• 농촌계획
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• 제30권1호
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• pp.81-97
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• 2024

This study examines the effects of adopting Information and Communication Technology (ICT) in livestock farm management on farm sales revenue. Using the 2020 Census of Agriculture, Forestry, and Fisheries, a nationally representative data set constructed by Statistics Korea, this study focuses on a sample of 9,020 livestock farms in South Korea. We employ Propensity Score Matching (PSM) methods to address the potential selection bias between 2,076 farms that used ICT for livestock farm management and 6,944 farms that did not. The findings consistently show that the use of ICT significantly increases farm revenue, taking into account the selection bias. The utilization of ICT in livestock farms leads to a higher increase in sales revenue, particularly for farms with greater sales.

• 한국대기환경학회지
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• 제21권2호
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• pp.269-274
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• 2005

In this work, analytical bias arising from the gas chromatographic determination of sulfur compounds was evaluated by the application of direct loop injection method to the GC/PFPD detection of four sulfur compounds including H$_{2}$S, CH$_{3}$SH, DMS, and DMDS. For the proper evaluation of analytical uncertainties involved in GC calibration, we employed two comparative techniques of calibration at fxed concentration injection (CFCI) vs calibration at fixed volume injection (CFVI) method. The results of our study indicate that CFCI method exhibits very poor sensitivity due to the matrix effect with varying injection volumes. On the other hand, as CFVI method overcomes such limitation, it can be used to obtain very accurate quantification of S compounds at their high concentration levels above a few to a few tens ppb.

• 동의신경정신과학회지
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• 제28권3호
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• pp.165-182
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• 2017

Objectives: The purpose of this systematic review was to understand clinical usefulness of Emotional Freedom Techniques (EFT) on students' mental health. Methods: Ten databases were included to extract clinical studies on effects of EFT intervention with students. Characteristics of selected studies were described, and biases were assessed with Risk of Bias (RoB) or Risk of Bias Assessment for Non-Randomized Studies (RoBANS). Results: A total of 14 clinical trials were extracted for analysis. There were 8 randomized-controlled trials (RCTs), 2 non-randomized-controlled trials (nRCTs), and 4 before-after studies. EFT have significant clinical usefulness in public speaking anxiety, test anxiety, stress, depression, learning related emotions, adolescent anxiety, and eating issues. The risk of selection bias in most studies was high or uncertain. Conclusions: EFT is an effective clinical technique for managing students' mental health issues. However, the included studies have been conducted with relatively poor quality and small sample size. Clinical trials with high quality study design and well-designed EFT education programs are needed to generalize clinical usefulness.

• 대한치과의사협회지
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• 제58권3호
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• pp.152-168
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• 2020

The propensity score matching method is a statistical method used to reduce selection bias in observational studies and to show effects similar to random allocation. There are many observational studies in dentistry research, and differences in baseline covariates between the control and case groups affect the outcome. In order to reduce the bias due to confounding variables, the propensity scores are used by equating groups based on the baseline covariates. This method is effective, especially when there are many covariates or the sample size is small. In this paper, the propensity score matching method was explained in a simple way with a dental example by using R software. This simulated data were obtained from one of retrospective study. The control group and the case group were matched according to the propensity score and compared before and after treatment. The propensity score matching method could be an alternative to compensate for the disadvantage of the observation study by reducing the bias based on the covariates with the propensity score.

• International Journal of Human Ecology
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• 제4권2호
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• pp.77-87
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• 2003

This paper tried to construct statistical and econometric models on the basis of economic theory in order to discuss the issue of statistical efficiency and unbiasedness including the sample selection bias correcting problem. Comparative analytical tool were one stage Tobit of Maximum Likelihood estimation and Heckman's two-step Tobit of Ordinary Least Squares. The results showed that the adequacy of model for the analysis on demand and choice, we believe that there is no big difference in explanatory variables between the first selection model and the second linear probability model. Since the Lambda, the self- selectivity correction factor, in the Type II Tobit is not statistically significant, there is no self-selectivity in the Type II Tobit model, indicating that Type I Tobit model would give us better explanation in the demand for and choice which is less complicated statistical method rather than type II model.

• Journal of Information Processing Systems
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• 제10권2호
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• pp.314-333
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• 2014

When analyzing default predictions in real estate companies, the number of non-defaulted cases always greatly exceeds the defaulted ones, which creates the two-class imbalance problem. This lowers the ability of prediction models to distinguish the default sample. In order to avoid this sample selection bias and to improve the prediction model, this paper applies a minority sample generation approach to create new minority samples. The logistic regression, support vector machine (SVM) classification, and neural network (NN) classification use an imbalanced dataset. They were used as benchmarks with a single prediction model that used a balanced dataset corrected by the minority samples generation approach. Instead of using prediction-oriented tests and the overall accuracy, the true positive rate (TPR), the true negative rate (TNR), G-mean, and F-score are used to measure the performance of default prediction models for imbalanced dataset. In this paper, we describe an empirical experiment that used a sampling of 14 default and 315 non-default listed real estate companies in China and report that most results using single prediction models with a balanced dataset generated better results than an imbalanced dataset.

• 한국정보통신학회논문지
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• 제14권2호
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• pp.534-539
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• 2010

게놈 연구에서 수천 개의 특징들은 비교적 작은 샘플들로부터 모아진다. 게놈 연구의 목적은 미래 관찰들의 결과를 예측하는 분류기를 만드는 것이다. 분류기를 만들기 위해서는 특징 선택, 모델 선택 그리고 예측 평가 등의 3단계 과정을 거친다. 본 논문은 예측 평가에 초점을 맞추고 모든 슬라이드의 사분위수를 똑같게 맞추는 quantilenormalization 적용하여 마이크로어레이 데이터를 표준화 한 후 특징 선택에 앞서 예측 모델의 '진짜' 예측 에러를 평가하기 위해 몇 개의 방법들을 비교하는 시스템을 고안하고 방법들의 예측 에러를 비교 분석 하였다. LOOCV는 전체적으로 작은 MSE와 bias를 나타내었고, 크기가 작은 샘플에서 split 방법과 2-fold CV는 매우 좋지 않는 결과를 보였다. 계산적으로 번거로운 분석에 대해서는 10-fold CV가 LOOCV보다 오히려 더 낳은 경향을 보였다.

• 천문학회지
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• 제48권1호
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• pp.83-92
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• 2015

Recent large scale surveys such as Sloan Digital Sky Survey have produced homogeneous samples of multiple-image gravitationally lensed quasars with well-defined selection effects. Statistical analysis on these can yield independent constraints on cosmological parameters. Here we use the image separation statistics of lensed quasars from Sloan Digital Sky Survey Quasar Lens Search (SQLS) to derive constraints on cosmological parameters. Our analysis does not require knowledge of the magnification bias, which can only be estimated from the detailed knowledge on the quasar luminosity function at all redshifts, and includes the consideration for the bias against small image separation quasars due to selection against faint lens galaxy in the follow-up observations for confirmation. We first use the mean image separation of the lensed quasars as a function of redshift to find that cosmological models with extreme curvature are inconsistent with observed lensed quasars. We then apply the maximum likelihood test to the statistical sample of 16 lensed quasars that have both measured redshift and magnitude of lens galaxy. The likelihood incorporates the probability that the observed image separation is realized given the luminosity of the lens galaxy in the same manner as Im et al. (1997). We find that the 95% confidence range for the cosmological constant (i.e., the vacuum energy density) is $0.72{\leq}{\Omega}_{\Lambda}{\leq}1.0$ for a flat universe. We also find that the equation of state parameter can be consistent with -1 as long as the matter density ${\Omega}_m{\leq}0.4$ (95% confidence range). We conclude that the image separation statistics incorporating the brightness of lens galaxies can provide robust constraints on the cosmological parameters.

• Journal of Animal Science and Technology
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• 제65권6호
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• pp.1180-1193
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• 2023

Most carcass and meat quality traits are moderate to highly heritable, indicating that they can be improved through selection. Genetic evaluation for these types of traits is performed using performance data obtained from commercial and progeny testing evaluation. The performance data from commercial farms are available in large volume, however, some drawbacks have been observed. The drawback of the commercial data is mainly due to sorting of animals based on live weight prior to slaughter, and this could lead to bias in the genetic evaluation of later measured traits such as carcass traits. The current study has two components to address the drawback of the commercial data. The first component of the study aimed to estimate genetic parameters for carcass and meat quality traits in Korean Hanwoo cattle using a large sample size of industry-based carcass performance records (n = 469,002). The second component of the study aimed to describe the impact of sorting animals into different contemporary groups based on an early measured trait and then examine the effect on the genetic evaluation of subsequently measured traits. To demonstrate our objectives, we used real performance data to estimate genetic parameters and simulated data was used to assess the bias in genetic evaluation. The results of our first study showed that commercial data obtained from slaughterhouses is a potential source of carcass performance data and useful for genetic evaluation of carcass traits to improve beef cattle performance. However, we observed some harvesting effect which leads to bias in genetic evaluation of carcass traits. This is mainly due to the selection of animal based on their body weight before arrival to slaughterhouse. Overall, the non-random allocation of animals into a contemporary group leads to a biased estimated breeding value in genetic evaluation, the severity of which increases when the evaluation traits are highly correlated.

• 경영과학
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• 제27권1호
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• pp.91-105
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• 2010

We proposed and stratified a selection standard model on Open Source Functional Board which could be found in Web. So we could grasp the weight about Performance Evaluation from the viewpoints of planners, developers, and web disigner professional of views. We suggested applying diverse measurement types in case of item which could chart Evaluation Standards on chosen sample boards. In case of item which couldn't do that, we compared and analyzed it by using selective type of 9 point scaling method on professionalists in every sample board. As a result of weight on upper estimate section of evaluation model chart, the order of importance was convenience(0.334), performance(0.333), function(0.240) and design(0.093) respectively. It indicates that there is more weight on performance and convenience which are hard to be structurally modified than designs and functions that are directly shown to the users. Also, it was evident that opposite results came out when using 9-point scale survey and measurement with objective data such as function and performance. The reason is because the surveyed subject can have his or her own subjectivity and bias unlike objective data. However, objectivity of the administrator is also an important factor thus both two perspectives have to be all considered when selecting the bulletin board.