• Title/Summary/Keyword: Statistical Database

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Food and Agriculture Statistics of the UN-FAO

  • Kim, Joo-Hwan
    • Communications for Statistical Applications and Methods
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    • v.10 no.1
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    • pp.39-48
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    • 2003
  • Quality in agriculture statistics at the international level is very important to all countries in the world. We investigate international organizations which produce worldwide agricultural statistics. The UN-FAO is one of the most important organization in agricultural statistics fields. We first introduce the Statistics division in FAO and present some considerations like production, reliability, quality of the agriculture data from my own experience as a consultant in FAO and Ministry of Agriculture and Forestry in Korea.

Identification of Implementation Strategy by Practical Interpretations of Significance Level, Significance Probability, and Known Parameters in Statistical Inferences (통계적 추론에서 유의수준, 유의확률과 모수기지의 실무적 해석에 의한 적용방안)

  • Choe, Seong-Un
    • Proceedings of the Safety Management and Science Conference
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    • 2012.04a
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    • pp.75-80
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    • 2012
  • The research presents a guideline for quality practitioners to provide a full comprehension of differences in theoretical and practical interpretations of assumed sampling errors of and significance probability of calculated p-value. Besides, the study recommends the use of statistical inferences methods with known parameters to identify the improvement effects. In practice, the quality practitioners obtain the known parameters through systematic quality Database (DB) activities.

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Improvement of Historical-Hanja Recognition Using a Nonlinear Transform of Contour Directional Feature Vectors

  • Kim, Min Soo;Kim, Jin Hyung
    • Communications for Statistical Applications and Methods
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    • v.11 no.3
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    • pp.503-511
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    • 2004
  • In Korea, OCR-based techniques have been developed for digital library construction of historical documents. In this paper, we propose the nonlinear transform of contour directional feature (CDF) vectors using log it and power transforms with skewness criterion to enhance the discriminant power. Experiments were conducted using samples from Seung-jung-won diaries (Diaries of King's Secretaries). Our results show that proposed method outperforms the others like Box-Cox transform in this database.

A Statistical Estimation of The Universal Constants Using A Simulation Predictor

  • Park, Jeong-Soo-
    • Proceedings of the Korea Society for Simulation Conference
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    • 1992.10a
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    • pp.6-6
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    • 1992
  • This work deals with nonlinear least squares method for estimating unknown universial constants C in a computer simulation code real experimental data(or database) and computer simulation data. The best linear unbiased predictor based on a spatial statistical model is fitted from the computer simulation data. Then nonlinear least squares estimation method is applied to the real data using the fitted prediction model(or simulation predictor) as if it were the true simulation model. An application to the computational nuclear fusion device is presented.

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Excavation Mechanism of Roadheader and Statistical Analysis of its Key Design Parameters Based on Database (로드헤더의 굴착 원리와 데이터베이스를 활용한 로드헤더 핵심 설계 항목의 통계분석)

  • Park, Young-Taek;Choi, Soon-Wook;Park, Jae-Hyun;Lee, Chul-Ho;Chang, Soo-Ho
    • Tunnel and Underground Space
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    • v.23 no.5
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    • pp.428-441
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    • 2013
  • Nowadays, a roadheader as a mechanical excavator is in high demand, especially for mines under various conditions and tunnels where TBMs are inapplicable. However, the records of roadheaders in Korea are seldom reported. Moreover, the number of countries with their intrinsic design and manufacturing technologies of roadheaders is very limited. Therefore, this study aimed to analyse the excavation principles of roadheader as well as its key design parameters for its optimized selection and design. In addition, the database with 143 world-widely collected roadheader design data was built, and a few statistical correlations were derived from it. A schematic procedure for roadheader design based on the database was also proposed.

Software for Nutritional Assessment Using a Semi-Quantitative Food Frequency Questionnaire and the 24-hour Recall Method (반 정량 식품빈도 조사법 (SQFFQ)과 24시간 회상법을 이용한 영양평가 Software 개발)

  • 이상아;이경신;김형숙;이해정;최혜미
    • Korean Journal of Community Nutrition
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    • v.7 no.4
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    • pp.548-558
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    • 2002
  • The purpose of this study was to develop a computer software program for nutritional assessment using a Semi-Quantitative Food Frequency Questionnaire (SQFFQs) and the 24-hour Recall Method. The software for the SQFFQ was divided into input, output, and database. For dietary analyses, recipe and food databases were used. The recipe database included 25 items and the food database was divided into 18 food groups. The food database was composed of 19 general nutrient items, 33 fatty acids, and 18 amino acids. The software developed in this study can be summarized as follows: 1) input items related to the individual s ages information, lifestyle, biological values, and dietary habits; 2) individualized data in percent of the Korean RDA, the energy ratios of carbohydrates, proteins and fats, the ratio of animal to plant source intakes, and the distribution of food group intakes; 3) Statistical data on the individual's information, lifestyle, biological values, and dietary intakes including the frequency of intake of cooked foods, the amounts of food, and the number of food groups, and nutrients. In the 24-hour Recall Method, the input and output consisted of the individual s information and cooked dish intakes. The individual s report included the amounts of nutrient intake according to number of meal and days, in comparison to the Korean RDA, the energy ratio for carbohydrates, proteins and fats, the ratio of animal to plant source intakes, and the distribution of food group intakes. The statistical report presented the number of food groups and foods, and the nutrient intakes. To evaluate the validity of the SQFFQ, the Spearman Rank Order Correlation and kappa values were used. As a result, correlation coefficients comparing the 24-hour Recall Method appeared to be more than 0.5, except for vitamin $B_1, B_2$, niacin, and vitamin E. The kappa values for energy and carbohydrate intakes were both 0.7, and protein, fat, vitamin C, folate, Ca, and iron intakes ranged from 0.3 to 0.7.

APPLICATION AND CROSS-VALIDATION OF SPATIAL LOGISTIC MULTIPLE REGRESSION FOR LANDSLIDE SUSCEPTIBILITY ANALYSIS

  • LEE SARO
    • Proceedings of the KSRS Conference
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    • 2004.10a
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    • pp.302-305
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    • 2004
  • The aim of this study is to apply and crossvalidate a spatial logistic multiple-regression model at Boun, Korea, using a Geographic Information System (GIS). Landslide locations in the Boun area were identified by interpretation of aerial photographs and field surveys. Maps of the topography, soil type, forest cover, geology, and land-use were constructed from a spatial database. The factors that influence landslide occurrence, such as slope, aspect, and curvature of topography, were calculated from the topographic database. Texture, material, drainage, and effective soil thickness were extracted from the soil database, and type, diameter, and density of forest were extracted from the forest database. Lithology was extracted from the geological database and land-use was classified from the Landsat TM image satellite image. Landslide susceptibility was analyzed using landslide-occurrence factors by logistic multiple-regression methods. For validation and cross-validation, the result of the analysis was applied both to the study area, Boun, and another area, Youngin, Korea. The validation and cross-validation results showed satisfactory agreement between the susceptibility map and the existing data with respect to landslide locations. The GIS was used to analyze the vast amount of data efficiently, and statistical programs were used to maintain specificity and accuracy.

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Development of new on-line statistical program for the Korean Society for Radiation Oncology

  • Song, Si Yeol;Ahn, Seung Do;Chung, Weon Kuu;Shin, Kyung Hwan;Choi, Eun Kyung;Cho, Kwan Ho
    • Radiation Oncology Journal
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    • v.33 no.2
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    • pp.142-148
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    • 2015
  • Purpose: To develop new on-line statistical program for the Korean Society for Radiation Oncology (KOSRO) to collect and extract medical data in radiation oncology more efficiently. Materials and Methods: The statistical program is a web-based program. The directory was placed in a sub-folder of the homepage of KOSRO and its web address is http://www.kosro.or.kr/asda. The operating systems server is Linux and the webserver is the Apache HTTP server. For database (DB) server, MySQL is adopted and dedicated scripting language is the PHP. Each ID and password are controlled independently and all screen pages for data input or analysis are made to be friendly to users. Scroll-down menu is actively used for the convenience of user and the consistence of data analysis. Results: Year of data is one of top categories and main topics include human resource, equipment, clinical statistics, specialized treatment and research achievement. Each topic or category has several subcategorized topics. Real-time on-line report of analysis is produced immediately after entering each data and the administrator is able to monitor status of data input of each hospital. Backup of data as spread sheets can be accessed by the administrator and be used for academic works by any members of the KOSRO. Conclusion: The new on-line statistical program was developed to collect data from nationwide departments of radiation oncology. Intuitive screen and consistent input structure are expected to promote entering data of member hospitals and annual statistics should be a cornerstone of advance in radiation oncology.

Questionnaire Survey and Analysis Using Data Mining (데이터마이닝을 이용한 설문조사 및 분석)

  • 박만희;채화성;신완선
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.25 no.5
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    • pp.46-52
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    • 2002
  • Today's database system needs to collect huge amount of questionnaire that results from development of the information technology by the internet, so it has to be administrable. However, there are many difficulties concerned with finding analytic data or useful information in the high capacity-database. Data mining can solve these problems and utilize the database. Questionnaire analysis that uses data mining has drawn relevant patterns that did not look or was tended to overlook before. These patterns can be applied by a new business rule. The purpose of this research is to analyze the questionnaire results and to present the result that can help to make decision easily with data mining. Recognition and analysis about these techniques of data mining show suitable type of questionnaire survey. This research focus on the form of present composition and the model of suitable questionnaire to analyze the type of it. Also, the comparison between the actual questionnaire result and the conventional statistical analysis is examined.

Shear strength prediction for SFRC and UHPC beams using a Bayesian approach

  • Cho, Hae-Chang;Park, Min-Kook;Hwang, Jin-Ha;Kang, Won-Hee;Kim, Kang Su
    • Structural Engineering and Mechanics
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    • v.74 no.4
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    • pp.503-514
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    • 2020
  • This study proposes prediction models for the shear strength of steel fiber reinforced concrete (SFRC) and ultra-high-performance fiber reinforced concrete (UHPC) beams using a Bayesian parameter estimation approach and a collected experimental database. Previous researchers had already proposed shear strength prediction models for SFRC and UHPC beams, but their performances were limited in terms of their prediction accuracies and the applicability to UHPC beams. Therefore, this study adopted a statistical approach based on a collected database to develop prediction models. In the database, 89 and 37 experimental data for SFRC and UHPC beams without stirrups were collected, respectively, and the proposed equations were developed using the Bayesian parameter estimation approach. The proposed models have a simplified form with important parameters, and in comparison to the existing prediction models, provide unbiased high prediction accuracy.