• 유체기계공업학회:학술대회논문집
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• 2006.08a
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• pp.145-146
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• 2006

Recently, the next-generation advanced flow visualization techniques such as holographic PIV, dynamic PIV, echo-PIV, micro/nano-PIV, and X-ray PIV have been introduced. These advanced measurement techniques have a big potential as the core technology for analyzing outmost thermo-fluid flows in future. These would be indispensable in solving complicated thermo-fluid flow problems not only in the industrial fields such as automotive, space, electronics, aero- and hydro-dynamics, steel, and information engineering, but also in the research fields of medical science, bio-medical engineering, environmental and energy engineering etc. Especially, NT (Nano Technology) and BT (Bio Technology) strongly demand these advanced measurement techniques, because it is impossible for conventional measurement methods to observe most complicated nano- and bio-fluidic phenomena. In this presentation, the basic principle of these high-tech flow visualization techniques and their practical applications which cannot be resolved by conventional methods, such as blood flows in a micro-tube, in vivo analysis of micro-circulation, and flow around a living body will be introduced as a blue ocean strategy.

• 한국전산유체공학회:학술대회논문집
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• 2008.03a
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• pp.14-17
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• 2008

Recently, several advanced flow visualization techniques such as Particle Image Velocimetry (PIV) including stereo PIV, holographic PIV, and dynamic PIV have been developed. These advanced techniques have strong potential as the experimental technology which can be used for verifying numerical simulation. In addition, there would be indispensable in solving complicated thermo-fluid flow problems not only in the industrial fields such as automotive, space, electronics, aero- and hydro-dynamics, steel, and information engineering, but also in the basic research fields of medical science, bio-medical engineering, environmental and energy engineering etc. Especially, NT Nano Technology) and BT (Bio Technology) strongly demand these advanced measurement techniques, because it is difficult for conventional methods to observe most complicated nano- and bio-fluidic phenomena. In this paper, the basic principle of these advanced visualization techniques and their practical applications which cannot be resolved by conventional methods, such as flow in automotive HVAC system, ship and propeller wake, three-dimensional flow measurement in micro-conduits, and flow around a circulating cylinder will be introduced.

• 한국전산유체공학회:학술대회논문집
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• 2008.10a
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• pp.14-17
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• 2008

Recently, several advanced flow visualization techniques such as Particle Image Velocimetry (PIV) including stereo PIV, holographic PIV, and dynamic PIV have been developed. These advanced techniques have strong potential as the experimental technology which can be used for verifying numerical simulation. In addition, there would be indispensable in solving complicated thermo-fluid flow problems not only in the industrial fields such as automotive, space, electronics, aero- and hydro-dynamics, steel, and information engineering, but also in the basic research fields of medical science, bio-medical engineering, environmental and energy engineering etc. Especially, NT (Nano Technology) and BT (Bio Technology) strongly demand these advanced measurement techniques, because it is difficult for conventional methods to observe most complicated nano- and bio-fluidic phenomena. In this paper, the basic principle of these advanced visualization techniques and their practical applications which cannot be resolved by conventional methods, such as flow in automotive HVAC system, ship and propeller wake, three-dimensional flow measurement in micro-conduits, and flow around a circulating cylinder will be introduced.

• Journal of Information Science Theory and Practice
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• v.7 no.2
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• pp.32-39
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• 2019

A convolutional neural network (CNN) has been widely used in facial expression recognition (FER) because it can automatically learn discriminative appearance features from an expression image. To make full use of its discriminating capability, this paper suggests a simple but effective method for CNN based FER. Specifically, instead of an original expression image that contains facial appearance only, the expression image with facial geometry visualization is used as input to CNN. In this way, geometric and appearance features could be simultaneously learned, making CNN more discriminative for FER. A simple CNN extension is also presented in this paper, aiming to utilize geometric expression change derived from an expression image sequence. Experimental results on two public datasets (CK+ and MMI) show that CNN using facial geometry visualization clearly outperforms the conventional CNN using facial appearance only.

• Journal of the Korean Society of Visualization
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• v.18 no.3
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• pp.3-13
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• 2020

• Journal of the Korean Society of Visualization
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• v.20 no.3
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• pp.1-9
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• 2022

• Journal of the Korean Society of Visualization
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• v.21 no.2
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• pp.1-7
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• 2023

• The Journal of the Convergence on Culture Technology
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• v.10 no.2
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• pp.357-363
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• 2024

As AR display virtual technology enters public learning life extensively, the way in which reality and virtual connection are connected is also changing. The purpose of this paper is to study the expression between the 3D connection sensory information visualization experience and virtual reality enhancement through the visual direction sensory information visualization experience of the plane. It is analyzed by examining the basic setting method compared to the current application of AR display and flat visualization cases. The scope of this paper is to enable users to have a better experience through the relationship with sensory visualization, centering on eye tracking technology in the four categories of AR display connection design: gesture connection, eye tracking, voice connection, and sensor. Focusing on eye tracking technology through AR display interaction and current application and comparative analysis of flat visualization cases, the geometric consistency of visual figures, light and color consistency, combination of multi-sensory interaction methods, rational content display, and smart push presented sensory visualization in virtual reality more realistically and conveniently, providing a simple and convenient sensory visualization experience to the audience.

• Journal of Information Management
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• v.42 no.2
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• pp.85-102
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• 2011

Conventionally, scientific data visualization is thought of as one of activities performed by scientists during the scientific data analysis. However, recently, there exits a set of research papers which count scientific data visualization as a independent research area. They show the research subjects for studying the scientific data visualization technology and methods. In case, a scientist or group of scientists can not solve their own visualization problem due to the unskillfulness and inexperience on using visualization tool. Therefore, it needs to help them by the systematic way for solving the problem. In this study, we analyze and propose the national level scientific visualization support system for scientists. In particular, we first analyze the existing papers and find out the critical success factors. Then, by integrating the findings of the analysis, we propose the research areas which need to be focused, and the strategic direction and specific research topics for scientific data visualization support system in national level.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.11
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• pp.1696-1707
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• 2021

With the recent growth of information technology, various literacy such as digital literacy, data literacy, AI literacy is being studied. In this paper, we focus on data visualization literacy as visualization is an essential part of big data analysis and is used in several mobile apps. Visualization Literacy Assessment Test(VLAT) was developed in 2016 and we introduce how the test was developed and modified to a Korean version, K-VLAT. K-VLAT is consisted of 12 visualizations and 53 questions through a website. Additionally, to understand the research trend in visualization literacy we analyzed 81 papers that had cited the VLAT publication. We categorized the research into 4 categories with 11 sub-categories. The area of studies visualization literacy related to was understanding the relation with cognition, expanding the literacy measures, relation with education, utilization for developing user-centric dashboards or using the test to show effectiveness of visualizations. At last, we discuss about different ways to utilize K-VLAT for future research.