• The Korean Journal of Pharmacology
• /
• v.23 no.1
• /
• pp.1-7
• /
• 1987

The renal handling and tissue distribution of pyrazinamide were studied after administration of single dose intravenous injection for 15 min or constant infusion in New Zealand White rabbits. Peak pyrazinamide serum concentration ranged from 57.3 to $105.0{\mu}g/ml$ ($mean{\pm}SD;83.0{\pm}17.8$). The mean half-life of the a phase was $0.143{\pm}0.047$ hr while the ${\beta}$ phase ranged from 1.66 to 3.25 hr($mean{\pm}SD;2.38{\pm}0.57$). The mean steady-state volume of distribution in non-compartmental model was $0.935{\pm}0.362\;L/kg$ Excretion ratio of pyrazinamide was dramatically reduced from 1.02 to 0.30 when unbound serum pyrazinamide concentration was increased from 6.04 to $60.9\;{\mu}g/ml$. The urine flow dependency of renal clearance of pyrazinamide was demonstrated in steady-state serum concentration. The tissue/serum concentration ratio of pyrazinamide was highest in kidney and lowest in skeletal muscle among the tissues examined. The results suggested that a large fraction of pyrazinamide filtered by glomerulus and secreted by renal tubule was reabsorbed and this tubular reabsorption of pyrazinamide might be greatly influenced by urine flow.

• Journal of the Korean Society of Food Science and Nutrition
• /
• v.43 no.8
• /
• pp.1296-1303
• /
• 2014

This study was conducted to develop predictive models for the growth of Bacillus cereus on carrot treated with slightly acidic electrolyzed water (SAcEW) and ultrasonication (US) at different storage temperatures. In addition, the inactivation of B. cereus by US with SAcEW was investigated. US treatment with a frequency of 40 kHz and an acoustic energy density of 400 W/L at $40^{\circ}C$ for 3 min showed the maximum reduction of 2.87 log CFU/g B. cereus on carrot, while combined treatment of US (400 W/L, $40^{\circ}C$, 3 min) with SAcEW reached to 3.1 log CFU/g reduction. Growth data of B. cereus on carrot treated with SAcEW and US at different temperatures (4, 10, 15, 20, 25, 30, and $35^{\circ}C$) were collected and used to develop predictive models. The modified Gompertz model was found to be more suitable to describe the growth data. The specific growth rate (SGR) and lag time (LT) obtained from the modified Gompertz model were employed to establish the secondary models. The newly developed secondary models were validated using the root mean square error, bias factor, and accuracy factor. All results of these factors were in the acceptable range of values. After compared SGR and LT of B. cereus on carrot, the results showed that the growth of B. cereus on carrot treated with SAcEW and US was slower than that of single treatment. This result indicates that shelf life of carrot treated with SAcEW and US could be extended. The developed predictive models might also be used to assess the microbiological risk of B. cereus infection in carrot treated with SAcEW and US.

• Journal of Sericultural and Entomological Science
• /
• v.53 no.2
• /
• pp.135-142
• /
• 2015

The American cockroaches, Periplaneta americana L. was the most important worldwide pest species. It has been an public health problems. We were determinated life cycle and extraction of crude extracts by chemical reagents from cockraches (P. americana L.). The extracted crude solution has been antibacterial activity to gram negative bacteria (Pseudomonas aeruginosa, $6.44{\pm}1.03mm$), gram positive bacteria (Bacillus subtilis, $1.88{\pm}0.40mm$), and fungus (Candida albicans, $5.61{\pm}0.57mm$) using radial diffusion assay. We were analysed of up-regulation of Glutathione-S-transferases (GSTs) stimulation, indicating that antioxidantial protein from various classes are simultaneously expressed in a single insect upon infection or injury. The gene from Periplaneta americana L. were cloned, analysed sequence, and measured protein expression by Real Time PCR (Polymerase Chain Reaction).

• Korean Journal of Heritage: History & Science
• /
• v.50 no.3
• /
• pp.64-87
• /
• 2017

Dahoe is a traditional braid in Joseon Dynasty. There are many Dahoe artifacts, which can give us a glimpse of the costume, culture, and life of that era. The study of Dahoe is necessary in various fields, but it is difficult because this manufacturing technique has been passed down from hand to hand. Few studies have been done so far. This research examines the manufacturing technique of KwangDahoe which is passed down by Maedeupjang (Decorative Knotting) and is generally used for knotting and/or tying objects. The main characteristic of TieKwangDahoe, made through the same method as WonDahoe, is the square hole in the middle. It was impossibile to remake the original braid because there is no confirmed number of the strand. Especially it is very difficult to do conservation and restoration on serious degradation state of the fiber. Therefore, it is necessary to analyze the non-destructive manufacturing techniques method for Dahoe and assess their applicability. First, we analyzed the artifacts' manufacturing technique based on the database of the Dahoe's manufacturing technique. In order to do that, we undertook schematization, restoration, morphological analyzation of the Dahoe. And then, X-ray CT scans were performed to improve the reliability of the DB. These results of scanning were interpreted based on the manufacturing technique. The selected Tie-KwangDahoe on the sword for the study are artifacts including artistic value and symbolism in Joseon Dynasty. Based on the analysis of the manufacturing technique, we found that both artifacts were made of 20-strand braid of single cross according to the length-scale measure. It was manufactured using 8-strand on left-right side, 12-strand on front-back side by the braiding manufacturing technique method Finally, this research suggests non-destructive analysis method of Dahoe's manufacturing technique is based on the database and the analysis results. I hope this research can be useful in various professional fields of Dahoe in the future. Moreover, I hope this can be of any help in preserving Korean cultural heritage.

• Journal of Intelligence and Information Systems
• /
• v.24 no.4
• /
• pp.1-32
• /
• 2018

In addition to stakeholders including managers, employees, creditors, and investors of bankrupt companies, corporate defaults have a ripple effect on the local and national economy. Before the Asian financial crisis, the Korean government only analyzed SMEs and tried to improve the forecasting power of a default prediction model, rather than developing various corporate default models. As a result, even large corporations called 'chaebol enterprises' become bankrupt. Even after that, the analysis of past corporate defaults has been focused on specific variables, and when the government restructured immediately after the global financial crisis, they only focused on certain main variables such as 'debt ratio'. A multifaceted study of corporate default prediction models is essential to ensure diverse interests, to avoid situations like the 'Lehman Brothers Case' of the global financial crisis, to avoid total collapse in a single moment. The key variables used in corporate defaults vary over time. This is confirmed by Beaver (1967, 1968) and Altman's (1968) analysis that Deakins'(1972) study shows that the major factors affecting corporate failure have changed. In Grice's (2001) study, the importance of predictive variables was also found through Zmijewski's (1984) and Ohlson's (1980) models. However, the studies that have been carried out in the past use static models. Most of them do not consider the changes that occur in the course of time. Therefore, in order to construct consistent prediction models, it is necessary to compensate the time-dependent bias by means of a time series analysis algorithm reflecting dynamic change. Based on the global financial crisis, which has had a significant impact on Korea, this study is conducted using 10 years of annual corporate data from 2000 to 2009. Data are divided into training data, validation data, and test data respectively, and are divided into 7, 2, and 1 years respectively. In order to construct a consistent bankruptcy model in the flow of time change, we first train a time series deep learning algorithm model using the data before the financial crisis (2000~2006). The parameter tuning of the existing model and the deep learning time series algorithm is conducted with validation data including the financial crisis period (2007~2008). As a result, we construct a model that shows similar pattern to the results of the learning data and shows excellent prediction power. After that, each bankruptcy prediction model is restructured by integrating the learning data and validation data again (2000 ~ 2008), applying the optimal parameters as in the previous validation. Finally, each corporate default prediction model is evaluated and compared using test data (2009) based on the trained models over nine years. Then, the usefulness of the corporate default prediction model based on the deep learning time series algorithm is proved. In addition, by adding the Lasso regression analysis to the existing methods (multiple discriminant analysis, logit model) which select the variables, it is proved that the deep learning time series algorithm model based on the three bundles of variables is useful for robust corporate default prediction. The definition of bankruptcy used is the same as that of Lee (2015). Independent variables include financial information such as financial ratios used in previous studies. Multivariate discriminant analysis, logit model, and Lasso regression model are used to select the optimal variable group. The influence of the Multivariate discriminant analysis model proposed by Altman (1968), the Logit model proposed by Ohlson (1980), the non-time series machine learning algorithms, and the deep learning time series algorithms are compared. In the case of corporate data, there are limitations of 'nonlinear variables', 'multi-collinearity' of variables, and 'lack of data'. While the logit model is nonlinear, the Lasso regression model solves the multi-collinearity problem, and the deep learning time series algorithm using the variable data generation method complements the lack of data. Big Data Technology, a leading technology in the future, is moving from simple human analysis, to automated AI analysis, and finally towards future intertwined AI applications. Although the study of the corporate default prediction model using the time series algorithm is still in its early stages, deep learning algorithm is much faster than regression analysis at corporate default prediction modeling. Also, it is more effective on prediction power. Through the Fourth Industrial Revolution, the current government and other overseas governments are working hard to integrate the system in everyday life of their nation and society. Yet the field of deep learning time series research for the financial industry is still insufficient. This is an initial study on deep learning time series algorithm analysis of corporate defaults. Therefore it is hoped that it will be used as a comparative analysis data for non-specialists who start a study combining financial data and deep learning time series algorithm.

• Journal of Distribution Research
• /
• v.15 no.1
• /
• pp.1-24
• /
• 2010

I. Introduction The industry of domestic discount store was reorganized with 2 bigs and 1 middle, and then Home Plus took over Home Ever in 2008. In present, Oct, 2008, E-Mart has 118 outlets, Home Plus 112 outlets, and Lotte Mart 60 stores. With total number of 403 outlets, they are getting closer to a saturation point. We know that the industry of discount store has been getting through the mature stage in retail life cycle. There are many efforts to maintain existing customers rather than to get new customers. These competitions in this industry lead firms to acknowledge 'store loyalty' to be the first strategic tool for their sustainable competitiveness. In other words, the strategic goal of discount store is to boost up the repurchase rate of customers throughout increasing store loyalty. If owners of retail shops can figure out main factors for store loyalty, they can easily make more efficient and effective retail strategies which bring about more sales and profits. In this practical sense, there are many papers which are focusing on the antecedents of store loyalty. Many researchers have been inspecting causal relationships between antecedents and store loyalty; store characteristics, store image, atmosphere in store, sales promotion in store, service quality, customer characteristics, crowding, switching cost, trust, satisfaction, commitment, etc., In recent times, many academic researchers and practitioners have been interested in 'dual path model for service loyalty'. There are two paths in store loyalty. First path has an emphasis on symbolic and emotional dimension of service brand, and second path focuses on quality of product and service. We will call the former an extrinsic path and call the latter an intrinsic path. This means that consumers' cognitive path for store loyalty is not single but dual. Existing studies for dual path model are as follows; First, in extrinsic path, some papers in domestic settings show that there is 'store personality-identification-loyalty' path. Second, service quality has an effect on loyalty, which is a behavioral variable, in the mediation of customer satisfaction. But, it's very difficult to find out an empirical paper applied to domestic discount store based on this mediating model. The domestic research for store loyalty concentrates on not only intrinsic path but also extrinsic path. Relatively, an attention for intrinsic path is scarce. And then, we acknowledge that there should be a need for integrating extrinsic and intrinsic path. Also, in terms of retail industry, this study is meaningful because retailers want to achieve their competitiveness by using store loyalty. And so, the purpose of this paper is to integrate and complement two existing paths into one specific model, dual path model. This model includes both intrinsic and extrinsic path for store loyalty. With this research, we would expect to understand the full process of forming customers' store loyalty which had not been clearly explained. In other words, we propose the dual path model for discount store loyalty which has been originated from store personality and service quality. This model is composed of extrinsic path, discount store personality$\rightarrow$store identification$\rightarrow$store loyalty, and intrinsic path, service quality of discount store$\rightarrow$customer satisfaction$\rightarrow$store loyalty. II. Research Model Dual path model integrates intrinsic path and extrinsic path into one specific model. Intrinsic path put an emphasis on quality characteristics and extrinsic path focuses on brand characteristics. Intrinsic path is based on information processing perspective, and extrinsic path emphasizes symbolic and emotional dimension of brand. This model is composed of extrinsic path, discount store personality$\rightarrow$store identification$\rightarrow$store loyalty, and intrinsic path, service quality of discount store$\rightarrow$customer satisfaction$\rightarrow$store loyalty. Hypotheses are as follows; Hypothesis 1: Service quality perceived by customers in discount store has an positive effect on customer satisfaction Hypothesis 2: Store personality perceived by customers in discount store has an positive effect on store identification Hypothesis 3: Customer satisfaction in discount store has an positive effect on store loyalty. Hypothesis 4: Store identification has an positive effect on store loyalty. III. Results and Implications We examined consumers who patronize discount stores for samples of this study. With the structural equation model(SEM) analysis, we empirically tested the validity and fitness of the dual path model for store loyalty in discount stores. As results, the fitness indices of this model were well fitted to data obtained. In an intrinsic path, service quality(SQ) is positively related to customer satisfaction(CS), customer satisfaction(CS) has very significantly positive effect on store loyalty(SL). Also, in an extrinsic path, the store personality(SP) is positively related to store identification(SI), it shows significant effect on store loyalty. Table 1 shows the results as follows; There are some theoretical and practical implications. First, Many studies on discount store loyalty have been executed from various perspectives. But there has been no integrative view on this issue. And so, this research was theoretically designed to integrate various and controversial arguments into one systematic model. We empirically tested dual path model forming store loyalty, and brought up a systematic and integrative framework for future studies. We want to expect creative and aggressive research activities. Second, a few established papers are focused on the relationship between antecedents and store loyalty; store characteristics, atmosphere, sales promotion in store, service quality, trust, commitment, etc., There has been some limits in understanding thoroughly the formation process of store loyalty with a singular path, intrinsic or extrinsic. Beyond these limits in single path, we could propose the new path for store loyalty. This is meaningful. Third, discount store firms make and execute marketing strategies for increasing store loyalty. This research provides real practitioners with reference framework needed for actual strategy formation. Because this paper shows integrated and systematic path for store loyalty. A special feature of this study is to represent 6 sub dimensions of service quality in intrinsic path and 4 sub dimensions of store personality in extrinsic path. Marketers can make more analytic marketing planning with concrete sub dimensions of service quality and store personality. When marketers of discount stores make strategic planning like MPR, Ads, campaign, sales promotion, they can use many items which are more competitive than competitors.

• Journal of Bio-Environment Control
• /
• v.22 no.4
• /
• pp.355-360
• /
• 2013

Diesel-burning air heater (air heater) and infrared heating lamp (infrared heater) were installed as auxiliary heaters in two single water-curtained plastic greenhouses with a set night temperature of $6^{\circ}C$ for cultivation of strawberry 'Seolhyang'. The average night air temperature was $6.6^{\circ}C$ in the infrared heater treatment and $7.1^{\circ}C$ in the air heater treatment. However, when the minimum outside temperature fell below $-10^{\circ}C$, the air heater had less internal temperature fluctuations. In contrast, the infrared heater had some cases of falling below the set temperature. The relative humidity was higher than 98% by the side-effect of water-curtain system regardless of the heating system. There was about $5^{\circ}C$ difference in leaf temperature between the turned-on and -off state of the infrared heater, and the efficacy of the infrared heater on leaf temperature was only limited to about 4 meters from the system. Peduncle length and plant height in the infrared heater tended to be greater than those in the air heater. There was, however, no statistically difference in leaf size and numbers of leaves, flowers on first cluster and branches. There was no difference in soluble solids content, fruit firmness, average fruit weight of the harvested fruits, and the yield. Comparing the heating costs, the air heater system took 622,662 won based on 543 L tax-free diesel, while the infrared heater system took 235,284 won by consuming 5,685 kWh of electricity, and 62.2% heating costs saving was achieved.

• Korean Journal of Environment and Ecology
• /
• v.28 no.5
• /
• pp.550-558
• /
• 2014

This study was conducted to investigate the distribution and the population dynamics of Hipparchia autonoe by using a line transect and Mark-Release-Recapture (MRR) at the Mt. Halla in Jeju Island. The results showed that H. autonoe was found from 1,500 m above the sea level. Total 1,493 H. autonoe with 978 males and 515 females were captured and released in the MRR study site. Among them, 518 individuals including 284 males and 234 females were recaptured. The average survival time was 2.31 days with 2.14 days for males and 3.47 days for females, indicating longer survival time in case of females than males. The daily population size of males estimated in the MRR study site was maintained about 1,000 individuals in July and gradually decreased less than 200 in August. The number of females showed peak at 335 individuals on July 24, and gradually decreased less than 120 in August. Thus, female population was 1/3 of males. The average travel distance of male and female H. autonoe were $116.8{\pm}191.9m$ and $118.4{\pm}161.5m$, respectively, indicating almost same between sexes. H. autonoe in the Mt. Halla formed single population group in the wide meadow around the Baekrokdam Lake. The highest population density of H. autonoe was occurred in the restored area from damages, where host plants such as the sheep's fescue or the food plant are abundant by artificial restoration efforts.

• Journal of Embryo Transfer
• /
• v.31 no.3
• /
• pp.227-233
• /
• 2016

This study was conducted to analyze the effect of single nucleotide polymorphisms (SNPs) on the equine chromosomes (ECA) 3 for the body conformations of 12 month of age in Jeju crossbred (Jeju horses ${\times}$ Thoroughbred). A total of 199 Jeju crossbred horse samples were obtained from the National Institute of Subtropical Livestock Research Institute for this study. To correctly estimate the body conformations, we measured thirteen elements relevant to the body conformation such as body weight, wither height, body length for all the 199 horses at 12 month of age. Furthermore, all the horses were genotyped using four SNPs including the BIEC2-808466, BIEC2-808543, BIEC2-808967, BIEC2-809370, of which genomic coordinates range approximately from 105.1Mbp to 110 Mbp in the ECA3. For the phenotypic data sets, the average body weight was $193.7{\pm}24.5kg$ and the height was $124.5{\pm}4.0cm$. As for the genotypic data, the miner allele frequencies of the SNPs were shown to be varied from 0.01 to 0.291. Using the phenotypic and genotypic data sets, analysis of covariance was performed to find any association between those SNP genotypes and body conformations, using year of birth, month of birth, sex, and parity as the covariance components. The result showed that alternative genotypes in the BIEC2-808967 and BIEC2-809370 SNPs were significantly associated with the body length (P<0.05) and the wither height (P<0.05) respectively in the Jeju crossbred horses. Therefore, it is estimated that there are significant associations in the body conformation of 12 month of age of Jeju crossbred for those two SNPs used in this study.

• Investigative Magnetic Resonance Imaging
• /
• v.6 no.1
• /
• pp.64-72
• /
• 2002

Purpose : To introduce and demonstrate the advantages of the new hybrid two-dimensional (2D) proton spectroscopic imaging (SI) over the single voxel spectroscopy (SVS) and conventional 2D SI in the clinical application of spectroscopy for pediatric cerebral disease. Materials and Methods : Eighty-one hybrid 2D proton spectroscopic imaging was performed in 79 children (36 normal infants and children, 10 with hypoxic-ischemic injury, 20 with toxic-metabolic encephalopathy, seven with brain tumor, three with meningoencephalitis, one with neurofibromatosis, one with Sturge-Weber syndrome and one with lissencephaly) ranging in age from the third day of life to 15 years. In adult volunteers (n=5), all three techniques including hybrid 2D proton SI, SVS using PRESS sequence, and conventional 2D proton SI were performed. Both hybrid 2D proton SI and SVS using PRESS sequence were performed in clinical cases (n=). All measurements were performed with a 1.5-T scanner using standard head quadrature coil. The 16$\times$16 phase encoding steps were set on variable field of view (FOV) depending on the size of the brain. The hybrid volume of interest inside FOV was set as $75{\times}75{\times}15{\;}\textrm{mm}^3$ or smaller to get rid of unwanted fat signal. Point-resolved spectroscopy (TR/TE=1,500 msec/135 or 270msec) was employed with standard chemical shift selective saturation (CHESSI pulses for water suppression. The acquisition time and spectral quality of hybrid 2D proton SI were compared with those of SVS and conventional 2D proton SI. Results : The hybrid 2D proton SI was successfully conducted upon all patients.