• Journal of the Korean Society of Earth Science Education
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• v.17 no.2
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• pp.123-136
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• 2024

This study examines the performance expectations (PEs) and clarification statements of each PE in the 2022 revised national science and mathematics education standards from a data visualization competency perspective. First, the authors intensively reviewed data visualization literature to define key competencies and developed a framework comprising four main categories: collection and pre-processing skills, technical skills, thinking skills, and interaction skills. Based on the framework, the authors extracted a total of 191 mathematics and 230 science PEs from the 2022 revised science and mathematics education standards (Ministry of Education Ordinance No. 2022-33, Volumes 8 and 9) as the main data set. The analysis process consisted of three steps: first, the authors organized the data (421 PEs) by the four categories of the framework and four grade levels (3-4th, 5-6th, 7-9th, and 10th grade); second, the numbers of PEs in each grade level were standardized by the accomplishing period (1-3 years) of each PE depending on the grade level; lastly, the data set was represented by heatmaps to visualize the relationship between the four categories of visualization competency and four grade levels, and the differences between the competency categories and grade levels were quantitatively analyzed using the Mann-Whitney U test and independent sample Kruskal-Wallis tests. The analysis results revealed that in mathematics, there was no significant difference between the number of PEs by grade. However, on average, the number of PEs categorized in 'thinking skills' was significantly lower than those in the technical skills (p = .002) and interaction skills categories (p = .001). In science, it was observed that as grade level increased, PEs also increased (pairwise comparison: Grades 5-6 vs. 7-9, p = .001; Grades 5-6 vs. Grade 10, p = .029; Grades 3-4 vs. 7-9, p = .022). Particularly, the frequency of PEs in 'thinking skills' was significantly lower than in the other skills (pairwise comparison: technical skills p = .024; collection and pre-processing skills p = .012; interaction skills p = .010). Based on the results, two implications for revising national science and mathematics standards and teacher education were suggested.

• The KIPS Transactions:PartA
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• v.9A no.3
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• pp.387-398
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• 2002

As whole genome sequences of many organisms have been revealed by small-scale genome projects, the intensive research on individual genes and their functions has been performed. However on-memory algorithms are inefficient to analysis of whole genome sequences, since the size of individual whole genome is from several million base pairs to hundreds billion base pairs. In order to effectively manipulate the huge sequence data, it is necessary to use the indexed data structure for external memory. In this paper, we introduce a workbench system for analysis and visualization of whole genome sequence using string B-tree that is suitable for analysis of huge data. This system consists of two parts : analysis query part and visualization part. Query system supports various transactions such as sequence search, k-occurrence, and k-mer analysis. Visualization system helps biological scientist to easily understand whole structure and specificity by many kinds of visualization such as whole genome sequence, annotation, CGR (Chaos Game Representation), k-mer, and RWP (Random Walk Plot). One can find the relations among organisms, predict the genes in a genome, and research on the function of junk DNA using our workbench.

• Genomics & Informatics
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• v.15 no.4
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• pp.178-182
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• 2017

Next-generation sequencing (NGS) technology has become a trend in the genomics research area. There are many software programs and automated pipelines to analyze NGS data, which can ease the pain for traditional scientists who are not familiar with computer programming. However, downstream analyses, such as finding differentially expressed genes or visualizing linkage disequilibrium maps and genome-wide association study (GWAS) data, still remain a challenge. Here, we introduce a dockerized web application written in R using the Shiny platform to visualize pre-analyzed RNA sequencing and GWAS data. In addition, we have integrated a genome browser based on the JBrowse platform and an automated intermediate parsing process required for custom track construction, so that users can easily build and navigate their personal genome tracks with in-house datasets. This application will help scientists perform series of downstream analyses and obtain a more integrative understanding about various types of genomic data by interactively visualizing them with customizable options.

• Journal of Digital Contents Society
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• v.9 no.4
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• pp.707-715
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• 2008

The ocean ecosystem and the marine farms were damaged after latest oil spill in Taean. They suffered heavily due to the expansion of the red tide on the coast and the sudden changes in water temperature. We should develop the way to deal with various factors to reduce the damage. In this paper, real time data with which are supplied us through many kinds of sensors on measure equipments will be processed to the visualized shape. Simple numeric data and 2D graph will be changed 2D or 3D graphic objects and animations using WPF, a new effect method in user interface area. This visualization system for environmental data shows us various pictures and offers multimedia data communication.

• The Korean Journal of Applied Statistics
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• v.21 no.6
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• pp.911-921
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• 2008

Visualization of the gene expression data on a low-dimensional graph is helpful in uncovering biological information contained in the data. In this study, we focus on two modified versions of the parallel coordinate plot. First one is the ePCP(enhanced parallel coordinate plot) which shows "near smooth" connecting curves between axes spaced proportionately to the proximity of re-ordered variables. Second one is APCP(Andrews' type parallel coordinate plot) which is obtained by rotating Andrews' plot that has a form of the parallel coordinate plot. Visualization procdures using ePCP and APCP are given for the lymphoma data case.

• Journal of the Korea Society of Computer and Information
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• v.13 no.2
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• pp.105-111
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• 2008

Various visualizing methods have been proposed according to the input and output types. To show complex and large-scale raw data and information. LOD and special region scale method have been used for them. In this paper, I propose level scale interface for dynamic and interactive controlling large scale data such as bio-data. The method has not only advantage of LOD and special region scale but also dynamic and real-time processing. In addition, the method supports elaborate control from large scale to small one for visualization on a region in detail. Proposed method was adopted for genome relationship visualization tool and showed reasonable control method.

• Journal of Korea Society of Digital Industry and Information Management
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• v.14 no.4
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• pp.57-68
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• 2018

This paper presents a smart firefighting appliances monitoring system based on big data analytics platform using GS1 for Smart City. Typical firefighting appliances are fire hydrant, fire extinguisher, fire alarm, sprinkler, fire engine, etc. for the fire of classes A/B/C/D/E. Among them, the dry chemical fire extinguisher have been widely supplied and 6 millions ones were replaced for the aging ones over 10 years in the past year. However, only 5% of them have been collected for recycling of chemical materials included the heavy metals of environment pollution. Therefore, we considered the trace of firefighting appliances from production to disposal for the public open service. In the paper, we suggest 1) a smart firefighting appliances system using GS1, 2) a big data analytics platform and 3) a public open service and visualization with the analyzed information, for fire extinguishers from production to disposal. It can give the information and the visualized diagrams with the analyzed data through the public open service and the free Apps.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.6
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• pp.11-19
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• 2018

Recently, many companies offer various web-based map that is based on GIS(Geographic Information System) information. Google Map, Open street, Bing Map, Naver Map, Daum Map, Vwolrd Map, etc are the few examples of such system. In this paper, we propose a method to visualize ocean forecasting model data considering the flow diagram of tidal current, streamline expression algorithm, and user convenience by using vector field data information that is currently being served. It is confirmed that the proposed method of the flow diagram of tidal current, and stream line expression algorithm is faster than that of conventional ocean prediction model data by more than 2 times.

• Journal of Digital Convergence
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• v.19 no.4
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• pp.19-24
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• 2021

In this paper, an index of women's safety facilities was created and visualized using public data related to Seoul. CPTED, the women's safety facilities index was created by collecting and analyzing eight data related to the local women's safety index and five major crime victims of women. As a result of the correlation analysis between the factors of the female safety facility index and the number of female crime victims, three data were selected as the main factors, "CCTV," "street lamps," and "female security guardians", which were found to be meaningful at the 95% level of reliability. The distinction women's safety facility index was calculated by weighting the correlation coefficient between the main factors for calculating the women's safety facility index, and visualized using Python's Follium library.

• Journal of the Korean Society of Visualization
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• v.21 no.1
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• pp.18-25
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• 2023

In these days, high dimensional data prediction technology based on neural network shows compelling results in many different kind of field including engineering. Especially, a lot of variants of convolution neural network are widely utilized to develop pixel level prediction model for high dimensional data such as picture, or physical field value from the sensors. In this study, velocity vector field of ideal flow on ship surface is estimated on pixel level by Unet. First, potential flow analysis was conducted for the set of hull form data which are generated by hull form transformation method. Thereafter, four different neural network with a U-shape structure were conFig.d to train velocity vectors at the node position of pre-processed hull form data. As a result, for the test hull forms, it was confirmed that the network with short skip-connection gives the most accurate prediction results of streamlines and velocity magnitude. And the results also have a good agreement with potential flow analysis results. However, in some cases which don't have nothing in common with training data in terms of speed or shape, the network has relatively high error at the region of large curvature.