• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 1999.10a
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• pp.73-81
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• 1999

Inchon Port is the second largest import-export port of Korea, and has the point ant issue such as the excessive logistics cost because of the limits of handing capacity and the chronic demurrage. There is few research activities on the analysis and improvement of the whole port operation, because Inchon Port not only has the dual dock system and various facilities but also handles a various kind of cargo. The purpose of this paper is to develop the simulation program as a long-term strategic support tool, considering the dual dock system and the TOC(terminal operation company) system executed from March, 1997 in Inchon Port. The basic input parameters such as arrival intervals, cargo tons, service rates are analyzed and the probability density function for this parameters are estimated. The main mechanism of simulation model is the discrete event-driven simulation and the next-event time advancing. The program is executed based on the knowledge base and database, and is constructed using VISUAL BASIC and ACCESS database. From the simulation model, it is possible to estimate the demurrage status through analyzing scenarios such as the variation of cargo ton and cargo handing level, the increase of service rate, and so on, and to establish the long-term port strategic plan.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1162-1164
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• 2003

The methods of the geometric reconstruction and sensor calibration of satellite linear pushbroom images are investigated. The model of the sensor used is based on the SPOT model that is developed by Kraiky. The satellite trajectory is a Keplerian trajectory in the approximation. Four orbit parameters, longitude of the ascending node(${\omega}$), inclination of the orbit plan(I), latitude argument of the satellite(W) and distance between earth center and satellite, are used for the camera modeling. Time-dependent orbit parameters are expressed by quadratic polynomials. SPOT-5 images have been used for validation tests. The results are that the RMSE acquired from 20 GCPs is 1.763m and the RMSE of 5 checking points 2.470m. Because the ground resolution of SPOT-5 is 2.5m, the result obtained in this study has a good accuracy. It demonstrates that the sensor model developed by this study can be used to reconstruct the geometry of satellite image using pushbroom camera.

• Proceedings of the Korea Society for Simulation Conference
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• 2003.11a
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• pp.3-10
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• 2003

Developments in science and technology based on computer technology influenced military fields and created up-to-date weapons and equipment, and as a result, which is changing the war accomplishing methods of the future warfare. Due to these changes in the war accomplishing methods, the army command centers are requested to make changes in their decision-making process. In other words, they need to apply more scientific methods rather than just build a scheme by the mere analysis of commanders and the staffs as in the past. Consequently, we propose a model, Vision 21 we developed as a war game model for division-size unit analysis use, in the COA development process, which is the most important part in establishing the OPLAN for mission accomplishment. Vision 21, with a comparative analysis of the other COA built in the COA development process, can be applied to making the best COA. Model employment concept can let us choose the best COA, operating war games on condition that the COA of the opposite forces is fixed and ours sequentially opposed against, and with a comparative analysis also. Moreover, if the time available is limited, before establishing several courses, we can apply the COA to the process for making the best decision, analysing in stages or by main phases and not establishing several courses for a special purpose.

• Fashion & Textile Research Journal
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• v.23 no.4
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• pp.480-490
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• 2021

Sales forecasting is crucial for many retail operations. For apparel retailers, accurate sales forecast for the next season is critical to properly manage inventory and plan their supply chains. The challenge in this increases because apparel products are always new for the next season, have numerous variations, short life cycles, long lead times, and seasonal trends. In this study, a sales forecasting model is proposed for apparel products using machine learning techniques. The sales data pertaining to outerwear items for four years were collected from a Korean sports brand and filtered with outliers. Subsequently, the data were standardized by removing the effects of exogenous variables. The sales patterns of outerwear items were clustered by applying K-means clustering, and outerwear attributes associated with the specific sales-pattern type were determined by using a decision tree classifier. Six types of sales pattern clusters were derived and classified using a hybrid model of clustering and decision tree algorithm, and finally, the relationship between outerwear attributes and sales patterns was revealed. Each sales pattern can be used to predict stock-keeping-unit-level sales based on item attributes.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.4
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• pp.59-66
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• 2020

In this study, we consider the problem of forecasting the number of inbound foreigners visiting Korea. Forecasting tourism demand is an essential decision to plan related facilities and staffs, thus many studies have been carried out, mainly focusing on the number of inbound or outbound tourists. In order to forecast tourism demand, we use a seasonal ARIMA (SARIMA) model, as well as a SARIMAX model which additionally comprises an exogenous variable affecting the dependent variable, i.e., tourism demand. For constructing the forecasting model, we use a search procedure that can be used to determine the values of the orders of the SARIMA and SARIMAX. For the exogenous variable, we introduce factors that could cause the tourism demand reduction, such as the 9/11 attack, the SARS and MERS epidemic, and the deployment of THAAD. In this study, we propose a procedure, called Measuring Impact on Demand (MID), where the impact of each factor on tourism demand is measured and the value of the exogenous variable corresponding to the factor is determined based on the measurement. To show the performance of the proposed forecasting method, an empirical analysis was conducted where the monthly number of foreign visitors in 2019 were forecasted. It was shown that the proposed method can find more accurate forecasts than other benchmarks in terms of the mean absolute percentage error (MAPE).

• Journal of the Architectural Institute of Korea Planning & Design
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• v.34 no.6
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• pp.127-134
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• 2018

The purpose of this study is to derive a model of urban regeneration business using idle facilities in the old city center. The scope of the study was set as empty houses and empty stores owned by private companies, and analyzed the 50 central city revitalization projects using idle facilities in 14 local cities in Japan. The results of this study are follows; First, as an urban regeneration strategy using idle facilities in the old town, it was a combination of other functions centering on commercial functions or introducing new functions required in the city center. Second, various financial supports have been provided to induce the utilization of idle facilities by the private sector, and different strategies have been implemented for businesses that need maintenance first. Third, based on the analysis results, it was possible to derive urban regeneration business model. Fourth, in order to operate smooth business, it is a need for an organization that is in charge of reviewing the consistency of upper-level planning and urban guiding functions such as urban revitalization plan, balance review of expenditure and revenues by cost subsidy and loan repayment, consultation among the business partners.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.3
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• pp.148-154
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• 2021

We propose the AI Smart Factory Model for integrated management of production processes in this paper .It is an integrated platform system for the production of food packaging containers, consisting of a platform system for the main producer, one or more production partner platform systems, and one or more raw material partner platform systems while each subsystem of the three systems consists of an integrated storage server platform that can be expanded infinitely with flexible systems that can extend client PCs and main servers according to size and integrated management of overall raw materials and production-related information. The hardware collects production site information in real time by using various equipment such as PLCs, on-site PCs, barcode printers, and wireless APs at the production site. MES and e-SCM data are stored in the cloud database server to ensure security and high availability of data, and accumulated as big data. It was built based on the project focused on dissemination and diffusion of the smart factory construction, advancement, and easy maintenance system promoted by the Ministry of SMEs and Startups to enhance the competitiveness of small and medium-sized enterprises (SMEs) manufacturing sites while we plan to propose this model in the paper to state funding projects for SMEs.

• Journal of Korean Public Health Nursing
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• v.36 no.1
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• pp.47-58
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• 2022

Purpose: This study was undertaken to present an effective plan for the development of an educational program and a strategy to promote patient safety management activities for nursing students by identifying factors that affect these activities based on the theory of planned behavior. Methods: A self-report questionnaire was distributed to 300 nursing students who had clinical practice experience at three nursing colleges in Daejeon, Gyeongbuk, and Jeonbuk. The significance of the model fit, and the path effect was confirmed by confirmatory factor analysis. Results: The hypothetical model for patient safety management activities was appropriate. Among the 5 pathways, 4 were significant. It was found that behavioral intention had a direct influence on patient safety management activities, and perceived behavioral control and attitude had an influence on behavioral intention. Conclusion: To strengthen the perceived behavioral control of nursing students' patient safety management activities, it is necessary to analyze and remove obstacles and provide education that reflects the characteristics of the subject's health problems. In addition, through self-directed learning involving simulation practice, nursing students should be exposed to patient safety accidents, so that they can recognize the risks early and solve problems through critical thinking while bringing about the necessary changes in their attitude.

• Wind and Structures
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• v.36 no.2
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• pp.105-120
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• 2023

The present study is performed to find the effect of corner recession on a square plan-shaped tall building. A series of numerical simulations have been carried out to find the two orthogonal wind force coefficients on various model configurations using Computational Fluid Dynamics (CFD). Numerical analyses are performed by using ANSYS-CFX (k-ℇ turbulence model) considering the length scale of 1:300. The study is performed for 0° to 360° wind angle of attack. The CFD data thus generated is utilised to fit parametric equations to predict alongwind and crosswind force coefficients, C_fx and C_fy. The precision of the parametric equations is validated by employing a wind tunnel study for the 40% corner recession model, and an excellent match is observed. Upon satisfactory validation, the parametric equations are further used to carry out multiobjective optimization considering two orthogonal force coefficients. Pareto optimal design results are presented to propose suitable percentages of corner recession for the study building. The optimization is based on reducing the alongwind and crosswind forces simultaneously to enhance the aerodynamic performance of the building.

• International conference on construction engineering and project management
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• 2013.01a
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• pp.294-299
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• 2013

In many urban cities, super-tall buildings have been being constructed around New York and Chicago as the center since 1930 to improve the efficiency of land use and respond to new residential type. In terms of energy consumption, super-tall buildings are classified as a top energy consumption building. Also, as time passed, the degradation of energy performance occurs in super-tall buildings like general things so that these cannot show the initial performance planned in the design phase. Accordingly, building owners need to make a plan to apply energy saving measures to existing building during the operation phase. In order to select energy saving measures, calculus-based methods and enumerative schemes have been typically used. However, these methods are time-consuming and previous studies which used these methods have problems with not considering the initial construction cost. Consequently, this study proposes a model for selecting an optimal combination of energy saving measures which derives maximum energy saving within allowable cost using genetic algorithms. As a contribution of this research, it would be expected that a model is utilized as one of the decision-making tools during the planning stage for energy saving.