• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.11 no.2
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• pp.161-168
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• 2001

The types of exposure data needed in an industry-based study depend on the diseases of interest and the study design to be used. The best situation occurs when we have quantified personal exposure estimates for the agents of interest, the least informative case occurs when we have only knowledge of the fact of employment in a plant, industry, or trade where exposure probability is high. Exposure information for most industry-based studies falls somewhere between these tow extremes. Job exposure matrices(JEM) are designed to link information on occupation with information on exposure to specific workplace hazards. Some forms of systematic error of bias may be less likely to occur in studies that utilize job-exposure matrices to indirectly infer exposures from job titles than in studies that assess exposures by asking subjects about their past exposure. JEM can be used effectively in industry-based studies for historic cohort studies, case-control study to assist with the retrospective assessment of occupational exposures among workers whose individual exposure histories are unavailable. JEM generally consist of a computerized database that links information about job categories and likely exposures. These two major axes may be stratified by calendar time. This article reviews the design of JEM in support of industry-based studies. Specific matrices may find broader applicability along with the increasing availability of detailed hygienic data.

• Asian-Australasian Journal of Animal Sciences
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• v.21 no.8
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• pp.1109-1115
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• 2008

The reproduction component traits are important components of sow efficiency. The objective of this study was to evaluate the phenotypic and genetic parameters of four reproduction component traits (age at puberty (AP), preweaning number dead (PND), weaning to service interval (WSI), and intra-individual SD in litter size (IISDLS)) of sows in two Chinese indigenous pig breeds. Available reproductive records including 22,591 piglets born from 2,054 litters by 574 Jiangquhai sows and 464 Meishan sows were used in this investigation. A set of mixed models and restricted maximum likelihood methodology were used for the multiple trait analyses of these traits. The results showed that the estimates of heritabilities (${\pm}$standard error) for AP, PND, WSI and IISDLS were $0.40{\pm}0.05$, $0.06{\pm}0.03$, $0.20{\pm}0.02$ and 0.09{\pm}0.03 in Jiangquhai sows, and $0.35{\pm}0.06$, $0.05{\pm}0.03$, $0.18{\pm}0.03$ and $0.10{\pm}0.04$ in Meishan sows, respectively. There was moderate genetic correlation between AP and WSI, while there were low genetic correlations between the other pairwise traits. The genetic correlations were positive for most of the pairwise traits, except for the one between AP and IISDLS. The results indicated that all traits except for AP were difficult to make genetic improvement by traditional selection methods due to low heritabilities and the favorable improvement of AP might result in unfavorable changes of IISDLS due to the trend of genetic antagonism.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.6
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• pp.19-27
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• 2010

This paper proposes a method for enhancing detection performance and reducing computational cost when detecting a human face by applying B-spline active contour to the frame difference of consecutive images. Firstly, the method estimates amount of user's motion using kurtosis. If the kurtosis is smaller than a pre-defined threshold, it is considered that the amount of user's motion is insufficient and thus the contour fitting is not applied. Otherwise, the contour fitting is applied by exploiting the fact that the amount of motion is sufficient. Secondly, for the contour fitting, difference edges are detected by combining the distance transformation of the binarized frame difference and the edges of current frame. Lastly, the face is located by assigning the contour fitting process to the detected difference edges. Kurtosis-based motion amount estimation can reduce a computational cost and stabilize the results of the contour fitting. In addition, distance transformation-based difference edge detection can enhance the problems of contour lag and discontinuous difference edges. Experimental results confirm that the proposed method can reduce the face localization error caused by the contour lag and discontinuity of edges, and decrease the computational cost by omitting approximately 39% of the contour fitting.

• Journal of the Korean Geotechnical Society
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• v.31 no.11
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• pp.41-48
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• 2015

An investigation of a void and a loose layer of the ground is essential in order to prevent the losses of life and properties caused by subsidence and sinkage of the ground. Recently, studies on the ground penetrating radar survey have been actively conducted in order to estimate the void and the loose layer of the ground. However, an error can be committed by contrarily predicting a dense ground and a loose layer because the ground penetrating radar estimates an interface depth between geo-materials that have different electrical impedances. In this study, a loose ground depth is estimated using the characteristics of the reflected electromagnetic wave obtained from the ground penetrating radar survey. To gather the signals according to the loose ground depths, the ground penetrating radar survey is conducted on a field which underwent a huge ground settlement. In addition, the dynamic cone penetration test is performed to verify the result of the loose ground depth estimation from the ground penetrating radar survey. From the analysis of the reflection characteristics of the electromagnetic wave, a phase of an electromagnetic wave reflected from a denser soil layer is found to be identical with that of the first measured signal. On the other hand, a phase of an electromagnetic wave reflected from the loose soil layer is found to be opposed to that of the first detected signal. The comparison between the dynamic cone penetration index and electromagnetic signals by the ground penetrating radar shows that the estimated depth of the loose or dense layer is perfectly matched with a high reliability. The ground penetrating radar survey and the signal analysis performed in this study can be used not only for the survey of interface depth between the discontinuity layers but also for the estimation of the loose layer.

• Journal of Korea Water Resources Association
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• v.43 no.1
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• pp.81-94
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• 2010

Input variable selection is one of the various techniques for improving the performance of artificial neural network. In this study, mutual information is applied for input variable selection technique instead of correlation coefficient that is widely used. Among 152 variables of RDAPS (Regional Data Assimilation and Prediction System) output results, input variables for artificial neural network are chosen by computing mutual information between rainfall records and RDAPS' variables. At first the rainfall forecast variable of RDAPS result, namely APCP, is included as input variable and the other input variables are selected according to the rank of mutual information and correlation coefficient. The input variables using mutual information are usually those variables about wind velocity such as D300, U925, etc. Several statistical error estimates show that the result from mutual information is generally more accurate than those from the previous research and correlation coefficient. In addition, the artificial neural network using input variables computed by mutual information can effectively reduce the relative errors corresponding to the high rainfall events.

• Journal of Broadcast Engineering
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• v.19 no.6
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• pp.866-876
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• 2014

Generating of digital hologram of video contents with computer graphics(CG) requires natural fusion of 3D information between real and virtual. In this paper, we propose the system which can fuse real-virtual 3D information naturally and fast generate the digital hologram of fused results using multiple-GPUs based computer-generated-hologram(CGH) computing part. The system calculates camera projection matrix of RGB-Depth camera, and estimates the 3D information of virtual object. The 3D information of virtual object from projection matrix and real space are transmitted to Z buffer, which can fuse the 3D information, naturally. The fused result in Z buffer is transmitted to multiple-GPUs based CGH computing part. In this part, the digital hologram of fused result can be calculated fast. In experiment, the 3D information of virtual object from proposed system has the mean relative error(MRE) about 0.5138% in relation to real 3D information. In other words, it has the about 99% high-accuracy. In addition, we verify that proposed system can fast generate the digital hologram of fused result by using multiple GPUs based CGH calculation.

• Asian-Australasian Journal of Animal Sciences
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• v.23 no.11
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• pp.1445-1454
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• 2010

Two separate animal trials were conducted to evaluate the coincidence of dry matter intake (DMI) and average daily gain (ADG) predicted by the Cornell Net Carbohydrate and Protein System (CNCPS) and observed actually in crossbred growing bulls kept in a traditionally confined feeding system in China. In Trial 1, 45 growing Simmental${\times}$Mongolia crossbred F1 bulls were assigned to three treatments (T1-3) with 15 animals in each treatment. Trial 2 was conducted with 60 Limousin${\times}$Fuzhou crossbred F2 bulls allocated to 4 treatments (t1-4). All of the animals were confined in individual stalls. DMI and ADG for each bull were measured as a mean of each treatment. All of the data about animals, environment, management and feeds required by the CNCPS model were collected, and model predictions were generated for animals on each treatment. Subsequently, model-predicted DMI and ADG were compared with the actually recorded results. In the three treatments in Trial 1, 93.3, 80.0 and 73.3% of points fell within the range from -0.4 to 0.4 kg/d for DMI mean bias; similarly, in the four treatments in Trial 2, about 86.7, 73.3, 73.3 and 80.0% of points fell within the same range. These results indicate that the CNCPS model can accurately predict DMI of crossbred bulls in the traditionally confined feeding system in China. There were no significant differences between predicted and observed ADG for T1 (p = 0.06) and T2 (p = 0.09) in Trial 1, and for t1 (p = 0.07), t2 (p = 0.14) and t4 (p = 0.83) in Trial 2. However, significant differences between predicted and observed ADG values were observed for T3 in Trial 1 (p<0.01) and for t3 in Trial 2 (p = 0.04). By regression analysis, a statistically different value of intercept from zero for the regression equation of DMI (p<0.01) or an identical value of ADG (p = 0.06) were obtained, whereas the slopes were significantly different (p<0.01) from unity for both DMI and ADG. Additionally, small root mean square error (RMSE) values were obtained for the unbiased estimator of the two variances (DMI and ADG). Thus, the present results indicated that the CNCPS model can give acceptable estimates of DMI and ADG of crossbred growing bulls kept in a traditionally confined feeding system in China.

• The KIPS Transactions:PartD
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• v.8D no.2
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• pp.154-165
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• 2001

A number of attempts to develop methods for measuring software effort have been focused on the area of software engineering and many models have also been suggested to estimate the effort of software projects. Almost all current models use algorithmic or statistical mechanisms, but the existing algorithmic effort estimation models have failed to produce accurate estimates. Furthermore, they are unable to reflect the rapidly changing technical environment of software development such as module reuse, 4GL, CASE tool, etc. In addition, these models do not consider the paradigm shift of software engineering and information systems(i.e., Object Oriented system, Client-Server architecture, Internet/Intranet based system etc.). Thus, a new approach to software effort estimation is needed. After reviewing and analyzing the problems of the current estimation models, we have developed a model and a system architecture that will improve estimation performance. In this paper, we have adopted a neural network model to overcome some drawbacks and to increase estimation performance. We will also address the efficient system architecture and estimation procedure by a similar case-based approach and finally suggest the heuristic search method to find the best estimate of target project through empirical experiments. According to our experiment with the optimally parsimonious neural network model the mean error rate was significantly reduced to 14.3%.

• Asian-Australasian Journal of Animal Sciences
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• v.33 no.7
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• pp.1057-1067
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• 2020

Objective: This study evaluated the effect of pedigree errors (PEs) on the accuracy of estimated breeding value (EBV) and genetic gain for carcass traits in Korean Hanwoo cattle. Methods: The raw data set was based on the pedigree records of Korean Hanwoo cattle. The animals' information was obtained using Hanwoo registration records from Korean animal improvement association database. The record comprised of 46,704 animals, where the number of the sires used was 1,298 and the dams were 38,366 animals. The traits considered were carcass weight (CWT), eye muscle area (EMA), back fat thickness (BFT), and marbling score (MS). Errors were introduced in the pedigree dataset through randomly assigning sires to all progenies. The error rates substituted were 5%, 10%, 20%, 30%, 40%, 50%, 60%, 70%, and 80%, respectively. A simulation was performed to produce a population of 1,650 animals from the pedigree data. A restricted maximum likelihood based animal model was applied to estimate the EBV, accuracy of the EBV, expected genetic gain, variance components, and heritability (h²) estimates for carcass traits. Correlation of the simulated data under PEs was also estimated using Pearson's method. Results: The results showed that the carcass traits per slaughter year were not consistent. The average CWT, EMA, BFT, and MS were 342.60 kg, 78.76 ㎠, 8.63 mm, and 3.31, respectively. When errors were introduced in the pedigree, the accuracy of EBV, genetic gain and h² of carcass traits was reduced in this study. In addition, the correlation of the simulation was slightly affected under PEs. Conclusion: This study reveals the effect of PEs on the accuracy of EBV and genetic parameters for carcass traits, which provides valuable information for further study in Korean Hanwoo cattle.

• Journal of Biomedical Engineering Research
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• v.28 no.4
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• pp.569-576
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• 2007

Ventricular Assist Device(VAD) has switched its goal from a short-tenn use for bridge-to-transplantation to a long-tenn use for destination therapy, With this goal, the importance of long-tenn reliability gets more interests and importances, H-VAD is an portable extracorporeal biventricular assist device, and adopts an electro-pneumatic driving mechanism. The pneumatic pressure to pump out blood is generated with compression of bellows, and is transmitted in a closed pneumatic circuit through a pneumatic line. The existing pneumatic VAD adopts a air compressor which can generate stable pressures but has defects such as a noise and a size problem. Thus, it is not suitable for being used as a portable device, These problems are covered with adopting a closed pneumatic circuit mechanism with a bellows which has a small size and small noise generation, but it has defects that improper pneumatic setting causes a failure of adequate flow generation. In this study, the pneumatic pressure regulation system is developed to cover these defects of a bellows-type pneumatic VAD. The optimal pneumatic pressure conditions according to various afterload conditions for an optimal flow rate were investigated and the afterload estimation algorithm was developed, The final pneumatic regulation system estimates a current afterload and regulate the pneumatic pressure to the optimal point at a given afterload condition. The afterload estimation algorithm showed a sufficient performance that the standard deviation of error is 8.8 mmHg, The pneumatic pressure regulation system showed a sufficient performance that the flow rate was stably governed to various afterload conditions. In a further study, if a additional sensor such as ultrasonic sensor is developed to monitor the direct movement of diaphragm in a blood pump part, the reliability would be greatly increased. Moreover, if the afterload estimation algorithm gets more accuracy, it would be also helpful to monitor the hemodynamic condition of patients.