• Journal of Korean Society of Forest Science
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• v.95 no.3
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• pp.240-249
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• 2006

Recently, dispersion of damaged forest by pine wilt disease has been regarded as a serious social issue. Damages by pine wilt disease have been spreaded by natural area expansion of the vectors in the damaged area, while the national wide damage spread has induced by human-involved carrying infected trees out of damaged area. In this study, damaged trees were detected and located on the digital map by aerial photograph and terrestrial surveys. The spatial distribution pattern of damaged trees, and the relationship of spatial distribution of damaged trees and some geomorphological factors were geostatistically analysed. Finally, we maked natural spread pattern map of pine wilt disease using geostatistical CART(Classification and Regression Trees) model. This study verified that geostatistical analysis and CART model are useful tools for understanding spatial distribution and natural spread pattern of pine wilt diseases.

• Journal of the Korean Society for Railway
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• v.11 no.3
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• pp.216-224
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• 2008

In general, based on criteria of subway law, radius 500m from subway station is defined as SIA(Subway Station Influence Area). Therefore, in this paper, selection models of SIA are developed to identify appropriate SIA for recently developed 4 new towns based based on CART analysis. As a result, following outputs are obtained; (1) walking distance from subway station is the most influential factor to define SIA (2) SIAs vary with new towns (i.e., bundang city: 856m, ilsan sanbon city 508m, pyungchon city 495m), and (3) walking distance from subway station is influential to land price of SIA. In addition, bundang and pyungchon new town are more affected in land price and walking distance. Therefore, it is desirable for current definition of SIA (radius 500m from subway station) to reflect characteristics of land use and walking distance in the new towns.

• The Journal of the Convergence on Culture Technology
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• v.9 no.4
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• pp.707-715
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• 2023

This study utilized CART algorithm, a decision tree analysis method, to comparatively analyze factors affecting housing and residential environment satisfaction by region using data from Ministry of Land, Infrastructure and Transport's housing survey in 2020. First, in terms of residential environment satisfaction, accessibility to medical facilities and school district showed higher importance in metropolitan cities and areas compared to other regions, whereas safety from accident showed the opposite trait, showing difference between region. Second, housing characteristics were important in housing satisfaction, indoor environment level satisfaction and indoor safety and hygiene being important in almost all regions, while residential environment characteristics were more important in residential environment satisfaction and influencing factors were relatively evenly distributed. In order to generalize these regional characteristics, research using time series data needs to be conducted later.

• The Journal of Engineering Geology
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• v.31 no.3
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• pp.395-432
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• 2021

Groundwater recharge rates vary widely by location and with time. They are difficult to measure directly and are thus often estimated using simulations. This study employed frequency and regression analysis and a classification and regression tree (CART) algorithm in a machine learning method to estimate groundwater recharge. CART algorithms are considered for the distribution of precipitation by subbasin (PCP), geomorphological data, indices of the relationship between vegetation and landuse, and soil type. The considered geomorphological data were digital elevaion model (DEM), surface slope (SLOP), surface aspect (ASPT), and indices were the perpendicular vegetation index (PVI), normalized difference vegetation index (NDVI), normalized difference tillage index (NDTI), normalized difference residue index (NDRI). The spatio-temperal distribution of groundwater recharge in the SWAT-MOD-FLOW program, was classified as group 4, run in R, sampled for random and a model trained its groundwater recharge was predicted by CART condidering modified PVI, NDVI, NDTI, NDRI, PCP, and geomorphological data. To assess inter-rater reliability for group 4 groundwater recharge, the Kappa coefficient and overall accuracy and confusion matrix using K-fold cross-validation were calculated. The model obtained a Kappa coefficient of 0.3-0.6 and an overall accuracy of 0.5-0.7, indicating that the proposed model for estimating groundwater recharge with respect to soil type and vegetation cover is quite reliable.

• The Transactions of the Korean Institute of Power Electronics
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• v.23 no.1
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• pp.1-8
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• 2018

A problem exists in the conventional transportation cart applications, in which an external power supply with mechanical contact connection (bus bar connection) is required to drive the motor. Therefore, continuous effort for maintenance is required, aside from the expensive bus bar connector. To solve this problem, a self-electricity-generated transportation cart system without bus bar has recently been introduced. In this system, a battery needs to store the power of the generated wheel, and a boost converter, which converts the low battery voltage to high bus voltage to drive the motor inverter, is necessary. However, since the instantaneous large current required for starting the motor is supplied from the battery, a battery with large size and volume should be adopted to withstand this large current. In this study, a boost converter that can supply a large instantaneous current by using super Capacitor string is proposed. The proposed converter can be realized with a small size and volume compared with the conventional battery-fed boost converter. Operational principles, analysis, and design of the proposed converter are presented, and experimental results are provided to validate the proposed converter.

• Safety and Health at Work
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• v.1 no.2
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• pp.140-148
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• 2010

Objectives: Determining the work-relatedness of lung cancer developed through occupational exposures is very difficult. Aims of the present study are to develop a decision tree of occupational lung cancer. Methods: 153 cases of lung cancer surveyed by the Occupational Safety and Health Research Institute (OSHRI) from 1992-2007 were included. The target variable was whether the case was approved as work-related lung cancer, and independent variables were age, sex, pack-years of smoking, histological type, type of industry, latency, working period and exposure material in the workplace. The Classification and Regression Test (CART) model was used in searching for predictors of occupational lung cancer. Results: In the CART model, the best predictor was exposure to known lung carcinogens. The second best predictor was 8.6 years or higher latency and the third best predictor was smoking history of less than 11.25 pack-years. The CART model must be used sparingly in deciding the work-relatedness of lung cancer because it is not absolute. Conclusion: We found that exposure to lung carcinogens, latency and smoking history were predictive factors of approval for occupational lung cancer. Further studies for work-relatedness of occupational disease are needed.

• Bulletin of the Korean Chemical Society
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• v.30 no.11
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• pp.2717-2722
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• 2009

The use of the classification and regression tree (CART) methodology was studied in a quantitative structure-activity relationship (QSAR) context on a data set consisting of the binding affinities of 39 imidazobenzodiazepines for the α1 benzodiazepine receptor. The 3-D structures of these compounds were optimized using HyperChem software with semiempirical AM1 optimization method. After optimization a set of 1481 zero-to three-dimentional descriptors was calculated for each molecule in the data set. The response (dependent variable) in the tree model consisted of the binding affinities of drugs. Three descriptors (two topological and one 3D-Morse descriptors) were applied in the final tree structure to describe the binding affinities. The mean relative error percent for the data set is 3.20%, compared with a previous model with mean relative error percent of 6.63%. To evaluate the predictive power of CART cross validation method was also performed.

• 한국IT서비스학회:학술대회논문집
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• 2002.11a
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• pp.225-231
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• 2002

B2B EC는 그 시장규모와 기업, 사회전반에 미치는 영향이 커다란 주요한 연구 분야이다. 그런데, B2C EC와 달리 B2B EC에서는, 구매자의 전자시장에서의 구매기록은 ERP로 대표되는 기업내의 전자구매시스템과 통합되어야 한다. 이를 위한 구조로서 기존의 Inside-Out 접근방식과 Outside-In 접근방식, 그리고, 최근의 b-Cart 접근방식이 있다. 본 논문에서는 이들 3가지 방식에 대한 고찰과 비교 분석을 시도한다. 이를 통해서 기업간 전자상거래에 있어서 ERP와 전자시장과의 통합구조로 b-Cart 접근방식이 효율적인 프레임웍임을 확인한다.

• Nuclear Engineering and Technology
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• v.52 no.3
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• pp.461-468
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• 2020

The improvements of the DeCART/MUSAD code system for uncertainty analysis of HTGR neutronic parameters are presented in this paper. The function for quantifying an uncertainty of critical-spectrumweighted few group cross section was implemented using the generalized adjoint B₁ equation solver. Though the changes between the infinite and critical spectra cause a considerable difference in the contribution by the graphite scattering cross section, it does not significantly affect the total uncertainty. To reduce the number of iterations of the generalized adjoint transport equation solver, the generalized adjoint B₁ solution was used as the initial value for it and the number of iterations decreased to 50%. To reflect the implicit uncertainty, the correction factor was derived with the resonance integral. Moreover, an additional correction factor for the double heterogeneity was derived with the effective cross section of the DH region and it reduces the difference from the complete uncertainty. The code system was examined with the MHTGR-350 Ex.II-2 3D core benchmark. The k_eff uncertainty for Ex.II-2a with only the fresh fuel block was similar to that of the block and the uncertainty for Ex.II-2b with the fresh fuel and the burnt fuel blocks was smaller than that of the fresh fuel block.

• Journal of Korea Multimedia Society
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• v.19 no.4
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• pp.747-755
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• 2016

Automated guided vehicles have been used for a long time to increase work efficiency in the logistics field, but it is difficult to apply to a variety of logistics sites due to either the restricted movement mechanism or expensive devices. In this paper, we present a flexible software architecture that is hardware-independent for a mobile power cart of the follow mode and implement it using a ROS software platform. Through the SCV analysis for the system functionalities, we design a package to track a user movement and a package to control a new hardware platform. It has an advantage to use a variety of movement algorithms and hardware platforms by applying the strategy pattern and the template method pattern for the design of a software architecture. Through the performance evaluation, we show that the proposed design is maintainable in terms of a software complexity and it detects a user's movement by obtaining a user skeleton information so that it can control a hardware platform to move at a certain distance.