• Information Systems Review
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• v.21 no.2
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• pp.117-137
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• 2019

In the Big Data era, data science has become popular with the production of numerous data in various domains, and the power of data has become a competitive power. There is a growing interest in unstructured data, which accounts for more than 80% of the world's data. Along with the everyday use of social media, most of the unstructured data is in the form of text data and plays an important role in various areas such as marketing, finance, and distribution. However, text mining using social media is difficult to access and difficult to use compared to data mining using numerical data. Thus, this study aims to develop Korean Natural Language Application (KoALA) as an integrated application for easy and handy social media text mining without relying on programming language or high-level hardware or solution. KoALA is a specialized application for social media text mining. It is an integrated application that can analyze both Korean and English. KoALA handles the entire process from data collection to preprocessing, analysis and visualization. This paper describes the process of designing, implementing, and applying KoALA applications using the design science methodology. Lastly, we will discuss practical use of KoALA through a block-chain business case. Through this paper, we hope to popularize social media text mining and utilize it for practical and academic use in various domains.

• Journal of Environmental Health Sciences
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• v.37 no.6
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• pp.429-439
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• 2011

Objectives: Ethylene oxide (EtO) is classified as a human carcinogen, but EtO is still widely used to sterilize heat-sensitive materials in hospitals. Employees working around sterilizers are exposed to EtO after sterilization. The aim of the present study was to assess the exposure of EtO level, coupled with occupationally induced micronuclei from hospital workers. The influence of genetic polymorphisms of detoxifying genes (GSTT1 and GSTM1) and DNA repair genes (XRCC1 and XRCC3) on the frequencies of micronuclei in relation to exposure of EtO was also investigated. Methods: The study population was composed of 35 occupationally exposed workers to EtO, 18 student controls and 44 unexposed hospital controls in Korea. Exposure to EtO is measured by passive personal samplers. We analyzed the frequencies of micronuclei by performing cytokinesis-block micronucleus assay (CBMN assay) and GSTM1, GSTT1, XRCC1, and XRCC3 were also genotyped by performing polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP). Results: The frequencies of micronuclei in EtO exposure group, student controls and hospital controls were $18.00{\pm}7.73$, $10.47{\pm}7.96$ and $13.86{\pm}6.35$ respectively and their differences were statistically significant, but no significant differences according to the level of EtO were observed. There was a dose-response relationship between the frequencies of micronuclei and cumulative dose of EtO, but no significantly differences were observed. We also investigated the influence of genetic polymorphisms (GSTM1, GSTT1, XRCC1, and XRCC3) on the frequencies of micronuclei, but there were no differences in the frequencies of micronuclei by genetic polymorphisms. Conclusions: The frequencies of micronuclei in EtO exposure group was significantly higher than control groups. A dose-response relationship was found between the level of EtO exposure and the frequencies of micronuclei, but no statistically differences were observed. We also found that the frequencies of micronuclei were increased according to cumulative EtO level. There was no association of the genetic GSTM1, GSTT1, XRCC1, and XRCC3 state with the frequency of micronuclei induced by EtO exposure.