• Transactions of Materials Processing
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• v.33 no.3
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• pp.193-199
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• 2024

The friction welding characteristics of stainless steels, mainly used in energy and chemical plant industries due to its excellent corrosion resistance and high strength, was evaluated in this study. Friction welding was introduced and conducted at a rotation speed of 2,000 RPM, friction pressure of 30 MPa, burn-off length of 5 mm and upset pressure of 110 ~ 200 MPa on rod typed specimens. The grain boundary characteristics distributions such a grain size, shape, misorientation angle and kernel average misorientation of the welds were clarified by electron backscattering diffraction method. The application of friction welding on SUS304 alloy resulted in a significant refinement of the grain size in the weld zone (5.11 mm) compared to that of the base material (48.09 mm). The mechanical properties of the welds, on the other hand, appeared to be relatively low or similar to those of the base material, which were mainly caused by dislocation density in the initial material and grain refinement in the welds.

• Journal of the Korea Society of Computer and Information
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• v.18 no.4
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• pp.19-26
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• 2013

Pseudo sample neural network (PSNN) is a variant of traditional neural network using pseudo samples to mitigate the local-optima-convergence problem when the size of training samples is small. PSNN can take advantage of the smoothed solution space through the use of pseudo samples. PSNN has a focus on the quantity problem in training, whereas, methods stressing the quality of training samples is presented in this paper to improve further the performance of PSNN. It is evident that typical samples and highly correlated features help in training. In this paper, therefore, kernel density estimation is used to select typical samples and correlation factor is introduced to select features, which can improve the performance of PSNN. Debris flow data set is used to demonstrate the usefulness of the proposed methods.

• Interdisciplinary Bio Central
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• v.4 no.1
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• pp.2.1-2.7
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• 2012

Introduction: Histone deacetylases (HDAC) are a class of enzymes that remove acetyl groups from ${\varepsilon}$-N-acetyl lysine amino acids of histone proteins. Their action is opposite to that of histone acetyltransferase that adds acetyl groups to these lysines. Only few HDAC inhibitors are approved and used as anti-cancer therapeutics. Thus, discovery of new and potential HDAC inhibitors are necessary in the effective treatment of cancer. Materials and Methods: This study proposed a method using support vector machine (SVM) to classify HDAC8 inhibitors and non-inhibitors in early-phase virtual compound filtering and screening. The 100 experimentally known HDAC8 inhibitors including 52 inhibitors and 48 non-inhibitors were used in this study. A set of molecular descriptors was calculated for all compounds in the dataset using ADRIANA. Code of Molecular Networks. Different kernel functions available from SVM Tools of free support vector machine software and training and test sets of varying size were used in model generation and validation. Results and Conclusion: The best model obtained using kernel functions has shown 75% of accuracy on test set prediction. The other models have also displayed good prediction over the test set compounds. The results of this study can be used as simple and effective filters in the drug discovery process.

• Journal of the Korean Ceramic Society
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• v.44 no.2 s.297
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• pp.124-131
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• 2007

In this study, first the ADU gel particle, an intermediate for final $UO_2$ kernel of a HTGR nuclear fuel, was prepared from sol-gel method using the broth solution which was made by mixing of the uranyl nitrate, poly vinyl alcohol and tetra-hydrofurfuryl alcohol. The prepared dried-ADU gel particles were converted to the $UO_2\;via\;UO_3$ from thermal treatment with the 4% $H_2$ atmosphere. The sizes of the spherical liquid droplets appeared $1900{\sim}2100{\mu}m$, and the harmony between the flow rate of the broth solution and the frequency and the amplitude of a vibrating system are important factors for the spherical ADU gel particles via the mono size spherical droplets. From the XRD and FT-IR analyses, the prepared ADU gel particles were judged to be a $UO_3{\cdot}xNH_3{\cdot}yH_2O$ form, and the most important factor during the thermal treatment of the dried-ADU gel particle must be avoided a rapidly heating rate in the range of $180{\sim}400^{\circ}C$, and the heating rate should be kept below $5^{\circ}C/min$.

• Journal of the Korean Wood Science and Technology
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• v.38 no.6
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• pp.498-506
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• 2010

To use domestic softwood for structural lumber, appropriate grading system for quality, production and distribution condition of domestic lumber should be prepared. Kim et al. developed an automatic image processing system for grading domestic structural lumber (2009a and b). This study was carried out to investigate optimal image merging conditions for improving performance of image input system which is the key technique of image processing system, developed in the previous paper. To merge digital images of Korean larch lumber, choosing the green channel information of obtained image data showed the most accurate merging performance. As a pre-treatment process, applying Y-derivative Sharr's kernel filter could improve the image merging accuracy, but the effect of camera calibration was imperceptible. The optimal size of template image was verified as 30 pixel widths and 150 pixel heights. When applying the above mentioned conditions, the error length of images was 3.1 mm and the processing time was 9.7 seconds in average.

• Journal of Digital Convergence
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• v.11 no.11
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• pp.421-427
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• 2013

Disk Cache Manager(DCM), a functional server of microkernel based, to improve the I/O power of shared disks is designed and implemented in this work. DCM interfaces other different servers with message passing through ports by serving as a system actor the multi-thread mode on the Minix3 micro-kernel. DCM proposed in this paper uses the shared disk logically as a Seven Disk and Sodd Disk to enable parallel I/O. DCM enables the efficient placement of disk data because it raises disk cache hit-ratio by increasing the cache size when the utilization of the particular disk is high. Through experimental results, we show that DCM is quite efficient for a shared disk with higher utilization.

• Progress in Medical Physics
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• v.7 no.1
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• pp.9-17
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• 1996

The response function of ionization chambers are measured in the narrow radiation field Nominal photon energies are 4MV, 6MV and 15MV. the Radii of the chambers are 0.5cm～3.05cm and the field size is 0.2$\times$20$\textrm{cm}^2$. The measurements are taken in the water phantom at 10cm depth. The beam kernel (radiation distribution profile) for narrow radiation field in the phantom are obtained from Monte Carlo simulation (EGS4, Electron Gamma Shower 4). The beam kernel components in the measured chamber response function are deconvolved in order to get the ideal chamber response function of the $\delta$-shaped function radiation field. The chamber response functions have energy dependent tendency before deconvolution, while they show energy invariant properties, after the components of beam kernels are removed by deconvolution method.

• Journal of the Optical Society of Korea
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• v.19 no.2
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• pp.136-143
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• 2015

Image deblurring by a deconvolution method requires accurate knowledge of the blur kernel. Existing point spread function (PSF) models in the literature corresponding to lens aberrations and defocus are either parameterized and spatially invariant or spatially varying but discretely defined. In this paper, a parameterized model is developed and presented for a PSF which is spatially varying due to lens aberrations and defocus in an imaging system. The model is established from the Seidel third-order aberration coefficient and the Hu moment. A skew normal Gauss model is selected for parameterized PSF geometry structure. The accuracy of the model is demonstrated with simulations and measurements for a defocused infrared camera and a single spherical lens digital camera. Compared with optical software Code V, the visual results of two optical systems validate our analysis and proposed method in size, shape and direction. Quantitative evaluation results reveal the excellent accuracy of the blur kernel model.

• Journal of Environmental Science International
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• v.27 no.8
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• pp.665-675
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• 2018

The purpose of this study was to identify the characteristics of the home range and habitat use of Rhinolophus ferrumequinum individuals that inhabit urban areas. The bats were tracked using GPS tags. For analysis of the home rage, Minimum Convex Polygon (MCP) and Kernel Home Range (KHR) methods were used. The landscape types of all positional information were analyzed using ArcGIS 9.3.1 (ESRI Inc.). The average home range of 16 R. ferrumequinum individuals was $68.63{\pm}25.23ha$, and the size of the overall home range for the females ($85.49{\pm}25.40ha$) was larger than that for the males ($51.76{\pm}8.30ha$). The highest average home range for the males was found in August ($61.21{\pm}0.01ha$), whereas that for the females was found in September ($112.27{\pm}5.94ha$). The size of 50% KHR ranged from a minimum of 13.26 ha to a maximum of 31.00 for the males and a minimum of 8.02 ha to a maxinum of 42.16 ha for the females, showing no significant differences between the two sexes. In addition, males and females showed no differences in the size of 50% KHR in the monthly comparisons. However, the females showed differences in the size of their core area between periods before and after giving birth. The comparisons between 100% MCP and 50% KHR showed that the types of habitats used by R. ferrumequinum were mostly forest areas, including some farmlands. In addition, comparisons with a land cover map showed that the proportion of broad-leaved forests was the highest, followed by that of mixed forests.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2004.04a
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• pp.471-475
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• 2004

LiDAR의 표고점 데이터에서 건물, 수목 등과 같이 주위보다 높은 고도 값을 가지는 대상물을 제거하여 DEM을 생성하기 위한 여러 가지 필터링 기법들이 개발되고 있으며 대표적인 필터링 방법으로는 분산을 이용한 linear prediction 기법, 주변 점들과의 경사관계를 이용한 slope-based 기법, morphology 필터, dual rank 필터 등이 있다. 이러한 기법들은 커널(kernel)의 크기를 대상 지역에 맞도록 사용자가 직접 지정해주어야 하고, 건물의 크기가 다양한 지역에 적용하기 위해서는 가변 크기(variable size)의 커널을 필요로 한다. 본 연구에서는 다양한 크기의 건물이 존재하는 지역에 대하여 커널의 크기를 변화시키지 않고 필터링을 수행하는 새로운 커널 연산 기법을 제안하였다. 또한 기존 필터링 기법에서는 커널에 의해 갱신된 연산값이 다음 연산에 반영되지 않으나 본 연구에서는 갱신된 값이 바로 다음 연산에 반영되도록 하였다. 건물과 수목 등을 제거하기 위하여 주변 화소와의 높이 차를 이용하였으며 대상물이 제거된 부분은 주변 화소를 이용하여 보간하였다.