• Journal of Preventive Medicine and Public Health
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• v.21 no.1 s.23
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• pp.195-206
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• 1988

Two major issues of the blood bank management are quality assurance and inventory control. Recently, in Korea blood donation has gained popularity increasingly to allow considerable improvement of the quality assurance with respect to blood collection, transportation, storage, component preparation skills and hematological tests. Nevertheless the inventory control, the other issue of blood bank management, has been neglected so far. For the supply of blood by donation barely meets the demand, the blood bank policy on the inventory control has been 'the more the better.' The shortage itself by no means unnecessitate inventory control. In fact, in spite of shortage, no small amount of blood is outdated. The efficient blood inventory control makes it possible to economize the blood usage in the practice of state-of-the-art medical care. For the efficient blood inventory control in Korean hospitals, this tudy is to develop formulae forecasting the standard blood inventory level and suggest a set of policies improving the blood inventory control. For this study informations of $A^+$ whole bloods and packed cells inventory control were collected from a University Hospital and the Central Blood Bank of the Korean Red Cross. Using this informations, 1,461 daily blood inventory records were formulated.48 varieties of blood inventory control environment were identified on the basis of selected combinations of 4 inventory control variables-crossmatch, transfusion, inhospital donation and age of bloods from external supply. In order to decide the optimal blood inventory level for each environment, simulation models were designed to calculate the measures of performance of each environment. After the decision of 48 optimal blood inventory levels, stepwise multiple regression analysis was started where the independent variables were 4 inventory control variables and the dependent variable was optimal inventory level of each environment. Finally the standard blood inventory level decision rule was developed using the backward elimination procedure to select the best regression equation. And the effective alternatives of the issuing policy and crossmatch release period were suggested according to the measures of performance under the condition of the standard blood inventory level. The results of this study' were as follows ; 1. The formulae to calculate the standard blood inventory level($S^*$)was $S^*=2.8617X(d)^{0.9342}$ where d is the mean daily crossmatch(demand) for a blood type. 2. The measures of performace - outdate rate, average period of storage, mean age of transfused bloods, and mean daily available inventory level - were improved after maintenance of the standard inventory level in comparison with the present system. 3. Issuing policy of First In-First Out(FIFO) decreased the outdate rate, while Last In-First Out(LIFO) decreased the mean age of transfused bloods. The decrease of the crossmatch release period reduced the outdate rate and the mean age of transfused bloods.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1131-1131
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• 2001

To develop a nondestructive quality evaluation technique of fruits, a K-mean algorism is applied to near infrared (NIR) spectroscopy of apples. The K-mean algorism is one of neural network partition methods and the goal is to partition the set of objects O into K disjoint clusters, where K is assumed to be known a priori. The algorism introduced by Macqueen draws an initial partition of the objects at random. It then computes the cluster centroids, assigns objects to the closest of them and iterates until a local minimum is obtained. The advantage of using neural network is that the spectra at the wavelengths having absorptions against chemical bonds including C-H and O-H types can be selected directly as input data. In conventional multiple regression approaches, the first wavelength is selected manually around the absorbance wavelengths as showing a high correlation coefficient between the NIR $2^{nd}$ derivative spectrum and Brix value with a single regression. After that, the second and following wavelengths are selected statistically as the calibration equation shows a high correlation. Therefore, the second and following wavelengths are selected not in a NIR spectroscopic way but in a statistical way. In this research, the spectra at the six wavelengths including 900, 904, 914, 990, 1000 and 1016nm are selected as input data for K-mean analysis. 904nm is selected because the wavelength shows the highest correlation coefficients and is regarded as the absorbance wavelength. The others are selected because they show relatively high correlation coefficients and are revealed as the absorbance wavelengths against the chemical structures by B. G. Osborne. The experiment was performed with two phases. In first phase, a reflectance was acquired using fiber optics. The reflectance was calculated by comparing near infrared energy reflected from a Teflon sphere as a standard reference, and the $2^{nd}$ derivative spectra were used for K-mean analysis. Samples are intact 67 apples which are called Fuji and cultivated in Aomori prefecture in Japan. In second phase, the Brix values were measured with a commercially available refractometer in order to estimate the result of K-mean approach. The result shows a partition of the spectral data sets of 67 samples into eight clusters, and the apples are classified into samples having high Brix value and low Brix value. Consequently, the K-mean analysis realized the classification of apples on the basis of the Brix values.

• Current Research on Agriculture and Life Sciences
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• v.10
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• pp.35-40
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• 1992

The purpose of this study is to develop regression equations between peak flow and physical characteristic factors of watersheds. 112 irrigation reservoirs located in South Korea which are equal or larger than 200 has. in the irrigation area, are used in the analysis of this study. The results obtained from this study are as follows. 1. The results of correlation analysis of the relationships among the characteristic factors of the watersheds have been derived high significances. 2. Relationship between the peak flow and the simple correlation analysis of physical characteristic factors of the watersheds has been derived low significance. 3. The result of the multiple regression analysis between the peak flow and four physical characteristic factors of watershed such as watershed area, main stream length, average slope of main stream and elevation of reservoir are shown as the equation ; $Q_{100}=66.43A^{0.869}L^{-0.536}S^{0.456}Hs^{-0.122}$.(r=0.838)

• Korean Journal of Food Science and Technology
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• v.23 no.1
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• pp.88-92
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• 1991

To analyze the effects of the system parameters on the target parameters, which include the amount of water evaporation, water solubility index(WSI) and water absorption index(WAI), test trials of fractional factorial design of the three process variables at three levels were carried out for corn grit with a laboratory twin-screw extruder with three different screw configurations. The system parameters collected from the trials, such as extrusion temperature, specific mechanical energy input(SME) and mean residence time(RT), were showed the ranges of $129{\sim}182^{\circ}C$, $67{\sim}163\;kwh/ton$ and $12{\sim}34\;sec$, respectively. Within these ranges of the system parameters, the target parameters were able to be quantified by using multiple regression equations. The correlation of results with the system parameters blocked by the screw configuration as dependent variables, yield correlation coefficients above 0.90, and the correlation using the system parameters obtained from whole experiment system as the dependent variables yield correlation coefficients around 0.80. The functional relationship, which can be quantified by second order polynomial regression equation with only two system parameters within necessary degree of accuracy, can he graped in three dimensional surface response and contour diagrams.

• Journal of Nutrition and Health
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• v.39 no.4
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• pp.417-425
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• 2006

The purpose of this study were to a) investigate operation of human resource in contract foodservice management company (CFMC), b) identify the staffing indices for the establishment an labor productivity for CFMC, and c) develop standardized model of staffing demand as foodservice's scale in CFMC. The data was collected using FS intra-net system from 138 contract-managed foodservice operations in A CFMC and statistical analysis was completed using the SAS/win package (ver. 8.0) for description analysis, ANOVA, Duncan multiple comparison, pearson correlation analysis, and regression analysis. The types of operation were included factory (45%), small scale operation (26%), office (11%), department store (10%), training institute (4%), and hospital (3%). The distribution of foodservice scale was classified by meal served was as follows; 'less than 500 meals (47%)', 'from 500 to 1500 meals (25%)', 'from 1500 to 2500 meals (17%)', and 'more than 2500 meals (12%)'. There was two types of contract method, fee-contract (53%) and profit-and-loss contract (46%) Some variables were significantly high operation indices such as selling price, food cost, monthly sales, net profit and others were significantly low operation indices such as labor, meal time a day in the small foodservice on meal scale (p<.001). The more foodservice was large, the more human resource was disposed on dietitian, cook, cooking employee altogether (p<.001). Foodservice in A CFMC was divided into 2 groups by 500 meals a day, according to comparative analysis of labor productivity as meal scale per working hour, meal scale a day and operation indices as meal per foodservice employee, meal per cooking employee (p<.001). The regression equation model was developed as 'the number of employees=1.82+0.014 ${\times}$ meal served' in the operation of less than 500 meals, 'the number of employees=9.42+0.013 ${\times}$ meal scale a day -0.94 ${\times}$ meal scale per working hour' in the operation over 500 meal scale using labor productivity indices and operation indices. Therefore, CFMC could be enhanced efficiency of human resource arrangement using the standardized model of staffing demand and would be increased effectiveness of profit.

• Korean Journal of Soil Science and Fertilizer
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• v.24 no.1
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• pp.10-16
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• 1991

Mean values and the relative contribution of OM and clay to total CEC for soil textural classes were obtained from the analytical results of the typical profiles(sample size : 3,182) which were described by the detailed soil maps througthout Korea with an exception of Jeju island. The results are below. 1. Mean values of the soil CEC were 2.9 for S, 4.7 for LS, 6.7 for SL, 9.0 for L, 10.2 for SiL, 10.7 for CL, 8.6 for SCL, 12.2 for SiCL, 16.1 for SiC, and 17.4me/100gr for C, respectively. 2. The multiple regression equation and partial regression coefficient tended to show that OM and clay had the highly significant effect on CEC. 3. Clay content of the coarse, moderately coarse, and moderately fine soil was 1.10 to 1.89 times as important as OM content whereas OM of the medium and fine soil 1.09 to 2.94 times as important as clay in predicting CEC. 4. Mean values of CEC of the humus and clay in Korean soils were about 62.9 and 24.0me/100gr, respectively.

• Journal of Korean Society of Disaster and Security
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• v.13 no.1
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• pp.1-11
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• 2020

One of the important problem in statistical hydrology is to estimate the appropriated probability distribution for a given sample data. For the problem, a goodness-of-fit test is conducted based on the similarity between estimated probability distribution and assumed theoretical probability distribution. Probability plot correlation coefficient test (PPCC) is one of the goodness-of-fit test method. PPCC has high rejection power and its application is simple. In this study, test statistics of PPCC were derived for generalized extreme value distribution (GEV) models based on L-moments and these statistics were suggested by the multiple and nonlinear regression equations for its usability. To review the rejection power of the newly proposed method in this study, Monte Carlo simulation was performed with other goodness-of-fit tests including the existing PPCC test. The results showed that PPCC-A test which is proposed in this study demonstrated better rejection power than other methods, including the existing PPCC test. It is expected that the new method will be helpful to estimate the appropriate probability distribution model.

• Korean Journal of Food Science and Technology
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• v.18 no.1
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• pp.16-23
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• 1986

Physico-chemical and sensory characteristics of 28 black tea samples prepared by oaring the mixing ratio of 1 kind of Korean and 9 kinds of foreign black tea were determined, and their relationship was statistically analysed. Korean black tea was found to be lower in bulk density, caffeine, theobromine, crude protein, theaflavin, thearubigin and soluble solids, and higher in Hunter L- and b- value, neutral detergent fiber, calcium and ratio of oxidized matter as compared with foreign black tea. The palatability for 8 kinds of foreign black tea was generally increased by mixing with Korean black tea. The number of black tea whose palatability were higher than that of Korean black tea was 12, which was mostly mixed black tea. Theaflavin. Hunter a-value, soluble solids of the tea infusion, and potassium of the manufactured tea were the major guiding characteristics as a result of stepwise multiple regression analysis, and about 67% of the total variations in the palatability of black tea could be explained by the regression equation formulated by the preceding 4 characteristics.

• Journal of Bio-Environment Control
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• v.20 no.4
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• pp.297-303
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• 2011

The contents of capsaicinoid, free sugars and organic acids of six varieties of Korean hot pepper, Supermanita, Dokyacheongcheong, Shinseokyeoi, Wangdaebak, Hanbando, and Chungyang, were measured. The sensory evaluations of its extracts were compared in order to investigate the indirect effect or reaction of the composition of taste components on sensory acceptability of Korean hot pepper. The contents of capsaicinoid were considerably from $37.8mg{\cdot}100g^{-1}$ to $164.1mg{\cdot}100g^{-1}$, and the contents of free sugars were from 9.3% to 18.2%, and the contents of organic acids were from 8.1% to 14.7% in Korean hot peppers. Although the pungent sensory evaluation of water extract of pepper powder was completely accordant with instrumental analysis result of capsaicinoid contents, they did not show a significant relationship to the sensory of taste. Multiple regression with capsaicinoid (CAP), total sugars (TS) and total organic acid (TOA) contents increased the correlation coefficient for sensory of taste to r = 0.927 and the coefficient of determination for them to $R^2=0.906$. However, we suggest the more efficient function for it which is composed of two independent variables only. As the result, a regression equation of Y = 0.69 X + 0.11 with $R^2=0.884$ was obtained for quantitative analysis of sensory evaluation of pepper taste by two factors between capsaicinoid and total free sugar.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.9
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• pp.359-368
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• 2016

In the 21st century, the Korean university education system is focused on innovation and change, including cooperation between industry and universities. It should be a goal to foster an industry-university ecosystem through interactions between universities and industry. Therefore, it is important to measure their relationships and to find advisable ways to measure the final results of industry-university cooperation. This paper sets out the achievements in cooperation and the satisfaction from such enterprises and measures mutual relationships influencing satisfaction from industry-university cooperation as to adherence and cooperation. Therefore, this research focuses on regression equation analysis in order to analyze the influence from satisfaction with industry-university cooperation based on factors in the relations between industry and universities. Also, as we examined the multicollinearity problem, before analyzing multiple regression, the multicollinearity problem appeared to be relatively irrelevant. In particular, the satisfaction variable, which can also be set as a subordinate variable, was in this research constructed as a high-dimensional subordinate variable composed of five individual variables. We then analyzed how the adherence construct factor and degree of cooperation construct factor influences the respective and subordinate satisfaction variables. As a result, the degree of realization of local customized programs was shown by the most significant variables. The biggest factor influencing satisfaction with industry-university cooperation proves the degree of realization for appropriate programs under local conditions, such as education, research, and technique guidance.