• Tribology and Lubricants
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• v.35 no.1
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• pp.1-8
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• 2019

Demand for plastic gears are increasing in many industries due to their low production cost, light weight, applicability without lubricant, corrosion resistance and high resilience. Despite these benefits, utilizing plastic gears is limited due to their poor material properties. In this work, DLC coating was applied to improve the tribological properties of polyamide66 gear. 0 V, 40 V, and 70 V of negative bias voltages were selected as a deposition parameter in DC magnetron sputtering system. Pin-on-disk experiment was performed in order to investigate the wear characteristics of the gears. The results of the pin-on-disk experiment showed that DLC coated polyamide66 with 40 V of negative bias voltage had the lowest friction coefficient value (0.134) and DLC coated PA66 with 0 V of negative bias voltage showed the best wear resistance ($9.83{\times}10^{-10}mm^3/N{\cdot}mm$) among all the specimens. Based on these results, durability tests were conducted for DLC coated polyamide66 gears with 0 V of negative bias voltage. The tests showed that the temperature of the uncoated polyamide66 gear increased to about $37^{\circ}C$ while the DLC coated gear saturated at about $25^{\circ}C$. Also, the power transmission efficiency of the DLC coated gear increased by about 6% compared to those without coating. Weight loss of the polyamide66 gears were reduced by about 73%.

• Communications for Statistical Applications and Methods
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• v.12 no.1
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• pp.169-179
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• 2005

In this study, we investigate the effects of the weight function in the bounded influence regression quantile (BIRQ) estimator for the AR(l) model with additive outliers. In order to down-weight the outliers of X -axis, the Mallows' (1973) weight function has been commonly used in the BIRQ estimator. However, in our Monte Carlo study, the BIRQ estimator using the Tukey's bisquare weight function shows less MSE and bias than that of using the Mallows' weight function or Huber's weight function. Thus, the use of the Tukey's weight function is recommended in the BIRQ estimator for our model.

• Nutrition Research and Practice
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• v.12 no.4
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• pp.283-290
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• 2018

BACKGROUND/OBJECTIVES: Indirect calorimetry is the gold-standard method for the measurement of resting energy expenditure. However, this method is time consuming, expensive, and requires highly trained personnel. To overcome these limitations, various predictive equations have been developed. The objective of this study was to assess the validity of predictive equations for resting energy expenditure (REE) in Korean non-obese adults. SUBJECTS/METHODS: The present study involved 109 participants (54 men and 55 women) aged between 20 and 64 years. The REE was measured by indirect calorimetry. Nineteen REE equations were evaluated for validity, by comparing predicted and measured REE results. Predictive equation accuracy was assessed by determining percent bias, root mean squared prediction error (RMSE), and percentage of accurate predictions. RESULTS: The measured REE was significantly higher in men than in women (P < 0.001), but the difference was not significant after adjusting for body weight (P > 0.05). The equation developed in this study had an accuracy rate of 71%, a bias of 0%, and an RMSE of 155 kcal/day. Among published equations, the $FAO_{weight}$ equation gave the highest accuracy rate (70%), along with a bias of -4.4% and an RMSE of 184 kcal/day. CONCLUSIONS: The newly developed equation provided the best accuracy in predicting REE for Korean non-obese adults. Among the previously published equations, the $FAO_{weight}$ equation showed the highest overall accuracy. Regardless, at an individual level, the equations could lead to inaccuracies in a considerable number of subjects.

• Proceedings of the Korean Association for Survey Research Conference
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• 2003.06a
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• pp.19-28
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• 2003

Weighting adjustment is a method of improving the efficiency of the estimator by incorporating auxiliary variables at the estimation stage. One commonly used method of weighting adjustment is the poststratification, which is a special case of regression estimation but is relatively feasible in terms of actual implementation. If too many auxiliary variables are used in the poststratification, the bias of the resulting point estimator is no longer negligible and the final weights may have extreme weights. In this study, we propose a method of weight ing adjustment that compromises the efficiency and the bias of the point estimator. A limited simulation study is also presented.

• Survey Research
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• v.10 no.1
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• pp.169-186
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• 2009

The propensity score method is used to minimize the bias level in social survey, which comes from nonresponse. The theoretical concept and the background of the propensity score method is discussed first. The propensity score method was first applied in the epidemiology observational study. I have summarized the process of the three propensity score methods that were used to reduce estimation bias in this study. Matching by propensity score is applied to the relatively large control group. Subclassification has the advantage of using whole control group data and regression adjustment is applied to multiple covariates as well as propensity score of each unit is computable and usable. Lastly, the application procedures of propensity score method to reduce the nonresponse bias is suggested and its applicability to real situation is reviewed with the existing data.

• Journal of the Korean Society of Clothing and Textiles
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• v.28 no.6
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• pp.776-783
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• 2004

The purpose of this study was to identify the reasonable gathering conditions as consider of effect of gathering and variation of silhouette made by gathering conditions. The experimental design consists of four factorial design: (1) three kinds of different weight and different thickness fabrics (2) three kinds of different stitch densities (3) five kinds of different ratio of gathers (4) three kinds of different angles. Therefore one hundred thirty five (135) samples were made. Data analysis utilize SPSS WIN 10.0 Package. The results of this study were as follows: 1. In the aspect of fabrics, it is shown the visual propriety that it is as thin as the small stitch, and as thick as the big stitch. 2. As stitch densities, it shows the different stabilized nodes. 3. In the aspect of ratio of gathers, it is shown the visual propriety that a few was small stitches, which help formations of nodes, and a lot were big stitches, which help increased the effect of gather. 4. In the aspect of angle of bias, the drape appearance was excellent as a sample of cutting by 0 angle(0$^{\circ}$) of bias. The big stitches that help formations of stabilized nodes, and a case of cutting by 45 angle(45$^{\circ}$) of bias was small stitch.

• Nutrition Research and Practice
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• v.6 no.1
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• pp.51-60
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• 2012

Weight-controlling can be supported by a proper prescription of energy intake. The individual energy requirement is usually determined through resting energy expenditure (REE) and physical activity. Because REE contributes to 60-70% of daily energy expenditure, the assessment of REE is very important. REE is often predicted using various equations, which are usually based on the body weight, height, age, gender, and so on. The aim of this study is to validate the published predictive equations for resting energy expenditure in 76 normal weight and 52 obese Korean children and adolescents in the 7-18 years old age group. The open-circuit indirect calorimetry using a ventilated hood system was used to measure REE. Sixteen REE predictive equations were included, which were based on weight and/or height of children and adolescents, or which were commonly used in clinical settings despite its use based on adults. The accuracy of the equations was evaluated on bias, RMSPE, and percentage of accurate prediction. The means of age and height were not significantly different among the groups. Weight and BMI were significantly higher in obese group (64.0 kg, $25.9kg/m^2$) than in the non-obese group (44.8 kg, $19.0kg/m^2$). For the obese group, the Molnar, Mifflin, Liu, and Harris-Benedict equations provided the accurate predictions of > 70% (87%, 79% 77%, and 73%, respectively). On the other hand, for non-obese group, only the Molnar equation had a high level of accuracy (bias of 0.6%, RMSPE of 90.4 kcal/d, and accurate prediction of 72%). The accurate prediction of the Schofield (W/WH), WHO (W/WH), and Henry (W/WH) equations was less than 60% for all groups. Our results showed that the Molnar equation appears to be the most accurate and precise for both the non-obese and the obese groups. This equation might be useful for clinical professionals when calculating energy needs in Korean children and adolescents.

• Journal of the Korean Statistical Society
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• v.30 no.1
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• pp.77-87
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• 2001

Some asymptotic results on the local likelihood density estimator of Copas(1995) are derived when the locally parametric model has several parameters. It turns out that it has the same asymptotic mean squared error as that of Hjort and Jones(1996).

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.2
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• pp.625-633
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• 2013

Multiple response surface optimization (MRSO) aims at finding a setting of input variables which simultaneously optimizes multiple responses. The minimization of mean squared error (MSE), which consists of the squared bias and variance terms, is an effective way to consider the location and dispersion effects of the responses in MRSO. This approach basically assumes that both the terms have an equal weight. However, they need to be weighted differently depending on a problem situation, for example, in case that they are not of the same importance. This paper proposes to use the weighted MSE (WMSE) criterion instead of the MSE criterion in MRSO to consider an unequal weight situation.

• Korean Journal of Organic Agriculture
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• v.19 no.4
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• pp.565-575
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• 2011

Recently, the use of antibiotics to improve animal productivity in livestock industry was strictly restricted. For these reason, probiotics have been regarded as one of promising materials for an antibiotic alternative. In this study, we investigated how the probiotics influences on the performance of broiler chicken via meta-analysis. Eighteen researches from 1997 to 2010 were used for meta-analysis. The standard summary effects were calculated via fixed effect model and random effect model (Borenstein et al., 2009). Heterogeneity was calculated by using the Cochran's Q statistics (Kook et al., 2009) and publication bias was calculated via Egger's regression (Lee et al., 2011). In fixed model average daily gain, body weight serum protein content and cecal LAB showed positive effect significantly. Feed intake, feed/gain and serum cholesterol showed significant negative effect. In serum triglyceride, negative effect was found but significance was not shown. In random model, average daily gain body weight and cecal LAB showed positive effects with significance and feed/gain and serum cholesterol represented significant negative effects. Publication bias was found only in feed/gain.