• Journal of the Korean Society of Food Science and Nutrition
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• v.26 no.4
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• pp.733-742
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• 1997

A computerized dietary prescription and nutritional counseling system for patients having hyperlipidemia has been developed using a personal computer. This system is composed of three programs. The first program is designed to investigate dietary history of patient, such as a dietary habit and a preference of food, to find out his incorrect dietary behavior and to give him some suggestions to correct dietary behavior. The second one is developed to analyze the energy and nutrients intake using 24-hour dietary recall method and also evaluate the status of dietary intake, especially the status of dietary fat. With these data, patient can replan pattern of his food intake including in-between-meal snack as well as regular meals. The third one is the diet and menu Planning program made using food exchange table. It provides the patient with a meal pattern suitable in his weight, activity and the other status of the body. Practicing these programs, patient with hyperlipidemia can help himself very conveniently in organizing his meal plan and in improving his dietary behavior.

• Journal of The Korean Association For Science Education
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• v.31 no.1
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• pp.78-98
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• 2011

The purpose of this study was to analyze elementary school students' interpretation of data characteristics by cognitive style. Participants were elementary students in sixth grade who can use integrated inquiry process skills. The students were divided into two groups, analytic cognitive style and wholistic cognitive style according to their response to Cognitive Style Analysis. They performed scientific interpretation of data activity. To collect data for this study, participants recorded the result on scientific interpretation of data activity paper and researcher recorded the situation on videotape and interviewed with participants after the end of interpretation of data to get additional data. And the findings of this study were as follows: First, the study analyzed interpretation of data characteristics by the operator regarding different situations of interpreting data according to cognitive style. For example, in the intermediate state, analytic-cognitive style students showed high achievement in identifying variables, and wholistic-cognitive style students were active in using prior knowledge to interpret data. Second, the result of analysis on the direction of interpreting data and preference for data types in interpreting data activities according to cognitive style are as follows: Wholistic-cognitive style students showed relatively high perception of information through the top-down approach. On the other hand, analytic-cognitive style students usually used the bottom-up approach gradually expanding detailed information to the scientific question-related answer and showed a preference data of the table type. Through the result, this study aimed to help establish a data interpretation strategy for learners to solve problems based on understanding of interpretation of data characteristics according to learners' cognitive style, and purposed the instruction design suggesting the data requiring various data interpretation strategies to develop learners' data interpretation ability.

• Korean Journal of Food Science and Technology
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• v.50 no.3
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• pp.331-338
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• 2018

The purpose of this study was to determine the optimum sterilization conditions for the production of retorted steamed egg using response surface methodology. Sterilization processes for eighteen conditions using varying sterilization temperature ($X_1$), time ($X_2$), and method ($X_3$) as the independent variables were carried out through a $3^2{\times}2$ experimental factorial design. Quality evaluations after sterilization included measurements of $F_0$ value ($Y_1$), peak stress ($Y_2$), pH ($Y_3$), color value ($Y_{4-6}$), and organoleptic test [preference for appearance ($Y_7$), overall acceptability ($Y_8$), and preference for texture ($Y_9$) and egg taste ($Y_{10}$)]. Dependent variables ($Y_{1-10}$) of eighteen conditions were more affected by temperature and time than by the sterilization method. Eight factors were selected among the dependent variables as significant factors related to the quality of the steamed egg. Finally, by establishing an optimum range of each dependent variable and contour analysis, the optimum sterilization conditions for the production of steamed egg were determined to be $120^{\circ}C$ for 25 min using a 2-step sterilization process.

• Journal of the East Asian Society of Dietary Life
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• v.14 no.1
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• pp.1-10
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• 2004

This study was conducted to investigate the dietary behavior and image and preference of Japanese foods. The Subjects were consisted of 570 university students(243 males and 327 females) in Daegu and Kyungbuk area, Korea. The students responses to the 10 questions about image of Japanese foods were also measured on 5 point Likert scale. Data were presented by using frequency, percentage, chi-square test and T-test. The results of this study were as follows: (1) On the eating habits, 'the whole family has breakfast together with same foods everyday'scored high as 42.3％ and 'foods put in a big platter by gathering everyday'as 35.8％. (2) About the eating customs, 53.5％ of the subjects responded that the seat was fixed at meal time, 56.4％ didn't start to eat before the patriarch started a meal and 30.9％ responded that the head of a family had more foods in number and quantity. (3) On the table manners, 13.4％ of the subjects were scolded about 'watching TV on eating', 11.5％ about 'making left-over foods', 8.0％ about 'misuse of spoon and chopsticks'. (4) The preferred ethnic foods by University students was in other of Korean, Chinese, Italian, Japanese and French foods. (5) Among subjects, 93.8％ had no experience of visiting Japan and 92.6％ wanted to visit Japan. Images on the Japanese foods were 'the price is too expensive' (mean 4.15) and 'the decoration is wonderful'(mean 4.05). But the subjects did not think Japanese foods as 'hot'(mean 2.21) and 'greasy'(mean 2.51). (6) The favorite Japanese food of subjects was Udon(mean 3.98), Sushi(mean 3.85) and Tempura(mean 3.69). So Udon turned out to be the most popular Japanese foods by university students in Daegu and Kyungbuk area, Korea. But they did not prefer Natto(mean 2.68), Ochazuke(mean 2.76), Okonomiyaki(mean 2.87) and Misosiru and did not eat. From the above results, Korean university students preferred Udon to Natto among Japanese traditional foods, and they estimated Japanese foods as 'too expensive'. Therefore, lowering the price and developing the cooking method for Korean taste were needed to increase the intake of Japanese traditional foods by Korean university students and.

• 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