• The Journal of Asian Finance, Economics and Business
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• v.7 no.5
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• pp.259-268
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• 2020

This study aims to provide empirical evidence on the causal relationship between bribery and firm innovation. To this end, we use a micro-dataset of small and medium firms in Vietnam surveyed in 2015. Given the binary nature of the dependent variable, a simple probit regression model is employed. However, as bribery variable is potentially endogenous, a simple probit regression may give biased estimates. We deal with the potential endogeneity by making use of the bivariate probit model. A property of the bivariate probit model is that it can produce efficient estimates of a typical probit model with endogenous binary explanatory variable. A Hausman-like likelihood ratio test is implemented following the estimation to test the existence of endogeneity. We find that bribery significantly undermines firm innovation. Also, firms run by household appear less innovative. The probability of innovation diminishes significantly if firm owners or managers have previous experience in firm products. As expected, larger firms seem to be more innovative. Exporters tend to be more innovative compared to non-exporters. Our findings provide support to the hypothesis that bribery is detrimental to firm innovation and, thus, innovation may be a mediating channel, through which, bribery impedes firm long-term performance.

• Journal of the Korean Data and Information Science Society
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• v.6 no.1
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• pp.1-11
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• 1995

The parameters in the multiplicative model $Y_{1}={\alpha}_{0}{\prod}^{p}_{k=1}X_{kj}^{{\beta}_K}v_{j}$ are usually estimated by the least squares method after logarithmic transformation, and the least square Estimator of ${\alpha}_{0}$ is known to be biased, i.e., $E(e xp(\hat{\beta}_{0})){\neq}{\alpha}_{0})$. In the present study the unbaised estimators of ${\alpha}_{0}$ are examined(1) by modifying the least squares estimator and (2) by applying the Finney's results. The variances are also compared. In addition it has been observed that multiplicative model can be used to express the relationship beetween rice yield and yield components.

• Smart Structures and Systems
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• v.31 no.4
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• pp.383-392
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• 2023

Post-earthquake building condition assessment is crucial for subsequent rescue and remediation and can be automated by emerging computer vision and deep learning technologies. This study is based on an endeavour for the 2nd International Competition of Structural Health Monitoring (IC-SHM 2021). The task package includes five image segmentation objectives - defects (crack/spall/rebar exposure), structural component, and damage state. The structural component and damage state tasks are identified as the priority that can form actionable decisions. A multi-task Convolutional Neural Network (CNN) is proposed to conduct the two major tasks simultaneously. The rest 3 sub-tasks (spall/crack/rebar exposure) were incorporated as auxiliary tasks. By synchronously learning defect information (spall/crack/rebar exposure), the multi-task CNN model outperforms the counterpart single-task models in recognizing structural components and estimating damage states. Particularly, the pixel-level damage state estimation witnesses a mIoU (mean intersection over union) improvement from 0.5855 to 0.6374. For the defect detection tasks, rebar exposure is omitted due to the extremely biased sample distribution. The segmentations of crack and spall are automated by single-task U-Net but with extra efforts to resample the provided data. The segmentation of small objects (spall and crack) benefits from the resampling method, with a substantial IoU increment of nearly 10%.

• Nuclear Engineering and Technology
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• v.54 no.12
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• pp.4644-4651
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• 2022

Due to its short half-life, thoron gas has been assumed to have negligible health hazards on humans compared to radon. But, one of the decay products with a long half-life can make it to be transported to a long distance and to cause a severe internal dose through respiration. Since most commercial radon detectors can not discriminate thoron signals from radon signals, it is very common to overestimate radon doses which in turn result in biased estimation of lung cancer risk in epidemiological studies. Though some methods had been suggested to measure thoron and radon separately, they could not be used for real-time measurement because of CR-39 or LR-115. In this study, an effective method was suggested to measure radon and thoron separately from the free air. It was observed that the activity of thoron decreases exponentially due to delay time caused by a long pipe between two chambers. Therefore from two ion chambers apart in time, it was demonstrated that thoron and radon could be measured separately and simultaneously. We also developed a collimated alpha source and with this source and an SBD, we could convert the ion chamber reading to count rate in cps.

• The KIPS Transactions:PartB
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• v.16B no.2
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• pp.123-130
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• 2009

Motion estimation (ME) plays an important role in digital video compression. But it limits the performance of image quality and encoding speed and is computational demanding part of the encoder. To reduce computational time and maintain the image quality, integer pel and fractional pel ME methods are proposed in this paper. The proposed method for integer pel ME uses a hierarchical search strategy. This strategy method consists of symmetrical cross-X pattern, multi square grid pattern, diamond patterns. These search patterns places search points symmetrically and evenly that can cover the overall search area not to fall into the local minimum and to reduce the computational time. The proposed method for fractional pel uses full search pattern, center biased fractional pel search pattern and the proposed search pattern. According to block sizes, the proposed method for fractional pel decides the search pattern adaptively. Experiment results show that the speedup improvement of the proposed method over Unsymmetrical cross Multi Hexagon grid Search (UMHexagonS) and Full Search (FS) can be up to around $1.2{\sim}5.2$ times faster. Compared to image quality of FS, the proposed method shows an average PSNR drop of 0.01 dB while showing an average PSNR gain of 0.02 dB in comparison to that of UMHexagonS.

• The Korean Journal of Applied Statistics
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• v.26 no.5
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• pp.697-712
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• 2013

When analyzing repeated binary data, the generalized estimating equations(GEE) approach produces consistent estimates for regression parameters even if an incorrect working correlation matrix is used. However, time-varying covariates experience larger changes in coefficients than time-invariant covariates across various working correlation structures for finite samples. In addition, the GEE approach may give biased estimates under missing at random(MAR). Weighted estimating equations and multiple imputation methods have been proposed to reduce biases in parameter estimates under MAR. This article studies if the two methods produce robust estimates across various working correlation structures for longitudinal binary data with time-varying covariates under different missing mechanisms. Through simulation, we observe that time-varying covariates have greater differences in parameter estimates across different working correlation structures than time-invariant covariates. The multiple imputation method produces more robust estimates under any working correlation structure and smaller biases compared to the other two methods.

• Journal of Environmental Health Sciences
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• v.46 no.1
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• pp.65-77
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• 2020

Objectives: This study investigated the average number of drinkers in Korea, the number of high-risk drinkers, the average amount of alcohol consumed by high-risk drinkers, and the types of alcohol consumed according to the characteristics of the group of dependent drinkers. Methods: The results were obtained by analyzing the following data: The Global Status Report on Alcohol and Health; Country Profile 2014; WHO Country Profile 2014; Korea National Health and Nutrition Examination Survey 2014, Korean Statistical Information Service; National Tax Statistics-Liquor Tax; Gallup Drinking Frequency Survey 2015 Results: This study found that a large proportion of drinkers in Korea are already high-risk drinkers, and even among drinkers, alcohol consumption was highly biased. It was reported that 49.8% of men in the problem, abuse, and dependence groups accounted for 92.4% of total alcohol consumption among the male population. Notably, the 9.6% of men making up the dependent group consumed more than 30% of the alcohol ingested among males. Women had significant variations within groups that were considered high-risk and exhibited a large share of alcohol consumption in the problem (10.0% of the female population), abuse (1.8% of the female population), and dependence (1.5% of the female population) groups, constituting 72.8% of total alcohol consumption. The average amount of alcohol consumed by drinkers in Korea seems to have exceeded the level of intake by high-risk groups. Alcohol-dependent groups consumed 900.7 mL of soju, 405.2 mL of table wine, and 2,043.8 mL of beer, which is very similar to the consumption average of 2,031 mL of beer and 895.2 mL of soju in the drinking group. Conclusion: It has been shown that men's dependence on alcohol is serious, and it is possible to infer that alcohol consumption in some vulnerable groups is very high. As the average alcohol intake among alcohol-dependent groups and ordinary drinkers is very similar, it is highly likely that the drinker is an alcohol-dependent consumer in Korea.

• The Korean Journal of Applied Statistics
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• v.14 no.1
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• pp.39-57
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• 2001

Categorical data has sometimes misclassification errors. If this data will be analyzed, then estimated cell probabilities could be biased and the standard Pearson X2 tests may have inflated true type I error rates. On the other hand, if we regard wellclassified data with misclassified one, then we might spend lots of cost and time on adjustment of misclassification. It is a necessary and important step to ask whether categorical data is misclassified before analyzing data. In this paper, when data is misclassified at one of two variables for two-dimensional contingency table and marginal sums of a well-classified variable are fixed. We explore to partition marginal sums into each cells via the concepts of Bound and Collapse of Sebastiani and Ramoni (1997). The double sampling scheme (Tenenbein 1970) is used to obtain informations of misclassification. We propose test statistics in order to solve misclassification problems and examine behaviors of the statistics by simulation studies.

• Journal of Preventive Medicine and Public Health
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• v.43 no.6
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• pp.543-548
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• 2010

Objectives: The objective of this study was to calculate sample size and power in an ongoing cohort, Korea radiation effect and epidemiology cohort (KREEC). Method: Sample size calculation was performed using PASS 2002 based on Cox regression and Poisson regression models. Person-year was calculated by using data from '1993-1997 Total cancer incidence by sex and age, Seoul' and Korean statistical informative service. Results: With the assumption of relative risk=1.3, exposure:non-exposure=1:2 and power=0.8, sample size calculation was 405 events based on a Cox regression model. When the relative risk was assumed to be 1.5 then number of events was 170. Based on a Poisson regression model, relative risk=1.3, exposure:non-exposure=1:2 and power=0.8 rendered 385 events. Relative risk of 1.5 resulted in a total of 157 events. We calculated person-years (PY) with event numbers and cancer incidence rate in the nonexposure group. Based on a Cox regression model, with relative risk=1.3, exposure:non-exposure=1:2 and power=0.8, 136 245PY was needed to secure the power. In a Poisson regression model, with relative risk=1.3, exposure:non-exposure=1:2 and power=0.8, person-year needed was 129517PY. A total of 1939 cases were identified in KREEC until December 2007. Conclusions: A retrospective power calculation in an ongoing study might be biased by the data. Prospective power calculation should be carried out based on various assumptions prior to the study.

• Korean Journal of Community Nutrition
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• v.25 no.2
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• pp.150-158
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• 2020

Objectives: This study was conducted to estimate usual meat intake distribution, which may have been over/underestimated when estimations were made using only the third food codes of the Korea National Health and Nutrition Examination Survey (KNHANES). Methods: For this purpose, 24-hour recall data from the 2009 Korea National Health and Nutrition Examination Survey, which conducted a partial 2-day survey of food intake, were used. The Multiple Source Method (MSM) was used to estimate the distribution of the usual intake of red and processed meats. Results: The results of this study show that the mean intake of red meat was 45.07 g while that of processed meat was 4.33 g. These results are slightly higher than the consumption calculated using only tertiary food code, and the difference was statistically significant. Furthermore, characteristics of the estimated usual intake distribution were a smaller standard deviation, increased lower percentiles, and decreased upper percentiles compared to the 2-day mean intake distribution for both red and processed meats. The proportion of individuals not consuming red meat decreased substantially from approximately 37% to 0.7%. The proportion of consumption that exceeded 90 g, which is the upper limit of red meat intake recommended by the National Health Service (NHS), was only approximately 10% in the distribution of usual intake. Conclusions: As the consumption of processed foods is expected to continuously increase, caution is needed regarding the processes used to calculate food (group) intake to avoid over/underestimation. Moreover, use of KNHANES data to calculate the proportion of the population at risk of insufficiency or excess intake of certain nutrients or food (group), based on one day intake that does not address within-individual variation, may lead to biased estimates.