• KIPS Transactions on Software and Data Engineering
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• v.5 no.6
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• pp.261-266
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• 2016

Chart suggestion method provided by various existing data visualization tools makes chart recommendations without considering the user intention. Data visualization is not properly carried out and thus, unclear in some tools because they do not follow the segmented quantitative data classification policy. This paper provides a guideline that clearly classifies the quantitative input data and that effectively suggests charts based on user intention. The guideline is two-fold; the analysis guideline examines the quantitative data and the suggestion guideline recommends charts based on the input data type and the user intention. Following this guideline, we excluded charts in disagreement with the user intention and confirmed that the time user spends in the chart selection process has decreased.

• International Journal of Computer Science & Network Security
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• v.23 no.2
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• pp.133-139
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• 2023

As the old saying goes "a picture is worth a thousand words" data visualization is essential in almost every industry. Companies make Data-driven decisions and gain insights from visual data. However, there is a need to investigate the role of data visualization in human resource management. This review aims to highlight the power of data visualization in the field of human resources. In addition, visualize the latest trends in the research area of human resource and data visualization by conducting a quantitative method for analysis. The study adopted a literature review on recent publications from 2017 to 2022 to address research questions.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.32 no.2
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• pp.76-84
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• 2009

Since too much information has been generated, it became very difficult to find out valuable and necessary information. In order to deal with the problem of information overload, the taxonomy for information visualization techniques has been based upon visualized shapes such as tree map, fisheye view and parallel coordinates, so that it was difficult to choose the right representation technique by data characteristics. Therefore, this study was designed to introduce a new taxonomy for the information visualization by data characteristics which defined by space (3D vs. multi-dimensions), time (continuous vs. discrete), and relations of data (qualitative vs. quantitative). To verify the new taxonomy, forensic data which were generated to investigate the culprit of network security was used. The result showed that the new taxonomy was found to be very efficient and effective to choose the right visualized shape for forensic data for network security. In conclusion, the new taxonomy was proven to be very helpful to choose the right information visualization technique by data characteristics.

• The Korean Journal of Applied Statistics
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• v.31 no.2
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• pp.167-188
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• 2018

Minard's figurative map is an infographic on Napoleon's Russian Campaign of 1812. Tufte (The Visual Display of Quantitative Information, Graphics Press, 1983) declared that Napoleon's March "may well be the best statistical graphic ever produced." We can use this data map as storytelling material for data visualization education. In this paper, with Minard's figurative map, we study four themes (infographics, information design, Minard, and the Russian Campaign) in data visualization education.

• Korean Journal of Computational Design and Engineering
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• v.11 no.6
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• pp.455-463
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• 2006

Hidden line removal(HLR) algorithms can be devised either in the image space or in the object space. This paper describes a hidden line removal algorithm in the object space specifically for the CAD viewer data. The approach is based on the Appel's 'Quantitative Invisibility' algorithm and fundamental concept of 'back face culling'. Input data considered in this algorithm can be distinguished from those considered for HLR algorithm in general. The original QI algorithm can be applied for the polyhedron models. During preprocessing step of our proposed algorithm, the self intersecting surfaces in the view direction are divided along the silhouette curves so that the QI algorithm can be applied. By this way the algorithm can be used for any triangulated freeform surfaces. A major advantage of this algorithm is the applicability to general CAD models and surface-based visualization data.

• Journal of Advanced Marine Engineering and Technology
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• v.27 no.3
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• pp.395-404
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• 2003

Quantitative data of the temperature and velocity were obtained simultaneously by using liquid crystal tracer. PIV(Particle Image Velocimety) based on a grey-level cross-correlation method was used for visualizing and analysis of the flow field. The temperature gradient was obtained by applying the color-image processing to a visualized image, and a neural-network a1gorithm was applied to the color-to-temperature calibration. This simultaneous measurement was applied to the Rayleigh-Bernard convection. This paper describes the method, and presents the quantitative visualization of Rayleigh-Bernard convection and the effect of aspect ratio and viscosity. Also the experimental results were compared with the numerical results.

• Spatial Information Research
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• v.23 no.6
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• pp.109-116
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• 2015

In this study, define the concept of spatial big data and special feature of spatial big data, examine information visualization methodology for increase the insight into the data. Also presented problems and solutions in the visualization process. Spatial big data is defined as a result of quantitative expansion from spatial information and qualitative expansion from big data. Characteristics of spatial big data id defined as 6V (Volume, Variety, Velocity, Value, Veracity, Visualization), As the utilization and service aspects of spatial big data at issue, visualization of spatial big data has received attention for provide insight into the spatial big data to improve the data value. Methods of information visualization is organized in a variety of ways through Matthias, Ben, information design textbook, etc, but visualization of the spatial big data will go through the process of organizing data in the target because of the vast amounts of raw data, need to extract information from data for want delivered to user. The extracted information is used efficient visual representation of the characteristic, The large amounts of data representing visually can not provide accurate information to user, need to data reduction methods such as filtering, sampling, data binning, clustering.

• The Korean Journal of Applied Statistics
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• v.29 no.6
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• pp.1007-1023
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• 2016

This paper explores the conditions and potential of newly designed and tried methodology of big data analysis that apply to Korean history subject matter. In order to advance them, we need to pay more attention to quantitative analysis methodologies over pre-existing qualitative analysis. To obtain our new challenge, I propose 'digital history' methods along with associated disciplines such as linguistics and computer science, data science and statistics, and visualization techniques. As one example, I apply interdisciplinary convergence approaches to the principle and mechanism of elite reproduction during the Korean medieval age. I propose how to compensate for a lack of historical material by applying a semi-supervised learning method, how to create a database that utilizes text-mining techniques, how to analyze quantitative data with statistical methods, and how to indicate analytical outcomes with intuitive visualization.

• Journal of the Korean Society of Visualization
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• v.8 no.2
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• pp.40-44
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• 2010

Thermal comfort inside a passenger car has been receiving large attention in automobile industries. Especially, the performance of windshield defroster is important in the design of a car to ensure passenger comport and safety. Thereby, better understanding on the ventilation flow along the vehicle windshield is essential to evaluate the performance of windshield defroster. However, most previous studies dealt with the defrost flow using CFD (computational fluid dynamics) calculations or scale-down model experiments. In this study, a real commercial automobile was used to investigate the flow discharged from the vehicle defroster and the ventilation flow along the windshield using a PIV velocity field measurement technique. The experimental data would be useful to understand the flow characteristics in detail and also can be used to validate numerical predictions.

• Journal of Power System Engineering
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• v.20 no.6
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• pp.51-57
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• 2016

Experiment is carried out to investigate the mixed convective flow in three-dimensional horizontal rectangular channels filled with high viscous fluid. The particle image velocimetry(PIV) with thermo-sensitive liquid crystal tracers is used for visualizing and analysis. Quantitative data of temperature and velocity are obtained by applying the color-image processing to a visualized image, and neural network is applied to the color-to-temperature calibration. In this study, the fluid used is silicon oil(Pr=909), the aspect ratio(channel width to heigh) is 4 and Reynolds number is $2{\times}10^{-2}$. From the present study, we can visualize the quantitative temperature and velocity of mixed convective flow in three-dimensional horizontal rectangular channels simultaneously.