• Journal of Environmental Analysis, Health and Toxicology
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• v.21 no.4
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• pp.237-242
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• 2018

Strontium (Sr) commonly exists in rock, groundwater, soil, plants, and animals. The Sr isotope ratio offers important information as a tracer on nature because the Sr isotopic composition is not fractionated by any biological process in these ecosystems. Hence, Sr isotope ratio has been used in several studies on tracing the Sr source for contaminated sites and human migration. In this study, we developed a separation method for Sr content, and then improved Sr isotope analysis using multi-collector inductively coupled plasma mass spectrometry (MC-ICP-MS). A powdered rock standard (NIST 2710a) was used to determine the removal of interference elements (Rb and Ca) and the recovery rate of Sr content. The results ranged from 98% to 106%. Additionally, three standard samples (NBS 987, IAPSO and NIST 1486) were analyzed to evaluate the precision and accuracy of the results. The measured $^{87}Sr/^{86}Sr$ ratio for all the samples were consistent with the reported values, within an error. These results indicate that our established Sr separation and Sr isotope measurement methods are reliable and can hence be useful in the fields of environmental and forensic sciences.

• Journal of electromagnetic engineering and science
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• v.5 no.4
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• pp.176-182
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• 2005

In this paper, an efficient multipaction analysis method of a manifold multiplexer for satellite applications is presented. While FEM(Finite Element Method) is used for the multipaction analysis of the lowpass filter, the equivalent circuit model is used for the analysis of the channel filters and the manifold. Employing equivalent circuit model for multipaction analysis takes less time than using EM(Electromagnetic) field analysis method while keeping the accuracy of the multipaction analysis. This present analysis method is applied to the manifold multiplexer for Ka-band satellite transponders and the results show that the present method is as accurate as the conventional EM field analysis method.

• Journal of Korean Medical classics
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• v.20 no.4
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• pp.171-186
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• 2007

The fusion research subjects of Oriental medicine and Bio-Technology are actively advanced. Development of information analysis algorithm for constitution diagnosis using clinical and biological information is started recently. In addition, the research for providing personal oriented treatment information with Diagnosis result is to in the process of advancing. This paper considers the inside and outside of the country technical development trend of research for using clinical and biological information by analyzing patents and papers. It executed information analysis about changes to number of research papers and patents, present state and star higher officer of research facility from the dissertation which it sees. It is known that our country research result is slight so far in quantity and quality as result of analysis. But hereafter it contains a many developmental possibility. Also it reflects the appearance and a growth of new field like bioinformatics from constitution and bio information application field. The combination of bio information similar to constitution and heredity and computing technology to control those information efficiently comes to think with core technique.

• The Research Journal of the Costume Culture
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• v.27 no.3
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• pp.274-284
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• 2019

Research on cosmetic behavior has developed significantly since the 2000s. Reviewing cosmetic behavior research can be meaningful because it can grasp trends in the domestic cosmetics market, and it can also illuminate how domestic consumers' interest in makeup has changed over time. The purpose of this study is to investigate the links between major keywords and the keywords which affect makeup behavior of different age groups through network analysis. In this study we analyzed thesis and journal data based on makeup behavior through network analysis using Nodexl. We analyzed 10 years of journals and theses - from 2000 to 2017, and investigated age-related differences in variables related to makeup behavior. Research subjects were divided into age-based groups: 10, 20-40, and over 50. The total number of theses collected was 82. In order to perform network analysis using the Nodexl program, we extracted the frequency of representative words using the KrKwic program. The extracted core words were analyzed for degree centrality, betweenness centrality and eigenvector centrality using Nodexl. The expected result is that the network analysis using keywords will lead to different variables depending on age and the main goal of the cosmetics market, and it is expected to be used as the basis for follow-up research related to cosmetic behavior.

• Nuclear Engineering and Technology
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• v.54 no.7
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• pp.2418-2426
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• 2022

The grouping analysis is a method guided by the Korea Radioactive Waste Agency for efficient analysis of radioactive waste for disposal. In this study, experiments to verify the adequacy of grouping analysis were conducted with radioactive soil, concrete, and dry active waste in similar environments. First, analysis results of the major radionuclide concentrations in individual waste samples were reviewed to evaluate whether wastes from similar environments correspond to a single waste stream. As a result, the soil and concrete waste were identified as a single waste stream because the distribution range of radionuclide concentrations was "within a factor of 10", the range that meet the criterion of the U.S. Nuclear Regulatory Commission for a single waste stream. On the other hand, the dry active waste was judged to correspond to distinct waste streams. Second, after analyzing the composite samples prepared by grouping the individual samples, the population means of the values of "composite sample analysis results/individual sample analysis results" were estimated at a 95% confidence level. The results showed that all evaluation values for soil and concrete waste were within the set reference values (0.1-10) when five-package and ten-package grouping analyses were conducted, verifying the adequacy of the grouping analysis.

• Journal of the Korea Society of Computer and Information
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• v.28 no.10
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• pp.55-65
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• 2023

In this paper, we apply KeyBERT(Keyword extraction with Bidirectional Encoder Representations of Transformers) algorithm-driven topic extraction and topic frequency analysis to deep learning and reinforcement learning research to discover the rapidly changing trends in them. First, we crawled abstracts of research papers on deep learning and reinforcement learning, and temporally divided them into two groups. After pre-processing the crawled data, we extracted topics using KeyBERT algorithm, and then analyzed the extracted topics in terms of topic occurrence frequency. This analysis reveals that there are distinct trends in research work of all analyzed algorithms and applications, and we can clearly tell which topics are gaining more interest. The analysis also proves the effectiveness of the utilized topic extraction and topic frequency analysis in research trend analysis, and this trend analysis scheme is expected to be used for research trend analysis in other research fields. In addition, the analysis can provide insight into how deep learning will evolve in the near future, and provide guidance for select research topics and methodologies by informing researchers of research topics and methodologies which are recently attracting attention.

• Journal of Korean Society for Quality Management
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• v.44 no.2
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• pp.389-408
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• 2016

Purpose: This study was designed to analyze the behavioral change of knowledge structures and the trends of research topics in the quality management field. Methods: The network structure and knowledge structure of the words were visualized in map form using co-word analysis, cluster analysis and strategic diagram. Results: Summarizing the research results obtained in this study are as follows. First, the word network derived from co-occurrence matrix had 106 nodes and 5,314 links and its density was analyzed to 0.95. Average betweenness centrality of word network was 2.37. In addition, average closeness centrality and average eigenvector centrality of word network were 0.01. Second, by applying optimal criteria of cluster decision and K-means algorithm to word co-occurrence matrix, 106 words were grouped into seven clusters such as standard & efficiency, product design, reliability, control chart, quality model, 6 sigma, and service quality. Conclusion: According to the results of strategic diagram analysis over time, the traditional research topics of quality management field related to reliability, 6 sigma, control chart topics in the third quadrant were revealed to be declined for their study importance. Research topics related to product design and customer satisfaction were found to be an important research topic over analysis periods. Research topic related to management innovation was emerging state and the scope of research topics related to process model was extended to research topics with system performance. Research topic related to service quality located in the first quadrant was analyzed as the key research topic.

• Journal of Korean Academy of Nursing Administration
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• v.23 no.1
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• pp.101-110
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• 2017

Purpose: This study aimed to identify research trends in the Journal of Korean Academy of Nursing Administration from 2013 to 2015. Methods: For this study, 171 articles were analyzed. Research designs, participants, research settings, sampling, and data analyses methods were reviewed using established analysis criteria. Keyword centrality and clusters were generated by keyword network analysis. Results: Most of studies used quantitative methods (82.5%), and sampling mainly focused on nurses (68.8%). The most commonly used data analyses methods were t-test, ANOVA, correlation, and regression. The most central keywords were turnover and empowerment. Network analysis generated four network groups: 1) burnout; 2) turnover; 3) happiness; and 4) nursing professionalism. Conclusion: The results of this study identify current trends and interests in Korean nursing administration research. The findings from this study suggest that future studies include a variety of research methods and maintain appropriate research ethics.

• The Korean Journal of Food And Nutrition
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• v.31 no.3
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• pp.416-424
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• 2018

The physiologically advantageous aspects of green tea have been identified recently and green tea has been a favorite drink of many people. Due to the increased awareness of green tea's positive effects on human health, the demand for foods containing green tea has increased. This has led to the development of diverse green tea-related beverages; thereby many companies in Korea have put a wide variety of manufactured green tea beverages on the market. However, the components within green tea beverages have not been examined in Korea yet. In this study, we investigated the contents of the physiologically functional materials found in green tea, such as catechin, catechin gallate, epicatechin, epicatechin gallate, epigallocatecin gallate, gallocatechin gallate and caffeine. Fifty-six green tea products purchased from the local grocery stores and cafes were analyzed using high performance liquid chromatography (HPLC) analysis. As a result, all tested products contained catechin and caffeine, although the amount of each component was largely different. The total amount of catechin derivatives in the manufactured green tea beverages purchased from cafes was 263.17 mg/L, while they were 61.99 mg/L in the beverages purchased from the local grocery stores. And, to the almost samples the amount of caffeine was proportional to the amount of catechin.

• Korean Journal of Hazardous Materials
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• v.2 no.1
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• pp.6-11
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• 2014

There have been frequent chemical leaks over the past 10 years. Particularly, inorganic acids like sulfuric acid, nitric acid, and hydrogen chloride take up 37 % of the total chemical accidents which took place for the past 10 years. When an acid chemical leak happens, fume is generated, diffusing into the air, which might cause serious damage to health of local residents and the environment. However, most of the acid-based chemicals, detecting and analysis methods have not been settled considering the frequency of accidents. In this study, we investigated detection and analysis methods to quickly analyze accident sites and evaluate the impacts on environments. Reviewing local and international test analysis methods of acids suggested that nitric acid, sulfuric acid, hydrogen chloride and hydrogen fluoride can be analyzed with IC. It was also found that UV is better for the analysis of hydrogen fluoride and GC/MS for acrylic acid. The analytical methods suggested in the official test methods basically have limitations of consuming much time at stages of preparation and analysis. Considering prompt responses to chemical accidents, further studies should be done to compare the applicability of rapid monitoring methods such as FT-IR, IMR-MS and SIFT-MS.