• Journal of Biosystems Engineering
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• 제33권4호
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• pp.260-268
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• 2008

Optical diffuse reflectance sensing has potential for rapid and reliable on-site estimation of soil properties. For good results, proper calibration to measured soil properties is required. One issue is whether it is necessary to develop calibrations using samples from the specific area or areas (e.g., field, soil series) in which the sensor will be applied, or whether a general "factory" calibration is sufficient. A further question is if specific calibration is required, how many sample points are needed. In this study, these issues were addressed using data from 42 paddy fields representing 14 distinct soil series accounting for 74% of the total Korean paddy field area. Partial least squares (PLS) regression was used to develop calibrations between soil properties and reflectance spectra. Model evaluation was based on coefficient of determination ($R^2$) root mean square error of prediction (RMSEP), and RPD, the ratio of standard deviation to RMSEP. When sample data from a soil series were included in the calibration stage (full information calibration), RPD values of prediction models were increased by 0.03 to 3.32, compared with results from calibration models not including data from the test soil series (calibration without site-specific information). Higher $R^2$ values were also obtained in most cases. Including some samples from the test soil series (hybrid calibration) generally increased RPD rapidly up to a certain number of sample points. A large portion of the potential improvement could be obtained by adding about 8 to 22 points, depending on the soil properties to be estimated, where the numbers were 10 to 18 for pH, 18-22 for EC, and 8 to 22 for total C. These results provide guidance on sampling and calibration requirements for NIR soil property estimation.

• 한국조사연구학회지:조사연구
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• 제9권3호
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• pp.55-69
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• 2008

이제까지 우리나라에서 전화조사를 위한 표본목록은 거의 대부분 전화번호부로부터 나왔다. 그러나 전화번호부의 모집단 포함률이 너무 떨어진다는 지적이 있어 대응수단으로 국제적 기준인 RDD(random digit dialing, 임의번호걸기)가 구현된 바 있다. 2007년 12월의 17대 대통령선거에 대한 예측을 위해 투표일을 $5{\sim}6$일 앞서 실시된 KBS MBC 전화조사는 표본을 반씩 나누어 절반은 RDD로, 나머지 절반은 전화번호부에서 응답자 표본목록을 추출하였다. 이 사례연구는 KBS MBC 전화조사의 RDD 표본과 전화번호부 표본을 대비시켜 공통점과 상이점을 살펴본 것이다. 향후 수년 동안 전화번호부 표본과 RDD 표본이 공존할 것으로 예상되는 상황에서, 이 연구결과가 두 방식의 비교에 시사점을 제시할 것으로 기대한다.

• 한국지반공학회:학술대회논문집
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• 한국지반공학회 2008년도 추계 학술발표회
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• pp.466-474
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• 2008

The purpose of this study was to comparatively analyze the measured values and modelling values when a sample mountain was cut and thereby, assess the fitness of the prediction model. For this purpose, the researcher analyzed the relationship between the groundwater levels measured at 7 monitoring holes set within the area of the underground flow prediction model and the levels of the groundwater monitoring holes before and after mountain cutting. As a result of this analysis, it was found that the MODFLOW program itself was limited and uncertain in terms of calibration of the modelling values. Since the model was based on the assumption that the same amount of rainfalls would permeate into the ground when the sample mountain area was cut up to 50m high, it was deemed inevitable that the result of modelling was different from the actual measurement.

• 대기
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• 제32권4호
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• pp.353-365
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• 2022

This paper evaluates precipitation forecast skill of Global/Regional Integrated Model system (GRIMs) over South Korea in a boreal winter from December 2013 to February 2014. Three types of precipitation are classified based on development mechanism: 1) convection type (C type), 2) low pressure type (L type), and 3) orographic type (O type), in which their frequencies are 44.4%, 25.0%, and 30.6%, respectively. It appears that the model significantly overestimates precipitation occurrence (0.1 mm d^-1) for all types of winter precipitation. Objective measured skill scores of GRIMs are comparably high for L type and O type. Except for precipitation occurrence, the model shows high predictability for L type precipitation with the most unbiased prediction. It is noted that Equitable Threat Score (ETS) is inappropriate for measuring rare events due to its high dependency on the sample size, as in the case of Critical Success Index as well. The Symmetric Extreme Dependency Score (SEDS) demonstrates less sensitivity on the number of samples. Thus, SEDS is used for the evaluation of prediction skill to supplement the limit of ETS. The evaluation via SEDS shows that the prediction skill score for L type is the highest in the range of 5.0, 10.0 mm d^-1 and the score for O type is the highest in the range of 1.0, 20.0 mm d^-1. C type has the lowest scores in overall range. The difference in precipitation forecast skill by precipitation type can be explained by the spatial distribution and intensity of precipitation in each representative case.

• The Korean Journal of Pain
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• 제33권2호
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• pp.153-165
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• 2020

Background: Well-validated risk prediction models help to identify individuals at high risk of diseases and suggest preventive measures. A recent systematic review reported lack of validated prediction models for low back pain (LBP). We aimed to develop prediction models to estimate the 8-year risk of developing LBP and its recurrence. Methods: A population based prospective cohort study using data from 435,968 participants in the National Health Insurance Service-National Sample Cohort enrolled from 2002 to 2010. We used Cox proportional hazards models. Results: During median follow-up period of 8.4 years, there were 143,396 (32.9%) first onset LBP cases. The prediction model of first onset consisted of age, sex, income grade, alcohol consumption, physical exercise, body mass index (BMI), total cholesterol, blood pressure, and medical history of diseases. The model of 5-year recurrence risk was comprised of age, sex, income grade, BMI, length of prescription, and medical history of diseases. The Harrell's C-statistic was 0.812 (95% confidence interval [CI], 0.804-0.820) and 0.916 (95% CI, 0.907-0.924) in validation cohorts of LBP onset and recurrence models, respectively. Age, disc degeneration, and sex conferred the highest risk points for onset, whereas age, spondylolisthesis, and disc degeneration conferred the highest risk for recurrence. Conclusions: LBP risk prediction models and simplified risk scores have been developed and validated using data from general medical practice. This study also offers an opportunity for external validation and updating of the models by incorporating other risk predictors in other settings, especially in this era of precision medicine.

• Nuclear Engineering and Technology
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• 제19권4호
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• pp.233-241
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• 1987

본 연구는 제한된 수의 핵연료의 경험적 파손자료로부터 핵연료 파손 확률을 현실적으로 예측하기 위해 결정론적 모델로부터의 파손화률 예측치와 실제 경험적 자료로부터의 파손 확률 예측치를 접합하는 방법을 시도하였다. 이 접합 방법에 의한 파손 화률 예측치는 결정론적 모델 또는 경험적 파손 자료로부터의 독립적인 예측치보다 신뢰도가 높다. 본 연구에서는 핵연료 성능 예측코드인 SPEAR의 방법론을 응용한 핵연료 파손 패턴의 체계적 발견법 (hierarchical pattern discovery)이 접합 모델에서의 결정론적 모델로부터의 예측치에 대한 가중치와 패턴 경계를 체계적으로 찾기 위해 고안되었다. 이 연구에서 개발된 접합 방법을 PROFIT모델과 경험적 파손자료를 이용하여 CANDU형 핵연료 재장전중 출력 상승에 의해 수반되는 핵연료파손 예측에 적응시켜 보았다.

• 대한토목학회논문집
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• 제31권1D호
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• pp.43-50
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• 2011

택시 프로브(Probe)를 이용한 구간통행속도 모니터링체계는 지능형교통체계(ITS)의 핵심적인 하부시스템 중 하나이다. 택시 프로브기법을 통해 수집되는 구간통행속도는 도시가로망의 교통상태 모니터링과 통행시간 정보제공에 널리 활용되고 있다. 그러나 택시 Probe기법은 표본수가 적고 교통혼잡으로 인하여 구간통행시간이 자료수집 주기보다 큰 경우, 실시간으로 자료가 수집되지 않는 누락상태가 발생하게 된다. 이러한 누락상태는 단일시간대에서 다중시간대에 걸쳐 발생하게 되며, 기존의 단일시간대 예측기법으로는 다중시간대의 상태를 예측하지 못하는 단점이 있다. 따라서 다중시간대 누락상태에서 실시간 구간통행속도를 예측하기위한 기법이 요구된다. 본 연구에서는 기존의 단일시간대 예측기법의 한계를 극복하면서 단일 및 다중시간대 통행속도를 예측하기위한 기법을 개발하였다. 개발된 모형은 비모수회귀(NPR)을 기반으로 개발되었으며, 다중시간대 예측에도 불구하고 기존의 단일시간대 예측기법보다 우수한 정확도를 보였다.

• 생물환경조절학회지
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• 제1권2호
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• pp.162-168
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• 1992

As the automation of nutrient solution management proceeds in the field of hydroponics, effective supporting systems to manage the nutrient solution by computer become needed. This study was attempt to predict the EC of nutrient solution using the neural networks. The multilayer perceptron consisting of 3 layers with the back propagation learning algorithm was selected for EC prediction, of which nine variables in the input layer were the concentrations of each ion and one variable in the output layer the EC of nutrient solution. The meq unit in ion concentration was selected fir input variable in the input layer. After the 10,000 learning sweeps with 108 sample data, the comparison of predicted and measured ECs for 72 test data showed good agreements with the correlation coefficient of 0.998. In addition, the predicted ECs by neural network showed relatively equal or closer to the measured ones than those by current complicated models.

• 한국식품과학회지
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• 제24권5호
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• pp.408-413
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• 1992

신속간편법으로서 식품의 성분함량 측정에 이용되는 근적외 반사분광분석에서 문제가 되고 있는 시료의 균질도의 차이가 흡광도에 미치는 영향을 조사하고 흡광도로 나타난 수치를 수학적으로 처리함으로써 예측의 오차는 다음과 같이 감소하였다. 1. 세절도가 일정한 시료의 흡광도를 무변형, 1차 미분 및 2차 미분하여 calibration한 후 세절도가 다양한 시료의 성분을 예측한 결과 예측오차(standard error of prediction)는 수분함량에 있어서 1.478%, 0.658% 및 0.580%, 지방함량의 예측오차 0.949%, 0.637%, 및 0.527%이었으며 단백질 측정시 각각 0.514%, 0.493% 및 0.394%로 2차 미분의 예측오차가 모든 성분측정에서 가장 낮음을 알 수 있었다. 2. 세절도가 다양한 시료의 무변형, 1차 미분 및 2차 미분처리한 calibration을 이용하여 세절도가 다양한 시료의 성분을 예측한 결과 수분함량 예측오차는 각각 1.026%, 0.589% 및 0.568%, 지방함량 예측오차는 각각 0.828%, 0.639% 및 0.602% 이었으며 단백질함량 예측오차는 0.860%, 0.557% 및 0.399%로서 역시 2차 미분, 1차 미분, 무변형의 순으로 정확성이 높았다. 결과를 종합할 때 흡광도를 수학적으로 처리하여 calibration에 이용하므로서 calibration시료의 세절도에 관계없이 측정결과의 정확성은 높아졌다.

• 대한간호학회지
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• 제39권4호
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• pp.518-527
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• 2009

Purpose: The purpose of this study was to identify factors influencing quality of life in kidney transplant recipients and to understand the concrete pathway of influence and the power of each variable, so that integrated prediction model to promote the quality of life of kidney transplant recipients could be developed. Methods: The sample was composed of 218 patients in follow-up care after a kidney transplant in one of 4 university hospitals in the Honam area. A structured questionnaire was used and the collected data were analyzed for fitness, using the LISREL program. Results: This model was concise and extensive in predicting the quality of life of kidney transplant recipients. Conclusion: The research verified the factors influencing quality of life for kidney transplant recipients and it verified that direct factors such as perception of health state, compliance, self-efficacy, stress and indirect factors such as self-efficacy and social support can be important factors to predict the quality of life for recipients. Moreover, those variables represent 87% of variance in explaining quality of life in a prediction model so that the variables can be utilized to predict quality of life for kidney transplant recipients.