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.
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.
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.
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.
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.
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.
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.
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.
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.
The paper considers the foreign experience of teaching engineering students to analyze speech signals using instrumental methods. Examples of obtaining spectrograms are given, as well as the capabilities of speech analysis software used in undergraduate and graduate engineering courses at the University of California (Los Angeles, USA). The disadvantages of speech analysis and visualization based on Fourier transform are shown. New solutions for processing and visualizing speech signals based on multilevel wavelet analysis are proposed. The main characteristics of the developed WaveView and WaveView-MWA programs that provide increased time-frequency resolution of vowel sounds are considered. For the first time, the results of high-precision analysis and visualization of consonant sounds - non-stationary signals inaccessible to spectral analysis using the Fourier transform are presented. A comparative analysis of the time-frequency resolution of spectrograms and wavelet sonograms in the visualization of English speech is performed. The developed technology of high-precision analysis and visualization of speech signals is used in the training of specialists of the Department of «Information Security» of the Faculty of «Informatics and Management» of the Bauman Moscow State Technical University during laboratory work on the course «Forensic study of phonograms».
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.
This study presents a comparative analysis of software efficiency for photogrammetric digitization and visualization of energy infrastructure objects. Experimental evaluation was conducted on a production boiler house section using Agisoft Metashape, 3DF Zephyr, Meshroom, RealityCapture, Pix4D, and the neural platform LumaAI. Results demonstrate that RealityCapture delivers superior reconstruction accuracy (1-10 mm error) and geometric detail preservation under complex reflective surface conditions, attributable to its hybrid data processing algorithms and GPU optimization. LumaAI exhibits rapid data processing capabilities and hidden area reconstruction technology (NeRF), but remains unsuitable for digitizing classified infrastructure due to data leakage risks. Critical limitations were identified for Meshroom (inefficiency with large frame sets) and Pix4D (inadaptability to terrestrial photogrammetry). Sanction-related deployment challenges for RealityCapture in the Russian Federation are highlighted. The findings substantiate the necessity for specialized domestic solutions integrating classical method precision with AI algorithms while ensuring cybersecurity. This research establishes fundamental software selection criteria for energy asset digitization, digital twin development, and VR simulator creation.
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 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.
This paper examines the problem of targeted search for specific objects in a video stream on request and recording the timestamps of their appearance. Since the solutions currently available on the market were inadequate for the task, it was decided to implement such a tool independently as part of an ongoing research project conducted at the Keldysh Institute of Applied Mathematics of the Russian Academy of Sciences
The paper considers the principle of analytical transition to a local function at points on the domain of an implicit function defining a geometric object. Herewith, a transition to partial derivatives is provided to obtain a general form of an implicit local function describing the local geometry for any single point in the object domain. On the analogy of R-functional modeling, a mathematical apparatus for union/intersecting local geometric characteristics of a local function at a single point is provided to construct a discrete region of a complex geometric object. An example of the intersection of two functions on a defined domain of arguments demonstrates the obtaining of a discretely geometrized three-dimensional manifold for describing a cylinder. The proposed work is the continued development of method of the Functional Voxel Modeling which offers an analytical structure for the discrete-continuous description of complex geometric objects instead of the means of linear approximation currently used in this method.
Visualization of transport movement on the plane and in 3-dimensional space is presented. Examples of implementation using frameworks and libraries (WF, WPF, OpenVDB+Blender3D, Manim). A circle consisting of lanes in two-dimensional version and corridors in three-dimensional version was considered as a motion trajectory. The method of setting an arbitrary trajectory for the movement of agents in the model of transportation flow based on the action potential is considered. The formulas allowing to take into account the displacements of both the corridors of the trajectory and the positions of the agents in them are given. This allows us to correctly handle the rearrangements of agents between trajectories, as well as to visualize the simulation results.
The article describes a new method for testing the independence of random data sets. This method uses representation of connections between data points in the form of nearest neighbor graphs and compares parameters of the resulting specific graph — such as the number of connected components and vertex degree distribution — to numerically derived critical statistics for random nearest neighbor graphs obtained by the author. The proposed method can be applied to various practical situations. It can be used to test the independence of random vectors in low-dimensional metric spaces. Such problems arise when analyzing data from physical measurements. Additionally, this approach is applicable for analyzing random points in high-dimensional spaces where direct numerical evaluations require exhaustive enumeration and are therefore impractical or impossible to obtain exactly. This problem relates to object classification characterized by many parameters. Moreover, proximity function between points may not necessarily be symmetric, which allows application of graph methods even in such cases. Alongside the task of sample testing, one could also consider comparing pseudo-random number generators by benchmarking structural graph statistics based on them. Considered probabilities of graph structure realization provide an independent set of criteria. For example, the number of fragments in some random graph might be typical for independent random variables while vertex degree distributions could differ significantly. This extends the applicability domain of statistical analysis. The paper presents a collection of model examples illustrating how the methodology works with respect to several types of practical scenarios mentioned above. A comparison of this method with other statistical approaches is provided. We emphasize that using graphs as visualization tools enables immediate identification of dependent elements within samples if there exist cluster centers represented by vertices with anomalously large degrees.
The paper focuses on the visualization of vegetation arrays within virtual environment systems through a novel type of virtual object known as multiplicable point cloud (MPC). It addresses the challenge of adapting virtual vegetation samples, derived from 3D scans of real natural objects, to the MPC-format. The research highlights key discrepancies between these samples and the MPC-format, and presents a method to resolve these issues using the open-source CloudCompare software. Additionally, the paper proposes an output file format for the adapted virtual samples, utilizing a straightforward and easily interpretable PLY-syntax (Polygon File Format). Under the approbation of the proposed solutions, the adaptation and multiobject visualization of various virtual samples of tree- and grass-like plants were conducted. The results of the approbation affirm the expediency of the proposed method and approach, as well as their potential to effectively enhance the realism of virtual environments.
The peculiarities of unmanned vehicle application in the field of cargo transportation lead to the formulation of new problems for optimising cargo transportation plans, where several types of additional constraints and conditions must be taken into consideration simultaneously. The process of solving such problems requires considering and analysing numerous heterogeneous parameters, which is most effective when done interactively using visualisation techniques. We consider a problem involving the formation of heterogeneous cargo transportation plans using unmanned aerial vehicles, and propose an approach for constructing a visual model to support the interactive setting of problem parameters and to display optimisation results via a visual interface. This approach is based on the concept of visualisation metaphors, including spatial and representational metaphors. The structure and features of the metaphorical representation for different problem formulations and modelling stages are discussed.
