• Journal of Nutrition and Health
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• v.41 no.1
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• pp.77-88
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• 2008

This research was carried out a to investigate the food habit and preference of parents' social and economic level with 681 children (145 of Kindergarten, 300 of Children, 236 of Adolescences) in Seoul and Gyeonggi area using question naires. The parents' income level divided into 2 groups, less than 4 million won and equal or greater than 4 million won. Most of the middle years were over-weighing but kindergarten and adolescences had standard weights. The majority of parents had Bachelor degrees, most of father were office workers, majority of mothers of kindergarten with parents' income level less than 4 million won were professional women and mothers of the rest of the groups were mostly house wives. The middle years with parents income level less than 4 million son were skipping meals most frequently, but other groups didn't show much differences in their eating habits. All age groups showed that they like meats the most and dislike vegetables the worst. All age groups also showed that they mostly eat out 1-2 times a week and the next was 3-4 times a week. All age groups preferred ice creams, fruits, juices and snacks for their desserts. The middle years with parents' income equal or greater than 4 million won also showed high preference on strawberry and chocolate flavored milk, burgers and pizzas. The food s that preferred to eat when dining out were Chinese foods (Ja-jang-myeon and sweet and sour pork) for kindergarten group, Korean foods (kalbi and bulgogi) for the middle years with parents' income level less than 4 million won, family restaurant food (steak and rib) for the middle years with parents' income level equal or greater than 4 million won and Korean foods (kalbi and bulgogi) for the adolescences. The preferred cooking methods were roast (fish and sea weeds) for the kindergarten, roasted meat for the middle years, Kimchi and bean paste pot stew for the adolescences with parents' income level less than 4 million won and roasted meats for the adolescences with parents' income level equal or greater than 4 million won. The results showed that the adolescences with higher parental income lever preferred meats.

• Journal of the Korean association of regional geographers
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• v.5 no.2
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• pp.47-117
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• 1999

This study concern with the pattern of Pusan Station shopping district within Pusan City, Korea, one of the special functioned shopping district within Pusan City. This paper will serve as a part of series studies which attempt to clarify the internal structure of Pusan as a whole. Part(II) of this study deals with the functions including living related, restaurants and others. The pattern of floors, size of shops, street corners and widths of streets were also analysed. The results are as follows: 1. In terms of numbers of firms in living related function, Pusan Station shopping district is the $7{\sim}8th$ ranked central place among nine the highest centers within Pusan City. Pusan Station shopping district has not much promoted vertical spatial differentiation comparatively, and also it's intensity of land use is the lower among nine the highest centers. It is presented that intimate relationship between intensity of vertical land use and classes of central places within the city. The ratio of inns and hotels in Pusan Station shopping district is third ranked in Pusan City. And the size of inns and hotels in this area is the most largest among the nine highest ranked central places within Pusan City. These presented that the traditional characteristics of station area as a special functioned shopping district. Inns and hotels mainly located along the narrower and back street. And it forms agglomerated areas or 'an alley of inns' at the inner parts of blocks, some like a 'hidden flower'. In Korea, 'alley' means that an area of specialization gains the prestige, traditionally. 2. Restaurants mainly locate along the narrower and back streets. And agglomerated areas of restaurants coincide with the agglomerated area of drinking places. It shows that these two kinds of functions need the same locational conditions. The ratio of Chinese restaurants is the highest in the Pusan Station shopping district. It's due to the agglomerated area these kinds of restaurants at the 'China town'. 3. Pusan Station shopping district has been formed along the streets within the residential areas. It's means that this shopping district now at the initial or middle growth era in development stage of shopping areas. 4. In general, wholesales and light manufacturing are located at peripheries within shopping district. But in Pusan Station shopping district, it dose not appear these spatial pattern. It shows that this area is lower ranked central place and not much progressed in spatial differentiation. 5. Particular firms which customers and workers have stayed more longer period of time are located at the far from the first floor. This vertical spatial differentiation is similar to the horizontal sequences. 6. Firms which have more ability of rental payment are located at street comers such as banks and pharmacies. In Pusan Station shopping district commercial facilities could not invade into the second third floors at narrower streets and first floor of back streets, still now.

• The Southeast Asian review
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• v.28 no.3
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• pp.159-212
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• 2018

This paper is focused on analyzing the social environment of a rapidly changing on Vietnamese company. The key analysis of this study is on the change of perception in Vietnam and the regional difference of CSR acception. The social acceptance research of CSR is centered on the comparative analysis of Korean, Japanese and Chinese companies Social Activities in Vietnam. In addition, This paper seek to way of contribute to the sustainable development of Korean companies, and its harmonious cooperation with Vietnamese society through reviewing the CSR activities and direction of their CSR expectation. In the paper, linkage analysis was conducted with the results of the study on CSR value development process in Vietnam society and analysis of social responsibility values obtained from empirical studies. Through this, finally, we trying to search the value of social responsibility in Vietnam and its future directions. When we understand Vietnam's CSR, based on 'locality' of Vietnam, Northern and Southern can be understand on its different backgrounds. And it can be analyzed by their CSR characteristics of acception. As the result of this research, In the North, Foreign companies' CSR is understanded to be viewed from the corporate economic income and distribution. In the South, there is a strong tendency to understand CSR activities of foreign companies as marketing activities. On the whole, In northern Hanoi, there was a strong expectation in terms of 'employment improvement' and 'workers' working conditions'. In the South, there was a greater interest in improving the 'quality of life of residents' and 'consumer protection'. This is due to the influence of the economic system experienced during the process of different colonization, modernization and communization between the two regions. Since the Reform and Opening of Vietnam, Social Awareness of CSR seems that the regional differences were formed by the pace of economic development and the economic environment has played a role. In particular, the social acceptance of CSR values showed a slight difference in recognition between the North and South regions, but as both regions showed common hope for 'intervention in the role of government'. Therefore, Social Awareness of Vietnam's CSR is based on relation of 'government-society' formed from the 'Communitarianism'. As foreign investment flows more, CSR awareness and expectations in Vietnam's society will increase further. And the CSR expectations of local governments and stakeholder will be more complicated. It is time to check the needs of Vietnamese society in relation to locality of the social responsibility activities.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.1-23
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• 2018

From the 21st century, various high-quality services have come up with the growth of the internet or 'Information and Communication Technologies'. Especially, the scale of E-commerce industry in which Amazon and E-bay are standing out is exploding in a large way. As E-commerce grows, Customers could get what they want to buy easily while comparing various products because more products have been registered at online shopping malls. However, a problem has arisen with the growth of E-commerce. As too many products have been registered, it has become difficult for customers to search what they really need in the flood of products. When customers search for desired products with a generalized keyword, too many products have come out as a result. On the contrary, few products have been searched if customers type in details of products because concrete product-attributes have been registered rarely. In this situation, recognizing texts in images automatically with a machine can be a solution. Because bulk of product details are written in catalogs as image format, most of product information are not searched with text inputs in the current text-based searching system. It means if information in images can be converted to text format, customers can search products with product-details, which make them shop more conveniently. There are various existing OCR(Optical Character Recognition) programs which can recognize texts in images. But existing OCR programs are hard to be applied to catalog because they have problems in recognizing texts in certain circumstances, like texts are not big enough or fonts are not consistent. Therefore, this research suggests the way to recognize keywords in catalog with the Deep Learning algorithm which is state of the art in image-recognition area from 2010s. Single Shot Multibox Detector(SSD), which is a credited model for object-detection performance, can be used with structures re-designed to take into account the difference of text from object. But there is an issue that SSD model needs a lot of labeled-train data to be trained, because of the characteristic of deep learning algorithms, that it should be trained by supervised-learning. To collect data, we can try labelling location and classification information to texts in catalog manually. But if data are collected manually, many problems would come up. Some keywords would be missed because human can make mistakes while labelling train data. And it becomes too time-consuming to collect train data considering the scale of data needed or costly if a lot of workers are hired to shorten the time. Furthermore, if some specific keywords are needed to be trained, searching images that have the words would be difficult, as well. To solve the data issue, this research developed a program which create train data automatically. This program can make images which have various keywords and pictures like catalog and save location-information of keywords at the same time. With this program, not only data can be collected efficiently, but also the performance of SSD model becomes better. The SSD model recorded 81.99% of recognition rate with 20,000 data created by the program. Moreover, this research had an efficiency test of SSD model according to data differences to analyze what feature of data exert influence upon the performance of recognizing texts in images. As a result, it is figured out that the number of labeled keywords, the addition of overlapped keyword label, the existence of keywords that is not labeled, the spaces among keywords and the differences of background images are related to the performance of SSD model. This test can lead performance improvement of SSD model or other text-recognizing machine based on deep learning algorithm with high-quality data. SSD model which is re-designed to recognize texts in images and the program developed for creating train data are expected to contribute to improvement of searching system in E-commerce. Suppliers can put less time to register keywords for products and customers can search products with product-details which is written on the catalog.