• Conservation Science in Museum
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• v.26
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• pp.25-34
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• 2021

3D printing technology has been actively applied for the restoration of cultural properties. However, its application to the restoration of glass cultural properties has not yet been reported and thus requires further study. In this study, 3D printing technology was used to restore a defective part of a glass sarira bottle that forms an element of a series of sarira reliquaries commissioned by Yi Seonggye (known as King Taejo after founding the Joseon Dynasty) that was excavated from Geumgangsan Mountain (designated as Treasure No. 1925) and is currently housed at the National Museum of Korea. The defective area was reproduced using 3D printing and the printed reproduction was reproduced again using an epoxy resin. This latter piece was used as the restoration component rather than the 3D printed element. After the completion of the conservation treatment, the materials used for the 3D printing were compared with transparent materials used to restore ceramics to evaluate their usability and stability. A total of five specimens were produced, including from photocurable resin made by a stereo lithography apparatus (SLA), epoxy resin, acrylic resin, and more. They were exposed to UV for 96 hours to test for yellowing. Of the two specimens made of photocurable resins and exposed to UV, one was sprayed with a UV blocking agent but the other was exposed as-is. The UV exposure test showed that the specimen made by the SLA and sprayed with a UV blocking agent and the specimen made of epoxy resin were stable in terms of yellowing with a change in the b-value was less than 1. They are thus considered to be suitable materials for the restoration of glass cultural properties. Such glass cultural properties are often diverse in shape and their restoration can be difficult as they generally consist of a range of complex parts that hamper restoration. In this regard, diverse materials should be considered when selecting materials for the restoration of glass cultural properties.

• Korean Journal of Heritage: History & Science
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• v.55 no.2
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• pp.66-79
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• 2022

In the mid-Kofun period, the technology employed in the southern part of the Korean Peninsula had reached the Japanese archipelago, and a Japanese-style unglazed earthenware called Sueki was produced. During the early period of the spread of technology, regional elements from all over the Korean Peninsula remained strong, with production on the Japanese archipelago carried out only in very limited regions. After that, production in all parts of the archipelago began gradually. The Sueki culture was introduced to the Japanese archipelago with the technology of the Korean Peninsula; however, many excavations have been reported in the Korean Peninsula(these excavations are even called Suekitype). Many of these excavations were conducted in Jeolla-do, Yeongnam, and the Yeongsan River basin. As revealed in previous studies, however, many imitations were excavated around Jeolla-do, while Sueki of the Japanese archipelago were excavated from tombs in the Yeongnam area. The excavation period was generally from the late 5^th century to the early 6^th century(especially from the TK23 to MT15 stage), which is fundamentally different from that of Jeolla-do. Regarding the locations where Sueki were excavated, the majority were found in the tombs of local authorities. They were rarely excavated from the tombs of the royal people. Furthermore, there is no evidence of special meaning given to funeral ceremonies or Sueki in the Japanese archipelago form; therefore, most of them are thought to have been treated the same as unglazed earthenware. Considering the tombs as a whole, influential people(groups, families, and forces) were not only connected to certain areas of the Gaya region but also had complex and larger relationships. In other words, the Sueki excavated from the Yeongnam area may reflect the rise and fall of the forces in each Gaya region and the changes of the Yeongnam period. The role of negotiation and exchange can be seen not only from the fact that influential people in the central government of the Gaya region were involved but also from the existence of areas(groups, families, forces) discovered in the Gaya region indicating mutual relationships.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1505-1514
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• 2022

Image matching is a crucial preprocessing step for effective utilization of multi-temporal and multi-sensor very high resolution (VHR) satellite images. Deep learning (DL) method which is attracting widespread interest has proven to be an efficient approach to measure the similarity between image pairs in quick and accurate manner by extracting complex and detailed features from satellite images. However, Image matching of VHR satellite images remains challenging due to limitations of DL models in which the results are depending on the quantity and quality of training dataset, as well as the difficulty of creating training dataset with VHR satellite images. Therefore, this study examines the feasibility of DL-based method in matching pair extraction which is the most time-consuming process during image registration. This paper also aims to analyze factors that affect the accuracy based on the configuration of training dataset, when developing training dataset from existing multi-sensor VHR image database with bias for DL-based image matching. For this purpose, the generated training dataset were composed of correct matching pairs and incorrect matching pairs by assigning true and false labels to image pairs extracted using a grid-based Scale Invariant Feature Transform (SIFT) algorithm for a total of 12 multi-temporal and multi-sensor VHR images. The Siamese convolutional neural network (SCNN), proposed for matching pair extraction on constructed training dataset, proceeds with model learning and measures similarities by passing two images in parallel to the two identical convolutional neural network structures. The results from this study confirm that data acquired from VHR satellite image database can be used as DL training dataset and indicate the potential to improve efficiency of the matching process by appropriate configuration of multi-sensor images. DL-based image matching techniques using multi-sensor VHR satellite images are expected to replace existing manual-based feature extraction methods based on its stable performance, thus further develop into an integrated DL-based image registration framework.

• Journal of The Korean Association For Science Education
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• v.42 no.4
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• pp.397-415
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• 2022

As the global warming problem becomes serious, the need for carbon cycle education in school is increasing. Adopting systems thinking ability is needed to understand the carbon cycle systematically. Furthermore, under the rapid change of environment, society, and economy, systems thinking ability is being emphasized as it can strengthen the competencies of students who will be leading the future society. The purposes of this study are as follows: first, is developing the systems thinking instrument for the carbon cycle and the rubric for analysis of systems thinking instrument. The second is analyzing the systems thinking ability of students using the developed instrument and rubric. In order to perform this study, previous studies related to the carbon cycle and systems thinking education were analyzed. Based on the analysis results, the systems thinking instrument for the carbon cycle and rubric were developed. The systems thinking ability was analyzed by implementing the developed instrument and rubric to 172 high school and university students. The results of this study are as follows: first, the systems thinking instrument for the carbon cycle was developed, and a rubric utilization guide was constructed. The instrument and rubric were modified through pilot study for middle school students producing expert opinion in relation to systems thinking and carbon cycle. Second, the systems thinking ability of students was analyzed. Consequently, students had systems thinking ability fully at a low level, such as identifying the variables related to the carbon cycle. However, it was shown that they lacked the systems thinking ability at a high level, such as time delay and feedback processes. The importance of the carbon cycle has been increasing since the global warming is the most pressing issue and significant environmental problem facing us today. Application of the systems thinking ability can contribute to understanding these complex problems and finding fundamental solutions.

• Journal of Food Hygiene and Safety
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• v.37 no.3
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• pp.136-142
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• 2022

The research aims to develop a rapid and easy analytical method for methoprene using liquid chromatography-tandem mass spectrometry (LC-MS/MS). A simple, highly sensitive, and specific analytical method for the determination of methoprene in livestock products (beef, pork, chicken, milk, eggs, and fat) was developed. Methoprene was effectively extracted with 1% acetic acid in acetonitrile and acetone (1:1), followed by the addition of anhydrous magnesium sulfate (MgSO₄) and anhydrous sodium acetate. Subsequently, the lipids in the livestock sample were extracted by freezing them at -20℃. The extracts were cleaned using MgSO₄, primary secondary amine (PSA), and octadecyl (C₁₈), which were then centrifuged to separate the supernatant. Nitrogen gas was used to evaporate the supernatant, which was then dissolved in methanol. The matrix-matched calibration curves were constructed using 8 levels (1, 2.5, 5, 10, 25, 50, 100, 150 ng/mL) and the coefficient of determination (R²) was above 0.9964. Average recoveries spiked at three levels (0.01, 0.1, and 0.5 mg/kg), and ranged from 79.5-105.1%, with relative standard deviations (RSDs) smaller than 14.2%, as required by the Codex guideline (CODEX CAC/GL 40). This study could be useful for residue safety management in livestock products.

• Journal of the Korea Society for Simulation
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• v.18 no.3
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• pp.73-82
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• 2009

Due to the many advantages including low price, low power consumption, and miniaturization, the CMOS camera has been utilized in many applications, including mobile phones, the automotive industry, medical sciences and sensoring, robotic controls, and research in the security field. In particular, the 360 degree omni-directional camera when utilized in multi-camera applications has displayed issues of software nature, interface communication management, delays, and a complicated image display control. Other issues include energy management problems, and miniaturization of a multi-camera in the hardware field. Traditional CMOS camera systems are comprised of an embedded system that consists of a high-performance MCU enabling a camera to send and receive images and a multi-layer system similar to an individual control system that consists of the camera's high performance Micro Controller Unit. We proposed the SL-AVS (Small Size/Low power Around-View System) to be able to control a camera while collecting image data using a high speed synchronization technique on the foundation of a single layer low performance MCU. It is an initial model of the omni-directional camera that takes images from a 360 view drawing from several CMOS camera utilizing a 110 degree view. We then connected a single MCU with four low-power CMOS cameras and implemented controls that include synchronization, controlling, and transmit/receive functions of individual camera compared with the traditional system. The synchronization of the respective cameras were controlled and then memorized by handling each interrupt through the MCU. We were able to improve the efficiency of data transmission that minimizes re-synchronization amongst a target, the CMOS camera, and the MCU. Further, depending on the choice of users, respective or groups of images divided into 4 domains were then provided with a target. We finally analyzed and compared the performance of the developed camera system including the synchronization and time of data transfer and image data loss, etc.

• Journal of the Korean earth science society
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• v.44 no.1
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• pp.13-35
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• 2023

Ocean currents play the most important role in causing and controlling global climate change. The water depth of the Yellow Sea is very shallow compared to the East Sea, and the circulation and currents of seawater are quite complicated owing to the influence of various wind fields, ocean currents, and river discharge with low-salinity seawater. The Yellow Sea Warm Current (YSWC) is one of the most representative currents of the Yellow Sea in winter and is closely related to the weather of the southwest coast of the Korean Peninsula, so it needs to be treated as important in secondary-school textbooks. Based on the 2015 revised national educational curriculum, secondary-school science and earth science textbooks were analyzed for content related to the YSWC. In addition, a questionnaire survey of secondary-school science teachers was conducted to investigate their perceptions of the temporal variability of ocean currents. Most teachers appeared to have the incorrect knowledge that the YSWC moves north all year round to the west coast of the Korean Peninsula and is strong in the summer like a general warm current. The YSWC does not have strong seasonal variability in current strength, unlike the North Korean Cold Current (NKCC), but does not exist all year round and appears only in winter. These errors in teachers' subject knowledge had a background similar to why they had a misconception that the NKCC was strong in winter. Therefore, errors in textbook contents on the YSWC were analyzed and presented. In addition, to develop students' and teachers' data literacy, class materials on the YSWC that can be used in inquiry activities were developed. A graphical user interface (GUI) program that can visualize the sea surface temperature of the Yellow Sea was introduced, and a program displaying the spatial distribution of water temperature and salinity was developed using World Ocean Atlas (WOA) 2018 oceanic in-situ measurements of water temperature and salinity data and ocean numerical model reanalysis field data. This data visualization materials using oceanic data is expected to improve teachers' misunderstandings and serve as an opportunity to cultivate both students and teachers' ocean and data literacy.

• Journal of Korean Tunnelling and Underground Space Association
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• v.11 no.1
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• pp.57-70
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• 2009

Considerable advance has been made on research on effect of steel pipe Umbrella Arch Method (UAM) and mechanical reinforcement mechanism through numerical analyses and experiments. Due to long analysis time of three-dimensional analysis and its complexity, un-quantitative two-dimensional analysis is dominantly used in the design and application, where equivalent material properties of UAM reinforced area and ground are used, For this reason, development of reasonable, theoretical, quantitative and easy to use design and analysis method is required. In this study, both field UAM tests and laboratory tests were performed in the residual soil to highly weathered rock; field tests to observe the range of reinforcement, and laboratory tests to investigate the change of material properties between prior to and after UAM reinforcement. It has been observed that the increase in material property of neighboring ground is negligible, and that only stiffness of steel pipe and cement column formed inside the steel pipe and the gap between steel pipe and borehole contributes to ground reinforcement. Based on these results and concept of Convergence Confinement Method (CCM), two dimensional axisymmetric analyses have been performed to obtain the longitudinal displacement profile (LDP) corresponding to arching effect of tunnel face, UAM effect and effect of supports. In addition, modified load distribution method in two dimensional plane-strain analysis has been suggested, in which effect of UAM is transformed to internal pressure and modified load distribution ratios are suggested. Comparison between the modified method and conventional method shows that larger displacement occur in the conventional method than that in the modified method although it may be different depending on ground condition, depth and size of tunnel, types of steel pipe and initial stress state. Consequently, it can be concluded that the effect of UAM as a beam in a longitudinal direction is not considered properly in the conventional method.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.11
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• pp.471-480
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• 2023

The Korean construction order volume in South Korea grew significantly from 91.3 trillion won in public orders in 2013 to a total of 212 trillion won in 2021, particularly in the private sector. As the size of the domestic and overseas markets grew, the scale and complexity of EPC (Engineering, Procurement, Construction) projects increased, and risk management of project management and ITB (Invitation to Bid) documents became a critical issue. The time granted to actual construction companies in the bidding process following the EPC project award is not only limited, but also extremely challenging to review all the risk terms in the ITB document due to manpower and cost issues. Previous research attempted to categorize the risk terms in EPC contract documents and detect them based on AI, but there were limitations to practical use due to problems related to data, such as the limit of labeled data utilization and class imbalance. Therefore, this study aims to develop an AI model that can categorize the contract terms based on the FIDIC Yellow 2017(Federation Internationale Des Ingenieurs-Conseils Contract terms) standard in detail, rather than defining and classifying risk terms like previous research. A multi-text classification function is necessary because the contract terms that need to be reviewed in detail may vary depending on the scale and type of the project. To enhance the performance of the multi-text classification model, we developed the ELECTRA PLM (Pre-trained Language Model) capable of efficiently learning the context of text data from the pre-training stage, and conducted a four-step experiment to validate the performance of the model. As a result, the ensemble version of the self-developed ITB-ELECTRA model and Legal-BERT achieved the best performance with a weighted average F1-Score of 76% in the classification of 57 contract terms.

• Journal of Intelligence and Information Systems
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• v.18 no.4
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• pp.19-42
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• 2012

Consumer consumption patterns are shifting rapidly as buyers migrate from offline markets to e-commerce routes, such as shopping channels on TV and internet shopping malls. In the offline markets consumers go shopping, see the shopping items, and choose from them. Recently consumers tend towards buying at shopping sites free from time and place. However, as e-commerce markets continue to expand, customers are complaining that it is becoming a bigger hassle to shop online. In the online shopping, shoppers have very limited information on the products. The delivered products can be different from what they have wanted. This case results to purchase cancellation. Because these things happen frequently, they are likely to refer to the consumer reviews and companies should be concerned about consumer's voice. E-commerce is a very important marketing tool for suppliers. It can recommend products to customers and connect them directly with suppliers with just a click of a button. The recommender system is being studied in various ways. Some of the more prominent ones include recommendation based on best-seller and demographics, contents filtering, and collaborative filtering. However, these systems all share two weaknesses : they cannot recommend products to consumers on a personal level, and they cannot recommend products to new consumers with no buying history. To fix these problems, we can use the information which has been collected from the questionnaires about their demographics and preference ratings. But, consumers feel these questionnaires are a burden and are unlikely to provide correct information. This study investigates combining collaborative filtering with the centrality of social network analysis. This centrality measure provides the information to infer the preference of new consumers from the shopping history of existing and previous ones. While the past researches had focused on the existing consumers with similar shopping patterns, this study tried to improve the accuracy of recommendation with all shopping information, which included not only similar shopping patterns but also dissimilar ones. Data used in this study, Movie Lens' data, was made by Group Lens research Project Team at University of Minnesota to recommend movies with a collaborative filtering technique. This data was built from the questionnaires of 943 respondents which gave the information on the preference ratings on 1,684 movies. Total data of 100,000 was organized by time, with initial data of 50,000 being existing customers and the latter 50,000 being new customers. The proposed recommender system consists of three systems : [+] group recommender system, [-] group recommender system, and integrated recommender system. [+] group recommender system looks at customers with similar buying patterns as 'neighbors', whereas [-] group recommender system looks at customers with opposite buying patterns as 'contraries'. Integrated recommender system uses both of the aforementioned recommender systems to recommend movies that both recommender systems pick. The study of three systems allows us to find the most suitable recommender system that will optimize accuracy and customer satisfaction. Our analysis showed that integrated recommender system is the best solution among the three systems studied, followed by [-] group recommended system and [+] group recommender system. This result conforms to the intuition that the accuracy of recommendation can be improved using all the relevant information. We provided contour maps and graphs to easily compare the accuracy of each recommender system. Although we saw improvement on accuracy with the integrated recommender system, we must remember that this research is based on static data with no live customers. In other words, consumers did not see the movies actually recommended from the system. Also, this recommendation system may not work well with products other than movies. Thus, it is important to note that recommendation systems need particular calibration for specific product/customer types.