• Preventive Nutrition and Food Science
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• v.13 no.3
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• pp.225-230
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• 2008

Onion slices were dehydrated in a single layer at drying air temperatures ranging from $50{\sim}70^{\circ}C$ in a laboratory scale convective hot-air dryer at an air velocity of 0.66 m/s. The effect of drying air temperature on the drying kinetic characteristics were determined. It was found that onion slices would dry within $210{\sim}460\;min$ under these drying conditions. Moisture transfer during dehydration was described by applying the Fick's diffusion model and the effective diffusivity changed between $1.345{\times}10^{-8}$ and $2.658{\times}10^{-8}\;m^2/s$. A non-linear regression procedure was used to fit 9 thin layer drying models available in the literature to the experimental drying curves. The Logarithmic model provided a better fit to the experimental drying data as compared to other models. Temperature dependency of the effective diffusivity during the hot-air drying process obeyed the Arrhenius relationship with estimated activation energy being 31.36 kJ/mol. The effect of the drying air temperature on the drying model constants and coefficients were also determined.

• Journal of Korea Foresty Energy
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• v.2 no.2
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• pp.1-12
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• 1982

To study tile comparison of aboveground biomass of Pinus rigida Mill. of 18-year-old, plantations located in Whaseong, Yuseong and Wanju district were selected. Ten sample trees in each district selected taking account of DBH distribution were felled carefully to minimize loss of branches and stem analysed by 1m lag segment sectioned from base . The tree height and DBH were measured for sample trees in total growing within $200m^2$ experimental plot. The diagram of oven-dry weight distribution of stem, branch and needle for each 1m segment was constructed. The logarithmic regression equations between dry weight of each component and the two variables, $DBH^2$ and tree height, combined term were presented. The standing crops in the sample stand was estimated to be as much as 23.88, 54.09 and 42.68 tons of dry matter, above ground , per ha in Whaseong, Yuseong anf Wanju district respectively. Annual net production was estimated at 253,657 and 3.65 tons per ha per year respectively. The net assimilation rate was 1.65,1.95 and 1.81 kg/kg/yr in Whaseong, Yuseong and Wanju district respectively. The efficency of leaf to produce stem was 0.99, 1.12 and 1.30 kg/kg/yr respectively.

• Journal of Information Technology Applications and Management
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• v.20 no.4
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• pp.67-81
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• 2013

Domestic telecommunication companies have increased in marketing expenditures and capital investments in their plants and equipments. Their expectation for their investment sometimes results in the shrinking of their ARPUs(average revenues per user) as well as decreasing of net profits. Those financial efforts have not always been positive relation with their ARPUs. Since western and european telecommunication industry recently have similar situation with our market where their mobile and network users have been saturated so that no more increased users are estimated. Therefore, this paper aims for first to explore methods maximizing the investments efficiency for the telecommunication company so that we choose bechmarked telecommmunication companies to explore their investment managing situation with resepct to their marketing and capital expenditure. Secondly this paper tried to suggest several public policy guidelines for domestic telecommunication industry. Total seventeen foreign telecommunication companies were selected and data set through official IR as well as AR were chosen. Curvilinear logarithmic regression analysis were tested to obtain elasticities as well as marginal effects. As a result, overspending on the marketing investment showed more negative indicators to their revenues, on the other hand, more investment in the Capex such as network infrastructures and other service facilities were more likely related to positive revenues.

• Journal of the Korean Society for Geothermal and Hydrothermal Energy
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• v.17 no.4
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• pp.15-27
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• 2021

In this study, the effect of design factors in a pump station on the pressure variations which are the main cause of water hammering has been investigated by numerical simulations. As design factors, the flow rate, Young's modulus, diameter, thickness, roughness coefficient of pipeline are considered. The relationships between the pressure variations and the design factors are analyzed. The results show that the pressure variation increases sensitively with the flow rate and Young's modulus, and increases gradually with the thickness and roughness coefficient of pipe, whereas it decreases with the pipe diameter. The wavelength of the pressure wave becomes longer for a smaller Young's modulus, a smaller pipe thickness and a bigger pipe diameter. These relationships are nondimensionalized, and logarithmic curve-fitted functions are proposed by regression analysis. Most effective factors on the nondimensional pressure variation is Young's modulus. Flow rate, roughness coefficient, relative thickness and pipe diameters are the next impact factors.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.27 no.1
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• pp.84-86
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• 1982

The experiment was conducted with three varieties (Hicks, Burley 21, and Sohyang) and cultivation type (Improved mulching, general mulching, and non mulching) of NC 2326 to model to curve of tabacco growth against time. The basic growth data were obtained by harvest method at intervals of ten days from transplanting at 7-8 times and analyzed by polynomial regression, orthogonal polynomial, and logarithmic transformation. It is shown that the C model of growth curve: T = A +$\sqrt{(1.4 AK + K)}$2K provides an excellent fit.

• The Journal of the Korea Contents Association
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• v.9 no.8
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• pp.147-157
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• 2009

Recently, there has been continued research on UCP from the development effort estimation method to a software development project applying object oriented development methodology. Current research proposes a linear model estimating the developmenteffort by multiplying a constant to AUCP which applies technical and environmental factors. However, the fact that a non-linear regression model is more appropriate as the software size increases, the development period increases exponentially. In addition, in the UCP calculation process the occurrence of FP errors due to the application of TCF and EF, it is unrealistic to estimate the size with AUCP. This paper presents the issue of current research based on UCP without considering problems of the research, for example, TCF and EF and expresses the models (linear, logarithmic, polynomial, power and exponential type) estimating the development effort directly from UUCP. Consequently, the exponential model within non-linear models exhibit more accurate results than the current linear model. Therefore, after calculating the UUCP of the developing software system, using the proposed model to estimate the development effort, it is possible to estimate the direct cost required in development.

• Journal of Preventive Medicine and Public Health
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• v.38 no.4
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• pp.408-414
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• 2005

Objectives : The purpose of this study was to determine the impact of the sociodemographic and health characteristics on the out-of-pocket health spending of the individuals aged 20 and older in Korea. Methods : We used the data from the 2001 National Public Health and Nutrition Survey. The final sample size was 26,154 persons. Multiple linear regression models were used according to the age groups, that is, one model was used for those people under the age of sixty-five and the other was used for those people aged sixty-five and older. In these analyses, the expenditures were transformed to a logarithmic scale to reduce the skewness of the results. Results : Out-of-pocket health expenditures for those people under the age of 65 averaged 14,800 won per month, whereas expenditures for those people aged 65 and older averaged 27,200 won per month. In the regression analysis, the insurance type, resident area, self-reported health status, acute or chronic condition and bed-disability days were the statistically significant determinants for both age groups. Gender and age were statistically significant determinants only for the non-elderly. Conclusions : The findings from this study show that the mean out-of-pocket health expenditures varied according to the age groups and also several diverse characteristics. Thus, policymakers should consider the out-of-pocket health expenditure differential between the elderly and non-elderly persons. Improvement of the insurance coverage for the economically vulnerable subgroups that were identified in this study should be carefully considered. In addition, it is necessary to assess the impact of out-of-pocket spending on the peoples' health care utilization.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.4
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• pp.12-22
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• 2021

This article suggests the machine learning model, i.e., classifier, for predicting the production quality of free-machining 303-series stainless steel(STS303) small rolling wire rods according to the operating condition of the manufacturing process. For the development of the classifier, manufacturing data for 37 operating variables were collected from the manufacturing execution system(MES) of Company S, and the 12 types of derived variables were generated based on literature review and interviews with field experts. This research was performed with data preprocessing, exploratory data analysis, feature selection, machine learning modeling, and the evaluation of alternative models. In the preprocessing stage, missing values and outliers are removed, and oversampling using SMOTE(Synthetic oversampling technique) to resolve data imbalance. Features are selected by variable importance of LASSO(Least absolute shrinkage and selection operator) regression, extreme gradient boosting(XGBoost), and random forest models. Finally, logistic regression, support vector machine(SVM), random forest, and XGBoost are developed as a classifier to predict the adequate or defective products with new operating conditions. The optimal hyper-parameters for each model are investigated by the grid search and random search methods based on k-fold cross-validation. As a result of the experiment, XGBoost showed relatively high predictive performance compared to other models with an accuracy of 0.9929, specificity of 0.9372, F₁-score of 0.9963, and logarithmic loss of 0.0209. The classifier developed in this study is expected to improve productivity by enabling effective management of the manufacturing process for the STS303 small rolling wire rods.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.1
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• pp.127-142
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• 2023

The management of size and weight, which are the growth information of aquaculture fish in fish-farms, is the most basic goal. In this study, the epoch is defined in fish-farms from the time of stocking or dividing to the time of shipment, and the growth data for a total of three epoch is analyzed from a time series perspective. Growth information such as the size and weight of aquaculture fish that occur over time in fish-farms is compared and analyzed with water quality environmental information and feeding information, and a model is presented using the analysis results. In this study, linear, exponential, and logarithmic regression models are presented using the Box-Jenkins method for size and weight by epoch using data obtained in the field.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.4
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• pp.171-181
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• 2013

Recently, ground penetrating radar(GPR) has been widely used in detecting metallic and nonmetallic buried landmines and a number of related researches have been reported. A novel preprocessing method is proposed in this paper to flag potential locations of buried mine-like objects from GPR array measurements. GPR operates by measuring the reflection of an electromagnetic pulse from discontinuities in subsurface dielectric properties. As the GPR pulse propagates in the geologic medium, it suffers nonlinear attenuation as the result of absorption and dispersion, besides spherical divergence. In the proposed algorithm, a logarithmic transformed regression model which successfully represents the time-varying signal amplitude of the GPR data is estimated at first. Then, background signals may be densely distributed near the regression model and candidate signals of targets may be far away from the regression model in the time-amplitude space. Based on the observation, GPR signals are decomposed into candidate signals of targets and background signals using residuals computed from the estimated value by regression and the measurement of GPR. Candidate signals which may contain target signals and noise signals need to be refined. Finally, targets are detected through the refinement of candidate signals based on geometric signatures of mine-like objects. Our algorithm is evaluated using real GPR data obtained from indoor controlled environment and the experimental results demonstrate remarkable performance of our mine-like object detection method.