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  • Comparison of Agile BPM-Based CRM Development with Anti-Pattern Hard Coding

    Software development, namely CRM-systems to improve the efficiency of the company, regardless of the area, is the most effective for business in terms of organizational and managerial activities. An important aspect of the successful implementation and implementation of the system in the company is the principle of developing and building the system architecture at the server level. For users to work in the system, a deep analysis of the company's business processes and the projection of technical requirements, both on the user interface and on the system's performance, are required. The correctness of the system is based on an important factor - further support of the existing code, this requirement is relevant for any project and depends on the initially chosen method of system development and the quality of tasks performed by programmers.

    Keywords: CRM-system, BPM, hardcode, development, flexible settings

  • Decentralized data Registry in Sovereign Identity Technology

    This article discusses the practical implementation of the self sovereign system based on the technology of a distributed decentralized data registry, also known as blockchain. An implementation of the system based on the Proof of Stake (PoS) consensus-building mechanism is presented, which provides a number of advantages over alternative implementations described in the literature. The results of measuring system performance in comparison with known implementations based on Proof of Work (PoW) are presented, confirming the high efficiency of the proposed solution.

    Keywords: decentralized, user-centric, identity-based encryption, blockchain, self Sovereign identity system

  • Information system for forecasting the collection of payments in the post offices of the Russian Post using machine learning

    This article discusses the forecasting of the collection of payments in post offices, taking into account seasonality and the use of machine learning. An algorithm for constructing a calculation model has been developed, which provides an opportunity for analysts of the Russian Post to make a monthly forecast of the collection of payments for each UFPS (Federal Postal Administration), taking into account seasonality. This model allows you to identify deviations from the norm in matters related to the collection of payments and more accurately adjust the increase in tariffs for services. The SSA algorithm is considered, which consists of 4 steps: embedding, singular decomposition, grouping, diagonal averaging. This information system is implemented in the form of a website using a framework ASP.NET Core and libraries for machine learning ML.NET . Then the forecast is evaluated using various methods.

    Keywords: mathematical modeling, seasonally adjusted forecasting, collection of payments, machine learning, neural network

  • Application of ontologies in learning systems

    The article provides general information about ontologies (including definitions of ontology), its formal (mathematical) model, and also provides a step-by-step process for developing an ontology. The areas of application of ontologies are considered and special attention is paid to the use of ontologies in the field of education. There are some suggestions about using ontologies as a knowledge base for an information security learning system. Also the fragment of a graphical representation of an ontology for biometrics, which is one of the areas of information security, is given. Ontology for biometrics is based on the national standard and developed in the Protege system.

    Keywords: biometrics, knowledge, information security, knowledge representation model, learning system, learning, ontology, ontological model, OWL, RDF

  • Analysis of identification methods when determining the contours of skins from photographs

    The article discusses correlation methods of image identification. An algorithm of the "rare grid" method has been developed.

    Keywords: image identification, algorithm, recognition, cutting, reference frame, element correlations, minimum search

  • Development of a recommendation system for training selection

    The article discusses the methods and approaches developed by the authors for the recommendation system, which are aimed at improving the quality of rehabilitation of the patient during respiratory training. To describe the training, we developed our own language for a specific subject area, as well as its grammar and syntax analyzer. Thanks to this language, it is possible to build a devereve describing a specific patient's training. Two main methods considered in the article are applied to the resulting tree: "A method for analyzing problem areas during training by patients" and "A method for fuzzy search of similar areas in training". With the help of these methods, it is proposed to analyze the problem areas of patients' training during rehabilitation and look for similar difficult areas of the patient to select similar exercises in order to maintain the level of diversity of tasks and involve the patient in the process.

    Keywords: Recommendation system, learning management system, rehabilitation, medicine, respiratory training, marker system, domain-specific language, Levenshtein distance

  • Organization of a competition for regression models of unloading wagons on railway transport

    The paper describes the procedure for conducting a competition for regression models based on statistical data for the East Siberian Railway. At the same time, it is assumed to build a set of additive alternative versions of the model with the subsequent choice of the best option based on the involvement of a number of adequacy criteria. The unloading of wagons is singled out as the output variable of the model, and the input variables are: the average gross weight of a freight train, cases of failures of technical means of the 1st – 2nd category of operational nature, the working fleet of freight wagons. The implementation of the model competition allowed us to build over two hundred alternative options, from which the best alternative was selected using multi-criteria selection methods based in this case on a continuous criterion of consistency of behavior.

    Keywords: railway transport, mathematical model, regression analysis, least squares method, model competition, adequacy criteria, multi-criteria selection

  • Using machine learning to promote websites

    Search engine optimization allows a website to rank higher in search engines. Through a lot of manipulations on working with the site, you can achieve good results in increasing the conversion of sites. Modern systems for all kinds of data analysis using neural networks can greatly improve the work on this optimization.

    Keywords: website promotion, search engine optimization, neural networks, code optimization, convolutional neural networks

  • Application of machine vision methods on embedded systems

    The article discusses the application of machine vision methods for embedded systems using modern microcontrollers. Machine learning methods that are used in embedded systems to solve recognition problems, as well as neural network models, are described. The use of trained models for solving image recognition problems in embedded systems is proposed. The architectures of YOLOv3 and R-CN neural networks are compared. The Jetson TX2 hardware platform is considered. The results of comparing the calculation speed for different modes of the device are presented.

    Keywords: machine vision, neural networks, artificial intelligence, embedded systems, pattern recognition, YOLO, RCN, Jetson, Tensorflow

  • Method of calculating the application coefficient of the standard control system equipment on the test bench

    The article considers an approach to estimating the application coefficient of standard control system equipment on a test bench. The relevance of the evaluation task at the design stage of the test bench is shown and a description of the method for solving this problem is given. The proposed approaches can be applied both at the stage of creating a test stand and when upgrading an existing positionю.

    Keywords: automatic control system, test bench, analysis of the testing process, experimental testing, standard equipment, centralized control software package, application coefficient of equipment

  • Development of an advisory system for evaluating a person's image

    The development of a decision support system for evaluating a fashionable image of a person is described. This is done by selecting a set of visual attributes from an image and comparing this set with "fashionable" patterns. Fashion patterns are set by the user himself. These are images that are defined in the system as reference images. This paper provides an overview of decision-making methods, analyzes the relevance of decision-making systems in different spheres of society. The algorithm of the program and the tools with which the image is first preprocessed are considered, then the visual attributes are highlighted. The method of making decisions for different types of attributes is given. The comparison of colors in HSL notation is considered.

    Keywords: decision support system, decision making methods, machine learning, Python, model learning, image, fashion, information and analytical system, k-means method

  • Recognition of a clothing brand by image using machine learning methods

    The article discusses the developed model for recognizing a clothing brand by image. The model not only predicts the type and brand of clothing, but can also determine their similarity. At the initial stage, a dataset was collected containing images of clothing from various brands with a total volume of 9,000 images. In this work, the ViT (Vision Transformer) neural network architecture was used, a model for working with images, which was presented by experts from Google Brain. The vit-base-patch16-224 model acted as a representative of the transformer architecture. Before training, all images were converted to black and white, and data augmentation was also used: image rotation by a random angle, mirror transformation. All photos have been normalized – pixel coordinates have been adjusted to the interval [0,1].

    Keywords: neural network, model, machine learning, Vision Transformer, fashion industry, clothing brand prediction, clothing type prediction, brand similarity determination

  • Study of the effect of light on the operation of machine vision sensors

    Research subject. The influence of the intensity of the light source and the direction of its beam on the process of object recognition by machine vision sensors - visible spectrum cameras and light detection and ranging systems (LiDAR) has been studied. Factors such as the intensity of light, its trajectory and the angle of the beam relative to the horizon are taken into account. Method. The solution to the problem of analyzing the ability of machine vision sensors to recognize the ArUco marker under conditions of various levels of illumination is based on empirical research methods. The main results. During the recognition of objects by a machine vision camera at a high level of illumination, a distortion of the light flux on the camera matrix occurred. Bugs in the operation of LiDAR were also found. Practical significance. Obtaining research results was used to develop a means of assessing a high level of assessment of a high degree of probability of detecting objects of sensory vision.

    Keywords: machine vision, LiDAR, influence of light, empirical study

  • Development of a computer program intended for experimental studies of metallic materials microstructures

    The text describes software tools for analyzing the structure of metallic materials, including ferrous and non-ferrous metals. It presents image processing methods for edge detection and segmentation of structural elements on the metal surface. A Python program is described, which applies watershed algorithms and searches for white and black grains to segment metal images. The program performs analysis of grain sizes and shapes, and the results are presented visually and for further use. This tool is crucial for quality control and optimization of the properties of metallic materials.

    Keywords: software tool, metal, quantitative analysis of microstructure, computer program, Python programming language

  • Comparison of the Kanban method and the multi-agent approach in the distribution of resources between the same type of units of an industrial enterprise

    Large industrial enterprises can be compared to a complex dynamic system in which management decisions are constantly required. One of the main management decisions, on which the main performance indicators of the enterprise depend, is the process of managing the planning of production. In the process of organizing decision-making, information systems can be used, which are based on mathematical and heuristic calculation methods.organizations of the new enterprises, redistribution of investments in interests of the organization and development of new production on available floor spaces. The most important organizational economic targets of a diversification of management are presented by innovative activity of the industrial enterprise.

    Keywords: production planning, resource allocation, Kanban

  • Analysis of the testing time of the control system on the test bench

    The article analyzes the testing time of the control system on the test bench, identifies the components of the testing time, and provides the calculation procedure for a typical test bench. The results obtained can be used to estimate the time of testing control systems at the design stage of test benches.

    Keywords: automatic control system, rocket and space technology, test bench, analysis of the testing process, experimental testing, testing time

  • Geoinformation mapping of road conditions using OpenStreetMap spatial data

    In this paper, the importance of transport networks for the development of the country's economy is considered. It is determined that at the same time, a huge number of heterogeneous factors affect the functioning of transport networks. In this case, in order to optimize transportation processes, it is necessary to have information about the state of the road network in advance. Geoinformation systems are an effective tool for presenting data of this kind, which allow storing and processing spatial and related attribute data. The author proposes a technique for geoinformation mapping of road conditions using the open OSM project. Openstreetmap provides access to up-to-date geographical information, as well as software tools for data processing. The paper defines the type and levels of damage to the roadway, a geoinformation project has been developed, which reflects the main types of damage to the roadway of a section of the road network.

    Keywords: geoinformation system, geoinformation mapping, road network, OpenStreetMap

  • Age structure of the forestry fund of the Republic of Karelia (analytical review)

    Maintaining the optimal age structure of the forestry fund is an important factor in the use of forest resources. The purpose of this study was to analyze the age structure of the forestry fund of exploitation forests of the Republic of Karelia. For this purpose, data on the age structure of the forest fund by species groups was collected for 17 central forest districts of the study region. Data sources were forest planning documents. The results of the study showed that coniferous forests predominate in the Republic of Karelia. Deciduous tree species are more widely represented in the southern part of the study region. Deciduous and coniferous forests have different age structures. Young stock, mature timber and overmature forest predominate. At the same time, Young stocks are predominantly represented by coniferous forests. A small proportion of forest approaching maturity is one of the fundamental problems of the region under study, as it helps to curb the increase in logging volumes.

    Keywords: forest resources, logging, age structure, coniferous species, deciduous species, ripening forests

  • Review of methods for detecting faults in a permanent magnet synchronous motor

    Overview of existing methods for diagnosing faults in synchronous electric motors and methods for their detection. Classification and analysis of existing methods, their applicability in detecting faults, advantages and disadvantages. Three classes of possible faults in synchronous permanent magnet motors are considered and described: electrical faults, mechanical faults, and demagnetization. The article discusses three classes of diagnostic methods: based on the construction of a mathematical model of a real electric motor and modeling its errors, based on processing signals from sensors, and intelligent methods based on processing collected data using artificial intelligence. The following error detection methods based on modeling are considered: detection based on the model of the electrical schematic, based on the analytical model, and based on the digital simulation model. The following frequency-time analysis methods of the obtained signals from the sensors are considered: analysis using fast Fourier transform, short-time Fourier transform, wavelet transform, Hilbert-Huang transform, and Wigner-Ville distribution. The following intelligent diagnostic methods are considered: diagnosis using convolutional neural networks, recurrent neural networks, support vector machines, fuzzy logic, and sparse representation.

    Keywords: Synchronous motor with permanent magnets, faults of electric motor, modeling, fast Fourier transform, wavelet transform, Hilbert-Huang transform, Wigner-Ville distribution, neural networks, fuzzy logic, support vector machine, sparse representation.

  • Possibilities for implementing the content and language integrated learning model at a university

    The article discusses the possibilities of implementing the model of subject-language integrated learning in higher education institutions, and the authors focus on their professional experience in implementing this model in Southern Federal University for undergraduates. The authors managed to highlight in detail the working options of CLIL, taking into account the specifics of the modern labor market. The authors conclude that the presented technology can and should be applied in practice while observing the principle of feasibility in the perception of professional content in a foreign language by the target audience. This approach requires the teacher to be flexible in the development of such disciplines, since their subject content is adapted in accordance with the language level of the students.

    Keywords: content and language integrated learning, social order, bilingual education, communicative approach, professionally-oriented content, didactic principles, professional

  • Development of a seven-channel laser system prototype for a multi-aperture wave-front sensor physical modeling

    The paper considers a model of a multi-aperture wave-front sensor for an active laser beam control system based on the iterative image reconstruction algorithms with limitations, particularly, on the Gerchberg-Saxton algorithm. The specifics of these algorithms is the presence of the so-called divergence factor which is characterized by obtaining “successful” and “unsuccessful” solutions, and may be clarified by stagnation conditions available (or by local extrema). The use of global optimization methods allows to avoid this constraint and to build quite an effective strategy for retrieving phase information. An experimental research was conducted to restore phase information using this method. For this purpose, a model of a seven-channel laser system with a different phase shift was developed.

    Keywords: multichannel laser systems, wavefront sensor, Gerchberg-Saxton algorithm, physical modeling, image reconstruction, phase retrieval

  • Mathematical model of optimization of the departmental segment of the feedback platform

    The paper considers the problem of managing the reliability of the departmental segment of the feedback platform, which ensures the reception and consideration of citizens' electronic appeals by the Federal Penitentiary Service of Russia. In this aspect, the reliability optimization problem is an optimal control problem with phase constraints. Using the method of penalty functions, the problem of minimal control is formulated, in which phase constraints are taken into account using an external quadratic penalty function. To solve the resulting problem, a wide range of analytical and numerical methods for finding the optimal solution is available.

    Keywords: public administration, feedback platform, departmental segment, queuing system, resource management, optimal management task, optimization task, Federal Penitentiary Service of Russia

  • About Vue, Svelte, Solid and Lit frameworks for developing client web applications

    This paper discusses the Vue, Svelte, Solid and Lit frameworks used to create the View part of client web applications. Their design, the proposed approach to developing client applications, the problems they solve and create, their strengths and weaknesses, as well as their features and limitations in application are studied.

    Keywords: Vue, Svelte, Solid, Lit, Web Components, view frameworks, client web applications, front end, rendering

  • Registration of holograms with an inclined reference beam using modern photosensors

    A method for recording holograms using digital cameras with high spatial resolution is considered. To register holograms obtained in optical setups with an inclined reference beam, a high resolution of registration systems is required. To do this, it is necessary to use media with a resolution of 2000-4000 lines per mm. The use of photographic plates requires a fairly long exposure and development time, which is usually done separately from the optical setup. In the case of holographic interferometry systems, it is necessary to provide for mounting the hologram back into the optical setup with sufficiently high accuracy. Therefore, digital holography methods have been developed to record holograms on photomatrices with limited resolution. These methods are based on the use of optical schemes at small angles (less than 5 degrees) between interfering beams. Recently, sensors with a single element size of 1.33 µm and 0.56 µm have appeared. This resolution makes it possible to return to registration schemes with angles between interfering beams of 30-60 degrees. This allows us to hope for the revival of holographic methods and methods of holographic interferometry at the modern level without the use of intermediate recording media.

    Keywords: holography, holographic interferometry, photomatrices with high spatial resolution, holography with an inclined reference beam, digital holography, Fourier transform

  • Investigation of the influence of the pre-trained bases of neural networks on the quality of segmentation of ore pieces in the photo

    The article deals with the problem of inaccurate allocation of the boundaries of ore pieces after an explosion in a quarry in the photo. In this article, the possibility of using neural networks for segmentation of photographs was investigated, and training, testing and comparison of the pre-trained bases of neural networks were carried out. The family of pre-irradiated bases EfficientNet and SEResNet was tested on the FPN neural network. Neural networks were tested on the same number of learning epochs, and competitively on three, five, seven and ten learning epochs. Training for more than ten epochs was impractical, since almost all networks were undergoing retraining. According to the results of the test and comparison, the result was obtained that the FPN neural network on the pre-trained EfficientNetB2 bases after 7 epochs of training has a segmentation quality of 98.93% in three segmentation classes and 55.1% in the "ore pieces" class.

    Keywords: segmentation, neural network, pre-trained foundation, EfficientNet, SEResNet