• Journal of Climate Change Research
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• v.7 no.3
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• pp.289-297
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• 2016

In this study, we researched the emission source category and it was calculated emissions estimates from existing research or literature review related to port. In addition, we have created the basis for a policy that can reduce greenhouse gas emissions calculation based on the results of the harbor. Greenhouse gas emissions estimation results, we proposed a method for allocating the GIS space. In this study, we confirmed based on the calculated greenhouse gas emissions by sources resulting in the GIS Map Port result of the expression construct for space allocation. Based on these results, it tries to provide the basic data that can be used when you want to create a local government measures to reduce scenario in the future.

• The Korean Journal of Franchise Management
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• v.13 no.1
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• pp.19-33
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• 2022

Purpose: Based on the resource-based view and the competitive advantage theory, the study views marketing capabilities (product, pricing, delivery/inventory, and promotional support) as sources of competitive advantage (differentiation advantage and low-cost advantage) and examines their impacts on competitive advantage, which in turn, will influence non-business and business performance. Research design, data and methodology: Data were collected from 149 representatives of franchising companies in South Korea and analyzed with SmartPLS 3.3.7. Results: First, promotional support and product have a significant impact on differentiation advantage. Second, pricing and promotional support have a significant impact on low-cost advantage. Third, differentiation advantage has an influence on non-financial and financial business performance. Fourth, low-cost advantage has an impact on non-financial performance but has no significant direct impact on financial performance. Fifth, non-financial performance is related to financial performance. Finally, the result of IPMA shows that importance and performance values of exogeneous variables are different depending on firm size. Conclusions: The findings suggest that franchisors should focus on different marketing capabilities depending on their strategic focus and objectives. Finally, the findings based on an IPMA suggest that small companies perceive low-cost advantage as important, while their counterparts do not. Several theoretical and managerial implications are offered.

• Nuclear Engineering and Technology
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• v.54 no.3
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• pp.826-833
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• 2022

A two-phase natural circulation test using SMART integral test loop (SMART-ITL) was conducted to explore thermo-hydraulic phenomena of two-phase natural circulation in the SMART reactor. Specifically, the test examined the natural circulation in the primary loop under a stepwise coolant inventory loss while keeping the core power constant at 5% of the scaled full power. Based on the test results, three flow regimes were observed: single-phase natural circulation (SPNC), two-phase natural circulation (TPNC), and boiler-condenser natural circulation (BCNC). The flow rate remained steady in the SPNC, slightly increased in the TPNC, and dropped abruptly and maintained in the BCNC. Using a natural circulation flow map, the natural circulation characteristic in the SMART-ITL was compared with those in pressurized water reactor simulators. In the SMART-ITL, a BCNC regime appeared instead of siphon condensation and reflux condensation regimes because of the use of once-through steam generators.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.484-484
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• 2021

본 연구를 통해 개발된 웹기반 가뭄아틀라스에 탑재되는 가뭄인벤토리 지도서비스 모듈은 GIS기반 가뭄상황관리를 위해 일정 수준의 가공이 필요한 다양한 GIS 가뭄분석정보를 제공하여 가뭄 대응 업무 담당자가 공간에 기반한 가뭄분석 업무에 사용함을 주목적으로 해당 서비스 모듈을 개발하였다. 본 연구를 통해 개발된 지도서비스 모듈은 JAVA 언어로 개발되었으며, 오픈소스 기반의 Geosever와 Openlayer를 적용하여 167개 시군을 대상으로 가뭄 관련 분석지도를 제공하는 서비스 모듈이다. 지도 레이어별 가시화를 통한 중첩분석이 가능하며, 사용자 필요 시 해당 분석지도를 다운로드 받을 수 있도록 개발을 진행하였다. 상세 제공 정보로는 가뭄 분석을 위한 면적정보와 통계정보로 이원화하여 서비스를 제공하며, 개별 가뭄인벤토리 지도는 지역별 차트정보와 속성DB 테이블을 같이 지도화면에 표출한다. 주요기능으로는 가뭄인벤토리 지도서비스 창을 활성화하여 사용자가 필요한 가뭄인벤토리 지도를 체크하면 가뭄아틀라스 지도화면에 가시화된다. 체크된 가뭄인벤토리 지도는 테이블정보 표출과 자료 다운로드 기능을 제공한다. 해당 서비스 모듈의 관리 및 사용 방법으로는 가뭄인벤토리 지도데이터를 GIS 데이터셋화하여 Geoserver에 로딩하며, 로딩된 지도데이터는 WMS(web tilemap service) 포맷으로 변환한 뒤, 각각의 분석지도가 가지고 있는 속성DB정보를 고려해 지도 스타일을 적용하였다. 웹 브라우저 표출방법으로는 Openlayer 기반으로 GeoWebCache를 생성해 가뭄인벤토리 지도를 웹기반 가뭄아틀라스 상에 표출한다.

• Geomechanics and Engineering
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• v.37 no.2
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• pp.135-147
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• 2024

A GIS-based landslide susceptibility mapping (LSM) was carried out using frequency ratio (FR), modified frequency ratio (M-FR), analytic hierarchy process (AHP), and modified analytic hierarchy process (M-AHP) methods to identify and delineate the potential failure zones along the Halong - Vandon expressway. The thematic layers of various landslide causative factors were generated for modeling in GIS, including geology, rainfall, distance to fault, distance to road, slope, aspect, landuse, density of landslide, vertical relief, and horizontal relief. In addition, a landslide inventory along the road network was prepared using data provided by the management department during the course of construction and operation from 2017 to 2019, when many landslides were documented. The validation results showed that the M-FR method had the highest AUC value (AUC = 0.971), which was followed by the FR method with AUC = 0.961. The AUC values were 0.939 and 0.892 for the M-AHP and AHP methods, respectively. The generated LSM obtained from M-FR method classified the study area into five susceptibility classes: very low (0), low (0-1), moderate (1-2), high (2-3), and very high (3-4) classes, which could be useful for various stakeholders like planners, engineers, designers, and local public for future construction and maintenance in the study area.

• Geomechanics and Engineering
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• v.36 no.5
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• pp.441-453
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• 2024

Sinkhole subsidence and collapse is a common geohazard often formed in karst areas such as the state of Florida, United States of America. To predict the sinkhole occurrence, we need to understand the formation mechanism of sinkhole and its karst hydrogeology. For this purpose, investigating the factors affecting sinkholes is an essential and important step. The main objectives of the presenting study are (1) the development of a machine learning (ML)-based model, namely C5.0 decision tree (C5.0 DT), for the prediction of sinkhole susceptibility, which accounts for sinkhole/subsidence inventory and sinkhole contributing factors (e.g., geological/hydrogeological) and (2) the construction of a regional-scale sinkhole susceptibility map. The study area is east central Florida (ECF) where a cover-collapse type is commonly reported. The C5.0 DT algorithm was used to account for twelve (12) identified hydrogeological factors. In this study, a total of 1,113 sinkholes in ECF were identified and the dataset was then randomly divided into 70% and 30% subsets for training and testing, respectively. The performance of the sinkhole susceptibility model was evaluated using a receiver operating characteristic (ROC) curve, particularly the area under the curve (AUC). The C5.0 model showed a high prediction accuracy of 83.52%. It is concluded that a decision tree is a promising tool and classifier for spatial prediction of karst sinkholes and subsidence in the ECF area.

• Journal of Climate Change Research
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• v.4 no.2
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• pp.177-188
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• 2013

In this research, forest cover distribution change, forest volume and carbon stock in Yongin-city, Gyeonggi procince were estimated focused on the forest of Yongin-City using forest type map and HyTAG model in relation to climate change. Present forest volume of Yongin-city was estimated using the data from $5^{th}$ Forest Type Map and Korean National Forest Inventory (NFI). And for the future 100 years potential forest distribution by 10-year interval were estimated using HyTAG model. Forest volume was also calculated using algebraic differences form of the growth model. According to the $5^{th}$ Forest Type Map, present needleleaf forest occupied 37.8% and broadleaf forest 62.2% of forest area. And the forest cover distribution after 30 years would be changed to 0.13% of needleleaf forest and 99.97% of broadleaf forest. Finally, 60 years later, whole forest of Yongin-city would be covered by broad-leaf forest. Also the current forest carbon stocks was measured 1,773,862 tC(56.79 tC/ha) and future carbon stocks after 50 years was predicted to 4,432,351 tC(141.90 tC/ha) by HyTAG model. The carbon stocks after 100 years later was 6,884,063 tC (220.40 tC/ha). According to the HyTAG model prediction, Pinus koraiensis, Larix kaempferi, Pinus rigida, and Pinus densiflora are not suitable to the future climate of 10-year, 30-year, 30-year, and 50-year later respectively. All Quercus spp. was predicted to be suitable to the future climate.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.25 no.4
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• pp.49-65
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• 2022

Since trees in the city are green assets that create a healthy environment for the city, systematic management of trees improves urban ecosystem services. The sporadic urban tree information centered on the site is vast, and it is difficult to manage the data, so efforts to increase efficiency are needed. This paper summarizes tree data inventory based on data constructed by Seoul Green Trust activists and constructs and discloses online database maps using Tableau Software. In order to verify the utilization of the map, we divided into consumer and supplier aspects to collect various opinions and reflect feedback to implement tree database maps for each area and species of Seoul Forest. As a result, the utilization value of tree database in urban parks was presented. The technical significance of this study is to systematically record the process of constructing and implementing a dashboard directly using the Mapbox platform and Tableau Software in the field of landscaping for the first time in Korea. In addition, the implications and supplements of landscape information were derived by collecting user opinions on the results. This can be used as an exploratory basis in the process of developing online-based services such as web and apps by utilizing landscaping tree information in the future. Although the visualization database currently constructed has limitations that ordinary users cannot interact in both directions because it utilizes business intelligence tools in terms of service provision it has affirmed both the database construction and its usability in web public format. In the future it is essential to investigate the assets of the trees in the city park and to build a database as a public asset of the city. The survey participants positively recognized that information is intuitively presented based on the map and responded that it is necessary to provide information on the overall urban assets such as small parks and roadside trees by using open source maps in the future.

• Korean Journal of Remote Sensing
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• v.31 no.5
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• pp.449-459
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• 2015

The conventional National Forest Inventory(NFI)-based forest carbon stock estimation method is suitable for national-scale estimation, but is not for regional-scale estimation due to the lack of NFI plots. In this study, for the purpose of regional-scale carbon stock estimation, we created grid-based forest carbon stock maps using spatial ancillary data and two types of up-scaling methods. Chungnam province was chosen to represent the study area and for which the $5^{th}$ NFI (2006~2009) data was collected. The first method (method 1) selects forest type map as ancillary data and uses regression model for forest carbon stock estimation, whereas the second method (method 2) uses satellite imagery and k-Nearest Neighbor(k-NN) algorithm. Additionally, in order to consider uncertainty effects, the final AGB carbon stock maps were generated by performing 200 iterative processes with Monte Carlo simulation. As a result, compared to the NFI-based estimation(21,136,911 tonC), the total carbon stock was over-estimated by method 1(22,948,151 tonC), but was under-estimated by method 2(19,750,315 tonC). In the paired T-test with 186 independent data, the average carbon stock estimation by the NFI-based method was statistically different from method2(p<0.01), but was not different from method1(p>0.01). In particular, by means of Monte Carlo simulation, it was found that the smoothing effect of k-NN algorithm and mis-registration error between NFI plots and satellite image can lead to large uncertainty in carbon stock estimation. Although method 1 was found suitable for carbon stock estimation of forest stands that feature heterogeneous trees in Korea, satellite-based method is still in demand to provide periodic estimates of un-investigated, large forest area. In these respects, future work will focus on spatial and temporal extent of study area and robust carbon stock estimation with various satellite images and estimation methods.

• 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.