• Korean Journal of Agricultural and Forest Meteorology
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• v.17 no.1
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• pp.58-68
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• 2015

This study compares the wind stability of Larix kaempferi (Lamb.) Carr., Pinus koraiensis Sie. & Zucc. and Abies holophylla Maxim. to understand and inform wind risk management of these plantation trees at Daegwallyeong, Korea. Temporary square plots of $20m{\times}20m$ ($400m^2$) were laid out, and DBH (Diameter at Breast Height) and height for trees greater than 10 cm in DBH were measured by species. A total of 15 plots with 5 plots each in L. kaempferi, P. koraiensis and A. holophylla stands were sampled at random. Among the species, A. holophylla and P. koraiensis have comparatively lower h/d (Height/DBH) ratios than L. kaempferi. These results indicate that the former two species are more wind firm than the latter species. About 9% of the L. kaempferi trees have higher h/d ratios than the critical threshold limit 80. These trees are vulnerable to wind damage and should be removed in the next thinning regime. The analysis of variance detected a significant difference (p < 0.05) in the h/d ratios and Gini coefficient indicating species differences and DBH size variation, respectively. Gini coefficient was 16.4% in A. holophylla, 15.9% in P. koraiensis and 14% in L. kaempferi stands indicating limited DBH size variation. Lower h/d ratios are attributed to thinning in these stands and tree morphological differences. To increase wind firmness, low thinning should concentrate to remove trees with the h/d ratio above 80 coinciding at the time of stand distinction phase. Forest managers and practitioners should measure and maintain h/d ratios of trees below the critical threshold limit of 80 through stand density management. Variable density thinning approach should be tested to increase tree DBH sizes of the even-aged stands.

• Journal of Life Science
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• v.18 no.3
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• pp.291-297
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• 2008

We investigated whether 1) the combined capsaicin (75 mg), sesamin (30 mg), and L-carnitine (900 mg) (CCSC) ingestion enhances autonomic nervous system (ANS) activities including thermogenic sympathetic activity as energy metabolic modulator, 2) ${\beta}_3-AR$ polymorphism of each subject influences with ANS activity. Seven healthy males $(22.0{\pm}0.5\;yr)$ volunteered for this study. The cardiac autonomic nervous activities evaluated by means of heart rate variability of power spectral analysis were continuously measured during 5 min every 30 min for total 120 min resting condition with CCSC or placebo oral administration chosen at random. The results indicated that, there are not $Arp/Arg^{64}$ variants of the ${\beta}_3-AR$ genotypes in our subjects. There were not also significant differences in heart rate during rest between both trials. The difference of ANS activity did not reach the statistical significance between both trials. However, the significant improvement showed TOTAL power, HF component, and the indices of SNS and PNS activities before and at 30 min after CCSC ingestion (p<0.05, respectively). In conclusions, although each component of combined CCSC is associated with lipolysis and/or fat oxidation, the combined CCSC consumption is not influenced in stimulation of thermogenic sympathetic activity as modulator of energy metabolism. In rather, our results suggested that CCSC ingestion improves the balance of both SNS and PNS activities. Therefore, it will be considered many combined nutrient components for ergogenic and/or lipolysis effects as well as genetic variants affecting ANS activity in further studies.

• Journal of Korean Public Health Nursing
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• v.13 no.1
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• pp.97-113
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• 1999

To investigate the actual condition of the adult-smoking in Chinan County. I used self-reporting questionnaires among 923 residents living in nine districts selected at random among the sites of eleven eup-myons from December 28. 1998 to January 6. 1999. collected data and analyized using SPSS. The smoking rate of adults in Chinan County was $36.9\%$. There was a significant difference in smoking rate according to the age. gender, education and job among general characteristics. The smoking rate in group of above 40s was about $40\%$ and that of the male took $55.5\%$ which was higher than that of female and the smoking rate of the people having high-school education was the highest$(46.2\%)$. With regard to the career. the smoking rate of the farmers ranked first$(46.1\%)$. Therefore anti-smoking business for smokers should be focused on above 40 years old, males. people having high school education and farmers. As the result of the survey of smoking habits of 340 people who smoke currently, the average smoking begining age was 21.8 and $81.5\%$ among them was between 16-25 years old. $4.4\%$ was under 15. during around the elementary school. Most motives to smoke were as followed; curiosity or taste$(33.6\%)$, relief of stress $(31.2\%)$, peer presure$(26.5\%)$ And considering the amount of the cigarette which is smoked per day, the case which is less than a pack of cigarettes was highest as $75.5\%$ and the people who smoke over one pack of cigarettes took $24.5\%$. As for the kind of tobacco which is smoked, how to smoke and the desire for the smoking, most case was toxin was moderate$(47.8\%)$ or mild$(46.9\%)$. shallowly$(49.0\%)$ or deeply$(46.3\%)$ and under stress$(33.4\%)$. after meals$(27.8\%)$, during drink$(15.7\%)$ and so on. The highest point marked among the factors of smoking motives was 'the reduce of negative emotion' $(3.27\pm1.00)$. followed by 'uncomfortable habits' $(2.87\pm1.02)$, 'addiction' $(2.84\pm1.06)$. 'habit' $(2.74\pm1.12)$. 'pleasure' $(2.70\pm1.04)$. 'stimulus' $(2.59\pm.90)$, 'sensation-exercise satisfaction' $(2.42\pm.97)$. Smokers smoke to reduce the negative emotions when angry in most common case. depressed. anxious. uncomfortable. lone. ashamed or embarrased. and intend to solve the certain problem. etc. Other motives are uncomfortable habit. addiction. habit. pleasure and the pursuit of stimulus. The level of nicotine dependence of adults m Chinan County was 10.57 which amount to 'high' wholly. As the resulf of the level of nicotine dependence score. the people who are low in the level of nicotine was $33.5\%$. the people who are high was $48.2\%$. very high was $18.4\%$. The approach for anti-smoking for smokers should be conducted differently according to the level of the nicotine. For the people who are in low level of nicotin dependence the prohibition of the smoking should be guided through the approach to foster strong will. for those who are in 'high' by acquiring proper method for the prohibition of smoking. and for those who are 'very high' the anti-smoking should be induced by providing proper program because of the possibility of the suffer from abstinence syndrome. The difference of the level of nicotine with the general characteristics of the objects had not statistically significant difference. The difference of the level of nicotine dependence accompanied by smoking habit had statistically significant difference according to the amount of smoke, the kind of tobacos. smoke inhale habit. In other words, the group of heavy smokers had higher level of the nicotine dependence than that of the light smokers relatively and the group which smoke strong taboaco has higher level of nicotine than that of which smoke mild or moderate. And the group of smokers who smoke deeply has higher level of nicotine than that who smoke shallowly or nonswallow. Aa a result of the analysis of the correlation between smoking motive factors and the level of nicotine, there was the indication that people who smoke for the decrease of the negative emotion. habit, pleasure. stimulus. sensation-exercise satisfaction had high level of the nicotine dependence. As the result of the anti-smoking will of smokers. $65.0\%$ of them had prohibition of smoking will. $29.3\%$ had no will to quit smoke. The most important reason for anti-smoking was health. $67.9\%$ had experience to try to quit smoke and the biggest reason to fail to quit smoking was the lack of the will power to keep anti-smoking. $52.8\%$ of them were advised to stop smoking from their spouses or children. only $2.8\%$ were by medical. The people who have the opinion to need anti-smoking education were $69.6\%$. Therefore when the business for the hygine of the mouth for adult is set. it should be centered on the people who have intention of prohibition of the smoking and help to quit smoking by way of other affirmative counter-program not smoking under stress.

• Korean Journal of Health Education and Promotion
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• v.21 no.2
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• pp.17-32
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• 2004

The purpose of this study was to evaluate the patterns of stresses arising from various life styles and their related sociodemographic factors in urban residents. The subjects were recruited from the population of two ‘Dong’s (administrative blocks) representative of Daejeon city through stratified cluster random sampling during the period ranging from June I st to Aug. 31 st, 2003. Self-administered questionnaires, including items asking about subjects' sociodemographic characteristics, daily life styles, measurement of stresses by General Health Questionnaire (Goldberg, 1978), were delivered to 396 residents and their responses were analyzed with the following results. 1. Based on the discriminant scores of HPI, 46.7％ of the subjects were found to have less than 4 points (poor life style), whereas 53.3％ had points higher than 5 (good life style). Higher than 5 points were scored more frequently in females than in the male, in the age group of 40's - 60's than the 30's, in the group with spouse than without, in the group with both spouse and offsprings than without, and in the group owning a house than not. 2. Based on the degree of stress, 17.7％ of the subjects were determined to be healthy, 74.5％ were potentially under stress, and 7.8％ were at higher risk of stress. The proportion of healthy individuals were significantly higher in the male, advanced aged group(40's and 60's), the group with higher education years( over highschool), with higher monthly income over two million Won, and with spouse, than their respective counterparts. On the other hand the proportion of the individuals potentially under stress and at higher risk of stress was significantly higher in the female, in the age group of 30's and over 60's, in the group with academic career lower than middle school, with monthly income lower than two million Won, and without spouse. 3. Based on the relation of HPI with degree of stresses, subjects with HPI scores lower than 4 had increased rate of falling into the groups under potential stress and at higher risk of stress, while on the other hand those with over 5 points were found to be healthy in light of stress. 4. Based on the specific relation of each item of HPI with degree of stress, the proportion of healthy individuals was higher in the groups who take appropriate hours of sleep(7-8hours), who take breakfasts everyday, who take physical exercises everyday, who don't smoke, who don't drink alcohol, who take snacks everyday, who are overweight and obese, whereas the proportion of the group under potential stress and at higher risk of stress was higher in their comparable counterparts. 5. The relation of mean scores of HPI with stress scores in both male and female subjects showed negative correlation that the higher HPI scores, the lower stress scores. 6. Multivariate regression analysis to reveal the factors influencing the stress of the subjects showed that for men the significant factors were age, education, presence of job or not, exercise, subjective health status, with the explanatory power of 26.3％. For women, they included educational years, presence of spouse or not, job, owning a house or not, sleeping hours, drinking habit, taking snacks, subjective health status, with the explanatory power of 31.8％. The above study results suggests that stresses of urban residents have significant correlation with daily life styles and this correlation is also remarkably distinguished by different age and sex.

• 한국벤처창업학회:학술대회논문집
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• 2010.08a
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• pp.139-160
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• 2010

On July 21st in 2005, People's Bank of China (PBOC) turned the currency peg against the U.S. dollar into managed currency system based on a basket of unnamed currencies under China's exchanged rate regime. This change means that China's enterprises are not free from currency fluctuations. The purpose of this study is to analyze the relations between Renminbi fluctuations in the floating exchange rate and financial results of venture companies. The process and outcomes of this study are as follows, First, in order to measure the financial results of venture companies, I choose venture companies in Shandong Province listed on the Shanghai Stock Exchange (SSE) at random and several quarter financial sheets according to safety ratios, profitability ratios, growth ratios, activity ratios. Second, I arrange the daily Renminbi exchange rate data announced from July 21st, 2005 to December 31st, 2008 by PBOC into the quarterly data. Third, in order to confirm the relations between Renminbi fluctuations and financial results of venture companies, I carry out Pearson's correlation analysis. As a result, the revaluation of the Chinese Renminbi has weakly negative effects on debt ratio, total assets turnover ratio and equity turnover ratio in statistics. But the revaluation of the Chinese Renminbi is not related to other financial index in statistics. The result of this study is that the revaluation of the Chinese Renminbi has little influence on the export and import of Chinese venture companies and certifies the fact that Chinese venture companies have much foreign currency assets. In addition to avoid the currency exposure risk, this study shows the effective method about currency exposure risk which adjusts proportion of Renminbi to foreign currency.

• Journal of Mushroom
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• v.11 no.3
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• pp.154-158
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• 2013

To develop a new variety of oyster mushroom(Pleurotus ostreatus), parental strains was selected by the method of Mon-Mon crossing between monokaryotic strains derived from ASI 2596(Suhan No.3) and ASI 2782(Black pileus mutant). The SB-73(ASI 2596-11 x 2782-8) was shown the best cultural characteristics, selected to be a new variety and named as 'Dagul'. The 'Dagul' was formed incompatibility line distinctly in the confrontation growth of parental strains Suhan No.3 and ASI 2782. The optimum temperature for mycelial growth, fruiting body development and pH arrange were $25{\sim}30^{\circ}C$, $14{\sim}17^{\circ}C$ and pH5~8, respectively. Fruiting body production per bottle was about $68.0{\pm}24.1$ g which is almost 115% quantity compared to that of other variety Suhan No.3. And also the stipe is long and individual generation is multiple. Analysis of the genetic characteristics of the new variety 'Dagul' showed different DNA bands as that of the control strains, Suhan No.3 and ASI 2782, when RAPD(Random Amplified Polymorphic DNA) primers URP7 and Rcb1 were used. This new variety 'Dagul' of oyster mushroom is characterized by multiple of individual generation and the stipe is long. We therefore expect that this new strain will increase of the income by cultivation of field.

• Journal of Aquaculture
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• v.13 no.2
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• pp.129-135
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• 2000

Genetic variabilities of local populations of Anthocidaris crassispina and Hemicentrotus pulcherrimus were analysed by random amplified polymorphic DNA (RAPD) technique with phenotypic variabilities in timing of gonadal maturation, reproductive output and size of individuals in Cheju. H, pulcherrimus, collected from 4 locations during March 1997, indicated that Daepo individuals were significantly smaller than that at Hamdok, Wimi site A and Wimi site B (ANOVA, p>0.001). Gonodal-somatic index (GSI) of the Wimi site B population was significantly higher than that of three other locations (ANOVA, P>0.0001). An ANOVA test conducted on test size of A. crassispina, harvested from six different locations of Cheju during June 1997, indicated that the size of individuals from Pophwan was significantly smaller (P>0.0001) than that from five other locations. GSIs of urchin m Wimi and Hanlim were significantly higher than that from Pohwan and Oedo (ANOVA, p>0.0001). Genetic similarity, calculated from k13 primer analysis of total DNA, among the six different populations of A. crassispina varied from 0.67 to 0.92, and the values for H. pulcherrimus from 0.60 to 0.73; thus there was no genetic variation among different populations of the same species. Therefore, the populations are genetically homologous and the observed phenotypic variabilities were possibly associated with water temperature and food.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.46 no.6
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• pp.453-458
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• 2001

The Rural Development Administration (RDA) of Korea now operates a system called Rice Variety Selection Tests (RVST), which are now being implemented in eight Agricultural Research and Extension Services located in eight province RVST's objective is to provide accurate yield estimates and to select well-adapted varieties to each province. Systematic evaluation of entries included in RVST is a highly important task to select the best-adapted varieties to specific location and to observe the performance of entries across a wide range of test sites within a region. The rice yield data in RVST for ordinary transplanting in Kangwon province during 1997-2000 were analyzed. The experiments were carried out in three replications of a random complete block design with eleven entries across five locations. Additive Main effects and Multiplicative Interaction (AMMI) model was employed to examine the interaction between genotype and environment (G$\times$E) in the biplot form. It was found that genotype variability was as high as 66％, followed by G$\times$E interaction variability, 21％, and variability by environment, 13％. G$\times$E interaction was partitioned into two significant (P＜0.05) principal components. Pattern analysis was used for interpretation on G$\times$E interaction and adaptibility. Major determinants among the meteorological factors on G$\times$E matrix were canopy minimum temperature, minimum relative humidity, sunshine hours, precipitation and mean cloud amount. Odaebyeo, Obongbyeo and Jinbubyeo were relatively stable varieties in all the regions. Furthermore, the most adapted varieties in each region, in terms of productivity, were evaluated.

• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.39-54
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• 2013

Recent explosive increase of electronic commerce provides many advantageous purchase opportunities to customers. In this situation, customers who do not have enough knowledge about their purchases, may accept product recommendations. Product recommender systems automatically reflect user's preference and provide recommendation list to the users. Thus, product recommender system in online shopping store has been known as one of the most popular tools for one-to-one marketing. However, recommender systems which do not properly reflect user's preference cause user's disappointment and waste of time. In this study, we propose a novel recommender system which uses data mining and multi-model ensemble techniques to enhance the recommendation performance through reflecting the precise user's preference. The research data is collected from the real-world online shopping store, which deals products from famous art galleries and museums in Korea. The data initially contain 5759 transaction data, but finally remain 3167 transaction data after deletion of null data. In this study, we transform the categorical variables into dummy variables and exclude outlier data. The proposed model consists of two steps. The first step predicts customers who have high likelihood to purchase products in the online shopping store. In this step, we first use logistic regression, decision trees, and artificial neural networks to predict customers who have high likelihood to purchase products in each product group. We perform above data mining techniques using SAS E-Miner software. In this study, we partition datasets into two sets as modeling and validation sets for the logistic regression and decision trees. We also partition datasets into three sets as training, test, and validation sets for the artificial neural network model. The validation dataset is equal for the all experiments. Then we composite the results of each predictor using the multi-model ensemble techniques such as bagging and bumping. Bagging is the abbreviation of "Bootstrap Aggregation" and it composite outputs from several machine learning techniques for raising the performance and stability of prediction or classification. This technique is special form of the averaging method. Bumping is the abbreviation of "Bootstrap Umbrella of Model Parameter," and it only considers the model which has the lowest error value. The results show that bumping outperforms bagging and the other predictors except for "Poster" product group. For the "Poster" product group, artificial neural network model performs better than the other models. In the second step, we use the market basket analysis to extract association rules for co-purchased products. We can extract thirty one association rules according to values of Lift, Support, and Confidence measure. We set the minimum transaction frequency to support associations as 5%, maximum number of items in an association as 4, and minimum confidence for rule generation as 10%. This study also excludes the extracted association rules below 1 of lift value. We finally get fifteen association rules by excluding duplicate rules. Among the fifteen association rules, eleven rules contain association between products in "Office Supplies" product group, one rules include the association between "Office Supplies" and "Fashion" product groups, and other three rules contain association between "Office Supplies" and "Home Decoration" product groups. Finally, the proposed product recommender systems provides list of recommendations to the proper customers. We test the usability of the proposed system by using prototype and real-world transaction and profile data. For this end, we construct the prototype system by using the ASP, Java Script and Microsoft Access. In addition, we survey about user satisfaction for the recommended product list from the proposed system and the randomly selected product lists. The participants for the survey are 173 persons who use MSN Messenger, Daum Caf$\acute{e}$, and P2P services. We evaluate the user satisfaction using five-scale Likert measure. This study also performs "Paired Sample T-test" for the results of the survey. The results show that the proposed model outperforms the random selection model with 1% statistical significance level. It means that the users satisfied the recommended product list significantly. The results also show that the proposed system may be useful in real-world online shopping store.

• Journal of Intelligence and Information Systems
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• v.25 no.4
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• pp.105-122
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• 2019

Dimensionality reduction is one of the methods to handle big data in text mining. For dimensionality reduction, we should consider the density of data, which has a significant influence on the performance of sentence classification. It requires lots of computations for data of higher dimensions. Eventually, it can cause lots of computational cost and overfitting in the model. Thus, the dimension reduction process is necessary to improve the performance of the model. Diverse methods have been proposed from only lessening the noise of data like misspelling or informal text to including semantic and syntactic information. On top of it, the expression and selection of the text features have impacts on the performance of the classifier for sentence classification, which is one of the fields of Natural Language Processing. The common goal of dimension reduction is to find latent space that is representative of raw data from observation space. Existing methods utilize various algorithms for dimensionality reduction, such as feature extraction and feature selection. In addition to these algorithms, word embeddings, learning low-dimensional vector space representations of words, that can capture semantic and syntactic information from data are also utilized. For improving performance, recent studies have suggested methods that the word dictionary is modified according to the positive and negative score of pre-defined words. The basic idea of this study is that similar words have similar vector representations. Once the feature selection algorithm selects the words that are not important, we thought the words that are similar to the selected words also have no impacts on sentence classification. This study proposes two ways to achieve more accurate classification that conduct selective word elimination under specific regulations and construct word embedding based on Word2Vec embedding. To select words having low importance from the text, we use information gain algorithm to measure the importance and cosine similarity to search for similar words. First, we eliminate words that have comparatively low information gain values from the raw text and form word embedding. Second, we select words additionally that are similar to the words that have a low level of information gain values and make word embedding. In the end, these filtered text and word embedding apply to the deep learning models; Convolutional Neural Network and Attention-Based Bidirectional LSTM. This study uses customer reviews on Kindle in Amazon.com, IMDB, and Yelp as datasets, and classify each data using the deep learning models. The reviews got more than five helpful votes, and the ratio of helpful votes was over 70% classified as helpful reviews. Also, Yelp only shows the number of helpful votes. We extracted 100,000 reviews which got more than five helpful votes using a random sampling method among 750,000 reviews. The minimal preprocessing was executed to each dataset, such as removing numbers and special characters from text data. To evaluate the proposed methods, we compared the performances of Word2Vec and GloVe word embeddings, which used all the words. We showed that one of the proposed methods is better than the embeddings with all the words. By removing unimportant words, we can get better performance. However, if we removed too many words, it showed that the performance was lowered. For future research, it is required to consider diverse ways of preprocessing and the in-depth analysis for the co-occurrence of words to measure similarity values among words. Also, we only applied the proposed method with Word2Vec. Other embedding methods such as GloVe, fastText, ELMo can be applied with the proposed methods, and it is possible to identify the possible combinations between word embedding methods and elimination methods.