• 한국운동역학회지
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• 제25권2호
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• pp.157-165
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• 2015

Object : The goals of this research were to make Performance Enhanced Model(PE) taken the largest performance index (PI) through artificial variation of principle components calculated by principle component analysis for trial data, and to verify the effect through comparing kinematic factors between trial data (Raw) and PE. Method : Ten subjects (5 men, 5 women) were recruited and 80% of their maximal record was considered. The PI is a regression equation. In order to develop PE, we extracted Principle components from trial position data (by Principle Components Analysis (PCA)). Before PCA, we made 17 position data to 3 row matrix according to components. We calculated 3 eigen value (principle components) through PCA. And except Y (medial-lateral direction) component (because motion of Y component is small), principle components of X (anterior-posterior direction) and Z (vertical direction) components were changed as following. Changed principle components = principle components + principle components ${\times}$ k. After changing the each principle component, we reconstructed position data using the changed principle components and calculated performance index (PI). A Paired t-test was used to compare Raw data and Performance Enhanced Model data. The level of statistical significance was set at $p{\leq}0.05$. Result : The PI was significantly increased about 12.9kg at PE ($101.92{\pm}6.25$) when compared to the Raw data ($91.29{\pm}7.10$). It means that performance can be increased by optimizing 3D positions. The difference of kinematic factors as follows : the movement distance of the bar from start to lock out was significantly larger (about 1cm) for PE, the width of anterior-posterior bar position in full phase was significantly wider (about 1.3cm) for PE and the horizontal displacement toward the weightlifter after beginning of descent from maximal height was significantly greater (about 0.4cm) for PE. Additionally, the minimum knee angle in the 2-pull phase was significantly smaller (approximately 2.7cm) for the PE compared to that of the Raw. PE was decided at proximal position from the Raw (origin point (0,0)) of PC variation). Conclusion : PI was decided at proximal position from the Raw (origin point (0,0)) of PC variation). This means that Performance Enhanced Model was decided by similar motion to the Raw without a great change. Therefore, weightlifters could be accept Performance Enhanced Model easily, comfortably and without large stress. The Performance Enhance Model can provide training direction for athletes to improve their weightlifting records.

• Journal of the Korean Statistical Society
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• 제29권2호
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• pp.231-245
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• 2000

This paper considers a linear regression model with space and time data in where the disturbances follow spatially correlated error components. We provide the best linear unbiased predictor for the one way error components. We provide the best linear unbiased predictor for the one way error component model with spatial autocorrelation. Further, we derive two diagnostic test statistics for the assessment of model specification due to spatial dependence and random effects as an application of the Lagrange Multiplier principle.

• 한국신뢰성학회지:신뢰성응용연구
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• 제16권2호
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• pp.98-103
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• 2016

Purpose: The purpose of this paper is to get a meaningful information for improving manufacturing quality of the products before they are produced in client's manufacturing process. Methods: A variety of data mining techniques have been being used for wide range of industries from process data in manufacturing factories for quality improvement. One application of those is to get meaningful information from process data in manufacturing factories for quality improvement. In this paper, the failure rate at client's manufacturing process is predicted by using the parameters of the characteristics of the product based on PCA (Principle Component Analysis) and regression analysis. Results: Through a case study, we proposed the predicting methodology and regression model. The proposed model is verified through comparing the failure rates of actual data and the estimated value. Conclusion: This study can provide the guidance for predicting the failure rate on the manufacturing process. And the manufacturers can prevent the defects by confirming the factor which affects the failure rate.

• 환경영향평가
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• 제23권3호
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• pp.187-196
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• 2014

The objective of this study is to evaluate and analyze Osu stream watershed water environment system. The data were collected from January 2009 to December 2011 including water temperature, pH, DO, EC, BOD, COD, TOC, SS, T-N, T-P and discharge. The data were used for principle component analysis and factor analysis. The results are as followes. The primary factors obtained from both the principal component analysis and the factor analysis were BOD, COD, TOC, SS and T-P. Once principal component analysis and factor analysis have been performed with the collected data and then the results will be applied to both simple regression model and multiple regression model. The regression model was developed into case 1 using concentrations of water quality parameters and case 2 using delivery loads. The value of the coefficient of determination on case 1 fell between 0.629 and 0.866; this was lower than case 2 value which fell between 0.946 and 0.998. Therefore, case 2 model would be a reliable choice.The coefficient of determination between the estimated figure using data which was developed to the regression model in 2012 and the actual measurement value was over 0.6, overall. It can be safely deduced that the correlation value between the two findings was high. The same model can be applied to get TOC concentrations in future.

• 정보처리학회논문지D
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• 제9D권1호
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• pp.75-80
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• 2002

Putnam은 소프트웨어 프로젝트에 참여하는 인력이 Rayleigh 분포를 따르는 SLIM 모델을 제시하였다. 이 모델에서 인력분포를 얻기 위해서는 총 개발노력과 개발 난이도를 추정해야 한다. 프로젝트 개발에 참여할 것인지 여부를 결정하기 위해서는 소프트웨어 생명주기의 초기단계에서 이 모수들을 보다 적확히 추정하는 것이 필요하다. Putnam은 시스템 속성들 중 강한 상관관계가 있는 변량을 제거하고 나머지 변량들만으로 총 개발노력과 개발 난이도를 추정하였다. 그러나 통계적 방법에 따라 변량들이 다르게 선택되며 모델의 성능에 차이가 발생한다. 본 논문은 Putnam 방법 대신 주성분분석을 이용하여 최적의 시스템 속성을 선택하였다. 모델의 성능분석 결과 주성분분석 방법이 Putnam의 방법보다 9.85% 성능향상을 보였다. 또한, 제안된 모델은 단순하고 쉽게 구현할 수 있다.

• 한국통신학회논문지
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• 제29권1C호
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• pp.65-71
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• 2004

본 논문은 주성분분석(PCA, Principle Component Analysis) 혹은 독립성분분석(ICA, Independent Principle Component Analysis)를 이용하여 HMM(Hidden Markov Model) 파라메타의 차수를 감소시킴으로써 MLLR(Maximum Likelihood Linear Regression) 화자 적응 알고리즘을 개선하였다. 데이터의 특징을 잘 나타내는 PCA와 ICA를 통해 모델 mixture component의 상관관계를 줄이고 상대적으로 데이터의 분포가 적은 축을 삭제함으로써 추정해야 하는 적응 파라메타의 수를 줄였다. 기존의 MLLR 알고리즘은 SI(Speaker Independent)모델 보다 좋은 인식성능을 나타내기 위해 30초 이상의 적응 데이터가 요구되었고, 반면 제안한 알고리즘은 적응 파라메타의 수를 감소시킴으로써 10초 이상의 적응데이터가 요구되었다. 또한, 36차의 HMM 파라메타는 기존의 MLLR 알고리즘과 비슷한 인식성능을 나다내는 10차의 주성분이나 독릭성분을 사용함으로써 MLLR 알고리즘에서 적응파라메타를 추정할 때 요구되는 연산량을 1/167로 감소시켰다.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2014년도 추계학술대회 논문집
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• pp.481-482
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• 2014

• Journal of Biosystems Engineering
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• 제29권6호
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• pp.539-543
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• 2004

The purpose of this study was to develop a real-time sensor for beef freshness. Contents of biogenic amines (BA), saccharides and proteins were highly related with freshness on the beef meats. Relations of those chemical contents and NIR spectra were studied. Tyramine showed the best correlation coefficient at 1250nm. Correlation between VBN (volatile basic nitrogen) and K value, which were both freshness measurement method, was determined by the PCR (principle component regression). The correlation model had the values of $R^2=0.989$ and SEC=1.78, respectively. The model was validated at $R^2=0.963$ and SEP=2.285, respectively.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.1343-1346
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• 2005

In the cold rolling mill, coil breakage that generated in rolling process makes the various types of troubles such as the degradation of productivity and the damage of equipment. Recent researches were done by the mechanical analysis such as the analysis of roll chattering or strip inclining and the prevention of breakage that detects the crack of coil. But they could cover some kind of breakages. The prediction of Coil breakage was very complicated and occurred rarely. We propose to build effective prediction modes for coil breakage in rolling process, based on data mining model. We proposed three prediction models for coil breakage: (1) decision tree based model, (2) regression based model and (3) neural network based model. To reduce model parameters, we selected important variables related to the occurrence of coil breakage from the attributes of coil setup by using the methods such as decision tree, variable selection and the choice of domain experts. We developed these prediction models and chose the best model among them using SEMMA process that proposed in SAS E-miner environment. We estimated model accuracy by scoring the prediction model with the posterior probability. We also have developed a software tool to analyze the data and generate the proposed prediction models either automatically and in a user-driven manner. It also has an effective visualization feature that is based on PCA (Principle Component Analysis).

• 한국산학기술학회논문지
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• 제13권9호
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• pp.3900-3914
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• 2012

본 연구에서는 미국발 금융위기의 근본 원인과 국내,외 금융시장에서 관심의 대상이 되고 있는 장외파생상품의 일종인 신용부도스왑(Credit Default Swap, CDS) 혹은 합성부채담보부채권에 대한 내용을 사전적으로 분석하였다. 2007년부터 문제화가 되기 시작한 미국발 금융위기의 근본 배경으로서, 2000년부터 2008년 초까지 약 5배나 급속히 상승한 국제유가 요인 등이 동 위기의 기조원인으로서 분석되었다. 기존의 국내기업 관련 CDS 스프레드 분석연구결과 등과 비교하여(예: Park & Kim, 2011), 본 연구에서는 일반성(commonality)과 견고성(robustness)의 제고를 위하여, 해당 실증적 방법론과 변수들(즉, 산업별 더미변수들 포함한 총 18가지의 설명변수들과 종속변수들(3가지))의 활용에서도, 더욱 포괄적이고 심층적인 분석을 수행하고자 하였다. 결과와 관련하여, 종속변수인 CDS 스프레드의 재무적 특성 혹은 결정요인으로서, 4가지 설명변수들 (무위험수익률, 이자율의 기간구조, 자산의 크기, 변동성)이 다중회귀모형을 통하여 각각의 통계적인 유의성(5% 신뢰수준)을 나타낸 반면, 추가적인 설명변수의 발견을 위하여 주성분분석을 사용한 결과, 5가지 변수들(체계적 위험(베타), 수익성, 매출액 성장성, 변동성, 장부상 부채비욜)이 CDS 스프레드에 대한 유의성을 보였다. 상기 결과들의 robustness 제고를 위하여, 사용된 총 18가지의 설명변수를 종합적으로 활용한 '단계적 회귀식(stepwise regression)'의 결과에서는 CDS스프레드의 대용치인 모든 종속변수에서, 다음의 4가지 설명변수들이 결정요인으로서 발견되었다: 무위험수익률, 이자율의 기간구조, 변동성, 체계적 위험(베타). 또한, 산업별 유의성 관련, 수출주도형 산업으로 분류되는 자동차산업과 철강산업은 종속변수와 음(-)의 상관관계를 나타낸 반면, 내수업종인 통신서비스업종은 양(+)의 유의성을 보였다.