• 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.

• Asia pacific journal of information systems
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• v.22 no.4
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• pp.7-29
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• 2012

Smartphone and its applications (i.e. apps) are increasingly penetrating consumer markets. According to a recent report from Korea Communications Commission, nearly 50% of mobile subscribers in South Korea are smartphone users that accounts for over 25 million people. In particular, the importance of smartphone has risen as a geospatially-aware device that provides various location-based services (LBS) equipped with GPS capability. The popular LBS include map and navigation, traffic and transportation updates, shopping and coupon services, and location-sensitive social network services. Overall, the emerging location-based smartphone apps (LBA) offer significant value by providing greater connectivity, personalization, and information and entertainment in a location-specific context. Conversely, the rapid growth of LBA and their benefits have been accompanied by concerns over the collection and dissemination of individual users' personal information through ongoing tracking of their location, identity, preferences, and social behaviors. The majority of LBA users tend to agree and consent to the LBA provider's terms and privacy policy on use of location data to get the immediate services. This tendency further increases the potential risks of unprotected exposure of personal information and serious invasion and breaches of individual privacy. To address the complex issues surrounding LBA particularly from the user's behavioral perspective, this study applied the privacy calculus model (PCM) to explore the factors that influence the adoption of LBA. According to PCM, consumers are engaged in a dynamic adjustment process in which privacy risks are weighted against benefits of information disclosure. Consistent with the principal notion of PCM, we investigated how individual users make a risk-benefit assessment under which personalized service and locatability act as benefit-side factors and information privacy risks act as a risk-side factor accompanying LBA adoption. In addition, we consider the moderating role of trust on the service providers in the prohibiting effects of privacy risks on user intention to adopt LBA. Further we include perceived ease of use and usefulness as additional constructs to examine whether the technology acceptance model (TAM) can be applied in the context of LBA adoption. The research model with ten (10) hypotheses was tested using data gathered from 98 respondents through a quasi-experimental survey method. During the survey, each participant was asked to navigate the website where the experimental simulation of a LBA allows the participant to purchase time-and-location sensitive discounted tickets for nearby stores. Structural equations modeling using partial least square validated the instrument and the proposed model. The results showed that six (6) out of ten (10) hypotheses were supported. On the subject of the core PCM, H2 (locatability ${\rightarrow}$ intention to use LBA) and H3 (privacy risks ${\rightarrow}$ intention to use LBA) were supported, while H1 (personalization ${\rightarrow}$ intention to use LBA) was not supported. Further, we could not any interaction effects (personalization X privacy risks, H4 & locatability X privacy risks, H5) on the intention to use LBA. In terms of privacy risks and trust, as mentioned above we found the significant negative influence from privacy risks on intention to use (H3), but positive influence from trust, which supported H6 (trust ${\rightarrow}$ intention to use LBA). The moderating effect of trust on the negative relationship between privacy risks and intention to use LBA was tested and confirmed by supporting H7 (privacy risks X trust ${\rightarrow}$ intention to use LBA). The two hypotheses regarding to the TAM, including H8 (perceived ease of use ${\rightarrow}$ perceived usefulness) and H9 (perceived ease of use ${\rightarrow}$ intention to use LBA) were supported; however, H10 (perceived effectiveness ${\rightarrow}$ intention to use LBA) was not supported. Results of this study offer the following key findings and implications. First the application of PCM was found to be a good analysis framework in the context of LBA adoption. Many of the hypotheses in the model were confirmed and the high value of $R^2$ (i.,e., 51%) indicated a good fit of the model. In particular, locatability and privacy risks are found to be the appropriate PCM-based antecedent variables. Second, the existence of moderating effect of trust on service provider suggests that the same marginal change in the level of privacy risks may differentially influence the intention to use LBA. That is, while the privacy risks increasingly become important social issues and will negatively influence the intention to use LBA, it is critical for LBA providers to build consumer trust and confidence to successfully mitigate this negative impact. Lastly, we could not find sufficient evidence that the intention to use LBA is influenced by perceived usefulness, which has been very well supported in most previous TAM research. This may suggest that more future research should examine the validity of applying TAM and further extend or modify it in the context of LBA or other similar smartphone apps.

• The Korean Journal of Quaternary Research
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• v.21 no.1
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• pp.27-36
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• 2007

The severe damage of cultural heritages induced by natural hazards like heavy rain has been dramatically increased since 1990. The number of the repair works of stone heritage of 2005 was six times as many as those of 1986 year. Especially the ratio of the repair works of Gyeongsang Province and Jeolla Province stood 63% of those of all over the country. Since 1990, the typhoons usually struck the southern part of Korea and went northward. The heavy damage of stone heritages in two provinces was caused by them. We made a preliminary survey the stone heritages that exposed to the natural hazards on the basis of repair works of them and a field survey. The analysis results indicate that the natural hazards such as landslide and soil disaster of the stone heritages related to a sloping surface stood 58% of all kind of natural hazards. The reasons are caused by the 59 % of all the stone heritages distributed in a sloping surface resulted in natural hazards like landslide and soil disaster. The bases of stone heritages can be easily eroded by the surface water with high energy induced by heavy rainfall. Most of the stone heritages like Maebul were engraved on a natural rock wall(outcrop). But some of them engraved on rolling stones are very vulnerable in a change of a base condition caused by erosion and ground subsidence and they can be tilted or fell down. The distribution of the stone heritages vulnerable in natural hazard is related to that of the rainfall distribution compounded five typhoons after 1990. Most of them are included in level two on the rainfall distribution map except those of Taean peninsula and some of Gyeonggi Province. They seem to be rather related to the rainfall distribution of the Typhoon Olga.

• Korean Journal of Heritage: History & Science
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• v.51 no.2
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• pp.138-153
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• 2018

The purpose of this study was to analyze , which was made in the late Joseon Dynasty to specify the vegetation landscape of the Donhwamun Gate area in Changdeokgung Palace. The study results can be summarized as below. First, based on "Jieziyuan Huazhuan(芥子園畵傳)", the introductory book of tree expression delivered from China in the 17th century, allowed the classification criteria of the trees described in the picture to be established and helped identify their types. As a result of the classification, there were 10 species and 50 trees in the Donhwamun Gate area of . Second, it was possible to measure the real size of the trees described in the picture through the elevated drawing scale of . The height of the trees ranged from a minimum of 4.37 m to a maximum of 22.37 m. According to the measurement results, compared to the old trees currently living in Changdeokgung Palace, the trees described in the picture were found to be produced in almost actual size without exaggeration. Thus, the measured height of the trees turned out to be appropriate as baseline data for reproduction of the vegetation landscape. Third, through the Rubber Sheeting Transformation of , it was possible to make a ground plan for the planting of on the current digital topographic map. In particular, as the transformed area of was departmentalized and control points were added, the precision of transformation improved. It was possible to grasp the changed position of planting as well as the change in planting density through a ground plan of planting of . Lastly, it was possible to produce a three-dimensional vegetation landscape model by using the information of the shape of the trees and the ground plan for the planting of . Based on the three-dimensional model, it was easy to examine the characteristics of the three-dimensional view of the current vegetation via the view axis, skyline, and openness to and cover from the adjacent regions at the level of the eyes. This study is differentiated from others in that it verified the realism of and suggested the possibility of ascertaining the original form of the vegetation landscape described in the painting.

• Korean Journal of Remote Sensing
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• v.39 no.5_3
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• pp.1009-1029
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• 2023

Urban trees play a vital role in urban ecosystems,significantly reducing impervious surfaces and impacting carbon cycling within the city. Although previous research has demonstrated the efficacy of employing artificial intelligence in conjunction with airborne light detection and ranging (LiDAR) data to generate urban tree information, the availability and cost constraints associated with LiDAR data pose limitations. Consequently, this study employed freely accessible, high-resolution multispectral satellite imagery (i.e., Sentinel-2 data) to estimate fractional tree canopy cover (FTC) within the urban confines of Suwon, South Korea, employing machine learning techniques. This study leveraged a median composite image derived from a time series of Sentinel-2 images. In order to account for the diverse land cover found in urban areas, the model incorporated three types of input variables: average (mean) and standard deviation (std) values within a 30-meter grid from 10 m resolution of optical indices from Sentinel-2, and fractional coverage for distinct land cover classes within 30 m grids from the existing level 3 land cover map. Four schemes with different combinations of input variables were compared. Notably, when all three factors (i.e., mean, std, and fractional cover) were used to consider the variation of landcover in urban areas(Scheme 4, S4), the machine learning model exhibited improved performance compared to using only the mean of optical indices (Scheme 1). Of the various models proposed, the random forest (RF) model with S4 demonstrated the most remarkable performance, achieving R² of 0.8196, and mean absolute error (MAE) of 0.0749, and a root mean squared error (RMSE) of 0.1022. The std variable exhibited the highest impact on model outputs within the heterogeneous land covers based on the variable importance analysis. This trained RF model with S4 was then applied to the entire Suwon region, consistently delivering robust results with an R² of 0.8702, MAE of 0.0873, and RMSE of 0.1335. The FTC estimation method developed in this study is expected to offer advantages for application in various regions, providing fundamental data for a better understanding of carbon dynamics in urban ecosystems in the future.

• Journal of Global Scholars of Marketing Science
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• v.19 no.2
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• pp.17-26
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• 2009

As the lifestyle of consumers changes and the need for various products increases, new products are being developed in the market. Each household owns various home appliances which are purchased through the choice of a decision maker. These appliances include not only large-sized products such as TV, refrigerator, and washing machine, but also small-sized products such as microwave oven and air cleaner. There exists latent correlation among possession of home appliances, even though they are purchased independently. The purpose of this research is to analyze the effect of demographic factors on the purchase and possession of each home appliances, and to derive some relationships among various appliances. To achieve this purpose, the present status on the possession of each home appliances are investigated through consumer survey data on the electric and energy product. And a multivariate probit(MVP) model is applied for the empirical analysis. From the estimation results, some appliances show a substitutive or complementary pattern as expected, while others which look apparently unrelated have correlation by co-incidence. This research has several advantages compared to previous literatures on home appliances. First, this research focuses on the various products which are purchased by each household, while previous researches such as Matsukawa and Ito(1998) and Yoon(2007) focus just on a particular product. Second, the methodology of this research can consider a choice process of each product and correlation among products simultaneously. Lastly, this research can analyze not only a substitutive or complementary relationship in the same category, but also the correlation among products in the different categories. As the data on the possession of home appliances in each household has a characteristic of multiple choice, not a single choice, a MVP model are used for the empirical analysis. A MVP model is derived from a random utility model, and has an advantage compared to a multinomial logit model in that correlation among error terms can be derive(Manchanda et al., 1999; Edwards and Allenby, 2003). It is assumed that the error term has a normal distribution with zero mean and variance-covariance matrix ${\Omega}$. Hence, the sign and value of correlation coefficients means the relationship between two alternatives(Manchanda et al., 1999). This research uses the data of 'TEMEP Household ICT/Energy Survey (THIES) 2008' which is conducted by Technology Management, Economics and Policy Program in Seoul National University. The empirical analysis of this research is accomplished in two steps. First, a MVP model with demographic variables is estimated to analyze the effect of the characteristics of household on the purchase of each home appliances. In this research, some variables such as education level, region, size of family, average income, type of house are considered. Second, a MVP model excluding demographic variables is estimated to analyze the correlation among each home appliances. According to the estimation results of variance-covariance matrix, each households tend to own some appliances such as washing machine-refrigerator-cleaner-microwave oven, and air conditioner-dish washer-washing machine and so on. On the other hand, several products such as analog braun tube TV-digital braun tube TV and desktop PC-portable PC show a substitutive pattern. Lastly, the correlation map of home appliances are derived using multi-dimensional scaling(MDS) method based on the result of variance-covariance matrix. This research can provide significant implications for the firm's marketing strategies such as bundling, pricing, display and so on. In addition, this research can provide significant information for the development of convergence products and related technologies. A convergence product can decrease its market uncertainty, if two products which consumers tend to purchase together are integrated into it. The results of this research are more meaningful because it is based on the possession status of each household through the survey data.

• Communications of Mathematical Education
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• v.25 no.1
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• pp.99-118
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• 2011

For this case study of gifted education, two classrooms in two locations, show life in general of the gifted educational system. And for this case study the identity of teachers and the gifted, help to activate the mathematically gifted education for these research questions, which are as followed: Firstly, how is the gifted education classroom life? Secondly, what kind of identity do the teachers and gifted students bring to mathematics, mathematics teaching and mathematics learning? Being selected in the gifted children's education center solves the research problem of characteristic and approach. Backed by the condition and the permission possibility, 2 selected classes and 2 people, which are coming and going. Gifted education classroom life, the identity of teachers and gifted students in mathematics and mathematics teaching and mathematic learning. It will be for 3 months, with various recordings and vocal instruction between teacher and students. Collected observations and interviews will be analyzed over the course of instruction. The results analyzed include, social participation, structure, and the formation of the gifted education classroom life. The organization of classes were analyzed by the classes conscious levels to collect and retain data. The classes verification levels depended on the program's first class incentive, teaching and learning levels and understanding of gifted math. A performance assessment will be applied after the final lesson and a consultation with parents and students after the final class. The six kinds of social participation structure come out of the type of the most important roles in gifted education accounts, for these types of group discussions and interactions, students must have an interaction or individual activity that students can use, such as a work product through the real materials, which release teachers and other students for that type of questions to evaluate. In order for the development of meaningful mathematical concepts to formulate, mathematical principles require problem solving among all students, which will appear in the resolution or it will be impossible to map the meaning of the instruction from which it was formed. These results show the analysis of the mathematics, mathematics teaching, mathematics learning and about the identity of the teachers and gifted. Gifted education teachers are defined by gifted math, which is more difficult and requires more differentiated learning, suitable for gifted students. Gifted was defined when higher level math was created and challenged students to deeper thinking. Gifted students think that gifted math is creative learning and they are forward or passive to one-way according to the education atmosphere.

• Journal of Korean Society for Geospatial Information Science
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• v.18 no.1
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• pp.21-29
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• 2010

Nakdong Estuary Delta plays various roles of worldwide habitat for migratory birds and a sand supplier to Haewoondae Beach and Gwanganri, which are tourist attractions of Busan. In this study, long-term topographical changes of Nakdong Estuary (Jinwoo Islet, Sinja Islet, Doyodeung, Dadae Beach) coast were detected and interpreted. Through the analysis of 34 years' satellite images, it was found out that a part in between front side and back side of Jinwoo Islet increased, Sinja Islet was divided into two belts in 1970, and has formed an islet since the 1980s and extended westward. Due to the rapid development of small islets in front of Baekhabdeung since 1990s, Doyodeung formed in the late 1990s and is still growing. To make coastal map of Nakdong Estuary area, 13 images, of which the tide level was $99{\pm}13cm$, from the 112 Landsat images of the period from 1975 to 2009 were selected to section into water zone and land zone using NDV. And the rates of coastal line change such as MATLAB EPR(End Point Rate) and LRR(Linear Regression Rate) were calculated using DSAS 4.0(Digital Shoreline Analysis System). Through detecting topographical changes, EPR showed that the front(south) and back side(north) of Jinwoo Islet moved southward at -0.93~2.56m/yr, and changes in costal line and area of Jinwoo Islet were low and stable. The front and backside of Sinja Islet moved northward at 1~4m/yr, whereas the west side of Sinja Islet was stable at 2~3m/yr and east side of Sinja Islet moved northward at 10m/yr or faster. The front and back side of Doyodeung moved northward at 18~27m/yr, causing the increase of area, while the coastal line of Dadae Beach moved westward at 7m/yr, causing the expansion of the beach. LRR also demonstrated a similar trend to EPR. Although analysis of satellite images and GIS could enabled detection of topographical changes and quantitative analysis of natural phenomena, we found that continuous observation of natural phenomena and various analytical methods are required.

• Current Research on Agriculture and Life Sciences
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• v.29
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• pp.83-89
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• 2011

Various functional and useful components in Portulaca oleracea were extracted with ethanol and the optimum solvent conditions were set by monitoring of response surface methodology(RSM). A central composite design for optimization was applied to investigate the effects of the three independent variables of extraction temperature, ethanol concentration, and extraction time, on dependent variables including total phenolics, electron-donating ability, brown clolor and total flavonoids of Portulaca oleracea. The content of total phenol was essentially unaffected by extraction time or extraction temperature, but it was highly influenced by ethanol concentration. The maximum total phenol content was 31.70mg/mL obtained at 45.84% of ethanol concentration, $79.66^{\circ}C$, and after 2.67hr of extraction. Electron-donating ability (EDA) was affected by ethanol concentration and the maximum EDA was 74.67mg/mL at 52.95% ethanol concentration, $52.33^{\circ}C$ and 4.84hr of extration time. The browning color was rarely affected by extraction time but, it was highly influenced by ethanol concentration and extraction temperature. The maximum extent of browning color was obtained at 97.75% of ethanol concentraion, $65.88^{\circ}C$ and 2.93hr of extraction time. The content of total flavonoid was significantly influenced by extraction time, and the maximum total flavonoid level was 58.28mg/mL obtained at 96.62% ethanol concentration, $61.87^{\circ}C$ after 3.70hr of extraction. As a result, The optimal conditions for effective extraction were predicted as follows, 70.3% of ethanol concentration, $62.1^{\circ}C$ of extraction temperature and 3.3hr of extraction time.

• Journal of the Korean Institute of Landscape Architecture
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• v.36 no.3
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• pp.9-20
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• 2008

The government is planning to link a small park with the soon to be ready subway line 9 as a part of Seoul's policy, "The standard or plan for making a water-friendly space by water use" (2007). However, the specified concepts and instructions of the small parks need further work. Therefore, the policy is expected to expand to neighboring small parks near the subway station, but these are not supported by research or data which suggests the needs or actual user behavior and utilization of small parks. our country added the specified concept of small parks and theme parks to the classification of urban parks in the Urban Park Act Revision (2005.3.31), but the concept of small parks is not clearly settled in the law in the scopes of its function, scale, promotion nor particularly defined plans for small park projects. This study examines as small park near a subway station. The characteristics of there region and users vary from the characteristics of the station and region. In the "directions for concrete standards under the types of urban parks and green zones" (2007.2) the types of small parks are classified by "regional characteristics" and "user characteristics". Therefore, this study classifies the subject of neighboring small parks near subway stations as the neighborhood and small urban parks according to the Urban Park Act. The study was paralleled with observation and questionnaires on the analysis of the neighborhood and small urban parks. The actual conditions of park utilization and user behavioral characteristics were deducted by observation, while the questionnaire determined actual user utilization, importance and satisfaction level as well as the small park environment. This study largely focused on three aspects: park facility, design of this sentence isn't even complete. The second aspect isn't finished and the third isn't here.