• Title/Summary/Keyword: Administration Data

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Algorithms for Determining Korea Meteorological Administration (KMA)'s Official Typhoon Best Tracks in the National Typhoon Center (기상청 국가태풍센터의 태풍 베스트트랙 생산체계 소개)

  • Kim, Jinyeon;Hwang, Seung-On;Kim, Seong-Su;Oh, Imyong;Ham, Dong-Ju
    • Atmosphere
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    • v.32 no.4
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    • pp.381-394
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    • 2022
  • The Korea Meteorological Administration (KMA) National Typhoon Center has been officially releasing reanalyzed best tracks for the previous year's northwest Pacific typhoons since 2015. However, while most typhoon researchers are aware of the data released by other institutions, such as the Joint Typhoon Warning Center (JTWC) and the Regional Specialized Meteorological Center (RSMC) Tokyo, they are often unfamiliar with the KMA products. In this technical note, we describe the best track data released by KMA, and the algorithms that are used to generate it. We hope that this will increase the usefulness of the data to typhoon researchers, and help raise awareness of the product. The best track reanalysis process is initiated when the necessary database of observations-which includes satellite, synoptic, ocean, and radar observations-has become complete for the required year. Three categories of best track information-position (track), intensity (maximum sustained winds and central pressure), and size (radii of high-wind areas)-are estimated based on scientific processes. These estimates are then examined by typhoon forecasters and other internal and external experts, and issued as an official product when final approval has been given.

The Study on Application of Data Gathering for the site and Statistical analysis process (초기 데이터 분석 로드맵을 적용한 사례 연구)

  • Choi, Eun-Hyang;Ree, Sang-Bok
    • Proceedings of the Korean Society for Quality Management Conference
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    • 2010.04a
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    • pp.226-234
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    • 2010
  • In this thesis, we present process that remove mistake of data before statistical analysis. If field data which is not simple examination about validity of data, we cannot believe analyzed statistics information. As statistical analysis information is produced based on data to be input in statistical analysis process, the data to be input should be free of error. In this paper, we study the application of statistical analysis road map that can enhance application on site by organizing basic theory and approaching on initial data exploratory phase, essential step before conducting statistical analysis. Therefore, access to statistical analysis can be enhanced and reliability on result of analysis can be secured by conducting correct statistical analysis.

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Data Integration for DW Construction

  • Yongmoo Suh;Jung, Chul-Yong
    • The Journal of Information Technology and Database
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    • v.4 no.2
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    • pp.79-95
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    • 1998
  • Useful data being distributed over several systems, we have a problem in accessing and utilizing them. Recognizing this problem, researchers have proposed two concepts as solutions to the problem, multidatabase and data warehouse. The one provides a virtual view over the distributed data, and the latter is a materialized view of it. Recently, more attention has been paid to the latter, which is a single of distributed database, collected along a time dimension. So, the major issues in building a data warehouse are 1) how to define a global schema for the data warehouse, 2) how to capture changes from local databases, and 3) how to represent time-varying values of data item. This paper presents an integrated approach to these issues, borrowing the research results from such areas as multidatabase, active databases and temporal databases.

Building Smarter City through Big Data - Best Practices in Seoul Metropolitan Gov.

  • Kim, Ki-Byoung
    • International conference on construction engineering and project management
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    • 2015.10a
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    • pp.19-20
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    • 2015
  • Since 2013, Seoul Metropolitan Government (SMG) has introduced big data initiatively in administration and put into practices in transportation, safety, welfare in order to overcome limited resources and conflicting interests. For establishing a new midnight bus service, SMG prepared optimized midnight bus routes by analyzing big data from mobile phone Call Data Record (CDR) through collaboration with a telecommunication company. Despite of limited budget and resources, newly identified routes can cover over 42% of the citizen with 9 routes and less than 1% of buses compare with day time operation. In addition to solve transportation problem, SMG utilizes big data to resolve location selection problem for choosing new facility locations such as life double cropping centers and senior citizen leisure centers. As results, SMG demonstrates big data as a good tool to make policies and to build smarter city by overcome space-time limitation of resources, mediation of conflicts, and maximizes benefit of the citizen.

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A Study on the Big Data Analysis and Predictive Models for Quality Issues in Defense C5ISR (국방 C5ISR 분야 품질문제의 빅데이터 분석 및 예측 모델에 대한 연구)

  • Hyoung Jo Huh;Sujin Ko;Seung Hyun Baek
    • Journal of Korean Society for Quality Management
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    • v.51 no.4
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    • pp.551-571
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    • 2023
  • Purpose: The purpose of this study is to propose useful suggestions by analyzing the causal effect relationship between the failure rate of quality and the process variables in the C5ISR domain of the defense industry. Methods: The collected data through the in house Systems were analyzed using Big data analysis. Data analysis between quality data and A/S history data was conducted using the CRISP-DM(Cross-Industry Standard Process for Data Mining) analysis process. Results: The results of this study are as follows: After evaluating the performance of candidate models for the influence of inspection data and A/S history data, logistic regression was selected as the final model because it performed relatively well compared to the decision tree with an accuracy of 82%/67% and an AUC of 0.66/0.57. Based on this model, we estimated the coefficients using 'R', a data analysis tool, and found that a specific variable(continuous maximum discharge current time) had a statistically significant effect on the A/S quality failure rate and it was analysed that 82% of the failure rate could be predicted. Conclusion: As the first case of applying big data analysis to quality issues in the defense industry, this study confirms that it is possible to improve the market failure rates of defense products by focusing on the measured values of the main causes of failures derived through the big data analysis process, and identifies improvements, such as the number of data samples and data collection limitations, to be addressed in subsequent studies for a more reliable analysis model.

Detection of Stock Price Manipulation : A Data Mining Approach (데이터마이닝기법을 이용한 주식시장의 이상매매 적출)

  • Hong, Chung-Hun;Ahn, Sung Mahn;Wee, Kyung Woo
    • Journal of Intelligence and Information Systems
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    • v.12 no.4
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    • pp.15-37
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    • 2006
  • In this paper, we discuss a data mining approach to detection of stock price manipulation in the Korean stock market. First of all, we review current methods which is being exercised in the Korean stock market as well as in the US stock market. And then we apply data mining techniques to the problem using data from the Korean stock market and discuss the results along with their implications.

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HPLC-based metabolic profiling and quality control of leaves of different Panax species

  • Yang, Seung-Ok;Lee, Sang Won;Kim, Young Ock;Sohn, Sang-Hyun;Kim, Young Chang;Hyun, Dong Yoon;Hong, Yoon Pyo;Shin, Yu Su
    • Journal of Ginseng Research
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    • v.37 no.2
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    • pp.248-253
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    • 2013
  • Leaves from Panax ginseng Meyer (Korean origin and Chinese origin of Korean ginseng) and P. quinquefolius (American ginseng) were harvested in Haenam province, Korea, and were analyzed to investigate patterns in major metabolites using HPLC-based metabolic profiling. Partial least squares discriminant analysis (PLS-DA) was used to analyze the the HPLC chromatogram data. There was a clear separation between Panax species and/or origins from different countries in the PLS-DA score plots. The ginsenoside compounds of Rg1, Re, Rg2, Rb2, Rb3, and Rd in Korean leaves were higher than in Chinese and American ginseng leaves, and the Rb1 level in P. quinquefolius leaves was higher than in P. ginseng (Korean origin or Chinese origin). HPLC chromatogram data coupled with multivariate statistical analysis can be used to profile the metabolite content and undertake quality control of Panax products.

Statistical Analysis of Determining Optimal Monitoring Time Schedule for Crop Water Stress Index (CWSI) (작물 수분 스트레스 지수 산정을 위한 최적의 관측 간격과 시간에 대한 통계적 분석)

  • Choi, Yonghun;Kim, Minyoung;Oh, Woohyun;Cho, Junggun;Yun, Seokkyu;Lee, Sangbong;Kim, Youngjin;Jeon, Jonggil
    • Journal of The Korean Society of Agricultural Engineers
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    • v.61 no.6
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    • pp.73-79
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    • 2019
  • Continuous and tremendous data (canopy temperature and meteorological variables) are necessary to determine Crop Water Stress Index (CWSI). This study investigated the optimal monitoring time and interval of canopy temperature and meteorological variables (air temperature, relative humidity, solar radiation and wind speed) to determine CWSIs. The Nash-Sutcliffe model efficiency coefficient (NSE) was used to quantitatively describe the accuracy of sampling method depending upon various time intervals (t=5, 10, 15, 20, 30 and 60 minutes) and CWSIs per every minute were used as a reference. The NSE coefficient of wind speed was 0.516 at the sampling time of 60 minutes, while the ones of other meteorological variables and canopy temperature were greater than 0.8. The pattern of daily CWSIs increased from 8:00 am, reached the maximum value at 12:00 pm, then decreased after 2:00 pm. The statistical analysis showed that the data collection at 11:40 am produced the closest CWSI value to the daily average of CWSI, which indicates that just one time of measurement could be representative throughout the day. Overall, the findings of this study contributes to the economical and convenient method of quantifying CWSIs and irrigation management.

Comparative nutritional analysis for protopanaxadiol-enhanced genetically modified rice and its non-transgenic counterpart

  • Na Yeon Kim;Sung Dug Oh;Soo Yun Park;An Cheol Chang;Seong Kon Lee;Ye Jin Jang;So-Hyeon Baek;Yong Eui Choi;Jong-Chan Park;Doh Won Yun
    • Korean Journal of Agricultural Science
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    • v.51 no.2
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    • pp.239-249
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    • 2024
  • In the assessment of the biosafety of genetically modified (GM) crops, a comparative approach to identifying similarities and differences between transgenic and non-transgenic crops is helpful in identifying potential safety and nutritional issues. In this study, we aimed to compare the nutritional composition of a protopanaxadiol-enhanced genetically modified rice (PPD GM rice) with its non-transgenic counterpart. The nutritional profile of PPD GM rice was assessed against that of the parental rice cultivar 'Dongjin' to ascertain nutritional equivalence. No differences were observed between PPD GM and Non-GM rice cultivar in proximate analysis, mineral content, and amino acid composition. Although significant differences were observed in crude fat, crude protein, total dietary fiber, and some minerals between PPD GM rice and Dongjin, these variances fell within the range suggested by common cultivars (Anmi and Nipponbare) and Organization for Economic Cooperation and Development (OECD) data. Similarly, while some amino acids showed significant differences, these metabolites did not deviate from the OECD range. Principal component analysis (PCA) was conducted using the nutritional analysis data of PPD GM rice and Dongjin. The results revealed that PPD GM rice and Dongjin were grouped according to their respective cultivation years. This suggests that the variability in the nutritional composition of PPD GM rice tends to resemble that of the parental rice cultivar 'Dongjin' rather than being solely attributed to genetic modification. Overall, our findings indicate that the nutritional composition of PPD GM rice is substantially equivalent to that of its non-transgenic counterpart.

National Standard Food Composition Tables Provide the Infrastructure for Food and Nutrition Research According to Policy and Industry (식품 영양 연구, 정책, 산업의 기반이 되는 국가표준식품성분표의 활용)

  • Lim, Sung-Hee;Kim, Jung-Bong;Cho, Young-Sook;Choi, YoungMin;Park, Hong-Ju;Kim, Se-Na
    • The Korean Journal of Food And Nutrition
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    • v.26 no.4
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    • pp.886-894
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    • 2013
  • The National Standard Food Composition Table published by the Rural Development Administration (RDA) provides the foundations in research, nutrition monitoring, policy and dietary practices in Korea. This databases consists of several sets of data including food descriptions, nutrients, portion weights, and source of data. The National Standard Food Composition Table have been published since 1970 and, recently, new version (8th edition) of Food Composition Table which has quantitative and qualitative nutrient data is released in 2011. In addition, the User-friendly Food Composition Table is divided into adult, children, and elderly categories depending on the subjects because we need different nutrients according to various ages. The Tables of Food Functional Composition is firstly edited in 2009. RDA published the minerals and fatty acids composition table, tables of amino acid, fat-soluble vitamin composition table, and the cholesterol table. The resulting database will be widely used. The users of the databases are from diverse fields, includeing federal agencies, the food industry, health professionals, restaurants, software application developers, academia and research organizations, international organizations, and foreign governments ect. Therefore, consistent improvements of the database is important, so that people can better address such health challenges by providing reliable and accurate data.