Информатика и вычислительная техника. Рубрика в журнале - Вестник Южно-Уральского государственного университета. Серия: Компьютерные технологии, управление, радиоэлектроника
Статья научная
Рассмотрено применение 3D параметризации как нового эффективного инструментального средства компьютерных графических редакторов САПР для решения задач геометрического моделирования. Показаны особенности и возможности 3D параметризации для создания алгоритмов решения задач и их исследования. В качестве примеров приведены сложные и исторически известные задачи: построение прямой, пересекающей четыре скрещивающиеся прямые (задача о трансверсалях), нахождение тетраэдра или тройки осей по их заданной проекции (реконструкция теоремы Польке - Шварца), построение сферы, касательной к четырем заданным сферам (задача П. Ферма), усложненный вариант задачи совмещения коники и квадрики. Показана доступность, эффективность и актуальность новых методов в сравнении с методами начертательной геометрии, обоснована необходимость включения их в учебный процесс геометро-графической подготовки студентов.
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A fingerprint matching algorithm
Статья научная
Fingerprint pattern knowledge is largely applied in many fields such as access control and identity administration. This is however associated with some problem of automatic fingerprint recognition and therefore this has rendered to the use of the most known method that is biometric identification. Every finger of the hand shows a different pattern of ridges and depression different from the other finger and this pattern remains sole and constant thus helping in identity since fingerprint pattern from one person is different to that of another person. This pattern may alter whenever there are cuts and bruises in the outer part of the finger. Fingerprint pattern recognition method includes the following steps: firstly, matching of the fingerprint which includes the pattern based method and the minutiae method. Secondly, the used algorithm in the recognition and comparing of the fingerprint images. Thirdly, the image enhancement process that helps to improve the quality of the fingerprint pattern and forth the reduction of the size of the image which includes identification of the region of small minutiae and actual minutiae. The objective of this research is recognition of the fingerprint pattern.
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Статья научная
The paper considers the process of algorithmization of reference security models implemented on the basis of the existing formal security models. Main approaches to practical implementation of reference security models in a key of identifying potential areas for improvement are studied. The paper describes the analysis of constraints of models for synthesis based on their formal reference model amenable to implementation in a software algorithm for subsequent practical security analysis of real systems. On the basis of a formalized model graph is built which combines multiple information security vulnerabilities and attack methods of realization of the consequences for the security systems on the basis of which controllable models of real systems can be created. An algorithm of the semi-automatic analysis of the security of corporate automated systems is developed.
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Application of Cutter-Jordan-Bossen method for data hiding in the image spatial area
Статья научная
The article deals with the main methods of digital steganography and presents a classification scheme. Special attention is paid to Cutter-Jordan-Bossen method for hiding data in the spatial area of the image. Aim. The study of digital shorthand methods, as well as the assessment of their applicability for hiding information in images. The main task is to analyze the Cutter-Jordan-Bossen method for hiding data in the spatial area of the image and evaluate its effectiveness under various conditions. Materials and methods. In this work, various methods of digital shorthand were used, including the Cutter-Jordan-Bossen method. Images of various types and quality, as well as various embedding parameters were used for testing. Results. As a result of the study, it was revealed that the Cutter-Jordan-Bossen method is effective for hiding information in the spatial area of the image. The dependence of the data extraction quality on the embedding parameters was tested, which showed that the optimal parameters depend on the type of image and its quality. The resistance of the information hidden by this method to distortion during compression was also tested. The test results showed that JPEG compression, even at low and high energy values, leads to the destruction of information hidden in the container. It was found that the best results are achieved when using the Cutter-Jordan-Bossen method with optimal embedding parameters, which allows you to save hidden information when compressing an image. Conclusion. In conclusion, we can say that the study of digital shorthand methods and their application to conceal information in images is an urgent and important topic. The Cutter-Jordan-Bossen method has shown good results in hiding information in the spatial area of the image, but for each specific case it is necessary to choose the optimal embedding parameters. It was found that JPEG compression can significantly affect the quality of information extraction, so it is necessary to take this factor into account when choosing a method for hiding data in an image. In general, the study of digital shorthand techniques and their application to conceal information in images can be useful for various fields, such as the protection of confidential information and digital watermark.
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Статья научная
Introduction. Currently, the Industry 4.0 concept integrates modern methodologies and practices for strategic and operational management of industrial enterprises and economies into the digital economy. It involves a wide and deep digitalization of physical and virtual objects, their connections, processes with the further possibility of their analytical analysis. Goal of the study. Analysis of the requirements for the degree of formalization of the description of the digital twin of the production system using graphoanalytic metalanguages classified according to the Chomsky hierarchy. Materials and methods. It is proposed to use a set-theoretic and categorical approach to the classification, identification, traceability and structuring of objects of production systems and their business processes in accordance with the requirements of quality standards. Results. The article substantiates the relevance of using intelligent business intelligence (BI) systems in the heterogeneous information space of a production system for analytical processing of semantic (content), logical and quantitative information. Conclusion. Modern organizations are complex systems, information management of which is provided by a wide range of software, a large number of data sources makes it difficult to consolidate data and receive aggregated reports. The use of intelligent business intelligence systems will allow targeted data extraction and analytical analysis. Models of business processes are isomorphically displayed in aggregate data accumulated in information systems. That is, these models are used to structure aggregate data in the required context.
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Applying bio-inspired algorithms to routing problem solution in FANET
Статья научная
The advances in Unmanned Aerial Vehicles (UAVs) development provide new opportunities for their civil application. UAVs are an integral part of the scientific research nowadays. UAVs implementation requires that a group of interacting UAVs takes part in the task completion. Organizing a multi-UAV network calls for special routing algorithms developed with due concern of their features. The article gives a brief review of the existing routing algorithms for ad hoc networks based on swarm intelligence. The test analysis has been carried out proving that bio-inspired algorithms can be effectively applied to solve the routing problem in FANET networks. This has been proved on the example of BeeAdHoc and AntHocNet, modeling the natural behavior of bees and ants.
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Approach to educational course comparison using natural language processing techniques
Статья научная
As numbers of educational programmes and courses grow, the need for a method of comparison becomes apparent. In this paper we discuss the overall state of education data mining, the variety of document types and formats used for educational content and propose the combined similarity measure for educational course programmes, Our proposed similarity measure uses three most important in our opinion elements of course programmes - course descriptions, educational results of the course and the structure of the educational course. We describe our approach to calculate similarity for each of this component pairs as well as provide primary experimental results and their evaluation using mean average precision metric.
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Статья научная
Time series analysis became one of the most investigated fields of knowledge during spreading of the COVID-19 around the world. The problem of modeling and forecasting infection cases of COVID-19, deaths, recoveries and other parameters is still urgent. Purpose of the study. Our article is devoted to investigation of classical statistical and neural network models that can be used for forecasting COVID-19 cases. Materials and methods. We discuss neural network model NNAR, compare it with linear and nonlinear models (BATS, TBATS, Holt's linear trend, ARIMA, classical epidemiological SIR model). In our article we discuss the Epemedic.Network algorithm using the R programming language. This algorithm takes the time series as input data and chooses the best model from SIR, statistical models and neural network model. The model selection criterion is the MAPE error. We consider the implementation of our algorithm for analysis of time series for COVID -19 spreading in Chelyabinsk region, and predicting the possible peak of the third wave using three possible scenarios. We mention that the considered algorithm can work for any time series, not only for epidemiological ones. Results. The developed algorithm helped to identify the pattern of COVID -19 infection for Chelyabinsk region using the models realized as parts of the considered algorithm. It should be noted that the considered models make it possible to form short-term forecasts with sufficient accuracy. We show that the increase in the number of neurons led to increasing accuracy, as there are other cases where the error is reduced in case of reducing the number of neurons, and this depends on COVID -19 infection spreading pattern. Conclusion. Hence, to get a very accurate forecast, we recommend re-running the algorithm weekly. For medium-range forecasting, only the NNAR model can be used from among those considered but it also allows to get good forecasts only with horizon 1-2 weeks.
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Development of the identification system by fingerprints
Статья научная
Dactyloscopy (fingerprint recognition) is the most developed to the date biometric method of personal identification. The catalyst for the development of the method was its widespread use in criminology of the XX century. As each person has a unique papillary pattern of fingerprints, so identification is possible. Typically, algorithms use characteristic points on fingerprints: the end of the pattern line, branching lines, single points. In addition, information about the morphological structure of the fingerprint is attracted: the relative position of the closed lines of the papillary pattern, “arched” and spiral lines. Peculiarities of papillary patterns are converted to some unique codes, which preserves the information content of the fingerprint image. And it is “fingerprint codes” that are stored in the database used for searching and comparing. Currently, fingerprint recognition systems occupy more than half of the biometric market. A lot of companies are engaged in the production of access control systems based on the method of fingerprinting identification. Due to the fact that this direction is one of the oldest, it has become the most widespread and is currently the most developed. Fingerprint scanners have come a really long way to improve. Modern systems are equipped with various sensors (temperature, pressing force, etc.), which increase the degree of protection against counterfeiting. Every day the systems become more convenient and compact.
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Federated learning for vision-based obstacle avoidance in mobile robots
Статья научная
Federated learning (FL) is a machine learning approach that allows multiple devices or systems to train a model collaboratively, without exchanging their data. This is particularly useful for autonomous mobile robots, as it allows them to train models customized to their specific environment and tasks, while keeping the data they collect private. Research Objective to train a model to recognize and classify different types of objects, or to navigate around obstacles in its environment. Materials and methods we used FL to train models for a variety of tasks, such as object recognition, obstacle avoidance, localization, and path planning by an autonomous mobile robot operating in a warehouse FL. We equipped the robot with sensors and a processor to collect data and perform machine learning tasks. The robot must communicate with a central server or cloud platform that coordinates the training process and collects model updates from different devices. We trained a neural network (CNN) and used a PID algorithm to generate a control signal that adjusts the position or other variable of the system based on the difference between the desired and actual values, using the relative, integrative and derivative terms to achieve the desired performance. Results through careful design and execution, there are several challenges to implementing FL in autonomous mobile robots, including the need to ensure data privacy and security, and the need to manage communications and the computational resources needed to train the model. Conclusion. We conclude that FL enables autonomous mobile robots to continuously improve their performance and adapt to changing environments and potentially improve the performance of vision-based obstacle avoidance strategies and enable them to learn and adapt more quickly and effectively, leading to more robust and autonomous systems.
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Informational support of decision-making based on intellectual adaptive forum
Статья научная
This paper focuses on the issue of online forum information overload. Web forum technology are considered, the disadvantages of existing implementations which leads to the problem of information overload are defined. Also, the paper described the existing methods of solutions to this problem. The algorithm of structural and semantic analysis on the web forum that allows combine messages into logical units (subtopics) was offered. Structural web forum adaptation methods based on this algorithm, to automatically structure the web forum posts, according to their semantic content, was proposed. The prospects of using this approach to deal with information overload were shown.
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Статья научная
This study examines the perspective of artificial neural networks for forecast Normalized Differential Vegetation Index (NDVI) on Diyala River basin and also how information about of bioclimatic landscapes will affect to forecasting performance. To do this, in the first stage of the experiment, a total of 20 perceptrons with different one hidden layer architectures were trained with site-specific variables (latitude, longitude, minimal, maximal and mean height, landcover type) and seasonal meteorological variables (precipitation sum, and minimal, maximal and average daily temperatures) by error back propagation algorithm on the data of 2000-2010 years and tested on data for 2011-2016 years. It has been shown that the best performance, with determination coefficient R2 of 0.78, was achieved by perceptron model with 12 hidden neurons the activated by logistic activation function and hyperbolic tangential activation of output value of NDVI. The large spatial heterogeneity of forecasting performance of the best perceptron was detected: in upper part of basin characterized according to Köppen - Trewartha bioclimatic classification, as landscapes of temperate mountain climate and the subtropical climate with dry summers, R2 was 0.76-0.80, whereas in dry steppe landscapes and semi-desert landscapes of Diyala downstream R2 was 0.6-0.7. The second stage of experiments with 20 models of perceptrons where the type of landscape was added as input variable or where 150 individual perceptrons were selected for each landscape, have shown that these approaches allows to R2 increase up to 0.73-0.85. However, the strong contrast between characteristics of individual models complicates their use in the practice and requires to finding of new forecasting approaches.
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Mathematical model of geodinamic risk assessment
Статья научная
A mathematical model of geodynamic disasters assessment, specifically earthquakes, based on an analysis of geodynamic instability indirect indicators, namely, horizontal gradients of gravity anomalies in isostatic reduction, is presented in this paper. Special attention is paid to the probability mathematical model of assessment of seismic risks, the core of which is the representation of probable geodynamic states of geologic environment as a simplest event flow, followed by the construction of the Kolmogorov differential equations system. The principal results of the practical application of the mathematical models developed by the authors to assess seismic risks exemplified by way of the examples of the Baikal region and the north-western territory in Turkey are given and considered herein.
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Merge of microelectronics and human nervous system
Статья научная
The main theoretical aspects necessary for understanding the functioning of biological neural networks for the purpose of their subsequent reproduction in the form of equivalent electronic devices are considered in the article. The devices used for the last 4 years for direct interaction with neurons and their drawbacks are considered, as well as a model of a flexible and effective device, that does not face the problems discussed and allows interacting directly with the human nervous system at several levels.
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Статья научная
The use of neural networks for the classification of text data is an important area of digital transformation of socio-economic systems. The article is devoted to the description of the methodology for classifying citizens' appeals. The proposed technique involves the use of a convolutional neural network. The stages of processing citizens' appeals in the amount of 7000 appeals are described. In order to reduce the dimension of the problem, methods of filtering and removing stop words were applied. The resulting data set allows you to choose the best classifier in terms of accuracy, specificity, sensitivity. Training and test samples were used, as well as cross-validation. The article shows the effectiveness of using this method to distribute requests on 15 topics of citizens' appeals to the “hotline” of the President of the Russian Federation. Automating the classification of received appeals by topic allows them to be processed quickly for further study by the relevant departments. The purpose of the study is automation of the distribution of citizens' appeals to the President's hotline by category based on the use of modern machine learning methods. Materials and methods. The development of software that automates the process of distributing citizens into categories is carried out using a convolutional neural network written in the Python programming language. Results. With the help of the prepared data set, the pre-trained model of NL BERT and sciBERT was trained by the deep learning method. The model shows an accuracy of 86% in the estimates of quality metrics. Conclusion. A pre-trained model was trained using a convolutional neural model using a prepared data set. Even if the forecast does not match the real category, the model gives a minor error, correctly determines the category of the appeal. The results obtained can be recommended for practical application by authors of scientific publications, scientific institutions, editors and reviewers of publishing houses.
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Methods and principles of using a priori knowledge in recognition tasks
Статья научная
The using of a priori knowledge is an important part of the development of pattern recognition systems. Often the proper use of a priori knowledge allows bring quality of recognition algorithm to the level of practical usage. The main advantage of using a priori knowledge is that the classification algorithms are prone to errors, whereas a priori statements are always true. In the article will be show how to improve the quality of recognition system using a priori knowledge. The evolution of approaches to the use of knowledge considered by the example of the task of object detection, the advantages and disadvantages of these approaches analyzed. The basic principles of using a priori knowledge in recognition algorithms formulated.
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O точности численных методов решения уравнений Вольтерра I рода в задачах теплопереноса
Статья научная
Статья посвящена исследованию точности методов решения задачи измерения, возникающей при определении температуры внутри объекта, подвергаемого влиянию внешнего управляющего теплового воздействия. Подход к построению численного решения задачи измерения, связанной с проблемой определения температуры, основан на сведении первоначальной задачи к решению интегрального уравнения, характеризующего прямую зависимость температуры от измеряемых величин. Интегральное уравнение получено с помощью прямого и обратного преобразований Лапласа с привлечением регуляризующего подхода и математического аппарата теории обратных задач. Результирующее интегральное уравнение относится к классу уравнений Вольтерра I рода типа свертки с ядром, имеющим специфические особенности. В данной работе исследуется точность численных методов решении интегрального уравнения со специфическим ядром с точки зрения механизмов реализации машинной арифметики. Вычислительные схемы методов основаны на использовании product integration method, квадратуры средних прямоугольников. В работе также приведены результаты исследования погрешности вычислительной схемы оптимального по порядку метода, основанного на применении преобразований Фурье и метода проекционной регуляризации. Метод применяется для непосредственного решения исходной задачи без перехода к интегральной модели и позволяет получать численные решения с гарантированной точностью. С целью получения экспериментальной оценки точности численных методов и сравнительного анализа машинной точности методов интегральной аппроксимации и оптимального по порядку метода проведен вычислительный эксперимент. Результаты эксперимента свидетельствуют о принципиальной возможности получения численных решений задачи измерения с высоким уровнем точности.
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On exponential stability for linear difference equations with delays
Статья научная
The article gives an overview of recent results on the stability of finite-difference equations with delay. All results are compared with known signs of exponential stability of linear difference equations. The results are obtained using the Bohl-Perron theorem and comparing the equation under study with an equation for which the Cauchy function is positive. The Bohl-Perron theorem allows us to reduce the question of the exponential stability of a linear difference equation with delay to the solvability of an operator equation in one of the functional infinite-dimensional spaces. That is, in fact, to an estimate of the norm or the spectral radius of a bounded linear operator in this space. For this estimation, different difference inequalities are used. One way to obtain such inequalities is to evaluate the fundamental solution in the event that this solution is positive.
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Review of image reconstruction methods in X-ray computed tomography with cone-beam geometry
Статья научная
The article reflects the main task of the X-ray computed tomography and its mathematical description. Direct and inverse Radon transform are given. The methods of image reconstruction in X-ray computed tomography are presented. Their brief classification are given. The author have reviewed classical problem of two-dimensional computed tomography and basics approaches to its solution. Emphasis is placed on back projection algorithm with filtering convolution. The derivation of the algorithm for parallel and fan-beam reconstruction are given. The analysis of the problem of three-dimensional reconstruction are presented. The author describes the additional conditions imposed on the projection data, the computational efficiency of the algorithms and the quality of the images. The basic trajectory of the X-ray source, providing the condition Tuy, are considered. The article gives an overview of existing methods of three-dimensional reconstruction with cone-beam geometry, their advantages, disadvantages, clinical applications. Their brief classification are given. Approximate algorithms of three-dimensional reconstruction are presented. The Feldkamp algorithm, the extended parallel backprojection, and the advanced single-slice rebinning are described. The author raises the question of developing approaches and methods for obtaining images with three-dimensional reconstruction for cone-beam spiral CT.
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Universals and mathematical linguistics
Статья научная
Universals (from Latin “universalis” - general) - general concepts - are a subject matter of logicians since the ancient times. The question of universals represents the eternal issues. The nature of universals was thoroughly studied the philosophers of the Middle Ages. In IX-XIV centuries the scholastics continued the discussion about the essence of universals: do they really exist or are they certain names? The supporters of realism claimed that universals really existed and preceded the emergence of singular objects. Nominalists (from the Latin word ‘nomen’ - name) defended the contrary view point. In the article we emphasize the linguistic aspect. Mathematical linguistics develops methods of learning natural and formal languages. Linguistics, logic and mathematics are closely connected. Besides, there exists psycholinguistics as well. In our paper we consider current difficult sections: logic and linguistics of non-formalized and even non-formalizable concepts, the topic closely adjacent with the one discussed in the book by T.K. Kerimov of the same name. These sections broaden the opportunities of studying complex systems of logic and linguistics. As it was noted by the authors of “Mathematical linguistics” (R.G. Piotrovsky, K.B. Bektaev, A.A. Piotrovskaya) mathematics and a natural language represent semantic systems of information transfer. Moreover, there occurred a verbal analysis of mathematical problems solution. Language universal, a feature common for all the languages, is a kind of generalization of the language concept. The existential assertion of universals gives the opportunity to formulate a more grounded theory and practice of linguistics. The language universal determination is based both on extrapolation and empirical matter.
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