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How to Improve Utilizing Neural Interface by Means of Ontology-Driven Scientific Visualization Tools 如何利用本体驱动的科学可视化工具改进神经接口
Q4 Computer Science Pub Date : 2022-01-01 DOI: 10.26583/sv.14.4.08
S. Chuprina, I. Labutin
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引用次数: 0
Graph Visualization of the Terminological Thesaurus by F.M. Dostoevsky's Gospel Text (using the Example of Bigram Models) 陀思妥耶夫斯基福音书中术语词库的图形可视化(以Bigram模型为例)
Q4 Computer Science Pub Date : 2022-01-01 DOI: 10.26583/sv.14.5.03
V. Borisova
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引用次数: 1
The Role of Subjective Perception in Visualization, Controllability Hypothesis and Abstract Visualization 主观知觉在可视化中的作用、可控性假设与抽象可视化
Q4 Computer Science Pub Date : 2022-01-01 DOI: 10.26583/sv.14.3.09
A. Zakharova, A. Shklyar, E. Vekhter
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.
可视化分析工具用于解释和分析弱形式化或非形式化的数据。本文考虑了主观因素对可视化工具效率的影响问题。基于先前提出和发展的符号学可视化模型,制定了一个对可视化工具的有效性有重大影响的启动因素系统。提出了可控性假设,并在此基础上对可视化系统的局限性进行了假设,提出在设计新的可视化分析工具时应考虑这些局限性。对工作中提出的断言的认可是在社会数据的例子上进行的。
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引用次数: 0
On Expressiveness of Visualization Systems' Interfaces 论可视化系统界面的表达性
Q4 Computer Science Pub Date : 2022-01-01 DOI: 10.26583/sv.14.5.06
P. Vasev, M. Bakhterev, D. Manakov, S. Porshnev, M. Forghani
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引用次数: 1
Overview of BSDF Reconstruction Methods for Rough Surfaces 粗糙表面的BSDF重构方法综述
Q4 Computer Science Pub Date : 2022-01-01 DOI: 10.26583/sv.14.3.10
V. Sokolov, A. Voloboy, I. Potemin, V. Galaktionov
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 exam-ple, 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 ques-tions 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.
本文综述了粗糙表面双向散射分布函数(BSDF)的重建方法。具有粗糙表面的元素永久存在于我们的生活中,并广泛应用于现代光学设备中,例如,用于显示照明系统的导光板,汽车仪表板或灯具。粗糙表面的光散射是水、玻璃、皮肤等许多材料视觉外观的重要组成部分。粗糙表面的可视化是一个复杂的问题,包含了许多不同的方面。因此,有许多技术来提供他们的现实渲染。在许多照明模拟和光学设计任务中,用BSDF表示的表面光学特性代替粗糙表面的真实几何形状是充分和有效的。因此,准确地重建粗糙表面的散射特性是可视化任务和生成逼真图像的重要因素。在某些情况下,BSDF可以被测量。然而,在许多情况下,直接测量BSDF是不可能的,例如,如果需要在材料内部定义BSDF,并且测量设备探测器和光源都不能放置在材料内部。这就导致了BSDF重建方法的发展。它开始于上世纪末,随着许多基于粗糙表面微面模型的分析方法的发展,如Phong, Ward反射,Cook-Torrance模型。目前出现了许多直接的BSDF数值重建方法,如基于正态分布和高度分布的方法。通常,这些方法使用光线追踪来计算BSDF。微粗糙度的尺寸可以很小,足以引起光波或射线在这里更合适的问题。为了回答这个问题以及其他与BSDF重建相关的问题,我们对已知的有效重建方法进行了调查。本文还介绍了8个实际粗糙表面不同轮廓参数样品的研究结果。通过与实测数据的数值对比和不同重构BSDF生成图像的视觉对比,验证了算法的正确性。最后,提出了关于哪些方法和哪些应用更合适的一般建议。
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引用次数: 1
About Development and Application of a Software Platform for Machine Vision for Various Laser Technologies 基于各种激光技术的机器视觉软件平台的开发与应用
Q4 Computer Science Pub Date : 2022-01-01 DOI: 10.26583/sv.14.5.08
A. Molotkov, O. Tretiyakova, D. Tuzhilin
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引用次数: 0
Numerical Calculation and Visualization of Pseudosymmetry Attributes of Biological Objects 生物物体伪对称属性的数值计算与可视化
Q4 Computer Science Pub Date : 2022-01-01 DOI: 10.26583/sv.14.2.04
E. Popov, T. Popova, A. Nizhegorodtsev, D. Vershinina
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引用次数: 0
Software Package for Visualization and Modeling Based on BPMN Notation 基于BPMN符号的可视化建模软件包
Q4 Computer Science Pub Date : 2022-01-01 DOI: 10.26583/sv.14.3.02
N. D. Badanina, V. Sudakov, N.A. Yаshin
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引用次数: 0
Cognitive Clarity of Graph Models: an Approach to Understanding the Idea and a Way to Identify Influencing Factors Based on Visual Analysis 图模型的认知清晰度:一种理解思想的方法和基于视觉分析的影响因素识别方法
Q4 Computer Science Pub Date : 2022-01-01 DOI: 10.26583/sv.14.4.04
R. Isaev, A. Podvesovskii
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引用次数: 0
Visualization Problems of a Supersonic Tip Vortex in a Heat Wake 热尾迹中超音速尖端涡的可视化问题
Q4 Computer Science Pub Date : 2022-01-01 DOI: 10.26583/sv.14.4.07
T. Konstantinovskaya, V. Borisov, A. Lutsky
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引用次数: 1
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