Keywords: volumetric petrophysical model, geostatistics, kriging, seismic exploration, geological well logging, seismic attribute, optimization
The geological environment parameters are widely used in the hydrocarbon deposits exploration and study. They store information about the rocks physical characteristics, the location of the reservoirs, the boundaries of the layers separation, etc. The numerical values of the parameters under consideration are obtained by conducting geophysical well logging (GWL), or by recalculating existing logging curves based on known petrophysical laws. Because GWL can be carried out only if there is a drilled well, the environment parameters are often known only in a small near-wellbore space. This makes urgent the task of predicting the geological environment parameters within the entire field. The existing methods for solving this task can be conditionally divided into two groups: using only GWL data; complexly using 3D seismic and GWL data. The first group is effective when there is a dense grid of downhole measurements. The second group shows the best results in the conditions of a sparse irregular grid, however, it requires the seismic data availability within the entire studied field. This paper describes a new method for predicting geological environment parameters based on the GWL data and 3D seismic prospecting combined use. The paper also provides an algorithmic implementation of the new method; ways of optimizing algorithmic implementation are considered.
Keywords: volumetric petrophysical model, geostatistics, kriging, seismic exploration, geological well logging, seismic attribute, optimization
This article considers the issue of ensuring the effective use of proactive control of the functional characteristics of the radar complex, taking into account the technical readiness of hardware and software and the level of training of operators and maintenance personnel. The importance of the human factor contribution in ensuring the combat readiness and effectiveness of the use of the radar complex for its intended purpose is emphasized. As a result of the analysis of the existing methodological apparatus for assessing the level of training of operators and service personnel for the modern proactive management methods implementation, the necessity and ways of improving it are determined based on the competence approach adopted a priori in the Russian Federation. The concepts of the professional competence portrait of the operator and the reference professional competence portrait describing the necessary and sufficient set of competencies required by the operator for timely and effective management and application of the radar complex are introduced. An information model of a professional competence portrait is described, a metric for calculating a quantitative integral assessment of the level of its formation is proposed, which is applicable for software implementation as part of automated training tools. The scheme of application of automated training tools for solving operational tasks of proactive control of the radar complex is presented. The necessity of using Big Data of operational data of the repair and diagnostic complex for detecting signs, determining the causes and eliminating/preventing failures, as well as archival and up-to-date data from automated training facilities on the state of training of operators and maintenance personnel in the process of proactive control of the radar complex is noted. Based on the results obtained, it can be concluded that it is advisable to integrate training facilities and systems of technical and functional control of the radar complex to achieve a given level of probability of performing the tasks of the radar complex according to its intended purpose.
Keywords: proactive management, technical control, artificial intelligence, big Data, educational and training tools, competence approach
In the modern world, there are various means of communication: electronic devices, web and mobile applications (Internet forums, chats, blogs, social networks). As a result, a huge amount of information appears about the users themselves, about their attitude to other people, to events taking place in the world. This information can be useful in modeling the processes occurring in society, predicting the behavior of people. Thus, the methods of collecting and analyzing information contained on the Internet are interesting for research. Information on the Internet is presented in the form of a text in a natural language, therefore it is necessary to use the methods of computational linguistics. For example, let's say we have text. Without reading, is it possible to understand what emotion he carries? You can, for example, classify an emotion into positive and negative. The paper discusses Convolutional Neural Networks, which were originally developed for image processing, but also cope with tasks in the field of automatic word processing and Recurrent Neural Networks, the main difference from traditional ones is the logic of the network operation, in which each neuron interacts with itself.
Keywords: sentiment analysis, processing of notes and comments, information, text, convolutional neural networks, recurrent neural network
To restore the motor functions of the lower extremities in post-stroke patients, it is proposed to use a biotechnical system with a robotic device. The control is based on the analysis and classification of electromyosignals. The robotic device is controlled by a fuzzy control module, which allows maintaining three modes of rehabilitation, selecting and switching them depending on the functional state of the patient, thereby deciding on the optimal rehabilitation program for the current functional state of the patient. The control model includes three fuzzy control modules with the corresponding bases of fuzzy decision rules and it allows you to adapt the rehabilitation procedure to the functional state of the patient. To assess the effectiveness of the proposed method of rehabilitation, the experimental group included 23 patients who underwent exacerbations from 25 days to 5 years, including patients with subacute (<180 days after exacerbation) and chronic (> 180 days after exacerbation) conditions. After a course of rehabilitation by means of a biotechnical system with a fuzzy control module, there is a significant increase in the maxima of the support reaction force Rz on the affected leg in the experimental group in relation to the control group. Accordingly, the amplitude of the front push in the experimental group increased by 62% (120%), the rear push by 58% (115%), while in the control group the amplitude increase was 40% (101%) and 41% (105 %). In this case, distinct maxima of the support reaction component Rz appear on the paretic leg.
Keywords: fuzzy control module, post-stroke patients, robotic device, algorithm, base of fuzzy decision rules
The article describes an algorithm for regulating the quantity of slots in the implementation of the anti-collision protocol Q when it is used in information systems for the international goods transportation. The purpose of the study is to develop and substantiate an algorithm for regulating the number of slots when implementing the anti-collision protocol Q in information systems for international goods transportation. Results. An appropriate algorithm was proposed, which differs from existing solutions in fewer required variables and fewer operations required to calculate the number of slots. This algorithm should help to decrease the time needed to transfer information from RFID tags to information systems for international goods transportation. Upon condition an equal quantity of frames, the proposed algorithm reduces the total number of operations to determine the number of slots that will be required to read a set of RFID tags by 16.7%. The algorithm is applicable due to the fulfillment of the requirement to achieve maximum system efficiency not lower than for existing solutions, which was proved with simulation modeling. Practical significance: the results obtained can be used to ensure the availability of information when information from RFID tags enters the information systems for the international transportation of goods, as state information systems. The results can be used by customs authorities in the development of information support for labeling and traceability systems
Keywords: RFID-technology, RFID-mark, RFID-collision, mark collision, RFID-marking, customs bodies, goods marking, RFID, anticollision protocol
The exploitation of mineral deposits requires their rational use. In order to avoid deterioration of water quality and disruption of hydrodynamic processes of deposits, a unified system of monitoring and management of the process of extraction of natural resources is necessary. In this regard, the task is to develop an automated control system that can analyze the changes taking place and make adjustments to the production parameters. However, modern methods of modeling hydrogeological objects have a number of disadvantages and require serious analysis to obtain reliable modeling results. In the course of the study, the methods of modeling hydrogeological systems implemented at the Kavminvod deposits were considered. The main direction of development was obtained by methods using filtration modeling. Such equations describing the processes of geofiltration as two-dimensional and three-dimensional are considered. The results of the study represent the design and physical parameters of the considered models implemented on hydrogeological objects of the CMS region. The models have an acceptable error determined on the basis of comparing the values of the model experiment with the data obtained on real objects, and therefore it is concluded that they are effective in solving this class of problems. To increase the reliability of the results, it is necessary to take into account the number of layers, their composition, structure and integrity, in addition, to include parameters that take into account their mutual influence.
Keywords: modeling methods, hydrogeological system, geofiltration processes, three-dimensional modeling, system analysis
Abstract: The challenges of modern information security threats that have a destabilizing effect on special purpose communication systems (SSSN) require a response. At the same time, counteraction in the SSSN is considered as a complex, multilevel hierarchical process, and the information conflict is considered as a way of interaction between the components of the system, the result of which is not predetermined in advance. As a result, it is possible to implement various strategies for protecting information systems based on possible options for action. When analyzing the information conflict in the SSSN, the models of conflicts based on control theory, game theory, and the probabilistic-temporal approach are considered. On the basis of the principle of direct modeling of the conflict process, a model of conflict interaction "СССН-intruder" is proposed. The proposed model of the conflict "СССН-intruder" at the conceptual level is structurally presented in the form of a system with two control loops, having a common object of influence СССН and directly opposite goals of functioning, and the dynamics of their interaction is presented in the form of a scheme "impact-response" with the possibility of making a decision on the application of measures to counter conflict impact both after the fact of impact, and after establishing the fact of active scanning of vulnerabilities. The counteraction strategy in this case involves the use of the available resource, according to a certain algorithm, for the response of the system to the impact. It is shown that the choice of the countermeasures strategy, as well as the conflict interaction itself, depends on the operating conditions and parameters of the SCCH. As a result of modeling, it was shown that the conflict interaction over the entire time interval is cyclical, i.e. there is a predominance of the conflict impact or the strategy of counteraction to the conflict impact, at each step of the conflicting interaction of the parties.
Keywords: protection strategies, threats to information security, communication system of special purpose, information conflict, conflict interaction, management of the information security system
The article is devoted to the problem of detecting network attacks in Industrial Internet of Things systems. The topicality of the problem under consideration due to a high level of security risks in such systems is analyzed. Various algorithms of network attack detection are considered, and an increasing interest to applying methods of artificial intelligence for solving this kind of problems is noted. The advantages of combining various algorithms of artificial intelligence and methods of machine learning as a part of hybrid intrusion detection systems are underlined. The approach to design of hybrid intelligent intrusion detection system (IDS) is proposed, which includes at the lower level the artificial immune system, responsible for detection of anomalies and unknown network attacks, fulfilling so a function of preliminary network traffic filtration, and the multiclass classificator at the upper level, determining the class of the attack detected at the lower level of the system. The neural network and the random forest algorithm are considered as methods of constructing the classifier of the upper level. The training and efficiency estimation of the system proposed were carried out with use of the NSL-KDD dataset. As experiments showed, the best results were achieved by combination in hybrid IDS of the algorithms of artificial immune system and random forest.
Keywords: information security, network attack, machine learning, artificial immune system, neural network, random forest, hybrid intelligent system
A two-person noncooperative game that models a process of purchasing protection means for a computer system is considered. One of the players in this game is a party responsible for the security of the system. Having a certain amount of money that can be spent on the purchase of the protection means this party determines which of these funds should be purchased. Actions of the other player (and it's the external world in relation to the computer system) are attacks on the computer system implemented via the network. For each of the protection means that can be purchased as well as for each of the types of attacks that can be used in an assault on the computer system a probability with which the attack will be reflected by the protection mean is known. By choosing the protection means a party responsible for the security seeks to minimize overall losses which include first a cost of the purchased protection means and secondly a damage expected from use of the other party attacks on the computer system. A study of an optimality principle implementations of which are lexicographically maximin strategies of a player which is a party responsible for ensuring the security of the system is carried out. A result of this study is statements that determine a method of finding all lexicographically maximin strategies of the specified player.
Keywords: noncooperative game, maximin strategy, nondominated strategy, lexicographically maximin strategy, computer system, attack on a computer system, protection of a computer system
The scientific idea of this work is the formalization of the known thesis that there is a direct relationship between the quality of project management and consumer properties of the resulting product. Hardware and software complexes are a kind of complex systems, which proves the possibility of scientific adaptation of well-known approaches used in the research of complex systems of a different nature to the field of ensuring the functional safety of the hardware and software systems. One sign of this "relationship" of software and hardware systems with complex systems of different nature are typical problem situations arising in the implementation of projects. In the publications, at the declarative level, typical problem situations that occurs in managing of complex systems of different nature are described, and are called system archetypes. In this paper, on the example of the system archetype “limits of success’, a formal approach to the analysis of the compliance of the quality of hardware and software complex project management a with the state of the control object is proposed.The paper proposes a new systemic combination of models and approaches known in system analysis, which made it possible to increase the degree of formalization of research focused on assessing the impact of project management quality on the functional safety of hardware and software systems.
Keywords: project management, problem situation, functional safety, hardware-software system, system archetype “limits to success”
The research is devoted to the construction of a convolutional neural network model for recognizing medical images on the example of X-ray images database of patients with an established diagnosis of brain tumor. The convolutional neural network model is proposed, the architecture of which includes two convolutional layers and one fully connected layer. The accuracy results of the proposed classifier and accuracy results of the pre-trained models VGG16, VGG19, Inception-V3, InceptionResNet-V2, ResNet50, ResNet152 and Xception are compared. The considered CNN models on the test dataset achieved the image recognition accuracy from 95.36% to 98.84%. The highest accuracy of the results in solving the problem of recognizing a brain tumor was achieved by the models VGG 16, VGG 19, Xception and the proposed model. However, the training time of the constructed models differs depending on the architecture of the neural network. At the same time, for the proposed CNN model, there 0.783% were no detected signs of the disease among the X-ray samples of patients with an established diagnosis of a brain tumor. The proposed neural network model can act as an additional tool of a doctor in the diagnosis of a brain tumor. The introduction of computer vision algorithms into the daily work of a doctor will make it possible to promptly carry out an additional examination of the patient, make a diagnosis and carry out treatment in a timely manner. The use of services based on artificial intelligence algorithms can reduce the total time spent on diagnostic studies, identify pathologies at an early stage of the disease and are more likely to expect that treatment will lead to positive results.
Keywords: convolutional neural networks, image recognition, image classification, brain tumor, pretrained neural networks
Population algorithms enable simultaneously search many elements of approximation of Pareto optimal decisions set and hereupon provide large advantage in consumption of time compare to scalar goal function method that found a single decision in the search cycle. The capability of open-source platform PlatEMO for solving of problems of multiobjective optimization of electrical filters characteristics was investigated in this work. Experience has shown that for two-objectives optimization problems only 6 algorithms of 71 provided good results. Approximations of Pareto set found by these algorithms were better than approximation found by scalar goal function method. Comparison was carried out by means of Coverage indicator that estimates the part of the first approximation elements dominated by the second approximation elements. For three-objectives optimization problems only two algorithms provided acceptable results. In this case approximations of Pareto set found by population algorithms were worse than that found by scalar goal function method. The conclusion was made that a rational method may consist of application of population algorithm for the solving of several two-objective optimization problems with constrains on other objectives and successive aggregation of found subsets.
Keywords: pareto-optimality, population algorithm, scalarization, decomposition, dominance, gain-frequency response, phase-frequency response
Abstract: One of the most important problems in the organization of an effective educational process is the problem of matching the qualities of teachers and students. The relevance of solving this problem is determined by the growth of the volume and complexity of educational material, as well as the introduction of digital technologies into the educational process. Digital technologies allow us to formally describe the characteristics of the personalities of teachers and students who have the greatest influence on the educational process. These properties of personalities form their portraits. The purpose of the article is a vector-stochastic description of a joint portrait of a teacher and a student. To achieve this goal, the apparatus of formal grammars is used. It is proposed to associate a vector of a point assessment with each student and each teacher. The vector evaluation is presented in the form of deducible chains of a formal language in a probabilistic grammar. The corresponding output tree is built. The output tree is considered as a network of a special type – an information graph. Matrices describing the graph are constructed (the adjacency matrix and the matrix of the sum of adjacency matrices in different degrees). The resulting graph describes the information system. It is shown how to calculate the probabilities of finding the system in each level. To explain the developed method, a specific numerical example of calculating the system parameters is considered. The criterion of the dynamic unity of the portraits of the teacher and the student is formulated. The result of the research is the developed new method of mathematical description of the joint portrait of a teacher and a student. The developed method can be used in models of digitalization of education and similar areas.
Keywords: evaluation vector, inferred language chains, probabilistic grammar, rule scheme, inference tree, information graph, system, adjacency matrix
One of the most important factors that are affecting of quality of processes service in a distributed system is the way of managing shared resources. At the same time, it is necessary to take into account that each process (task) has a set of characteristics, the complex accounting of which makes it possible to increase the efficiency of executing processes. Among the most important characteristics are the execution time of the process and its significance for solving system-wide tasks. This article is devoted to the development of a resource allocation algorithm based on a two-criteria process assessment. The priority and order of tasks execution is determined based on the importance weights formed by the PROMETHEE II multicriteria decision-making method. The paper describes the features of the application of this method to solve the problem and design an algorithm for the resource’s allocation based on a two-criteria assessment of processes. The algorithm provides for the possibility of interrupting the service of processes and forming a queue based on the importance weights. To automate the resource planning process, a software product has been developed that implements the stages of the algorithm. The calculations have shown that the proposed algorithm improves the quality of management of distributed systems, making the resource planning process more flexible and efficient. The approach described in the work is universal and can be extended for the case of an arbitrary number of criteria for evaluating processes.
Keywords: distributed systems, resource allocation, multi-criteria decision-making (MCDM), PROMETHEE II, virtual machine
Currently, simulators are used in various fields of training specialists. Especially the ability to repeatedly and accurately recreate various situations allows students to practice a variety of scenarios. In medical education, there is a need to improve the acquired knowledge in order to prepare for working directly with patients. It is not always possible to conduct practical classes, and even the proposed practice cannot cover the entire range of clinical cases. One of the most important aspects of training a doctor is the development of certain thinking skills, and the closer they are to real practice, the more effective the training of a specialist will be. The automated training system is a complex of technical, educational, methodological, linguistic, software and organizational support on a computer basis and provides a simplified model of the phenomenon being studied. This facilitates different cases easy perception and research, the development of certain skills and abilities to apply special knowledge. The article identifies the some problems of diagnosing abdominal diseases. The solution to these problems can be the introduction of an auxiliary tool in the form of an automated training system at the stage of training specialists. A database for the system operation is proposed, the order of its formation and building is described. Flowcharts for drawing up a task variant are developed. Also an interaction workflow and a possible interface forms design of the system modules are presented.
Keywords: diagnostic errors, medical training simulator, abdominal pathologies, situational tasks, clinical thinking, medical education, automated training system
For many years, assisted reproductive technologies (ART) have been helping to conceive a child when this is not possible naturally. We can consider the ART protocol to be successful not only in case of pregnancy, but also in case of its successful completion: the birth of a healthy child. The article describes the creation of a software application for employees of ART centers, which helps to predict the outcome of the protocol, including the probability of pregnancy, the forecast of possible complications during its course, the forecast of the time and method of delivery, and the health group (1-5) of the born child. To create the application, we used data on 854 protocols implemented in 2016-2018, because of which 464 children were born. The analysis of their health contains information from birth to three years of age. The application uses sixteen binary classifiers, nine of which implement multi-class classifications of the term of delivery, the delivery method and children’s health groups. To implement multiclass inference, the “one-vs-all” strategy was used. Сross-validation was used to check the quality. The remaining 7 classifiers predict the likelihood of pregnancy and the occurrence of its complications: cervical incompetence, hypertensive disorders, placenta previa, gestational diabetes mellitus, violations of the amount of amniotic fluid and premature rupture of the membranes. We have built all the models based on the random forest algorithm using the Python programming language. The interface was created using the PyQT5 and QtDesigner libraries.
Keywords: machine learning, assisted reproductive technologies, expert system, software application, child health status prediction
The issue of constructing a solution to an initial-boundary value problem for an evolutionary differential equation with a spatial variable varying on a network (geometric graph) has remained under review of researchers over the past few years. There were many practical reasons for this - a large number of mathematical models describing the transport processes of continuous media over network carriers use formalisms of partial differential equations and their corresponding initial-boundary value problems. In this paper, classical approaches were used for approximating differential equations on linear network fragments (graph edges), and the principles of constructing approximations of differential relations generated by generalized Kirchhoff conditions at the junction points of these fragments (at the graph nodes) were also indicated. The latter was a distinctive feature of differential equations concept with a spatial variable, changing on a network (graph) and its corresponding finite-difference analogue of the classical equation and finite-difference analogue. The problems of the elliptic operator approximation of the initial-boundary value problem were studied (the error of approximations was established), the stability of the two-layer difference scheme and detailed analysis of its stability was carried out. An algorithm for constructing a solution was developed, based on new numerical methods for analyzing transport problems in materials with complex structure with non-uniformly distributed properties of a continuous medium over a network carrier. A computer program has been developed and tested on test objectives targeted at applied problems. The obtained results can be used in the analysis of initial-boundary value problems for differential equations with distributed parameters on a multidimensional network having interesting analogies with multiphase problems in multidimensional hydrodynamics.
Keywords: initial-boundary value transfer problem, network (directed graph), weak solution, finite-dimensional analogue of differential operators, stability of difference schemes
Statin (lipid-lowering medications) therapy is a key focus in the treatment and prevention of cardiovascular disease. In this study, 23 % of patients stopped taking statins at 3 months after discharge and 27 % of patients at 6 months after discharge. These figures are similar to the previous analysis of adherence to statins. Low adherence determines the continuing of identifying factors influencing the keeping up treatment. In order to study the factors influencing compliance the “decision tree” was used. The research has been conducted on the group of 69 patients who had been treated in the cardiological department and who had been observed at the outpatient stage during the 6 months. The intellectual technology «decision tree» has been used with a view to analysing of affecting the compliance with recommendations for the reception of statins after hospital care. For building «decision trees» the input data has been applied: age, gender, social status, reasons for hospitalization, treatment before hospital, arterial hypertension length, heart failure presence, atrial fibrillation, ischemic heart disease, history of myocardial infarction, comorbidity, tendency to forgetfulness in taking medication, side effects of medicines, well-being during treatment, drug replacement, giving of visual recommendations. Output data: keeping up/cessation of medical regimen during 3 and 6 months after hospital. «Decision trees» have identified determinative outcome factors: the presence of a history of coronary heart disease, the reason for hospitalization, giving of visual recommendations, the drug replacement, the age of patients, the arterial hypertension length, the social status. The failure to comply with the recommendations is most specific for the senior age group, for patients with small experience of arterial hypertension and changes in therapy. The non-complementary groups of patients need to fix the attention of patients by a detailed explanation method for the purpose of prescribing a drug and the reasons for replacing drugs in the future.
Keywords: adherence to statin therapy, «decision tree», model selection cross validate, adherence factors, visual recommendations for patients
The article deals with the problem of optimizing the educational process through the use of cloud technologies. The purpose is to study the effectiveness of using cloud technologies in solving problems of optimizing the educational process. The paper considers the theoretical aspects of optimizing the educational process, the features of cloud technologies; the analysis of existing cloud computing solutions in the educational space is carried out; the necessity of using cloud technologies in teaching based on computer classes is formulated; the results of using the cloud service for solving optimization problems in the educational space of the school are presented. An analysis of existing cloud computing solutions has shown that there are currently three models for deploying cloud systems: private, public and hybrid, and three service models depending on the type of services provided: IaaS, PaaS and SaaS. In accordance with the objectives of the study, Amazon Web Services was selected to achieve the research goal, at the level of free access for one year monthly for 750 hours of operation of the t2.micro instance with Linux or Windows. The results of the study showed that when using cloud technologies in combination with pedagogical technologies, it was possible to increase the level of knowledge and skills of students in Computer Science and information technologies with the least time, while minimal material resources were spent on achieving the set results for a certain period of time.
Keywords: educational process, training optimization, information technologies, cloud computing, service models, deployment models
The current-voltage characteristic (CVC) is an important integral characteristic of the salt ion transfer process in electromembrane systems, which are considered as the desalination channel of the electrodialysis apparatus. The article examines the theoretical current-voltage characteristic, for the calculation of which a new 2D mathematical model of non-stationary 1:1 transfer of an electrolyte in a potentiodynamic mode is formulated and numerically solved, taking into account the electroconvection and non-catalytic reaction of dissociation and recombination of water molecules. The main regularities of changes in the current-voltage characteristic and their connection with the electroconvection and non-catalytic reaction of dissociation and recombination of water molecules are established. It is shown that before the occurrence of electroconvection, the values of CVC, taking into account the dissociation/recombination reaction of water molecules, are higher than the values of CVC without taking into account this reaction. This difference is caused by the effect on the electric field strength of the products of water dissociation, i.e., the exaltation of the limiting current. Electroconvection begins later, taking into account the dissociation/recombination reaction of water molecules, than without taking into account this reaction. At higher values of the potential jump, the values of the VAC taking into account the dissociation/recombination reaction of water molecules are lower than the values of the CVC without taking into account this reaction. It is established that the non-solenoidal part of the current is small, so the total current and the solenoid part of the current coincide with good accuracy, both in the case of taking into account and in the case without taking into account the dissociation/recombination reaction of water molecules. Thus, in the first approximation, the total current can be considered as the solenoid part of the current, which is calculated using a double integral that is resistant to rounding errors in spatial variables, but retains all the features of the change in current density over time.
Keywords: current-voltage characteristic, membrane systems, mathematical model, cross-section of the desalting channel, ion-exchange membrane
The relevance of the study is due to the fact that protecting valuable documents from unauthorized copying and falsification is an important task in the modern world. In this regard, this article proposes a computational method for visualizing information hidden in an image, based on a modification of the known method for detecting and controlling latent images, the elements of which are highlighted by algorithms for varying the direction of lines and wavelet transformation of the document file. The difference between the developed method lies in the preliminary determination of the type of the analyzed image with an embedded hidden message, based on perceptual hash functions. Depending on the type of hidden information, the corresponding transformation of the image is performed using a previously defined wavelet characteristic of this type. This approach reduces rendering time by 3 times. An experiment was carried out to test the proposed method, during which a comparison was made of the visualization of digital images by the known method and the developed modified one with a predetermined type of image. As a result of the experiment, it was found that the computational method can reduce time costs by 3 times. However, this is not the final result, from the theoretical model it follows that the computational method for controlling hidden information in the image can reduce the time spent up to 6 times. This statement is planned to be confirmed experimentally using more types of digital images.
Keywords: hidden image, latent image, wavelet analysis, hidden information control method, hidden image recognition
In this article a neural network trained by hybrid neuroevolution solves the maze problem. Hybrid neuroevolution combines differential evolution with the novelty search. Algorithms that preserve the best solutions face the problem that estimates of the novelty of these archival solutions will not change from generation to generation. This article aims to address this problem by proposing two methods for adjusting estimates of the novelty of solutions: novelty destruction and actualization of novelty rates. The novelty destruction allows novelty to diminish over time, thereby allowing the search algorithm to evolve, while the actualization of novelty rates updates the novelty of these solutions in each generation. When testing on the problem of navigation in the maze, it was noticed that the novelty destruction and the actualization of novelty rates converge faster than just the standard search by objective function and the novelty search.
Keywords: neuroevolution, neural networks, maze, novelty search, differential evolution
The result of the solving of crimes is one of the important indicators of the activities of law enforcement agencies. Despite the improvement of crime investigation methods, the success rate of crime detection in the Russian Federation remains at the level of 51%–56%. The article describes a method for constructing a mathematical model – a digital double of a registered crime. As the initial data for constructing the model, an array of information – primary accounting documents, about 341 thousand crimes committed on the territory of the Primorsky Krai over 11 years-from 2010 to 2020. The model allows you: with 88% confidence, based on the formalized primary information contained in the primary accounting documents – statistical cards Form No. 1 “On the detected crime”, to make a forecast about whether the crime will be solved or not; to audit unsolved crimes of previous years in order to determine the crimes that have a high probability of detection; to identify the features in the statistical cards that most affect the forecast of the detection of crimes. The model is based on the use of machine learning algorithms “gradient boosting over decision trees”, implemented in the open library of artificial intelligence CatBoost from Yandex. The accuracy of the model is confirmed by the preparation and verification of the forecast of the result of the investigation of crimes in January–June 2021 for 16408 crimes committed on the territory of the Primorsky Krai.
Keywords: digital double, predictive model, crime, statistical cards, machine learning, artificial intelligence, catBoost, gradient boosting, decision trees, feature importance
The article considers the development and programming stages of alternative specialized microcontroller systems, implemented with a view to solving managerial and access control problems, concerning the admission to sensitive facilities of particular importance, under the conditions of costs minimization and the maintenance of the designed hardware and software complex quality indicators. Thus, the main trend in the development of modern technical protection means for objects with particular importance (ALE) is the integration of various technical means and systems into a single information and technical complex - an integrated security system (ISS). ISS provides comprehensive security of objects under protection by merging various subsystems into a single hardware-software (information) platform. Training complexes for the automation of checkpoints, designed to ensure control and management of personnel and transport access to the restricted areas of the ALE in an automated mode, for example, may be used as the elements of these information systems. The reason for defining the problem stems from the fact that there is currently an interest in finding and choosing inexpensive automated control systems in technical systems of security objects with integration algorithms implementation along with database management systems (DBMS). ACS are not always suitable for solving some problems inherent in special facilities. This is due to the sometimes high cost of software or technical solutions, the limited functionality of devices from specific manufacturers, and the atypical nature of the tasks being solved. In this respect, the research is of practical relevance when applied to improving the engineering and technical support of ACS ALE. In other words, the development of specialized problem-oriented control systems, information processing, decision-making and providing subsequent scientific basis for the presented solutions with the aim of assessing the effectiveness of ALE technical support optimization is nowadays in demand. The key approach to researching and testing the methods for the development of alternative programmable logic controllers for ACS OOV is the invention of relevant algorithms for logical management of access control to OLE and their formalization in the form of a program code as well as the eventual formation of the visitors’ database and their ACS identifiers. As a result of the study, the hardware and software implementation of the ACS controller ALE and its software integration with the developed ACS database have been undertaken; additionally, the scientific basis for the targeted use effectiveness of the reviewed information microcontroller system has been outlined.
Keywords: hardware and software complex, access control and management system, information system, information process, stability, programmable microcontroller, database management system, program code, efficiency
Nowadays, cloud computing technology is gaining popularity. That is a technology in which the computer resources of a data center are provided for a user over a network as an online service. Demand stimulates the growth in the number and size of data centers that deliver these services. The pandemic has led to the transition of many services to online mode. Many organizations have noted the effectiveness of remote work and, therefore, the prevalence of distance learning is growing. Thus, there is a need to optimize the operation of service providers’ IT infrastructure in order to increase its cost-effectiveness and environmental friendliness (compliance with the Green computing concept) while maintaining a predetermined level of service quality. One of the key challenges of providing cloud services is the optimal distribution of virtual machines on physical servers. This problem has been studied by many researchers, and in this article the analysis of the existing approaches to its solution is carried out. All of them are based on the current workload examination and then adjusting the allocation of virtual machines. This paper proposes hardware resource use intellectualization of a datacenter, which involves proactive management of hardware platforms, placement of virtual machines, based on the prediction of the workload in the future. To test the outlined approach, we used the capabilities of the CloudSim framework.
Keywords: cloud computing, virtualization, workload forecasting, cloudsim, datacenter, optimization
The article examines one of the processes associated with management in a network organizational system based on a leadership strategy, the process of classification transformation of grouping objects according to the conditions of the management center. The main task is to determine the boundary values of the parameters of the conditions specified on a discrete set in such a way as to distribute resource provision to objects with the maximum potential for achieving target indicators. It is shown that such a problem, when formalized, is a Boolean programming problem. Optimization models of classification ordering are presented for two conditions for rating objects to top classes. These models support a first-order classification ordering process. For solving the task of the secondary sequences of objects not included in the top class, a characteristic feature of the stepwise variation of the integral function is used depending on the numbering of objects corresponding to the rank sequence. Separate stepwise changes are identified as function jumps and determine the optimization nature of their belonging to a given class. An optimization problem is a minimal coverage Boolean programming problem. Using a unified scheme based on the patterns of randomized search, genetic algorithm, and expert estimation is proposed to solve the generated Boolean programming problems.
Keywords: network organizational system, classification transformation, optimization modeling, boolean programming, integral estimates
Artificial intelligence systems are used in many areas of human life support for example finance or medicine. Every year intelligent systems process more and more data and make more and more decisions. All these decisions have an increasing impact on the fate of people. The corner-stone is a distrust of completely non-human, autonomous artificial intelligence systems. The key to distrust lies in the misunderstanding of why intelligent systems make this or that decision, based on what beliefs such systems operate (and whether they have their own beliefs or only those that were given to them by the developers). To solve the problem of “distrust” in such sys-tems, the methods of explainable artificial intelligence have been used. This article provides a brief overview of the most popular methods in the academic environment such methods as PDP, SHAP, LIME, DeepLIFT, permutation importance, ICE plots. Practical exercises demonstrate the ease of application of PDP and SHAP methods, as well as the convenience of "reading" the graphical results of these methods, which explain the constructed decision tree model and ran-dom forest model on the example of a small set of sales data
Keywords: artificial intelligence, explainable artificial intelligence, interpretable artificial intelligence, explainability, interpretability, XAI, PDP, SHAP
Structural interference is one of the most dangerous for communication systems, for example, radio security systems. The article describes some of the known approaches to assessing noise immunity in conditions of structural interference. It is indicated that the analysis of the noise immunity of wireless data transmission systems under the influence of structural interference is analytically complex. The estimates of the noise immunity of coherent reception of signals with frequency and quadrature phase shift keying under the influence of structural noise have been developed, based on the approach proposed in [6, 13]. Using the developed estimates of noise immunity, graphs of the averaged dependence of the bit error probability on the signal-to-noise ratio were constructed. Based on the graphs obtained and the approach from [6, 10], it is shown that coherent reception of signals with quadrature phase shift keying under the influence of structural noise at fixed values of the bit error probability provides more efficient signal reception compared to coherent reception of signals with frequency shift keying. The obtained probabilistic values in the long term will allow planning measures both for setting up structural interference and for protecting against them in radio security systems. In addition, the research carried out can be useful to the developers and manufacturers of radio security systems. Further research in this area is seen as promising, in particular, the use of complex noise-like signals, for example, chaotic signals, to counteract structural interference.
Keywords: radio security systems, phase shift keying, frequency shift keying, structural interference, noise immunity
The relevance of the study is due to the need to improve the speed and quality of information exchange in information infrastructures protected by means of information security centers (security operation centers) during the period of active malicious impact on the communication channel, the use of high-load or low-speed (unstable) communication channels. In this regard, this article is aimed at identifying a method (or method) for compressing transmitted data in real time (or with minimal delays), working with minimal requirements for the resources involved and allowing you to achieve the highest possible level of data compression. The method to study this problem is to compare the capabilities and characteristics of various methods and methods of data compression under specified conditions. This approach allows you to comprehensively consider the advantages and disadvantages of each of the proposed methods and methods, as well as to select and evaluate the most appropriate one. The article presents a large number of different methods and methods of data compression, reveals the main advantages of the chosen method of data compression by direct syntactic replacement, identifies its advantages and disadvantages, and justifies the need to use this method for compressing transmitted data about identified events and incidents of information security. The materials of the article are of practical value for specialists and developers working in the field of information security, as well as theoretical value for researchers conducting their research both in the field of information security and in the field of information technology in general.
Keywords: database, coding, compression, database management system, information security events and incidents, communication channels
The study is relevant due to the need for minimization of the negative impact on the integrity and confidentiality of data processed by the automated system, as well as on the state of the system components during penetration testing as part of the security control measure. In this regard, this article is aimed to identify methods for creating and using virtual system layouts for their subsequent use in testing. The leading research approach is the modeling of real-world processes of system users functioning: malicious users, officials, responsible for ensuring the security of information processed in the system based on the queuing theory, which makes it possible to comprehensively consider the functioning of automated systems in terms of processing user and attacker requests. The article presents an abstract model of the automated systems functioning. It makes it possible to assess the system security by analyzing the values of the probability that the system will process user requests for access to information resources and inquiry from intruders aimed at violating the confidentiality, integrity, and availability of system components and processed information resources. The article materials are of practical value for creating a virtual test bench for penetration testing, simulating the functioning of an automated circuit, and minimizing the impact on a real system.
Keywords: information security, automated system, information security system, information security control, active security check, queuing system, emulation