• The Korean Journal of Archival Studies
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• no.32
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• pp.177-217
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• 2012

The National Archives of Korea(NAK) has a mission to ingest large-scaled digital records and information from a number of different government agencies annually from 2015. There are important issues related to the digital records and information transfer between NAK and agencies, and one of them is how to configure deployment of digital repositories for the archives management systems. The purpose of this paper is to offer the way to design it by examining the checkpoints through the whole life cycle of digital records and information in the archives management systems and calculating the amount of ingested digital records and information to the systems in 2015 and deploying the digital repositories configured according to the amount the records and information. Firstly, this paper suggests that the archives management systems in NAK should be considered and examined into at least three different parts called Ingest tier, Preservation tier and Access tier in aspects to the characteristics of the flow and process of the digital records and information. Secondly, as a results of the calculation the amount of the digital records and information ingested to the archives management systems in 2015 is sum up to around 2.5 Tera bytes. This research draws several requirements related to the large-scaled data and bulk operations which should be satisfied by the database or database management system implemented on to the archives management systems. Thirdly, this paper configures digital repositories deployment according to the characteristics of the three tiers respectively. This research triggers discussion in depth and gives specific clues about how to design the digital repositories in the archives management systems for preparing the year of 2015.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.6
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• pp.511-519
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• 2020

For camera calibration, a checkerboard is generally used to determine the principal point, focal length, and lens distortions. The checkerboard has a planar and three-dimensional shape, and camera calibration parameters are affected by the size of the checkerboard, the placement of the target, and the number of target points. In this study, the accuracies of the types of checkerboards were compared using checkpoints for stereo camera calibration, and the purpose of this study was to propose the best performance checkerboard. The checkerboard with large flat shape showed comparatively high accuracy through comparison with the check points. However, due to the size of the checkerboard, it was inconvenient to move and rotate, and there was a disadvantage in that it was difficult to shoot so that the target points could all appear in the stereo camera. The checkerboard, which was manufactured in a small size in a flat shape, was easy to move and rotate but had the lowest three-dimensional accuracy. The checkerboard with targets with height values had the hassle of having to determine the three-dimensional coordinates of the target points by using observation equipment for camera calibration, but it was small in size, convenient to move and rotate, and showed the highest three-dimensional accuracy.

• Journal of the Korean Association of Geographic Information Studies
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• v.24 no.1
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• pp.1-11
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• 2021

Detection of surface water features including river, wetland, reservoir from the satellite imagery can be utilized for sustainable management and survey of water resources. This research compared the water indices derived from the multispectral bands and the machine learning technique for detecting the surface water features from he Landsat-8 satellite image acquired in Daegu through the following steps. First, the NDWI(Normalized Difference Water Index) image and the MNDWI(Modified Normalized Difference Water Index) image were separately generated using the multispectral bands of the given Landsat-8 satellite image, and the two binary images were generated from these NDWI and MNDWI images, respectively. Then SVM(Support Vector Machine), the widely used machine learning techniques, were employed to generate the land cover image and the binary image was also generated from the generated land cover image. Finally the error matrices were used for measuring the accuracy of the three binary images for detecting the surface water features. The statistical results showed that the binary image generated from the MNDWI image(84%) had the relatively low accuracy than the binary image generated from the NDWI image(94%) and generated by SVM(96%). And some misclassification errors occurred in all three binary images where the land features were misclassified as the surface water features because of the shadow effects.

• Korean Journal of Remote Sensing
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• v.36 no.6_1
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• pp.1393-1405
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• 2020

UAV (Unmanned Aerial Vehicle) can acquire high-resolution images due to low-altitude flight, and it can be photographed at any time. Therefore, the UAV images can be updated at any time in map production. Due to these advantages, studies on the possibility of producing large-scale digital maps using UAV images are actively being conducted. Precise digital maps can be used as base data for digital twins or smart cites. For producing a precise digital map, precise sensor modeling using GCPs (Ground Control Points) must be preceded. In this study, geometric models of UAV images were established through a precision sensor modeling algorithm developed in house. Then, a digital map by stereo plotting was produced to evaluate the possibility of large-scale digital map. For this study, images and GCPs were acquired for Ganseok-dong, Incheon and Yeouido, Seoul. As a result of precision sensor modeling accuracy analysis, high accuracy was confirmed within 3 pixels of the average error of the checkpoints and 4 pixels of the RMSE was confirmed for the two study regions. As a result of the mapping accuracy analysis, it satisfied the 1:1,000 mapping accuracy announced by the NGII (National Geographic information Institute). Therefore, the precision sensor modeling technology suggested the possibility of producing a 1:1,000 large-scale digital map by UAV images.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.6
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• pp.549-554
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• 2021

Precise 3D road geospatial information is the basic infrastructure for autonomous driving and is essential data for safe autonomous driving. MMS (Mobile Mapping System) is being used as equipment for road spatial information construction, and related research is being conducted. However, there are insufficient studies to analyze the effect of the baseline reference point distance, which is an important factor in the accuracy of the MMS outcome, on the accuracy of the outcome. Therefore, in this study, the accuracy of the data acquired using MMS by reference point distance was analyzed. Point cloud data was constructed using MMS for the road in the study site. For data processing, 4 data were constructed considering the distance from the reference point for MMS data, and the accuracy was analyzed by comparing the results of 12 checkpoints for accuracy evaluation. The accuracy of the MMS data showed a difference of -0.09 m to 0.11 m in the horizontal direction and 0.04 m to 0.19 m in the height direction. The error in the vertical direction was larger than that in the horizontal direction, and it was found that the accuracy decreased as the distance from the reference point increased. In addition, as the length of the road increases, the distance from the reference point may vary, so additional research is needed. If the accuracy evaluation of the method using multiple reference points is made in the future, it will be possible to present an effective method of using reference points for the construction of precise road spatial information.

• Korean Journal of Clinical Laboratory Science
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• v.56 no.1
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• pp.73-84
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• 2024

A pulsed electromagnetic field (PEMF) enhances the efficacy of several anticancer drugs. Doxorubicin (DOX) is an anticancer agent used to treat various malignancies, including breast cancer. This study examined whether a PEMF increases the anticancer effect of DOX on MCF-7 human breast cancer cells and elucidated the underlying mechanisms affected by PEMF stimulation in DOX-treated MCF-7 human breast cancer cells. A cotreatment with DOX and a PEMF potentiated the reduction in MCF-7 cell viability compared to the treatment with DOX alone. The PEMF elevated DOX-induced G1 arrest by affecting cyclin-dependent kinase 2 phosphorylation and the expression of G1 arrest-related molecules, including p53, p21, cyclin E2, and polo like kinase 1. In addition, PEMF increased the DOX-induced upregulation of proapoptotic proteins, such as Fas and Bcl-2-associated X, and the downregulation of antiapoptotic proteins, including myeloid leukemia 1 and survivin. PEMF promoted the DOX-induced activation of caspases-8, -9, and -7 and poly (adenosine diphosphate-ribose) polymerase cleavage in MCF-7 cells. In conclusion, PEMF enhances the anticancer activity in DOX-treated MCF-7 breast cancer cells by increasing G1 cell cycle arrest and caspase-dependent apoptosis. These findings highlight the potential use of a PEMF as an adjuvant treatment for DOX-based chemotherapy against breast cancer.

• Journal of the Korean Association of Geographic Information Studies
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• v.24 no.3
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• pp.73-82
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• 2021

Rural roads are the significant infrastructure for developing and managing the rural areas, hence the utilization of the remote sensing datasets for managing the rural roads is necessary for expanding the rural transportation infrastructure and improving the life quality of the rural residents. In this research, the two different methods such as image classification and image segmentation were compared for mapping the rural road based on the given high-resolution satellite image acquired in the rural areas. In the image classification method, the deep learning with the multiple neural networks was employed to the given high-resolution satellite image for generating the object classification map, then the rural roads were mapped by extracting the road objects from the generated object classification map. In the image segmentation method, the multiresolution segmentation was employed to the same satellite image for generating the segment image, then the rural roads were mapped by merging the road objects located on the rural roads on the satellite image. We used the 100 checkpoints for assessing the accuracy of the two rural roads mapped by the different methods and drew the following conclusions. The image segmentation method had the better performance than the image classification method for mapping the rural roads using the give satellite image, because some of the rural roads mapped by the image classification method were not identified due to the miclassification errors occurred in the object classification map, while all of the rural roads mapped by the image segmentation method were identified. However some of the rural roads mapped by the image segmentation method also had the miclassfication errors due to some rural road segments including the non-rural road objects. In future research the object-oriented classification or the convolutional neural networks widely used for detecting the precise objects from the image sources would be used for improving the accuracy of the rural roads using the high-resolution satellite image.