• Journal of Pharmacopuncture
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• v.24 no.3
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• pp.142-151
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• 2021

Objectives: Although Korean Medicine (KM) subsidized by the National Health Insurance (NHI) has been used for a long time, there has been no active analysis using claims data. Therefore, the purpose of this study was to examine the NHI KM utilization trend using NHI statistics and to measure the level of market concentration by year. Methods: By restructuring the contents of NHI Statistics for Pharmaceuticals for 2010-2019, the claim cases, costs, and annual growth rates of KM were demonstrated by year, sex, age group, region, therapeutic group, and KM treatment. The proportion of highly used k treatments in cost was calculated as the concentration ratio (CR) k and its trend by year was investigated. Results: In 2019, the NHI cost on KM amounted to ₩38.2 billion KRW, increasing by 11.6% per year on average in 2010-2019. Notably, KM was used more frequently among women and patients aged ≥ 65 years, and the mixed formulation accounted for 95% of the total cost of KM. The CR of the simple formulation increased rapidly, whereas that of the mixed formulation remained constant. In 2019, three simple formulation treatments- peony, licorice, and ginseng- accounted for 93.8% of the total cost for KM (CR3 = 93.8%). Conclusion: NHI KM is rapidly increasing. Investigating the CR of KM confirmed that KM prescriptions have been concentrated in small numbers over the past 10 years.

• The Journal of the Korea Contents Association
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• v.20 no.7
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• pp.66-85
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• 2020

The purpose of this study is to explain and predict trends the AI development process based on AI technology patents (total) and AI reporting frames in major newspapers. To that end, a summary of South Korean and U.S. technology patents filed over the past nine years and the AI (Artificial Intelligence) news text of major domestic newspapers were analyzed. In this study, Topic Modeling and Time Series Return Analysis using Big Data were used, and additional network agenda correlation and regression analysis techniques were used. First, the results of this study were confirmed in the order of artificial intelligence and algorithm 5G (hot AI technology) in the AI technical patent summary, and in the news report, AI industrial application and data analysis market application were confirmed in the order, indicating the trend of reporting on AI's social culture. Second, as a result of the time series regression analysis, the social and cultural use of AI and the start of industrial application were derived from the rising trend topics. The downward trend was centered on system and hardware technology. Third, QAP analysis using correlation and regression relationship showed a high correlation between AI technology patents and news reporting frames. Through this, AI technology patents and news reporting frames have tended to be socially constructed by the determinants of media discourse in AI development.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.3
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• pp.171-176
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• 2024

IT-related fields are very diverse. As of 2018, the IT revolution from the Fourth Industrial Revolution not only brought out the new fields that were different from the previous ones, but it also made a reexamination of various fields that had already been an issue in the past. Companies and public institutions have a great interest in understanding IT trends in this situation. Therefore, in this paper, IT trends are identified through the analyzation of keywords provided by domestic papers. Moreover, unlike previous industry trend analysis or economic analysis, this paper focuses on analyzing the keyword provided by the doctoral thesis or master's thesis about direct IT-related research, and grasps the more basic and direct IT trend. This analysis predicts and presents the vision based on the data of the analysis from the academic papers that researched in IT technology for IT related students or IT related educators.

• Journal of Fashion Business
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• v.6 no.2
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• pp.67-76
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• 2002

This research examines the characteristic trends through analysis on cue in the contemporary fashion distinctly and systematically. It is carried out by both qualitative analysis and quantitative analysis. In the qualitative analysis, the four important street fashions of neo-mods/jazz, neo-hippie/grunge, sportivecasual and technos/cyber-punk are grouped. In the quantitative analysis, statistical data are sampled from Collection II of the 1990s S/S. It takes frequency, percentage, $\chi^2$-test and etc. by using the comprehensive tools for statistical treatment. There were significant differences between the S/S fashion. According to the cues, there are also significant differences between the fashion in the 1990s. In 'Neo-Mos/Jazz' style shows highly androgynous look, deep and strong tone, green/blue colors, natural fabric, stripe pattern, long hair style, and hided make-up. 'Neo-hippie/gnenge' style shows highly folklore look, vivid tone purple colors, seethrough/knit fabric, natural /traditional pattern, decorative hair special makeup. 'Sportive casuals' style shows highly sportive look, greish tone, white/grey colours, natural fabric, solid patten, bobbed hair, and natural make-up. 'Techno/cyber punk style shows highly comocorps look, pale tone black colors avangard fabric, solid patten, punk/dyed hair special make-up.

• Journal of Digital Convergence
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• v.15 no.6
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• pp.133-143
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• 2017

Data is the most important asset in the financial sector. On average, 71 percent of financial institutions generate competitive advantage over data analysis. In particular, in the card industry, the card transaction data is widely used in the development of merchant information, economic fluctuations, and information services by analyzing patterns of consumer behavior and preference trends of all customers. However, creation of new value through fusion of data is insufficient. This study introduces the analysis and forecasting of consumption trends of credit card companies which convergently analyzed the social data and the sales data of the company's own. BC Card developed an algorithm for linking card and social data with trend profiling, and developed a visualization system for analysis contents. In order to verify the performance, BC card analyzed the trends related to 'Six Pocket' and conducted th pilot marketing campaign. As a result, they increased marketing multiplier by 40~100%. This study has implications for creating a methodology and case for analyzing the convergence of structured and unstructured data analysis that have been done separately in the past. This will provide useful implications for future trends not only in card industry but also in other industries.

• Journal of Korean Society for Atmospheric Environment
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• v.13 no.1
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• pp.9-18
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• 1997

Precipitation samples were collected by the wet- only event sampling method from Seoul during September 1991 to April 1995. These samples were analyzed for the concentrations of the major ionic components (N $O_3$$^{[-10]}$ , N $O_2$$^{[-10]}$ , S $O_4$$^{2-}$, C $l^{[-10]}$ , $F^{[-10]}$ , N $a^{＋}$, $K^{+}$, $Ca^{2＋}$, $Mg^{2＋}$, and N $H_4$$^{＋}$), pH, and electric conductivity. During the study period, a total of 182 samples were collected, but only 163 samples were used for the data analysis via quality assurance of precipitation chemistry data. The volume-weighted pH was found to be 4.7. The major acidifying species from our precipitation studies were identified to be non-seasalt sulfate (84$\pm$9 $\mu$eq/L) and nitrate (24$\pm$2 $\mu$eq/L) except for chloride. Because the Cl/Na ratio in the precipitation was close to the ratio in seawater. If all of the non-seasalt sulfate and nitrate were in the form of sulfuric and nitric acids, the mean pH in the precipitation could have been as low as 3.7 lower than the computed value. Consequently, the difference between two pH values indicate that the acidity of precipitation was neutralized by alkaline species. The equivalent concentration ratio of sulfate to nitrate was 3.5, indicating that sulfuric and nitric acids can comprise 78％ and 22％ of the precipitation acidity, respectively. Analysis of temporal trend in the measured acidity and ionic components were also performed using the linear regression method. The precipitation acidity generally showed a significantly decreasing trend, which was compatible with the pattern of the ratio (N $H_4$$^{＋}$＋C $a^{2＋}$)/ (nss-S $O_4$$^{2-}$＋N $O_3$$^{[-10]}$ ).).

• Proceedings of the Korean Society of Computer Information Conference
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• 2013.01a
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• pp.99-101
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• 2013

본 논문에서는 사춘기 여고생들의 기능성 화장품의 신상품 개발과 성능 향상을 위한 효율적인 정보의 분석과 생산 정책을 위한 SNS 분석시스템을 제안한다. 제안하는 시스템은 여고생들의 기능성 화장품에 관한 SNS 내용을 분석하기 위한 효율적 알고리즘과 방법론을 제안하여 시스템의 처리량을 최대화하고, 각 작업의 수행시간을 최소화한다. 또한 여고생들의 기능성 화장품에 대한 기호 상태를 파악하여, 그 분석 결과를 제품의 개발 및 생산에 반영하기 위한 비주얼 방법론을 함께 제안한다. 따라서 본 논문에서 제안하는 시스템은 단지 화장품에 대한 분석뿐만 아니라 이와 비슷한 소비자의 기호가 빠르게 변화하는 제조업 분야에서 다양하게 응용이 가능하다.

• Journal of Information Science Theory and Practice
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• v.10 no.spc
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• pp.112-122
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• 2022

Food security and its sovereignty have become among the most important key issues due to changes in the international situation. Regarding these issues, many countries now give attention to smart agriculture, which would increase production efficiency through a data-based system. The Korean government also has attempted to promote smart agriculture by 1) implementing the agri-food ICT (information and communications technology) policy, and 2) increasing the R&D budget by more than double in recent years. However, its endeavors only centered on large-scale farms which a number of domestic farmers rarely utilized in their farming. To promote smart agriculture more effectively, we diagnosed the government R&D trends of smart agriculture based on NTIS (National Science and Technology Information Service) data. We identified the research trends for each R&D period by analyzing three pieces of information: the regional information, research actor, and topic. Based on these findings, we could suggest systematic R&D directions and implications.

• The Journal of the Korea Contents Association
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• v.20 no.3
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• pp.515-526
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• 2020

Digital healthcare is a combined area of medical field and IT and various information on digital healthcare is provided in social media. This study aims to find the research trend of digital healthcare by collecting and analyzing data related to digital healthcare through the social media. The data were collected from Naver and Daum's news and blogs from January 2008 to June 2019. Major keywords with high frequency were extracted and visualized with wordcloud and network analysis was used to analyze the relationship between major keywords. Research combining medical field and IT from 2008 to 2001, various convergence research based on medical field and IT from 2012 to 2015, convergence research that applied the 4th industrial revolution technologies such as big data, blockchain and AI were actively conducted from 2016 to June 2019.

• The Korean Journal of Applied Statistics
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• v.19 no.2
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• pp.319-330
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• 2006

A signal in real world usually composes of multiple signals having different scales of frequencies. For example sun-spot data is fluctuated over 11 year and 85 year. Economic data is supposed to be compound of seasonal component, cyclic component and long-term trend. Decomposition of the signal is one of the main topics in time series analysis. However when the signal is subject to nonstationarity, traditional time series analysis such as spectral analysis is not suitable. Huang et. at(1998) proposed data-adaptive method called empirical mode decomposition (EMD) . Due to its robustness to nonstationarity, EMD has been applied to various fields. Huang et. at, however, have not considered denoising when data is contaminated by error. In this paper we propose efficient denoising method utilizing cross-validation.