• 대한토목학회논문집
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• 제39권3호
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• pp.381-389
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• 2019

최근 빈번히 발생하는 이상기후의 영향으로 홍수범람 가능성이 커짐에 따라 침수범위에 대한 예측은 점점 어려워지고 있다. 이러한 홍수에 대비하기 위한 비구조적 대책 중의 하나인 호우피해 예측지도의 작성은 필수적이며 홍수범람 해석에서 중요한 부분을 차지한다. 하지만, 호우피해 예측지도의 정량적 평가방법과 기준이 없는 실정이다. 본 연구에서는 Receiver Operation Characteristics (ROC) 분석과 Lee Sallee Shape Index (LSSI) 방법을 이용하여 10개 행정구역에 대한 호우피해 예측지도의 정확도를 평가하였다. 그 결과 ROC Curve Score는 0.631, LSSI 방법은 25.16 %로 분석되었으며, 각 행정구역에 대한 분석결과와 전체 결과를 활용하여 점수구간을 5개로 나누어 호우피해 예측지도 평가에 대한 정량적 평가방법을 제안하였다. 또한, 검 보정이 완료된 XP-SWMM 모형의 ROC 분석과 LSSI 결과, 각각 0.8496, 51.92 %로 분석되어 침수피해 예측지도에 대한 평가기준의 적정성을 확보하였다. 본 연구에서 제안한 호우피해 예측지도에 대한 정략적인 평가기준은 다양한 재해지도에 적용 가능할 것으로 판단된다.

• Communications for Statistical Applications and Methods
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• 제14권1호
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• pp.169-182
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• 2007

Receive operating characteristic (ROC) approach can be employed to rank candidate genes from a microarray experiment, in particular, for the biomarker development with the purpose of population screening of a cancer. In the cancer microarray experiment based on n patients the researcher often wants to compare the tumor tissue with the normal tissue within the same individual using a common reference RNA. Ideally, this experiment produces n pairs of microarray data. However, it is often the case that there are missing values either in the normal or tumor tissue data. Practically, we have $n_1$ pairs of complete observations, $n_2$ "normal only" and $n_3$ "tumor only" data for the microarray. We refer to this data set as a mixed data set. We develop a ROC approach on the mixed data set to rank candidate genes for the biomarker development for the colorectal cancer screening. It turns out that the correlation between two ranks in terms of ROC and t statistics based on the top 50 genes of ROC rank is less than 0.6. This result indicates that employing a right approach of ranking candidate genes for the biomarker development is important for the allocation of resources.

• Asian Pacific Journal of Cancer Prevention
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• 제15권10호
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• pp.4143-4145
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• 2014

Background: This study used receiver operating characteristic curve to analyze Surveillance, Epidemiology and End Results (SEER) Ewing sarcoma (ES) outcome data. The aim of this study was to identify and optimize ES-specific survival prediction models and sources of survival disparities. Materials and Methods: This study analyzed socio-economic, staging and treatment factors available in the SEER database for ES. 1844 patients diagnosed between 1973-2009 were used for this study. For the risk modeling, each factor was fitted by a Generalized Linear Model to predict the outcome (bone and joint specific death, yes/no). The area under the receiver operating characteristic curve (ROC) was computed. Similar strata were combined to construct the most parsimonious models. Results: The mean follow up time (S.D.) was 74.48 (89.66) months. 36% of the patients were female. The mean (S.D.) age was 18.7 (12) years. The SEER staging has the highest ROC (S.D.) area of 0.616 (0.032) among the factors tested. We simplified the 4-layered risk levels (local, regional, distant, un-staged) to a simpler non-metastatic (I and II) versus metastatic (III) versus un-staged model. The ROC area (S.D.) of the 3-tiered model was 0.612 (0.008). Several other biologic factors were also predictive of ES-specific survival, but not the socio-economic factors tested here. Conclusions: ROC analysis measured and optimized the performance of ES survival prediction models. Optimized models will provide a more efficient way to stratify patients for clinical trials.

• 치과방사선
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• 제24권2호
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• pp.439-450
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• 1994

Recently, the digital image was introduced into radiological image. The digital image has the power of contrast enhancement, histogram control, and other digitally enhancement. At the point of the resolution, periapical radiograph is superior to the digital image, but enhanced digital procedure improves the diagnostic ability of the digital image. The purpose of this study was to evaluate the diagnostic ability of artificial proximal caries in conventional radiographs, digital radiographs and enhanced digital radiographs (histogram specification). ROC (Receiver Operating Characteristic) analysis and paired t-test were used for the evaluation of detectability, and following results were acquired: 1. The mean ROC area of conventional radiographs was 0.9274. 2. The mean ROC area of unenhanced digital image was 0.9168. 3. The mean ROC area of enhanced digital image was 0.9339. 4. The diagnostic ability of three imaging methods was not significant difference(p>0.05). So, the digital images had similar diagnostic ability of artificial proximal caries to conventional radiographs. If properly enhanced digital image, it may be superior to conventional radiographs.

• 한국군사과학기술학회지
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• 제2권1호
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• pp.19-29
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• 1999

This paper treats the implementation of concurrent engineering principles for ROC development of a future infantry fighting vehicle. Based on the acquisition process of weapon systems and operational requirements provided by users, Quality Function Deployment(QFD) is used to translate the requirements of the user into specific trade-off analysis. Results of these studies and the use of concurrent engineering principles are presented.

• Communications for Statistical Applications and Methods
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• 제11권1호
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• pp.21-30
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• 2004

Often the accuracy is not adequate as a performance measure of classifiers when costs are different for different prediction errors. ROC and cost graphs can be used in such case to compare and identify cost-sensitive classifiers. We extend ROC and cost graphs so that they can be used when more general cost matrix is given, where not only misclassifications but correct classifications also incur penalties.

• Journal of the Korean Data and Information Science Society
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• 제15권4호
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• pp.911-920
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• 2004

We try receiver operating characteristic(ROC) curves by neural networks of logistic function. The models are shown to arise from model classification for normal (diseased) and abnormal (nondiseased) groups in medical research. A few goodness-of-fit test statistics using normality curves are discussed and the performances using neural networks of logistic function are conducted.

• 시스템엔지니어링학술지
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• 제15권2호
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• pp.9-16
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• 2019

The most important task in acquiring the weapon system is to determine the required performance and to test & evaluate it. The importance of the weapon system by ROC (Required Operational Capability) is not considered, and system development and test evaluation are carried out. In addition, technical incidental performance is tested on the same basis as ROC in the test evaluation and determined according to the result. Development test and evaluation that evaluates technical ability is very important, but development agency is supervised and performed. In this paper, we propose a method to give weights considering the importance of ROC, a technical incidental performance determination and test procedure, and a improvement plan for the development and operational test & evaluation.

• Communications for Statistical Applications and Methods
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• 제22권3호
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• pp.223-232
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• 2015

The area under the ROC curve (AUC), the volume under the ROC surface (VUS) and the hypervolume under the ROC manifold (HUM) are defined and interpreted with probability that measures the discriminant power of classification models. AUC, VUS and HUM are expressed with the summation and integration notations for discrete and continuous random variables, respectively. AUC for discrete two random samples is represented as the nonparametric Mann-Whitney statistic. In this work, we define conditional Mann-Whitney statistics to compare more than two discrete random samples as well as propose that VUS and HUM are represented as functions of the conditional Mann-Whitney statistics. Three and four discrete random samples with some tie values are generated. Values of VUS and HUM are obtained using the proposed statistic. The values of VUS and HUM are identical with those obtained by definition; therefore, both VUS and HUM could be represented with conditional Mann-Whitney statistics proposed in this paper.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제5권3호
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• pp.263-267
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• 2005

Building classifiers for financial real-world classification problems is often plagued by severely overlapping and highly skewed class distribution. New performance measures such as receiver operating characteristic (ROC) curve and area under ROC curve (AUC) have been recently introduced in evaluating and building classifiers for those kind of problems. They are, however, in-effective to evaluation of classifier's discrimination performance in a particular class of the classification problems that interests lie in only a local operating range of the classifier, In this paper, a new method is proposed that enables us to directly improve classifier's discrimination performance at a desired local operating range by defining and optimizing a partial area under ROC curve or domain-specific curve, which is difficult to achieve with conventional classification accuracy based learning methods. The effectiveness of the proposed approach is demonstrated in terms of fraud detection capability in a real-world fraud detection problem compared with the MSE-based approach.