• Journal of KIISE:Computer Systems and Theory
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• v.36 no.2
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• pp.60-67
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• 2009

Analyzing protein-protein interactions(PPI) is an important task in bioinformatics as it can help in new drugs' discovery process. However, due to vast amount of PPI data and their complexity, efficient visualization of the data is still remained as a challenging problem. We have developed efficient and effective visualization system that integrates Gene Ontology(GO) and PPI network to provide better insights to scientists. To provide efficient data visualization, we have employed dynamic interactive graph drawing methods and context-based browsing strategy. In addition, quick and flexible cross-reference system between GO and PPI; LCA(Least Common Ancestor) finding for GO; and etc are supported as special features. In terms of interface, our visualization system provides two separate graphical windows side-by-side for GO graphs and PPI network, and also provides cross-reference functions between them.

• Genomics & Informatics
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• v.7 no.1
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• pp.38-40
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• 2009

The EST Knowledge Integrated System, EKIS (http://ekis.kribb.re.kr), was established as a part of Korea's Ministry of Education, Science and Technology initiative for genome sequencing and application research of the biological model organisms (GEAR) project. The goals of the EKIS are to collect EST information from GEAR projects and make an integrated database to provide transcriptomic and metabolomic information for biological scientists. The EKIS constitutes five independent categories and several retrieval systems in each category for incorporating massive EST data from high-throughput sequencing of 65 different species. Through the EKIS database, scientists can freely access information including BLAST functional annotation as well as Genechip and pathway information for KEGG. By integrating complex data into a framework of existing EST knowledge information, the EKIS provides new insights into specialized metabolic pathway information for an applied industrial material.

• Journal of the Society of Cosmetic Scientists of Korea
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• v.39 no.2
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• pp.105-115
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• 2013

In Korea, the human skin tests to evaluate the anti-wrinkles and whitening effect have been accomplished in accordance with the KFDA guideline. Regarding the data of the visual assessment and machinery evaluation of the results for the human skin test, unpaired t-test have been used in order to compare between the test and the control groups and paired t-test for the comparison of effects for before and after. Descriptive statistics such as frequency analyses was used for the questionnaire evaluation data. In many cases of the European and American clinical test centers, the methodology and the statistical analysis were similar to ours. But, the documentation obtained by repeated application from identical individual has high relation. For this reason, it is desirable to apply RM ANCOVA and RM ANOVA to a visual assessment and machinery evaluation. We suggested that RM ANCOVA and RM ANOVA is the new approach to statistical analysis of human test data of functional cosmetics.

• Genomics & Informatics
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• v.13 no.1
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• pp.7-14
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• 2015

During recent years, there has been exponential growth in biological information. With the emergence of large datasets in biology, life scientists are encountering bottlenecks in handling the biological data. This study presents an integrated geographic information system (GIS)-ontology application for handling microbial genome data. The application uses a linear referencing technique as one of the GIS functionalities to represent genes as linear events on the genome layer, where users can define/change the attributes of genes in an event table and interactively see the gene events on a genome layer. Our application adopted ontology to portray and store genomic data in a semantic framework, which facilitates data-sharing among biology domains, applications, and experts. The application was developed in two steps. In the first step, the genome annotated data were prepared and stored in a MySQL database. The second step involved the connection of the database to both ArcGIS and $Prot{\acute{e}}g{\acute{e}}$ as the GIS engine and ontology platform, respectively. We have designed this application specifically to manage the genome-annotated data of rumen microbial populations. Such a GIS-ontology application offers powerful capabilities for visualizing, managing, reusing, sharing, and querying genome-related data.

• Journal of KIISE:Computing Practices and Letters
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• v.14 no.2
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• pp.211-215
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• 2008

the data-centric publish/subscribe middle-ware is suitable for a communication environment in which various devices dynamically forms a network domain and same type of data are frequently exchanged. For this purpose, OMG has standardized DDS (Data Distribution Service) specification. In this study, we designed the RiTiCoM, data distribution service system that observes the OMG DDS (Data Distribution Service) standard specification and supports the automation of system management, and analyzed the performance and compared with the JMS.

• Journal of Computing Science and Engineering
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• v.2 no.3
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• pp.274-300
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• 2008

Software testing cost can be reduced if the process of testing is automated. However, the test data generation task is still performed mostly by hand although numerous theoretical works have been proposed to automate the process of generating test data and even commercial test data generators appeared on the market. Despite prolific research reports, few attempts have been made to evaluate and characterize those techniques. Therefore, a lot of works have been proposed to automate the process of generating test data. However, there is no overall evaluation and comparison of these techniques. Evaluation and comparison of existing techniques are useful for choosing appropriate approaches for particular applications, and also provide insights into the strengths and weaknesses of current methods. This paper conducts experiments on four representative test data generation techniques and discusses the experimental results. The results of the experiments show that the genetic algorithm (GA)-based test data generation performs the best. However, there are still some weaknesses in the GA-based method. Therefore, we modify the standard GA-based method to cope with these weaknesses. The experiments are carried out to compare the standard GA-based method and two modified versions of the GA-based method.

• Journal of KIISE:Databases
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• v.34 no.4
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• pp.369-377
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• 2007

Histogram is one of tools that efficiently summarize data, and it is widely used for selectivity estimation and approximate query answering. Existing histogram construction algorithms are applicable to point data represented by a set of values. As often as point data, we can meet interval data such as daily temperature and daily stock prices. In this paper, we thus propose the histogram construction algorithms for interval data by extending several methods used in existing histogram construction algorithms. Our experiment results, using synthetic data, show our algorithms outperform naive extension of existing algorithms.

• Journal of KIISE:Computer Systems and Theory
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• v.27 no.6
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• pp.592-598
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• 2000

The locality of data references at the distributed shared memory systems affects the performance significantly. Data allocation methods by considering the locality of data references can improve the performance of DSM systems. This paper evaluates the performance for the dynamic limited directory scheme which data allocation methods can apply very effectively. The information of the data allocation is used by the dynamic limited directory scheme to set the presence bit effectively. And the proper use of the presence bit improves the performance by reducing memory overhead and using directory pool efficiently. Simulations are conducted using three application programs which have various data sharing. The results show that the optimal data allocation method improves the performance up to 3.6 times in the proposed scheme.

• Proceedings of the Korean Information Science Society Conference
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• 2008.06c
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• pp.36-40
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• 2008

SIMS manages data for various spatial and non-spatial as integral management system to support space information administration environment and support several application works. Without being limited to spatial data that existent spatial Data Mining question language advances handling in this paper, did so that can find useful information from various data connected with automatically data collection, artificial satellite side upside service, remote sensing, GPS. Mobile Computing and data about Spatio-Temporal. Also, we designed spatial Data Mining query language that support a spatial Data Mining exclusive use system based on SIMS.

• Journal of Korean Society for Quality Management
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• v.45 no.4
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• pp.677-696
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• 2017

Purpose: This study suggests that Six Sigma MBB should be used as a key talent to lead the fourth industrial revolution era by training them with big data processing capability. Methods: Through the analysis between articles on the fourth industrial revolution and Six Sigma related papers, common competencies of data scientists and Six Sigma MBBs were identified and the big data analysis capabilities needed for Six Sigma MBB were derived. Then, training was conducted to improve the big data analysis capabilities so that Six Sigma MBB is able to design algorithms required in the fourth industrial revolution era. Results: Six Sigma MBBs, equipped with the knowledge in field site improvement and basic statistics, were provided with 40 hours of big data analysis training and then were made to design a big data algorithm. Positive results were obtained after applying a AI algorithm which could forecast process defects in a field site. Conclusion: Six Sigma MBB equipped with big data capability will make the best talent for the fourth industrial revolution era. A Six Sigma MBB has an excellent capability for improving field sites. Utilizing the competencies of MBB can be a key to success in the fourth industrial revolution. We hope that the results of this study will be shared with many companies and many more improved case studies will arise in the future as a result of this study.