• 한국통계학회:학술대회논문집
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• 한국통계학회 2000년도 추계학술발표회 논문집
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• pp.97-104
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• 2000

Time-related underemployment exists when a person's employment is insufficient in terms of the volume of work. Two alternative definitions can be considered based on a longer-term view or a shorter-term view and these were designed into a single questionnaire. We conducted a pilot sample survey with about 6,000 respondents in Korea. The estimates of underemployment using the two definitions show some differences given the ages, genders, industrial areas and main activities of the respondents. A larger number of people could be identified as underemployed when the longer-term view is used than when the shorter-term view is used, but there is a greater cost associated with the former. The cost-benefit of the interviewers' time was investigated by multiple visits to households. Biases and costs are also analyzed using the results of the comparison of the decrease in non-responses with the increase in the costs for the interviews.

• 한국물환경학회지
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• 제24권2호
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• pp.195-200
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• 2008

To analyze the riverine microbial community structure, genetic fingerprints and ecological indexes such as species abundances, diversity, evenness, dominance of targeted rivers in Gyeonggi Province were acquired and evaluated using terminal restriction fragment length polymorphism (T-RFLP) technique. Genetic fingerprinting technique such as T-RFLP, which is able to show the microbial community clearly unlike traditional culture-dependent techniques, was thought to be useful to analyse the riverine microbial ecosystem under various factors. Riverine ecosystem evaluation using visible organisms would give biased results with time, targeted organism and researcher. But, T-RFLP, which can exclude the subjected biases such as culture condition and identification, would be an option to understand natural ecosystem by including the microorganisms that defy culture but perform important functions.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2006년도 학술발표회 논문집
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• pp.51-56
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• 2006

Biases embedded in numerical weather precipitation forecasts by the RDAPS model was determined, quantified and corrected. The ultimate objective is to eventually enhance the reliability of reservoir operation by Korean Water Resources Corporation (KOWACO), which is based on precipitation-driven forecasts of stream flow. Statistical post-processing, so called MOS (Model Output Statistics) was applied to RDAPS to improve their performance. The Artificial Neural Nwetwork (ANN) model was applied for 4 cases of 'Probability of Precipitation (PoP) for wet and dry season' and 'Quantitative Precipitation Forecasts (QPF) for wet and dry season'. The reduction on the large systematic bias was especially remarkable. The performance of both networks may be improved by retraining, probably every month. In addition, it is expected that performance of the networks will improve once atmospheric profile data are incorporated in the analysis. The key to the optimal performance of ANN is to have a large data set relevant to the predictand variable. The more complex the process to be modeled by the ANN, the larger the data set needs to be.

• Communications for Statistical Applications and Methods
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• 제18권4호
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• pp.537-548
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• 2011

In this paper following Singh et al. (2008), we propose a modified ratio-product type exponential estimator to estimate the finite population mean $\={Y}$ of the study variable y in presence of non-response in different situations viz. (i) population mean $\={X}$ is known, and (ii) population mean $\={X}$ is unknown. The expressions of biases and mean squared error of the proposed estimators have been obtained under large sample approximation using single as well as double sampling. Some realistic conditions have been obtained under which the proposed estimator is more efficient than usual unbiased estimators, ratio estimators, product estimators and exponential ratio and product estimators reported by Rao (1986) and Singh et al. (2010) are found to be more efficient in many situations.

• Nuclear Engineering and Technology
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• 제28권5호
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• pp.467-481
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• 1996

An integrated framework of modeling the human operator cognitive behavior during nuclear power plant accident scenarios is presented. It incorporates both plant and operator models. The basic structure of the operator model is similar to that of existing cognitive models, however, this model differs from those existing ones largely in too aspects. First, using frame and membership function, the pattern matching behavior, which is identified as the dominant cognitive process of operators responding to an accident sequence, is explicitly implemented in this model. Second, the non-task-related human cognitive activities like effect of stress and cognitive biases such as confirmation bias and availability bias, are also considered. A computer code, OPEC is assembled to simulate this framework and is actually applied to an SGTR sequence, and the resultant simulated behaviors of operator are obtained.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회 2003년도 추계학술대회 및 정기총회
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• pp.11-14
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• 2003

The dynamics of unobservable short rate are frequently estimated directly by using a proxy. We estimate the biases resulting from this practice ("proxy problem"). To solve this problem, State-Space models have been proposed by many researchers. State-Space models have been used to estimate the unobservable variables from the observable variables in econometrics. However, applications of State-Space models often result in a misleading interpretation of the underlying processes especially when the absorbability of the State-Space model and the assumption of noise processes in the state vector are not properly considered. In this study, we propose the exact State-Space model that properly considers the faults of previous researchers to solve the proxy problem.

• 응용통계연구
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• 제8권1호
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• pp.9-26
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• 1995

응답자들이 응답을 꺼려하는 민감한 사항에 대한 조사에 거짓응답을 하거나 응답을 회피함으로써 응답편의(response bias)가 발생한다. Warner(1965)는 이러한 응답편의를 줄여주기 위하여 확률장치를 사용하는 확률화응답기법을 제안하였다. 그러나 이 기법은 이론적으로 우수함에도 불구하고 실제 사용하려고 할 때에 여러가지 문제점을 갖고 있다. 따라서 본 연구에서는 확률화응답기법의 실용화를 위하여 이 기법들이 적용된 사례들을 비교분석하고 특징과 문제점등을 찾아 이를 보완하여 실용화를 위한 단계적 방안을 제시하였다. 또한 이들을 실제조사에 적용하였다.

• Journal of Astronomy and Space Sciences
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• 제27권3호
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• pp.213-220
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• 2010

As an observation instrument of the longest record of tropospheric water vapor, radiosonde data provide upper-air pressure (geopotential height), temperature, humidity and wind. However, the data have some well-known elements related to inaccuracy. In this article, radiosonde precipitable water vapor (PWV) at Sokcho observatory was compared with global positioning system (GPS) PWV during each summertime of year 2007 and 2008 and the biases were calculated. As a result, the mean bias showed negative values regardless of the rainfall occurrence. In addition, on the basis of GPS PWV, the maximum root mean square error (RMSE) was 5.67 mm over the radiosonde PWV.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회 2008년도 추계학술대회 및 정기총회
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• pp.319-323
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• 2008

"How does advertising affect sales?" is the fundamental issue of modern advertising research. There is an interesting issue for estimating carry over effects of advertising on sales, and the aggregated data biases exist in the duration of advertising effect. This research suggests a modified model at micro-data using Koyck model (Koyck 1954) by estimated model the aggregate data, and empirically shows the aggregated data bias. Our modified model with the aggregated level of actual data is more appropriate than the base model for micro-data. The result shows that it is very important to consider the disaggregated data level in the analysis of dynamic effects of adverting such as lagged effects.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2006년도 Proceedings of ISRS 2006 PORSEC Volume II
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• pp.578-581
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• 2006

Usually to achieve precise geolocation of satellite images, we need to get GCPs (Ground control points) from individual scenes. This requirement greatly increases the cost and processing time for satellite mapping. In this article, we focus on finding appropriate sensor models for entire image strips composing of several adjacent scenes. We tested the feasibility of modelling whole satellite image strips by establishing sensor models of one scene with GCPs and by applying the models to neighboring scenes without GCPs. For this, we developed two types of sensor models: collinearity-based type and orbit-based type and tested them using different sets of unknowns. Results indicated that although the performance of two types was very similar, for modelling individual scenes, it was not for modelling the whole strips. Moreover, the performance of sensor models was remarkably sensitive to different sets of unknowns. It was found that the orbit-based model using attitude biases as unknowns can be used to model SPOT image strips of 420 Km in length.