Journal of Korea Entertainment Industry Association
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v.13
no.1
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pp.99-109
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2019
The study was conducted to investigate the activities of working people in the sports club. The subject of this study was to take samples of workers who participated in the physical education system using the convenience sampling method. Out of a total of 400 questionnaires, 387 were used for research purposes, except for invalid or error questionnaires. Factor analysis and reliability tests were performed using IBM SPSS statistics Ver 21.0. Frequency analysis was conducted to explore the general characteristics of the study participants. An independent sample t-test ANOVA were conducted to verify differences among groups according to demographic characteristics, and a correlation analysis was conducted to examine the relationship between variables. Regression was performed to verify the effect of variable factors. The results of the study are as follows. First, there was no difference in wellness and job satisfaction according to gender. Second, there was no difference in wellness and job satisfaction according to sport. Third, there was a significant difference intellectual wellness according to age. In particular, 40s and 50s were higher than 60s and over. Fourth, there was a significant difference in social wellness according to activity duration. In particular, 1~2 years were higher than 3 years or more. Finally, If you look at the impact of working people's wellness lifestyle sports club activities on job satisfaction, the professional wellness lifestyle club activities showed significant influence on job satisfaction.
In-Ung Song;Woo-Sung Kwon;Hagyong Khim;Yun-Woo Lee;Jong Ung Lee;Ho-Soon Yang
Korean Journal of Optics and Photonics
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v.34
no.3
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pp.117-123
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2023
The size of an optical surface can significantly affect the performance of an optical system, and high spatial frequency errors have a greater impact. Therefore, it is crucial to measure the surface figure error with high frequency. To address this, a new method called rotational prism stitching interferometer (RPSI) is proposed in this study. The RPSI is a type of stitching interferometer that enhances spatial resolution, but it differs from conventional stitching interferometers in that it does not require the movement of either the mirror tested or the interferometer itself to obtain sub-aperture interferograms. Instead, the RPSI uses a beam expander and a rotating Dove prism to select particular sub-apertures from the entire aperture. These sub-apertures are then stitched together to obtain a full-aperture result proportional to the square of the beam expander's magnification. The RPSI's effectiveness was demonstrated by measuring a 40 mm diameter spherical mirror using a three-magnification beam expander and comparing the results with those obtained from a commercial interferometer. The RPSI achieved surface testing results with nine times higher sampling density than the interferometer alone, with a small difference of approximately 1 nm RMS.
The N-value from the Standard Penetration Test (SPT), which is one of the representative in-situ test, is an important index that provides basic geological information and the depth of the bearing layer for the design of geotechnical structures. In the aspect of time and cost-effectiveness, there is a need to carry out a representative sampling test. However, the various variability and uncertainty are existing in the soil layer, so it is difficult to grasp the characteristics of the entire field from the limited test results. Thus the spatial interpolation techniques such as Kriging and IDW (inverse distance weighted) have been used for predicting unknown point from existing data. Recently, in order to increase the accuracy of interpolation results, studies that combine the geotechnics and deep learning method have been conducted. In this study, based on the SPT results of about 22,000 holes of ground survey, a comparative study was conducted to predict the depth of the bearing layer using deep learning methods and IDW. The average error among the prediction results of the bearing layer of each analysis model was 3.01 m for IDW, 3.22 m and 2.46 m for fully connected network and PointNet, respectively. The standard deviation was 3.99 for IDW, 3.95 and 3.54 for fully connected network and PointNet. As a result, the point net deep learing algorithm showed improved results compared to IDW and other deep learning method.
Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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v.40
no.1
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pp.51-66
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2022
SST (Sea Surface Temperature) is based on the atmosphere-ocean interaction, one of the most important mechanisms for the Earth system. Because it is a crucial oceanic and meteorological factor for understanding climate change, gap-free grid data at a specific spatial and temporal resolution is beneficial in SST studies. This paper examined the production of daily SST grid maps from 137 stations in 2020 through the ordinary kriging with variogram optimization and their accuracy assessment. The variogram optimization was achieved by WLS (Weighted Least Squares) method, and the blind tests for the interpolation accuracy assessment were conducted by an objective and spatially unbiased sampling scheme. The four-round blind tests showed a pretty high accuracy: a root mean square error between 0.995 and 1.035℃ and a correlation coefficient between 0.981 and 0.982. In terms of season, the accuracy in summer was a bit lower, presumably because of the abrupt change in SST affected by the typhoon. The accuracy was better in the far seas than in the near seas. West Sea showed better accuracy than East or South Sea. It is because the semi-enclosed sea in the near seas can have different physical characteristics. The seasonal and regional factors should be considered for accuracy improvement in future work, and the improved SST can be a member of the SST ensemble around South Korea.
Hyo Sang Lee;Yeongkuk Kim;Doo Ho Lee;Dongwon Seo;Dong Jae Lee;Chang Hee Do;Phuong Thanh N. Dinh;Waruni Ekanayake;Kil Hwan Lee;Duhak Yoon;Seung Hwan Lee;Yang Mo Koo
Journal of Animal Science and Technology
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v.65
no.4
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pp.720-734
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2023
In Korea, Korea Proven Bulls (KPN) program has been well-developed. Breeding and evaluation of cows are also an essential factor to increase earnings and genetic gain. This study aimed to evaluate the accuracy of cow breeding value by using three methods (pedigree index [PI], pedigree-based best linear unbiased prediction [PBLUP], and genomic-BLUP [GBLUP]). The reference population (n = 16,971) was used to estimate breeding values for 481 females as a test population. The accuracy of GBLUP was 0.63, 0.66, 0.62 and 0.63 for carcass weight (CWT), eye muscle area (EMA), back-fat thickness (BFT), and marbling score (MS), respectively. As for the PBLUP method, accuracy of prediction was 0.43 for CWT, 0.45 for EMA, 0.43 for MS, and 0.44 for BFT. Accuracy of PI method was the lowest (0.28 to 0.29 for carcass traits). The increase by approximate 20% in accuracy of GBLUP method than other methods could be because genomic information may explain Mendelian sampling error that pedigree information cannot detect. Bias can cause reducing accuracy of estimated breeding value (EBV) for selected animals. Regression coefficient between true breeding value (TBV) and GBLUP EBV, PBLUP EBV, and PI EBV were 0.78, 0.625, and 0.35, respectively for CWT. This showed that genomic EBV (GEBV) is less biased than PBLUP and PI EBV in this study. In addition, number of effective chromosome segments (Me) statistic that indicates the independent loci is one of the important factors affecting the accuracy of BLUP. The correlation between Me and the accuracy of GBLUP is related to the genetic relationship between reference and test population. The correlations between Me and accuracy were -0.74 in CWT, -0.75 in EMA, -0.73 in MS, and -0.75 in BF, which were strongly negative. These results proved that the estimation of genetic ability using genomic data is the most effective, and the smaller the Me, the higher the accuracy of EBV.
To determine the quality control of UGIS, we acquired 105 patients sampling image at 21 general screening centers. The results of image quality evaluation table containing two countries's UGIS showed that the mean of image qualified education table of our country was 73.3 and the standard error was 4.49; In addition, 19 organizations of 21 general screening centers were given appropriate judgement. The average of image qualified education table of Japan was 58 and the standard error was 4.45. Only 8 organizations were given appropriate judgement. Although we made the image quality evaluation tables with same images, there were many differences in the result of two tables. We figured out the problem about the description of whole stomach and photograph skills. Furthermore, we analysed the situation of the UGIS at each general screening center with the acquired images. The biggest problem of the UGIS of our country was that the procedures were performed without clear medical methods. Methods of UGIS were different at every 21 general screening centers, and most of them did not take exam of anterior surface of stomach of the UGIS. In addition, some general screening centers did not include mucosal relief method or esophagography which is required to include in the image qualified education table of our country. Because polisography is used in the same body position, the problem occured about indiscreet exposure dose of patients. Therefore we have to make an effort to get X-ray images which have enough diagnosis information by the quality control of UGIS.
Purpose: The aim of this study was to develop a bioinformatics software and to test it in serum samples of papillary thyroid cancer using mass spectrometry (SELDI-TOF-MS). Materials and Methods: Development of 'Protein analysis' software performing decision tree analysis was done by customizing C4.5. Sixty-one serum samples from 27 papillary thyroid cancer, 17 autoimmune thyroiditis, 17 controls were applied to 2 types of protein chips, CM10 (weak cation exchange) and IMAC3 (metal binding - Cu). Mass spectrometry was performed to reveal the protein expression profiles. Decision trees were generated using 'Protein analysis' software, and automatically detected biomarker candidates. Validation analysis was performed for CM10 chip by random sampling. Results: Decision tree software, which can perform training and validation from profiling data, was developed. For CM10 and IMAC3 chips, 23 of 113 and 8 of 41 protein peaks were significantly different among 3 groups (p<0.05), respectively. Decision tree correctly classified 3 groups with an error rate of 3.3% for CM10 and 2.0% for IMAC3, and 4 and 7 biomarker candidates were detected respectively. In 2 group comparisons, all cancer samples were correctly discriminated from non-cancer samples (error rate = 0%) for CM10 by single node and for IMAC3 by multiple nodes. Validation results from 5 test sets revealed SELDI-TOF-MS and decision tree correctly differentiated cancers from non-cancers (54/55, 98%), while predictability was moderate in 3 group classification (36/55, 65%). Conclusion: Our in-house software was able to successfully build decision trees and detect biomarker candidates, therefore it could be useful for biomarker discovery and clinical follow up of papillary thyroid cancer.
Jintaek Kang;Chiung Ko;Jeongmuk Park;Jongsu Yim;Sun-Jeong Lee;Myoungsoo Won
Journal of Korean Society of Forest Science
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v.112
no.4
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pp.472-489
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2023
This study was conducted to derive the optimal estimation equations for deriving the green and dry weights of Larix kaempferi (Japanese larch) and Pinus rigida (Rigida pine), which are major coniferous tree species in South Korea. The equations were then used to develop weight tables. Table development began with the sampling of 150 L. kaempferi and 90 P. rigida trees distributed throughout the national scale, after which green weights were measured on-site. Samples from each stand were then collected, and their dry weights were measured in a laboratory. The equation used to calculate green and dry weights was divided into a one-variable formula that uses only the diameter at breast height (DBH) and a two-variable equation that employs DBH and height. The equations used to estimate the green and dry weights of logs were divided into one- and two-variable equations using DBH. Statistical data, such as the fitness index (FI), root mean square error, standard error of estimation, and residual diagram, were used to verify the suitability of the estimation equations. Applicability was examined by calculating weights using the derived optimal equations. The equation W = bD+cD2 was used in measurements involving only DBH, whereas the equation W = aDbHc was employed in cases involving both diameter and height at breast height. The FI of W = bD+cD2 was 0.91, while that of W = aDbHc was 0.95, both of which are high values. With these estimation formulas, weight tables for the green and dry weights of L. kaempferi and P. rigida were prepared and compared with weight tables created 20 years ago. The green and dry weight tables of both species were larger.
We used the health screening data of some rural and urban residents to examine the cross-sectional association between leukocyte count and hypertension. The 206 male and 203 female rural residents were selected by multi-stage cluster sampling method in Kyungsan-Kun area of Kyungbuk province in 1985 and 600 urban residents were selected by the same sampling method as the rural residents in Daegu city of the same province in 1986 compatible with age-sex distribution of Daegu city of 1985 census, but of whom 384 actually responded. The rest of 600 were replaced by age and sex with those who were members of the medical insurance plan visiting the health management department of the university hospital to get the biannual preventive medical checkups. Excluded in the analysis were those having hypertensive history, diseases and extreme outlying values of the screening tests, leaving 373 rural and 571 urban residents. Leukocyte count was measured with ELT-8 Laser shadow method and the unit $cells/mm^3$, Blood pressures were determined with an aneroid sphygmomanometer with pre-standardized method and hypertensives were defined as those showing systolic blood pressure more than 140mmHg and/or diastolic blood pressure more than 90mmHg. Total residents pooled (N=944) showed a significant difference between hypertensives and normotensives ($6965.93{\pm}1997.01\;vs\;6490.61{\pm}1941.32,\;P=0.00$) and in rural residents was noted the similar significant difference (P=0.03). None of significant differences were noted in any stratum stratified by residency and sex. Compared to the lowest quintile of WBC, 2/5 quintile showed odds ratio 0.99 (95% Confidence interval, Ci 0.62-1.59), 3/5 quintile 1.41 (95% CI 0.90-2.21), 4/5 quintile 1.76 (95% CI. 1.14-2.72), and highest quintile 1.80 (1.15-2.82) in the total residents. Likelihood ratio test for linear trend for it indicated a significant trend ($X^2_{trend}=5.53,\;df=1,\;P<0.05$). There were no other significant odds ratios compared to the lowest quintile of WBC in strata stratified by residency and sex. The odds ratios in total residents which had showed significant odds ratios became nonsignificant and of reduced magnitude after controlling age, frequency of smoking and drinking with multiple logistic. regression. In each stratum, it changed magnitudes of odds ratios slightly and unstably. None of the trend tests showed any significant trend. These results suggest that the Friedman et al's finding of association between leukocyte count and hypertension may be due to an statistical type I error resulting from the data dredging in an exploratory study, in which more than 800 variables were screened as possible predictors of hypertension.
Observations were made on the blood picture of total 196 heads of healthy Korean cattles, including 98 males and females in the purpose of determination of blood chemical values and their sex differences and seasonal variations during one year period from December, 1963 to November, 1964. The blood sampling were scheduled by random in four different seasons and the sample size of both sex included in each season were designated to be same size. The ranges, averages or mean values of the blood glucose, total serum protein, serum globulin, serum albumin, total non-protein nitrogen, blood urea nitrogn, total serum cholesterol, serum inorganic phosphorus and serum calcium were determined in this studies and their respective standard deviation, standard error of means, sex differences and seasonal variations were as follows. 1. The blood glucose values for the male ranged from 32.8 to 70.0 mg/100cc. with a mean of $49.781{\pm}0.823mg/100cc$; for the female the range was 32.0 to 64.0mg/100cc. with a mean of $47.235{\pm}0.782mg/100cc$. Sex difference showed significant at 5% level and seasonal variation was highly significant at 1% level. 2. The total serum protein values for the male ranged from 5.61 to 8.83 gm/100cc with a. mean of $7.366{\pm}0.062gm/100cc$; for the female ranged from 5.53 to 8. 43 gm/100cc. with a mean of $6.832{\pm}0.063gm/100cc$. Sex difference and seasonal variation was not significant. 3. The serum globulin values for the male ranged from 2.97 to 4.78 gm/100cc. with a mean of $3.961{\pm}0.039gm/100cc$.; for the female ranged from 2.87 to 4.41 gm/100cc. with a mean of $3.699{\pm}0.037gm/100cc$. Sex difference showed highly significant at 1% level and seasonal variation was not significant. 4. The serum albumin values for the male ranged from 2.58 to 4.21 gm/100cc. with a mean of $3.405{\pm}0.029gm/100cc$.; for the female ranged from 2.39 to 4.10 gm/100cc. with a mean of $3.204{\pm}0.031gm/100cc$. Sex difference showed highly significant at 1% level and seasonal variation was not significant. 5. The total non-protein nitrogan values for the male ranged from 19.1 to 44.8 gm/100cc. with a mean of $31.166{\pm}0.582mg/100cc$.; for the female the range was 15.2 to 50.5 mg/100cc. with a mean of $28.89.6{\pm}0.673mg/100cc$. Sex difference showed significant at 5% level and seasonal variation was highly significant at 1 % level. 6. The blood urea nitrogen values for the male ranged from 6.4 to 28.3 mg/100cc. with a mean of $13.371{\pm}0.466mg/100cc$.; for the female the range, was 6.0 to 26.9 mg/100cc. with a mean of $13.631{\pm}0.321mg/100cc$. Sex difference was not significant and seasonal variation showed highly significant at 1 % level. 7. The total serum cholesterol values for the male ranged from 60.0 to 238.6 mg/100cc. with a mean of $140.897{\pm}2.826mg/100cc$.; for the female ranged from 50.0 to 243.0 mg/100cc. with a mean of $124.840{\pm}3.553mg/100cc$. Sex difference and seasonal variation showed highly significant at 1% level. 8. The serum inorganic phosphorus values for the male ranged from 3.5 to 7.8 mg/100cc. with a mean of $5.426{\pm}0.096mg/100cc$.; for the female ranged from 3.1 to 8.8 mg/100cc. with a mean of $5.570{\pm}0.128mg/100cc$. Sex difference and seasonal variation showed no significant. 9. The serum calcium values for the male ranged from 7.8 to 12.8 mg/100cc. with a mean of $10.761{\pm}0.102mg/100cc$.; for the female ranged from 8.0 to 13.0 mg/100cc. with a mean of 10. $756{\pm}0.097mg/100cc$. Sex difference was not significant and seasonal variation showed highly significant at 1% level. 10. The age of test group ranged from 2 years to 6 years in both sex and the averageage were, $4.45{\pm}0.114$ years in male and $4.50{\pm}0116$ years in female. Sex difference and seasonal variation of age were not found to be significant.
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