• Journal of the Korean Society of Food Science and Nutrition
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• v.34 no.7
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• pp.987-999
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• 2005

The purpose of this study was to evaluate the effect of short-term nutrition education camp on food and nutrient intakes of obese children. The subjects of the study were 30 obese children in Gumi city who have obesity index over $130\%$. The food consumption of the subjects was surveyed for three days before the camp, for eleven days during the first camp and for three days after the second camp, by food record method. The mean intakes of energy and carbohydrates in obese children were significantly decreased during and after the nutrition education camp, and that of vitamin C was significantly increased after the camp. The mean daily total food intake of the subjects was gradually decreased from 1646.4g before the camp to 1438.6g during the camp and 1412.66g after the camp. Energy and fat intake ratios from grains and milks were significantly decreased after the camp compared with that before the camp, and the energy intake ratio from grains, milks and eggs was significantly low during the camp. The protein intake ratios from grains, potatoes, vegetables and fishes were significantly increased after the camp. The calcium intake ratios from potatoes and milks were significantly increased during and after the camp, and the ratio from eggs was significantly decreased after the camp. The iron intake ratios from potatoes and fishes were significantly increased during and after the camp, and the ratio from grains was significantly low during the camp. The results of the study demonstrated that the short-term nutrition education program positively affected the overall food consumption and nutrients intakes of obese children.

• Journal of the Korean Society of Food Science and Nutrition
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• v.21 no.1
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• pp.36-42
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• 1992

The lipid compositions of total lipid extracted from the flesh divided into albinic type and melanic type of culture shellfishes, i.e. Achatina fucica Bowdich, Ampullarius insularus were compared. Total lipid contents of shellfishes were $1.11{\sim}3.25%$, the levels were appeared higher in Ampullarius insularus than Achatina fucica Bowdich, and in albinic type than melanic type. It was found that the contents of neutral lipids $(31.79{\sim}40.60%)$ and phospholipids $(50.95{\sim}62.12%)$ were high, while that of glycolipids $(4.84{\sim}9.47%)$ were low. The major fatty acids in total lipid of each sample were $C_{18:2}(11.92{\sim}14.37%)$, $C_{18:1}(12.34{\sim}13.64%)$, $C_{20:4}(11.03{\sim}13.74%)$, $C_{16:0}(7.45{\sim}15.39%)$ and $C_{18:0}(7.34{\sim}11.80%)$ and additionally $C_{20:2}(9.62{\sim}10.19%)$ in Achatina fucica Bowdich, and the major fatty acid composition in total lipids of each sample showed no significant differences between albinic type and melanic type, respectively. Particularly the content of $C_{16:0}$ in total lipids was shown more abundant in Ampullarius insularus and that of $C_{18:0}$, C_{20:2}$ in Achatina fucica Bowdich. The content of polyene acids in total lipids occupied higher level in Achatina fucica Bowdich but $C_{22:6}$ was almost detected, and observed relatively higher amounts in Ampullarius insularus. The main fatty acids in neutral lipid of Achatina fucica Bowdich were $C_{18:2}(16.80{\sim}17.74%)$, $C_{20:2}(12.15{\sim}12.59%)$, $C_{18:1}(9.79{\sim}10.37%)$, $C_{18:0}(7.71{\sim}12.43%)$ and C_{16:0},\;C_{20:4}$ and additionally $C_{18:3} (20.90%)$ was shown predominant in melanic type and the level of polyene acid highest in neutral lipids. The neutral lipids in each type of Ampullarius insularus were mainly composed of $C_{16:0}(16.96{\sim}17.46%)$, $C_{18:1}(13.79{\sim}13.95%)$ and $C_{18:2} (12.90{\sim}15.70%)$ and additionally it chiefly consisted of $C_{18:1}$, $C_{20:4}$and$C_{22:6}$. The major fatty acids in each type of glycolipids were $C_{18:2}(19.01{\sim}19.72)$, $C_{16:0}(12.89{\sim}18.76%)$ and $C_{18:0}(12.68{\sim}17.52%)$ and additionally $C_{18:1}$ in Achatina fucica Bowdich, but $C_{22:1}$ was detected in relatively higher level by 6.95% in albinic type only. The major fatty acids in glycolipids were $C_{18:2}(12.46{\sim}18.21%)$, $C_{16:0}(10.43{\sim}18.48%)$, $C_{20:1}(10.51{\sim}14.59%)$, $C_{20:4}(8.24{\sim}12.34%)$ and additionally it chiefly consisted of $C_{18:0}\;and\;C_{18:1}$ in Ampullarius insularus. The fatty acid composition in phospholipids of each sample was very resembled to total lipids, respectively.

• Journal of the Korean Society of Food Science and Nutrition
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• v.12 no.2
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• pp.122-136
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• 1983

The effect of dietary casein, calcium, magnesium and some vegetable oils such as seasme, perilla and soybean oil on the serum cholesterol level in the rabbit were studied for a period of 5 weeks using isocalories and isonitrogenous as basal diets. The experimental rabbits fed the following basal diets containing crude protein 68.47%, carbohydrates 13.35%. fats 16.18% and vegetable oil 10%. casein 10%, calcium and magnesium according to experimental plan making. In order to calculate the feeding efficiency, protein efficiency and calorie efficiency during period, the body weight gains were measured at the same time using same balance, respectively. The results are summarized as follows. Body weight gains per week of the group fed perilla oil, calcium and basal diet were the higher than any other groups. And body weights gains per week of the group fed basal diet, vegetable oil were the lower than any other groups. In the case of efficiency of reed, protein and calorie, the efficiency ratios of the group fed perilla oil were the higher than any other groups. Especially, perilla oil and calcium diet effect on body weight gain in rabbit. In the case of serum protein, the total proteins in serum were almost same value for all the groups. Serum albumin of group fed basal diet. vegetable oil and casein were the higher than any other groups. The ${\alpha}$-globulin of the groups, fed basal diet and calcium was the lower than any other grosps. The ${\beta}$-globulins of the groups fed basad diet, perilla oil and casein were the highest value. In serum lipoprotein, lipalbumin was almost same value for the groups fed vegetable oil, but fed vegetable oil and calcium diet was the lowest value. The ${\beta}$-lipoprotein in high cholesterol level group was increased some degree, the group fed perilla oil added was lower. The ratio of ${\beta}$-lipoprotein per lipalbumin was from 0.11 to 0.26. The ratio of lipalbumin per total lipoprotein was high in calcium and soybean oil added diet. In serum triglyceride, the level of triglyceride of groups fed seasme oil or perilla oil was the higher than any othe groups, but in the group fed casein and calcium or magnesium, the level of triglyceride level was decreased. Calcium and magnesium effect on triglyceridge level lowering action. In serum total cholesterol, the group does fed vegetable oil with basal diet and casein added more, total cholesterol level increased as much as triglyceride level increased. But the group does fed perilla oil and magnesium shows total cholesterol level decreased remarkably. In the group fed basal diet with calium, the amount of serum calcium was increased, but of serum magnesium was decreased. In the case of blood glucose, the group fed basal diet and vegetable oil was decreased. According to the regression and correlation coefficient in blood components in rabbit, there are positive correlation $${\gamma}{\sim_=}1$$ between serum cholesterol and triglyceride, ${\beta}$-lipoprotein, ${\alpha}$-globulin, calcium and magnesium according to diet composition. From the above results, the serum cholesterol level lowering factors in rabbit, was the amount of triglyceride and ${\beta}$-lipoprotein which was decreased in perilla oil fed. It assumes that serum cholesterol and triglyceride level lowering factors are not only unsaturation degree of fatty acid but the amount of calcium and magnesium and the ratio calcium per magnesium 2:1 in the diet.

• Journal of Global Scholars of Marketing Science
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• v.18 no.1
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• pp.59-80
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• 2008

Recently, e-sports are growing with potentiality as a new industry with conspicuous profit model. But studies that dealing with e-sports are not enough. Hence, proposes of this paper are both to establish basic model that is for the design of e-sport marketing strategy and to contribute toward future studies which are related to e-sports. Recently, the researches to explain sports-sponsorship through the identification theory have been discovered. Many researches say that somewhat proper identification is a requirement for most sponsors to improve the their images which is essential to sponsorship activity. Consequently, the research for sponsorship associated with identification in the e-sports, not in the physical sports is the core sector of this study. We extracted the variables from online's major characteristics and existing sport sponsorship researches. First, because e-sports mean the tournaments or leagues in the use of online game, the main event of the game is likely to call it online game. Online media's attributes are distinguished from those of offline. Especially, interactivity, anonymity, and expandibility as a e-sport game attributes are able to be mentioned. So, these inherent online attributes are examined on the relationship with flow. Second, in physical sports games, Fisher(1998) revealed that team similarity and team attractivity were positively related to team identification. Wann(1996) said that the result of former game influenced the evaluation of the next game, then in turn has an effect on the identification of team supporters. Considering these results in the e-sports side, e-sports gamer' attractivity, similarity, and match result seem to be important precedent variables of the identification with a gamer. So, these e-sport gamer attributes are examined on the relationship with both flow and identification with a gamer. Csikszentmihalyi(1988) defined the term flow as feeling status for him to be making current positive experience optimally. Hoffman and Novak(1996) also said that if a user experienced the flow he would visit a website without any reward. Therefore flow might be positively associated with user's identification with a gamer. And, Swanson(2003) disclosed that team identification influenced the positive results of sponsorship, which included attitude toward sponsors, sponsor patronage, and satisfaction with sponsors. That is, identification with a gamer expect to be connected with corporation identification significantly. According to the above, we can design the following research model. All variables used in this study(interactivity, anonymity, expandibility, attractivity, similarity, match result, flow, identification with a gamer, and identification with a sponsor) definitely were defined operationally underlying precedent researches. Sample collection was carried out to the person who has an experience to have enjoyed e-sports during June 2006. Much portion of samples is men because much more men than women enjoy e-sports in general. Two-step approach was used to test the hypotheses. First, confirmatory factor analysis was committed to guarantee the validity and reliability of variables. The results showed that all variables had not only intensive and discriminant validity, but also reliability. Then, research model was examined with fully structural equation using LISREL 8.3 version. The fitness of the suggested model mostly was at the acceptable level. Shortly speaking about the results, first of all, in e-sports game attributes, only interactivity which is called a basic feature in online situation affected flow positively. Secondly, in e-sports gamer's attributes, similarity with a gamer and match result influenced flow positively, but there was no significant effect in the relationship between the attractivity of a gamer and flow. And as expected, similarity had an effect on identification with a gamer significantly. But unexpectedly attractivity and match result did not influence identification with a gamer significantly. Just the same as the fact verified in the many precedent researches, flow greatly influenced identification with a gamer, and identification with a gamer continually had an influence on the identification with a sponsor significantly. There are some implications in these results. If the sponsor of e-sports supports the pro-game player who absolutely should have the superior ability to others and is similar to the user enjoying e-sports, many amateur gamers will feel much of the flow and identification with a pro-gamer, and then after all, feel the identification with a sponsor. Such identification with a sponsor leads people enjoying e-sports to have purchasing intention for products produced by the sponsor and to make a positive word-of-mouth for those products or the sponsor. For the future studies, we recommend a few ideas. Based on the results of this study, it is necessary to find new variables relating to the e-sports, which is not mentioned in this study. For this work to be possible, qualitative research seems to be needed to consider the inherent e-sport attributes. Finally, to generalize the results related to e-sports, a wide range of generations not a specific generation should be researched.

• Journal of Korean Home Economics Education Association
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• v.18 no.3 s.41
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• pp.1-22
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• 2006

The purpose of this study is that I should look for a desirous directions about home economics by studying the requirements and perception of the high school parents who have finished the course of home economics. It was about 600 parents whom I have searched Seoul-Pusan, Ganwon. Ghynggi province, Choongcheong-Gyungsang province, Cheonla and Jeju province of 600, I chose only 560 as apparently suitable research. The questions include 61 requirements about home economics and one which we never fail to keep among the contents, whenever possible and one about the perception of home economics aims 11 about the perception of home economics courses and management. The collections were analyzed frequency, percent, mean. standard deviation t-test by using SAS program. The followings is the summary result of studying of it. 1. All the boys and girls learning together about the Idea of healthy lives and desirous human formulation and knowledge together are higher. 2. Among the teaching purposes of home economics, the item of the scientific principle and knowledge for improvements of home life shows 15.7% below average value. 3. The recognition degree about the quality of home economics is highly related with the real life, and about the system. we recognize lacking in periods and contents of home economics field and about guiding content, accomplishment and application qualities are higher regardless of sex. 4. The important term which we should emphasize in the subject of home economics is family part. 5. Among the needs of home economic requirement in freshman, in the middle unit, their growth and development are higher than anything else, representing 4.11, and by contrast the basic principle and actuality is 3.70, which is lowest among them. 6. In the case of second grade requirement of home economics content for parents in the middle unit young man and consuming life is 4.09 highest. 7. In the case of 3rd grade requirement of economics contents in the middle unit the choice of coming direction and job ethics is highest 4.16, and preparing meals and evaluation is lowest 3.50.

• Journal of Intelligence and Information Systems
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• v.18 no.3
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• pp.185-202
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• 2012

.Since the value of information has been realized in the information society, the usage and collection of information has become important. A facial expression that contains thousands of information as an artistic painting can be described in thousands of words. Followed by the idea, there has recently been a number of attempts to provide customers and companies with an intelligent service, which enables the perception of human emotions through one's facial expressions. For example, MIT Media Lab, the leading organization in this research area, has developed the human emotion prediction model, and has applied their studies to the commercial business. In the academic area, a number of the conventional methods such as Multiple Regression Analysis (MRA) or Artificial Neural Networks (ANN) have been applied to predict human emotion in prior studies. However, MRA is generally criticized because of its low prediction accuracy. This is inevitable since MRA can only explain the linear relationship between the dependent variables and the independent variable. To mitigate the limitations of MRA, some studies like Jung and Kim (2012) have used ANN as the alternative, and they reported that ANN generated more accurate prediction than the statistical methods like MRA. However, it has also been criticized due to over fitting and the difficulty of the network design (e.g. setting the number of the layers and the number of the nodes in the hidden layers). Under this background, we propose a novel model using Support Vector Regression (SVR) in order to increase the prediction accuracy. SVR is an extensive version of Support Vector Machine (SVM) designated to solve the regression problems. The model produced by SVR only depends on a subset of the training data, because the cost function for building the model ignores any training data that is close (within a threshold ${\varepsilon}$) to the model prediction. Using SVR, we tried to build a model that can measure the level of arousal and valence from the facial features. To validate the usefulness of the proposed model, we collected the data of facial reactions when providing appropriate visual stimulating contents, and extracted the features from the data. Next, the steps of the preprocessing were taken to choose statistically significant variables. In total, 297 cases were used for the experiment. As the comparative models, we also applied MRA and ANN to the same data set. For SVR, we adopted '${\varepsilon}$-insensitive loss function', and 'grid search' technique to find the optimal values of the parameters like C, d, ${\sigma}^2$, and ${\varepsilon}$. In the case of ANN, we adopted a standard three-layer backpropagation network, which has a single hidden layer. The learning rate and momentum rate of ANN were set to 10%, and we used sigmoid function as the transfer function of hidden and output nodes. We performed the experiments repeatedly by varying the number of nodes in the hidden layer to n/2, n, 3n/2, and 2n, where n is the number of the input variables. The stopping condition for ANN was set to 50,000 learning events. And, we used MAE (Mean Absolute Error) as the measure for performance comparison. From the experiment, we found that SVR achieved the highest prediction accuracy for the hold-out data set compared to MRA and ANN. Regardless of the target variables (the level of arousal, or the level of positive / negative valence), SVR showed the best performance for the hold-out data set. ANN also outperformed MRA, however, it showed the considerably lower prediction accuracy than SVR for both target variables. The findings of our research are expected to be useful to the researchers or practitioners who are willing to build the models for recognizing human emotions.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.137-148
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• 2014

Recommender system has become one of the most important technologies in e-commerce in these days. The ultimate reason to shop online, for many consumers, is to reduce the efforts for information search and purchase. Recommender system is a key technology to serve these needs. Many of the past studies about recommender systems have been devoted to developing and improving recommendation algorithms and collaborative filtering (CF) is known to be the most successful one. Despite its success, however, CF has several shortcomings such as cold-start, sparsity, gray sheep problems. In order to be able to generate recommendations, ordinary CF algorithms require evaluations or preference information directly from users. For new users who do not have any evaluations or preference information, therefore, CF cannot come up with recommendations (Cold-star problem). As the numbers of products and customers increase, the scale of the data increases exponentially and most of the data cells are empty. This sparse dataset makes computation for recommendation extremely hard (Sparsity problem). Since CF is based on the assumption that there are groups of users sharing common preferences or tastes, CF becomes inaccurate if there are many users with rare and unique tastes (Gray sheep problem). This study proposes a new algorithm that utilizes Social Network Analysis (SNA) techniques to resolve the gray sheep problem. We utilize 'degree centrality' in SNA to identify users with unique preferences (gray sheep). Degree centrality in SNA refers to the number of direct links to and from a node. In a network of users who are connected through common preferences or tastes, those with unique tastes have fewer links to other users (nodes) and they are isolated from other users. Therefore, gray sheep can be identified by calculating degree centrality of each node. We divide the dataset into two, gray sheep and others, based on the degree centrality of the users. Then, different similarity measures and recommendation methods are applied to these two datasets. More detail algorithm is as follows: Step 1: Convert the initial data which is a two-mode network (user to item) into an one-mode network (user to user). Step 2: Calculate degree centrality of each node and separate those nodes having degree centrality values lower than the pre-set threshold. The threshold value is determined by simulations such that the accuracy of CF for the remaining dataset is maximized. Step 3: Ordinary CF algorithm is applied to the remaining dataset. Step 4: Since the separated dataset consist of users with unique tastes, an ordinary CF algorithm cannot generate recommendations for them. A 'popular item' method is used to generate recommendations for these users. The F measures of the two datasets are weighted by the numbers of nodes and summed to be used as the final performance metric. In order to test performance improvement by this new algorithm, an empirical study was conducted using a publically available dataset - the MovieLens data by GroupLens research team. We used 100,000 evaluations by 943 users on 1,682 movies. The proposed algorithm was compared with an ordinary CF algorithm utilizing 'Best-N-neighbors' and 'Cosine' similarity method. The empirical results show that F measure was improved about 11% on average when the proposed algorithm was used