• 한국해양학회지
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• v.28 no.2
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• pp.114-120
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• 1993

Numerical method of nonlinear regression was introduced to characterize grain-size distribution more effectively than using the traditional textural parameters. This technique proved critical particularly to multimodal size distributions, as exemplified by samples from Cheju strait continental shelf. Grain-size analysis of samples collected from the Cheju Strait continental shelf reveals that 86% of the grain-size distributions are multimodal. As multimodal grain-size distribution deviates from the statistical (log) normal distribution, the grain-size parameters traditionally used in sediment studies do not describe the distribution efficiently. Therefore, the use of grain-size curves into elementary normal component curves was used. Means and standard deviations of 387 decomposed normal components were decided by a decomposition method (nonlinear least square regression) from 167 size curves of the Cheju Strait sediments. The mean values of decomposed normal components show peaks at 1-3 phi and 8-9 phi size classes. The plot of mean values of the coarse fraction normal components on the map shows a characteristic and complex areal distribution. On the basis of the areal distribution of the mean values of the components and that of isopach of total Plenipotence sediment, the areal distribution of layers composing a transgressive sand of Late Plenipotence age were revealed.

• Food Science of Animal Resources
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• v.33 no.2
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• pp.281-286
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• 2013

Salmonella Gallinarum (SG) is known as an important pathogen that causes fowl typhoid in chickens. To investigate SG outer-membrane proteins (OMPs) as a vaccine candidate, we used proteomic mapping and database analysis techniques with extracted OMPs. Also, extracted OMPs were evaluated in several aspects to their safety, immune response in their host and protective effects. Our research has established a proteomic map and database of immunogenic SG-OMPs used as inactive vaccine against salmonellosis in chickens. A total of 22 spots were detected by 2-dimensional gel electrophoresis and immunogenic protein analysis. Eight spots were identified by Matrix-Assisted Laser Desorption/Ionization-Time of Flight-Mass spectrometry (MALDI-TOF-MS) and peptide mass fingerprinting (PMF) and categorized into four different types of proteins. Among these proteins, OmpA is considered to be an immunogenic protein and involved in the hosts' immune system. To estimate the minimum safety dose in chickens, 35 brown layers were immunized with various concentrations of OMPs, respectively. Consequently, all chickens immunized with more than a $50{\mu}g$ dose were protected against challenges. Moreover, intramuscular administration of OMPs to chickens was more effective compared to subcutaneous administration. These results suggest that the adjuvanted SG-OMP vaccine not only induces both the humoral and cellular immune response in the host but also highly protects the hosts' exposed to virulent SG with $50{\mu}g$ OMPs extracted by our method.

• Spatial Information Research
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• v.18 no.2
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• pp.35-44
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• 2010

This research intended to estimate the damage information from torrential rainfalls using airphotos and spatial data which have been rapidly increasing their applicability recently. The study area was Bonghwagun of Gyungsangbukdo where the large amount of damages were occurred from torrential rainfall in July, 2008. For this study, the database was constructed for the study area by collecting usable data. The interpretable items from the airphotos of 40cm spatial resolution were selected. Also, the useful GIS layers such as road were selected in the digital map to extract the damage information more accurately and rapidly. The damaged area was easily identified through the comparison of pre- and post-disaster airphotos. The recovery cost was estimated by applying unit cost to the damaged area. GIS's overlay function was used to extract the damage information of for individual items damaged. The method for extracting damages information using GIS and airphotos could be more efficient and cost effective in case of relatively wide and unapproachable damaged areas. It is also expected that the method using high resolution imagery would lead to minimize the secondary damages as well since it can facilitate the damage estimation within short period of time thereby supporting early securing budget for recovery.

• The Journal of Engineering Research
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• v.5 no.1
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• pp.89-107
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• 2004

This study has tried to develop the modified DRASTIC Model by supplying the parameters, such as structural lineament density and landuse, into conventional DRASTIC model, and to predict the potential of groundwater contamination using GIS in Whanam 2 Area, Gyeonggi Province, Korea. Since the aquifers in Korea is generally through the joints of rock-mass in hydrogeological environment, lineament density affects to the behavior of groundwater and contaminated plumes directly, and land-use reflect the effect of point or non-point source of contamination indirectly. For the statistical analysis, lattice layers of each parameter were generated, and then level of confidence was assessed by analyzing each correlation coefficient. Composite contamination map was achieved as a final result by comparing modified DRASTIC potential and the amount of generation load of several contaminant sources logically. The result could suggest the predictability of the area of contamination potential on the respects of hydrogeological aspect and water quality.

• Journal of Convergence for Information Technology
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• v.11 no.10
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• pp.45-52
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• 2021

In this paper, we proposed an Atrous Residual U-Net (AR-UNet) to improve the segmentation accuracy of semantic segmentation method based on U-Net. The U-Net is mainly used in fields such as medical image analysis, autonomous vehicles, and remote sensing images. The conventional U-Net lacks extracted features due to the small number of convolution layers in the encoder part. The extracted features are essential for classifying object categories, and if they are insufficient, it causes a problem of lowering the segmentation accuracy. Therefore, to improve this problem, we proposed the AR-UNet using residual learning and ASPP in the encoder. Residual learning improves feature extraction ability and is effective in preventing feature loss and vanishing gradient problems caused by continuous convolutions. In addition, ASPP enables additional feature extraction without reducing the resolution of the feature map. Experiments verified the effectiveness of the AR-UNet with Cityscapes dataset. The experimental results showed that the AR-UNet showed improved segmentation results compared to the conventional U-Net. In this way, AR-UNet can contribute to the advancement of many applications where accuracy is important.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.6
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• pp.483-497
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• 2018

Image mosaicking, which combines several images into one image, is effective for analyzing images and important in various fields of spatial information such as a continuous image map. The crucial processes of the image mosaicking are optimal seamline determination and color correction of mosaicked images. In this study, the overlap regions were determined by SURF (Speeded Up Robust Features) for image matching. Based on the characteristics of the edges extracted by Canny filter, seamline candidates were selected from classified edges with their characteristics, and the edges were connected by using Dijkstra algorithm. In particular, anisotropic filter and image pyramid were applied to extract reliable seamlines. In addition, it was possible to determine seamlines effectively and efficiently by utilizing building and road layers from digital maps. Finally, histogram matching and seamline feathering were performed to improve visual quality of the mosaicked images.

• Korean Journal of Heritage: History & Science
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• v.48 no.4
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• pp.44-61
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• 2015

Mural tomb in Goa-ri(Goryeong) built in the 6th Century Gaya period investigated precisely by the scientific method. They were used to optical equipments for investigation and made a damage map according to the damaging types. The mortar layer was mostly exfoliated from the rest of the wall except for the burial chamber ceiling and corridor ceiling. Also painting layers rarely not observed. Most of the paintings were damaged except lotus painting in burial chamber ceiling. Various damage types that exfoliation, earthen dirt, film coating were found in murals. Damage factors of mural were the porous characteristics of mortar layer and the movement of moisture in the murals. They were caused physical damage such as crack, exfoliation. It was getting worse and causing to secondary damage like earthen dirt, film coating.

• Journal of Drive and Control
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• v.20 no.2
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• pp.15-23
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• 2023

In this study, two-dimensional location of crops for auto weeding was detected using deep learning. To construct a dataset for soybean detection, an image-capturing system was developed using a mono camera and single-board computer and the system was mounted on a weeding robot to collect soybean images. A dataset was constructed by extracting RoI (region of interest) from the raw image and each sample was labeled with soybean and the background for classification learning. The deep learning model consisted of four convolutional layers and was trained with a weakly supervised learning method that can provide object localization only using image-level labeling. Localization of the soybean area can be visualized via CAM and the two-dimensional position of the soybean was estimated by clustering the pixels associated with the soybean area and transforming the pixel coordinates to world coordinates. The actual position, which is determined manually as pixel coordinates in the image was evaluated and performances were 6.6(X-axis), 5.1(Y-axis) and 1.2(X-axis), 2.2(Y-axis) for MSE and RMSE about world coordinates, respectively. From the results, we confirmed that the center position of the soybean area derived through deep learning was sufficient for use in automatic weeding systems.

• Korean Journal of Remote Sensing
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• v.39 no.3
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• pp.339-353
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• 2023

As the availability of high-resolution satellite imagery increases, improvement of positioning accuracy of satellite images is required. The importance of orthorectified images is also increasing, which removes relief displacement and establishes true localization of man-made structures. In this paper, we performed automated extraction of building rooftops and total building areas within original satellite images using the existing building height database. We relocated the rooftop sin their true position and generated an orthorectified building layer. The extracted total building areas were used to blank out building areas and generate true orthographic non-building layer. A final orthorectified image was provided by overlapping the building layer and non-building layer.We tested the proposed method with KOMPSAT-3 and KOMPSAT-3A satellite images and verified the results by overlapping with a digital topographical map. Test results showed that orthorectified building layers were generated with a position error of 0.4m.Through the proposed method, the feasibility of automated true orthoimage generation within dense urban areas was confirmed.

• Journal of Advanced Navigation Technology
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• v.27 no.5
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• pp.495-501
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• 2023

P-3C/K aircraft for maritime patrols that Republic of Korea Navy is using, is equipped with a variety of sensors and communication devices. Collected data from the aircraft is managed as tactical information by flight operators and stored. When the flight mission is completed, this information is transferred to tactical support center on the ground and played back or used for follow-up work through a analysis tool. During a flight mission, there are tens of thousands of detection objects within an hour in KADIZ (Korea air defense identification zone). In contrast, in TSD (tactical situation display), which displays a map when using the analysis tool, all detected objects are expressed as symbols. The increase in display symbols has a significant impact on the TSD image updating and consequently interferes with the smooth operation of operators. In this paper, we propose applying multiple threads and multiple layers to improve the performance of existing TSD. And the performance improvement is proven through the execution results.