• The Korean Journal of Archival Studies
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• no.13
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• pp.41-90
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• 2006

It's needed for the archivists to design a flexible and stable ERMS(Electronic Records Management System) which can ingest and store records through a consistent way and let users search and use records easily what they want. The basis of the design for ERMS are the conceptual composition and the logical and physical structure of the records when they are stored and managed in the ERMS. This paper explains the process of defining components and designing structure of electronic records using 3-layered approaches which consist of conceptual, logical and physical layer and shows advantages of this approaches. After benchmarking the information models of OAIS which is a reference model for the long-term preservation of digital information objects, this paper applies the model of AIP to a record as a 'Record AIP' and discusses the composition and structure of it. It's a critical task to identify mandatory or optional metadata groups which consists of the 'Record AIP's in the conceptual layer. This paper emphases that the metadata group related to services for the record information to users is required as a result of benchmarking OAIS information models. Various issues about the structure of 'Record AIP's are discussed according to the kind of preservation strategy such as migration or emulation and whether the encapsulation of records is required or not in the logical layer.

• Journal of the Korean Society of Radiology
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• v.12 no.7
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• pp.813-819
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• 2018

To demonstrate the 3D usefulness of MDCT, a 73-year-old male patient with subclavian thrombosis was obtained 3D images of maximum intensity projection (MIP), volume rendering, and multiplanar reformation (MPR) to clearly detect and locate the subclavian artery. The data will be provided to the patient for diagnosis and treatment. The scan data were acquired as 3D CT images MIP, volume rendering, curved MPR, and virtual endoscopy images. In the 3D program, the ascending aorta was measured as 364.28 HU, the left carotid artery was 413.77 HU, and the left subclavian artery was 15.72 HU. MIP coronal image shows the closure of the subclavian artery in the left side. Three-dimensional volume images were obtained with 100% permeability and 87-1265 HU. The coronal curved MPR and sagittal curved MPR images show the closure of the subclavian artery due to thrombus using 3D image processing. In the case of subclavian arterial occlusion due to thrombosis, the patient is scanned with MDCT and 3D image processing can be used to confirm occlusion of subclavian artery.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.4
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• pp.336-342
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• 2019

With the entry of an aging society, the average life span of accreditation has been extended. Therefore, interest in the appearance of men and women in modern society has increased. It is the wrinkles of the face that can judge the most outwardly. People tend to have various kinds of treatments to have a clean, wrinkle-free and resilient healthy skin regardless of sex. There is a lot of practice of lifting procedures in one of the procedures. A suture using a melting thread is a method of lifting by squeezing it into the skin as a non-incision type centering on a region where the thread can be fixed in the skin by injecting it into the subcutaneous fat layer. To evaluate the lifting efficacy of Cog - type suture for the improvement of skin wrinkles, preclinical experiments were conducted. We developed a wrinkle evaluation program using Labview. Data from preclinical experiments were used at 8 weeks after suturing. The average wrinkle depth was 415.6 mm in the control group. At 8 weeks, the depth of wrinkles was deepened to 888.3mm due to the aging process of the control group. On the other hand, the depth of the wrinkles before surgery was 640.3 mm in the suture group. It was confirmed that the depth of wrinkles decreased to 566.5mm at 8th week after the suture operation.

• Journal of Conservation Science
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• v.35 no.3
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• pp.217-225
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• 2019

The chimi(ridge-end tile) of Wangheungsa temple is the oldest in our country. The upper part of the chimi was excavated from the southern side of Wangheungsa temple and the lower part from the northern side. These parts are considered to be portions of the same chimi, because they are similar in shape and are excavated from two sides of the same temple structure. However, the original shape of the chimi cannot be determined owing to substantial deterioration. Hence, in this study, replicas of the deteriorated chimi portions of Wangheungsa temple were fabricated by employing 3D scanning technology and the computer numerical control machining method. While observing the bending phenomenon of the chimi, the proposed model was warped realistically on the basis of the bending direction of the actual chimi. Consequently, the restoration process was modified several times. The results indicated that no gaps can be found between the upper and lower parts, and the corresponding patterns connect naturally. Furthermore, the proposed method is contactless, safe, operable, reproducible, and appropriate for restoration of artifacts. Additionally, the modeling data is semi-permanent. Hence, if modelling data is appropriately applied as per the characteristics of artifacts, it can be utilized in various fields such as virtual exhibitions, hands-on exhibitions, cultural heritage restoration, and production of teaching aids and souvenirs.

• The Journal of Korean Institute of Next Generation Computing
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• v.15 no.5
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• pp.64-74
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• 2019

Although a non-rigid registration has high demands in clinical practice, it has a high computational complexity and it is very difficult for ensuring the accuracy and robustness of registration. This study proposes a method of applying a non-rigid registration to 3D magnetic resonance images of brain in an unsupervised learning environment by using a deep-learning network. A feature vector between two images is produced through the network by receiving both images from two different patients as inputs and it transforms the target image to match the source image by creating a displacement vector field. The network is designed based on a U-Net shape so that feature vectors that consider all global and local differences between two images can be constructed when performing the registration. As a regularization term is added to a loss function, a transformation result similar to that of a real brain movement can be obtained after the application of trilinear interpolation. This method enables a non-rigid registration with a single-pass deformation by only receiving two arbitrary images as inputs through an unsupervised learning. Therefore, it can perform faster than other non-learning-based registration methods that require iterative optimization processes. Our experiment was performed with 3D magnetic resonance images of 50 human brains, and the measurement result of the dice similarity coefficient confirmed an approximately 16% similarity improvement by using our method after the registration. It also showed a similar performance compared with the non-learning-based method, with about 10,000 times speed increase. The proposed method can be used for non-rigid registration of various kinds of medical image data.

• The Journal of Korean Institute of Next Generation Computing
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• v.14 no.5
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• pp.19-30
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• 2018

Visual information understanding is known as one of the most difficult and challenging problems in the realization of machine intelligence. This paper proposes deriving visual verb and construction of ActionNet database as a video database for video semantic understanding. Even though development AI (artificial intelligence) algorithms have contributed to the large part of modern advances in AI technologies, huge amount of database for algorithm development and test plays a great role as well. As the performance of object recognition algorithms in still images are surpassing human's ability, research interests shifting to semantic understanding of video contents. This paper proposes candidates of visual verb requiring in the construction of ActionNet as a learning and test database for video understanding. In order to this, we first investigate verb taxonomy in linguistics, and then propose candidates of visual verb from video description database and frequency of verbs. Based on the derived visual verb candidates, we have defined and constructed ActionNet schema and database. According to expanding usability of ActionNet database on open environment, we expect to contribute in the development of video understanding technologies.

• The Journal of the Korea Contents Association
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• v.21 no.1
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• pp.277-283
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• 2021

Traffic data by vehicle classification are important data used as basic data in various fields such as road and traffic design. Traffic data is collected through permanent and temporary surveys and is provided as an annual average daily traffic (AATD) in the statistical yearbook of road traffic. permanent surveys are collected through traffic collection equipment (AVC), and the AVC consists of a loop sensor that detects traffic volume and a piezo sensor that detects the number of axes. Due to the nature of the buried type of traffic collection equipment, missing data is generated due to failure of detection equipment. In the existing method, it is corrected through historical data and the trend of traffic around the point. However, this method has a disadvantage in that it does not reflect temporal and spatial characteristics and that the existing data used for correction may also be a correction value. In this study, we proposed a method to correct the missing traffic volume by calculating the axis correction coefficient through the accumulated number of axes acquired by using a piezo sensor that can detect the axis of the vehicle. This has the advantage of being able to reflect temporal and spatial characteristics, which are the limitations of the existing methods, and as a result of comparative evaluation, the error rate was derived lower than that of the existing methods. The traffic volume correction system using axis count is judged as a correction method applicable to the field system with a simple algorithm.

• Korean Journal of Construction Engineering and Management
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• v.23 no.3
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• pp.95-103
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• 2022

Recently, the fourth industrial revolution has a great influence on the development of many industries as well as the construction industry. Various technologies related to the industrial revolution 4.0, such as AI and big data, have gained much attention. However, little has been known about the importance and preparedness of stakeholders of the construction industry in Korea for the industry 4.0 technologies so far. This study revealed how the stakeholders perceive and prepare for industry 4.0 using a survey. In addition, collaboration potential score for each technology was calculated to find technologies with high potential for collaboration. Result is that the importance of the technologies was evaluated high in overall, but the preparedness and implementation in university education or business was evaluated low. Technologies with high potential for industry-university collaboration are AI/big data and 3D printing/3D scanning. This study can contribute to the training of industry 4.0 experts and improving preparedness, which would enable the innovation and application of industry 4.0 technologies in the construction industry.

• Journal of the Korea Society of Computer and Information
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• v.28 no.8
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• pp.175-186
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• 2023

In this paper, we aim to build a gentrification analysis model and examine its characteristics, focusing on the point at which rents rose sharply alongside the recovery of commercial districts after the gradual resumption of daily life. Recently, in Korea, the influence of social distancing measures after the pandemic has led to the formation of small-scale commercial districts, known as 'hot places', rather than large-scale ones. These hot places have gained popularity by leveraging various media and social networking services to attract customers effectively. As a result, with an increase in the floating population, commercial districts have become active, leading to a rapid surge in rents. However, for small business owners, coping with the sudden rise in rent even with increased sales can lead to gentrification, where they might be forced to leave the area. Therefore, in this study, we seek to analyze the periods before and after by identifying points where rents rise sharply as commercial districts experience revitalization. Firstly, we collect text data to explore topics related to gentrification, utilizing LDA topic modeling. Based on this, we gather data at the commercial district level and build a gentrification analysis model to examine its characteristics. We hope that the analysis of gentrification through this model during a time when commercial districts are being revitalized after facing challenges due to the pandemic can contribute to policies supporting small businesses.

• Journal of the Korean Geotechnical Society
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• v.39 no.4
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• pp.45-54
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• 2023

The settlement prediction during the design phase is primarily conducted using theoretical methods. However, measurement-based settlement prediction methods that predict future settlements based on measured settlement data over time are primarily used during construction due to accuracy issues. Among these methods, the hyperbolic method is commonly used. However, the existing hyperbolic method has accuracy issues and statistical limitations. Therefore, a weighted nonlinear regression hyperbolic method has been proposed. In this study, two weighting methods were applied to the weighted nonlinear regression hyperbolic method to compare and analyze the accuracy of settlement prediction. Measured settlement plate data from two sites located in Busan New Port were used. The settlement of the remaining sections was predicted by setting the regression analysis section to 30%, 50%, and 70% of the total data. Thus, regardless of the weight assignment method, the settlement prediction based on the hyperbolic method demonstrated a remarkable increase in accuracy as the regression analysis section increased. The weighted nonlinear regression hyperbolic method predicted settlement more accurately than the existing linear regression hyperbolic method. In particular, despite a smaller regression analysis section, the weighted nonlinear regression hyperbolic method showed higher settlement prediction performance than the existing linear regression hyperbolic method. Thus, it was confirmed that the weighted nonlinear regression hyperbolic method could predict settlement much faster and more accurately.