• 한국전산유체공학회:학술대회논문집
• /
• 2009.04a
• /
• pp.51-56
• /
• 2009

Optimization with metamodel is one of numerical optimization methods. Response surface method is performed for making metamodel. The Hcks-Henne function is used for designing 2D shape of the airfoil and spring analogy is used to change the grid according to the change in shape of the airfoil. Aerodynamic coefficient required for response surface method are obtained by using Navier-Stokes solver with $\kappa-\omega$ shear stress transport turbulence model. For the baseline airfoils, OA 312, OA 309, and OA 407 airfoils select and optimize to improve aerodynamic performance.

• Journal of Mechanical Science and Technology
• /
• v.14 no.9
• /
• pp.1013-1019
• /
• 2000

A numerical investigation was performed to determine the effect of the Gurney flap on a NACA 23012 airfoil. A Navier-Stokes code, RAMPANT, was used to calculate the flow field about the airfoil. Fully-turbulent results were obtained using the standard ${\kappa}-{\varepsilon}$ two-equation turbulence model. The numerical solutions showed that the Gurney flap increased both lift and drag. These results suggested that the Gurney flap served to increase the effective camber of the airfoil. The Gurney flap provided a significant increase in the lift-to-drag ratio relatively at low angle of attack and for high lift coefficient. It turned out that 0.6% chord size of flap was the best. The numerical results exhibited detailed flow structures at the trailing edge and provided a possible explanation for the increased aerodynamic performance.

• Proceedings of the KSRS Conference
• /
• 2003.11a
• /
• pp.107-109
• /
• 2003

Optical sensor-based land cover categories produce spectral signature confusion along with degraded classification accuracy. In the classification tasks, the goal of fusing data from different sensors is to reduce the classification error rate obtained by single source classification. This paper describes the result of land cover/land use classification derived from solely of Landsat TM (TM) and multisensor image fusion between JERS 1 SAR (JERS) and TM data. The best radar data manipulation is fused with TM through various techniques. Classification results are relatively good. The highest Kappa Coefficient is derived from classification using principal component analysis-high pass filtering (PCA+HPF) technique with the Overall Accuracy significantly high.

• Journal of the Ergonomics Society of Korea
• /
• v.29 no.5
• /
• pp.811-818
• /
• 2010

In this study, a self-administered checklist for evaluation of the musculoskeletal disorders risk factors in construction industry was developed, and its reliability and validity were studied. 10 items of the checklist were determined based on the literature review, and total 2,793 construction workers participated in the analysis of the checklist's applicability. The results from the reliability analysis showed high Cohen's kappa coefficient (0.50~0.77), and high validity was also obtained in terms of relative risk (RR 1.73~9.14). Positive predictability was relatively low (13.0~32.5%), while negative predictability was high (80.1~96.8%). It can be concluded that the checklist would be suitable as a quick filtering tool of the ergonomic risk factors.

• 한국전산유체공학회:학술대회논문집
• /
• 2001.10a
• /
• pp.70-75
• /
• 2001

This paper presents the results of numerical simulation of wind environment and wind coefficient around super high-rise building. The analysis of aerodynamic response due to wind-induced forces and wind effect to surrounding buildings is important to high-rise building. This paper simulates the wind force to the high-rise building and wind flow pattern around the high-rise building, and shows the usability of CFD analysis to design process of high-rise building. A Navier-Stokes-Solver (FLUENT) with Quick spatial discretization scheme and RNG $\kappa-\epsilon$ turbulence model has been applied to the computation of the three dimensional turbulent flow.

• Journal of The Korean Society of Agricultural Engineers
• /
• v.58 no.1
• /
• pp.91-97
• /
• 2016

The objective of this study was to classify between radish and Chinese cabbage in autumn using hyperspectral images. The hyperspectral images were acquired by Compact Airborne Spectrographic Imager (CASI) with 1m spatial resolution and 48 bands covering the visible and near infrared portions of the solar spectrum from 370 to 1044 nm with a bandwidth of 14 nm. An object-based technique is used for classification of radish and Chinese cabbage. It was found that the optimum parameter values for image segmentation were scale 400, shape 0.1, color 0.9, compactness 0.5 and smoothness 0.5. As a result, the overall accuracy of classification was 90.7 % and the kappa coefficient was 0.71. The hyperspectral images can be used to classify other crops with higher accuracy than radish and Chines cabbage because of their similar characteristic and growth time.

• Korean Journal of Remote Sensing
• /
• v.33 no.1
• /
• pp.61-67
• /
• 2017

The detection of oil spills using radar image has been studied extensively. However, most of the proposed techniques have been focused on improving detection accuracy through the advancement of algorithms. In this study, research has been conducted to improve the accuracy of oil spill detection by improving the quality of radar images, which are used as input data to detect oil spills. Thresholding algorithms were used to measure the image improvement both before and after processing. The overall accuracy increased by approximately 16%, the producer accuracy increased by 40%, and the user accuracy increased by 1.5%. The kappa coefficient also increased significantly, from 0.48 to 0.92.

• Proceedings of the KSRS Conference
• /
• 2008.10a
• /
• pp.111-114
• /
• 2008

The existence of noise bands may deform the typical shape of the spectrum, making the accuracy of clustering degraded. This paper proposes a statistical approach to remove noise bands in hyperspectral data using the correlation coefficient of bands as an indicator. Considering each band as a random variable, two adjacent signal bands in hyperspectral data are highly correlative. On the contrary, existence of a noise band will produce a low correlation. For clustering, the unsupervised ${\kappa}$-nearest neighbor clustering method is implemented in accordance with three well-accepted spectral matching measures, namely ED, SAM and SID. Furthermore, this paper proposes a hierarchical scheme of combining those measures. Finally, a separability assessment based on the between-class and the within-class scatter matrices is followed to evaluate the applicability of the proposed noise band removal method. Also, the paper brings out a comparison for spectral matching measures.

• Journal of the Korean Institute of Landscape Architecture
• /
• v.27 no.4
• /
• pp.131-136
• /
• 1999

Aerial videography techniques have been used to inventory conditions associated with grassland, forests, and agricultural crop production. Most recently, aerial videography has been used to verity satellite image classifications as part of the natural ecosystem survey. The objectives of this study were: (1) to use aerial video images of the study area, one part of Taean Seashore National Park, for the accuracy assessment, and (2) to determine the suitability of aerial videography as an accuracy assessment, of the land cover classification with Landsat-TM data. Video images were collected twice, summer and winter seasons, and divided into two kinds of images, wide angle and narrow angle images. Accuracy assessment methods include the calculation of the error matrix, the overall accuracy and kappa coefficient of agreement. This study indicates that aerial videography is an effective tool for accuracy assessment of the satellite image classifications of which features are relatively large and continuous. And it would be possible to overcome the limits of the present natural ecosystem survey method.

• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
• /
• 2000.11a
• /
• pp.81-84
• /
• 2000

Two-layer aquifer system with fractional flow dimension is composed of contiguous two layers: Layer 1 (lower layer) and Layer 2 (upper layer) with different permeability and specific storage each other. For this aquifer system, we assume that groundwater flow originates only from Layer 1 on the pumping well. The aquifer system considers wellbore storage and skin effects on the pumping well. Dimensionless drawdown curves for different flow dimensions are analyzed for different lambda (λ, crossflow coefficient) values, kappa ($textsc{k}$, permeability ratio between Layer 1 and Layer 2) values and omega ($\omega$, storativity ratio between Layer 1 and Layer 2) values. The curves for Layer 1 and Layer 2 show characteristic trend each other.