• Korean Journal of Mathematics
• /
• 제28권1호
• /
• pp.75-87
• /
• 2020

Category F Rel of fuzzy sets and relations does not form a topos. J. Harding, C. Walker and E. Walker [3] showed that FRel has a tensor product and V. Durov [1] introduced basic definitions related to the notion of vectoid endowed with a tensor product. In this paper, we show that FRel forms a quasi topos. Also we show that there are quasi power objects in FRel. And by the use of the concepts of FRel and quasi topos, we get the logic operators of FRel. Moreover, we show that FRel forms a vectoid.

• 대한전자공학회:학술대회논문집
• /
• 대한전자공학회 1999년도 하계종합학술대회 논문집
• /
• pp.1001-1004
• /
• 1999

We study on machine learning method for automatic document categorization using back propagation algorithm. Four categories are classified for the experiment and the system learns with 20 documents per a category by this method. As a result of the machine learning, we can find that a new document is automatically classified with a category according to the predefined ones.

• International Journal of Costume and Fashion
• /
• 제16권1호
• /
• pp.17-35
• /
• 2016

The purpose of this study is to investigate the benefits sought by luxury good customers contingent on product category, and to understand the relationship between the benefits sought and brand loyalty. A qualitative approach was used; therefore in-depth interviews were conducted with seven panels of professionals in the luxury industry. The findings are as follows: 1) Handbag customers mainly seek the social benefits in order to express their social status by purchasing well-known, easily-recognizable brands. 2) Shoe customers primarily seek the practical-functional benefits, which are comfort and function. 3) Small Leather Goods customers seek the social benefits for themselves and as gifts for others. 4) Brand loyalty for handbag customers is reported to be low, as their primary goals are the social benefits. Rather than devoting themselves to one specific brand, handbag customers prefer to purchase from various brands. 5) Shoe customers have reportedly higher brand loyalty, as they tend to come back to brands when they are satisfied with the benefits they pursue. The findings of this study provide more information on the practical implications of luxury good customer purchasing habits. Firstly, customers pursue different benefits depending on product category, and secondly, brand loyalty differs by customers' benefits.

• 부모자녀건강학회지
• /
• 제16권1호
• /
• pp.17-26
• /
• 2013

Purpose: This study was to examine the mother's knowledge of premature development and rearing and their education needs in order to provide information to develop an education program for premature mothers. Methods: The study participants was 73 mothers of premature infants. Knowledge on premature infant's development and rearing was measured by measurement tools developed by previous research. The education needs about development and rearing were measured by self-report questionnaire. The data were analyzed using descriptive statistics, t-Test, ANOVA using SPSS 20.0. Results: The score of knowledge on development was 59.3 out of 100. The category of knowledge on language development was rated the highest, and motor development category was the lowest. The score of knowledge on rearing was 77.8 out of 100. The knowledge on bathing category was rated the highest and defecation category was the lowest. The growth education needs for premature infant development was the highest education needs of premature infant development. The method for developmental improvement was the highest education needs of premature infant rearing. Conclusion: The results showed that premature infant mothers have less knowledge on premature development than premature rearing, also mothers were interested in development and there were many needs on premature infant's development.

• International Journal of Advanced Culture Technology
• /
• 제7권4호
• /
• pp.321-326
• /
• 2019

As AI technology is recently introduced into various fields, it is being applied to the fashion field. This paper proposes a system for recommending cody clothes suitable for a user's selected clothes. The proposed system consists of user app, cody recommendation module, and server interworking of each module and managing database data. Cody recommendation system classifies clothing images into 80 categories composed of feature combinations, selects multiple representative reference images for each category, and selects 3 full body cordy images for each representative reference image. Cody images of the representative reference image were determined by analyzing the user's preference using Google survey app. The proposed algorithm classifies categories the clothing image selected by the user into a category, recognizes the most similar image among the classification category reference images, and transmits the linked cody images to the user's app. The proposed system uses the ResNet-50 model to categorize the input image and measures similarity using ORB and HOG features to select a reference image in the category. We test the proposed algorithm in the Android app, and the result shows that the recommended system runs well.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• 제5권1호
• /
• pp.88-93
• /
• 2005

Web usage mining is a research field for searching potentially useful and valuable information from web log file. Web log file is a simple list of pages that users refer. Therefore, it is not easy to analyze user's current interest field from web log file. This paper presents web usage mining method for finding users' current interest based on fuzzy categories. We consider not only how many times a user visits pages but also when he visits. We describe a user's current interest with a fuzzy interest degree to categories. Based on fuzzy categories and fuzzy interest degrees, we also propose a method to cluster users according to their interests for user modeling. For user clustering, we define a category vector space. Experiments show that our method properly reflects the time factor of users' web visiting as well as the users' visit number.

• Journal of Information Technology Applications and Management
• /
• 제13권4호
• /
• pp.197-214
• /
• 2006

This study explores factors to facilitate web-based collaborative learning and the effect of learning, based on the PBL(Problem Based Learning) from the constructivist approach in e-learning. A research model, using the key variables such as situations, interactions, and systems, was developed. In order to test this proposed model, experimental design and post-survey was conducted to the learners who took on-line and off-line course with team project. In the research model, situation category was divided into instructor's support, unstructured problem, and self-directed learning. Interaction category was divided into three factors; 'interaction between learners', 'interaction between learner and instructor', and 'interaction between learner and technology'. System category was divided into.monitoring and incentives. As a result, it was found that collaborative learning can be improved by situations, interactions, and systems, and the effectiveness of learning can be improved by situations and interactions in PBL.

• Industrial Engineering and Management Systems
• /
• 제11권2호
• /
• pp.134-141
• /
• 2012

It is difficult to find an appropriate ordering policy for a many types of items. One of the reasons for this difficulty is that each item has a different demand trend. We will classify items by shipment trend and then decide the ordering policy for each item category. In this study, we indicate that categorizing items from their statistical characteristics leads to an ordering policy suitable for that category. We analyze the ordering policy and shipment trend and propose a new method for selecting the ordering policy which is based on finding the strongest relation between the classification of the items and the ordering policy. In our numerical experiment, from actual shipment data of about 5,000 items over the past year, we calculated many statistics that represent the trend of each item. Next, we applied the canonical correlation analysis between the evaluations of ordering policies and the various statistics. Furthermore, we applied the cluster analysis on the statistics concerning the performance of ordering policies. Finally, we separate items into several categories and show that the appropriate ordering policies are different for each category.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제8권2호
• /
• pp.583-600
• /
• 2014

Social media is considered a valuable platform for gathering and analyzing the collective and subconscious opinions of people in Internet and mobile environments, where they express, explicitly and implicitly, their daily preferences for brands and products. Extracting and tracking the various attitudes and concerns that people express through social media could enable us to categorize brands and decipher individuals' cognitive decision-making structure in their choice of brands. We investigate the cognitive network structure of consumers by building an inter-category map through the mining of big data. In so doing, we create an improved online recommendation model. Building on economic sociology theory, we suggest a framework for revealing collective preference by analyzing the patterns of brand names that users frequently mention in the online public sphere. We expect that our study will be useful for those conducting theoretical research on digital marketing strategies and doing practical work on branding strategies.

• Earthquakes and Structures
• /
• 제6권2호
• /
• pp.201-216
• /
• 2014

Many building codes use the empirical equation to determine fundamental period of vibration where in effect of length, width and the stiffness of the building is not explicitly accounted for. Also the equation, estimates the fundamental period of vibration with large safety margin beyond certain height of the building. An attempt is made to arrive at the simple empirical equations for fundamental period of vibration with adequate safety margin, using soft computing technique of Genetic Programming (GP). In the present study, GP models are developed in four categories, varying the number of input parameters in each category. Input parameters are chosen to represent mass, stiffness and geometry of the buildings directly or indirectly. Total numbers of 206 buildings are analyzed out of which, data set of 142 buildings is used to develop these models. It is observed that GP models developed under B and C category yield the same equation for fundamental period of vibration along X direction as well as along Y direction whereas the equation of fundamental period of vibration along X direction and along Y direction is of the same form for category D. The equations obtained as an output of GP models clearly indicate the influence of mass, geometry and stiffness of the building over fundamental period of vibration. These equations are then compared with the equation recommended by other researcher.