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Accepted papers
Visualization of Complex Roots for Nonlinear Algebraic Equations
Mehmet Pakdemirli
Accepted: 2025-05-26
Abstract
Visualization of complex roots of a nonlinear algebraic equation is discussed in this work. The method is based on calculating the modulus of the complex valued function and representing it as a surface in a three dimensional space where the axis consist of real and imaginary axis and the modulus function. Since it may be inconvenient to visualize multiple roots in a three dimensional surface, contour plot is suggested as an alternative to visualize better the location of roots. Roots of polynomial functions as well as non-polynomial functions are treated as examples. The contour plot is the best to visualize the complex roots in a single graph.
Simulation and visualization of optical distortions for virtual surveillance devices
A.V. Maltsev
Accepted: 2025-05-24
Abstract
The paper describes methods and approaches for imitation of optical effects when rendering images from models of various surveillance device in a three-dimensional virtual environment. This allows for the possibility expansion of such modeling by ensuring coverage of a wide range of real devices as prototypes for the virtual analogues being created. An original approach to two-stage image synthesis with radial distortion implementation is proposed, as well as methods and algorithms for simulation of lateral and longitudinal chromatic aberrations. Developed solutions are based on the use of modern multi-core graphics processing units and shader rendering technology. They provide visualization of video streams from simulated surveillance devices in real time. Software modules were created based on developed methods and approaches. Approbation of them was carried out in virtual environment system VirSim and showed adequacy and effectiveness of proposed solutions when using in virtual environment systems and training complexes.
DATA CLASSIFICATION WITH USING VISUALIZATION TOOLS
Andrey Dzengelewski
Accepted: 2025-04-29
Abstract
This article discusses ways to use visualization tools to build object classifiers during automation of a large enterprise. The proposed approaches allow stakeholders to get a visual representation and participate in the decisions required when building a classifier for large arrays of records.
The use of visualization tools is considered when selecting classification objects, determining the attributes and values of classification attributes, ensuring the convenience of the classifier and implementing conflicting requirements from stakeholders. Among the proposed solutions, the methods of using system classes, building logical and physical models of the classifier, multidimensional classification, attribute-value data model, logical data model for describing the required analytics are described.
The subject area is a classifier of works and services, examples of using the proposed solutions and the results of building a classifier at a large enterprise are given.
Design of a Hybrid Metric for Fingerprint Image Matching: A Grediant, Aczil, and SourceAFIS Approach
Mohammed Abdulameer Aljanabi, Noor Abd Alrazak Shnain
Accepted: 2025-04-29
Abstract
One of the most popular biometric matchings is the fingerprint used for personal matching, verification, and authentication. Numerous fingerprint metrics have been developed to detect various types of fingerprint image distortions. The majority of these metrics are based on a single approach. It is feasible to match a specific person's fingerprint image by comparing images of the same person's fingerprint, which we will discuss in detail in this paper. In this work, we provide an alternative technique by interpolating the Aczel metric with gradient matching and Source Automated Fingerprint Matching System (SourceAFIS) algorithm. The Aczel metric demonstrates strong predictive capabilities in discerning relationships among intensity values within fingerprint images while gradient matching is used to gage the change in contrast and structure in images. SourceAFIS describes fingerprints using high-level abstractions called minutiae, creates edges, matches minutiae and edges, and scores pairings based on random feature likelihood. The combined method has been tested against powerful statistical approaches for image analysis such as gradient matching metric and SourceAFIS matching algorithm. Simulation results using four well-known FVC2000, FVC2002, FVC2004, and FVC2006 image databases prove the effectiveness of the proposed technique achieves better consequences than the current methods in matching fingerprint images.
Using Sperm Imaging with Laser Interference Microscopy for Comprehensive Assessment of the Functional State of Cells during Cryopreservation and under the Action of Molecular Hydrogen
A.V. Deryugina, M.N. Ivaschenko, P.S. Ignatiev, V.B. Metelin
Accepted: 2025-04-29
Abstract
Significant advances have been made in sperm cryopreservation but the search for effective sperm cryopreservation technologies is a pressing issue in modern biology and medicine. The most effective cryopreservation leaves 50-60% of viable cells. The paper discusses the use of molecular hydrogen (H2) as a new approach to enhancing sperm protection during freezing and thawing. H2 is a universal antioxidant and limits damage to biomolecules. Visual registration of spermatozoa under the action of H2 was performed using modern microscopy techniques. Laser interference microscopy was used in the work. Laser interference microscopy records the cell surface architectonics depending on the modulation of the optical density of cellular structures. This visualization option provides information on the metabolic level and expands the possibilities for interpreting experimental results. Sample preparation, dyes, and fixatives are not used in interference visualization. The paper presents an analysis of phase images of spermatozoa during cryopreservation and using H2 as a cryoprotector. Verification of the method for analyzing phase characteristics of spermatozoa as an indicator of the metabolic state of cells was performed by analyzing clinical and laboratory parameters of spermatozoa. The phase height of spermatozoa during cryopreservation decreased, the intensity of energy processes decreased, and the oxidative potential of cells increased. A direct correlation was shown between the phase height of spermatozoa and the concentration of ATP, and an inverse correlation was found from the concentration of malondialdehyde (MDA). The use of H2 determined an increase in the phase height of spermatozoa, an increase in energy metabolism, and a decrease in cell oxidation. Changes in the metabolic activity of spermatozoa under the action of H2 were combined with an improvement in sperm fertility. Thus, phase interference microscopy allows for a qualitative and quantitative assessment of the physiological state of spermatozoa. It is an objective method of vital analysis of complex metabolic activity of cells. It can be used for express diagnostics of their functional state.
Glyph-Based Approach to Web Rendering of Geophysical Fields in Geoinformation Systems
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Accepted: 2025-04-29
Abstract
One of the significant problems in visualizing geophysical fields is the inability to simultaneously represent them as an integrated spatial layer, taking into account the complex nature of the parameters being analyzed. Currently, the designated visualization task is solved by decomposing the set of parameters into separate components, followed by rendering spatial layers that are not connected to each other either visually or logically. As a result, information that is important for research or decision-making is lost due to excessive overload of the geopatial image.
The paper proposes an approach to visualizing multicomponent geophysical fields based on graphical primitives called tensor glyphs, which are combined into a single spatial layer to represent several components of the geophysical field. Each individual image is a superellipse, composed of ellipses distributed along the axes and scaled according to the analyzed values, whose intersection points with each other and with the axes provide reference points connected using Lamé curves.
The operability and clarity of the proposed solution are examined using the parameters of the geomagnetic field as an example. Additionally, an analysis of performance metrics for its web implementation is conducted, which allows evaluating the quality of the corresponding solutions.
The Hashtag Health Revolution: A Bibliometric Study of Social Media in Health Literacy
Jasimudeen S, Jobin Jose, Deumy John, Jubin Jacob, Justin Joseph, Sheena George
Accepted: 2025-04-26
Abstract
This comprehensive study examines the burgeoning role of social media in public health literacy, utilizing Scopus as the primary database due to its extensive journal coverage. The study follows a PRISMA flow diagram to identify, screen meticulously, and include relevant papers in the bibliometric analysis. Using CiteSpace and Bibloshiny software, this study analyzes annual scientific production, identifies the most relevant sources and authors, and pinpoints the most globally cited documents. It explores trend topics, thematic maps, keyword co-occurrence, network analysis of cited journals, and timelines view of cited references and country collaboration. The findings highlight social media's critical role in disseminating health-related news, research updates, and personal experiences, especially during health crises like the COVID-19 pandemic. Health organizations and professionals are noted for utilizing social media to educate younger, digitally-savvy audiences about diseases, prevention, and healthy lifestyles. This research tries to analyse the prominence of social media in nurturing community sustenance and peer interaction, which is very significant for emotional welfare. Additionally, the study recognizes gaps in present literature and hands-on inferences for imminent studies, requiring more dedicated demographic research and the incorporation of progressive tools in health literacy.
Analysis of the Error Structure in Identifying the Author of a Text Using the Nearest Neighbor Graphs
M.Yu. Kislitsyna
Accepted: 2025-04-25
Abstract
In this paper, the nearest neighbor graph method is used to analyze the relationship between a large number of multidimensional vectors, which represents the distribution of letter combinations (n-grams) in the text, where n is 3. The task is the authorship attribution problem, which belongs to the field of natural language processing. The graph of the nearest neighbors is built according to the pattern distribution of the authors and visualizes the points of concentration and sparsity, which allows to identify the structure of text classification errors. The corpus consists of more 8 thousand authors and more 100 thousand literary texts in Russian including translations. Thus, this is one of the most extensive experiments with literary texts in Russian. All authors have at least five works in the corpus, each of which contains more than 10 thousand letters. The author's pattern is calculated by averaging the 3-gram statistics of his texts. The error structure associated with the proximity of texts and authors to the average pattern of lexicon is determined using graphs. It is shown that the densest centers of the graph are close to the average lexicon pattern with varying degrees of proximity. The text recognition error of such authors is about two times higher than the error of authors who are far from the lexicon. Some literary genres, such as philosophical ones, are localized at special distances.
Implementation of the Set-Theoretic Subtraction Operation in Point Calculus
A.A. Bezditnyi
Accepted: 2025-04-25
Abstract
This paper presents an approach to modeling solid geometric objects and their interactions using the apparatus of point calculus in the context of Boolean operations. The study explores the implementation of the Boolean subtraction operation for point-based bodies of various configurations. Parametric point equations are proposed for cuts and holes of different shapes, along with the required modeling parameters and their combinations.
Several modeling techniques are introduced, including the creation of holes through parameter adjustments without modifying the original point equations. This enables the construction of thin-walled structures based on point-defined solids. The method of combining surfaces into a unified body via a current point, with consistent parameter coordination, is also discussed. These techniques eliminate the need for intersection computations between surfaces, thereby avoiding issues such as discontinuities and invalid boundaries. The modeling accuracy is directly dependent on the available computational resources and is ensured by increasing the density of points within the solid object.
To visualize the equations obtained in the work, a point-represented geometric model is used, which is defined as an analytically defined ordered set of points in Euclidean space, formed using parametric equations, possessing a controllable internal structure and not requiring explicit topological connections.
Pressure-gradient method for the visualization of a wave attractor
Stepan Elistratov
Accepted: 2025-04-13
Abstract
A wave attractor, a phenomenon of self-focusing of internal/inertial waves on a closed trajectory, has recently been widely studied from different viewpoints. How-ever, there is a lack of investigations concerning its visualization. Peculiar set-ups lately studied show that conventional methods need some improvement.
Herewith, in gas dynamics, the Schlieren method, based on the density gradient, is widely used. Concerning incompressible flows, it is inapplicable; however, pressure can be considered instead density. In this work, a pressure gradient is used as a way to visualize an attractor.
Determination of Adiabatic Wall Temperature in High-Speed Gas Flows Using Infrared Thermography
Í.Ñ. Ìàëàñòîâñêèé, Í.À. Êèñåë¸â, À.Ã. Çäèòîâåö, À.Þ. Âèíîãðàäîâ
Accepted: 2025-03-21
Abstract
This paper presents a method for the non-contact determination of the adiabatic wall temperature in high-speed gas flows. The method is based on the processing of a sequence of thermograms obtained using an IR camera, within a program developed in Python 3.10. The approach demonstrated high efficiency when handling large datasets, particularly concerning minimizing temporal and computational demands. The adiabatic wall temperature was determined under both steady-state conditions, directly in the experiment, and transient conditions, through the extrapolation of the heat flux as a function of the current temperature of the examined surface. The effectiveness of this method was demonstrated in the investigation of non-mechanical energy separation in compressible gas flows.
Three-dimensional images of residual strain fields by wavelet transform method
I.V. Laktionov, E.V. Gladkih, A.P. Fedotkin, G.Kh. Sultanova, À.S. Useinov
Accepted: 2025-03-21
Abstract
The accuracy of measuring Vickers hardness values depends on image focusing both during automated determination of residual imprint diagonal lengths and during operator working. Widespread algorithms for image focusing are based on brightness and contrast adjustment. We propose a new approach based on alternative algorithms for more accurate microscope focusing system used in marking imprints after indentation. Implemented algorithms are based on variance, Laplace function and wavelet transform. We select the optimum values of the basis and transform depth when using the wavelet transform. We tested new approach on samples with poor contrast, rough surfaces, and materials with pile-ups occurred in the indentation process. Applying different focusing functions depending on focus position demonstrates a more stable performance of the algorithm with wavelet transform. We also demonstrated obtaining a fully focused frame and a pseudo three-dimensional map of the sample.
Visualization of the Assembly and Control Area of the BREST-OD-300 Reactor FA Using Virtual Reality Technologies
A.O. Tolokonskiy, D.G. Kovalionok
Accepted: 2025-03-20
Abstract
Currently, virtual reality technologies are used to train specialists in the field of nuclear energy, which allow the student to directly immerse himself in the environment of his activities, to conduct training as close as possible to real conditions, without causing harm to his health. In order to manufacture a fuel assembly (FA), it is necessary to pass a number of control settings at the production stage, confirming the quality and safety. The authors proposed the development of a virtual simulator with FA control settings for the BREST-OD-300 reactor plant, such as: FA washing and drying, FA tightness control, FA surface contamination control, FA mass and entry control into the slipway, FA geometry control.
This simulator was developed in the Unity environment using Oculus virtual reality glasses. The results of visualization of the control area allow checking the appearance of the FA for defects and damage, measuring the mass and length of the FA, as well as checking for tightness, absence of leaks and contamination.
Reconstruction of object inhomogeneity parameters by near-field measurements in microwave tomography using neural networks
A.V. Medvedev, M.Yu. Medvedik
Accepted: 2025-03-20
Abstract
The article proposes a method for reconstruction inhomogeneity parameters based on the results of near-field measurements in medical diagnostics. This is a classical inverse problem arising in various fields of science and technology. At the first stage, the problem of wave propagation inside an object is considered. A rigorous description of the problem is given both as a boundary value problem and as a volume integral equation. Next, using the numerical solution of this equation, the field values outside the body in the near zone are determined. At the second stage, using the obtained near-field values using a two-step algorithm, a search for heterogeneities inhomogeneities occurs. A specially trained neural network filters the values obtained before and after the two-step algorithm, thereby improving the quality of images visualizing inhomogeneities. Graphic illustrations of the original and restored values of inhomogeneities for the objects under consideration are presented. An experiment was conducted demonstrating the features of restoring object parameters using neural networks. The results show the effectiveness of filtering the calculated data by the autoencoder. A software package for determining the parameters of heterogeneities inside the object is proposed and implemented.
Visualization of Former Images of Destroyed Orthodox Churches Against the Background of Modern Reality Using Augmented Reality Technology
V.A. Nemtinov, V.F. Lisyunin, A.B. Borisenko, V.V. Morozov, Yu.V. Protasova, K.V. Nemtinov
Accepted: 2025-01-24
Abstract
Currently, virtual reality and augmented reality are among the most prospective technologies that are being implemented in many areas of human life. Augmented reality allows embedding virtual objects into real physical world. At the same time, it uses three principles of building augmented reality: Marker Tracking, Location-Based coordinate tracking and Image Tracking. In recent years, augmented reality technology has been widely used for preservation and reconstruction of cultural heritage. This article briefly examines the history of construction, operation and destruction of three of the seventeen churches in the city Tambov that existed at the beginning of the XX century: the Church in honor of the Intercession of the Holy Mother of God, the church in the name of Archdeacon Stephen (Utkinskaya Church) and the church in the name of the Great Martyr Barbara (Varvarinskaya Church). Based on available historical materials, the authors established a connection to famous people of Russia who lived and worked in the Tambov Region in the late XIX-early XX century and often visited these cathedrals, which were genuine decorations of the city. Reconstruction of destroyed Orthodox churches of the city of Tambov was carried out in the software for visualization of architectural projects Twinmotion. The images created by Twinmotion were then used to visualize the former images of destroyed Orthodox churches on the XXI century background using augmented reality technology, which provides integration of virtual objects into real physical world. The use of modern information technologies contributes not only to restoration and preservation of historical memory of Orthodox churches, but also to development and popularization of local history and museum activities, especially among the younger generation.
Visualization of Results of Bibliometric Analysis of Scilit Platform Data on AI & Machine Learning for 2021-2023
B.N. Chigarev
Accepted: 2024-12-16
Abstract
The aim of this study was to demonstrate the ability to visualize the results of the Scilit platform's bibliometric data analysis on the topic "AI & Machine Learning" to identify publications reflecting specific issues of the topic. Data source. Bibliometric records exported from the Scilit platform on the topic "AI & Machine Learning" for the years 2021–2023 were used. For each year, 6,000 records were downloaded in CSV and RIS format. Programs and utilities used. VOSviewer, Scimago Graphica, Inkscape, FP-growth utility, GSDMM algorithm. Used services: Elicit, QuillBot, Litmaps. Results. It has been shown that bibliometric data from the open access abstract database Scilit can serve as a quality alternative to subscription-only databases. Data exported from the Scilit platform require preprocessing to make them available in a format that can be processed by programs such as VOSviewer and Scimago Graphica. The use of GSDMM and FP-growth algorithms is effective for structuring bibliometric data for further visualization. The Scimago Graphica software provides wide possibilities for building compound diagrams, in particular, for representing the network of keywords in such important coordinates for bibliometric analysis as average year of publication and average normalized citation, as well as for building an alluvial diagram of co-occurrence of more than two keywords. The possibility of using such services as elicit.com, quillbot.com and app.litmaps.com to accelerate the selection of publications on the topic under study is shown.
Two-Channel High-Temperature Combustion Imaging System Based on High-Speed Cameras EVERCAM F 1000-16-C
F.A. Gubarev, L.Yu. Davydova, M.S. Tsiron
Accepted: 2024-11-24
Abstract
The paper presents the results of using Evercam F 1000-16-C high-speed cameras for high-speed visualization of laser initiation and high-temperature combustion of Al-CuO thermite mixture. The possibility of determining process parameters based on the results of high-speed shooting is demonstrated. Two visualization modes are considered: synchronous operation of two cameras to obtain images from two angles, and synchronous operation of two cameras as part of a laser monitor with a copper bromide vapor brightness amplifier. In the case of direct video recording, one of the cameras acts as the master one, and the recording frequency is set in the service program. It is proposed to use a two-angle video recording mode to study the spread of flame in a volume. For the first time, Evercam F 1000-16-C cameras were used as part of a laser monitor with a copper bromide vapor brightness amplifier. Laser monitoring, combined with direct video recording, makes it possible to study the surface of a sample in the area of igniting laser interaction and flame propagation in one of the planes. A feature of the operation of Evercam cameras as part of a laser monitor is the need to generate trains of clock pulses synchronized with the radiation pulses of the brightness amplifier and the radiation pulse of the igniting laser. In this case, both cameras work in slave mode. The synchronization unit is designed using the STM32F103C8T6 microcontroller board and has galvanically isolated input and output signals.
Visualization of Methods of Machine Learning. GUI Programming
N.O. Shesterin
Accepted: 2024-09-24
Abstract
The technologies of artificial intelligence and machine learning have made a fundamental leap in their capabilities in the last five years. The growth of processing power and the emergence of more and more effective methods of machine learning allows AI to not just solve the most typical tasks associated with the field, such as statistical analysis and optimization of mathematical processes, but also to find new applications in related fields of research, as well as practical applications, including those on the free market, available to the mass consumer. Image generation, audio, animation, self-learning models of control of robotic platforms and virtual mechanical models – these and many more novel applications of the recent years have led to a media-boom around AI and a growing interest from developers and authors from various fields and industries.
That being said, the methods for developing, research, testing, and integration of AI have largely remained unchanged and still require the knowledge of programming languages, machine learning libraries, as well as a deep understanding and experience specifically in the narrow field of AI. This barrier of specialization not only demands inclusion of machine learning specialists in the development process of otherwise trivial computer applications, typical for the field of AI, but also prevents small teams and independent developers from using the latest advances in these technologies without significant monetary and time investments into studying the subject.
I offer a novel solution to this issue in the form of a prototype graphical interface that allows the user without technical education and without the need for knowledge of programming languages to develop and tune various architectures of neural nets and other machine learning methods, methods of unsupervised machine learning, and to test these methods on a wide range of experimental tasks – from mathematical equations to controlling virtual mechanical models in a simulated physical environment. In this article, I give a brief description of its structure and organisation, its fundamental principles of operation, and the capabilities of this GUI.
Use of Hadamard matrices in single-pixel imaging
Denis V. Sych
Accepted: 2024-08-13
Abstract
Single-pixel imaging is a method of computational imaging that allows to obtain images of objects using a photodetector that does not have spatial resolution. In this method, the object is illuminated by light having a special spatio-temporal structure, — light patterns, and a single-pixel photodetector measures the total amount of light reflected from the object. The possibility of obtaining an image and the image quality are closely related to the properties of the applied patterns and computational algorithms. In this paper, we consider patterns obtained from modified Hadamard matrices and study the features of image calculation using single-pixel imaging. We show the possibility of reducing both the sampling time and the computational resources required to obtain images by modifying the pattern system. The proposed theoretical method can be used in the practical implementation of the single-pixel imaging method in an experiment.
Numerical Visualization of Vortex Wakes Behind Large Particles
À.À. Mochalov, À.Yu. Varaksin
Accepted: 2024-08-11
Abstract
An attempt has been made to visualize the flow formed in the wake of large particles moving in an ascending turbulent air flow in the channel. Numerical modeling was performed using a simplified version of the approach called "two–way coupling" (TWC) in English literature and taking into account the inverse effect of particles on gas characteristics. The particle motion was calculated in an approximate manner, therefore the method used is called "quasi – two–way coupling", TWC(Q). The results of numerical modeling of the characteristics of turbulent trails behind large moving particles based on the Reynolds averaged Navier-Stokes equations (RANS) are presented.
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