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Accepted papers
Generalized Computational Experiment State Analysis Using Three-Dimensional Visual Maps
A.A. Zakharova, D.A. Korostelyov, A.G. Podvesovskii, A.E. Bondarev, V.A. Galaktionov
Accepted: 2022-10-06
Abstract
The paper continues a series of publications of the authors’ research materials in the field of developing an approach to dynamic planning and control of a generalized computational experiment based on visualization methods and visual analytics. A generalized computational experiment involves multiple solution of a numerical simulation problem for different sets of values of model defining parameters, which makes it possible to obtain a solution immediately for a certain class of mathematical modeling problems specified in a multidimensional parameter space. The paper considers an extension of the existing authors’ approach to analysis of a generalized computational experiment state using visual maps, based on visualization metaphors that can display not only individual images but also their relationships. A method is proposed for constructing visual maps of a generalized computational experiment focused on visualizing relationships between single computational experiments in three-dimensional space. The method is based on the mechanism of formalization of the relationships between single computational experiments, as well as the concept of a graph model visualization metaphor that defines a visual map prototype. A description is given of a software system for constructing and analyzing three-dimensional visual maps of a generalized computational experiment. The paper also considers examples of its application in estimating the accuracy of numerical models of the OpenFOAM software platform for a three-dimensional problem of inviscid flow around a cone.
Towards Visualization of Generalized Mental Maps Representations
R.V. Chumakov, K.V. Ryabinin, K.I. Belousov
Accepted: 2022-10-06
Abstract
The paper is devoted to the visualization of generalized digital representations of mental maps. Digital mental map representations (DMMRs) are digital drawings of some certain spaces made by humans, reflecting their spatial experience and distinctive thoughts they have about the considered spatial places. Accordingly, DMMRs can be useful for identifying people’s subjective perception of some space. If there are many DMMRs and their manual analysis is difficult, some generalized representation can be used, which can help identify general patterns or trends in the perception of space by informants.
In addition to the visualization itself, this article also describes some of the issues that arise in the process of creating a generalized representation of the DMMRs and suggests novel methods for solving these issues. However, the proposed solutions do not guarantee full objectivity; they are only an approximation attempt. The methods to assess and increase the approximation quality are the matter of future work.
In previous works, the Creative Maps Studio web application was developed to collect DMMRs. This application is also used in this work. However, now it was been enriched by an analytical module that allows performing various transformations of the DMMRs and related data. This analytical module is based on the concept of data flow visual programming. Particular data processing operators within this module are described by ontologies. This makes that module quite flexible and easy to use. With the help of this module, the visualization of the generalized map is implemented.
One more question considered in the paper is the process of data preparation and visualization. Suggestions are made for the interpretation of the results. The strengths and weaknesses of the proposed data processing and visualization methods are discussed.
Cognitive Clarity of Graph Models: an Approach to Understanding the Idea and a Way to Identify Influencing Factors Based on Visual Analysis
R.A. Isaev, A.G. Podvesovskii
Accepted: 2022-10-06
Abstract
The article describes new authors’ approach to understanding the idea of cognitive clarity of graph models. A scheme for structuring concepts related to cognitive clarity is given. In accordance with this scheme there are distinguished cognitive clarity forming factors, cognitive clarity itself as a set of internal characteristics of a visual image of a model, as well as the effects of its presence revealed in the visual analysis of the model. Properties of various components of this scheme are discussed, and it is concluded that, due to their constructive nature, cognitive clarity forming factors are of the greatest interest. A detailed diagram of an approach to understanding cognitive clarity is described, based on two levels of a visualization metaphor, and individual components of this diagram are discussed. An approach is proposed to organizing experimental studies aimed at studying and evaluating the influence of various factors on cognitive clarity of graph models by measuring various indicators that characterize the degree of manifestation of cognitive clarity presence effects. The idea of this approach is to form a hypothesis about the influence of certain factors, followed by an experiment in which the analyst solves a certain task of visual analysis with the participation of these factors. As a result of registering the given indicators, the achieved effect of changing the level of cognitive clarity is assessed and the nature of the dependence or its absence is revealed, which makes it possible to accept, reject or refine the initial hypothesis. A generalized algorithm for preparing and conducting an experiment within the framework of the described approach is proposed, and implementation features of its individual stages are considered. An example of setting up an experiment is given, the purpose of which is to study the dependence of efficiency indicators of graph model visual analysis on the volume of its visual image. Promising areas of research in this area are discussed in the conclusion.
High-speed flow structures detection and tracking in multiple shadow images with matching to CFD using convolutional neural networks
I.A. Doroshchenko, I.A. Znamenskaya, N.N. Sysoev, A.E. Lutsky
Accepted: 2022-10-05
Abstract
Shadowgraph imaging has been widely used to study flow fields in experimental fluid dynamics. Nowadays high-speed cameras allow to obtain millions of frames per second. Thus, it is not possible to analyze and process such large data sets manually and automatic image processing software is required. In the present study a software for automatic flow structures detection and tracking was developed based on the convolutional neural network (the network architecture is based on the YOLOv2 algorithm). Auto ML techniques were used to automatically tune model and hyperparameters and speed-up model development and training process. The neural network was trained to detect shock waves, thermal plumes, and solid particles in the flow with high precision. We successfully tested out software on high-speed shadowgraph recordings of gas flow in shock tube with shock wave Mach number M = 2-4.5. Also, we performed CFD to simulate the same flow. In recent decades, the amount of data in numerical simulations has grown significantly due to the growth in performance of computers. Thus, machine learning is also required to process large arrays of CFD results. We developed another ML tool for experimental and simulated by CFD shadowgraph images matching. Our algorithm is based on the VGG16 deep neural network for feature vector extraction and k-nearest neighbors algorithm for finding the most similar images based on the cosine similarity. We successfully applied our algorithm to automatically find the corresponding experimental shadowgraph image for each CFD image of the flow in shock tube with a rectangular obstacle in the flow channel.
Graph visualization of the terminological thesaurus by F.M. Dostoevsky's Gospel text (using the example of bigram models)
V.V. Borisova
Accepted: 2022-09-24
Abstract
Methods and means of scientific visualization through graphs are actively used today in many areas, including the humanities. The effectiveness of their use is also evident in philological research. The article describes the graph model of the terminological thesaurus of the Gospel text by F.M. Dostoevsky, based on the clustering of digrams, taking into account their thematic belonging to different discourses. The identification and analysis of digrams as conceptual points of a terminological thesaurus is important for its network visualization, thanks to which it is clear in which conceptual conjugation key terms “work”, how they are distributed among certain clusters. In one cluster there can be terms from different discourses. This is an important indicator of how the terms are conjugated, how integral in this case is the metalanguage of the studies of the Gospel text by F.M. Dostoevsky. Those. the terminological thesaurus performs in this case a diagnostic and prognostic role.
Investigation of the algorithm for constructing a second-order surface defined by nine points
A.L. Kheyfets
Accepted: 2022-08-18
Abstract
An experimental realization of the historical problem of constructing a quadric given by nine points is presented. The well-known Engel algorithm (Engel J. H., 1889) is considered. Until recently the algorithm showed only theoretical possibility of constructing quadrics. Software is described which allowed experimental implementation and study of the algorithm. The programs were created in AutoLisp. Experiments have been carried out in the package AutoCAD.
Geometrical constructions leading to the realization of the problem are given. The stages of constructions are considered in details. The first and basic one is from setting nine points to building a cone on the quadric surface. The subsequent stages include setting the determinant of the quadric from three conics, construction of the center and main axes of the quadric, the framework and the final surface. The peculiarities of constructions at all stages are investigated. The main attention is paid to revealing and research of internal interrelations of parameters, leading to the appearance of real or imaginary solutions.
The scientific novelty of the work consists in the determination of conditions under which the solution is achieved without operations with imaginary parameters. The region of exact real solutions for a set of nine points is determined. It is shown that this area has the form of a curve line which is approximated by a hyperbola. An algorithm for its construction is proposed.
An algorithm for constructing the principal axes of the quadric is proposed and investigated. This algorithm is based on determining the secant plane, for which the perpendicular foot of the plane drawn from the center of the quadric coincides with the center of the conic section. The perpendicular takes the position of one of the principal axes of the quadric.
The relevance of the work lies in the experimental realization of Engel's historical algorithm and the creation and demonstration of modern geometrical methods for solving complex geometrical problems.
Overview of BSDF Reconstruction Methods for Rough Surfaces
V.G. Sokolov, A.G. Voloboy , I.S. Potemin, V.A. Galaktionov
Accepted: 2022-08-18
Abstract
The work provides an overview of methods aimed to the reconstruction of Bidirectional Scattering Distribution Function (BSDF) for rough surfaces. The elements with rough surfaces are permanently present in our life and widely used in modern optical devices, for example, in light guiding plates for display illuminating systems, car dashboards, or luminaires. Light scattering by rough surface is an important component in the visual appearance of many materials including water, glass, skin, etc. The problem of the rough surface visualization is complex and contains many different aspects. Accordingly there are many techniques to provide their realistic rendering. In many lighting simulation and optical design tasks it is sufficient and more effective to replace real geometry of rough surface by a surface optical characteristics expressed via BSDF. So, accurate reconstruction of scattering properties of rough surfaces is a significant factor in visualizations tasks and generation of photorealistic images. In some cases, BSDF can be just measured. However, in many cases direct BSDF measurements are impossible if, for example, it is required to define BSDF inside of the material and neither a measuring device detector nor a light source can be placed inside the material. So this results in the development of many approaches for BSDF reconstruction. It started in the end of the last century with the development of many analytical methods based on microfacet models of rough surface such as the Phong, the Ward reflection, the Cook-Torrance models. Nowadays many direct numerical methods of BSDF reconstruction appear, for example, methods based on normals and heights distribution. As a rule, these methods use ray tracing to calculate BSDF. Sizes of microroughness can be small, sufficient to raise a problem which optics wave or ray is more appropriate here. To answer this and other questions related to BSDF reconstruction, an investigation of well-known and effective reconstruct methods was conducted. This paper also presents the study results for eight real samples with different profile parameters of rough surface. The verification is based on numerical comparison with real measured data and visual comparison of images generated using different reconstructed BSDF. Finally, the general recommendations are presented about what methods and for what applications are more appropriate.
The Role of Subjective Perception in Visualization, Controllability Hypothesis and Abstract Visualization
Alena Zakharova, Aleksey Shklyar, Evgeniya Vekhter
Accepted: 2022-07-27
Abstract
Visual analytics tools are used when interpreting and analyzing weakly formalized or non-formalized data. The paper considers the problem of the influence of subjective factors on efficiency of the visualization tools. Based on the previously proposed and developed semiotic visualization model, a system of initiating factors is formulated that have a significant impact on the effectiveness of visualization tools. A controllability hypothesis is formulated, on the basis of which an assumption is made about limitations of visualization systems It is proposed to take these limitations into consideration when designing new visual analytics tools. Approbation of the assertions presented in the work was carried out on the example of social data.
Visual Management as an Effective Organizational Technology
N.N. Krupina
Accepted: 2022-07-25
Abstract
The article discusses the essence of the concept, characteristics, tasks and evolution of visual management (VM) from the standpoint of the analysis of the subject content of management and the features of organizational technology. The priority groups of production tasks that are successfully solved with the help of VM tools are identified - communications, safety and efficiency («lean production») of the production and technological cycle. Emphasis is placed on the ability of visualization techniques to present important operational information so that the employee «at a glance» can assess the current state of the working system and quickly eliminate detected deviations from the norm. Based on the principle of continuity of the organization's activities, a method for assessing the quality level of VM is proposed and illustrated on a conditional example. It is proposed to use the method of dynamic standards, which are taken as indicators of «labor productivity», «costs» and «net profit». A map of positioning options for the quality level of VM is given and alternative situations are characterized - productive, efficient, allowed and inefficient levels. In the context of the topic, the main aspects of the development of modern software are outlined.
Visualization of Digital Transformation of Industrial Production into the Educational Process
V.A. Nemtinov, A.B. Borisenko, V.V. Morozov, Yu.V. Nemtinova, K.V. Nemtinov
Accepted: 2022-07-25
Abstract
This paper considers the technology of creating an industrial production digital prototype, which can be used as a tool at the design and management stages of its functioning, as well as its application in the educational process while training highly qualified technical specialists - during lectures, practical and assessment classes with students. The virtual production space creation was carried out using the software environments Twinmotion, Bigscreen and 3D Vista Virtual Tour Pro. A digital prototype of a machine-building plant was created in the Twinmotion software environment, providing immersive architectural 3D visualization. The created virtual tour in the 3DVista Virtual Tour Pro environment is used for a variety of tasks: online discussion of the designed equipment 3D model; staff training; emergency situations drills; completing onsite educational quests. The Live Guided Tours tool included in 3DVista Virtual Tour Pro allows to conduct real time video conferences inside a virtual tour. The use of a multi-user social VR application for virtual reality Bigscreen provides network participants with the opportunity to meet and interact through avatars inside virtual reality rooms. Thus, the authors proposed an approach to the digital transformation of industrial production into the educational process. It allows us to provide conditions for improving the education quality, exchanging opinions, and mutual counseling. Visualization of a digital prototype of industrial production is available to all Internet users.
Arithmetic in Functional-Voxel Modeling
Alexey Tolok, Natalya Tolok
Accepted: 2022-07-19
Abstract
The paper considers the claim that the function-voxel model allows arithmetic operations over the space of values of two different functions given by a single domain. At the same time, there are three possible approaches to solving the problem, leading to a similar result: functional approach - when the analytical representation of functions is involved in the calculations; functional voxel approach - when voxel data representing local geometric characteristics are used in the construction of local functions for further use in the calculation; voxel approach - when exclusively voxel data is used for sequential recalculation of local geometric characteristics of the model. The basic arithmetic operations on functional voxel models are considered, including such procedures as: addition, subtraction, modulo, exponentiation, taking root expressions, multiplication and division of functional voxel models. It is shown that the obtained applicability of arithmetic operations to functional voxel models leads to obtaining new complex functional voxel models.
On the Visualization of Multidimensional Functions using Canonical Decomposition
A.K. Alekseev, A.E. Bondarev , Yu.S. Pyatakova
Accepted: 2022-07-14
Abstract
The approximation of a multidimensional function by means of tensor decompositions is considered in terms of storage, processing and visualization of the results of parametric calculations in computational aerogasdynamics problems. An algorithm for calculating the canonical decomposition using a combination of the alternative least squares method and stochastic gradient descent is described. Numerical results for interpolation of functions in six-dimensional space obtained using the canonical decomposition are presented, demonstrating the high computational efficiency and quality of results. Visual representations of the results are provided.
Method of Visualization of Geoinformative Data: on the Example of Reference Archaeological Objects
O.A. Ulchitskiy, E.K. Bulatova, E.K. Podobreeva, O.M. Veremey
Accepted: 2022-07-13
Abstract
The article reveals the results of an interdisciplinary study aimed at improving laboratory methods for collecting, analyzing and synthesizing geodata necessary to expand the methodological apparatus in scientific fields for the study and preservation of cultural heritage sites in vast areas, using triangulation in building a geogrid with reference to satellite cards. Data visualization significantly complements natural and instrumental methods of collecting information, searching, fixing, systematizing and inventorying in areas that are difficult to access for field research methods.
Fixation and binding of control points to the geogrid by the triangulation method is due to a number of advantages: the accuracy of building and fixing the binding objects, the possibility of scaling the grid, the triangulation algorithm along the smallest diagonal of the quadrilateral.
As a result of assigning properties of modifiers to reference points, which were selected as reference archaeological objects - the ruins of fortified settlements on high-resolution satellite maps, layers of inter-object edge connections were formed, which, when certain properties of modifiers were turned on, were displayed as differently colored edges on the geogrid, fixing invariants patterns of these relationships.
In the final experiment, we obtained a hybrid visualization of layers based on the specified properties of modifiers for edge connections, between reference objects in the geogrid system, which made it possible to obtain more objective results under the given conditions than by methods of constructing linear links by coordinates, using tracing and routing.
As an implementation of the results of testing the method, a project of an interactive scalable cartographic scheme with visualization of data on the objects under study and their relationships in a large location has been developed.
Single Image DnCNN Visibility Improvement (SImDnCNNVI)
Sangita Roy
Accepted: 2022-07-13
Abstract
The presence of fog, haze, or atmospheric particles reduces visibility which is an under-constrained challenging classical problem due to ambiguous scene radiance and transmission. Consequently, digital images captured under such conditions suffer from poor recognition. In this work, a fast single image physics based inversion scattering model is adopted to overcome these limitations. Denoising convolutional neural networks (DnCNNs) model is well suited for blind Gaussian denoising in a learning framework at hidden layers. With the DnCNN blind denoised depth map, high-quality transmission is estimated and finally by inverting scattering image formation model, a clear image is obtained along with tuned haziness factor. The proposed algorithm performs well compared to sixteen state-of-the-art methods qualitatively and quantitatively on Ground Truth (GT) O-Haze dataset. Output images are appealing, halo free, edge preserved, colour balanced, clear.
Software Package for Visualization and Modeling Based on BPMN Notation
N.D. Badanina, V.A. Sudakov, N.A. Yàshin
Accepted: 2022-06-27
Abstract
The article is devoted to the creation of software for visualization of complex processes. Since scientific organizations and business structures have demand for analysis and optimization of ongoing processes, the task of its effective modeling and visualization with the possibility of interaction is relevant. The software solutions available on the market are focused either on a static representation of the subject area, without the possibility of conducting computational experiments and optimizing solutions based on them, or on the use of non-standardized representations. A program has been developed that has the ability to animate the visualization of a loaded BPMN scheme, and also contains functionality for modeling the process described by the scheme, with the possibility of flexible parameter adjustment. The developed visualization program displays the result in the browser and a layer with animation of the passage of the involved resources according to the scheme is superimposed on top of the BPMN model. Visualization allows to reduce the probability of errors when modeling complex systems. The work also focuses on aspects of optimization, collecting statistics for subsequent analysis, modeling the process for a given number of time units. This functionality is included in the developed program and can be used both in console mode and in a web browser.
Modeling of biological microreliefs using the method of photogrammetry (on the example of cycloidal scales)
M.L. Tyagun, T.A. Khodzher
Accepted: 2022-06-10
Abstract
To reconstruct a biological relief object, we used a modeling method using a digital photogrammetric system that analyzes data from stereo pair images obtained by scanning electron microscopy. The method allows to analyze the principle of organization of both complex and simple microobjects, the construction of which requires clarity or refinement.
Using this method, the authors can describe the principle of organization of the cover relief layer of cycloid scales, characteristic of most Teleostei (evolutionarily late fish). Obtaining such three-dimensional images is relevant for understanding the construction of evolutionarily different types of fish exoskeleton. Also, the method will greatly facilitate the interpretation of the features of microrelief formed cyclically, which is necessary to accurately determine the age of modern fish species.
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