• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1511-1511
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• 2001

Energy content, expressed as calories per gram, is an important part of the evaluation and marketing of foods in developed countries. Currently accepted methods of measurement of energy by U.S. food labeling legislation include measurement of gross calories by bomb calorimetry with an adjustment for undigested protein and by calculation using specific factors for the energy values of protein, carbohydrate less the amount of insoluble dietary fiber, and total fat. The ability of NIRS to predict the energy value of diverse, processed and unprocessed cereal food products was investigated. NIR spectra of cereal products were obtained with an NIR Systems monochromator and the wavelength range used for analysis was 1104-2494 nm. Gross energy of the foods was measured by oxygen bomb calorimetry (Parr Manual No. 120) and expressed as calories per gram (CPGI, range 4.05-5.49 cal/g). Energy value was adjusted for undigested protein (CPG2, range 3.99-5.38 cal/g) and undigested protein and insoluble dietary fiber (CPG3, range 2.42-5.35 cal/g). Using a multivariate analysis software package (ISI International, Inc.) partial least squares models were developed for the prediction of energy content. The standard error of cross validation and multiple coefficient of determination for CPGI using modified partial least squares regression (n=127) was 0.060 cal/g and 0.95, respectively, and the standard error of performance, coefficient of determination, bias and slope using an independent validation set (n=59) were 0.057 cal/g, 0.98, -0.027 cal/g and 1.05 respectively. The PLS loading for factor 1 (Pearson correlation coefficient 0.92) had significant absorption peaks correlated to C-H stretch groups in lipid at 1722/1764 nm and 2304/2346 nm and O-H groups in carbohydrate at 1434 and 2076 nm. Thus the model appeared to be predominantly influenced by lipid and carbohydrate. Models for CPG2 and CPG3 showed similar trends with standard errors of performance, using the independent validation set, of 0.058 and 0.088 cal/g, respectively, and coefficients of determination of 0.96. Thus NIRS provides a rapid and efficient method of predicting energy content of diverse cereal foods.

• The Korean Journal of Applied Statistics
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• v.21 no.2
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• pp.291-299
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• 2008

This paper discusses model building for repeated binary response data with different time-dependent covariates each occasion. Since repeated measurements data are having correlated structure, weighed least squares(WLS) methodology is applied. Repeated measures designs are usually having different sizes of experimental units like split-plot designs. However repeated measures designs differ from split-plot designs in that the levels of one or more factors cannot be randomly assigned to one or more of the sizes of experimental units in the experiment. In this case, the levels of time cannot be assigned at random to the time intervals. Because of this nonrandom assignment, the errors corresponding to the respective experimental units may have a covariance matrix. So, the estimates of effects included in a suggested logit model are obtained by using covariance structures.

• Journal of Korean Society for Quality Management
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• v.45 no.1
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• pp.117-128
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• 2017

Purpose: This study analyzes automobile quality review data to develop alternative analytical method of informal data. Existing methods to analyze informal data are based mainly on the frequency of informal data, however, this research tries to use correlation information of each informal data. Method: After sentimental analysis to acquire the user information for automobile products, three classification methods, that is, $na{\ddot{i}}ve$ Bayes, random forest, and support vector machine, were employed to accurately classify the informal user opinions with respect to automobile qualities. Additionally, Word2vec was applied to discover correlated information about informal data. Result: As applicative results of three classification methods, random forest method shows most effective results compared to the other classification methods. Word2vec method manages to discover closest relevant data with automobile components. Conclusion: The proposed method shows its effectiveness in terms of accuracy and sensitivity on the analysis of informal quality data, however, only two sentiments (positive or negative) can be categorized due to human errors. Further studies are required to derive more sentiments to accurately classify informal quality data. Word2vec method also shows comparative results to discover the relevance of components precisely.

• Journal of Korean Academy of Fundamentals of Nursing
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• v.20 no.3
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• pp.278-288
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• 2013

Purpose: The purpose of this study was to investigate the influence of communication competence and burnout on nursing performance in intensive care units (ICU). Method: The participants were 209 nurses from four university hospitals. Measurements included a socio-demographic and job related survey, communication competence inventory, the Maslach burnout inventory and a nursing performance scale. Data were collected from February 6 to 24, 2012, with a self-report questionnaire. The statistical analyses were performed with SPSS 18.0 software. Results: The mean scores for communication competence, burnout and nursing performance were 50.49, 84.72, and 62.18, respectively. Communication competence (r=.44, p<.001) and burn out (r=-.32, p<.001) were significantly correlated with nursing performance. In the multiple linear regression, factors influencing nursing performance were communication competence, age and burnout. These variables explained about 46% of the total variance of nursing performance. Communication competence (${\beta}$=.34, p<.001) was the most influential factor. Conclusion: Nurses' poor communication skills and burnout can influence the occurrences of medical errors in ICU nursing performance. The results suggest that good communication and burnout resolution skills programs should be implemented to improve nursing performance efficiency.

• Atmosphere
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• v.19 no.2
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• pp.213-226
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• 2009

In order to investigate the characteristics of Changma over the Korean peninsula, KEOP-2007 IOP (Intensive Observing Period) was conducted from 15 June 2007 to 15 July 2007. KEOP-2007 IOP is high spatial and temporal radiosonde observations (RAOB) which consisted of three special stations (Munsan, Haenam, and Ieodo) from National Institute of Meteorological Research, five operational stations (Sokcho, Baengnyeongdo, Pohang, Heuksando, and Gosan) from Korea Meteorological Administration (KMA), and two operational stations (Osan and Gwangju) from Korean Air Force (KAF) using four different types of radiosonde sensors. The error statistics of the sensor of radiosonde were investigated using quality control check. The minimum and maximum error frequency appears at the sensor of RS92-SGP and RS1524L respectively. The error frequency of DFM-06 tends to increase below 200 hPa but RS80-15L and RS1524L show vice versa. Especially, the error frequency of RS1524L tends to increase rapidly over 200 hPa. Systematic biases of radiosonde show warm biases in case of temperature and dry biases in case of relative humidity compared with ECMWF (European Center for Medium-Range Weather Forecast) analysis data and precipitable water vapor from GPS. The maximum and minimum values of systematic bias appear at the sensor of DFM-06 and RS92-SGP in case of temperature and RS80-15L and DFM-06 in case of relative humidity. The systematic warm and dry biases at all sensors tend to increase during daytime than nighttime because air temperature around sensor increases from the solar heating during daytime. Systematic biases of radiosonde are affected by the sensor type and the height of the sun but random errors are more correlated with the moisture conditions at each observation station.

• Asian-Australasian Journal of Animal Sciences
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• v.18 no.8
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• pp.1075-1079
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• 2005

The main objective of this study is to examine genetic changes in growth rate and carcass composition traits in group housed, ad libitum fed pigs, from lines of Large White divergently selected over four years for high and low post-weaning daily gain on a fixed but restricted ration. Genetic parameters for production and carcass traits were also estimated by using average information-restricted maximum likelihood applied to a multivariate individual animal model. All analyses were carried out on 1,728 records of group housed ad libitum fed pigs, and include a full pedigree of 5,324 animals. Estimates of heritability (standard errors in parentheses) were 0.11 (0.04) for lifetime daily liveweight gain (LDG), 0.13 (0.04) for daily carcass weight gain (CDG) and 0.28 (0.06) for carcass backfat (CFT). Genetic correlations between LDG and CDG were highly positive and between LDG and CFT negative, suggesting that selection for lifetime daily gain under commercial conditions of group housing with ad libitum feeding would result in favourable improvement in carcass traits. CFT showed negative genetic correlations with CDG. Correlated genetic responses evaluated as estimated breeding values (EBVs) were obtained from a multivariate animal model-best linear unbiased prediction analysis. After four years of divergent selection for 6 week post-weaning growth rate on restricted feeding, pigs performance tested on ad libitum feeding in groups exhibited changes in EBVs of 6.77 and -9.93 (g/d) for LDG, 4.25 and -7.08 (g/d) for CDG, and -1.42 and 1.55 (mm) for CFT, in the high and low lines, respectively. It is concluded that selection for growth rate on restricted feeding would significantly improve genetic performance and carcass composition of their descendants when group housed and ad libitum fed as is a common commercial practice.

• Asian-Australasian Journal of Animal Sciences
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• v.30 no.11
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• pp.1590-1597
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• 2017

Objective: This study aims to identify the relationship between odd- and branched-chain fatty acids (OBCFAs) and microbial nucleic acid bases in the rumen, and to establish a model to accurately predict microbial protein flow by using OBCFA. Methods: To develop the regression equations, data on the rumen contents of individual cows were obtained from 2 feeding experiments. In the first experiment, 3 rumen-fistulated dry dairy cows arranged in a $3{\times}3$ Latin square were fed diets of differing forage to concentration ratios (F:C). The second experiment consisted of 9 lactating Holstein dairy cows of similar body weights at the same stage of pregnancy. For each lactation stage, 3 cows with similar milk production were selected. The rumen contents were sampled at 4 time points of every two hours after morning feeding 6 h, and then to analyse the concentrations of OBCFA and microbial nucleic acid bases in the rumen samples. Results: The ruminal bacteria nucleic acid bases were significantly influenced by feeding diets of differing forge to concentration ratios and lactation stages of dairy cows (p<0.05). The concentrations of OBCFAs, especially odd-chain fatty acids and C15:0 isomers, strongly correlated with the microbial nucleic acid bases in the rumen (p<0.05). The equations of ruminal microbial nucleic acid bases established by ruminal OBCFAs contents showed a good predictive capacity, as indicated by reasonably low standard errors and high R-squared values. Conclusion: This finding suggests that the rumen OBCFA composition could be used as an internal marker of rumen microbial matter.

• Water for future
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• v.10 no.1
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• pp.95-100
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• 1977

The empirical area-reduction method by W.M. Borland and C.R. Miller and its revised procedure by W.T. Moody were made of fitting the area and storage curves to the Van't Hul distributions. It should be noted that the reservoir is classified into one of the four standard types on the basis of the topographical feature of the reservoir in application of the method. In other words, this method did not take into account several considerafble factors affecting the mode of sediment deposition, but only the shape of the reservoir as a governign factor. This is why the method occasionally creates ambiguity in classification and accordingly leads to unexpected mode of deposition. This paper describes a generating an formula to decide the standard classification of four types Van's Hul distributions, taking into consideration quantitatively sediment-loss percent and capacity-inflow ratio as well as the shape of the reservoirs by multiple regression analysis using the least square method to get a better fit to the design curves. The result is expressed as $Y=-1.95+55.8X_1+0.14X_2+0.12X_3$ in which the the values of Y locate the standard type I through type IV in the range from ten to forty with the interval of ten. The regression analysis was correlated well with the standard errors of estimate of around two except for the case of the type IV. This formula does not give big difference from the Borland's work in general sityation, but it demonstrates acceptable results, giving somewhat precise replys for the specific reservoirs. Its application to the Soyang Lake, one of the largest reservoirs in the country, defined clearly the type II, while the original method located it in the boundary of the type II and type III.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.6B
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• pp.579-585
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• 2002

The investigation into the effect of various feedback errors on system performance can help the robust feedback channel design and transmission of exact feedback channel information as well. In this paper, we address the algorithm that determines space combining weight vector maximizing received signal power at mobile on frequency flat fading channel and investigate the performance degradation by feedback channel delay in the FDD/CDMA systems employing transmit beamforming. We observe the effect of feedback channel delay corresponding to the number of transmit antennas and the temporal/spatial correlation of channel. The results show that performance is more sensitive to feedback delay with the larger number of antennas when fadings at transmit antennas are not spatially correlated.

• Journal of Korea Society of Industrial Information Systems
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• v.23 no.2
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• pp.19-28
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• 2018

In this paper, we studied on the sampling of ocean meteorological data to analyze signature of naval ships. The newest ocean meteorological data, that was quality controled by the Korea Meteorological Administration(KMA), was collected. Outliers were removed from the data by setting the usable range of data. After that, the data size was reduced through the random sampling method, taking geopolitical significance and effective area of buoy, for probabilistic analysis. Moreover, the sample sizes were set at 100, 200, and 400 by considering the population size and a 95% confidence level. The final sample was obtained using the two-dimensional stratified sampling method based on highly correlated water temperature and air temperature. The sum of the squared errors and the confidence interval was calculated to compare the result of sampling. As a result, this study proposed reasonable sample size for infra­red signature analysis of naval ships.