• Journal of Korea Water Resources Association
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• v.34 no.6
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• pp.577-586
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• 2001

This study proposes a theoretical methodology for deriving a rainfall intensity-duration- frequency (I-D-F) curve using a simple rectangular pulses Poisson process model. As the I-D-F curve derived by considering the model structure is dependent on the rainfall model parameters estimated using the observed first and second order statistics, it becomes less sensitive to the unusual rainfall events than that derided using the annual maxima rainfall series. This study has been applied to the rainfall data at Seoul and Inchon stations to check its applicability by comparing the two I-D-F carves from the model and the data. The results obtained are as followed. (1) As the duration becomes longer, the overlap probability increases significantly. However, its contribution to the rainfall intensity decreases a little. (2) When considering the overlap of each rainfall event, especially for large duration and return period, we could see obvious increases of rainfall intensity. This result is normal as the rainfall intensity is calculated by considering both the overlap probability and return period. Also, the overlap effect for Seoul station is fecund much higher than that for Inchon station, which is mainly due to the different overlap probabilities calculated using different rainfall model parameter sets. (3) As the rectangular pulses Poisson processes model used in this study cannot consider the clustering characteristics of rainfall, the derived I-D-F curves show less rainfall intensities than those from the annual maxima series. However, overall pattern of both I-D-F curves are found very similar, and the difference is believed to be overcome by use of a rainfall model with the clustering consideration.

• Journal of Korean Society on Water Environment
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• v.27 no.1
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• pp.30-35
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• 2011

2D pollutant transport model was applied to the simulation of contaminant transport in the channel. At first, two kinds of virtual channels having different slopes were designed. The distribution of contaminant, which flows from one of the three drainages to the main channel, was simulated by each 2D model. Concentrations of 745 nodes were converted to input data of neural network model (Multi-perceptron) for training and verification using matrix. The first three cases (Case A-1, A-2, A-3) were used for training Multi-perceptron, the other three cases (Case B-1, B-2, B-3) were used for verification. As a result, Multi-perceptron reasonably divided the cases into the three characteristics which have different contaminant distributions due to the different input point of water pollution source. It can be a useful methodology for the water quality monitoring and backtracking.

• Proceedings of the Korean Geotechical Society Conference
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• 2010.09a
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• pp.580-586
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• 2010

The purpose of this study is to analyze the behavior of the concrete pile under the horizontal loads by the model tests in laboratory. The rock ground was modeled by the concrete of about 30MPa, and a model pile was made of some mortar with the capacity of 24MPa. The diameter(D) and length(L) of a model pile was each 1200mm and 1800mm. The embedment depth into the concrete block was varied with 1.0D, 1.5D, and 2.0D in the model tests. The results of model tests showed that the lateral resistance of a pile with the embedment depth of 2.0D was more large than other cases, and the lateral displacement of yielding was similar.

• KIPS Transactions on Software and Data Engineering
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• v.9 no.1
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• pp.11-16
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• 2020

3D printing is one of the emerging technologies and getting a lot of attention. To do 3D printing, 3D model is first generated, and then converted to G-code which is 3D printer's operations. Facet, which is a small triangle, represents a small surface of 3D model. Depending on the height or precision of the 3D model, the number of facets becomes very large and so the conversion time from 3D model to G-code takes longer. Apach Hadoop is a software framework to support distributed processing for large data set and its application range gets widening. In this paper, Hadoop is used to do the conversion works time-efficient way. 2-phase distributed algorithm is developed first. In the algorithm, all facets are sorted according to its lowest Z-value, divided into N parts, and converted on several nodes independently. The algorithm is implemented in four steps; preprocessing - Map - Shuffling - Reduce of Hadoop. Finally, to show the performance evaluation, Hadoop systems are set up and converts testing 3D model while changing the height or precision.

• The Journal of the Korea Contents Association
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• v.21 no.3
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• pp.184-193
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• 2021

This paper investigates the performance of technology innovation activities performed by firms in 16 major regions in Korea using 2002-2010 survey data by STEPI. The theoretical and empirical analysis is carried out via the 2 models which are the simple R&D - total revenue model and Cobb-Douglas model based on the simple model adding labor variable. The main results shows that for simple model, the R&D elasticity for total revenue is 0.42 for all areas and Ul-San shows the highest elasticity level, 0.66 and Bu-San the lowest level, 0.2. In case of Cobb Douglas model the R&D elasticities are not statistically significant for many regions. To overcome the low statistical significance, we grouped the 15 regions for 3 wider regions using ANOVA based on the R&D intensity for the homogeneity of R&D activities. By grouping, each region has more observations to analyze and the results from the empirical analysis shows higher statistical significance level and data explanation capability. In this case, Group 3 which shows larger firm size and slightly higher export share shows the highest level of R&D elasticity, 0.088 and Group 1 which has the smallest firm size and the lowest revenue growth rate shows the lowest level, 0.31. For the labor elasticity, Group 1 shows the higest level, 1.16 and Group2 the lowest level, 1.096. These results show that the regions which have many middle and small firms reveal low R&D-revenue elasticity and high labor-revenue elasticity.

• Journal of Technology Innovation
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• v.22 no.1
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• pp.1-22
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• 2014

R&D investment also has a gestation period similar to other investments in economics. The gestation period originates from time lag effect of input and output. Thus it is necessary to consider time lag effects when analyzing the relationship between firms' R&D investment and R&D performance. The main objective of this research is to estimate the length of time lag effect of R&D investment. The Almon distribution lag model was applied to estimate the time lag effect. The firm level panel dataset was established from 2002 to 2009. The net value of R&D investment and the number of patent applications were used to measure R&D input and output, respectively. This method found the estimated time lag to be 1~2 years across all datasets. The same analyses were applied to chemical, metal, electronic, exact science, and machinery industries' data. And we found there were differences among sectors in regard to the time lag effect.

• Journal of the Society of Naval Architects of Korea
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• v.56 no.1
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• pp.66-74
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• 2019

In the field of shipbuilding design, the use of 3D CAD is becoming commonplace, and most of the large shipyards are conducting 3D design. However at the production site, workers are still working on 2D drawings rather than 3D models. This tendency is even worse in small-scale shipyards and block manufacturing shops. Particularly, in a manufacturing shop that is engaged in the outsourcing of blocks, it may not be possible to provide 3D model. However, the demand for 3D models in the production field is steadily increasing. Therefore, it would be helpful if 3D model could be generated from a 2D drawing. In this paper, we propose a method to extract template and unfolded surface shape information from shell template offset drawing using computer vision technology. Also a 3D surface model was reconstructed and visualized from the extracted information. The result of this study is thought to be helpful in the work environment where 3D model information can not be obtained.

• Imaging Science in Dentistry
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• v.34 no.1
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• pp.13-18
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• 2004

Purpose : This study was to evaluate the influence of slice thickness of computed tomography (CT) and rapid protyping (RP) type on the accuracy of 3-dimensional medical model. Materials and Methods: Transaxial CT data of human dry skull were taken from multi-detector spiral CT. Slice thickness were 1, 2, 3 and 4 mm respectively. Three-dimensional image model reconstruction using 3-D visualization medical software (V-works /sup TM/ 3.0) and RP model fabrications were followed. 2-RP models were 3D printing (Z402, Z Corp., Burlington, USA) and Stereolithographic Apparatus model. Linear measurements of anatomical landmarks on dry skull, 3-D image model, and 2-RP models were done and compared according to slice thickness and RP model type. Results: There were relative error percentage in absolute value of 0.97, 1.98,3.83 between linear measurements of dry skull and image models of 1, 2, 3 mm slice thickness respectively. There was relative error percentage in absolute value of 0.79 between linear measurements of dry skull and SLA model. There was relative error difference in absolute value of 2.52 between linear measurements of dry skull and 3D printing model. Conclusion: These results indicated that 3-dimensional image model of thin slice thickness and stereolithographic RP model showed relative high accuracy.

• Journal of the Korea institute for structural maintenance and inspection
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• v.26 no.6
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• pp.157-166
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• 2022

Structural supervision on the construction site has been performed based on visual inspection, which is highly labor-intensive and subjective. In this study, the remote technique was developed to improve the efficiency of the measurements on rebar spacing using a 360° camera and reconstructed 3D models. The proposed method was verified by measuring the spacings in reinforced concrete structure, where the twelve locations in the construction site (265 m²) were scanned within 20 seconds per location and a total of 15 minutes was taken. SLAM, consisting of SIFT, RANSAC, and General framework graph optimization algorithms, produces RGB-based 3D and 3D point cloud models, respectively. The minimum resolution of the 3D point cloud was 0.1mm while that of the RGB-based 3D model was 10 mm. Based on the results from both 3D models, the measurement error was from 10.8% to 0.3% in the 3D point cloud and from 28.4% to 3.1% in the RGB-based 3D model. The results demonstrate that the proposed method has great potential for remote structural supervision with respect to its accuracy and objectivity.

• Korean Journal of Computational Design and Engineering
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• v.19 no.1
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• pp.41-49
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• 2014

For the reuse of the existing 3D block model of a ship, we analyze the hull modeling process using AVEVA Marine which is a representative CAD (Computer-Aided Design) system for the shipbuilding. In the AVEVA Marine environment where the design engineer makes 3D model on the 2D view that is so-called 2.5D, it cannot be possible to copy to reuse the block model just simply copying the 3D feature model itself like in the general mechanical CAD system or Smart Marine 3D which are on the basis of the 3D model representation. In this paper, we analyze the scheme file where the 3D model is defined in AVEVA Marine so that we develop the program for the block copy and the translation using this scheme file. It is significant that this program can be immediately available as a real-world application on the AVEVA Marine environment.