• Science of Emotion and Sensibility
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• v.24 no.1
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• pp.105-114
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• 2021

This study determines the differences between Korean female university students and their Chinese counterparts residing in Korea by evaluating the subjective sensation and tactile preference in fabrics for casual shirts. Seven types of white causal shirt fabrics were selected as specimens from those available in spring and autumn shirt collection. The fabrics were made from various fibers (cotton 100%, polyester 100%, flax 100%, polyester 80%/cotton 20%, polyester 65%/cotton 35%, polyester 50%/cotton 45%/spandex 5%, and polyester 50%/modal 50%). Forty Korean and Chinese female university students subjectively assessed the subjective sensation of fabrics used for casual shirts. Participants were asked to observe the seven types of fabrics and complete the questionnaire. The subjective sensation to be assessed for white casual shirt fabrics was classified into the following four factors: smoothness, lightness, softness, and stretchiness. Subjective sensation factors showed partially significant differences by nationality. Korean female students evaluated cotton fabric as being light, whereas their Chinese counterparts evaluated the polyester/cotton/spandex blended fabric as light. Korean female students evaluated polyester/modal blended fabric as being stretchable. The tactile preference for fiber composition of the fabrics showed partially significant differences by nationality. Korean female students preferred cotton 80%/polyester 20% blended fabric, polyester 50%/cotton 45%/spandex 5% blended fabric, and flax 100% fabric. The subjective sensation of the fabrics had different effects on preferences by nationality. Smoothness and softness had positive effects on preferences for the fabrics of Korean students. However, smoothness, softness, and stretchiness had positive effects on the preferences of Chinese students. The subjective sensation and tactile preference for casual shirt fabrics showed a difference between Korean female students and their Chinese counterparts. Therefore, when planning casual shirt fabrics for female university students, it is necessary to reflect on these differences in subjective sensation and tactile preference.

• Journal of the Korean Home Economics Association
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• v.44 no.9
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• pp.21-29
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• 2006

The purpose of this study was to investigate the preferences and utilization of green tea and its products for adults living in Chonbuk area. Self-administered questionnaires were collected from 388 (117 male, 271 female) subjects. who were classified into 5 groups by age. Data were analysed by chi-square and ANOVA. The results can be summarized as follows. On the investigation of preferences, there was a significant difference between and among the age groups(p<.001). More than 20% of the subjects in the $20{\sim}29$ years group preferred coffee and juice. A half of the elderly over 60 years preferred a kind of green tea. The frequency of green tea drinking was not significantly influenced by age. Drinking green tea less than once a day was replied by 59.0% of the subject of whom 44.3% drank the green tea at home. and 42.0% got information about green tea from TV or radio. Regarding the satisfaction with products using green tea, 62.6% of the subjects responded only 'mediocre.' The brown rice-green tea was marked to be the highest in terms of recognition among all kinds of products. The green tea-related products were rated higher by the elder group. In conclusion, future research should focus on the development of green tea and its products in accordance with the consumption pattern in each age group.

• Korean journal of food and cookery science
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• v.15 no.3
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• pp.272-287
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• 1999

Elementary schools students'degree of satisfaction on school food service and food preference were surveyed from 352 sixth-grade students in Kwangju and Chonnam area from June 22 to July 3 to enhance the quality of foodservice. The degree of satisfaction was high with cooked rice and soup in terms of temperature and serving state. There were significant differences in the degree of satisfaction depending upon the types of foodservice (p<0.001). There was significant differences in degree of satisfaction for side dishes depending upon the temperature (p<0.05), kinds (p<0.01) and amount (p<0.001). The degree of satisfaction with Kimchi was generally high in the serving state (p<0.05) and the amounts (p<0.01). The degree of satisfaction with desserts were high in the amount (p<0.001). The amount of leftover was high with soup, side dishes, kimchi, cooked rice, and desserts in order. The improvements made on children's behavior after the implementation of the school foodsevice were the adaptation to balanced diet and spending less money on sweets. The factors of influencing the school foodservice and the children's food intake were the education in school (teachers and dietitians) and the health status of their bodies (p<0.001). Children's favorite foods were sweet and sour pork, pork cutlets, oranges, watermelons, and strawberries in order. The least preferred foods were garlic seasoned with soy sauce, raw vegetables of broad bell-flowers, crown daisy greens, and steamed peppers. Children's favorite food types were fried food, desserts, one course meal, and bread. The least preferred types were pickled food, green and seasoned vegetables, cooked rice, and hard-boiled food in order. Generally, the children in the rural area favored most foods compared with those from urban area.

• Korean journal of food and cookery science
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• v.25 no.3
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• pp.357-364
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• 2009

The objectives of this study was to explore the knowledge, attitudes, and perceptions of elementary school students towards trans fatty acids. In addition, the students' preferences and consumption frequencies of processed food items containing trans fats, as well as their food behaviors relating to snack consumption, were investigated. The study population consisted of students from seven provinces, including Seoul, Busan, Daegu, Kwangju, Gyungnam, Chungnam, and Kangwon. Two schools were selected in each province and one class was randomly chosen in each school. All students from the selected classes were surveyed onsite (N=951). The data were analyzed with chi-square tests and t-tests using SPSS/Windows (ver.15.0) program. The results showed that the students' knowledge levels toward trans fatty acid were very low, particularly on the production process of trans fats. The students perceived that trans fatty acids can cause health problems and should be consumed in low amounts. They also felt there is a need for a good nutrition education on trans fats. Furthermore, the students responded that their most preferred foods were in the order of breads, biscuits, and snacks. The most frequently consumed snack item among 2nd graders was biscuits and among 5th graders it was breads. It was also found that 90% of the students had snacks once a day, and of them, 58% prepared their own snacks. Based on this, we propose that students who allowed to choose their own snacks should be carefully educated on trans fatty acids to prevent excessive consumption of high trans fat foods.

• Journal of Korean Society of Forest Science
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• v.95 no.6
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• pp.768-777
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• 2006

The purpose of this study lies in formulating the landscape preference model using a conditional logit that involves the effect of visual elements as well as landscape itself on landscape preferences. To measure landscape preferences, a photo-questionnaire composed of paired photographs of the Cairngorms National Park of Scotland and the Jirisan National Park of Korea was distributed to visitors to the Jirisan National Park of Korea. Visual elements of landscape quantitatively measured by photogrammetry were reduced to orthogonal principal components that were subsequently used as explanatory variables in a conditional logit. As a result, the mixed conditional logit including the effect of landscape itself satisfied the Independence of Irrelevant Alternatives (IIA) property and showed reliable goodness of fit (${\rho}^2=0.25$). It was concluded that the mixed conditional logit including the effect of landscape itself was appropriate for landscape preference model rather than usual conditional logit excluding the effect.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.10
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• pp.4717-4737
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• 2017

Today, smart grids, smart homes, smart water networks, and intelligent transportation, are infrastructure systems that connect our world more than we ever thought possible and are associated with a single concept, the Internet of Things (IoT). The number of devices connected to the IoT and hence the number of traffic flow increases continuously, as well as the emergence of new applications. Although cutting-edge hardware technology can be employed to achieve a fast implementation to handle this huge data streams, there will always be a limit on size of traffic supported by a given architecture. However, recent cloud-based big data technologies fortunately offer an ideal environment to handle this issue. Moreover, the ever-increasing high volume of traffic created on demand presents great challenges for flow management. As a solution, flow aggregation decreases the number of flows needed to be processed by the network. The previous works in the literature prove that most of aggregation strategies designed for smart grids aim at optimizing system operation performance. They consider a common identifier to aggregate traffic on each device, having its independent static aggregation policy. In this paper, we propose a dynamic approach to aggregate flows based on traffic characteristics and device preferences. Our algorithm runs on a big data platform to provide an end-to-end network visibility of flows, which performs high-speed and high-volume computations to identify the clusters of similar flows and aggregate massive number of mice flows into a few meta-flows. Compared with existing solutions, our approach dynamically aggregates large number of such small flows into fewer flows, based on traffic characteristics and access node preferences. Using this approach, we alleviate the problem of processing a large amount of micro flows, and also significantly improve the accuracy of meeting the access node QoS demands. We conducted experiments, using a dataset of up to 100,000 flows, and studied the performance of our algorithm analytically. The experimental results are presented to show the promising effectiveness and scalability of our proposed approach.

• Journal of the Korea Society of Computer and Information
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• v.22 no.2
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• pp.81-87
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• 2017

Nowadays wine is increasingly enjoyed by a wider range of consumers, and wine certification and quality assessment are key elements in supporting the wine industry to develop new technologies for both wine making and selling processes. There have been many attempts to construct a more methodical approach to the assessment of wines, but most of them rely on objective decision rather than subjective judgement. In this paper, we propose a data mining approach to predict human wine taste preferences that is based on easily available analytical tests at the certification step. We used sequential forward selection and decision tree for this purpose. Experiments with the wine quality dataset from the UC Irvine Machine Learning Repository demonstrate the accuracies of 76.7% and 78.7% for red and white wines respectively.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2000.10a
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• pp.302-305
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• 2000

The operation of a networked computing system (NCS), such as Internet, can be viewed as a resource allocation problem, and can be analyzed using the techniques of mathematical modeling. We define a general NCS and translate that setup into a model of an economy. The preferences of users are taken as primitives, and servers in the network are viewed as productive firms with priority input queues. Each sewer charges a rental price for its services by priority class. We characterize optimal system allocation, and derive formulae for supporting rental prices and priority premia such that the aggregated individual user demands do not exceed optimal levels and waiting-time expectations are correct. Our economic approach has the added benefit of providing a sound basis for evaluating NCS investment alternatives, using a process analogous to free entry and exit in free-enterprise economies.

• Management Science and Financial Engineering
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• v.17 no.1
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• pp.1-18
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• 2011

The present study provides a theoretical investigation on pioneering advantage based on reference dependence and loss aversion effect under prospect theory (Kahneman and Tversky, 1979). Behavioral explanations for pioneering advantage are provided from two different perspectives: one based on the prototypicality and the other on the utility uncertainty of the option. A pioneer brand creates the product category and makes a strong impression in customers' mind, and thus becomes the most representative or prototypical option of the category. In addition, the pioneer brand becomes the first option to be experienced by the majority of consumers in the product category, thus has the lowest level of utility uncertainty compared with the late movers. This study integrates the previous accounts for pioneering advantage by showing that consumers have higher preferences for the most prototypical and the least uncertain option based on loss aversion and reference dependence effect. This study suggests that firms should carefully analyze the consumers' loss aversion and perceived uncertainty and prototypicality of their products in order to develop effective market entry strategies.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2002.05a
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• pp.734-741
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• 2002

The importance of efficient Supply Chain Management is increasing in accordance with recent industrial environment, such as globalization of business, complexity and diversity of company's management structure, and variety of customer's demand. In a rapidly changed environment of business, quick and efficient decision making is the important matter to the survival of the company. The purpose of this study supports decision making for efficient supply chain management. In this study, we consider simultaneously and mutually reflecting the preference of each constituent (Supplier, Manufacturing plant, Distribution center, Customer) on supply chain network, and decide company's strategic choice and coordinated production/distribution models of company. The Analytical Hierarchy Process is used for decision making of qualitative and quantitative elements. We use the results of AHP as inputs and propose mathematical models thru Mixed Integer Programming.