• Journal of Wetlands Research
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• v.22 no.1
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• pp.15-23
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• 2020

The purpose of this study is to investigate how the degree of distribution influences the calibration of snow and runoff in distributed hydrological models using a multi-criteria calibration method. The Hydrology Laboratory-Research Distributed Hydrologic Model (HL-RDHM) developed by NOAA-National Weather Service (NWS) is employed to estimate optimized parameter sets. We have 3 scenarios depended on the model complexity for estimating best parameter sets: Lumped, Semi-Distributed, and Fully-Distributed. For the case study, the Durango River Basin, Colorado is selected as a study basin to consider both snow and water balance components. This study basin is in the mountainous western U.S. area and consists of 108 Hydrologic Rainfall Analysis Project (HRAP) grid cells. 5 and 13 parameters of snow and water balance models are calibrated with the Multi-Objective Shuffled Complex Evolution Metropolis (MOSCEM) algorithm. Model calibration and validation are conducted on 4km HRAP grids with 5 years (2001-2005) meteorological data and observations. Through case study, we show that snow and streamflow simulations are improved with multiple criteria calibrations without considering model complexity. In particular, we confirm that semi- and fully distributed models are better performances than those of lumped model. In case of lumped model, the Root Mean Square Error (RMSE) values improve by 35% on snow average and 42% on runoff from a priori parameter set through multi-criteria calibrations. On the other hand, the RMSE values are improved by 40% and 43% for snow and runoff on semi- and fully-distributed models.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.1
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• pp.71-82
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• 2020

The existing transportation system, which is based on internal combustion engines, is rapidly being converted to electrification. Thus, eco-friendly public transportation with high transportation efficiency will continue to spread throughout the market in the near future. The purpose of this study is to compare and analyze the cognitive characteristics of passengers redgarding the technical and social factors of various public transportation means to help a successful introduction of eco-friendly public transit. Through a survey questionnaire (N=485), seven factors of seven transportation modes were evaluated and analyzed using principal component analysis. As a result, it is confirmed that potential passengers have high expectations for the eco-friendliness and city image of the eco-friendly buses. Also, it is confirmed that eco-friendly buses are superior in cleanliness and ride comfort than diesel buses. Given the study's results, this study identifies the cognitive characteristics of passengers regarding eco-friendly public transportation. We hope that these results will be used as basic information for image positioning and improved service with the use of eco-friendly transportation.

• Journal of Korean Society of Transportation
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• v.31 no.3
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• pp.86-95
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• 2013

In this study, a model of compensation and amendment of forecasted travel demand was developed to calculate the range of values depends on the changes in the risk factors, selecting factors that might affect traffic demand changes among risk factors. Selected factors are as follows: influenced area population, the number of registrated vehicle per person, ratio of service industry workers, and city intervals. Then this model is applied to six routes of expressway and the calculated value were compensated with error rate being reflected on each quartile value with respect to influenced area population (200,000 people standards). Result from appling developed model to Cheongwon-Sangju expressway suggests that the model could compensate the error rate by more than 50%, which in turn validate the effectiveness of the model developed. Some limitations and future research agenda have also been identified.

• Journal of Korean Tunnelling and Underground Space Association
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• v.19 no.6
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• pp.1029-1044
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• 2017

The Discrete Element Method (DEM) is one of the useful numerical methods to analyze the behavior of the ground formation by computing the motion and interaction using particles. The DEM has not been applied in civil engineering but also a wide range of industrial fields, such as chemical engineering, pharmacy, material science, food engineering, etc. In this study, to review a performance of the spoke-type earth pressure balance (EPB) shield TBM (Tunnel Boring Machine), the commercial software based on the DEM technology was used. An analysis of the TBM during excavation was conducted according to two pre-defined excavation conditions with the different rotation speed of a cutterhead. During the analysis, the resistant torque at the face of the cutterhead, the compressive force at the cutterhead and shield surface, the muck discharge at the screw auger were measured and compared. Upon the two kinds of excavation conditions, the applicability of the DEM analysis was reviewed as a modelling method for the TBM.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.10
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• pp.345-352
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• 2022

Recent LiDAR(Light Detection And Ranging) sensor is used for scanning object around in real-time. This sensor can detect movement of the object and how it has changed. As the production cost of the sensors has been decreased, LiDAR begins to be used for various industries such as facility guard, smart city and self-driving car. However, LiDAR has a large input data size due to its real-time scanning process. So another way for processing a large amount of data are needed in LiDAR system because it can cause a bottleneck. This paper proposes edge computing to compress massive point cloud for processing quickly. Since laser's reflection range of LiDAR sensor is limited, multiple LiDAR should be used to scan a large area. In this reason multiple LiDAR sensor's data should be processed at once to detect or recognize object in real-time. Edge computer compress point cloud efficiently to accelerate data processing and decompress every data in the main cloud in real-time. In this way user can control LiDAR sensor in the main system without any bottleneck. The system we suggest solves the bottleneck which was problem on the cloud based method by applying edge computing service.

• Journal of the Korean Association of Geographic Information Studies
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• v.24 no.4
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• pp.148-163
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• 2021

The diversification of the New Deal urban regeneration projects, that started in 2017 in accordance with the "Special Act on Urban Regeneration Activation and Support", generated the increased demand for the accuracy of data-driven diagnosis and project type forecast. Thus, this research was conducted to develop an application model able to identify the most appropriate New Deal project type for "eup", "myeon" and "dong" across the country. Data for application model development were collected through Statistical geographic information service(SGIS) and the 'Urban Regeneration Comprehensive Information Open System' of the Urban Regeneration Information System, and data for the analysis model was constructed through data pre-processing. Four models were derived and simulations were performed through polynomial regression analysis and multinomial logistic regression analysis for the application of the appropriate New Deal project type. I verified the applicability and validity of the four models by the comparative analysis of spatial distribution of the previously selected New Deal projects by targeting the sites located in Seoul by each model and the result showed that the DI-54 model had the highest concordance rate.

• The Journal of the Convergence on Culture Technology
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• v.8 no.6
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• pp.819-829
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• 2022

Professional baseball is one of the spectator sports that has been loved for a long time by the citizens as a recreational activity since its establishment in 1982, and has been playing pivotal role as a national sport. However, there has been decline in the number of audiences since 2019. Hence, this research paper aimed to provide strategic direction for planning and improvement of professional baseball stadiums by applying the concept of servicescape. In this research, five key factors of servicescape that affects players performance and the level of immersion of spectators were derived through literature review, and based on these key factors, case study analysis were carried out for 51 domestic and foreign baseball stadiums while focusing on the factors derived. Domestic baseball stadiums highly concentrate on spectatorship without effectively responding to change in spectators demand and its effective use of space rather than baseball games. As in foreign cases, it is critical to modify mangement process and planning direction, and improve policies while perceiving baseball stadium as recreational and cultural space.

• Journal of Distribution Research
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• v.17 no.4
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• pp.1-27
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• 2012

Conceptualization of store image have been suggested in the past by many marketing scholars. The dominant perspective about store image is treated as the results of a multi-attribute model. Store image is expressed as a function of the salient attributes of a particular store that are evaluated. Though, there is a little confusions about what elements compose the store image, most scholars agree that merchandise, service, atmosphere, physical facilities, comfort, and location are generally accepted elements as store image. A considerable researches support that shopping can provide both hedonic and utilitarian value. Hedonic shopping value reflects the value received from fantasy and emotive aspects of shopping experience, while utilitarian shopping value reflects the acquisition of products. These two types of shopping value can affect shopping satisfaction. This study examines the relationships among stores images(store atmosphere, salespeople services, facilities, product assortment, and store location), shopping values(utilitarian shopping value and hedonic shopping value), and shopping satisfaction based on discount stores (E-Mart, Home plus, and Lotte Mart). The author hypothesized that five store image components affect shopping values, and these shopping values affect shopping satisfaction. The author focused on the roles of perceived retail crowding between these relationships. Specifically, the author hypothesized that perceived retailing crowding moderated the relationship between shopping values and shopping satisfaction. The author also hypothesized the direct effect of perceived retail crowding on shopping satisfaction. Finally, the author hypothesized that five store image components affect directly shopping satisfaction. Research model is presented in