• Journal of Life Science
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• v.23 no.1
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• pp.116-124
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• 2013

The aim was to examine resistance exercise-related genes after 8 weeks of resistance training. Thirty-two male Sprague-Dawley rats were divided into four groups: 4 weeks sedentary (4 wks CON, n=8), 8 weeks sedentary (8 wks CON, n=8), 4 weeks exercise training (4 wks REG, n=8), and 8 weeks exercise training (8 wks REG, n=8). The rats were trained to climb a 1-m vertical incline (85-degree), with weights secured to their tails. They climbed 10 times, 3 days per week, for 8 consecutive weeks. Skeletal muscle was taken from the flexor halucis longus after the exercise training. After separating the total RNA, large-scale gene expression was investigated by beadarray (Illumina RatRef-12 Expression BeadChip) analysis, and qPCR was used to inspect the beadarray data and to analyze the RNA quantitatively. The detection p-value for the genes was p<0.01, the M-value {M=$log_2$(condition)-$log_2$(reference)} was >1.0, and the DiffScore was >20. In total, the expression of 30 genes significantly increased 4 weeks after the exercise training, and the expression of six genes decreased. At 8 weeks, the expression of five genes significantly increased and that of 12 decreased. Several genes are potentially involved in resistance exercise and muscle hypertrophy, including 1) regulation of cell growth (IGFBP1, PLA2G2A, OKL38); 2) myogenesis (CSRP3); 3) tissue regeneration and muscle development (MUSTN1, MYBPH); 4) hypertrophy (CYR61, ATF3, NR4A3); and 5) glucose metabolism (G6PC, PCK1). These results may help to explain previously reported physiological changes of the skeletal muscle and suggest new avenues for further investigation.

• Korean Journal of Food Science and Technology
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• v.26 no.2
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• pp.141-146
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• 1994

As a foundational study for processing persimmon leaves tea, the physico-chemical characters were investigated in persimmon leaves from Chungdo Bansi, Sagoksi, Kyungsan Bansi and Hiratanenasi during growth. Flesh weights increased rapidly until the middle of May and then decreased slightly. Moisture contents decreased continuously from $79{\sim}81%$ at the beginning of May during growth. Water soluble tannin contents reached $1.55{\sim}2.25%$, maximum values at the middle of May and at the beginning of June, and increased again at the middle of July and then decreased. Contents of catechins, precursor of condensed tannin, indicated $12{\sim}27\;mg%$ at the middle of May and reached $17{\sim}34\;mg%$, maximum values at the middle of June. Contents of catechin were low in order of (+)-catechin, (-)-epicatechin, (-)-epicallocatechingallate, (-)-epigallocatechin and (-)-epicatechingallate. Sugars present in persimmon leaves were composed of sucrose, glucose, fructose, raffinose and mannitol. Sucrose increased continuously, glucose and fructose decreased during growth. Raffinose content was less than 0.1%. Glucose and fructose took more than 90% until the beginning of May, and then sucrose took up $60{\sim}80%$ of total sugar contents. Total vitamin C contents indicated maximum values at the middle of May and at the beginning of June in Chungdo Bansi, Sagoksi and Kyungsan Bansi, maximum vaule at the middle of July in Hiratanenasi. From the basis of these data It was suggested that proper period for picking persimmon leaves prior to processing persimmon leaves tea was from the middle of May to the beginning of June. Since maximum values for most of chemical components occurred at the middle of May and at the beginning of June and persimmon leaves thicken after the middle of June.

• Clinical and Experimental Pediatrics
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• v.50 no.8
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• pp.732-739
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• 2007

Purpose : A universal standard of the birth weight for gestational age cannot be made since birth weight distribution varies with races, nations and eras. This report aims to establish the birth weight for gestational age patterns by sex, plurality, and parity, specific for Korean live births. Methods : The national birth certificate data of all live births in Korea from January 2000 to December 2004 were used: for live births with gestational age 24 weeks to 42 weeks (n=2,585,5160), mean birth weight, standard deviation and 10th, 25th, 75th and 90th percentile values were obtained for each gestational age group by one week increment. To establish final standard values of Korean birth weight distribution by gestational age, the finite mixture model to eliminated erroneous birth weights was used for respective gestational age. Same as above method the birth weight for gestational age standard by sex, plurality, and parity were completed. Results : The male newborns are more heavier than female during the entire gestational age. The singletons are more heavier than twin during the entire gestational age. The para 2 are more heavier than the para 1 during the entire gestational age. Korean standard was more heavier in 10th and 50th percentile than Lubchenco's standard. Alexander's standard was more heavier in 50th and 90th percentile than Korean standard. Conclusion : These birth weight for gestational age patterns by sex, plurality, and parity are similar to the other standards. I hope that for Korean infants, this curve will help clinicians in defining and managing the large for gestational age infants and also for infants with intrauterine growth retardation.

• Journal of Korean Public Health Nursing
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• v.2 no.2
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• pp.81-98
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• 1988

The purpose of this study was to fine out the general physical status of the neonates, and to identify the risk factors of the mothers and the neonates which were significantly related to the neonatal diseases during hospitalization. The data were obtained from clinical records of 1098 neonates born in Seoul Red cross Hospital between January 1st of 1984 and December 31th of 1986. The results of this study were summarized as follows: 1. General characteristics of the maternal group. 1) The average of maternal age was 26.6 years, the $91.7\%$ of the mothers de liveried at the age of 20-34 years old. 2) The distribution of the types of delivey were as follows : spontaneous delivery $39.9\%$, cesarean section $32.4\%$, vaccum extraction $25.7\%$, and breech delivery$2.0\%$. 3) The $40.3\%$ of the total de liveried mother had experienced abortion. 4) The $42.3\%$ of the total deliveried mother had one or more obstetric risk factors. 2. General characteristics of the neonatal group. 1) In the distribution of sex, male was $49.4\%$, female $50.6\%$. 2) The average of birth weights was 3,020gm. The distribution of birth weight were as follows; nomal weight $85.5\%$, low birth weight $12.7\%$ and high birth weight $2.5\%$. 3) The average of gestational age was 39.2 weeks. The distribution of gestational age were as follows; full term $77.4\%$, preterm $13.7\%$, and postterm $8.9\%$. 4) The average of Apgar Score was 9.0 at one minute and 9.6 at five minutes. 5) The $5.7\%$ of the neonates had one or more neonatal risk symptoms and signs at birth. 3. Apgar Score by the maternal and neonatal factors. In Apgar Score at one minute, normal group was higher than that of abnormal group. Apgar Score at five minutes was slightly higher than that at one minute. 4. The distribution of the maternal risk factors and the neonatal risk factors. 1) The total numbers of the maternal risk factors were 1376. The distribution of the maternal risk factors were as follows: obstetric factor $33.7\%$, abortion $32.2\%$, breech and cesarean section delivery $27.5\%$ and maternal age under 19 years and over 35 years $6.6\%$. 2) The total numbers of the neonatal risk factors were 517. The distribution of the neonatal risk factors were as follows: gestational age under 37 weeks and over 42 weeks $48.0\%$, birth weight under 2500gm and over 4000gm $12.2\%$, Apgar score under 4 at one munute $6.4\%$ and Apgar score at five munutes $2.7\%$. 3) The total numbers of the obstetric risk factors were 661. The types of the obstetric risk factors were meconium stained amniotic fluid $22.0\%$, premature rupture of membrane $17.5\%$. absence prenatal care $14.1\%$, unmarried pregnancy $10.3\%$, placenta problem $9.0\%$, toxemia $8.0\%$. 4) The total numbers of the neonatal risk symptoms and signs at birth were 83. The types of the neonatal risk symptoms and signs were respiratory distress $65.1\%$, neonatal apnea $14.4\%$, convulsion $13.3%$, meconium aspiration syndrome $4.8\%$, cyanosis $2.4\%$. 5. The relationship between the maternal risk factors and the neonatal risk factors. 1) Maternal age under 19 years or over 35 years was significantly related to Apgar Score under 4 at 5 minutes. 2) Breech delivery or cesarean section was significantly related to neonatal risk factor at birth such as birth weight, gestational age, Apgar Score at one minute and at five minutes. and neonatal risk symptoms and signs. 3) Obstetric risk factors were significantly related to the neonatal risk factors at birth. 4) Abortion was not related to the neonatal risk factors. 6. The relationship between neonatal diseases during hosptalization and the maternal or the neonatal risk factors. 1) The total numbers of neonatal diseases during hospitalization were 281. The distribution of neonatal diseases were as follows: birth trauma $38.1\%$, infectious disease $31.3\%$, hematologic disease $21.4\%$, respiratory disease $6.0\%$, neurologic disease $2.5\%$. cardiovascular disease $0.7\%$. 3) Most maternal risk factors except abortion were significantly related to neonatal diseases. 4) Most neonatal risk factors at birth were significantly related to neonatal diseases.

• Korean Journal of Agricultural Science
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• v.14 no.1
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• pp.51-60
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• 1987

The study was conducted to estimate the heritabilities, genetic and phenotypic correlations on preweaning body weight and postweaning traits. The data analysis were the record of 253 male pigs produced from 54 boars of Landrace, Hampshire, Large Yorkshire and Duroc purebreds raised at National Animal Breeding Institute from 1978 to 1983. The results obtained in this study are summarized as follows. 1. The heritabilities of body weight at birth, 21days and 56days were $0.233{\pm}0.160$, $0.485{\pm}0.185$ and $0.758{\pm}0.214$, respectively, and the heritabilities estimated on postweaning traits were $0.270{\pm}0.164$ for average daily gain, $0.350{\pm}0.174$ for feed requirement, $0.272{\pm}0.165$ for backfat thickness, $0.887{\pm}0.221$ for days to 90Kg and $0.565{\pm}0.195$ for selection index. 2. Genetic correlations of body weight at birth with 21 days and 56 days were 0.349 and 0.19& and body weight at 21 days with 56 days was 0.907, and daily gain with feed requirement, backfat thickness, days to 90 Kg and selection index were -0.552, 0.107, -0.903 and 0.716, and feed requirement with backfat thickness, days to 90Kg and selection index were -0.058, 0.699 and -0.942, and backfat thickness with days to 90 Kg and selection index were -0.237 and -0.025, respectively. 3. Phenotypic correlations of body weight at birth with 21 days and 56 days were 0.342 and 0.287, and body weight at 21 days with 56 days was 0.893 and daily gain with feed requirement, backfat thickness, days to 90Kg and selection index were -0.062, 0.093, -0.651 and 0.540, and feed requirement with backfat thickness, days to 90Kg and selection index were 0.105, 0.601 and -0.613, and backfat thickness with days to 90Kg and selection index were -0.040, -0.416, respectively.

• Journal of the East Asian Society of Dietary Life
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• v.13 no.2
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• pp.98-110
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• 2003

This study investigated the nutritional status and the knowledge of the 204 elderly in Young-nam area. Their weight and height were measured and their dietary intake and nutritional knowledge evaluated. The sutjects were 74.7$\pm$5.9 years old in average. The BMIs were in the moderate range. Weights and BMI decreased significantly with age. The dietary assessment data showed that each energy intake of the males and the females was 90.9% and 97.0% compared with the Korean RDA, respectively. The dietary intake of vitamin A, calcium and iron was lower than that of the Korean RDA. The fiber intake of the subjects was 7.4g~7.8g. The MAR of vitamin $_{B2}$ was the lowest, 0.66 and that of phosphorus was the highest, 0.99. According to the nutritional knowledge level, the intake of protein, vitamin A, vitamin $B_1$and iron in the excellent group was significantly higher than that in the poor group. The correlation analysis revealed that the score of nutritional knowledge was positively associated with BMI, MAR and protein intake, while negatively with age.e.

• Journal of the Korean Society of Food Science and Nutrition
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• v.38 no.4
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• pp.415-422
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• 2009

We previously demonstrated that zinc plus arachidonic acid (ZA) treatment lowered blood glucose levels in streptozotocin-induced diabetic rats, genetically diabetic obese (ob/ob) mice, and genetically diabetic, non-obese Goto-Kakizaki rats. However, plasma insulin levels did not increase with ZA treatment, suggesting that ZA lowers blood glucose levels not by stimulating pancreatic insulin secretion. However, it is unclear whether these agents lower blood glucose levels by decreasing hepatic glucose output (HGO) or by increasing glucose utilization in peripheral tissues, or both. In order to determine ZA target organ of insulin action, we divided 18 Sprague-Dawley rats weighing ${\sim}130g$ into 3 groups (6 rats per group) and treated them for four weeks with: (1) Control diet (regular rat chow), (2) High fructose (60.0%) diet only, and (3) the same fructose diet plus zinc (10 mg/L) and arachidonic acid (50 mg/L) containing drinking water. After 4 weeks, insulin action was assessed using the hyperinsulinemic euglycemic clamp technique. Food intake and body weights were comparable in all three groups of rats throughout the study period. Plasma glucose and insulin concentrations, glucose uptake, and HGO in the basal state were all the same in these three rat groups. During the clamp study, fructose-treated and fructose+ZA treated rat groups did not exhibit any detectable change on insulin-mediated glucose uptake compared to controls. High fructose feeding impaired insulin mediated suppression of HGO, compared to controls during clamp (4.39 vs. 2.35 mg/kg/min; p<0.05). However, ZA treatment in high fructose-fed rats showed a remarkable increase in hepatic insulin sensitivity compared to high fructose-fed rats, reflected by a complete recovery in suppression of HGO during the clamp (4.39 vs. 2.18 mg/kg/min; p<0.05). This data suggests that ZA increases insulin sensitivity in liver but not glucose utilization of peripheral tissues in high fructose-fed rats.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.42 no.6
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• pp.729-738
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• 1997

To estimate the change in rice productivity around lake Juam due to construction of artificial lake, growth, yield components and yield of rice were measured at different locations around lake Juam for three years from 1994 to 1996. Automated weather stations(AWS) were installed nearby the experimental paddy fields, and daily maximum, average and minimum temperature, solar radiation, relative humidity, and precipitation were measured for the whole growing period of rice. Plant height, number of tillers, leaf area and shoot dry weight per hill were observed from 8 to 10 times in the interval of 7 days after transplanting. Yield and yield components of rice were observed at the harvest time. Simulation model of rice productivity used in the study was SIMRIW developed by Horie. The observed data of rice at 5 locations in 1994, 3 locations in 1995 and 4 locations in 1996 were inputted in the model to estimate the unknown parameters. Comparisons between observed and predicted values of shoot dry weights, leaf area indices, and rough rice yield were fairly well, so that SIMRIW appeared to predict relatively well the variations in productivity due to variations of climatic factors in the habitat. Climatic elements prior to as well as posterior to dam construction were generated at six locatons around lake Juam for thirty years by the method of Pickering et al. Climatic elements simulated in the study were daily maximum and minimum temperature, and amount of daily solar radiation. The change in rice productivity around lake Juam due to dam construction were estimated by inputting the generated climatic elements into SIMRIW. Average daily maximum temperature after dam construction appeared to be more or less lower than that before dam construction, while average daily minimum temperature became higher after dam construction. Average amount of daily solar radiation became lower with 0.9 MJ $d^{-1}$ after dam construction. As a result of simulation, the average productivity of habitats around lake Juam decreased about 5.6% by the construction of dam.

• Journal of Intelligence and Information Systems
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• v.21 no.3
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• pp.53-77
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• 2015

Korea has witnessed an increasing number of domestic patent applications, but a majority of them are not utilized to their maximum potential but end up becoming obsolete. According to the 2012 National Congress' Inspection of Administration, about 73% of patents possessed by universities and public-funded research institutions failed to lead to creating social values, but remain latent. One of the main problem of this issue is that patent creators such as individual researcher, university, or research institution lack abilities to commercialize their patents into viable businesses with those enterprises that are in need of them. Also, for enterprises side, it is hard to find the appropriate patents by searching keywords on all such occasions. This system proposes a patent recommendation system that can identify and recommend intellectual rights appropriate to users' interested fields among a rapidly accumulating number of patent assets in a more easy and efficient manner. The proposed system extracts core contents and technology sectors from the existing pool of patents, and combines it with secondary social knowledge, which derives from tags information created by users, in order to find the best patents recommended for users. That is to say, in an early stage where there is no accumulated tag information, the recommendation is done by utilizing content characteristics, which are identified through an analysis of key words contained in such parameters as 'Title of Invention' and 'Claim' among the various patent attributes. In order to do this, the suggested system extracts only nouns from patents and assigns a weight to each noun according to the importance of it in all patents by performing TF-IDF analysis. After that, it finds patents which have similar weights with preferred patents by a user. In this paper, this similarity is called a "Domain Similarity". Next, the suggested system extract technology sector's characteristics from patent document by analyzing the international technology classification code (International Patent Classification, IPC). Every patents have more than one IPC, and each user can attach more than one tag to the patents they like. Thus, each user has a set of IPC codes included in tagged patents. The suggested system manages this IPC set to analyze technology preference of each user and find the well-fitted patents for them. In order to do this, the suggeted system calcuates a 'Technology_Similarity' between a set of IPC codes and IPC codes contained in all other patents. After that, when the tag information of multiple users are accumulated, the system expands the recommendations in consideration of other users' social tag information relating to the patent that is tagged by a concerned user. The similarity between tag information of perferred 'patents by user and other patents are called a 'Social Simialrity' in this paper. Lastly, a 'Total Similarity' are calculated by adding these three differenent similarites and patents having the highest 'Total Similarity' are recommended to each user. The suggested system are applied to a total of 1,638 korean patents obtained from the Korea Industrial Property Rights Information Service (KIPRIS) run by the Korea Intellectual Property Office. However, since this original dataset does not include tag information, we create virtual tag information and utilized this to construct the semi-virtual dataset. The proposed recommendation algorithm was implemented with JAVA, a computer programming language, and a prototype graphic user interface was also designed for this study. As the proposed system did not have dependent variables and uses virtual data, it is impossible to verify the recommendation system with a statistical method. Therefore, the study uses a scenario test method to verify the operational feasibility and recommendation effectiveness of the system. The results of this study are expected to improve the possibility of matching promising patents with the best suitable businesses. It is assumed that users' experiential knowledge can be accumulated, managed, and utilized in the As-Is patent system, which currently only manages standardized patent information.

• Journal of Intelligence and Information Systems
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• v.18 no.1
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• pp.125-141
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• 2012

These days, the malicious attacks and hacks on the networked systems are dramatically increasing, and the patterns of them are changing rapidly. Consequently, it becomes more important to appropriately handle these malicious attacks and hacks, and there exist sufficient interests and demand in effective network security systems just like intrusion detection systems. Intrusion detection systems are the network security systems for detecting, identifying and responding to unauthorized or abnormal activities appropriately. Conventional intrusion detection systems have generally been designed using the experts' implicit knowledge on the network intrusions or the hackers' abnormal behaviors. However, they cannot handle new or unknown patterns of the network attacks, although they perform very well under the normal situation. As a result, recent studies on intrusion detection systems use artificial intelligence techniques, which can proactively respond to the unknown threats. For a long time, researchers have adopted and tested various kinds of artificial intelligence techniques such as artificial neural networks, decision trees, and support vector machines to detect intrusions on the network. However, most of them have just applied these techniques singularly, even though combining the techniques may lead to better detection. With this reason, we propose a new integrated model for intrusion detection. Our model is designed to combine prediction results of four different binary classification models-logistic regression (LOGIT), decision trees (DT), artificial neural networks (ANN), and support vector machines (SVM), which may be complementary to each other. As a tool for finding optimal combining weights, genetic algorithms (GA) are used. Our proposed model is designed to be built in two steps. At the first step, the optimal integration model whose prediction error (i.e. erroneous classification rate) is the least is generated. After that, in the second step, it explores the optimal classification threshold for determining intrusions, which minimizes the total misclassification cost. To calculate the total misclassification cost of intrusion detection system, we need to understand its asymmetric error cost scheme. Generally, there are two common forms of errors in intrusion detection. The first error type is the False-Positive Error (FPE). In the case of FPE, the wrong judgment on it may result in the unnecessary fixation. The second error type is the False-Negative Error (FNE) that mainly misjudges the malware of the program as normal. Compared to FPE, FNE is more fatal. Thus, total misclassification cost is more affected by FNE rather than FPE. To validate the practical applicability of our model, we applied it to the real-world dataset for network intrusion detection. The experimental dataset was collected from the IDS sensor of an official institution in Korea from January to June 2010. We collected 15,000 log data in total, and selected 10,000 samples from them by using random sampling method. Also, we compared the results from our model with the results from single techniques to confirm the superiority of the proposed model. LOGIT and DT was experimented using PASW Statistics v18.0, and ANN was experimented using Neuroshell R4.0. For SVM, LIBSVM v2.90-a freeware for training SVM classifier-was used. Empirical results showed that our proposed model based on GA outperformed all the other comparative models in detecting network intrusions from the accuracy perspective. They also showed that the proposed model outperformed all the other comparative models in the total misclassification cost perspective. Consequently, it is expected that our study may contribute to build cost-effective intelligent intrusion detection systems.