• 대한교통학회지
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• 제25권5호
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• pp.135-148
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• 2007

교통사고의 특성과 사고에 대한 지속시간 사이의 관계에 대한 이해는 사고의 효과적인 대응과 사고에 의한 혼잡을 감소시키는데 핵심 요소가 된다. 때문에 본 연구의 목적은 AFT metric 모형을 적용한 사고 지속시간을 분석하는 것이다. 비록 로그 로지스틱 및 로그 정규 AFT 모형이 통계적 이론과 기존 연구 사례를 기반으로 선정되었으나, 로그 로지스틱 모형이 보다 우수하게 추정되었다. AFT 모형은 예측 목적으로도 널리 사용되기 때문에, 추정된 모형은 사고 발생시 사고 관련 기본 정보 접수 즉시 고속도에서의 사고 지속시간 예측에 사용될 수 있다. 결과적으로, 예측된 사고 지속시간 정보는 사고를 처리하기 위한 제반 의사 결정에 도움을 줄 뿐 아니라 교통 혼잡의 감소 및 추가 사상자의 감소로 그 효과가 이어질 것으로 판단된다.

• 한국군사과학기술학회지
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• 제26권3호
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• pp.234-245
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• 2023

The Arena Fragmentation Test(AFT) is designed to analyze warhead performance by measuring fragmentation data. In order to evaluate the results of the AFT, a set of AFT images are captured by high-speed cameras. To detect objects in the AFT image set, ResNet-50 based Faster R-CNN is used as a detection model. However, because of the low resolution of the AFT image set, a detection model has shown low performance. To enhance the performance of the detection model, Super-resolution(SR) methods are used to increase the AFT image set resolution. To this end, The Bicubic method and three SR models: ZSSR, EDSR, and SwinIR are used. The use of SR images results in an increase in the performance of the detection model. While the increase in the number of pixels representing a fragment flame in the AFT images improves the Recall performance of the detection model, the number of pixels representing noise also increases, leading to a slight decreases in Precision performance. Consequently, the F1 score is increased by up to 9 %, demonstrating the effectiveness of SR in enhancing the performance of the detection model.

• 응용통계연구
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• 제34권3호
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• pp.411-425
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• 2021

가속화 실패시간모형은 로그 생존시간과 공변량간의 선형적 관계를 묘사해 준다. 가속화 실패시간모형에서 생존시간의 평균뿐만 아니라 변동성에도 영향을 미치는 공변량 효과를 추론하는 것은 흥미가 있다. 이를 위해 생존시간의 평균뿐만 아니라 분산을 모형화 하는 것이 필요하며, 이러한 모형을 평균-분산 가속화 실패시간모형이라 부른다. 본 논문에서는 벌점 가능도함수를 이용하여 평균-분산 가속화 실패시간모형에서 회귀모수에 대한 변수선택 절차를 제안한다. 여기서 벌점함수로서 LASSO, ALASSO, SCAD 그리고 HL (계층가능도)와 같은 네 가지 벌점함수를 연구한다. 제안된 변수선택 절차를 통해 중요한 공변량의 선택 뿐만 아니라 회귀모수의 추정을 동시에 제공할 수 있다. 제안된 방법의 성능은 모의실험을 통해 평가하고, 하나의 임상 예제자료를 통해 제안된 방법을 예증하고자 한다.

• Communications for Statistical Applications and Methods
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• 제25권6호
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• pp.591-604
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• 2018

The accelerated failure time (AFT) model is a linear model under the log-transformation of survival time that has been introduced as a useful alternative to the proportional hazards (PH) model. In this paper we propose variable-selection procedures of fixed effects in a parametric AFT model using penalized likelihood approaches. We use three popular penalty functions, least absolute shrinkage and selection operator (LASSO), adaptive LASSO and smoothly clipped absolute deviation (SCAD). With these procedures we can select important variables and estimate the fixed effects at the same time. The performance of the proposed method is evaluated using simulation studies, including the investigation of impact of misspecifying the assumed distribution. The proposed method is illustrated with a primary biliary cirrhosis (PBC) data set.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2009년도 추계학술대회 논문집
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• pp.656-660
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• 2009

Various dynamic models of seated posture human body have been developed because the importance about the ride comfort assessment of vehicles is highly emphasized from day to day. The dynamic models of human body make possible the simulation of ride comfort assessment by applied to the vehicle dynamic model. Recently, the importance of ride comfort is also regarded to working vehicles such as excavators and the research of the ride comfort assessment for working vehicle is required. Only vertical vibration dominantly occurs on the seat of the private car driving with constant velocity. In contrast, vertical/fore-and-aft/pitch vibration seriously occurs on the seat of the working excavator. So, the dynamic models of seated human body applied to working vehicles should describe the dynamic characteristics for vertical/fore-and-aft/pitch direction. In this paper, the dynamic characteristics of seated human body are represented as apparent inertia matrix. The apparent inertia matrix is obtained by the vertical/fore-and-aft/pitch excitation of seated human body. 6 resonance frequencies are observed in apparent inertia matrix. This result can be applied to develop the dynamic model for seated posture human body.

• Genomics & Informatics
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• 제14권4호
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• pp.166-172
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• 2016

Although a large number of genetic variants have been identified to be associated with common diseases through genome-wide association studies, there still exits limitations in explaining the missing heritability. One approach to solving this missing heritability problem is to investigate gene-gene interactions, rather than a single-locus approach. For gene-gene interaction analysis, the multifactor dimensionality reduction (MDR) method has been widely applied, since the constructive induction algorithm of MDR efficiently reduces high-order dimensions into one dimension by classifying multi-level genotypes into high- and low-risk groups. The MDR method has been extended to various phenotypes and has been improved to provide a significance test for gene-gene interactions. In this paper, we propose a simple method, called accelerated failure time (AFT) UM-MDR, in which the idea of a unified model-based MDR is extended to the survival phenotype by incorporating AFT-MDR into the classification step. The proposed AFT UM-MDR method is compared with AFT-MDR through simulation studies, and a short discussion is given.

• 대한산업공학회지
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• 제40권3호
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• pp.283-290
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• 2014

In the flat panel display industry, to meet production target quantities and the deadline of production, the scheduler and dispatching systems are major production management systems which control the order of facility production and the distribution of WIP (Work In Process). Especially the delivery time is a key factor of the dispatching system for the time when a lot can be supplied to the facility. In this paper, we use survival analysis methods to identify main factors of the delivery time and to build the delivery time forecasting model. To select important explanatory variables, the cox proportional hazard model is used to. To make a prediction model, the accelerated failure time (AFT) model was used. Performance comparisons were conducted with two other models, which are the technical statistics model based on transfer history and the linear regression model using same explanatory variables with AFT model. As a result, the mean square error (MSE) criteria, the AFT model decreased by 33.8% compared to the statistics prediction model, decreased by 5.3% compared to the linear regression model. This survival analysis approach is applicable to implementing the delivery time estimator in display manufacturing. And it can contribute to improve the productivity and reliability of production management system.

• Journal of the Korean Data and Information Science Society
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• 제25권5호
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• pp.1057-1067
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• 2014

인간게놈 프로젝트 이후 질병과 연관된 변이유전자를 탐색하기 위해 유전형질의 차이에 영향을 주는 단일 유전자를 중심으로 전장유전체 연관성 연구가 활발하게 진행되어왔다. 그러나 전장유전체 연관성 연구에서 접근한 단일유전자 분석방법에 한계점이 발견되면서 최근에는 다중유전자 분석방법이나 유전자-유전자간의 상호작용에 대한 연구들이 활발하게 진행 중이다. 이 중 다중차원축소방법은 유전자-유전자간의 상호작용의 연관성을 찾아내기 위하여 고차원을 일차원으로 축소하는 방법으로 이진형 반응변수를 기반으로 크게 활용되고 있다. 본 논문에서는 이 방법을 생존시간으로 확장하여 생존시간과 연관된 유전자-유전자간의 상호작용을 찾아내는 방법을 제안하고자 한다. 구체적으로 가속화 고장시간 회귀모형 하에서 표준화잔차 스코어를 분류기준으로 사용하여 다중차원축소방법을 적용하는 방법으로 AFT-MDR이라고 지칭하였다. 시뮬레이션 연구를 통하여 기존에 제안된 Surv-MDR과 Cox-MDR과의 검정력을 비교하였으며 국내의 백혈병환자 자료분석에 적용하였다. 시뮬레이션 결과로부터 AFT-MDR은 유전율이 높을수록 검정력이 커지며 회귀모형에 기반하여 공변량의 효과를 고려할 수 있다는 장점이 있으나 센서링 비율이 높아지면서 검정력이 매우 떨어진다는 단점이 발견되었다. 따라서 이를 보완하기 위한 추후연구의 필요성이 요구된다.

• 대한안전경영과학회지
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• 제17권2호
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• pp.241-247
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• 2015

The purpose of the warranty data analysis can be classified into two categories. Two goals is a failure cause analysis and life prediction analysis. In this paper first, we applied multivariate analysis method that can be estimated in consideration of various factors on the failure cause warranty data. In particular, we apply the Tree model and Cox model. The advantage of the Tree is easy to interpret this result as compared to other models. In addition Cox model can quantitatively express the risk. Second, this paper proposed a multivariate life prediction model (AFT) considering a variety of factors. By applying the actual warranty data confirmed the usability.

• Journal of the Korean Data and Information Science Society
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• 제21권4호
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• pp.765-775
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• 2010

For the accelerated failure time (AFT) model a lot of effort has been devoted to develop effective estimation methods. AFT model assumes a linear relationship between the logarithm of event time and covariates. In this paper we propose a semiparametric support vector machine to consider situations where the functional form of the effect of one or more covariates is unknown. The proposed estimating equation can be computed by a quadratic programming and a linear equation. We study the effect of several covariates on a censored response variable with an unknown probability distribution. We also provide a generalized approximate cross-validation method for choosing the hyper-parameters which affect the performance of the proposed approach. The proposed method is evaluated through simulations using the artificial example.