• Journal of Korea Society of Industrial Information Systems
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• v.19 no.2
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• pp.85-91
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• 2014

The objective of the research is to automatically recognize railway objects from MLS data in which 9 key objects including terrain, track, bed, vegetation, platform, barrier, posts, attachments, powerlines are targeted. The proposed method can be divided into two main sub-steps. First, multi-scale contextual features are extracted to take the advantage of characterizing objects of interest from different geometric levels such as point, line, volumetric and vertical profile. Second, by considering contextual interactions amongst object labels, a contextual classifier is utilized to make a prediction with local coherence. In here, the Conditional Random Field (CRF) is used to incorporate the object context. By maximizing the object label agreement in the local neighborhood, CRF model could compensate the local inconsistency prediction resulting from other local classifiers. The performance of proposed method was evaluated based on the analysis of commission and omission error and shows promising results for the practical use.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.1
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• pp.191-197
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• 2013

Conventional CT and MRI scans produce cross-section slices of body that are viewed sequentially by radiologists who must imagine or extrapolate from these views what the 3 dimensional anatomy should be. By using sophisticated algorithm and high performance computing, these cross-sections may be rendered as direct 3D representations of human anatomy. The 2D medical image analysis forced to use time-consuming, subjective, error-prone manual techniques, such as slice tracing and region painting, for extracting regions of interest. To overcome the drawbacks of 2D medical image analysis, combining with medical image processing, 3D visualization is essential for extracting anatomical structures and making measurements. We used the gray-level thresholding, region growing, contour following, deformable model to segment human organ and used the feature vectors from texture analysis to detect harmful cancer. We used the perspective projection and marching cube algorithm to render the surface from volumetric MR and CT image data. The 3D visualization of human anatomy and segmented human organ provides valuable benefits for radiation treatment planning, surgical planning, surgery simulation, image guided surgery and interventional imaging applications.

• Journal of Wetlands Research
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• v.19 no.1
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• pp.90-102
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• 2017

In this study, various types of nutrient models were tested by using two tears's water quality data collected from the stormwater wetland in Korea. Based on results, most important factor influencing nitrogen removal was hydraulic loading rate, which indicates that surface area of wetland is more important than its volumetric capacity, and model proposed by WEF was found to give a least error between measured and calculated values. For the phosphorus, in case assuming a power relationship between rate constant and temperature, the best prediction result were obtained, but temperature was most sensitive parameter affecting phosphorus removal. In addition, denitrification was always a limiting step for the nitrogen removal in this particular wetland mostly due to the lack of carbon source and high dissolved oxygen concentration. In this paper, several alternatives to improve nitrogen removal, including proper arrangement and designation of wetland elements and use of floating plants or synthetic fiber mat to control oxygen level and to capture the algal particles were proposed and discussed.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.42 no.4
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• pp.326-335
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• 2014

Aerodynamic characteristics of the small two-stage turbo blower were investigated using commercial CFD tool(ANSYS CFX Ver. 14.5) in this paper. Turbo blower, which is a centrifugal type of turbomachinery, is used in various industries. It is used for application that required high static pressure rising at relatively small volumetric flow rate. In order to understand the mechanism of static pressure rising, the aerodynamic characteristics of the small two-stage turbo blower are analyzed at high rotating speed in this study. The k-${\omega}$ SST turbulence model, which is good at prediction of adverse pressure gradient flows, was applied. The CFD results of the turbo blower are validated by performance test. The static pressure rising of the turbo blower is nonlinearly increased over the first stage and the second stage. The secondary flow occurred at guide vanes, between the casing and the first impeller shroud, and the bottom of the impeller disk. As a result, It is required that whole fluid area is analyzed to predict aerodynamic characteristics of small two-stage turbo blower. and the result should be selected with considering for error from experiment and CFD.