• Tunnel and Underground Space
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• v.33 no.6
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• pp.508-518
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• 2023

This paper presents a new approach for the automatic mapping of discontinuities in a tunnel face based on its 3D digital model reconstructed by LiDAR scan or photogrammetry techniques. The main idea revolves around the identification of discontinuity areas in the 3D digital model of a tunnel face by segmenting its 2D projected images using a deep-learning semantic segmentation model called U-Net. The proposed deep learning model integrates various features including the projected RGB image, depth map image, and local surface properties-based images i.e., normal vector and curvature images to effectively segment areas of discontinuity in the images. Subsequently, the segmentation results are projected back onto the 3D model using depth maps and projection matrices to obtain an accurate representation of the location and extent of discontinuities within the 3D space. The performance of the segmentation model is evaluated by comparing the segmented results with their corresponding ground truths, which demonstrates the high accuracy of segmentation results with the intersection-over-union metric of approximately 0.8. Despite still being limited in training data, this method exhibits promising potential to address the limitations of conventional approaches, which only rely on normal vectors and unsupervised machine learning algorithms for grouping points in the 3D model into distinct sets of discontinuities.

• Journal of the Korean Geographical Society
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• v.42 no.4
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• pp.582-600
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• 2007

In a long history of geography, a variety of regional concepts have been suggested to represent the particular situations in each period. Today, post-modem situations, characterized by the development of capitalism and globalization, demand a new variety of regional concepts. The regional characteristics, such as social relations, institutional systems, ideologies and symbolism, are now perceived basically on the level of subjectivity. Currently, it is the most urgent task to integrate many conflicting opinions among a variety of subjects into the one that would seek a voluntary consent from the majority of regional residents. In this paper, it is suggested that the concept of identity is the most efficient in examining and explaining the post-modem trend of a region: variability, subjectivity, mobility, changeability, Finally, it is suggested that a special attention should be paid to the role of institutions, that is institutionalization, in the construction of regional identity, to understand and interpret the cultural-historical aspect of a regional change.

• Investigative Magnetic Resonance Imaging
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• v.9 no.2
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• pp.117-133
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• 2005

For identifying the pathological findings in magnetic resonance images (MRIs), normal anatomical structures in MRIs should be identified in advance. For studying the anatomical structures in MRIs, a learning tool that includes the followings is necessary. First, MRIs of the entire body; second, horizontal, coronal, and sagittal MRIs; third, segmented images corresponding to the MRIs; fourth, three dimensional (3D) images of the anatomical structures in the MRIs; fifth, software incorporating the MRIs, segmented images, and 3D images. Such a learning tool, however, is hard to obtain. Therefore, in this research, such a learning tool which helps medical students and doctors study the normal anatomical structures in MRIs was made as follows. A healthy young Korean male adult with standard body shape was selected. Six hundred thirteen MRIs of the entire body were scanned (slice thickness 3 mm, interslice gap 0 mm, field of view 480 mm${\times}$480 mm, resolution 512${\times}$512, T1 weighted), and transferred to the personal computer. Sixty anatomical structures in the MRIs were segmented to make segmented images. Coronal, sagittal MRIs and coronal, sagittal segmented images were made. On the basis of the segmented images, forty-seven anatomical structures 3D images were made by manual surface reconstruction method. Software incorporating the MRIs, segmented images, and 3D images was composed. This learning tool that includes horizontal, coronal, sagittal MRIs of the entire body, corresponding segmented images, 3D images of the anatomical structures in the MRIs, and software is expected to help medical students and doctors study the normal anatomical structures in MRIs. This learning tool will be presented worldwide through Internet or CD titles.

• Journal of Chest Surgery
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• v.39 no.6 s.263
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• pp.427-433
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• 2006

Background: Current vascular prostheses are considered still inadequate for reconstruction of small-diameter vessels. To evaluate the potential use of xenograft vessels as small diameter arterial grafts, we implanted porcine vessels in goats. The grafts were treated with two different processes, freezing and acellularization, before implantation, and gross inspection as well as microscopic examination followed after a predetermined period. Material and Method: Bilateral porcine carotid arteries were harvested and immediately stored at $-70^{\circ}C$ within tissue preservation solution. One of them was designated as frozen xenograft vessel. The other one was put on acellularization process using NaCl-SDS solution and stored frozen until further use. Grafts were implanted in the place of carotid arteries of the same goat. The grafts have remained implanted for 1, 3, and 6 months in three animals, respectively. Periodic ultrasonographic examinations were performed during the observation period. After explantation, the grafts were analyzed grossly and histologically under light microscope. Result: All animals survived the experimental procedure without problems. Ultrasonographic examinations showed excellent patency of all the grafts during the observation period. Gross examination revealed nonthrombotic, patent lumens with smooth surfaces. Microscopic examinations of the explanted grafts showed cellular reconstruction at the 6-month stage in both grafts. Although more inflammatory responses were observed in the early phase of frozen xenografts, there was no evidence of significant rejection. Conclusion: These findings suggest that porcine xenograft vessels, regardless of pre-implantation processes of acelluarization or freezing, can be acceptably implanted in goats, although short duration of observation in a small number of animals may limit this study.

• The KIPS Transactions:PartC
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• v.13C no.1 s.104
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• pp.83-94
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• 2006

This paper describes ATM cell encipherment method using Rijndael Algorithm adopted as an AES(Advanced Encryption Standard) by NIST in 2001. ISO 9160 describes the requirement of physical layer data processing in encryption/decryption. For the description of ATM cell encipherment method, we implemented ATM data encipherment equipment which satisfies the requirements of ISO 9160, and verified the encipherment/decipherment processing at ATM STM-1 rate(155.52Mbps). The DES algorithm can process data in the block size of 64 bits and its key length is 64 bits, but the Rijndael algorithm can process data in the block size of 128 bits and the key length of 128, 192, or 256 bits selectively. So it is more flexible in high bit rate data processing and stronger in encription strength than DES. For tile real time encryption of high bit rate data stream. Rijndael algorithm was implemented in FPGA in this experiment. The boundary of serial UNI cell was detected by the CRC method, and in the case of user data cell the payload of 48 octets (384 bits) is converted in parallel and transferred to 3 Rijndael encipherment module in the block size of 128 bits individually. After completion of encryption, the header stored in buffer is attached to the enciphered payload and retransmitted in the format of cell. At the receiving end, the boundary of ceil is detected by the CRC method and the payload type is decided. n the payload type is the user data cell, the payload of the cell is transferred to the 3-Rijndael decryption module in the block sire of 128 bits for decryption of data. And in the case of maintenance cell, the payload is extracted without decryption processing.