• The International Journal of Costume Culture
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• v.13 no.2
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• pp.67-81
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• 2010

This study is a basic research to develop kit and program for fashion psychotherapy, a new genre of therapy. Symptom checklist, self-esteem evaluation, interpersonal relationship problem evaluation and fashion preference evaluation were conducted on 159 college students in Seoul. The results were analyzed with t-test and one-way ANOVA. The result showed that first, warm color preference was significantly high in interpersonal problem among psychological problems. Second, smooth material preference was significantly high in paranoia among psychological problems. Third, differences in design preferences by psychological problems were not significant. Fourth, differences in design preferences between abnormal range and normal range of psychological problems were significant in line shape, with depression abnormal group showing significantly high straight line preference. Additionally, complex shape preference was significant in complexity in somatization and phobia abnormal groups. This study can be utilized in kit development for a new field, fashion psychotherapy. This study is significant as practical basic data in constructing fashion psychotherapy program.

• Journal of the Korean Society of Food Culture
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• v.27 no.5
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• pp.459-468
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• 2012

The purpose of this study was to investigate the effects of eating habits and food preferences on the adoptive behavior of children with intellectual disabilities. Survey questionnaires were distributed to six special education schools located in the Daegu-Kyungbuk area, and data were collected from 552 families and teachers with intellectually disabled students. Identification of eating habits began with a factor analysis, and the results were a five-factor solution. Among the five patterns, factors 1 and 2 were significantly related with behavior problems of intellectually disabled children. Further, food preferences of the children were significantly related with adoptive behavior problems. The findings of this study clearly indicate that eating habits as well as food preferences are important factors in identifying adoptive behavior problems in intellectually disabled children. Based on the findings of this study, similarities and differences in eating habits are discussed, and implications for children are provided.

• Journal of People, Plants, and Environment
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• v.24 no.1
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• pp.63-73
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• 2021

Background and objective: This study was conducted to investigate the effects and preferences of horticultural therapy programs for stress relief according to MBTI personality types (Judging and Perceiving types) of female undergraduate students. Methods: The participants were divided into 15 Judging and 15 Perceiving types based on lifestyle preferences of the MBTI personality test, and a total of 30 participants participated in the horticultural therapy programs for 6 sessions. Results: Both Judging and Perceiving types showed a significant decrease in stress after participating in the horticultural therapy programs. Among the 8 life stress subfactors, Judging types showed significant stress relieving effects in 5 subfactors (relationship with the opposite sex, relationship with family, economic problems, future problems, value problems), while Perceiving types showed stress relieving effects in only 3 subfactors (relationship with family, economic problems, future problems). However, the changes in stress relief of 8 subfactors were not significantly different between the two personality types. The most preferred program for the Judging types was 'Making a flower basket', while the most preferred ones for the Perceiving types were 'Planting monstera', and 'Making preserved lemons with marigold', suggesting that the preferences varied depending on personality types. Conclusion: Therefore, it is necessary to develop suitable horticultural therapy programs for different subjects based on their personality types to enhance the effect of the programs on the subjects.

• Proceedings of the SAREK Conference
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• 2006.06a
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• pp.1061-1068
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• 2006

This study has been conducted to provide the basic datum to draw mechanical equipments needed for aged apartment housing remodeling by questioning survey and interview for residents who has been lived in the aged apartment housing. To preferences survey, we prepare four forms of sheets - questioning survey and interview for residents, interview for managers, and visiting interview for residents. The questioning survey results shows that some residents feel discomfort for water hammer and water supply noise and for noise and stink transmission from air duct installed ceiling to ventilate bathroom. The interview results for residents and managers shows typically two major problems. The first is insulation and heating problems when balcony extended in each household. The second is piping and shaft layouts problem for maintenance and remodeling flexibility. It is important to study indepth each problems because these problems will increase more in the future.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.12
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• pp.3798-3814
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• 2022

Social recommendation algorithm can alleviate data sparsity and cold start problems in recommendation system by integrated social information. Among them, matrix-based decomposition algorithms are the most widely used and studied. Such algorithms use dot product operations to calculate the similarity between users and items, which ignores user's potential preferences, reduces algorithms' recommendation accuracy. This deficiency can be avoided by a metric learning-based social recommendation algorithm, which learns the distance between user embedding vectors and item embedding vectors instead of vector dot-product operations. However, previous works provide no theoretical explanation for its plausibility. Moreover, most works focus on the indirect impact of social friends on user's preferences, ignoring the direct impact on user's rating preferences, which is the influence of user rating preferences. To solve these problems, this study proposes a user bias drift social recommendation algorithm based on metric learning (BDML). The main work of this paper is as follows: (1) the process of introducing metric learning in the social recommendation scenario is introduced in the form of equations, and explained the reason why metric learning can replace the click operation; (2) a new user bias is constructed to simultaneously model the impact of social relationships on user's ratings preferences and user's preferences; Experimental results on two datasets show that the BDML algorithm proposed in this study has better recommendation accuracy compared with other comparison algorithms, and will be able to guarantee the recommendation effect in a more sparse dataset.

• Fashion & Textile Research Journal
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• v.8 no.6
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• pp.618-626
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• 2006

This research explored the actual conditions, problems and design preferences of dementia inpatient clothing. Data were collected by surveying 21 dementia hospitals and nursing care facilities and 87 caregivers and nurses of dementia hospitals. The collected data were analysed through frequency analysis, descriptive analysis and factor analysis. The results were as follows, First, the inpatient clothes of dementia hospitals were two-piece styles, the shirts of front opening with buttons and pants of no opening with elastic band. Those of dementia care facilities were two piece styles of shirts and pants, training suits or private plain clothes not uniform. Severe dementia inpatient dressed uniforms of the jump suits or two piece styles in some dementia care facilities. Second, the problems of dementia inpatient clothing were composed of suitability of raw and subsidiary clothing material, diversity of design and size, durability and form stability of clothes and elastic bands. Third, the design elements similar to those of existing inpatient clothing were preferred with regard to improving dementia inpatient clothing. That is, the design preferences of shirts showed front opening style with buttons, round neckline and a three-quarter-length sleeves. Those of pants came out no opening style with elastic band and full length. Also, pink color and natural patterns were preferred, and the private plain clothing of inpatient and fusion Han-bok style were somewhat preferred.

• Journal of Information Processing Systems
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• v.8 no.2
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• pp.191-212
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• 2012

Since a social network by definition is so diverse, the problem of estimating the preferences of its users is becoming increasingly essential for personalized applications, which range from service recommender systems to the targeted advertising of services. However, unlike traditional estimation problems where the underlying target distribution is stationary; estimating a user's interests typically involves non-stationary distributions. The consequent time varying nature of the distribution to be tracked imposes stringent constraints on the "unlearning" capabilities of the estimator used. Therefore, resorting to strong estimators that converge with a probability of 1 is inefficient since they rely on the assumption that the distribution of the user's preferences is stationary. In this vein, we propose to use a family of stochastic-learning based Weak estimators for learning and tracking a user's time varying interests. Experimental results demonstrate that our proposed paradigm outperforms some of the traditional legacy approaches that represent the state-of-the-art technology.

• Journal of KIISE:Software and Applications
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• v.32 no.7
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• pp.581-591
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• 2005

Collaborative filtering systems have problems involving sparsity and the provision of recommendations by making correlations between only two users' preferences. These systems recommend items based only on the preferences without taking in to account the contents of the items. As a result, the accuracy of recommendations depends on the data from user-rated items. When users rate items, it can be expected that not all users ran do so earnestly. This brings down the accuracy of recommendations. This paper proposes a collaborative recommendation method for extracting typical group preferences using user-item matrix optimization and user profiles in collaborative tittering systems. The method excludes unproven users by using entropy based on data from user-rated items and groups users into clusters after generating user profiles, and then extracts typical group preferences. The proposed method generates collaborative user profiles by using association word mining to reflect contents as well as preferences of items and groups users into clusters based on the profiles by using the vector space model and the K-means algorithm. To compensate for the shortcoming of providing recommendations using correlations between only two user preferences, the proposed method extracts typical preferences of groups using the entropy theory The typical preferences are extracted by combining user entropies with item preferences. The recommender system using typical group preferences solves the problem caused by recommendations based on preferences rated incorrectly by users and reduces time for retrieving the most similar users in groups.

• Journal of Community Nutrition
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• v.1 no.1
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• pp.10-15
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• 1999

This study was undertaken with 542 fifth-grade elementary school children to investigate the characteristics in lifestyle, eating habits, food preferences of overweight and obese children in the Pocheon area of Korea. Anthropometry was conducted to determine obesity, and data was obtained on lifestyle, eating habits and food preferences by using questionnaires. The prevalence rate of obesity was 19.5% for boys and 8.5% for girls, and 14.3% of boys and 14.4% of girls were overweight. No significant differences was found in the body size and education years of parents, family income and the empolymental status of mother. Boys did not show any significant difference between subgroups in lifestyle, eating habits and food preferences. Obese girls watched TV longer and liked physical education less than normal and overweight groups, suggesting that an inactive lifestyle can be related to girls' obesity in this study. Overweight girls answered that they had significantly lower preferences for empty-calorie foods such as candies/caramels and cookies as well as high-fat foods such as samgyupsal(pork belly) than normal weight girls, implicating the fear of obesity for overweight girls, although more studies should be done including an assessment of actual intake of these foods. The preferences of obese girls for these foods were not higher than those of normal-weight girls, suggesting that the preference for certain foods may not be the characteristic of obese girls in this study. A special program for nutritional education with a different focus should be developed to combat the problems of each subgroup depending on gender and obesity status to improve the physical fitness of the children in this area.

• Journal of the Korea Computer Industry Society
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• v.8 no.2
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• pp.89-96
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• 2007

The object-based reservation scheduling techniques are to solve complex scheduling problems using constraint satisfaction problems and object-oriented concepts. We have tried to apply the object-based reservation scheduling techniques to the flight operation scheduling problems. For crew's satisfaction, we have considered the total crew's preferences board in the flight operation scheduling. To consider the over all satisfaction, the events of every object are alloted to the board along its priority. Constraints to reservation scheduling are classified to global and local. The definition of board and information of every event are global constraints and the preferences to object's board slots are local constraints. Actually, we have made an experiment on flight operation scheduling in order to raise crew's satisfaction.