• 제목/요약/키워드: Statistic Technique

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An Analysis of Marketing and Industrial Structure in Meat Processing Products (육가공품(肉加工品)의 유통(流通) 및 산업구조(産業構造) 분석(分析))

  • Kim, Chul Ho;Cho, Gyeong Ran
    • Korean Journal of Agricultural Science
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    • v.15 no.2
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    • pp.164-173
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    • 1988
  • This study is to analyse marketing and industrial structure of meat processing industry and to examine it's current situation related to agriculture. For this purpose 1. This paper surveys the history of meat processing industry, and analyses current situation of meat processing industry, based upon economic statistic data. 2. For the research of marketing structure of meat processing products, this paper not only ciassifies into three catagories; the supply of raw meat, main marketing organization, and path, but measures magnitude of Marketing Bill and Farmer's Share practically through statistic data and an on-the-spot survey. 3. This study also attempt to explain the relation of meat processing industry and the other industry and role of meat processing industry is Korean economy by the use of input-output table. The results of the study are as follows; 1. The meat processing industry in Korea produces low quality, and expensive raw meat with limited quality, inefficiency of marketing structure, and unrelated livestock and meat processing industry. 2. Korea market structure of meat processing products has been changed into oligopoly from monopoly by a new corporation entered into monopoly and the size of meat processing market firms has been normalized. 3. Meat processing industry is very important considering with its high back-linkage-effect. In order to develop meat processing industry and marketing, it is essential that operation of intergrated meat market center, meat market center should be efficiently operated. The efficient utilization of domestic resource for raw meat and development of processing technique have to be required, by means of the governmental support.

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Comparison of several criteria for ordering independent components (독립성분의 순서화 방법 비교)

  • Choi, Eunbin;Cho, Sulim;Park, Mira
    • The Korean Journal of Applied Statistics
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    • v.30 no.6
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    • pp.889-899
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    • 2017
  • Independent component analysis is a multivariate approach to separate mixed signals into original signals. It is the most widely used method of blind source separation technique. ICA uses linear transformations such as principal component analysis and factor analysis, but differs in that ICA requires statistical independence and non-Gaussian assumptions of original signals. PCA have a natural ordering based on cumulative proportion of explained variance; howerver, ICA algorithms cannot identify the unique optimal ordering of the components. It is meaningful to set order because major components can be used for further analysis such as clustering and low-dimensional graphs. In this paper, we compare the performance of several criteria to determine the order of the components. Kurtosis, absolute value of kurtosis, negentropy, Kolmogorov-Smirnov statistic and sum of squared coefficients are considered. The criteria are evaluated by their ability to classify known groups. Two types of data are analyzed for illustration.

Prediction of Rainfall-Induced Slope Failure Using Hotelling's T-Square Statistic (Hotelling의 T-square 통계량을 이용한 강우유발 사면붕괴 예측)

  • Kim, Seul-Bi;Na, Jong-Hwa;Seo, Yong-Seok
    • The Journal of Engineering Geology
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    • v.25 no.3
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    • pp.331-337
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    • 2015
  • A new technique is presented to detect unstable slope behavior, based on Hotelling's T2 analysis of pore pressure and water content obtained during flume tests using granitic and gneissic weathered soils. Three sets of pore pressure-water content values were simultaneously obtained during each test, and T2 statistics at the 90.0% and 95.0% confidence levels were calculated based on the correlations between values. The results show that unsuccessful detection of some local failures of the flume slope depended on the sensor position. In the case of global slope failures, anomalous behavior was detected between several hundred and several thousand seconds before the event as T2 statistics exceeded the confidence interval 90%. Hotelling's T2 analysis provides a single control criterion because it enables correlations between diverse measured values within the same slope; the criterion also includes stepwise criteria for a forecasting and warning system based on confidence levels.

A sampling design for e-learning industry status survey on the business demand sector (이러닝수요부문 사업체실태조사를 위한 표본설계)

  • Kim, Hea-Jung;Kwak, Hwa-Ryun
    • Journal of the Korean Data and Information Science Society
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    • v.24 no.4
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    • pp.701-712
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    • 2013
  • The e-learning industry status survey statistic provides information about the actual conditions of supply and demand of the e-learning industries. NIPA (National IT Industry Promotion Agency) has published the annual report of the survey results since 2004. Due to the 9th version of the KSIC (Korean standard industrial classification) revised in 2008, a refinement of the sampling design for the survey becomes necessary, especially that for the business demand sector. This article, based on the 9th revision of the KSIC, constructs a stratification of the target population used for the e-learning industry status survey on the business demand sector. Classification of strata in the business population is based on the industrial type and employment scale of business. Under the stratified population, we design a sampling scheme by using the power allocation method that enables us to satisfy a target coefficient of variation of each industrial stratum. In order to secure an accurate survey results based on the proposed sampling design, we consider the problem of calculating the design weights, derivation of parameter estimators, and formulas of their standard errors.

Analysis of ABC Success Factors Affecting Construction Project Performance (건설프로젝트 성과에 영향을 미치는 ABC 성공요인 분석)

  • Shin, Young-Su;Cho, jin-Ho;Kim, Byung-Soo
    • Korean Journal of Construction Engineering and Management
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    • v.23 no.3
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    • pp.56-65
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    • 2022
  • This study tried to identify the key success factors of ABC by identifying the influence of ABC's success factors on project performance and analyzing the moderating effect of communication. For this purpose, factors applicable to construction projects were extracted through case studies related to the success factors of ABC, an activity-based financial management technique. The survey method was conducted as an online survey method using the Delphi method. For statistical analysis, frequency analysis and factor analysis were performed with SPSS Statistic 20, and hypothesis testing was performed with SmartPLS 2.0. As a result of the analysis, it was found that linkage with quality initiatives affects not only ABC's success factors on project performance, but also communication moderation effects. It was confirmed that linkage and communication with quality initiatives are the most important key success factors for ABC's success. Based on the results of this study, it is expected that if ABC and quality management are well linked, it will be effective in improving project performance.

Estimation of a Nationwide Statistics of Hernia Operation Applying Data Mining Technique to the National Health Insurance Database (데이터마이닝 기법을 이용한 건강보험공단의 수술 통계량 근사치 추정 -허니아 수술을 중심으로-)

  • Kang, Sung-Hong;Seo, Seok-Kyung;Yang, Yeong-Ja;Lee, Ae-Kyung;Bae, Jong-Myon
    • Journal of Preventive Medicine and Public Health
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    • v.39 no.5
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    • pp.433-437
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    • 2006
  • Objectives: The aim of this study is to develop a methodology for estimating a nationwide statistic for hernia operations with using the claim database of the Korea Health Insurance Cooperation (KHIC). Methods: According to the insurance claim procedures, the claim database was divided into the electronic data interchange database (EDI_DB) and the sheet database (Paper_DB). Although the EDI_DB has operation and management codes showing the facts and kinds of operations, the Paper_DB doesn't. Using the hernia matched management code in the EDI_DB, the cases of hernia surgery were extracted. For drawing the potential cases from the Paper_DB, which doesn't have the code, the predictive model was developed using the data mining technique called SEMMA. The claim sheets of the cases that showed a predictive probability of an operation over the threshold, as was decided by the ROC curve, were identified in order to get the positive predictive value as an index of usefulness for the predictive model. Results: Of the claim databases in 2004, 14,386 cases had hernia related management codes with using the EDI system. For fitting the models with applying the data mining technique, logistic regression was chosen rather than the neural network method or the decision tree method. From the Paper_DB, 1,019 cases were extracted as potential cases. Direct review of the sheets of the extracted cases showed that the positive predictive value was 95.3%. Conclusions: The results suggested that applying the data mining technique to the claim database in the KHIC for estimating the nationwide surgical statistics would be useful from the aspect of execution and cost-effectiveness.

Goodness of Fit Testing for Exponential Distribution in Step-Stress Accelerated Life Testing (계단충격가속수명시험에서의 지수분포에 대한 적합도검정)

  • Jo, Geon-Ho
    • Journal of the Korean Data and Information Science Society
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    • v.5 no.2
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    • pp.75-85
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    • 1994
  • In this paper, I introduce the goodness-of-fit test statistics for exponential distribution using accelerated life test data. The ALT lifetime data were obtained by assuming step-stress ALT model, specially TRV model introduced by DeGroot and Goel(1979). The critical values are obtained for proposed test statistics, Kolmogorov-Smirnov, Kuiper, Watson, Cramer-von Mises, Anderson-Darling type, under various sample sizes and significance levels. The powers of the five test statistic are compared through Monte-Cairo simulation technique.

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Predicting Exchange Rates with Modified Elman Network (수정된 엘만신경망을 이용한 외환 예측)

  • Beum-Jo Park
    • Journal of Intelligence and Information Systems
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    • v.3 no.1
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    • pp.47-68
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    • 1997
  • This paper discusses a method of modified Elman network(1990) for nonlinear predictions and its a, pp.ication to forecasting daily exchange rate returns. The method consists of two stages that take advantages of both time domain filter and modified feedback networks. The first stage straightforwardly employs the filtering technique to remove extreme noise. In the second stage neural networks are designed to take the feedback from both hidden-layer units and the deviation of outputs from target values during learning. This combined feedback can be exploited to transfer unconsidered information on errors into the network system and, consequently, would improve predictions. The method a, pp.ars to dominate linear ARMA models and standard dynamic neural networks in one-step-ahead forecasting exchange rate returns.

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An Experimental Study on the Compressive Strength Deviation of Concrete With Different Consolidation Methods (다짐 방법에 따른 콘크리트 압축강도 편차에 관한 실험적 연구)

  • Seo, Il;Jun, Woo-Chul;Park, Hee-Gon;Lee, Hyun-Seok;Lee, Jae-Sam;Lee, Han-Seung
    • Proceedings of the Korean Institute of Building Construction Conference
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    • 2011.11a
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    • pp.77-78
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    • 2011
  • This paper presents a basic study which is to develop concrete cylinder moulds for a proficiency testing compressive strength of concrete among laboratories accredited Korea Laboratory Accreditation Scheme(KOLAS). The concrete cylinder moulds sufficiently have homogeneity for a proficiency testing which is a means of assessing the ability of laboratories to competently perform specific test and measurements. The concrete compressive strength specimens placed different consolidation methods were analyzed by a statistic technique. The methods of consolidation are rodding, and internal or external vibration.

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Control Charts Based on Self-critical Estimation Process

  • Won, Hyung-Gyoo
    • Journal of Korean Society for Quality Management
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    • v.25 no.1
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    • pp.100-115
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    • 1997
  • Shewhart control chart is a basic technique to monitor the state of a process. We observe samples of size four or five and plot some statistic(e.g., mean or range) of each sample on the chart. When setting up the chart, we need to obtain u, pp.r and lower control limits. It is common practice that those limits are calculated from the preliminary 20-40 samples presumed to be homogeneous. However, it may ha, pp.n in practice that the samples are contaminated by outlying observations caused by various reasons. The presence of outlying observations make the control limits wider and hence decrease the sensitivity of the charts. In this paper, we introduce robust control charts with tighter control limits when outlying observations are present in the preliminary samples. Examples will be given via simulation study.

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