• 제목/요약/키워드: Statistical Technique

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규제 순응도와 산업재해 발생 수준간의 관계 분석 - 로지스틱 회귀분석과 포아송 회귀분석을 중심으로 - (Analysis of the relationship between regulation compliance and occupational injuries - Focusing on logistic and poisson regression analysis -)

  • 이경용;김기식;윤영식
    • 대한안전경영과학회지
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    • 제15권2호
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    • pp.9-20
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    • 2013
  • OSHA(Occupational Safety and Health Act) generally regulates employer's business principles in the workplace to maintain safety environment. This act has the fundamental purpose to protect employee's safety and health in the workplace by reducing industrial accidents. Authors tried to investigate the correlation between 'occupational injuries and illnesses' and level of regulation compliance using Survey on Current Status of Occupational Safety & Health data by the various statistical methods, such as generalized regression analysis, logistic regression analysis and poison regression analysis in order to compare the results of those methods. The results have shown that the significant affecting compliance factors were different among those statistical methods. This means that specific interpretation should be considered based on each statistical method. In the future, relevant statistical technique will be developed considering the distribution type of occupational injuries.

Optimization and investigations of low-velocity bending impact of thin-walled beams

  • Hossein Taghipoor;Mahdi Sefidi
    • Steel and Composite Structures
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    • 제50권2호
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    • pp.159-181
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    • 2024
  • In the present study, the effect of geometrical parameters of two different types of aluminum thin-walled structures on energy absorption under three-bending impact loading has been investigated experimentally and numerically. To evaluate the effect of parameters on the specific energy absorption (SEA), initial peak crushing force (IPCF), and the maximum crushing distance (δ), a design of experiment technique (DOE) with response surface method (RSM) was applied. Four different thin-walled structures have been tested under the low-velocity impact, and then they have simulated by ABAQUS software. An acceptable consistency between the numerical and experimental results was obtained. In this study, statistical analysis has been performed on various parameters of three different types of tubes. In the first and the second statistical analysis, the dimensional parameters of the cross-section, the number of holes, and the dimensional parameter of holes were considered as the design variables. The diameter reduction rate and the number of sections with different diameters are related to the third statistical analysis. All design points of the statistical method have been simulated by the finite element package, ABAQUS/Explicit. The final result shows that the height and thickness of tubes were more effective than other geometrical parameters, and despite the fact that the deformations of the cylindrical tubes were around forty percent greater than the rectangular tubes, the top desirability was relevant to the cylindrical tubes with reduced cross-sections.

신 스플라인보간법의 퍼포먼스 가설점정 (Hypothesis Tests For Performances of a New Spline Interpolation Technique)

  • 유기윤
    • 대한공간정보학회지
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    • 제7권1호
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    • pp.29-40
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    • 1999
  • 벡터 GIS에서 자연선형체는 통상 일련의 직선분(line segments)에 의해 표시되나 그 대안으로 곡선분(curve segments) 역시 사용될 수 있다. 곡선분은 스플라인보간법에 의해 생성가능하며 이를 위해 Bezier방법과 신보간법(유기윤, 1998)이 사용될 수 있는데 본 연구에서는 신보간법의 퍼포먼스를 테스트해 보았다. 테스트는 두 가지에 촛점을 두었는데 (1) 새보간법에 의해 생성된 선형분이 직선분 보다 정확하게 자연선형체를 표현할 수 있는지 여부와 (2) 새보간법에 의해 생성된 선형분이 Bezier방법에 의해 생성된 선형분 보다 자연선형체를 정확하게 표현할 수 있는지 여부에 대한 검정이다. 이를 위해 t-테스트에 의한 가설검정법이 이용되었으며 자료로는 미 지질조사국의 7.5분 지형도가 이용되었다. 테스트결과 새보간법과 Bezier방법에 의해 생성된 선형분이 직선분 보다 자연선 형체를 정확하게 표현하였으며 새보간법에 의해 생성된 선형분이 Bezier방법에 의해 생성된 선형분보다 정확하게 표현하였다.

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Artificial neural network algorithm comparison for exchange rate prediction

  • Shin, Noo Ri;Yun, Dai Yeol;Hwang, Chi-gon
    • International Journal of Internet, Broadcasting and Communication
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    • 제12권3호
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    • pp.125-130
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    • 2020
  • At the end of 1997, the volatility of the exchange rate intensified as the nation's exchange rate system was converted into a free-floating exchange rate system. As a result, managing the exchange rate is becoming a very important task, and the need for forecasting the exchange rate is growing. The exchange rate prediction model using the existing exchange rate prediction method, statistical technique, cannot find a nonlinear pattern of the time series variable, and it is difficult to analyze the time series with the variability cluster phenomenon. And as the number of variables to be analyzed increases, the number of parameters to be estimated increases, and it is not easy to interpret the meaning of the estimated coefficients. Accordingly, the exchange rate prediction model using artificial neural network, rather than statistical technique, is presented. Using DNN, which is the basis of deep learning among artificial neural networks, and LSTM, a recurrent neural network model, the number of hidden layers, neurons, and activation function changes of each model found the optimal exchange rate prediction model. The study found that although there were model differences, LSTM models performed better than DNN models and performed best when the activation function was Tanh.

직류전위차법 자료에 대한 통계적 자료분석 (Statistical analysis of direct current potential drop data)

  • 이정희;이우동
    • Journal of the Korean Data and Information Science Society
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    • 제21권1호
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    • pp.139-146
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    • 2010
  • 비파괴검사방법 중 직류전위차법은 표면균열 측정에 유효한 수단으로 알려져 있다. 이차원 표면 균열을 가진 시험편에서 전류입출력점사이의 거리가 직류전위차에 미치는 영향을 알아보는 실험을 실시하여 자료를 얻었다. 이 자료로부터 전위차 값은 일정 전위차계측점사이의 거리에 있어 전류입출력점사이의 거리가 증가함에 따라 반비례적으로 감소하고, 노치의 길이에 비례하고 있었다. 이 실험에서 관찰된 자료를 통계적 모형에 적합시키고, 적합된 모형에서 전위차에 영향을 주는 유의한 변수를 알아보는 것은 비파괴검사에서 중요하다고 할 수 있다. 본 연구에서는 관찰된 자료를 적절하게 설명할 수 있는 통계적 모형을 제안하고, 제안된 모형에서 유의한 독립변수를 찾아보는 것이 목적이다.

작품 가격 추정을 위한 기계 학습 기법의 응용 및 가격 결정 요인 분석 (Price Determinant Factors of Artworks and Prediction Model Based on Machine Learning)

  • 장동률;박민재
    • 품질경영학회지
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    • 제47권4호
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    • pp.687-700
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    • 2019
  • Purpose: The purpose of this study is to investigate the interaction effects between price determinants of artworks. We expand the methodology in art market by applying machine learning techniques to estimate the price of artworks and compare linear regression and machine learning in terms of prediction accuracy. Methods: Moderated regression analysis was performed to verify the interaction effects of artistic characteristics on price. The moderating effects were studied by confirming the significance level of the interaction terms of the derived regression equation. In order to derive price estimation model, we use multiple linear regression analysis, which is a parametric statistical technique, and k-nearest neighbor (kNN) regression, which is a nonparametric statistical technique in machine learning methods. Results: Mostly, the influences of the price determinants of art are different according to the auction types and the artist 's reputation. However, the auction type did not control the influence of the genre of the work on the price. As a result of the analysis, the kNN regression was superior to the linear regression analysis based on the prediction accuracy. Conclusion: It provides a theoretical basis for the complexity that exists between pricing determinant factors of artworks. In addition, the nonparametric models and machine learning techniques as well as existing parameter models are implemented to estimate the artworks' price.

Developing a Molecular Prognostic Predictor of a Cancer based on a Small Sample

  • Kim Inyoung;Lee Sunho;Rha Sun Young;Kim Byungsoo
    • 한국통계학회:학술대회논문집
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    • 한국통계학회 2004년도 학술발표논문집
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    • pp.195-198
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    • 2004
  • One Important problem in a cancer microarray study is to identify a set of genes from which a molecular prognostic indicator can be developed. In parallel with this problem is to validate the chosen set of genes. We develop in this note a K-fold cross validation procedure by combining a 'pre-validation' technique and a bootstrap resampling procedure in the Cox regression . The pre-validation technique predicts the microarray predictor of a case without having seen the true class level of the case. It was suggested by Tibshirani and Efron (2002) to avoid the possible over-fitting in the regression in which a microarray based predictor is employed. The bootstrap resampling procedure for the Cox regression was proposed by Sauerbrei and Schumacher (1992) as a means of overcoming the instability of a stepwise selection procedure. We apply this K-fold cross validation to the microarray data of 92 gastric cancers of which the experiment was conducted at Cancer Metastasis Research Center, Yonsei University. We also share some of our experience on the 'false positive' result due to the information leak.

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단순화된 위성체의 통계적 에너지 해석법을 이용한 음향-진동 연성 해석 (Vibro-acoustic Analysis of Simplified Satellite Model by Using the Statistical Energy Analysis Technique)

  • 정철호;이정권;문상무;김홍배
    • 한국소음진동공학회:학술대회논문집
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    • 한국소음진동공학회 2002년도 추계학술대회논문집
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    • pp.711-714
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    • 2002
  • At the lift-off condition, the combustion and Jet noise of launch vehicle produces a severe acoustic environment and the acoustic loads may be damaging to paylaod and equipments. Prediction of the acoustic environment is thus needed to support the load-resistive design and test-qualification of components. Currently, such a high frequency problem is usually dealt with by using the SEA technique, for which the assumptions should match reasonably well with the vibro-acoustic condition of system. The subsystems of SEA model was composed of 16 flat plates, 8 L-shaped beams, and 2 acoustic cavities. The frequency range was 400 Hz - 4 kHz considering the modal parameter. The experiment was performed in a high intensity acoustic chamber, in which the diffuse acoustic field was assured. By comparing the SEA analysis and the experiments, the error less than 5 dB was observed.

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움직임 보상 보간 프레임에 대한 시공간적 통계특성에 기초한 블록기반의 신뢰도 평가 방법 (Reliability Evaluation Method Based on Spatio-Temporal Statistical Characteristics for Motion Compensated Interpolated Frame)

  • 김진수
    • 한국콘텐츠학회논문지
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    • 제13권5호
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    • pp.28-36
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    • 2013
  • 비디오 신호에서 움직임 보상 보간 기술은 다양한 응용 분야를 갖는다. 프레임율 증가 변환이나 분산 비디오 부호화 기술에서는 효과적인 움직임 보상 보간 알고리즘을 필요로 한다. 이러한 응용 분야에서는 움직임 보상 보간 프레임에 대한 효과적인 후처리 기술을 통하여 화질을 개선하거나 또는 가상 채널 잡음을 줄임으로써 채널 전송 비트율을 줄이기 위해 각 블록 단위의 신뢰도 측정이 요구된다. 본 논문에서는 움직임 보상 보간 블록에 대한 시공간적 통계특성에 기초한 블록 기반의 신뢰도 평가방법을 제안한다. 제안한 방법은 현재 보간 프레임의 시간적 정합척도를 조사하고, 이 결과를 시간적 통계특성 뿐만 아니라, 공간적 통계특성을 조사하는 방법으로 설계된다. 모의실험을 통하여 제안한 방식은 기존의 단순한 시간적 정합 비용에 의한 방식에 비해 우수한 성능을 보인다.

검사법의 일치도 평가를 위한 분석기법 (Statistical Test of Agreement between Measurements in Method-comparison Study)

  • 박선일;오태호
    • 한국임상수의학회지
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    • 제28권1호
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    • pp.108-112
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    • 2011
  • In clinical settings, researchers often want to assess agreement between two measurements (or tests) of the same continuous variable. For example, when new point-of-care analyzer for testing blood glucose level were introduced clinicians need to compare results from standard or established laboratory method of measurement to those of new or point-of-care analyzer. The question in a method-comparison study would either of two different methods be used to measure the same variable equivalently. In this paper common misuse of statistical methodologies seen in the medical literatures such as correlation coefficient and paired t-test are discussed. The Bland-Altman technique has been widely used for this purpose and provides a graphic in presentation of the findings from a method-comparison study, with a mean value of measurement, this bias and the limits of agreement. For ease of application and interpretation of this technique we discussed the analysis procedure and illustrated with two worked examples. Finally, a number of alternative ways in which data can be analysed and reported in such studies were reviewed.