• 한국물환경학회지
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• 제26권3호
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• pp.482-490
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• 2010

In this study 17 GCMs' simulations of late 20th century climate in Korea are examined. A regionally averaged time series formed by averaging the temperature and precipitation values at all the Korean grid points. In order to compare general circulation models with observations, observed spatially averaged temperature and precipitation is calculated using 24 stations for 1971 to 2000. The annual mean difference between models and observed data are compared. For temperature, most models have a slight cold bias. The models with least bias in annual average temperature are NIES(MIROC3.2 hires), GISS(AOM) and INGV(SXG2005). For precipitation, almost all models have a dry bias, and for some the bias exceeds 50%. Models with lowest bias are NIES(MIROC3.2 hires), CCCma(CGCM3-T47) and MPI-M(ECHAM5-OM). The models' simulated seasonal cycles show that for temperature, CSIRO(Mk3.0) has the best followed by CCCma(CGCM3-T47) and CCCma(CGCM3-T63), and for precipitation, NIES(MIROC3.2 hires) has the best followed by CSIRO(Mk3.0) and CNRM(CM3). In the assessment using Taylor diagram, CCCma(CGCM3-T47) ranks the best for temperature, and NIES(MIROC3.2 hires) ranks the best for precipitation.

• 대한통합의학회지
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• 제8권4호
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• pp.1-11
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• 2020

Purpose : The purpose of this meta-analysis was to examine the effects of microcurrent on inflammatory musculoskeletal diseases. Methods : Domestic databases (RISS, NDSL, KISS, DBpia, and Kmbase) were searched for studies that conducted clinical trials associated with microcurrent and its impact on inflammatory musculoskeletal diseases. A total of 606 studies published between 2002 and 2019 were identified, with 8 studies satisfying the inclusion data. The studies were classified according to patient, intervention, comparison, and outcome (PICO). The search outcomes were items associated with blood component, pain, and function. The 8 studies that were included in the study were evaluated using R meta-analysis (version 4.0). The quality of 7 randomized control trials was evaluated using Cochrane risk of bias (ROB). The quality of 1 non-randomized control trial was evaluated using risk of bias assessment tool for non-randomized studies (RoBANS). Effect sizes were computed as the corrected standard mean difference (SMD). A random-effect model was used to analyze the effect size because of the high heterogeneity among the studies. Egger's regression test was carried out to analyze the publishing bias. Results : The following factors had a large effect size involving microcurrent on inflammatory musculoskeletal diseases: blood component (Hedges's g=-2.46, 95 % CI=-4.20~-0.73), pain (Hedges's g=3.51, 95 % CI=2.44~4.77), and function (Hedges's g=3.06, 95 % CI: 1.53~4.58). Except for function (t=1.572, p=.191), Egger's regression test showed that the publishing bias had statistically significant differences. Conclusion : This study provides evidence for the effectiveness of microcurrent on inflammatory musculoskeletal diseases in terms of blood component, pain, and function. However, due to the small sample sizes used in the included studies, the results of our study should be interpreted cautiously, especially considering the publishing bias.

• 한국산업융합학회 논문집
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• 제26권2_2호
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• pp.293-306
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• 2023

The purpose of this study is a descriptive research study to analyze the factors that affect Christians' COVID-19 preventive behavior. The subjects of the study were 262 adult Christians, and the data collected were using SPSS 25.0 and AMOS 21.0 programs. As a result of the study, the subject's religious maturity level was 4.21 ± .55 points out of 5 points, COVID-19 stress was 2.86 ± .73 points out of 5 points, optimism bias was 2.94 ± 1.26 points out of 7 points, and COVID-19 preventive health behavior was 4 points. The total score was 3. 54 ± . 44 points. As a result of the correlation analysis of the subject's religious maturity, COVID-19 stress, optimistic bias, and COVID-19 preventive health behaviors, COVID-19 preventive health behaviors were faith maturity (r=.156, p=.012), COVID-19 stress (r=.216, There was a positive correlation with optimism bias (r=174, p=.005). In conclusion, it can be said that the higher the religious maturity, the higher the COVID-19 stress, and the higher the optimistic bias, the better the preventive health behavior of COVID-19, and the explanatory power of the overall model was 9.4%. In the post-COVID-19 era, it is necessary to develop educational programs that can prevent infectious diseases and promote health in the community.

• Journal of the Korean Statistical Society
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• 제7권2호
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• pp.101-104
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• 1978

This paper considers the problem of estimating $\hat{\beta}$ in the case errors occur in observing the values of q-variables $X_1, X_2, ..., X_q$. The approximated estimator $\hat{\beta}(e)$ is obtained and its expected value, bias and covariance matrix are studied.

• 한국재난관리표준학회지
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• 제2권3호
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• pp.39-46
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• 2009

소형루프 전자탐사는 지하매질의 전기비저항 분포를 비파괴적으로 영상화하는 효과적인 탐사방법이다. 하지만, 측정자료에 대한 정량적인 해석과 심도별 단면을 획득하기 위해서는 측정자료의 품질이 매우 중요하다. 본 연구에서는 소형루프 전자탐사 자료 획득 시 주변 배경잡음을 함께 측정하여 정량적 해석을 어렵게 하는 Bias noise를 제거하는 방법을 제시하였다. 이를 통해 잡음의 영향이 크게 감소한 신뢰성 있는 자료를 획득할 수 있었다. 이와 함께 측정자료로부터 전기비저항 영상을 간단하게 산출할 수 있는 겉보기 비저항 산출기법을 제시하였다. 본 연구에서 제시된 방법을 서로 다른 지하수위 조건을 가진 인공 모의지반 실험 사이트에 적용하였으며, 이를 통해 소형루프 전자탐사가 누수와 같이 지하수위 조건이 다른 지역을 탐지하는데 효과적인 방법임을 확인하였다.

• Journal of Preventive Medicine and Public Health
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• 제50권5호
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• pp.294-302
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• 2017

Objectives: The objectives of this study were to investigate the agreement between medical history questionnaire data and claims data and to identify the factors that were associated with discrepancies between these data types. Methods: Data from self-reported questionnaires that assessed an individual's history of hypertension, diabetes mellitus, dyslipidemia, stroke, heart disease, and pulmonary tuberculosis were collected from a general health screening database for 2014. Data for these diseases were collected from a healthcare utilization claims database between 2009 and 2014. Overall agreement, sensitivity, specificity, and kappa values were calculated. Multiple logistic regression analysis was performed to identify factors associated with discrepancies and was adjusted for age, gender, insurance type, insurance contribution, residential area, and comorbidities. Results: Agreement was highest between questionnaire data and claims data based on primary codes up to 1 year before the completion of self-reported questionnaires and was lowest for claims data based on primary and secondary codes up to 5 years before the completion of self-reported questionnaires. When comparing data based on primary codes up to 1 year before the completion of selfreported questionnaires, the overall agreement, sensitivity, specificity, and kappa values ranged from 93.2 to 98.8%, 26.2 to 84.3%, 95.7 to 99.6%, and 0.09 to 0.78, respectively. Agreement was excellent for hypertension and diabetes, fair to good for stroke and heart disease, and poor for pulmonary tuberculosis and dyslipidemia. Women, younger individuals, and employed individuals were most likely to under-report disease. Conclusions: Detailed patient characteristics that had an impact on information bias were identified through the differing levels of agreement.

• 정보처리학회논문지:소프트웨어 및 데이터공학
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• 제10권3호
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• pp.79-84
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• 2021

고차원의 데이터를 처리하기 위해서는 데이터의 성질을 유지하면서 특징을 잘 반영할 수 있는 특징 추출 방법이 필요하다. 주성분분석 방법은 고차원 데이터에 포함된 정보를 저차원의 데이터로 변환하여 원래 데이터의 변수 수보다 적은 수의 변수로 고차원 데이터를 표현 할 수 있는 방법으로서 데이터의 특징 추출을 위한 대표적인 방법이다. 본 연구에서는 데이터가 고차원인 경우 데이터 특징 추출을 위한 주성분 분석에 있어서 주성분 변수 선정 시 적응적 상관도를 기반으로 한 주성분 분석 방법을 제안한다. 제안하는 방법은 입력 데이터간의 상관 관계를 기반으로 상관도를 적응적으로 반영하여 데이터의 주성분을 분석함으로써 다른 여러 변수에 중복적으로 상관도가 높은 변수와 주성분을 유도하는데 연관성이 적은 변수를 주성분 변수 후보 대상에서 제외시키고자 한다. 고유벡터 계수 값에 의한 주성분 위계를 분석하고 위계가 낮은 주성분이 변수로 선정이 되는 것을 막고 또한 상관 분석을 통하여 데이터의 중복 발생이 데이터 편향을 유도하는 것을 최소화하 하고자 한다. 이를 통하여 주성분 변수 선정 시 데이터 편향성의 영향을 줄임으로써 실제 데이터의 특징을 잘 나타내는 주성분 변수를 선정하는 방법을 제안하고자 한다.

• 한국근적외분광분석학회:학술대회논문집
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• 한국근적외분광분석학회 2001년도 NIR-2001
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• pp.4107-4107
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• 2001

Previous works have shown the viability of NIRS technology for the prediction of fatty acids in Iberian pig fat, but although the resulting equations showed high precision, in the predictions of new samples important fluctuations were detected, greater with the time passed from calibration development to NIRS analysis. This fact makes the use of NIRS calibrations in routine analysis difficult. Moreover, this problem only appears in products like fat, that show spectrums with very defined absorption peaks at some wavelengths. This circumstance causes a high sensibility to small changes of the instrument, which are not perceived with the normal checks. To avoid these inconveniences, the software WinISI 1.04 has a mathematic algorithm that consist of create a “Repeatability File”. This file is used during calibration development to minimize the variation sources that can affect the NIRS predictions. The objective of the current work is the evaluation of the use of a repeatability file in quantitative NIRS analysis of Iberian pig fat. A total of 188 samples of Iberian pig fat, produced by COVAP, were used. NIR data were recorded using a FOSS NIRSystems 6500 I spectrophotometer equipped with a spinning module. Samples were analysed by folded transmission, using two sample cells of 0.1mm pathlength and gold surface. High accuracy calibration equations were obtained, without and with repeatability file, to determine the content of six fatty acids: miristic (SECV$\sub$without/=0.07% r$^2$$\sub$without/=0.76 and SECV$\sub$with/=0.08% r$^2$$\sub$with/=0.65), Palmitic (SECV$\sub$without/=0.28 r$^2$$\sub$without/=0.97 and SECV$\sub$with/=0.24% r$^2$$\sub$with/=0.98), palmitoleic (SECV$\sub$without/=0.08 r$^2$$\sub$without/=0.94 and SECV$\sub$with/=0.09% r$^2$$\sub$with/=0.92), Stearic (SECV$\sub$without/=0.27 r$^2$$\sub$without/=0.97 and SECV$\sub$with/=0.29% r$^2$$\sub$with/=0.96), oleic (SECV$\sub$without/=0.20 r$^2$$\sub$without/=0.99 and SECV$\sub$with/=0.20% r$^2$$\sub$with/=0.99) and linoleic (SECV$\sub$without/=0.16 r$^2$$\sub$without/=0.98 and SECV$\sub$with/=0.16% r$^2$$\sub$with/=0.98). The use of a repeatability file like a tool to reduce the variation sources that can disturbed the prediction accuracy was very effective. Although in calibration results the differences are negligible, the effect caused by the repeatability file is appreciated mainly when are predicted new samples that are not in the calibration set and whose spectrum were recorded a long time after the equation development. In this case, bias values corresponding to fatty acids predictions were lower when the repeatability file was used: miristic (bias$\sub$without/=-0.05 and bias$\sub$with/=-0.04), Palmitic (bias$\sub$without/=-0.42 and bias$\sub$with/=-0.11), Palmitoleic (bias$\sub$without/=-0.03 and bias$\sub$with/=0.03), Stearic (bias$\sub$without/=0.47 and bias$\sub$with/=0.28), oleic (bias$\sub$without/=0.14 and bias$\sub$with/=-0.04) and linoleic (bias$\sub$without/=0.25 and bias$\sub$with/=-0.20).

• Journal of the Korean Data and Information Science Society
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• 제20권2호
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• pp.349-356
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• 2009

국내의 행정구역상 시군구 등과 같은 소지역에 있어서 실업률에 대한 남녀별 공통 상대위험도를 추정하는데, 추정방법으로 단순한 합동추정, 울프 방법에 기초한 가중추정과 잭나이프 추정들을 고려하고 이 추정 방법들의 효율성을 편의와 평균제곱오차의 개념을 통해서 비교하고자 한다. 이를 위해 2002년 12월 경기지역의 경제활동인구조사 자료를 이용하여 이 지역 내의 24개 시군단위 소지역들의 남녀별 실업률에 대한 상대위험도의 편의 및 평균제곱오차가 본 연구에서 제시된 추정절차에 의해 추정된다. 또한, 이들 추정치들의 안정성과 신뢰성은 상대편의와 상대오차제곱근을 통하여 비교된다. 추정결과 잭나이프 추정이 다른 두 추정들에 비해 매우 효율적임을 보였다.

• 전자공학회논문지
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• 제52권10호
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• pp.73-81
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• 2015

이 논문은 프로토타입 선택 방법을 제안하고, 편의-분산 분해를 이용하여 최근접 이웃 알고리즘과 프로토타입 기반 분류 학습의 일반화 성능 비교 평가에 있다. 제안하는 프로토타입 분류기는 클래스 영역 내에서 가변 반지름을 이용한 다차원 구를 정의하고, 적은 수의 프로토타입으로 구성된 새로운 훈련 데이터 집합을 생성한다. 최근접 이웃 분류기는 새 훈련 집합을 이용하여 테스트 데이터의 클래스를 예측한다. 평균 기대 오류의 편의와 분산 요소를 분해하여 최근접 이웃 규칙, 베이지안 분류기, 고정 반지름을 이용한 프로토타입 선택 방법, 제안하는 프로토타입 선택 방법의 일반화 성능을 비교한다. 실험에서 제안하는 프로토타입 분류기의 편의-분산 변화 추세는 모든 훈련 데이터를 사용하는 최근접 이웃 알고리즘과 비슷한 편의-분산 추세를 보였으며, 프로토타입 선택 비율은 전체 데이터의 평균 약 27.0% 이하로 나타났다.