A GOAL-ORIENTED CHATBOT BASED ON MACHINE LEARNING
T.M.T Nguyen, M.V. Shcherbakov
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.
MODEL OF COMPLEX FLOWS ADDRESS THREATS TO INFORMATION SECURITY IN COMMUNICATION NETWORKS SPECIAL PURPOSE
O.I. Bokova, D.A. Zhayvoronok, S.V. Kanavin, N.S. Khokhlov
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.
METHOD OF COUNTERING DESTRUCTIVE ELECTROMAGNETIC INFLUENCES, BASED ON ADDITIONAL MODULATION WITH APPLICATION OF WAVELET TRANSFORMATION IN SPECIAL APPLICATION NETWORKS
I.V. Gilev, S.V. Kanavin, A.V. Popov, N.S. Khokhlov
The article discusses a method of counteracting destructive electromagnetic effects, based on the transfer of the signal spectrum using wavelet transforms in special communication networks (SS SN), operating on the basis of the WIMAX standard for mobile broadband access. A Gaussian bipolar pulse is selected as a model of destructive electromagnetic influence that affects the operation of a special purpose communication network. When this type of interference is affected by a WIMAX system signal, the normal operation of the CC SN is disrupted. The MHAT wavelet was chosen as the modulating function, since it is described in the time-frequency half-plane and its parameters depend on certain coefficients of the scaling factor and the time shift. Thus, it is possible to change the parameters of the modulated signal by changing the coefficients of the wavelet function by which it is modulated. MHAT wavelet, obtained as a result of double differentiation of the Gauss function. This method finds its application primarily due to the fact that the wavelet operates in the time-frequency half-plane and its parameters depend on certain coefficients (scaling factor and time shift). Thus, it is possible to change the parameters of the modulated signal by changing the coefficients of the wavelet function by which it is modulated. The results of this method are the transfer of the spectrum of the WIMAX signal to another frequency band, where the SS SN also functions by modulating the wavelet function, as well as increasing its power and expanding the spectrum.
Keywords:broadband communication system, WIMAX communication systems, modeling of functioning under conditions of destructive electromagnetic influences, а method of counteracting destructive electromagnetic influences using wavelet transform, MHAT-wavelet.
CHOOSING THE BEST ROUTING PROTOCOL FOR WIRELESS SENSOR NETWORKS
Due to the rapid development of wireless technologies, the optimal choice of network types and routing protocols is an urgent task. The current state of traffic models in terms of routing protocols in wireless sensor networks (WSN) is considered. The class of corresponding low-power network (LLN) provides efficient routing when transmitting data packets in small local networks. The AODV (Ad Hoc On-Demand Distance Vector) dynamic routing protocol in the BSS minimizes the length of the traffic route. Modeling traffic in the FSU is considered using color images as an example. For aggregated heterogeneous traffic flows in the network, the Kolmogorov criterion is applied, and dependences are obtained that allow one to calculate the Hurst coefficient using analysis of the variant variable . The same parameter is calculated as optimal for a packet of images on a sensor field of depending on the number of transmitting nodes and is equal to . For the WSN, various connection options with various connection options for the client and operator in the presence or absence of a base station are considered. Also, for wireless sensor networks, the RPL and AODV protocols are compared by simulation. Shown, the first is optimal. From the perspective of the 5th generation networks, it is possible to use D2D (device-to-device) connections. In this version of the two protocols (AODV, DSDV), AODV is more preferable both for the minimum total delay time and the minimum number of steps in data transfer. The development of 5th generation wireless networks will bring traffic to the level of broadband wired Internet and provide a qualitatively new level of opportunities for customers of these networks.
Keywords:wireless sensor network, RPL protocol, AODV protocol, D2D connections, Hurst coefficient, Kolmogorov criterion, 5G network.
А CLASSIFICATION APPROACH BASED ON A COMBINATION OF DEEP NEURAL NETWORKS FOR PREDICTING FAILURES OF COMPLEX MULTI-OBJECT SYSTEMS
K.A. Melekhina, P.P. Anan’ev, A.V. Plotnikova, S.A. Shestak
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 multi-object 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
DEVELOPMENT OF AN INFORMATION MODEL FOR SYNTHESIS OF COLOR COMPONENTS OF METAL-PLASTIC DENTURES
Modern medical practice is characterized by the universal use of technical means of diagnosis and treatment of diseases. One of the most rapidly developing trends in medicine is dentistry, in particular the aesthetic dentistry. The key problem in the aesthetic dentistry is the selection of an adequate color of dentures. To solve this problem, an information model was developed for synthesis of color components of metal-plastic dentures. A graph was developed to select the components that make up the mass of dyes for the selection of a given spectral component of the front part of prosthetic tooth. Regression analysis was used as the main method of analyzing the process of powder synthesis, which is a data analysis tool that allows investigate the influence of one or more independent variables on a dependent variable. Thus, a regression type mathematical model was developed in which the change of color components takes place in correlation; making it possible to compile interpolation equations and, based on them, to analyze and consider a single system for all sublevels of color gradations. To verify the operation of the developed information model, an algorithm and specialized software were developed. The conducted clinical studies have shown the full adequacy of the developed model.
Keywords:modeling, computer science, graph, regression model, algorithm, dentistry, denture, aesthetics.
ADAPTATION TO USER ENGAGEMENT IN AN ADAPTIVE LEARNING GAME
O.A. Shabalina, A.V. Kataev, A.A. Voronina
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.
SYNTHESIS OF A FUZZY CONTROLLER OF HEATING STEAM TEMPERATURE DURING THE PROCESS OF CARE TIRES VULCANIZATION UNDER POTENTIALLY HAZARDOUS CONDITIONS
B. Yahiaoui, A.A. Mitrokhin, V.L Burkovsky
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.
NETWORK ATTACK ROUTE ANALYSIS APPROACH
I.A. Kuznetsov, V.S. Oladko
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.
MATHEMATICAL MODELS FOR PREDICTING AND EARLY DIAGNOSIS OF DISEASES CAUSED BY ELECTROMAGNETIC FIELDS OF LOW-FREQUENCY RADIO FREQUENCY RANGE
N.A. Korenevsky, A.V. Titova, T.N. Govorukhina, D.A. Mednikov
The paper proposes mathematical models for predicting and diagnosing diseases provoked by exposure to electromagnetic fields of the radio frequency range, which make it possible to control the current state of a person in order to make further decisions about possible correction of body functions, if necessary. Given the incomplete and fuzzy description of the studied class of diseases, soft computing technology was chosen as the basic mathematical apparatus, and, in particular, the synthesis methodology of hybrid fuzzy decision rules, which has proven itself in solving problems with a similar data structure and type of uncertainty. The selected synthesis method allows us to take into account the multiplicative effect of exposure to the human body of electromagnetic fields (EMF) of various modality and intensity, taking into account other endogenous and exogenous risk factors. For powerful and stable EMFs, it is proposed to use a modification of well-known models obtained for industrial power grids. To assess the effect of low-intensity, unstable electromagnetic fields of the radio frequency range on the human body, it is proposed to use fuzzy tabular models and a number of indicators sensitive to the action of the electromagnetic field of the radio frequency range. Such indicators include the state of attention, memory, thinking, as well as the dynamics of changes in the energy state of biologically active points associated with the pathology under study. On the example of electric train drivers, mathematical models for predicting and early diagnosis of the appearance and development of diseases of the nervous system are obtained. It is shown that if additional information about the health status of the subjects is used with electromagnetic risk factors, then confidence in the correct prognosis reaches 0.85, and in the presence of early stages of diseases of the nervous system – 0.95.
Keywords:chronic obliterating diseases of lower limbs, theory of latent variables measurement, optimal treatment regimens.