• KSBB Journal
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• v.16 no.6
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• pp.538-546
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• 2001

An integrated data analysis program for DNA chip containing normalization, FDM analysis, various kinds of clustering methods, PCA, and SVD was applied to analyze combined yeast cell cycle data. This paper includes both comparisons of some clustering algorithms such as K-means, SOM and furry c-means and their results. For further analysis, clustering results from the integrated analysis program was used for function assignments to each cluster and for motif analysis. These results show an integrated analysis view on DNA chip data.

• Journal of the Korean Solar Energy Society
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• v.33 no.4
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• pp.101-110
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• 2013

The propose of this study is to understand the phenomenon of radiation and comparison of analysis of two methods. One is analysis method of same-time data and the another is analysis method of rank data. We confirmed that two methods of correlation analysis had the effectiveness and suitability. The followings are main results from this study. 1) The seasonal correlation coefficient of long and short-wave radiation is higher in winter than in summer because of high humidity in the summer season can makes easily cloud in the sky locally. 2) According to analysis method, there is big difference in correlation coefficient from 0.494(Analysis method of same-time data) to 0.967(Analysis method of rank data) with short-wave radiation by the location during summer. These results have significant value in solar radiation research and analysis. It has explored a new way for solar radiation research of analysis method as well.

• Genomics & Informatics
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• v.4 no.1
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• pp.40-44
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• 2006

Toxicogenomics combines transcriptome, proteome and metabolome profiling with conventional toxicology to investigate the interaction between biological molecules and toxicant or environmental stress in disease caution. Toxicogenomics faces the problems of comparison and integration across different sources of data. Cause of unusual characteristics of toxicogenomic data, researcher should be assisted by data analysis and annotation for getting meaningful information. There are already existing repositories which claim to stand for toxicogenomics database. However, those just contain limited abilities for toxicogenomic research. For supporting toxicologist who comes up against toxicogenomic data flood, now we propose novel toxicogenomics knowledgebase system, XPERANTO-TOX. XPERANTO-TOX is an integrated system for toxicogenomic data management and analysis. It is composed of three distinct but closely connected parts. Firstly, Data Storage System is for reposit many kinds of '-omics' data and conventional toxicology data. Secondly, Data Analysis System consists of analytical modules for integrated toxicogenomics data. At last, Data Annotation System is for giving extensive insight of data to researcher.

• International Journal of Computer Science & Network Security
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• v.23 no.10
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• pp.81-88
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• 2023

In the present scenario, enormous amounts of data are produced every second. These data also contain private information from sources including media platforms, the banking sector, finance, healthcare, and criminal histories. Data mining is a method for looking through and analyzing massive volumes of data to find usable information. Preserving personal data during data mining has become difficult, thus privacy-preserving data mining (PPDM) is used to do so. Data perturbation is one of the several tactics used by the PPDM data privacy protection mechanism. In Perturbation, datasets are perturbed in order to preserve personal information. Both data accuracy and data privacy are addressed by it. This paper will explore and compare several perturbation strategies that may be used to protect data privacy. For this experiment, two perturbation techniques based on random projection and principal component analysis were used. These techniques include Improved Random Projection Perturbation (IRPP) and Enhanced Principal Component Analysis based Technique (EPCAT). The Naive Bayes classification algorithm is used for data mining approaches. These methods are employed to assess the precision, run time, and accuracy of the experimental results. The best perturbation method in the Nave-Bayes classification is determined to be a random projection-based technique (IRPP) for both the cardiovascular and hypothyroid datasets.

• Health Policy and Management
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• v.25 no.4
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• pp.295-306
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• 2015

This study aims to examine the performance of public municipal hospitals through the analysis of data envelopment analysis, efficiency, profitability, and publicness by using panel data during period from 2006 to 2010. The main findings of the study are as follows. First, as a result of efficiency analysis during the period from 2006 to 2010, it was revealed that the number of staff by each job category, labor cost ratio, the number of operating beds need to be decreased. Second, the performance data represented by the indicators of efficiency, profitability and publicness were complementary and showed a tendency of being increased or decreased in same direction. Third, from the result of panel analysis, the efficiency was mainly influenced by the structural factors, while the profitability was influenced by managerial factors, and the publicness by medical environment. In conclusion, in order to enhance the performance of public municipal hospitals in Korea, it is important to harmonize the effort for efficiency, financial and policy support by central and local government, and the continuous participation of community residents.

• Nuclear Engineering and Technology
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• v.52 no.8
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• pp.1798-1806
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• 2020

In this study, we investigated whether there is a significant relationship between the natural radiation dose rate and the cancer incidences in Korea by using a big data analysis. The natural dose rate data for this analysis were the measurement data obtained from the 171 monitoring posts of the 113 administrative districts in Korea over the 10 years from 2007 to 2016. The relative cancer incidences for this analysis were the difference in the cancer patients per hundred thousand people year-on-year in the administrative districts with the five highest and the five lowest natural gamma dose rates each year over the same period. To analyze the correlation between the two variables, Spearman's rank correlation coefficient between the two rates was derived using R, a well-known big data analysis tool. The analysis showed that Spearman's rank correlation coefficient was more than 0.05 and that the correlation between the two variables was not statistically significant.

• Journal of Korea Technology Innovation Society
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• v.2 no.3
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• pp.94-106
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• 1999

In Korea Basic Science Institute(KBSI) the remote data analysis system is developed for the joint use of advanced equipments. This system enables the researchers to access the datas which are produced at KBSI and analyse them by Java program on the Web,. Except Web browser such as Internet Explorer or Netscape Navigator no additional softwares are required for analysing data. We have developed remote data analysis systems for five major equipments which KBSI supports for the researchers, The systems which are developed are those for NMR spectrometer High Reso-lution Tandem mass Spectrometer Microscopic Imaging System DNA Sequencer and Natural Ra-dioactivity Measruement System, These programs work on any computer platform and any operat-ing system only if the internet is available. This remote data analysis system will be served as a part of Collaboratory the remote collaborative system.

• Proceedings of the Safety Management and Science Conference
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• 2012.04a
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• pp.525-534
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• 2012

The issue is all about the study of warranty data collection and the analysis method to get a reasonable information of the products and improve reliability. In this paper, we consider the classification of warranty data analyses into a parametric and non-parametric analysis and method to get a reasonable information of the products. Also, it is considered the research trend by grouping the relationship among the studies. This study would be used to find the effective application and the condition of warranty data analysis.

• Journal of the Korean Data and Information Science Society
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• v.26 no.6
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• pp.1547-1555
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• 2015

We study the problem of nonignorable nonresponse in a two-way contingency table and there may be one or two missing categories. We describe a nonignorable nonresponse model for the analysis of two-way categorical table. One approach to analyze these data is to construct several tables (one complete and the others incomplete). There are nonidentifiable parameters in incomplete tables. We describe a hierarchical Bayesian model to analyze two-way categorical data. We use a nonignorable nonresponse model with Bayesian uncertainty analysis by placing priors in nonidentifiable parameters instead of a sensitivity analysis for nonidentifiable parameters. To reduce the effects of nonidentifiable parameters, we project the parameters to a lower dimensional space and we allow the reduced set of parameters to share a common distribution. We use the griddy Gibbs sampler to fit our models and compute DIC and BPP for model diagnostics. We illustrate our method using data from NHANES III data to obtain the finite population proportions.

• Journal of Korea Multimedia Society
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• v.19 no.5
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• pp.939-947
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• 2016

As the number of legacy database systems and the size of data to manipulate have been vastly increased, it has become more difficult and complex to analyze characteristics of data. To improve the efficiency of data analysis and help administrators to make decisions in business life, BI(Business Intelligence) system is used. To construct data warehouse and cube from legacy database systems makes it easy and fast to transform raw data into integrated and categorized meaningful information. In this paper, we built a BI system for an University administration. Several source system databases were integrated to data warehouse to build data cubes. The implemented BI system shows much faster data analysis and reporting ability than the manipulation in legacy systems. It is especially efficient in multi dimensional data analysis, nonetheless in single dimensional analysis.