• Journal of Korean Home Economics Education Association
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• v.22 no.1
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• pp.33-50
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• 2010

This study was conducted as a preparation for the operation of 2007 revised curriculum and an effort towards professional development for Home Economics teachers in clothing life culture area. The aim of this study was to develop an teacher training program based on the clothing life culture in three kingdoms period, apply it to teacher training, and evaluate the program by analyzing the purpose of participation, trainee expectation and gratification, change of recognition level about Han culture, trainee satisfaction, and willingness to apply to teaching and attend further training program. The characteristic of the training program was that it consisted of both highly qualified lectures on professional contents and practices with school classroom level, and it dealt with the ancient korean clothing as its central subject. The purpose of the training program was to elevate the recognition of Han culture and increase the possibility of application in the classroom situation. It showed that the trainees participated with high intrinsic motivations, aiming to improve their professionalism in subject content and expecting various subject content. It also showed that the trainee gratification was very high in professional knowledge of clothing culture area, and the trainees were gratified in most evaluation items. As to the recognition level of korean culture, even before the training program, it was generally higher than average. After the program, it increased meaningfully. Through the training program, the trainees became feel prouder of Han culture and people and themselves as Home economics teachers. The contents of the program were considered very helpful for the improvement of professionalism and the design of instruction and learning activity. It was revealed that Home Economics teachers had very high expectations of the development of instruction-learning models which could enable them to experience new and interesting ideas, help enhance their professionalism, and be applied to their teaching. Therefore, continuous development and operation of the teacher training program relating to the life culture such as clothing, food, and housing life are needed.

• The Korean Journal of Nuclear Medicine
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• v.38 no.6
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• pp.528-531
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• 2004

Purpose: PET has some disadvantage in the imaging of small animal due to poor resolution. With the advent of microPET scanner, it is possible to image small animals. However, the image quality was not good enough as human image. Due to larger brain, cat brain imaging was superior to mouse or rat. In this study, we established the cat brain infarction model and evaluate it and its temporal charge using microPET scanner. Materials and Methods: Two adult male cats were used. Anesthesia was done with xylazine and ketamine HCl. A burr hole was made at 1cm right lateral to the bregma. Collagenase type IV 10 ${\mu}l$ was injected using 30 G needle for 5 minutes to establish the infarction model. $^{18}F$-FDG microPET (Concorde Microsystems Inc., Knoxville, TN) scans were performed 1, 11 and 32 days after the infarction. In addition, $^{18}F$-FDG PET scans were performed using human PET scanner (Gemini, Philips medical systems, CA, USA) 13 and 47 days after the infarction. Results: Two cat brain infarction models were established. The glucose metabolism of an infarction lesion improved with time. An infarction lesion was also distinguishable in the human PET scan. Conclusion: We successfully established the cat brain infarction model and evaluated the infarcted lesion and its temporal change using $^{18}F$-FDG microPET scanner.

• Journal of Intelligence and Information Systems
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• v.21 no.3
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• pp.79-99
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• 2015

The prediction of bankruptcy has been extensively studied in the accounting and finance field. It can have an important impact on lending decisions and the profitability of financial institutions in terms of risk management. Many researchers have focused on constructing a more robust bankruptcy prediction model. Early studies primarily used statistical techniques such as multiple discriminant analysis (MDA) and logit analysis for bankruptcy prediction. However, many studies have demonstrated that artificial intelligence (AI) approaches, such as artificial neural networks (ANN), decision trees, case-based reasoning (CBR), and support vector machine (SVM), have been outperforming statistical techniques since 1990s for business classification problems because statistical methods have some rigid assumptions in their application. In previous studies on corporate bankruptcy, many researchers have focused on developing a bankruptcy prediction model using financial ratios. However, there are few studies that suggest the specific types of bankruptcy. Previous bankruptcy prediction models have generally been interested in predicting whether or not firms will become bankrupt. Most of the studies on bankruptcy types have focused on reviewing the previous literature or performing a case study. Thus, this study develops a model using data mining techniques for predicting the specific types of bankruptcy as well as the occurrence of bankruptcy in Korean small- and medium-sized construction firms in terms of profitability, stability, and activity index. Thus, firms will be able to prevent it from occurring in advance. We propose a hybrid approach using two artificial neural networks (ANNs) for the prediction of bankruptcy types. The first is a back-propagation neural network (BPN) model using supervised learning for bankruptcy prediction and the second is a self-organizing map (SOM) model using unsupervised learning to classify bankruptcy data into several types. Based on the constructed model, we predict the bankruptcy of companies by applying the BPN model to a validation set that was not utilized in the development of the model. This allows for identifying the specific types of bankruptcy by using bankruptcy data predicted by the BPN model. We calculated the average of selected input variables through statistical test for each cluster to interpret characteristics of the derived clusters in the SOM model. Each cluster represents bankruptcy type classified through data of bankruptcy firms, and input variables indicate financial ratios in interpreting the meaning of each cluster. The experimental result shows that each of five bankruptcy types has different characteristics according to financial ratios. Type 1 (severe bankruptcy) has inferior financial statements except for EBITDA (earnings before interest, taxes, depreciation, and amortization) to sales based on the clustering results. Type 2 (lack of stability) has a low quick ratio, low stockholder's equity to total assets, and high total borrowings to total assets. Type 3 (lack of activity) has a slightly low total asset turnover and fixed asset turnover. Type 4 (lack of profitability) has low retained earnings to total assets and EBITDA to sales which represent the indices of profitability. Type 5 (recoverable bankruptcy) includes firms that have a relatively good financial condition as compared to other bankruptcy types even though they are bankrupt. Based on the findings, researchers and practitioners engaged in the credit evaluation field can obtain more useful information about the types of corporate bankruptcy. In this paper, we utilized the financial ratios of firms to classify bankruptcy types. It is important to select the input variables that correctly predict bankruptcy and meaningfully classify the type of bankruptcy. In a further study, we will include non-financial factors such as size, industry, and age of the firms. Thus, we can obtain realistic clustering results for bankruptcy types by combining qualitative factors and reflecting the domain knowledge of experts.

• Journal of Animal Environmental Science
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• v.18 no.sup
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• pp.81-90
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• 2012

This study was evaluated high end research grade Near infrared spectrophotometer (NIRS) to low end popular field grade multiple Near infrared spectrophotometer (NIRS) for rapid analysis at forage quality at sight with 241 samples of Italian ryegrass silage during 3 years collected whole country for evaluate accuracy and precision between instruments. Firstly collected and build database high end research grade NIRS using with Unity Scientific Model 2500X (650 nm~2,500 nm) then trim and fit to low end popular field grade NIRS with Unity Scientific Model 1400 (1,400 nm~2,400 nm) then build and create calibration, transfer calibration with special transfer algorithm. The result between instruments was 0.000%~0.343% differences, rapidly analysis for chemical constituents, NDF, ADF, and crude protein, crude ash and fermentation parameter such as moisture, pH and lactic acid, finally forage quality parameter, TDN, DMI, RFV within 5 minutes at sight and the result equivalent with laboratory data. Nevertheless during 3 years collected samples for build calibration was organic samples that make differentiate by local or yearly bases etc. This strongly suggest population evaluation technique needed and constantly update calibration and maintenance calibration to proper handling database accumulation and spread out by knowledgable control laboratory analysis and reflect calibration update such as powerful control center needed for long lasting usage of forage analysis with NIRS at sight. Especially the agriculture products such as forage will continuously changes that made easily find out the changes and update routinely, if not near future NIRS was worthless due to those changes. Many research related NIRS was shortly study not long term study that made not well using NIRS, so the system needed check simple and instantly using with local language supported signal methods Global Distance (GD) and Neighbour Distance (ND) algorithm. Finally the multiple popular field grades instruments should be the same results not only between research grade instruments but also between multiple popular field grade instruments that needed easily transfer calibration and maintenance between instruments via internet networking techniques.

• Journal of The Korean Society of Grassland and Forage Science
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• v.36 no.1
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• pp.50-57
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• 2016

This study was conducted to determine the effect of mathematical transformation on near infrared spectroscopy (NIRS) calibrations for the prediction of chemical composition and fermentation parameters in corn silage. Corn silage samples (n=407) were collected from cattle farms and feed companies in Korea between 2014 and 2015. Samples of silage were scanned at 1 nm intervals over the wavelength range of 680~2,500 nm. The optical data were recorded as log 1/Reflectance (log 1/R) and scanned in intact fresh condition. The spectral data were regressed against a range of chemical parameters using partial least squares (PLS) multivariate analysis in conjunction with several spectral math treatments to reduce the effect of extraneous noise. The optimum calibrations were selected based on the highest coefficients of determination in cross validation ($R^2{_{cv}}$) and the lowest standard error of cross validation (SECV). Results of this study revealed that the NIRS method could be used to predict chemical constituents accurately (correlation coefficient of cross validation, $R^2{_{cv}}$, ranging from 0.77 to 0.91). The best mathematical treatment for moisture and crude protein (CP) was first-order derivatives (1, 16, 16, and 1, 4, 4), whereas the best mathematical treatment for neutral detergent fiber (NDF) and acid detergent fiber (ADF) was 2, 16, 16. The calibration models for fermentation parameters had lower predictive accuracy than chemical constituents. However, pH and lactic acids were predicted with considerable accuracy ($R^2{_{cv}}$ 0.74 to 0.77). The best mathematical treatment for them was 1, 8, 8 and 2, 16, 16, respectively. Results of this experiment demonstrate that it is possible to use NIRS method to predict the chemical composition and fermentation quality of fresh corn silages as a routine analysis method for feeding value evaluation to give advice to farmers.

• Journal of Food Hygiene and Safety
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• v.29 no.4
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• pp.305-311
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• 2014

Minimum infective dose (MID) data has been recognized as an important and absolutely needed in quantitative microbiological assessment (QMRA). In this study, we performed a comprehensive literature review and meta-analysis to better quantify this association. The meta-analysis applied a final selection of 82 published papers for total 12 species foodborne disease pathogens (bacteria 9, virus 2, and parasite 1 species) which were identified and classified based on the dose-response models related to QMRA studies from PubMed, ScienceDirect database and internet websites during 1980-2012. The main search keywords used the combination "food", "foodborne disease pathogen", "minimum infective dose", and "quantitative microbiological risk assessment". The appropriate minimum infective dose for B. cereus, C. jejuni, Cl. perfringens, Pathogenic E. coli (EHEC, ETEC, EPEC, EIEC), L. monocytogenes, Salmonella spp., Shigella spp., S. aureus, V. parahaemolyticus, Hepatitis A virus, Noro virus, and C. pavum were $10^5cells/g$ (fi = 0.32), 500 cells/g (fi = 0.57), $10^7cells/g$ (fi = 0.56), 10 cells/g (fi = 0.47) / $10^8cells/g$ (fi = 0.71) / $10^6cells/g$ (fi = 0.70) / $10^6cells/g$ (fi = 0.60), $10^2{\sim}10^3cells/g$ (fi = 0.23), 10 cells/g (fi = 0.30), 100 cells/g (fi = 0.32), $10^5cells/g$ (fi = 0.45), $10^6cells/g$ (fi = 0.64), $10{\sim}10^2particles/g$ (fi = 0.33), 10 particles/g (fi = 0.71), and $10{\sim}10^2oocyst/g$ (fi = 0.33), respectively. Therefore, these results provide the preliminary data necessary for the development of foodborne pathogens QMRA.

• Current Research on Agriculture and Life Sciences
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• v.32 no.4
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• pp.225-230
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• 2014

This study investigates the effect of organic certification of apples on consumer preference in China as a way to support the expanded export of Korean apples to China. A choice experiment was designed to analyze the apple consumption in China. A total of 298 Chinese consumers answered the survey, and multinomial logit models were used to analyze the results. Organic certification was identified as an important determinant of consumer preference for apples in China, affecting both the evaluation and choice of country of origin. The results also indicated that Korean organic certification significantly increased the probability of Chinese consumers choosing Korean apples. Thus, organic certification by the Korean government should be strengthened to promote apple exports to China, plus the results of this study may provide useful information to promote agricultural product exports and improve the organic certification system.

• Journal of agriculture & life science
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• v.46 no.1
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• pp.123-131
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• 2012

This study was conducted to estimate correlation structure between Hanwoo steer growth traits - body weights at 6 month, 12 month, 18 month and 24 month of age, average daily gain, carcass traits, body size traits at 18 months of age. Hanwoo progeny test data(body weight, body size traits) collected from 2004 to 2008 on a total of 1,838 steers at Hanwoo Improvement Main Center(NACF) were analyzed. Carcass traits were used to score the 24 months of age and slaughter. Correlation analyses were performed with observed scales of the traits and with residuals considering fixed effects in generalized linear models. The correlated coefficient estimated between live weight at slaughter(24 months of age) and cold carcass weight was high at 0.92. Correlation between beef yield index values and backfat thickness was estimated to be high and negative at -0.92. Hip height and wither height was found to be highly correlated(0.89). Chest width and chest depth also was found to be highly correlated at 0.73. Rump width was highly correlated with chest depth(0.75) and chest width(0.74). Correlation between pelvic width and rump width was estimated to be 0.74. Hipbone width was shown to be highly correlated with chest depth(0.73), chest width(0.70), rump width(0.75), or pelvic width(0.75). Correlation between wither height and carcass weight was 0.48 in observed scale. Chest girth was phenotyically (residual correlation) correlated with carcass weight (0.51), the estimates of which were some higher than than with the other carcass traits. This study will be utilized for Hanwoo Steers genetic evaluation.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.16 no.12
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• pp.1234-1268
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• 2004

A review on the papers published in the Korean Journal of Air-Conditioning and Refrigerating Engineering in 2002 and 2003 has been carried out. Focus has been put on current status of research in the aspect of heating, cooling, air-conditioning, ventilation, sanitation and building environment/design. The conclusions are as follows. (1) Most of fundamental studies on fluid flow were related with heat transportation in diverse facilities. Drop formation and rivulet flow on solid surfaces were interesting topics related with condensation augmentation. Research on micro environment considering flow, heat transfer, humidity was also interesting to promote comfortable living environment. It can be extended considering biological aspects. Development of fans and blowers of high performance and low noise were continuing research topics. Well developed CFD technologies were widely applied for analysis and design of various facilities and their systems. (2) Heat transfer characteristics of enhanced finned tube heat exchangers and heat sinks were extensively investigated. Experimental studies on the boiling heat transfer, vortex generators, fluidized bed heat exchangers, and frosting and defrosting characteristics were also conducted. In addition, the numerical simulations on various heat exchangers were performed and reported to show heat transfer characteristics and performance of the heat exchanger. (3) A review of the recent studies shows that the performance analysis of heat pump have been made by various simulations and experiments. Progresses have been made specifically on the multi-type heat pump systems and other heat pump systems in which exhaust energy is utilized. The performance characteristics of heat pipe have been studied numerically and experimentally, which proves the validity of the developed simulation programs. The effect of various factors on the heat pipe performance has also been examined. Studies of the ice storage system have been focused on the operational characteristics of the system and on the basics of thermal storage materials. Researches into the phase change have been carried out steadily. Several papers deal with the cycle analysis of a few thermodynamic systems which are very useful in the field of air-conditioning and refrigeration. (4) Recent studies on refrigeration and air-conditioning systems have focused on the system performance and efficiency enhancement when new alternative refrigerants are applied. Heat transfer characteristics during evaporation and condensation are investigated for several tube shapes and new alternative refrigerants including natural refrigerants. Efficiency of various compressors and performance of new expansion devices are also dealt with for better design of refrigeration/air conditioning system. In addition to the studies related with thermophysical properties of refrigerant mixtures, studies on new refrigerants are also carried out. It should be noted that the researches on two-phase flow are constantly carried out. (5) A review of the recent studies on absorption refrigeration system indicates that heat and mass transfer enhancement is the key factor in improving the system performance. Various experiments have been carried out and diverse simulation models have been presented. Study on the small scale absorption refrigeration system draws a new attention. Cooling tower was also the research object in the respect of enhancement its efficiency, and performance analysis and optimization was carried out. (6) Based on a review of recent studies on indoor thermal environment and building service systems, it is noticed that research issues have mainly focused on several innovative systems such as personal environmental modules, air-barrier type perimeterless system with UFAC, radiant floor cooling system, etc. New approaches are highlighted for improving indoor environmental conditions and minimizing energy consumption, various activities of building energy management and cost-benefit analysis for economic evaluation.

• Journal of Korea Water Resources Association
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• v.54 no.12
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• pp.1243-1254
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• 2021

For water resources operation or agricultural water management, it is important to accurately predict evapotranspiration for a long-term future over a seasonal or monthly basis. In this study, reference evapotranspiration forecast (up to 12 months in advance) was performed using statistically predicted monthly temperatures and temperature-based Hamon method for the Han River basin. First, the daily maximum and minimum temperature data for 15 meterological stations in the basin were derived by spatial-temporal downscaling the monthly temperature forecasts. The results of goodness-of-fit test for the downscaled temperature data at each site showed that the percent bias (PBIAS) ranged from 1.3 to 6.9%, the ratio of the root mean square error to the standard deviation of the observations (RSR) ranged from 0.22 to 0.27, the Nash-Sutcliffe efficiency (NSE) ranged from 0.93 to 0.95, and the Pearson correlation coefficient (r) ranged from 0.97 to 0.98 for the monthly average daily maximum temperature. And for the monthly average daily minimum temperature, PBIAS was 7.8 to 44.7%, RSR was 0.21 to 0.25, NSE was 0.94 to 0.96, and r was 0.98 to 0.99. The difference by site was not large, and the downscaled results were similar to the observations. In the results of comparing the forecasted reference evapotranspiration calculated using the downscaled data with the observed values for the entire region, PBIAS was 2.2 to 5.4%, RSR was 0.21 to 0.28, NSE was 0.92 to 0.96, and r was 0.96 to 0.98, indicating a very high fit. Due to the characteristics of the statistical models and uncertainty in the downscaling process, the predicted reference evapotranspiration may slightly deviate from the observed value in some periods when temperatures completely different from the past are observed. However, considering that it is a forecast result for the future period, it will be sufficiently useful as information for the evaluation or operation of water resources in the future.