• Proceedings of the KSRS Conference
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• 2008.03a
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• pp.213-218
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• 2008

동일 지점을 촬영한 위성영상은 위성의 센서나 영상의 취득 시기, 지형의 상태 등에 따라 그 지점에 나타나는 화소값이 일정하지 않다. 이러한 영상은 영상간 모자이크나 변화 탐지 결과에 영향을 미칠 가능성이 높으므로 방사보정(또는 방사정규화)을 통해 화소값의 차이를 최소화시킬 필요가 있다. 본 연구는 선형회귀식을 적용한 상대 방사정규화에 초점을 맞추고 있으며, 선형회귀식 구성에 필요한 PIF(Pseudo Invariant Feature)를 자동으로 추출하기 위해 Ordinal Rank 알고리즘을 적용하였다. 이 방법을 통해 각 밴드별 후보 PIF를 추출하고, 공통으로 해당되는 최종 PIF를 추출할 수 있었다. RMSE(Root Mean Square Error), Dynamic range, Coefficient of variation 등을 통해 방사보정 후의 결과를 평가해보았다. 영상회귀를 이용한 방사보정알고리즘과의 비교를 통해 제안된 알고리즘이 갖는 장점을 확인하였다.

• Journal of the Korea Safety Management & Science
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• v.9 no.2
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• pp.161-169
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• 2007

This paper presents three methods for expression of reliability measures for large and small data. First method is to express parametric estimation of cardinal reliability measure data for large sample, which requires numerous sample. Second is to obtain nonparametric distribution classification of ordinal reliability measure data for small sample. However it is difficult for field user to understand this method. Last method is to acquire parametric estimation of ordinal reliability measure data for small data. Because this method requires small sample and is comprehensive, we recommend this one among the proposed methods. Various reliability rank measures are presented.

• ETRI Journal
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• v.32 no.3
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• pp.490-492
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• 2010

This letter proposes a robust feature extraction method using a spatially normalized mean for temporal ordinal measurement. Before computing a rank matrix from the mean values of non-overlapped blocks, each block mean is normalized so that it obeys the invariance property against linear additive and subtractive noise effects and is insensitive against multiplied and divided noise effects. Then, the temporal ordinal measures of spatially normalized mean values are computed for the feature matching. The performance of the proposed method showed about 95% accuracy in both precision and recall rates on various distortion environments, which represents the 2.7% higher performance on average compared to the temporal ordinal measurement.

• Journal of the Korean Operations Research and Management Science Society
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• v.30 no.1
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• pp.161-176
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• 2005

In a situation that ordinal preferences on multiattribute weights are captured, we present two solution approaches: an exact approach and an approximate method. The former, an exact solution approach via interaction with a decision-maker, pursues the progressive reduction of a set of non-dominated alternatives by narrowing down the feasible attribute weights region. Subsequent interactive questions and responses, however, sometimes may not guarantee the best alternative or a complete rank order of a set of alternatives that the decision-maker desires to have. Approximate solution approaches, on the other hand, can be divided into three categories including surrogate weights methods, dominance value-based decision rules, and three classical decision rules. Their efficacies are evaluated in terms of choice accuracy via a simulation analysis. The simulation results indicate that a proposed hybrid approach, intended to combine an exact solution approach through interaction and a dominance value-based approach, is recommendable for aiding a decision making in a case that a final choice is seldom made at single step under attribute weights that are imprecisely specified beyond ordinal descriptions.

• Journal of Broadcast Engineering
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• v.7 no.2
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• pp.168-180
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• 2002

This paper proposes a novel method to detect unauthorized copies of digital images. This copy detection scheme can be used as either an alternative approach or a complementary approach to watermarking. A test image is reduced to 8$\times$8 sub-image by intensity averaging, and the AC coefficients of its discrete cosine transform (DCT) are used to compute distance from those generated from the query image, of which a user wants to find copies. Copies may be Processed to avoid copy detection or enhance image quality. We show ordinal measure of DCT coefficients, which is based on relative ordering of AC magnitude values and using distance metrics between two rank permutations, are robust to various modifications of the original image. The optimal threshold selection scheme using the maximum a posteriori (MAP) criterion is also addressed.

• Journal of Korea Technology Innovation Society
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• v.11 no.3
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• pp.376-399
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• 2008

Science and technology (S&T) is one of the most important elements in a nation's competitiveness. In an effort to strengthen their national competitiveness, all countries are focusing on upgrading the level of eir S&T. With these factors in mind, Korea has increased its support of national research and development (R&D). In recent years, this added support has resulted in an increased interest in the effectiveness of R&D. We have made continuous efforts to enhance the accountability and effectiveness of R&D by strengthening performance evaluation and considering R&D evaluation results during the budget review (appropriation) process. In order to change to a performance based system, we need to develop objective and scientific indicators to measure and evaluate the quality of the research performance of R&D programs. One of the primary research outcomes is publications. The impact factor of publications is widely used to evaluate overall journal quality and the quality of the papers published therein. However, the use of impact factors has been criticised because they can vary greatly when works from different subject areas are compared. In order to overcome this limitation, we have developed three kinds of qualitative indicators, which are functions of the impact factor. Two of these qualitative indicators, Modified Rank Normalized Impact Factor and Ordinal Rank Normalized Impact Factor, are based on order statistics (rank) for all journals from a specific specialty. The third qualitative indicator, Relative Field Impact Factor, uses the average impact factor of all journals within a subject category. We also suggest a quantitative indicator, Percentage of Contribution. In this study, we suggest 4 indicators and use them to evaluate the performance of outcomes from three R&D programs supported by the Ministry of Education, Science & Technology. We also perform a simulation study to verify the effectiveness of the proposed indicators. It can be shown that the proposed Ordinal Rank Normalized Impact Factor is the most reliable and effective indicator for comparing research performance across subject categories. However, we recommend using previous indicators in combination with the proposed indicators in this study for the research evaluation of R&D programs.

• Journal of the Korea Society of Computer and Information
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• v.21 no.4
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• pp.63-71
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• 2016

This paper is about applying efficient data mining method which improves the score calculation and proper building performance of credit ranking score system. The main idea of this data mining technique is accomplishing such objectives by applying Correlation based Feature Selection which could also be used to verify the properness of existing rank scores quickly. This study selected 2047 manufacturing companies on KOSPI market during the period of 2009 to 2013, which have their own credit rank scores given by NICE information service agency. Regarding the relevant financial variables, total 80 variables were collected from KIS-Value and DART (Data Analysis, Retrieval and Transfer System). If correlation based feature selection could select more important variables, then required information and cost would be reduced significantly. Through analysis, this study show that the proposed correlation based feature selection method improves selection and classification process of credit rank system so that the accuracy and credibility would be increased while the cost for building system would be decreased.

• Journal of Digestive Cancer Research
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• v.10 no.2
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• pp.99-106
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• 2022

Clinical research ultimately aimed to promptly diagnose and prevent diseases through precise biomarker development. Finding the optimal cut-off point of a regularly measured biomarker can help its interpretation and ultimately help in disease investigation and diagnosis, more specifically in determining the presence of diseases. Therefore, this study aimed to use the characteristics of outcome variables in clinical research to explain how to determine the optimal cutoff point. The outcome variables can be divided into dichotomous, ordinal, and survival types. The optimal cut-off point can be determined by finding points that maximize the Youden index, extended Youden index, and log-rank statistics. This study will enable clinical researchers to accurately determine the optimal cut-off points for regularly measured biomarkers, thereby enabling prompt disease diagnosis for effective treatment.

• Journal of Labour Economics
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• v.40 no.2
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• pp.1-29
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• 2017

We examine the extent to which students' performance relative to peers affects their career choice. Specifically, we analyze the relationship between a student's mathematics ranking in his/her school and the likelihood of choosing Mathematics and Science track in high school. Using a panel dataset of students in Seoul, we measure a student's performance using two variables: absolute performance and relative performance. The former measures a student's performance relative to the entire sample, while the latter measures performance relative to the student's peers in the same school. After controlling for test scores and other characteristics, we find that the students with a poor relative ranking are 11 percentage points less likely to choose the Mathematics and Science track. Relative performance affects girls more greatly than boys. Although relative performance affects a student's self-efficacy and class participation, our accounting exercise suggests that this channel accounts for only 12 percent of the impact, implying that students may respond to the relative ranking mostly due to other factors, such as strategic consideration to perform well in college applications.

• Journal of Korean Academy of Nursing
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• v.13 no.3
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• pp.106-118
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• 1983

The main purpose of this study is to systematically classify words indicating pain in terms of their ranks in each subclass. This study is a part of developing a Korean Pain Measurement Tool. This study didnot include exploration of each word's dimension such as sensory or affective. Eighty three Korean words tentatively classified in 19 subclasses in previous study were used for this study. At least three to six words were included in each subclass and the words were randomly placed in which each subject indicates their rank of pain degree. One hundred and fifty nursing students and one hundred clinical nurses were requested to indicate the rank of each word. One hundred and sixteen students and eighty three nurses completed the ratings for analysis. The data were collected from June 1983 to July 1983. The data using ordinal scale were analyzed by Friedman ANOVA to test significant difference between rank means. All of pain words indicated significant rank mean difference in all of 19 subclasses. Some of the words were either cancelled or replaced by other words, or rearranged for their ranks. Subclasses of which words were cancelled were 1) Simple stimulating pain, 2) Punctuate pressure, 3) peripheral nerve pain, 4) radiation pain, 5) punishment-related pain, and 6) suffering-related pain. Subclasses of which words were replaced or rearranged were 1) incisive pressure, 2) constrictive pressure, 3) dull pain, 4) tract pain, 5) digestion-related pain and 6) fear-related pain. Four subclasses such as traction pressure, thermal, cavity pressure, and fatigue- elated pain indicated significant differences among rank means in each subclasses and showed no visible overlaps of the ranks among means. Further research is needed using high level measurement of pain degree of each word and more sophisticated analysis of the pain degrees. Three pain words which would be related to chemical stimulation were newly explored and included as a new subclass. Through this study, the total number of subclasses increases from 19 to 20 and the total number of Korean words in the scale decreases from 83 to 80.