• Journal of the Korea Computer Industry Society
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• v.3 no.1
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• pp.1-8
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• 2002

This study is discussed research on management of items in PC's GUI(Graphical User Interface) environment. A items are general knowledge data like books, musical CD, English CD, and game CD, which are the time when we don't seek the right items in the case of re-reading and re-listening the items. In this paper, We propose an example designed to be used in the management of a items. The proposed example is implemented by educational VC＋＋(Visual C＋＋) programming language. This program and discussions for management of a items will understand the development procedure of searching and storing data, which will provide some basics into designing large database systems.

• Genomics & Informatics
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• v.20 no.3
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• pp.36.1-36.6
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• 2022

BLAST, a basic bioinformatics tool for searching local sequence similarity, has been one of the most widely used bioinformatics programs since its introduction in 1990. Users generally use the web-based NCBI-BLAST program for BLAST analysis. However, users with large sequence data are often faced with a problem of upload size limitation while using the web-based BLAST program. This proves inconvenient as scientists often want to run BLAST on their own data, such as transcriptome or whole genome sequences. To overcome this issue, we developed NBLAST, a graphical user interface-based BLAST program that employs a two-way system, allowing the use of input sequences either as "query" or "target" in the BLAST analysis. NBLAST is also equipped with a dot plot viewer, thus allowing researchers to create custom database for BLAST and run a dot plot similarity analysis within a single program. It is available to access to the NBLAST with http://nbitglobal.com/nblast.

• Journal of the Institute of Convergence Signal Processing
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• v.22 no.4
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• pp.185-192
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• 2021

Various methods have been proposed to determine the defect detection of welding bead, and recently sensor data and image data inspection have been steadily announced. There are advantages that sensor data inspection is highly accurate, and two-dimensional-based image data inspection is able to determine the position of the welding bead. However, when analyzing only with sensor data, it is difficult to determine whether the welding has been performed at the correct position. On the other hand, the image data inspection does not have high accuracy due to noise and measurement errors. In this paper, we propose a method that can complement the shortcomings of each inspection method and increase its advantages to improve accuracy and speed up inspection by fusing sensor data inspection which are average current, average volt, and mixed gas data, and image data inspection methods and is implemented as software. In addition, it is intended to allow users to conveniently and intuitively analyze and grasp the results by performing analysis using a graphical user interface(GUI) and checking the data and inspection results used for the inspection. Sensor inspection is performed using the characteristics of each sensor data, and image data is inspected by applying a morphology geodesic active contour algorithm. The experimental results showed 98% accuracy, and when performing the inspection on the four image data, and sensor data the inspection time was about 1.9 seconds, indicating the performance of software that can be used as a real-time inspector in the welding process.

• Communications for Statistical Applications and Methods
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• v.15 no.1
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• pp.65-76
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• 2008

Biplots are the multivariate analogue of scatter plots. They approximate the multivariate distribution of a sample in a few dimensions, typically two, and they superimpose on this display representations of the variables on which the samples are measured(Gower and Hand, 1996, Chapter 1). And the relationships between the observations and variables can be easily seen. Thus, biplots are useful for giving a graphical description of the data. However, this method does not give some concise interpretations between variables and observations when the number of observations are large. Therefore, in this study, we will suggest to interpret the biplot analysis by applying the K-means clustering analysis. It shows that the relationships between the clusters and variables can be easily interpreted. So, this method is more useful for giving a graphical description of the data than using raw data.

• The Korean Journal of Applied Statistics
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• v.31 no.1
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• pp.155-165
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• 2018

Outliers and influential observations often distort many numerical measures for data analysis. Jang and Anderson-Cook (Quality and Reliability Engineering International, 30, 1409-1425, 2014) proposed a graphical firework plot method for exploratory analysis purpose to provide a possible visualization of the trace of the impact of the possible outlying and influential observations on the univariate/bivariate data analysis and regression. They developed 3-D plot as well as pairwise plot for the appropriate measures of interest. We use firework plots as a graphical exploratory data analysis tool to detect outliers and evaluate the impact of outliers in statistical inference.

• The Korean Journal of Applied Statistics
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• v.27 no.2
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• pp.227-237
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• 2014

We use the regression model with the indicator variables in the case that we use qualitative variables as some predictor variables in regression analysis. We use the ANCOVA(Analysis of Covariance) model when comparing the response variable among groups while statistically controlling for variation in the response variable caused by a variation in the covariate. DD-plot can be used as a graphical exploratory data analysis tool before the confirmatory data analysis. With the DD-plot, we can discriminate the difference of groups in the regression model with the indicator variables or the ANCOVA model at a glance. Making DD-plot does not demand the statistical model assumption about error terms in regression model. Several examples show the usefulness of DD-plots as a graphical exploratory data analysis tool for the regression analysis.

• Genomics & Informatics
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• v.5 no.3
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• pp.129-132
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• 2007

arraylmpute is a software for exploratory analysis of missing data and imputation of missing values in microarray data. It also provides a comparative analysis of the imputed values obtained from various imputation methods. Thus, it allows the users to choose an appropriate imputation method for microarray data. It is built on R and provides a user-friendly graphical interface. Therefore, the users can easily use arraylmpute to explore, estimate missing data, and compare imputation methods for further analysis.

• Journal of Korea Multimedia Society
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• v.15 no.9
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• pp.1174-1183
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• 2012

This study, depending on the diversification of the information environment, was carried out to analyze the role of visual cues and the relationship between visual information structure in the process of user's visual immersion and recognition. Thus, we design evaluation model which used scientific instruments and subjective evaluation taking into account the latest graphical user trends, and analyze the data of immersion and recognition of the user experience that acquired through the process more systematic experimental procedure. Based on this, in the future, this study will be able to contribute implement the latest broadly applicable to the device of graphical information user basic design model and a standard evaluation model.

• Journal of the Korean Data and Information Science Society
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• v.14 no.2
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• pp.237-245
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• 2003

MDS(multi-dimensional scaling) for preference data is a graphical tool which usually figures out how consumers recognize, evaluate certain products. This article is mainly concerned with an optimal scaling for MDS when target configuration is available. Rotation of axis and SUR(seemingly unrelated regression) methods are employed to get a new configuration which is obtained as close to the target as we can. Methodologies developed here are also illustrated via a real data set.

• The Korean Journal of Applied Statistics
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• v.12 no.1
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• pp.81-81
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• 1999

A categorical data analysis system in the World Wide Web is proposed with an easy- to-use environment . This system is composed of four components. First, this system presents several graphical displays for Exploratory Data Analysis for categorical data. Second, it provides some measures of association Including dynamic graphics for mosaic plots of Hartigan and Kleiner (1981) and Friendly (1994). Dynamic graphics for mosaic plots give some useful informations. Third, this system can analyze categorical data with loglinear models. So we can select the best fitted loglinear model interactively.