• Korean Journal of Heritage: History & Science
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• v.54 no.3
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• pp.52-67
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• 2021

This study is an attempt to explore the roles of and the collaborative relationship between Daheojang and Maedeupjang. Daheojang and Maedeupjang share a similar manufacturing process. However, in modern times, Daheojang totally disappeared, and Maedeupjang was designated as an intangible cultural property. The present study will investigate the role of Daheojang and Maedeupjang based on the literature of the Joseon dynasty. Daheojang were craftsmen who made bands and strings of woven or twisted silk strands. They made mangsu and tassels or made knots to produce magnificent artifacts. Maedeupjang complete all steps of the process, from refining, dyeing, combining threads, daheo, maedeup, to the tassel. Daheojang in the Joseon dynasty was the center of this process. Daheojang belonged to almost all Uigwe because it used items ranging from large uso to cushion straps. Dahoe is a craft with various items and techniques. It has been widely used to produce majestic items like formal dresses, ritual ceremony pieces, and mountings, as well as daily items like jodae, pocket straps, and norigae. Based on the records of Uigwe in the late Joseon dynasty, the study explored the collaborative relationship between Daheojang and Maedeupjang. Sambang, the room where both Daheojang and Maedeupjang belong, was the room to produce the royal chair. The royal chair essentially includes large uso. The large uso is an artifact that ties a knot in a thick circle more than two meters long. While Daheojang made rounded daheo, Maedeupjang made delicate and balanced knots. Also, they produced royal inscriptions together with a royal seal with decorative mangsu and a seal of thick rounded daheo. In order to learn about traditional technology, it is necessary to study the system of the times and social trends. Therefore, the study focused on Daheojang, who were common master craftsmen during the Joseon dynasty but now are not familiar to most people.

• Conservation Science in Museum
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• v.25
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• pp.35-50
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• 2021

This study analyzed the basic properties of soil material gathered around Maegok-dong in Gwangju, Gyeonggi-do Province (hereafter, "Maegok soil") and the physicochemical changes in the Maegok soil resulting from the addition of other clay materials in order to present scientific information about the properties of clay available for pottery production. Gravel, coarse sand, and fine sand account for 73% of the total mass of the Maegok soil. Therefore, it required refinement through sifting in order to serve in pottery clay. After sifting, the amount of silt and clay in the soil increased to 95% of the total mass. However, since it lacked plasticity and viscosity, buncheong soil was added. When it was mixed with bungcheong soil at a ratio of 7:3, Maegok soil improved as pottery clay as its viscosity increased, demonstrating compositional properties appropriate for ceramic clay even after firing. Further, its water-absorption rate was decreased to 0.40. This means that soil gathered from anywhere can be used for pottery-making by refining its original properties and through mixture with clay with specific components which help the pottery maintain its shape even after firing.

• Journal of Convergence for Information Technology
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• v.11 no.3
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• pp.20-33
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• 2021

This study is to suggest improvements of personal information protection in South Korea, according to requiring the safety of process and protection of personal information. Accordingly, based on data collection and analysis through literature research, this study derived the issues and suitable standards of personal information for major artificial intelligence services. In addition, this cases studies were reviewed, focusing on the legal compliance and porcessing compliance for personal information proection in major countries. And it suggested the improvement plan applied in South Korea. As the results, in legal compliance, it is required reorganization of related laws, responsibility and compliance to develop and provide AI, and operation of risk management for personal information protection laws in AI services. In terms of processing compliance, first, in pre-processing and refining, it is necessary to standardize data set reference models, control data set quality, and voluntarily label AI applications. Second, in development and utilization of algorithm, it is need to establish and apply a clear regulation of the algorithm. As such, South Korea should apply suitable improvement tasks for personal information protection of safe AI service.

• Journal of the Society of Cosmetic Scientists of Korea
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• v.47 no.4
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• pp.317-331
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• 2021

Essential oil is a volatile substance obtained by physically obtaining fragrant plant materials made by one single plant and plant species, and is widely used for cosmetics, fragrances, and aroma therapy due to its excellent preservation, sterilization, and antibacterial effects. When essential oil would undergo the extraction and concentration processes, the agricultural chemicals thereof would be extracted and concentrated only to be harmful to the human body. This study analyzes 320 residual agricultural chemicals concentrated in the essential oil, and to this end, LC-MS/MS and GC-MS/MS are used, while the freezing process is applied instead of the conventional refining process hexane, to improve the preprocessing method. As a result of analyzing the essential oil, such ingredients as chlorpyrifos, piperonyl butoxide and silafluofen have been detected in Basil oil and Clove leaf oil. Hence, it is perceived that the residual agricultural chemicals should continue to be monitored for the essential oil.

• Journal of the Institute of Convergence Signal Processing
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• v.22 no.4
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• pp.149-155
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• 2021

In this study, we intend to develop a defective road surface object recognition model that automatically detects road surface defects that restrict the movement of the transportation handicapped using electric mobile devices with deep learning. For this purpose, road surface information was collected from the pedestrian and running routes where the electric mobility aid device is expected to move in five areas within the city of Busan. For data, images were collected by dividing the road surface and surroundings into objects constituting the surroundings. A series of recognition items such as the detection of breakage levels of sidewalk blocks were defined by classifying according to the degree of impeding the movement of the transportation handicapped in traffic from the collected data. A road surface object recognition deep learning model was implemented. In the final stage of the study, the performance verification process of a deep learning model that automatically detects defective road surface objects through model learning and validation after processing, refining, and annotation of image data separated and collected in units of objects through actual driving. proceeded.

• Applied Chemistry for Engineering
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• v.33 no.5
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• pp.496-501
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• 2022

In this study, an anode material for lithium secondary batteries was manufactured using petroleum-based residual oil, which is a petroleum refining by-product. Among petroleum-based residual oils, pyrolysis fuel oil (PFO), fluidized catalyst cracking-decant oil (FCC-DO), and vacuum residue (VR) were used as carbon precursors. The physicochemical characteristics of petroleum-based residual oil were confirmed through Matrix-assisted laser desorption/ionization Time-of-Flight (MALDI-TOF) and elemental analysis (EA), and the structural characteristics of anode materials manufactured from residual oil were evaluated using X-ray crystallography (XRD) and Raman spectroscopic techniques. VR was found to contain a wide range of molecular weight distributions and large amounts of impurities compared to PFO and FCC-DO, and PFO and FCC-DO exhibited almost similar physicochemical characteristics. From the XRD analysis results, carbonized PFO and FCC-DO showed similar d₀₀₂ values. However, it was confirmed that FCC-DO had a more developed layered structure than PFO in Lc (Length of a and c axes in the crystal system) and La values. In addition, FCC-DO showed the best cycle characteristics in electrochemical characteristics evaluation. According to the physicochemical and electrochemical results of the petroleum-based residual oil, FCC-DO is a better carbon precursor for a lithium secondary battery than PFO and VR.

• Journal of the Korean Institute of Gas
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• v.26 no.6
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• pp.45-51
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• 2022

Technologies for collecting and treating pollutants from point sources are steadily being developed, but Non-point sources, it is difficult to develop emission treatment technologies and effective emission coefficients. However, since non-point sources make up about 60% of domestic emissions, and first of all, the method of calculating emissions should be reasonable, and the workplace should develop emission reduction technologies based on this. This study suggest the effectiveness and improvement of the emission coefficient currently used for the petrochemical industry with high emissions. The emission characteristics of non-point sources emission were confirmed by analyzing the LDAR (Leak Detection And Repair) data of OO company located in Yeosu, Jeollanam-do over the past five years. As a result, there was no difference in discharge characteristics according to fluid phase, but it was confirmed that there was a difference in the size of the device and the characteristics of each manufacturer. In addition, it was confirmed that the emission coefficient applied in the petrochemical industry was larger than that of the refining industry, and improvement measures were suggested. Through these studies, it is expected that emission coefficients specialized in the petrochemical industry can be applied and that the workplace itself will contribute to the development of technologies that can drastically reduce them.

• Environmental and Resource Economics Review
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• v.31 no.3
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• pp.419-449
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• 2022

This paper aims to quantify the potential economic burdens of EU's carbon border adjustment mechanisms faced by Korean domestic industries. In addition, this study tries to compare and analyzes changes in the burden of each industry resulted from the implementation of the domestic low-carbon policy. Based on the quantitative findings, we intend to suggest policy implications for establishing mid- to long-term strategies in response to climate change risks. Based on the environmentally extended input-output analysis, the total economic burdens of the domestic industries due to the EU's carbon border adjustment mechanisms are estimated to be approximately KRW 8,245.6 billion in 2030. Looking at the impacts by industry, it is found that major industries such as petrochemicals, petroleum refining, transportation equipment, steel, automobiles, and electric/electronic equipment industries are expected to account for 84.3% of the total potential burdens. In addition, in multiple policy scenarios assuming technological developments and energy transition following the implementation of domestic low-carbon policies, the total economic burden of carbon border adjustment is expected to decrease by about 11.7% to 15.0%. The main result of this study suggests that we should not view EU EU's carbon border adjustment mechanism as a trade regulation, but to use it as a momentum for more effective implementation of the low-carbon and energy transition strategies in the global carbon neural era.

• Journal of Conservation Science
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• v.38 no.4
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• pp.289-300
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• 2022

In the 6^th and 7^th centuries, 5 iron artifacts excavated form the Baekje Stone Tomb in Guryong-ri site, Ungcheon, Boryeong, were studied. The sample were metal microscopic observation, SEM-EDS analysis and Raman micro-spectroscopy analysis were conducted to understand the metallurgical characteristics. The microstructure observation showed the presence of ferrite and pearlite throughout, and differences in carbon content existed depending on the direction. Non-metallic inclusions were in the form of long lines, and most of them were wüstite, fayalite. It is indicated that the artifacts were forge welded using hypoeutectoid steel, with signs of carburizing and decarburizing processes. Some crystals with high P₂O₅, TiO₂, CaO content were identified as sarcopside, ulvöspinel, and perovskite, respectively, through Raman spectroscopy. A comparison of the results with previous studies on the sites of Bujang-ri site in Seosan and Bongseon-ri site in Seocheon, which are adjacent sites in the coastal area, revealed that, while heat treatment technology was available, the artifacts were not heat-treated considering the purpose for use for these artifacts. The chemical composition of the non-metallic inclusions P₂O₅, TiO₂, CaO were plotted in proportions to SiO₂ and compared with adjacent sites. Considering that the P₂O₅/SiO₂ ratio was widely distributed, the refining technology was not uniform. In addition, the TiO₂/SiO₂ ratio was found to be higher than that of other sites, meaning that a titanium-containing ore was used to manufacture the artifacts, unlike in surrounding sites, but it is not detected in all artifacts, so it may have been affected by various factors such as furnace walls in addition to raw materials. Although slag formers were used, considering the CaO/SiO₂ ratio and the (Al₂O₃/SiO₂)/(CaO/SiO₂) ratio, which appear to be similar to the surrounding sites, but it is possible that CaO containing raw ore was used because it is also affected by the components of raw ore. As a result of the study, it is highly likely that ore different from that of the surrounding sites was used for production, but a more comprehensive comparative study with the surrounding sites is needed in the future.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.43-45
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• 2021

The short-term quantitative precipitation prediction (QPF) system is important socially and economically to prevent damage from severe weather. Recently, many studies for short-term QPF model applying the Deep Neural Network (DNN) has been conducted. These studies require the sophisticated pre-processing because the mistreatment of various and vast meteorological data sets leads to lower performance of QPF. Especially, for more accurate prediction of the non-linear trends in precipitation, the dataset needs to be carefully handled based on the physical and dynamical understands the data. Thereby, this paper proposes the following approaches: i) refining and combining major factors (weather radar, terrain, air temperature, and so on) related to precipitation development in order to construct training data for pattern analysis of precipitation; ii) producing predicted precipitation fields based on Convolutional with ConvLSTM. The proposed algorithm was evaluated by rainfall events in 2020. It is outperformed in the magnitude and strength of precipitation, and clearly predicted non-linear pattern of precipitation. The algorithm can be useful as a forecasting tool for preventing severe weather.