• Journal of the Korean Regional Science Association
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• v.35 no.3
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• pp.45-58
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• 2019

The government is recently pushing for five large-scale public housing sites near Seoul, the so-called third wave of new towns. In this regard, this study sought to analyze the key considerations in planning new towns from the perspective of the residents who are the consumers, using survey data. For this purpose, frequency analysis and variance analysis(ANOVA) were conducted on existing first and second era of new towns and the third era of new towns scheduled for construction. Eight indicators, such as environmental comfort, self-sufficiency such as jobs, transportation access and convenience, were set as subordinate variables, and characteristics of residents, including gender, age, number of households, household income, occupation, and residential areas, were set as explanatory variables. According to the analysis, the respondents rated the first era of new towns more positively than the second era of new towns. For self-sufficiency items such as jobs, both the first and second era of new towns showed low levels. In addition, for the eight indicators, the first era of new towns were no significant differences depending on gender, number of households, or household income, and the second era of new towns were no significant differences by the number of households, household income, occupations or place of residence. However, for new towns in the third period, the assessment of the importance of each indicator by age, number of households, household income and occupation showed significant differences. The results of the multi-comparison analysis of the third era of new towns showed that the importance of environmental comfort was highly valued by the youth, the managerial/professional/clerical position, single or five more persons of household, and the youth, high income household, the managerial/professional/clerical position when it comes to accessibility and convenience of transportation. It suggests that various personal characteristics and demands for each of the planning indicators need to be considered in planning for the third era of new towns.

• Journal of Animal Science and Technology
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• v.44 no.1
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• pp.45-54
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• 2002

This study was conducted to evaluate the feeding value of ascidian tunic shell the effects of its dietary supplementation on laying performance, egg-yolk pigmentation, egg-shell strength and egg taurine content. A total of 168 brown layers at the age of 29wks in commercial cage were fed for 4 wks with 7 different diets containing ascidian tunic shel1(AST) at varying levels of 0$\sim$5% Dm or 0% AST with 100ppm carophyll red. No differences were found in egg production and weight among the treatments indicating that ascidian tunic shell did not adversely affect the laying performances. Adding the ascidian tunic shell to the diets increased egg-yolk pigmentation compared to the control and resulted in simillar or better effect on egg-yolk pigmentation compared to 100ppm carophyll red. The data suggest that ascidian tunic shell may be used as feed ingredients in layer diet enrichment of egg-yolk pigmentation in the place of carophyll red(chemical pigment). Specific gravity and breaking strength of egg shell were significantly increased by the adding ascidian tunic shell to the diet, suggesting that ascidian tunic shell may be used as feed ingredients for increasing egg shell strength. Also taurine content of egg was significantly increased with increasing supplementation of ascidian tunic shell to the diet(p<0.05). Therefore, ascidian tunic shell may be used as feed ingredients in laying hen diet to improve egg quality such as egg-yolk pigmentation, egg-shell strength and egg taurine enrichment.

• Journal of Nutrition and Health
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• v.53 no.1
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• pp.27-38
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• 2020

Purpose: This study assessed the food intake and nutritional status of the elderly in long-term care facilities in order to provide adequate food services and improve the nutritional status. Methods: The survey was carried out from August 2019 to October 2019 for the elderly in long-term care facilities located in Gwangju Metropolitan City. The survey was conducted to collect data from 199 elderly persons (34 males and 165 females) aged over 65 years old. The food intake was assessed using a 1-day 24-hour recall method. Results: More than 90% of the subjects were over 75 years old. Forty five percent of the subjects were active, 44.2% of the subjects perceived themselves as not being healthy. Dementia and Parkinson's disease were the most common diseases, followed by hypertension, musculo-skeletal disease, diabetes, and stroke. Only 25.6% of the subjects had most of their teeth intact, and 44.7% of the subjects had difficulty in chewing and swallowing. The total food intake was 1,127 g in males and 1,078 g in females. The most frequently consumed foods were kimchi, cooked rice with multi-grains, soybean soup, cooked rice with white rice, yogurt, pumpkin porridge, soy milk, and duck soup. The average energy intake of the subjects was 1,564.9 kcal in males and 1,535.5 kcal in females. The overall nutritional status of the elderly in the long-term care facilities was poor. In particular, the intake of vitamin D and calcium, vitamin C, riboflavin, and potassium were very low. The intake of vitamin D was 5 ㎍, and 86.4% of the elderly were below the estimated average requirement, while the intake of sodium was high. Conclusion: The results of this study can be used to understand the health and nutritional status and to improve the food services and nutrition management for the elderly in longterm care facilities.

• Journal of Nutrition and Health
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• v.53 no.1
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• pp.39-53
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• 2020

Purpose: The purpose of the study was to examine the snack meal management for infants and toddlers and the demand for snack products according to mothers' sustainable dietary style in the Jeonbuk area. Methods: The participants were 359 mothers in the Jeonbuk area. The data was analyzed using factor analysis, cluster analysis, analysis of variance, and χ²-tests with SPSS v. 25.0. According to the sustainable dietary style, the situation of providing snacks at home, the purchasing behavior for snack products, and the satisfaction and, demand for snack products were investigated. Results: Using the K-clustering method, the sustainable dietary style of the subjects was categorized into 3 clusters. Cluster 1 was the family health-seeking group, cluster 2 was the sustainable dietary trend group, and cluster 3 was the sustainability-interested group. The frequency of snack intakes according to the cluster groups showed a significant difference (p < 0.001). Fruits were the snack item most frequently consumed by all the cluster groups. Approximately 92.8% of mothers had purchased snack products, and 95.2% of the subjects were satisfied with them (p < 0.05). The main reason for satisfaction with the snack products in all the cluster groups was the various kinds of products with considering the growth stage of children. Clusters 2 and 3 required the development of snack products using organic food materials, while cluster 1 required the snack products to be supplemented with various nutrients. Conclusion: It is necessary to develop various snack products according to the sustainable dietary style and the needs of mothers so that these snacks can increase the satisfaction of mothers with the snack products and lead them to better snack purchasing behavior.

• Journal of Nutrition and Health
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• v.40 no.7
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• pp.606-615
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• 2007

This study was performed to investigate anti-thrombogenic, anti-inflammatory effects of n-BuOH (B) and $CH_2Cl_2$ (MC) fractions extracted from Sancho (Zanthoxylum. schinifolium) leaves in rats fed high fat diets. The experimental animal groups were consisted of eight including one 5% fat (N) and one 20% fat (H) without the test materials in diets and six H groups of feeding three levels (50, 100 and 150 mg/day) of the B and the MC fractions from Z. schinifolium, respectively. Plasma activated partial thromboplastin times and thrombin times of H group were decreased compared to the N group, but they were increased by feeding the MC fraction of 50 mg and over. Polymorphonuclear leukocyte 5#-lipo-xygenase activities and leukotriene $B_4$ contents of the H group were significantly increased compared to the N group, but they were decreased in the 100 mg and 150 mg of B fraction or the 150 mg of MC fraction fed groups. Liver cytochrome $P_{450}$, $O_2^-$, $H_2O_2$ and GSSG contents were increased by the high fat diet but decreased by feeding the B fraction or the MC fraction, while GSH content and glutathione S-transferase activity lowered by high fat diet were increased by feeding the two solvent fractions. The effects of the solvent fractions were evident at the level of 100 mg/day and over. The present results confirmed that two solvent fractions from the leaves of Z, schinifolium have enhancing effects on anti-thrombosis and anti-inflammation partly by antioxidant action and partly by direct modulation of the respective processeds. In conclusion, the n-BuOH and $CH_2Cl_2$ fractions from leaves of Z, schinifolium can be utilized as the proper ingredients of functional foods for preventing chronic degenerative disease.

• Cartoon and Animation Studies
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• s.40
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• pp.1-31
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• 2015

The Korean animation that has relatively short history compared to the Western Europe and Japan's animation started out from the non-commercial short-piece animation produced as part of advertisement animation and culture movie in the later part of 1950s. In 1960s, the culture movie animation reflecting for the Movie Act and cultural policies has hardly been mentioned in the history of Korean animation, but they are the precious cultural work produced prior to the theatrical long-piece animation. In particular, compared to the 15-second short CF animation, the short-piece animations are ranging for 4 minutes to 10 minutes as the work pieces with the historic value to measure the level of the Korean animation at that time. in 1960s, approximately 20 short-piece animation works were produced and they contained the educational contents to enlighten general public in the process of modernization policy. Those short-piece animations produced in cultural movie at the National Film Production Center of Korea had been produced not only in cell-facilitating cartoon animation, but also in paper animation and puppet animation. In this background, this thesis takes a close look to the short-piece animation works produced in the National Film Production Center of Korea in 1960s. While there was almost no studies of early short-piece animation other than CF works, it is meaningful to discover and analyze the works, and, Director Park Young-il, Director Han Sung-hak, Director Jung Do-bin, Director Shin Dong-hyun, Director Nelson Shin and others participated in the creative work process have worked as the animation directors for theater that the analysis on the works would be considered as important fundamental studies to understand the Korean animation. Under this thesis, it is intended to study the historic implication and formative characteristics around some 10 work pieces to affirm participating personnel, including directors, for the short-piece animation created by the National Film Production Center of Korea as well as the situation of time to launch the National Film Production Center of Korea in 1960s. Through this effort, it is intended to come up with the starting point to process enriched researches on non-commercial short-piece animation as well as contemplation on the Korean animation history that have been neglected in the study of the Korean animation history through such effort.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.1
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• pp.325-335
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• 2017

This study examined the effects of mothers' smartphone usage habits on young children's aggression and emotional intelligence. For this purpose, a total of 275 questionnaires from mothers in Jeonbuk Province with 3~5 year old young children, who had experiences in using smartphones, were analyzed, and the results are as follows. First, an analysis of the general trend of mother's smartphone usage habits showed that young children's aggression and emotional intelligence according to the general trend of mother's smartphone usage habits had a generally low rate and 'the tolerance and flow' had a high score among its sub-factors. The general trend of young children's aggression also showed a generally low rate, and 'status acquired aggression' had a high score among its sub-factors. The general trend of young children's emotional intelligence showed a moderate level, and a high score was observed in 'mother relation' among its sub-factors. Second, an analysis of the relationship between mother's smartphone usage habits, and young children's aggression and emotional intelligence showed that mother's smartphone usage habits had a positive correlation with the young children's aggression while it did not correlate with the young children's emotional intelligence. On the other hand, a negative correlation was observed between the virtual world orientation among the sub-factors of smartphone usage habits and the self-emotion awareness and expression among the sub-factors of emotional intelligence. Third, an analysis of the effects of mother's smartphone usage habits on children's aggression showed that all of mother's smartphone usage habits and its sub-factors had a negative effect on children's aggression. Fourth, an analysis of the effects of mother's smartphone usage habits on young children's emotional intelligence showed that none of mother's smartphone usage habits or its sub-factors had a significant effect.

• Journal of Nutrition and Health
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• v.44 no.2
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• pp.171-180
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• 2011

Assessing human exposure to food-borne hazards requires standardized assessment tools. The objective of this study was to validate a newly developed dietary assessment questionnaire to assess human exposure to food-borne hazards, which include dietary behavior and food consumption patterns such as eating frequency, types of food containers and cooking methods. A total of 216 adults were recruited for two questionnaire surveys (questionnaire 1 and 2) about 1 week apart with a 3 day diet record. Reproducibility was evaluated by comparing responses from questionnaires 1 and 2, and validity was checked by comparing responses from questionnaire 2 and the 3 day diet record. Comparisons were based on the percent agreement and Spearman's rank correlation coefficient. The mean exact agreement of food containers at purchase between questionnaires 1 and 2 was 73.5%, for storing containers it was 71.9%, and for cooking methods it was 83.0%. The mean correlation coefficient for food intake frequency between questionnaires 1 and 2 was 0.71 (range, 0.50-0.83). The mean correlation coefficient of the food intake frequency between questionnaire 2 and the 3 day diet record was 0.21 (range, 0.04-0.48). The exact and adjacent agreement of food intake frequency quartile assessed by questionnaire 2 and the 3 day diet record was 65.4% (range, 51.0-82.1%). Although the correlation coefficient for food intake frequency between questionnaire 2 and the 3 day diet record was low, the exact and adjacent food intake frequency agreement was higher than 50% and reproducibility of the dietary behaviors exceeded 70%. Therefore, the questionnaire developed in this study could be applied to assess diets for the human exposure to food-borne hazards as a qualitative assessment in a large population.

• Journal of Intelligence and Information Systems
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• v.17 no.4
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• pp.241-254
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• 2011

Financial time-series forecasting is one of the most important issues because it is essential for the risk management of financial institutions. Therefore, researchers have tried to forecast financial time-series using various data mining techniques such as regression, artificial neural networks, decision trees, k-nearest neighbor etc. Recently, support vector machines (SVMs) are popularly applied to this research area because they have advantages that they don't require huge training data and have low possibility of overfitting. However, a user must determine several design factors by heuristics in order to use SVM. For example, the selection of appropriate kernel function and its parameters and proper feature subset selection are major design factors of SVM. Other than these factors, the proper selection of instance subset may also improve the forecasting performance of SVM by eliminating irrelevant and distorting training instances. Nonetheless, there have been few studies that have applied instance selection to SVM, especially in the domain of stock market prediction. Instance selection tries to choose proper instance subsets from original training data. It may be considered as a method of knowledge refinement and it maintains the instance-base. This study proposes the novel instance selection algorithm for SVMs. The proposed technique in this study uses genetic algorithm (GA) to optimize instance selection process with parameter optimization simultaneously. We call the model as ISVM (SVM with Instance selection) in this study. Experiments on stock market data are implemented using ISVM. In this study, the GA searches for optimal or near-optimal values of kernel parameters and relevant instances for SVMs. This study needs two sets of parameters in chromosomes in GA setting : The codes for kernel parameters and for instance selection. For the controlling parameters of the GA search, the population size is set at 50 organisms and the value of the crossover rate is set at 0.7 while the mutation rate is 0.1. As the stopping condition, 50 generations are permitted. The application data used in this study consists of technical indicators and the direction of change in the daily Korea stock price index (KOSPI). The total number of samples is 2218 trading days. We separate the whole data into three subsets as training, test, hold-out data set. The number of data in each subset is 1056, 581, 581 respectively. This study compares ISVM to several comparative models including logistic regression (logit), backpropagation neural networks (ANN), nearest neighbor (1-NN), conventional SVM (SVM) and SVM with the optimized parameters (PSVM). In especial, PSVM uses optimized kernel parameters by the genetic algorithm. The experimental results show that ISVM outperforms 1-NN by 15.32%, ANN by 6.89%, Logit and SVM by 5.34%, and PSVM by 4.82% for the holdout data. For ISVM, only 556 data from 1056 original training data are used to produce the result. In addition, the two-sample test for proportions is used to examine whether ISVM significantly outperforms other comparative models. The results indicate that ISVM outperforms ANN and 1-NN at the 1% statistical significance level. In addition, ISVM performs better than Logit, SVM and PSVM at the 5% statistical significance level.

• Journal of Intelligence and Information Systems
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• v.17 no.4
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• pp.95-108
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• 2011

TThis is a study of the personalization method that intelligently adapts the level of clustering considering purchasing index of a customer. In the e-biz era, many companies gather customers' demographic and transactional information such as age, gender, purchasing date and product category. They use this information to predict customer's preferences or purchasing patterns so that they can provide more customized services to their customers. The previous Customer-Segmentation method provides customized services for each customer group. This method clusters a whole customer set into different groups based on their similarity and builds predictive models for the resulting groups. Thus, it can manage the number of predictive models and also provide more data for the customers who do not have enough data to build a good predictive model by using the data of other similar customers. However, this method often fails to provide highly personalized services to each customer, which is especially important to VIP customers. Furthermore, it clusters the customers who already have a considerable amount of data as well as the customers who only have small amount of data, which causes to increase computational cost unnecessarily without significant performance improvement. The other conventional method called 1-to-1 method provides more customized services than the Customer-Segmentation method for each individual customer since the predictive model are built using only the data for the individual customer. This method not only provides highly personalized services but also builds a relatively simple and less costly model that satisfies with each customer. However, the 1-to-1 method has a limitation that it does not produce a good predictive model when a customer has only a few numbers of data. In other words, if a customer has insufficient number of transactional data then the performance rate of this method deteriorate. In order to overcome the limitations of these two conventional methods, we suggested the new method called Intelligent Customer Segmentation method that provides adaptive personalized services according to the customer's purchasing index. The suggested method clusters customers according to their purchasing index, so that the prediction for the less purchasing customers are based on the data in more intensively clustered groups, and for the VIP customers, who already have a considerable amount of data, clustered to a much lesser extent or not clustered at all. The main idea of this method is that applying clustering technique when the number of transactional data of the target customer is less than the predefined criterion data size. In order to find this criterion number, we suggest the algorithm called sliding window correlation analysis in this study. The algorithm purposes to find the transactional data size that the performance of the 1-to-1 method is radically decreased due to the data sparity. After finding this criterion data size, we apply the conventional 1-to-1 method for the customers who have more data than the criterion and apply clustering technique who have less than this amount until they can use at least the predefined criterion amount of data for model building processes. We apply the two conventional methods and the newly suggested method to Neilsen's beverage purchasing data to predict the purchasing amounts of the customers and the purchasing categories. We use two data mining techniques (Support Vector Machine and Linear Regression) and two types of performance measures (MAE and RMSE) in order to predict two dependent variables as aforementioned. The results show that the suggested Intelligent Customer Segmentation method can outperform the conventional 1-to-1 method in many cases and produces the same level of performances compare with the Customer-Segmentation method spending much less computational cost.