanization process control system. This paper presents the synthesis of a fuzzy controller of heating steam temperature of the car tire vulcanization process.
Keywords: fuzzy inference systems (fis), fuzzy logic, vulcanization, technological process, potentially dangerous objects
The article solves the problem of developing two coordination algorithms for managing large-scale projects. The first algorithm is designed to select the appropriate method of coordination when managing the projects under consideration. The algorithm is based on the thesis that the higher the threat of failure of the project plan, the higher the degree of centralization of project management should be, and the lower the threat, the less centralized the project management should be. With this approach, choosing the appropriate method of coordination actually comes down to assessing the threat level. Given that the concept of "level" is of a qualitative nature, it is proposed to characterize it by the function of belonging to gradations: "very high", "high", "medium"," low", and" zero", and to evaluate the current threat level, use the measure of hemming proximity, which uses the zero threat level as a reference. The second algorithm is designed to select optimal coordinating solutions based on the criterion of minimum deviation of the project from the specified target state. Its novelty and originality lies in the fact that, unlike the usual optimization approach, it is built on a combination of methods of full iteration and linear programming. This made it possible to correctly take into account the fact that coordinating and design solutions are inextricably linked with each other.
Keywords: project, coordination, project manager, project performer, membership function, algorithm
The goal is to predict the properties of bulk material flowing from the hopper device. The relevance of the study is due to the lack of input data for controlling the averaging process at processing plants. In this regard, this article is aimed at identifying the transfer function of the hopper device, and the delay time between the feed and the expiration of the material, which will allow you to predict the property of the bulk material, and therefore get the initial data for the averaging process, which is not always available. This article presents an analysis of the existing flow modes of bulk materials when they flow out of a hopper device with one or more holes, the equations describing the transfer function of the hopper device, as well as the time delay between the layer feed and its expiration, are derived. Based on these equations, a mathematical model for controlling the averaging process was constructed, which relates the relative fluctuations and frequency of change in the properties of the ore material entering the hopper. The compiled mathematical model provides reserves for reducing relative fluctuations in the factory. The materials of the article are of practical value for managing the process of averaging ore material at processing plants.
Keywords: mathematic modeling, transfer-function coefficient, averaging out of behavior, granular material, fluxion
Logistics curves are widely used in various fields of economics, technology, biology, chemistry. Estimating the parameters of logistic trends from the results of observations of the dynamic process in the economic system, with the aim of reliable analysis of economic indicators and predicting their future behavior, is one of the main tasks in the economy. One of the logistic models is the Ramsay function. The advantage of this function is the ability to use a linear difference equation to estimate its parameters. At the same time, non-linear data transformations are not required as for the logistics functions of Ferhulst or Gompertz. Modifications of a two-stage estimation algorithm based on the total least squares method and the extended instrumental variables method are proposed for estimating the parameters of the Ramsey curve.Tests have shown that the accuracy of parameter estimation using the proposed modifications is higher than the accuracy of the estimate obtained using the ordinary least squares method (LS).
Keywords: total least square, logistic curve, ramsay function, estimation of parameters
Process control in organizational systems is an activity aimed at fulfilling tasks (plans, fulfilling orders) throughout the list of system processes. To accomplish this task, management must timely evaluate the implementation of the program, monitor the tendency of performers to deviate from the planned norm and direct the resources at its disposal to eliminate these deviations. In many areas, the calculation of the number of intermediate and final results is automated, and staff can at any time know the numbers that characterize the progress. However, in areas such as construction, high technology and some others, it is rather difficult to evaluate how the program is implemented. Each operation to show the actual implementation of the program and control the timing of each type of result requires full monitoring. This is an expensive operation, often requiring a suspension of the process. Therefore, it is desirable that this be done as rarely as possible, but at the same time, the moment should not be missed when the tendency to deviation will develop into a threat to the program. The process of managing the work of an organizational system of a single-purpose type is considered, the volume of the program of which is expressed as a general equivalent - in units of output (tasks) or in cost. For programs that solve several important types of tasks, it is necessary to simultaneously monitor each type of task.
Keywords: control moment, organizational systems, program execution, modeling, single-purpose type
This article presents mathematical and simulation modeling of a distributed registry with a control node on the example of the raft consensus algorithm. The process of interaction between individual nodes of the distributed registry network is described, special attention is paid to the algorithm for conducting transactions within this network. The key aspect of this article is the development of a mathematical model of a distributed registry network as a Queuing system using queue theory. We consider the conceptual models of both the distributed registry as a whole and the model of the information process for accessing a cluster of notary nodes. Mathematical modeling of the distributed registry network, as well as the information process of obtaining access to the control node of the network. The state space is represented in a distributed registry with a control node. The description of an infinitesimal matrix for estimating the probability of transitions between States in a distributed registry is formed, the transition probabilities and the intensity of these processes are described. The characteristic of the laws of distribution of indicators in the system under consideration is described. Another important aspect of this article is the simulation of the process in order to identify the best combination of parameters to achieve maximum efficiency. A stack of variable indicators of the simulation model is formed. Tests were carried out on the basis of which the most effective set of characteristics was selected empirically. The results of mathematical and simulation modeling of a distributed registry with a control node are presented.
Keywords: distributed registry, dlt system, consensus algorithm, mathematical modeling, infinitesimal matrix, queuing theory, queue theory
Nowadays chatbots are becoming very popular in many areas, such as business, banking, healthcare, study, travel tips, etc. The popularity of messaging platforms such as Telegram, Messenger, Whatsapp, and others has made chatbots not only popular but also become a trend in the future. Since the end of December 2019, the onset of the COVID-19 pandemic has brought about a major global health crisis. Therefore, it is extremely important to provide information about the epidemic to all people. Many governments and organizations have launched chatbots to inform the public about COVID-19. However, these chat rules are limited as they understand a limited set of questions entered by users. Thereby, creating a chatbot based on machine learning for coronavirus information is an urgent task. The purpose of the study is the development of a chatbot for searching for information about COVID-19 coronavirus infection. The method of designing and developing a chatbot on the RASA framework, as well as testing of the developed prototype, are described. Three chatbot models were created: the baseline model (B), the baseline model with synonyms (BS), and the baseline model with synonyms and noises (BSS). The effectiveness of three models was evaluated based on the following indicators: accuracy, precision, and F-measure. The analysis results showed that the BS and BSS models are better than the B model.
Keywords: chat bot, natural language processing, serverless, intent, entities, rasa, covid-19
User engagement is one of the key indicators of the quality of interactive software (software), which is characterized by intense user interaction with the system. Training software belongs to the category of products, which, by definition, are based on interaction with the user, so the user's involvement in the process of his interaction with the training system directly affects the quality of the system. Modern trends in the development of educational software are associated with the personification of the processes of user interaction with the system, which has led to the emergence of adaptive educational systems that can monitor user actions and adapt to their capabilities and needs. User involvement has a significant impact on learning and directly affects the result, therefore, the level of user involvement in the process of its interaction with the training system, as an indirect assessment of the user's knowledge level, is applicable as a characteristic of the adaptation model in the development of adaptive learning systems. The results of the engagement analysis can be used to adapt the system aimed at retaining and increasing user engagement in the process of its interaction with the system, and thus improve its quality. The paper considers methods for assessing involvement and the possibility of their application to assessing the quality of educational software at different stages of its life cycle. The features of the use of online-assessment of engagement to adapt the learning process to the user in adaptive learning games are shown, related to the need to distinguish between involvement in the game and involvement in the learning process, and correlation of involvement and success in mastering knowledge in the game. Some possible combinations of assessments of the involvement and effectiveness of the user's knowledge level in the process of interaction with the educational game and their possible interpretations are proposed.
Keywords: engagement, engagement assessment, educational software quality, learning system, engagement online- assessment, adaptive learning game
The development of information technology is accompanied by a comprehensive transformation of the service sector, including microcredit. This sector of the Russian financial market shows steady growth annually. However, amid the high debt load on the Russian population, the availability of microcredit for most citizens, including online, has led to a high share of default disbursements of microloans in MFIs. Pressure from the regulator and a decrease in the income of Russians led the majority of MFIs to bankruptcy, while the remaining players in the microfinance market led to lower interest rates, and as a result, their margins decreased significantly. In this regard, MFIs have an urgent need to develop a scoring model that would be able to identify high-margin borrowers at the stage of applying for a microloan and “cut off” potentially defaulted borrowers. As part of this work, a methodology is proposed for clustering borrowers based on the fuzzy criterion “level of financial responsibility” and assessing the effectiveness of microfinancing based on the profitability of the loan portfolio depending on the proposed classification of borrowers.
Keywords: microfinance, fuzzy modeling, clustering techniques, risk management, classification of borrowers
The article is focused on one of the urgent problems arising in the course of active digitalization in production, social and economic systems – the increase of the number and volume of tasks within the framework of infocommunication systems. These tasks are related to the digital transformation of big data and the transfer of digital resources in the management and physical environment. The importance of staff in achieving these goals within the framework of human-machine system is significantly increased. A practice-oriented training mechanism is required to ensure high performance and error-free tasks. The formation of such a mechanism requires an optimization approach in managing the effectiveness of the personnel training system. Thesis discusses the formation of the algorithmic support of decision-making in the management of the educational system of dual training of staff information and communication systems. It is shown that the structure of the algorithmic procedure is determined by the sequence of optimization problems associated with the management in the development of the educational program on a variety of thematic modules that ensure the implementation of educational and professional standards, and forms of implementation of dual training. The peculiarity of extreme problems is their belonging to the class of discrete programming. The integrated multistage scheme of randomized search with certain conditions of transition of the iterative decision of optimization problems in sequence of reception of the optimum variant of the educational program is offered. The final management decision is determined by the evaluation, which is carried out by seeking the agreed opinion of the expert group.
Keywords: management, educational system, dual training, optimization, discrete programming, randomization, expert evaluation
If earlier the problem of authenticity concerned only printing products (securities, documents, tickets, money, etc.), today the protection of documents presented in digital form (scanned documents, photographs and other multimedia documents) is no less relevant. Therefore, the creation of systems for embedding hidden information in secured documents by various methods is an urgent task, because It will allow you to protect documents, as well as in disputed situations, confirm their authenticity or copyright. In this work, a mathematical model of the system for embedding and recognizing hidden images is developed, which differs from its analogues in the possibility of expanding the many used functions for embedding and recognition. In contrast to the well-known unified model of a system for embedding information in digital signals, a model is proposed that allows implementing the modular principle of constructing a system for recognizing images containing hidden information introduced by various methods. Also, on the basis of the constructed system model, an information system for the implementation and recognition of hidden images, consisting of three interconnected software modules, was developed. This system is a graphical shell for models developed in MATLAB. This approach allows you to integrate the system, add new ones or make changes to existing modules, make changes to the developed model.
Keywords: latent image, wavelet analysis, recognition of hidden images, decomposition by singular numbers, image embedding system
The article discusses the relevance of intelligent IT’ use in planning tourism activities for both individual and collective use. In this regard, this article is aimed at revealing a set of problems in the use of recommendation IT for generation of tourist routes based on optimization models. The process of describing information about tourist attractions and the process of generating a tourist route are presented in form of a formal model of linguistic descriptions for IT system and decision-making model. The methodology proposed by authors is based on methods of multicriteria optimization of discrete programming and methods of object-oriented programming. The article presents a functional model of developing a tourist route’ process as well as models of system and software architectures, a data model of developed software package. The presented methodological and software allows to reduce the complexity of tourist routes’ design, analyze expert opinions of various categories of experts. The specificity and results of experimental testing of development’s use for educational tourism are given.
Keywords: it in tourism, educational tourism, multi-criteria optimization, planning tourist routes
The study is devoted to the issue of assessing the living standards and quality of the Russian Federation regions in 2010-2018. An integral indicator is formed on the basis of the values of 33 socioeconomic indicators and acts as an indicator of assessing the living standards. Selected for the study indicators are combined into seven groups: the income level of the population, the level of development of the consumer market, the standard of housing and quality of housing conditions, level of development and availability of health and education, demographic indicators, employment and unemployment, as well as the environment. The information base of the study consists of official statistics for 2010-2018. Based on the results of the integral indicator calculations the distribution of Russian regions by the living standards is obtained. The changes dynamics in the average Russian integral indicator indicates a decrease in the living standards of over the period under review. To conduct a comparative analysis of changes in the living standard in the Russian Federation regions for each region, the total increments of the integral indicator and its components were obtained. These values formed a feature space for identifying homogeneous groups of regions by the total increment of each of the seven indicators using cluster analysis methods. As a result of the stable classification procedure, the Russian Federation regions were divided into three homogeneous groups and 13 atypical regions were identified. Atypical regions differ in subindex increments that are not typical for the selected groups. A significant disparity in the rate of change in the living standard was revealed. This characterizes the lack of effectiveness of state planning and implementation of social programs at the regional level.
Keywords: living standards, integral indicator, ranking, classification of regions, cluster analysis
There is considered the task of creating personalized blanks for project documents in office graphics formats. Personalized blanks are understood as documents filled with specific design data in order to free the developer from routine actions during subsequent design. Two levels of graphic personalization complexity are noted: parametric and structural. The formation of personalized blanks is carried out in two stages: template development; template personalization. At the first stage, a blank template with preliminary marking of personalization points is manually developed in the environment of a graphical editor. At the second stage, software processing of the template is performed, in which personalization points are found in the template and personal data from the database is placed in them. Personalization based on situationally-oriented databases is discussed — an integrator of heterogeneous data based on an information processor controlled by a built-in highly abstract hierarchical situational model. Access to heterogeneous data is specified in the situational model in the form of virtual documents that are mapped onto heterogeneous real data. The features of mapping a virtual document to documents in VDX and FODG, as well as VSDX and ODG are considered. If in the first case, mapping to an XML file is required, then in the second to a ZIP archive, in the folders of which XML files are located. Fragments of situational models are considered that provide personalization based on: searching nodes containing identification tags in the XML document tree and replacing them with database data. Compared to the traditional approach, this gives a simpler task definition. The practical use of the results for information support of educational design in the discipline of "database" is discussed. There is a decrease in the complexity of the routine part of the project, an increase in the possibilities of creative activity in the process of educational design.
Keywords: personalized documents, situation-oriented database, hierarchical situational model, virtual document, vdx, vsdx, odg