• Clinical and Experimental Reproductive Medicine
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• v.46 no.1
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• pp.8-13
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• 2019

Objective: Density gradient centrifugation (DGC) is frequently used to isolate high-motility fractions of spermatozoa. We compared the efficacy of four DGC media in terms of the percentage of morphologically normal spermatozoa, DNA fragmentation level, and hyaluronic acid (HA) binding ability. Methods: Thirty men with a total motile spermatozoa count > 80 million participated. Semen samples were divided into four aliquots, which were processed using PureSperm, PureCeption, Sidney, and SpermGrad media, respectively. The DNA fragmentation level was measured using the Halosperm assay kit and HA binding ability was measured using the HBA assay kit. Results: The mean percentage of morphologically normal spermatozoa was significantly enhanced after DGC using all four media (10.3%, 9.9%, 9.8%, and 10.7%, respectively; p< 0.05 for each when compared with 6.9% in raw semen). The DNA fragmentation level was significantly reduced after DGC using PureSperm, PureCeption, and SpermGrad media (6.0%, 6.5%, and 4.9%, respectively; p< 0.05 for each when compared with 11.2% in raw semen), but not after DGC using Sidney media (8.5%, p> 0.05). HA binding ability did not change after DGC using any of the four media. Conclusion: The four media were equally effective for obtaining a sperm fraction with highly motile, morphologically normal sperm. PureSperm, PureCeption, and SpermGrad media were equally effective for acquiring a sperm fraction with less DNA fragmentation.

• Proceedings of the KIEE Conference
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• 2000.07e
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• pp.22-25
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• 2000

Time dependent ozone generation characteristics of some oxide layers grown by ozone on the surface of corona discharge wires have been investigated experimentally in air ambience. Four wires of stainless steel, iron, silver and copper were used for the corona discharge wire of an ozone generator. And the effect of the metal oxide layers on ozone generation was studied and the contamination morphology of each layers was characterized. With the SEM images and the EDS spectra, it was found that all the surface of the corona wire were oxidized by the generated ozone and contaminated by airborne particles through the gradient force. As a result, the morphology and the electrical property of metal oxide layer grown on corona wire surface influenced on ozone generation characteristics i.e. discharge mechanisms.

• Proceedings of the Korea Information Processing Society Conference
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• 2004.11a
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• pp.847-850
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• 2004

본 논문에서는 모폴로지(Morphology) 재구성(Reconstruction)과 비선형 확산(Non-Linear Diffusion)을 이용하여 칼라 영상을 유사한 영역으로 분할하는 방법을 제안한다. 초기에 RGB 영상을 LUV 색상 공간으로 전환하고, 그 색상공간에 모폴로지를 응용한 재구성(Reconstruction)에 의한 닫힘(Closing) 연산과 비선형 확산(Non-Linear Diffusion)을 적용하여 잡음을 제거한 실험 영상을 획득한다. 이 영상에서 워터쉐드 알고리즘을 위한 칼라 영상의 기울기(Gradient) 정보를 획득하고, 그 영상에 마커(Marker) 정보를 이용한 워터쉐드(Watershed) 알고리즘을 적용하여 영상을 효과적으로 분할한다. 칼라 영상을 대상으로 한 실험에서 제안 방법이 영상을 효과적으로 분할함을 확인 하였다.

• Advances in aircraft and spacecraft science
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• v.8 no.1
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• pp.31-51
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• 2021

Selective laser melting (SLM), one of the most widely used powder bed fusion (PBF) additive manufacturing (AM) technology, enables the fabrication of customized metallic parts with complex geometry by layer-by-layer fashion. However, SLM inherently poses several problems such as the discontinuities in the molten track and the steep temperature gradient resulting in a high degree of residual stress. To avoid such defects, thisstudy proposes a temperature thread multiscale model of SLM for the evaluation of the process at different scales. In microscale melt pool analysis, the laser beam parameters were evaluated based on the predicted melt pool morphology to check for lack-of-fusion or keyhole defects. The analysis results at microscale were then used to build an equivalent body heat flux model to obtain the residual stress distribution and the part distortions at the macroscale (part level). To identify the source of uneven heat dissipation, a liquid lifetime contour at macroscale was investigated. The predicted distortion was also experimentally validated showing a good agreement with the experimental measurement.

• Proceedings of the Korean Society of Crop Science Conference
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• 2022.10a
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• pp.150-150
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• 2022

Plant reproduction associated with crop yields is highly vulnerable to global climate change components such as high and cold temperatures. The objectives of this study were to determine the effects of season-high exposure to temperature treatments in pollen morphology on Adzuki bean (V. angularis) and Mung bean (V. radiate). V. angularis and V. radiata were treated at high temperatures in the high temperature gradient greenhouse designed to cause temperature deviation. The pollen shapes treated at high temperature were compared by an electron scanning microscope. As a result, it was confirmed that the number of abnormal pollens morphology at high temperature was the least in V. radiata, and V. angularis was vulnerable to high temperatures. Also, it was found that the number of abnormal pollen morphology atT4 (Con +5~6℃) varied according to the cultivars of V. angularis. Therefore, the differences in Vigna species or cultivars with thermo-tolerance in pollen morphology to high temperature are projected to occur in the changeable future climate.

• Journal of the Korean Association of Geographic Information Studies
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• v.8 no.4
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• pp.91-101
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• 2005

To determine stream network and watershed boundary using DEM, it is necessary to remove sink and flat area in proper way. There are filling algorithm and breaching algorithm to remove sink and Jenson and Domingue algorithm, relief algorithm and combined gradient algorithm to determine flow direction in flat area. In this study, the algorithms are reviewed. The computer program which uses filling algorithm with breaching algorithm and combined gradient algorithm to remove errors in DEM is developed. The results from this program are compared with Arc/Info which uses filling algorithm and Jenson and Domingue algorithm. The characteristics of stream network extracted from the DEM are analyzed. They are compared with the stream from NGIS map for stream morphology and characters by stream order to examine the value of this study.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.6
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• pp.907-917
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• 2023

Recently, a self-driving car have applied deep learning technology to advanced driver assistance system can provide convenience to drivers, but it is shown deep that learning technology is vulnerable to adversarial evasion attacks. In this paper, we performed five adversarial evasion attacks, including MI-FGSM(Momentum Iterative-Fast Gradient Sign Method), targeting the object detection algorithm YOLOv5 (You Only Look Once), and measured the object detection performance in terms of mAP(mean Average Precision). In particular, we present a method applying morphology operations for YOLO to detect objects normally by removing noise and extracting boundary. As a result of analyzing its performance through experiments, when an adversarial attack was performed, YOLO's mAP dropped by at least 7.9%. The YOLO applied our proposed method can detect objects up to 87.3% of mAP performance.

• Journal of The Korean Astronomical Society
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• v.40 no.1
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• pp.9-16
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• 2007

We examine the morphology and luminosity distribution of a strongly warped spiral galaxy PGC 20348 by conducting a detailed BVI CCD surface photometry using BOAO 1.8m telescope. The radial surface brightness shows a break at warp radius $(r_{\omega})$ with a shallow gradient in the inner disk and a steeper gradient in the outer disk. The luminosity of east side of the disk is ${\sim}0.5$ mag fainter than the west side at r > $r_{\omega}$. The reason for the asymmetric luminosity distribution is thought to be the asymmetric flarings that result in the formation of a large diffuse region at the edge of the east disk and a smaller diffuse region at the west disk. The vertical luminosity profiles show a thick disk component whose scale heights increase with increasing galactocentric distances. The warp of PGC 20348 seems to be made by the tidal interactions with the two massive companion galaxies since the flarings and radial increase of disk scale heights are thought to be general properties of tidally perturbed disks. According to the colors of the two clumps inside the diffuse region at the edge of the east disk, they seem to be sites of active star formation triggered by tidal forces from the companion galaxies.

• Environmental Engineering Research
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• v.15 no.1
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• pp.3-7
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• 2010

To better understand the ecology of tetrade forming organisms (TFOs) floating in a large amount of dairy wastewater treatment plant (WWTP) effluent (sequencing batch reactor [SBR]) during the inefficient phosphorus (P) removal process of an enhanced biological P removal system, the TFOs from the effluent of a full scale WWTP were separated and attempts made to culture the TFOs in presence/absence of oxygen. The intact TFOs only grew aerobically in the form of unicellular short-rods. Furthermore, to identify the intact TFOs and unicellular short-rods the DNAs of both were extracted, analyzed using their denaturing gradient gel electrophoresis (DGGE)-profiles and then sequenced. The TFOs and unicellular short-rods exhibited the same banding pattern in their DGGE-profiles, and those sequencing data resulted in their identification as Acinetobacter sp. The intact TFOs appeared in clumps and packages of tetrade cells, and were identified as Acinetobacter sp., which are known as strict aerobes and efficient P-removers. The thick layer of extracellular polymeric substance surrounding Acinetobacter sp. may inhibit phosphate uptake, and the cell morphology of TFOs might subsequently be connected with their survival strategy under the anaerobic regime of the SBR system.

• Transactions of Materials Processing
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• v.32 no.2
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• pp.74-80
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• 2023

A deformation behavior of commercially pure titanium (CP-Ti) is highly dependent on material and processing parameters, such as deformation temperature, deformation direction, and strain rate. This study aims to predict the multivariable and nonlinear tensile behavior of CP-Ti using machine learning based on three algorithms: artificial neural network (ANN), light gradient boosting machine (LGBM), and long short-term memory (LSTM). The predictivity for tensile behaviors at the cryogenic temperature was lower than those in the room temperature due to the larger data scattering in the train dataset used in the machine learning. Although LGBM showed the lowest value of root mean squared error, it was not the best strategy owing to the overfitting and step-function morphology different from the actual data. LSTM performed the best as it effectively learned the continuous characteristics of a flow curve as well as it spent the reduced time for machine learning, even without sufficient database and hyperparameter tuning.