• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.7 no.4
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• pp.667-680
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• 1995

튜브 내의 입구영역에서 난류 유동에 의한 대류와 비회복사(non-gray radiation)가 동시에 일어날 때의 열전달특성을 수치해석적으로 연구하였다. 작동유체는 이산화탄소, 수증기, 질소의 혼합가스라고 가정하였다. 지배방정식을 계산하기 위해 유한차분법이 이용되었고, 복사전달방정식을 이차편미분방정식으로 바꾸기 위해 P-1 근사법이 사용되었다. 그리고 혼합가스의 비회흡수계수(non-gray absorption coefficient)는 지수광폭밴드모형(exponential wide band model)을 이용해서 구하였다. 열전달특성에 대한 온도조건의 영향을 조사하기 위해 튜브의 축방향에 대한 평균 온도와 뉴셀트수(Nusselt number)의 변화를 몇 가지 다른 온도조건에 대해 나타내었다. 또한, 가스의 성분조성에 대한 영향을 조사하였으며, 이러한 결과에 기초해서 튜브 내에서 난류유동에 의한 대류와 비화복사가 동시에 일어날 때의 복사 뉴셀트수를 쉽게 예측할 수 있는 방법을 제시하였다.

• Journal of The Korean Astronomical Society
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• v.31 no.2
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• pp.77-87
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• 1998

The accumulated knowledge of the influence of solar granulation on spectral lines, i.e. their asymmetry, provides a key to analyze stellar spectral line asymmetries. In this paper, a simple line synthesis using a simple 'model' of granulation was calculated. By adjusting the properties of the granule model, the observed imprints of convection on spectral lines can be reproduced. Since we depict convective flows using a continuous function rather than using a few components of flows (cf. Gray and Toner 1985, 1986; dravins 1990), we were able to identify which components of convection are important in line bisector shapes. The results of this study can be summarized as follows: Firstly, the intensity contrast (i.e. temperature fluctuation), and the area coverage of up- and down-flows are the two important factors which determine the line bisector shapes. Secondly, on the contrary to the assumption of other studies, the effect of horizontal flows is non-negligible. This exercise provides a qualitative understanding of the effect of convection on spectral lines. This knowledge serves as a guideline for understanding the characteristic difference in convection for stars on either side of the 'Granulation Boundary' (Gray 1982; Gray and Nagel 1989).

• Proceedings of the KSME Conference
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• 2004.04a
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• pp.1493-1498
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• 2004

WSGGM with gray gas regrouping is successfully applied to study the flame structure of counter flow flames including effect of radiative transfer. The statistical narrow band model is used to obtain the benchmark solutions. Results obtained by using the optically thin model are shown to overestimate the emission and to predict the flame structures inadequately especially for optically thick and low stretch rate flames. Computed results by using the WSGGM with 10 gray gases and SNB model show reasonable agreements with each other, and the required calculation time for the WSGGM is acceptable for engineering applications.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.20 no.10
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• pp.3371-3380
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• 1996

Low resolution spectral modeling of water vapor is carried out by applying the weighted-sum-of-gray-gases model (WSGGM) to a narrow band. For a given narrow band, focus is placed on proper modeling of gray gas absorption coefficients vs. temeprature relation used for any solution methods for the Radiative Transfer Equation(RTE). Comparison between the modeled emissivity and the "true" emissivity obtained from a high temperatue statistical narrow band parameters is made ofr the total spectrum as well as for a few typical narrow bands. Application of the model to nonuniform gas layers is also made. Low resolution spectral intensities at the boundary are obtained for uniform, parabolic and boundary layer type temeprature profiles using the obtained for uniform, parabolic and boundary layer type temperature profiles using the obtained WSGGM's with 9 gray gases. The results are compared with the narrow band spectral intensities as obtained by a narrow band model-based code with the Curtis-Godson approximation. Good agreement is found between them. Local heat source strength and total wall heat flux are also compared for the cases of Kim et al, which again gives promising agreement.

• Biomedical Science Letters
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• v.24 no.4
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• pp.418-425
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• 2018

Amyloid brain positron emission tomography (PET) images are visually and subjectively analyzed by the physician with a lot of time and effort to determine the ${\beta}$-Amyloid ($A{\beta}$) deposition. We designed a convolutional neural network (CNN) model that predicts the $A{\beta}$-positive and $A{\beta}$-negative status. We performed 18F-florbetaben (FBB) brain PET on controls and patients (n=176) with mild cognitive impairment and Alzheimer's Disease (AD). We classified brain PET images visually as per the on the brain amyloid plaque load score. We designed the visual geometry group (VGG16) model for the visual assessment of slice-based samples. To evaluate only the gray matter and not the white matter, gray matter masking (GMM) was applied to the slice-based standard samples. All the performance metrics were higher with GMM than without GMM (accuracy 92.39 vs. 89.60, sensitivity 87.93 vs. 85.76, and specificity 98.94 vs. 95.32). For the patient-based standard, all the performance metrics were almost the same (accuracy 89.78 vs. 89.21), lower (sensitivity 93.97 vs. 99.14), and higher (specificity 81.67 vs. 70.00). The area under curve with the VGG16 model that observed the gray matter region only was slightly higher than the model that observed the whole brain for both slice-based and patient-based decision processes. Amyloid brain PET images can be appropriately analyzed using the CNN model for predicting the $A{\beta}$-positive and $A{\beta}$-negative status.

• Proceedings of the KSME Conference
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• 2003.11a
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• pp.284-289
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• 2003

The narrow band-averaged transmissivity of $CO_2-H_2O$ mixtures is expressed by multiplying the transmissivities of $CO_2$ and $H_2O$. Applying the multiplication property of narrow band transmissivities for gas mixtures of $CO_2-H_2O$, the number of gray gases, required for accurate representation of the absorption characteristics by using the narrow band based WSGGM, is significantly increased. To reduce the computational loads by reducing the number of gray gases, we propose a gray gas regrouping process where the gray gases used for the WSGGM are regrouped into a specified number of groups according to the magnitudes of absorption coefficients. To evaluate the proposed WSGGM for gas mixtures, the radiative transfer problems through three-dimensional gas media are considered. The radiative source terms and the radiative heat fluxes obtained by using the proposed method are fairly well compared to those obtained by using the SNB model. The regrouping technique results in an excellent computational efficiency with minor loss of accuracy.

• Journal of Korea Multimedia Society
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• v.20 no.1
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• pp.43-50
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• 2017

According to living environment, the number of deaths due to thyroid diseases increased. In this paper, we proposed an algorithm for recognizing a thyroid detection using texture analysis based on shape, gray level co-occurrence matrix and gray level run length matrix. First of all, we segmented the region of interest (ROI) using active contour model algorithm. Then, we applied a total of 18 features (5 first order descriptors, 10 Gray level co-occurrence matrix features(GLCM), 2 Gray level run length matrix features and shape feature) to each thyroid region of interest. The extracted features are used as statistical analysis. Our results show that first order statistics (Skewness, Entropy, Energy, Smoothness), GLCM (Correlation, Contrast, Energy, Entropy, Difference variance, Difference Entropy, Homogeneity, Maximum Probability, Sum average, Sum entropy), GLRLM features and shape feature helped to distinguish thyroid benign and malignant. This algorithm will be helpful to diagnose of thyroid nodule on ultrasound images.

• Journal of Mechanical Science and Technology
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• v.15 no.6
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• pp.752-763
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• 2001

Although there are many different solution schemes proposed for multidimensional radiative transfer, reference solutions to benchmark these methods are very rare in the literature. In this paper we produced some accurate solutions for purely absorbing gray and nongray gases including H$_2$O and CO$_2$by using the discrete transfer method with sufficiently accurate T(sub)95 quadrature set. The spectral transmittances of the mixtures of H$_2$O and CO$_2$are estimated by using the narrow band model. The gray gas solutions are obtained for different absorption coefficients, and the nongray real gas solutions are obtained for different mixture fractions of H$_2$O and CO$_2$. The numerical solutions presented in this paper are proved to be sufficiently accurate as compared to the available exact solutions and they may be used as reference solutions in evaluating various solution schemes.

• Journal of Korea Multimedia Society
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• v.6 no.6
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• pp.968-976
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• 2003

In this paper, we propose a novel method for lip recognition. Lip model is built based on the concatenated gray level distribution model, and the recognition problem is simplified as the minimization problem of matching object function. The Down Hill Simplex Algorithm is used for the minimization with the proposed novel method for setting initial condition, which can refrain Iteration from converging to local minima. The proposed algorithm shows extracting lip shape from the test image where Active Shape Model fails.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.3
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• pp.91-102
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• 1994

For the analysis of textured image, it requires large storage space and computation time to calculate the matrix features such as SGLDM(Spatial Gray Level Dependence Matrix). NGLDM(Neighboring Gray Level Dependence Matrix). NSGLDM(Neighboring Spatial Gray Level Dependence Matrix) and GLRLM(Gray Level Run Length Matrix). In spite of a large amount of information that each matrix contains, a set of several correlated scalar features calculated from the matrix is not sufficient to approximate it. In this paper, we propose a new classifier for textured images based on these matrices in which the projected vectors of each matrix on the meaningful directions are used as features. In the proposed method, an unknown image is classified to the class of a known image that gives the maximum similarity between the projected model vector from the known image and the vector from the unknown image. In the experiment to classify images of agricultural products, the proposed method shows good performance as much as 85-95% of correct classification ratio.