• Journal of the Economic Geographical Society of Korea
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• v.5 no.1
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• pp.69-87
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• 2002

This study examines the spatial diffusion and locational charateristics of convenience stores in Daegu which had increased rapidly in the 1990s. The first convenience store (CVS) was introduced in the zone of transition of (Namgu district) adjacent to the city center or CBD in 1992. Thereafter they diffused into CBD and residential areas, but they have centered around places where their steady purchasing population was distributed. As a result, the spatial distribution of CVSs in Daegu shows a very uneven pattern concentrated in areas with many high school, in commercial and business areas, and apartment residential areas. It seems that this pattern is derived from two basic locational factors. Primarily, the location of CVSs in Daegu is very closely related with the spatial distribution of the demand population which will be clients for CVSs. Secondarily, it is also affected by the accessibility of streets which the demand population utilizes easily.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.3
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• pp.113-121
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• 2013

In this paper, we propose a sub-pixel rendering algorithm using learning-based 2D FIR filters. The proposed algorithm consists of two stages: the learning and synthesis stages. At the learning stage, we produce the low-resolution synthesis information derived from a sufficient number of high/low resolution block pairs, and store the synthesis information into a so-called dictionary. At the synthesis stage, the best candidate block corresponding to each input high-resolution block is found in the dictionary. Next, we can finally obtain the low-resolution image by synthesizing the low-resolution block using the selected 2D FIR filter on a sub-pixel basis. On the other hand, we additionally enhance the sharpness of the output image by using pre-emphasis considering RGB stripe pattern of display. The simulation results show that the proposed algorithm can provide significantly sharper results than conventional down-sampling methods, without blur effects and aliasing.

• Korean Journal of Occupational Health Nursing
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• v.12 no.1
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• pp.19-30
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• 2003

Increasing occupational cerebrovascular & cardiovascular disease, it becomes the most serious problem in the occupational health management. Hypertension is the most important risk factor of cerebrovascular & cardiovascular disease. Although treatment for hypertension has the priority, hypertension has not been managed systematically at the worksite. The objectives of this study were to investigate the actual situation of its treatment, figure out what factors can affect compliance for hypertension treatment and analyze the relations between compliance and employment status. Subjects were 28 workers who have been diagnosed as hypertension at periodic health examination, 20 workers who have been managed for hypertension at dispensary and 22 workers who were diagnosed during the study periods. The results of the study were as follows; 1. More women have been hired as part time workers and had lower education background and income than the full time workers. 2. Among the factors that have been known to affect the treatment compliance, part time workers had less supports from the company than full time workers. 3. We got the comparison of difference between compliance and variables that the factor grade of cure promotion and average ages are high in high compliance. In conclusion there were not the difference of compliance by employment status. But it was hard to rule out the selection vias because the sample size was so small. So it seems difficult to generalized the conclusion that employment status doesn't affect the treatment compliance.

• Journal of the Korean Society of Food Culture
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• v.33 no.2
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• pp.112-124
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• 2018

Despite the rapid increase in the number of foreign students, there has been a lack of research to help them adapt to Korean food culture and develop healthy eating habits. This study examined the dietary habits and problems of foreign students studying in universities of Korea. Although 97.0% of the 604 people surveyed live in dormitories, the visiting rate of the school cafeteria was low. In addition, only 30.2% of them ate three meals a day, and the frequency of eating midnight snack and convenience store foods was high. International students were positive about experiencing new Korean food, but food satisfaction in Korea was not high because of the difficulties in food selection due to religious problems and maladjustment to Korean sauces and seasonings. Information on Korean eating habits was obtained mainly from other foreign students from the same country (49.5%) and the Internet (33.8%), and there was very little interaction with Korean students at meals. The ratio of subjects who ate halal foods was 33.3%, and they were shown to have difficulty obtaining halal foods in Korea. Therefore, based on the results of this study, a support program should be developed in order to improve the dietary habits of international students.

• International Journal of Aeronautical and Space Sciences
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• v.4 no.1
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• pp.34-44
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• 2003

An advanced aeroelastic analysis using a computational structural dynamics (CSD), finite element method (FEM) and computational fluid dynamics (CFD) is presented in this Paper. A general aeroelastic analysis system is originally developed and applied to realistic design problems in the transonic flow region, where strong shock wave interactions exist. The present computational approach is based on the modal-based coupled nonlinear analysis with the matched-point concept and adopts the high-speed parallel processing technique on the low-cost network based PC-clustered machines. It can give very accurate and useful engineering data on the structural dynamic design of advanced flight vehicles. For the nonlinear unsteady aerodynamics in high transonic flow region, Euler equations using the unstructured grid system have been applied to easily consider complex configurations. It is typically shown that the advanced numerical approach can give very realistic and practical results for design engineers and safe flight tests. One can find that the present study conducts a virtual flutter flight test which are usually very dangerous in reality.

• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.39-54
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• 2013

Recent explosive increase of electronic commerce provides many advantageous purchase opportunities to customers. In this situation, customers who do not have enough knowledge about their purchases, may accept product recommendations. Product recommender systems automatically reflect user's preference and provide recommendation list to the users. Thus, product recommender system in online shopping store has been known as one of the most popular tools for one-to-one marketing. However, recommender systems which do not properly reflect user's preference cause user's disappointment and waste of time. In this study, we propose a novel recommender system which uses data mining and multi-model ensemble techniques to enhance the recommendation performance through reflecting the precise user's preference. The research data is collected from the real-world online shopping store, which deals products from famous art galleries and museums in Korea. The data initially contain 5759 transaction data, but finally remain 3167 transaction data after deletion of null data. In this study, we transform the categorical variables into dummy variables and exclude outlier data. The proposed model consists of two steps. The first step predicts customers who have high likelihood to purchase products in the online shopping store. In this step, we first use logistic regression, decision trees, and artificial neural networks to predict customers who have high likelihood to purchase products in each product group. We perform above data mining techniques using SAS E-Miner software. In this study, we partition datasets into two sets as modeling and validation sets for the logistic regression and decision trees. We also partition datasets into three sets as training, test, and validation sets for the artificial neural network model. The validation dataset is equal for the all experiments. Then we composite the results of each predictor using the multi-model ensemble techniques such as bagging and bumping. Bagging is the abbreviation of "Bootstrap Aggregation" and it composite outputs from several machine learning techniques for raising the performance and stability of prediction or classification. This technique is special form of the averaging method. Bumping is the abbreviation of "Bootstrap Umbrella of Model Parameter," and it only considers the model which has the lowest error value. The results show that bumping outperforms bagging and the other predictors except for "Poster" product group. For the "Poster" product group, artificial neural network model performs better than the other models. In the second step, we use the market basket analysis to extract association rules for co-purchased products. We can extract thirty one association rules according to values of Lift, Support, and Confidence measure. We set the minimum transaction frequency to support associations as 5%, maximum number of items in an association as 4, and minimum confidence for rule generation as 10%. This study also excludes the extracted association rules below 1 of lift value. We finally get fifteen association rules by excluding duplicate rules. Among the fifteen association rules, eleven rules contain association between products in "Office Supplies" product group, one rules include the association between "Office Supplies" and "Fashion" product groups, and other three rules contain association between "Office Supplies" and "Home Decoration" product groups. Finally, the proposed product recommender systems provides list of recommendations to the proper customers. We test the usability of the proposed system by using prototype and real-world transaction and profile data. For this end, we construct the prototype system by using the ASP, Java Script and Microsoft Access. In addition, we survey about user satisfaction for the recommended product list from the proposed system and the randomly selected product lists. The participants for the survey are 173 persons who use MSN Messenger, Daum Caf$\acute{e}$, and P2P services. We evaluate the user satisfaction using five-scale Likert measure. This study also performs "Paired Sample T-test" for the results of the survey. The results show that the proposed model outperforms the random selection model with 1% statistical significance level. It means that the users satisfied the recommended product list significantly. The results also show that the proposed system may be useful in real-world online shopping store.

• Journal of Distribution Science
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• v.16 no.12
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• pp.57-68
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• 2018

Purpose - The development of technologies lead the volume of sale on online market increase but an off-line shopping center is still a core component in the omni-channel strategy. It is generally thought that high-level retailtainment on brick and mortar store affects purchase intentions positively, but some previous studies dispute that and have reported that retailtainment does not affect purchase intentions. So we have studied the additional factors' effect - the nature of purchase and utility - with retailtainment. Research design, data, and methodology - There are 8 treatment groups which were assigned by the method of retailtainment (high vs. low), nature of purchase (essential vs. non-essential), and utility (acquisition vs. transaction). A total of 240 subjects (office workers = 163, 68%; undergraduates = 77, 32%; average age = 30s; female = 39%) were divided into groups and exposed to one of the eight scenarios. Participant's purchase intention was the dependent, and ANOVA and L-matrix were used to analyze for main and interactive effects between factors. Results - First, the main effect and interactive effect between retailtainment and the nature of purchase are significant. We also found that the contrast between essential and non-essential at low-level retailtainment is higher than that of high-level retailtainment. Second, in the case of retailtainment and utility, transaction utility under high-level retailtainment affects purchase intentions positively. Third, between the nature of the purchase and utility, the main effect of the nature of purchase and the interactive effect is significant, but the main effect of utility is not significant. In the case of non-essential goods, the purchase intention was high when transaction utility was provided but in the case of essential goods, acquisition utility increased purchase intentions. Finally, when transaction utility is given, purchase intentions of essential goods increase under low retailtainment, and the purchase intentions of non-essential goods increase under high retailtainment. Conclusions - When customers buy essential goods, discounts decrease purchase intentions. During the season for bargain sales, purchase intentions increase when retailtainment of essential goods is low, and retailtainment of non-essential goods is high.

• Journal of Intelligence and Information Systems
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• v.21 no.2
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• pp.93-112
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• 2015

Depending on the change in consumer's consumption pattern, existing retail shop has evolved in hypermarket or convenience store offering grocery and daily products mostly. Therefore, it is important to maintain the inventory levels and proper product configuration for effectively utilize the limited space in the retail store and increasing sales. Accordingly, this study proposed proper product configuration and inventory level strategy based on RFM(Recency, Frequency, Monetary) model and SOM(self-organizing map) for manage the retail shop effectively. RFM model is analytic model to analyze customer behaviors based on the past customer's buying activities. And it can differentiates important customers from large data by three variables. R represents recency, which refers to the last purchase of commodities. The latest consuming customer has bigger R. F represents frequency, which refers to the number of transactions in a particular period and M represents monetary, which refers to consumption money amount in a particular period. Thus, RFM method has been known to be a very effective model for customer segmentation. In this study, using a normalized value of the RFM variables, SOM cluster analysis was performed. SOM is regarded as one of the most distinguished artificial neural network models in the unsupervised learning tool space. It is a popular tool for clustering and visualization of high dimensional data in such a way that similar items are grouped spatially close to one another. In particular, it has been successfully applied in various technical fields for finding patterns. In our research, the procedure tries to find sales patterns by analyzing product sales records with Recency, Frequency and Monetary values. And to suggest a business strategy, we conduct the decision tree based on SOM results. To validate the proposed procedure in this study, we adopted the M-mart data collected between 2014.01.01~2014.12.31. Each product get the value of R, F, M, and they are clustered by 9 using SOM. And we also performed three tests using the weekday data, weekend data, whole data in order to analyze the sales pattern change. In order to propose the strategy of each cluster, we examine the criteria of product clustering. The clusters through the SOM can be explained by the characteristics of these clusters of decision trees. As a result, we can suggest the inventory management strategy of each 9 clusters through the suggested procedures of the study. The highest of all three value(R, F, M) cluster's products need to have high level of the inventory as well as to be disposed in a place where it can be increasing customer's path. In contrast, the lowest of all three value(R, F, M) cluster's products need to have low level of inventory as well as to be disposed in a place where visibility is low. The highest R value cluster's products is usually new releases products, and need to be placed on the front of the store. And, manager should decrease inventory levels gradually in the highest F value cluster's products purchased in the past. Because, we assume that cluster has lower R value and the M value than the average value of good. And it can be deduced that product are sold poorly in recent days and total sales also will be lower than the frequency. The procedure presented in this study is expected to contribute to raising the profitability of the retail store. The paper is organized as follows. The second chapter briefly reviews the literature related to this study. The third chapter suggests procedures for research proposals, and the fourth chapter applied suggested procedure using the actual product sales data. Finally, the fifth chapter described the conclusion of the study and further research.

• The Korean Journal of Franchise Management
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• v.9 no.3
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• pp.19-29
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• 2018

Purpose - Due to the increase in coffee consumption and competition, domestic coffee franchise companies are currently entering the overseas market. Therefore, coffee franchise companies are pursuing a variety of marketing strategies to meet customer needs and gain competitive advantage in overseas markets. From this perspective, overseas franchise companies need to ensure that their servicescapes meet the needs of their overseas customers. For these purposes, the study is to identify the impact servicescapes on customer satisfaction and customer loyalty focused on Global Coffee Franchise Company "C", which extended its business worldwide in Mongolia. Research design, data, and methodology - The data were collected from customers who had visited the stores of 'C' company in Ulaanbaatar, Mongolia. 435 valid questionnaires collected through online survey coded and analyzed using frequency, confirmatory factor analysis, correlations analysis, and structural equation modeling with SPSS 24 and SmartPLS 3.0. Result - Firstly, seating comfort, facility aesthetics, and cleanliness, ambient conditions among servicescapes influenced customer satisfaction. Secondly, servicescapes didn't affect the loyalty directly. Third, customer satisfaction had positive effect on loyalty. Fourthly, cleanliness which was ranked lower in Korea had a great effect on customer satisfaction in Mongolia. Fifthly, IPMA(Importance-performance map analysis) shows that the importance of servicescapes is higher for women than for men, and facility aesthetics for female and cleanliness is the most important for male. Conclusions - The results of this study show that there is a positive (+) effect on customer satisfaction in order of cleanliness, ambient conditions, aesthetics, and seating comfort. Therefore, franchise companies considering or advancing into Mongolia should consider importance in order of cleanliness, ambient conditions and aesthetics when entering Mongolia market. For example, franchise managers should select Monday as a "clean day," and all merchants should spend all of their open hours and keep their stores clean in accordance with the head office manual. In addition, franchise managers need to hire a VMD (visual merchandising) experts to build up a physical environment that will effectively highlight the space-specific display of the store so that Mongolian local customers can have a satisfactory climate and aesthetics. And, the IMPA analysis between servicescapes and customer satisfaction shows that women are more susceptible to servicescapes than men. Especially, in the case of women, the importance of esthetics is high, but the performance is low. Thus, if the aesthetics are actively improved, customer satisfaction can be effectively increased.

• Journal of the Korean Institute of Gas
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• v.18 no.1
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• pp.17-24
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• 2014

LNG storage tank is a facility to store liquefied natural gas (LNG) and its safety and stability to be greatly needed. When there is a LNG leakage in case of primary container problem, a special facility such as a bund wall should be constructed to store the leaked LNG. But this method makes the land usage inefficient and construction price high. So nowadays the full containment type LNG storage tank is selected instead of constructing a bund wall. In the full containment type tank, the concrete sidewall has the ability to store LNG temporarily. There are largely two methods to give the concrete sidewall the ability. In a method, rebar should be used when constructing the side wall of the LNG storage tank. In the other method, the protecting material such as sprayed polyurethane foam should be applied on the inner surface of the concrete sidewall. Sprayed PUF keeps the temperature of the sidewall above the specified temperature during the specified periods. Recently the thermal stability reinforcing method using sprayed polyurethane foam has been applied to all LNG storage tank built in Korea.