Data abstraction models: sampling (parallel coordinates), filtering, clustering

Manakov, Dmitry

doi:10.26583/sv.11.1.11

Cited by 6 publications

(4 citation statements)

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“…There are several methods for finding and choosing the optimal solution in the synthesis of a complex system, including methods of multicriteria optimization with the introduction of weight criteria [5,7] or taking into account preferences. This work is devoted to the stage of data preparation for the use of these methods, for which the results of computer simulation, presented in a visual for viewing, are interactively compared [10,11].…”

Section: Interactive Visual Analysis Of Simulation Resultsmentioning

confidence: 99%

Visualization of the interconnection between dynamics of the system and its basic characteristics

Kreinin¹,

Misyurin²,

Nelyubin³

et al. 2020

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The paper presents a dimensionless mathematical model of the dynamics of the drive complex and the visualization of the solution of this model, which allows to obtain comparative estimates (characteristics) of the solutions obtained in the first approximation.The authors proposed an original control system for the drive complex of two hydraulic actuators to lift the load in parallel mode. A distinctive feature is the adopted control circuit of the complex through three hydraulic switchgears, which are responsible for regulating the overall object lifting (and/or lowering) speed and maintaining the horizontal position of the object within the specified accuracy in the presence of disturbing factors of different nature. The difference in displacements of the hydraulic actuator rods from some initial (basic) position at a given time is a sign of deviation of the object from the horizontal position. The mathematical model of the object obtained is investigated in dimensionless variables, which greatly simplifies the visual synthesis of the object.

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Section: Interactive Visual Analysis Of Simulation Resultsmentioning

confidence: 99%

Visualization of the interconnection between dynamics of the system and its basic characteristics

Kreinin¹,

Misyurin²,

Nelyubin³

et al. 2020

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“…The authors propose to consider a structural or semantic unit of visual analysis, also called a unit, as a continuous map of a class of data subsets onto a logical space. Since the mapping of data to a visual representation is not an isomorphism, it is necessary to take into account the mathematical level of data abstraction [28].…”

Section: Systems Analysis Of Visualization Systemsmentioning

confidence: 99%

On Expressiveness of Visualization Systems' Interfaces

Vasev¹,

Bakhterev²,

Manakov³

et al. 2022

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The paper discusses elements of logical models of graphical user interfaces used in both universal and specialized scientific visualization systems. Criteria of expressiveness of programming language that are discussed in "Structure and Interpretation of Computer Programs" book are applied to graphical interfaces. It is shown that graphical interfaces allow users to operate on the same digital substance and with the same logical approaches as in textual programming languages. Both give basic elements, allow their combination, and support the procedures of abstraction. Authors suggest considering these aspects when developing graphical interfaces. This perspective is applied to the following presentation of the paper. The idea of modifiers (also known as behaviors or effects) and the idea of extensions (also known as plugins, modules, and applications) are discussed. Some methods of programming of scene dynamics are presented. Also languages and ontologies of scientific visualization are discussed, e.g. models for editing visualization pipeline: adding data to projects, filtering of that data, and methods of description of data representation on screen. Finally, we discuss additional ideas on systems analysis of visualization systems.

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“…These are a special case of abstract data types, the function range of which is a dynamic visual image. Abstracting parameters are considered as the subset implementation of data abstraction models (generalizations that allow abstracting from the source and ontology of data during visual analysis) [22].…”

Section: Theoretical Foundationmentioning

confidence: 99%