• Communications for Statistical Applications and Methods
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• v.28 no.4
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• pp.369-391
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• 2021

The vlda is an R (R Development Core team et al., 2011) package which provides functions for visualization of multidimensional longitudinal data. In particular, the R package vlda was developed to assist in producing a plot that more effectively expresses changes over time for two different types (long format and wide format) and uses a consistent calling scheme for longitudinal data. The main features of this package allow us to identify the relationship between categories and objects using an indicator matrix with object information, as well as to cluster objects. The R package vlda can be used to understand trends in observations over time in addition to identifying relative relationships at a simple visualization level. It also offers a new interactive implementation to perform additional interpretation, therefore it is useful for longitudinal data visual analysis. Due to the synergistic relationship between the existing VLDA plot and interactive features, the user is empowered by a refined observe the visual aspects of the VLDA plot layout. Furthermore, it allows the projection of supplementary information (supplementary objects and variables) that often occurs in longitudinal data of graphs. In this study, practical examples are provided to highlight the implemented methods of real applications.

• Journal of the Korea Society of Computer and Information
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• v.27 no.4
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• pp.37-43
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• 2022

In this paper, we calculate the word frequency by date and region using news data related to COVID-19 distributed for about 8 months from December 2019 to July 2020, and visualized the correlation with the current state data of COVID-19 patients using the results. News data was collected from Big Kids, a news big data system operated by the Korea Press Promotion Foundation. The visualization system proposed in this paper shows the news frequency of the selected region compared to the overall region, the key keyword of the selected region, the region of the main keyword, and the date change of the selected region. Through this visualization, the main keywords and trends of COVID-19 confirmed and infected people can be identified for previous events.

• Journal of the Korea Computer Graphics Society
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• v.21 no.3
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• pp.36-45
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• 2015

It is important subject of research in engineering and natural science field that creating continuing high-definition image from very large volume data. The necessity of software that helps analyze useful information in data has improved by effectively showing visual image information of high resolution data with visualization technique. In this paper, we designed multi-platform visualization system based on client-server to analyze and express earth environment data effectively constructed with observation and prediction. The visualization server comprised of cluster transfers data to clients through parallel/distributed computing, and the client is developed to be operated in various platform and visualize data. In addition, we aim user-friendly program through multi-touch, sensor and have made realistic simulation image with image-based lighting technique.

• Proceedings of the Korea Society of Design Studies Conference
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• 2002.05b
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• pp.154-155
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• 2002

• Bulletin of the Korean Chemical Society
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• v.25 no.7
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• pp.1061-1064
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• 2004

Molecular visualization software has the common objective of manipulation and interpretation of data from numerical simulations. They visualize many complicated molecular structures with personal computer and workstation, to help analyze a large quantity of data produced by various computational methods. However, users are often discouraged from using these tools for visualization and analysis due to the difficult and complicated user interface. In this regard, we have developed an easy-to-use three-dimensional molecular visualization and analysis program named POSMOL. This has been developed on the Microsoft Windows platform for the easy and convenient user environment, as a compact program which reads outputs from various computational chemistry software without editing or changing data. The program animates vibration modes which are needed for locating minima and transition states in computational chemistry, draws two and three dimensional (2D and 3D) views of molecular orbitals (including their atomic orbital components and these partial sums) together with molecular systems, measures various geometrical parameters, and edits molecules and molecular structures.

• Journal of Information Technology Applications and Management
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• v.19 no.1
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• pp.13-24
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• 2012

Usability and knowledge drawn from utilizing various ways of representing accounting data were examined. Classroom experiments were conducted to compare students' assessment of financial data using table of numbers, 2-dimensional column graphs (2D), 3-dimensional column graphs (3D), and mixed reality visualization of true 3-dimensional graphs (MR). The results showed that in assessing the financial status and performance of a firm, Table of numbers and MR took longer than 2D and 3D graphs. The time spent on true 3D graphs using MR technology was about the same as Table of numbers. When compared the assessment scores of the firm's financial status and performance between participants and experts, the difference was the least when participants used 2D graphs. However, MR was seen as being a new way to provide data of greater complexity and was very useful for financial information.

• Communications for Statistical Applications and Methods
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• v.8 no.3
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• pp.643-650
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• 2001

Some classical plots like scatterplot matrices and parallel coordinates are valuable tools for data visualization. These tools are extensively used in the modern data mining softwares to explore the inherent data structure, and hence to visually classify or cluster the database into appropriate groups. However, the interpretation of these plots are very sensitive to the arrangement of variables. In this work, we introduce two methods to arrange the variables for data visualization. First method is based on the work of Wegman (1999), and this is to arrange the variables using minimum distance among all the pairwise permutation of the variables. Second method is using the idea of principal components. We Investigate the effectiveness of these methods with parallel coordinates using real data sets, and show that each of the two proposed methods has its own strength from different aspects respectively.

• International Journal of Air-Conditioning and Refrigeration
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• v.15 no.4
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• pp.156-162
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• 2007

Flow visualization experiments were conducted for two louver arrays having large louver pitch ratio ($L_p/F_p=1.0$ and 1.4). Flow efficiencies and critical Reynolds numbers were obtained from the data, and were compared with existing correlations. The correlations failed to predict the present flow efficiency data adequately; some correlation overpredicted the data, while others underpredicted the data. Large louver pitch ratio of the present model, which is outside of the applicable range of the correlations may partly be responsible. The critical Reynolds numbers obtained from the present flow visualization data were in close agreement with those obtained from the heat transfer tests on actual flat tube heat exchangers. Existing correlations on the critical Reynolds number generally overpredicted the present data.

• Journal of Korean Elementary Science Education
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• v.43 no.1
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• pp.18-34
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• 2024

This study aimed to examine the effects of a science-learning program based on data visualization on the science inquiry and creative problem-solving abilities of elementary school science-gifted students. Accordingly, this research developed a data visualization science-learning program using Tableau, which had twelve sessions. The subjects encompassed 61 students in three gifted classes taught by the researcher. The scientific inquiry ability test and creative problem-solving ability test modified to suit the environment and situation were given to the subjects before and after the treatment. The results confirmed that science learning based on data visualization had no significant impact on basic science inquiry skills. Among the subdomains, significant results were obtained only in the reasoning subdomain. Moreover, integrative inquiry ability was significantly affected, unlike basic inquiry abilities. Among the five subdomains, significant differences were observed in three subdomains (data conversion, data interpretation, and variable control). However, concerning the generation of hypotheses and the control of variables, students exhibited confusion regarding the process of variable control and the exact concept of hypothesis development. This study also evaluated the effects of the program's application on creative problem-solving abilities and found a significant impact. Additionally, it was significantly different in all four subdomains. The results were interpreted to be owing to the students' mastery of Tableau's features, collaborative learning through discussion and debate, and the thematic impact of the data visualization program emphasizing procedural thinking. Finally, this study presented implications for science learning based on data visualization and the future direction of education.

• The Mathematical Education
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• v.41 no.1
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• pp.45-58
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• 2002

This study was conducted to investigate the gender-related effects of two instructional programs on spatial visualization skills of ninth grade students. Two instructional programs were developed for this study: a web-based virtual reality program and a paper-based program. 194 ninth graders from two middle schools in Seoul participated in this study. Six classes were divided into experimental groups and control groups. The Middle Grades Mathematics Projects (MGMP) Spatial Visualization Test was used to measure spatial visualization skills. The data analysis indicated that both the web-based and paper-based programs were effective to improve spatial visualization skills to treatment groups. Although boys'test mean scores were higher than girls' in the pretest, when deleting the effect of covariance of pretest, there were no statistical significance in the post-test. Girls in the treatment groups favored the paper-based spatial visualization program. These results imply that spatial training may benefit girls' performance more than that of boys and mode of instructional programs can create gender-related differences regarding spatial visualization skills.