• Journal of the Korean Institute of Landscape Architecture
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• v.46 no.2
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• pp.27-36
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• 2018

This study suggests the necessity of behavior analysis as changes to a park environment to reflect user desires can be implemented only by grasping the needs of park users. Online data (blog) were defined as the basic data of the study. After collecting data by 5 - year units, data mining was used to derive the characteristics of the time series behavior while the significance of the online data was verified through social network analysis. The results of the text mining analysis are as follows. First, primary results included 'walking', 'photography', 'riding bicycles'(inline, kickboard, etc.), and 'eating'. Second, in the early days of the collected data, active physical activity such as exercise was the main factor, but recent passive behavior such as eating, using a mobile phone, games, food and drinking coffee also appeared as a new behavior characteristic in parks. Third, the factors affecting the behavior of park users are the changes of various conditions of society such as internet development and a culture of expressing unique personalities and styles. Fourth, the special behaviors appearing at Olympic Park were derived from educational activities such as cultural activities including watching performances and history lessons. In conclusion, it has been shown that people's lifestyle changes and the behavior of a park are influenced by the changes of the various times rather than the original purpose that was intended during park planning and design. Therefore, it is necessary to create an environment tailored to users by considering the main behaviors and influencing factors of Olympic Park. Text mining used as an analytical method has the merit that past data can be collected. Therefore, it is possible to form analysis from a long-term viewpoint of behavior analysis as well as to measure new behavior and value with derived keywords. In addition, the validity of online data was verified through social network analysis to increase the legitimacy of research results. Research on more comprehensive behavior analysis should be carried out by diversifying the types of data collected later, and various methods for verifying the accuracy and reliability of large-volume data will be needed.

• Archives of design research
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• v.17 no.4
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• pp.223-232
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• 2004

The pedestrian space on the roads shows virtually different images, depending on the local uniqueness that exists in the roadsides, to the one walking. This sort of characteristics of the region originated from the physical special structures of the roadside building the form of the place. Thus, because of the structural difference of the roadside, Pedestrian sense the difference of regions through other images. Research focused on issues of the local roadside sidewalk spaces as what roadside structure is the type that brings out the unique images of the region, and what facets are pursued additionally here, is needed. A roadside of a prosperous region filled with many Pedestrians is selected as the range for the experiment in order to analyze the structure and image of the pedestrian space. Among the roads of the selected region, the structure of the pedestrian space on the roads with more than four lanes was evaluated. As result of the analysis, the images of 10 pedestrian space could be classified into two groups by the difference in proportions of the Df/H(the width of the sidewalk and the height of the roadside building) and the D/H(the width of the road and the height of the roadside building). In order to observe the images of the pedestrian space classified into two groups, the adjectives used to describe the image of scenery were researched, enabling one to induce the images of the two groups form them. One of the images is the image of prosperities, and the other is the image of pleasantness. In addition, as result to the evaluation focused on the characteristic of the roadside buildings in the selected area, it could be divided into two groups, i.e., the commercial region and the business region. The image of prosperities was sensed on the sidewalks of the commercial region, while the image of pleasantness was seen on that of the business region. This study enabled the acknowledgment that in a pedestrian space on a road structure with more than four lanes, the Pedestrian sense different images, depending on the proportional difference in the width of the sidewalk & the height of the roadside building, and the width of the road & the height of the roadside building. This result is expected to be a good reference when a road structure reflecting the uniqueness of its region is to be designed, and especially when the structure of a pedestrian space is to be created.

• The Korean Journal of Food And Nutrition
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• v.28 no.2
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• pp.228-240
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• 2015

This study was conducted to investigate the dietary and other factors affecting bone mineral density (BMD) in older Korean women. A total of 340 women aged 65 to 74 were recruited from the Kugoksoondam area (Kurye, Goksung, Soonchang and Damyang counties), known as the longevity-belt region in Jeonla province, Korea. They were categorized into two groups according to bone status by T-score : a nonosteoporotic group and an osteoporotic group. Demographic characteristics were collected, as well as information on physical measurements, blood tests for biochemical indicators, health status health-related life style, dietary behavior, favorite food groups, nutrient intake and mini nutrition assessment (MNA). The results are as follows: The mean age of 185 nonosteoporotic women was 69.6 years and that of 155 osteoporotic women was 70.9 years (p<0.001). The mean T-score of the nonosteoporotic group was $-1.5mg/cm^3$ and that of theosteoporotic group was $-3.2mg/cm^3$ (p<0.001). Height and body weight in the nonosteoporotic group were significantly higher than in the osteoporotic group (p<0.001, respectively). There was no significant difference in BMI, although the BMI in the nonosteoporotic group was slightly higher. Waist and hip circumferences in the nonosteoporotic group were significantly higher than in the osteoporotic group (p<0.01, respectively), and the mid upper arm and calf circumferences were also significantly higher than in the osteoporotic group (p<0.001, p<0.01, respectively). The 5 m walking ability was significantly superior compared to the osteoporotic group. Serum levels did not show any significant differences between the groups and were within normal range. The serum total protein, albumin and Insulin-like growth factor (IGFs) levels of the nonosteoporotic group were significantly higher than those of the osteoporotic group (p<0.05, p<0.05, p<0.001, respectively). IGF was 104.7 ng/mL for the nonosteoporotic group and 88.1 ng/mL for the osteoporotic group. Physical activity and appetite in the nonosteoporotic group were significantly higher (p<0.01, p<0.05, respectively). The favorite food groups of the nonosteoporotic group comprised more meats and fish than those of the osteoporotic group (p<0.05, respectively). Nutrient intake was not significantly different, with the exception of niacin intake (p<0.05), but the nutrient intake of the nonosteoporotic group was slightly higher than that of the osteoporotic group. The niacin intake of the nonosteoporotic group and the osteoporotic group were 11.4 mgNE and 10.0 mgNE, corresponding to 103.6% and 90.9% of the Korean EAR, respectively. The MNA score of the nonosteoporotic group was significantly more favorable than for the osteoporotic group. In conclusion, it is necessary to maintain adequate body weight and muscle mass. Habitual physical activity may have a beneficial effect on BMD for older women. Dietary factors, such as meat and fish, higher intake of niacin rich foods and nutrient status for older women also appear to have favorable effects on bone mineral density.

• Journal of Intelligence and Information Systems
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• v.29 no.1
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• pp.307-325
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• 2023

Due to the prolonged COVID-19 pandemic, the frequency of people who are tired of living indoors visiting nearby mountains and national parks to relieve depression and lethargy has exploded. There is a place where thousands of people who came out of nature stop walking and breathe and rest, that is the mineral spring. Even in mountains or national parks, there are about 600 mineral springs that can be found occasionally in neighboring parks or trails in the metropolitan area. However, due to irregular and manual water quality tests, people drink mineral water without knowing the test results in real time. Therefore, in this study, we intend to develop a model that can predict the quality of the spring water in real time by exploring the factors affecting the quality of the spring water and collecting data scattered in various places. After limiting the regions to Seoul and Gyeonggi-do due to the limitations of data collection, we obtained data on water quality tests from 2015 to 2020 for about 300 mineral springs in 18 cities where data management is well performed. A total of 10 factors were finally selected after two rounds of review among various factors that are considered to affect the suitability of the mineral spring water quality. Using AutoML, an automated machine learning technology that has recently been attracting attention, we derived the top 5 models based on prediction performance among about 20 machine learning methods. Among them, the catboost model has the highest performance with a prediction classification accuracy of 75.26%. In addition, as a result of examining the absolute influence of the variables used in the analysis through the SHAP method on the prediction, the most important factor was whether or not a water quality test was judged nonconforming in the previous water quality test. It was confirmed that the temperature on the day of the inspection and the altitude of the mineral spring had an influence on whether the water quality was unsuitable.

• Journal of Distribution Science
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• v.9 no.4
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• pp.5-13
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• 2011

This study provides analysis of the effectiveness of domestic marketing strategies of the Korean coffee shop "Caffe Bene". It bases its evaluation on statistical outputs of 'choice attributes,' "market segmentation," demographic characteristics," and "satisfaction differences." The results are summarized in four points. First, five choice attributes were extracted from factor analysis: price, atmosphere, comfort, taste, and location; these are related to coffee shop selection behavior. Based on these five factors, cluster analysis was conducted, with statistical results classifying customers into three major groups: atmosphere oriented; comfort oriented; and taste oriented. Second, discriminant analysis tested cluster analysis and showed two discriminant functions: location and atmosphere. Third, cross-tabulation analysis based on demographic characteristics showed distinctive demographic characteristics within the three groups. Atmosphere oriented group, early-20s, as women of all ages was found to be 'walking down the street 'and 'through acquaintances' in many cases, as the cognitive path, and mostly found the store through 'outdoor advertising', and 'introduction'. Comfort oriented group was mainly women who are students in their early twenties or professionals, and appeared as a group to be very loyal because of high recommendation to other customers compared to other groups. Taste oriented group, unlike the other group, was mainly late-20s' college graduates, and was confirmed, as low loyalty, with lower recommendation activity. Fourth, to analyze satisfaction differences, one-way ANOVA was conducted. It shows that groups which show high satisfaction in the five main factors also show high menu satisfaction and high overall satisfaction. This results show that segmented marketing strategies are necessary because customers are considering price, atmosphere, comfort, taste, location when they choose coffee shop and demographics show different attributes based on segmented groups. For example, atmosphere oriented group is satisfied with shop interior and comfort while dissatisfied with price because most of the customers in this group are early 20s and do not have great financial capability. Thus, price discounting marketing strategies based on individual situations through CRM system is critical. Comfort oriented group shows high satisfaction level about location and shop comfort. Also, in this group, there are many early 20s female customers, students, and self-employed people. This group customers show high word of mouth tendency, hence providing positive brand image to the customers would be important. In case of taste oriented group, while the scores of taste and location are high, word of mouth score is low. This group is mainly composed of educated and professional many late 20s customers, therefore, menu differentiation, increasing quality of coffee taste and price discrimination is critical to increase customers' satisfaction. However, it is hard to generalize the results of study to other coffee shop brand, because this study have researched only one domestic coffee shop, Caffe Bene. Thus if future study expand the scope of locations, brands, and occupations, the results of the study would provide more generalizable results. Finally, research of customer satisfactions of menu, trust, loyalty, and switching cost would be critical in the future study.