• Korean Journal of Mineralogy and Petrology
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• v.36 no.4
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• pp.233-257
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• 2023

Asbestos minerals are found at rocks and soils of the Hongseong and Bibong serpentine mines, western part of Chungnam. The area consists of and metasediment, and Mesozoic igneous intrusives with minor age-known gneiss complexes and Mesozoic sediments. With detailed geological investigations, rock samples for the serpentinite and amphibolite areas are collected at sites containing asbestos. Representative asbestos and rock samples are analysed by PLM, XRD, SEM and EPMA. Serpentinites are found as steeply dipping faults with adjacent gneiss complex to the NNE direction. Repeated alteration, including serpenitization and talcification, is found at the emplacement direction for the serpentinite body. Amphibollites occur as intrusives and stratiforms within the Precambrian gneiss complex. Serpentinite and amphibolite (or amphibole schist) contain amphiboles either as asbestiform or non-asbestiform. Varying amounts of asbestos minerals, including chrysotile, tremolite asbestos and actinolite asbestos, are found within the serpentinites. The asbestos minerals are found near the cracks or fractures and along the bedding plane. They occur as cross fiber, slip fiber and mass fiber types. Varying amounts of amphibole asbestos minerals, such as tremolite and actinolite asbestos, are found within amphibolites and as a mass fiber type. Overall results suggest that rocks of the serpentine mines contain serpentine and amphibole type asbestos minerals originated from the hydrothermal alteration. Considering construction nearby the mines and environmental risks by the asbestos, additional land management plans are required.

• Journal of The Korean Association For Science Education
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• v.44 no.3
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• pp.231-248
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• 2024

This study developed a chatbot for first-year high school students, employing open-source software and the Korean Sentence-BERT model for AI-powered document classification. The chatbot utilizes the Sentence-BERT model to find the six most similar Q&A pairs to a student's query and presents them in a carousel format. The initial dataset, built from online resources, was refined and expanded based on student feedback and usability throughout over the operational period. By the end of the 2023 academic year, the chatbot integrated a total of 30,819 datasets and recorded 3,457 student interactions. Analysis revealed students' inclination to use the chatbot when prompted by teachers during classes and primarily during self-study sessions after school, with an average of 2.1 to 2.2 inquiries per session, mostly via mobile phones. Text mining identified student input terms encompassing not only science-related queries but also aspects of school life such as assessment scope. Topic modeling using BERTopic, based on Sentence-BERT, categorized 88% of student questions into 35 topics, shedding light on common student interests. A year-end survey confirmed the efficacy of the carousel format and the chatbot's role in addressing curiosities beyond integrated science learning objectives. This study underscores the importance of developing chatbots tailored for student use in public education and highlights their educational potential through long-term usage analysis.

• Journal of Internet Computing and Services
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• v.25 no.1
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• pp.109-121
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• 2024

In various manufacturing processes such as textiles and automobiles, when equipment breaks down or stops, the machines do not work, which leads to time and financial losses for the company. Therefore, it is important to detect equipment abnormalities in advance so that equipment failures can be predicted and repaired before they occur. Most equipment failures are caused by bearing failures, which are essential parts of equipment, and detection bearing anomaly is the essence of PHM(Prognostics and Health Management) research. In this paper, we propose a preprocessing algorithm called SWT-SVD, which analyzes vibration signals from bearings and apply it to an anomaly transformer, one of the time series anomaly detection model networks, to implement bearing anomaly detection model. Vibration signals from the bearing manufacturing process contain noise due to the real-time generation of sensor values. To reduce noise in vibration signals, we use the Stationary Wavelet Transform to extract frequency components and perform preprocessing to extract meaningful features through the Singular Value Decomposition algorithm. For experimental validation of the proposed SWT-SVD preprocessing method in the bearing anomaly detection model, we utilize the PHM-2012-Challenge dataset provided by the IEEE PHM Conference. The experimental results demonstrate significant performance with an accuracy of 0.98 and an F1-Score of 0.97. Additionally, to substantiate performance improvement, we conduct a comparative analysis with previous studies, confirming that the proposed preprocessing method outperforms previous preprocessing methods in terms of performance.

• Journal of the Korean Society of Radiology
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• v.85 no.2
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• pp.297-307
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• 2024

Coronary artery disease (CAD) narrows vessel lumens at the sites of atherosclerosis, increasing the risk of myocardial ischemia or infarction. Early and accurate diagnosis of CAD is crucial to significantly improve prognosis and management. CT angiography (CTA) is a noninvasive imaging technique that enables assessment of vascular structure and stenosis with high resolution and contrast. Coronary CTA is useful in the diagnosis of CAD. Recently, the CAD-reporting and data system (CAD-RADS), a diagnostic classification system based on coronary CTA, has been developed to improve intervention efficacy in patients suspected of CAD. While the CADRAD is based on CTA, it includes borderline categories where interpreting the coronary artery status solely based on CTA findings may be challenging. This review introduces CTA findings that fall within the CAD-RADS categories that necessitate additional tests to decide to perform invasive coronary angiography and discusses appropriate management strategies.

• KOREAN JOURNAL OF PACKAGING SCIENCE & TECHNOLOGY
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• v.24 no.2
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• pp.65-71
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• 2018

Paper packs, glass bottles, metal cans, and plastic materials are classified according to packaging material recycling groups that are Extended Producer Responsibility (EPR). In the case of waste paper pack, the compressed cartons are dissociated to separate polyethylene films and other foreign substance, and then these are washed, pulverized and dried to produce toilet paper. Glass bottle for recycling is provided to the bottle manufacturers after the process of collecting the waste glass bottle, removing the foreign substance, sorting by color, crushing, raw materializing process. Waste glass recycling technology of Korea is largely manual, except for removal of metal components and low specific gravity materials. Metal can is classified into iron and aluminum cans through an automatic sorting machine, compressed, and reproduced as iron and aluminum through a blast furnace. In the case of composite plastic material, the selected compressed product is crushed and then recycled through melt molding and refined products are produced through solid fuel manufacturing steps through emulsification and compression molding through pyrolysis. In the recycling process of paper packs, glass bottles, metal cans, and plastic materials, the influx of recycled materials and other substances interferes with the recycling process and increases the recycling cost and time. Therefore, the government needs to improve the legal system which is necessary to use materials and structure that are easy to recycle from the design stage of products or packaging materials.

• Journal of Venture Innovation
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• v.2 no.2
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• pp.95-115
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• 2019

In the context of today's business environment, not only is the nation or company's credit rating considered very important in our recent society, but it is also becoming important in international transactions. Likewise, at this point of time when the importance and reliability of credit evaluation are becoming important at home and abroad, this study analyzes financial ratios related to corporate profitability, safety, activity, financial growth, and profit growth to study the impact of financial indicators on enterprise value and corporate taxes on credit evaluation. To proceed with this, the financial ratio of 465 companies of KOSPI securities listed in 2017 was calculated and the impact of enterprise value and corporate taxes on credit evaluation was analyzed. Especially, this further study tried to derive a reliable and consistent conclusion by analyzing the financial data of KOSPI securities listed companies for eight years from 2011, which is the first year of K-IFRS introduction, to 2018. Research has shown that the significance levels among variables that show the profitability, safety, activity, financial growth, and profit growth of each financial ratio were significant at the 99% level, except for the profit growth. Validation of the research hypothesis found that while the profitability of KOSPI-listed companies significantly affects corporate value and income tax, indicators such as safety ratio and growth ratio do not significantly affect corporate value and income tax. Activity ratio resulted in significant effects on the value of enterprise value but not significant impacts on income taxes. In addition, it was found that the enterprise value has a significant effect on the company's credit and corporate income taxes, and that corporate income taxes also have a significant effect on the corporate credit evaluation, and this also shows that there is a mediating function of corporate tax. And as a result of further study, when looking at the financial ratio for eight years from 2011 to 2018, it was found that two variables, KARA and LTAX, are significant at a 1% significant level to KISC, whereas LEVE variables is not significant to KISC. The limitation of this study is that credit rating score and financial score cannot be said to be reliable indicators that investors in the capital market can normally obtain, compared to ranking criteria for corporate bonds or corporate bills directly related to capital procurement costs of enterprise. Above all, it is necessary to develop credit rating score and financial score reflecting financial indicators such as business cash flow or net assets market value and non-financial indicators such as industry growth potential or production efficiency.

• Journal of Animal Environmental Science
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• v.6 no.3
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• pp.175-184
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• 2000

A lab-scale MF membrane reactor was installed to investigate the membrane permeability, characteristics of membrane fouling at each conditions, and quality of permeate (liquid livestock manure) in the separation of solid-matters using membrane. Experiment was divided three filtration type such as follows; continuous filtration, gravity filtration, and intermittent filtration. As a result of experiment, flux 1 LMH was maintained for 7days, and trans-membrane pressure(TMP) was increased gradually under 10cmHg, but it was increased immediately after 10cmHg, respectively. However, the flux was increased, the Tmax was decreased exponential more and more. During the pure-flux test, most of the fouling of membrane was reversible. At the gravity filtration, permeate could be obtained as 1.75 LMH for 3.5days without any other electronic pressure. As an investigation of membrane surface, this study could be decided that the reason of fouling at the lower flux (Run 1 and 2) was attached matters in membrane surface, but at the higher flux (Run 4-6) was concentration polarization.

• Journal of Radiation Protection and Research
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• v.39 no.1
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• pp.21-29
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• 2014

A new cold neutron triple-axis spectrometer (Cold-TAS) was recently constructed at the 30 MWth research reactor, HANARO. The spectrometer, which is composed of neutron optical components and radiation shield, required a redesign of the segmented monochromator shield due to the lack of adequate support of its weight. To shed some weight, lowering the height of the segmented shield was suggested while adding more radiation shield to the top cover of the monochromator chamber. To investigate the radiological effect of such change, we performed MCNPX simulations of a few different configurations of the Cold-TAS monochromator shield and obtained neutron and photon intensities at 5 reference points just outside the shield. Reducing the 35% of the height of the segmented shield and locating lead 10 cm from the bottom of the top cover made of polyethylene was shown to perform just as well as the original configuration as radiation shield excepting gamma flux at two points. Using gamma map by MCNPX, it was checked that is distribution of gamma. Increased flux had direction to the top and it had longer distance from top of segmented shield. However, because of reducing the 35% of the height, height of dissipated gamma was lower than original geometry. Reducing the 35% of the height of the segmented shield and locating lead 10cm from the bottom of the top cover was selected. After changing geometry, radiation dose was measured by TLD for confirming tester's safety at any condition. Neutron(0.21 ${\mu}Svhr^{-1}$) and gamma(3.69 ${\mu}Svhr^{-1}$) radiation dose were satisfied standard(6.25 ${\mu}Svhr^{-1}$).

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.4
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• pp.481-491
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• 2018

As the global business environment is dynamic, uncertain, and complex, supply chain management determines the performance of the supply chain in terms of the utilization of resources and capabilities of companies involved in the supply chain. Companies pursuing open innovation gain greater access to the external environment and accumulate knowledge flows and learning experiences, and may generate better business performance from dynamic capabilities. This study analyzed the effects of supply chain dynamic capabilities, open innovation, and supply uncertainty on supply chain performance. Through questionnaires on 178 companies listed on KOSDAQ, empirical results are as follows: First, integration and reactivity capabilities among supply chain dynamic capabilities have a positive effect on supply chain performance. Second, the moderating effect of open innovation showed a negative correlation in the case of information exchange, and a positive correlation in the cases of integration, cooperation and reactivity. Third, two of the 3-way interaction terms, "information exchange*open innovation*supply uncertainty" and "integration*open innovation*supply uncertainty" were statistically significant. The implications of this study are as follows: First, as the supply chain needs to achieve optimization of the whole process between supply chain components rather than individual companies, dynamic capabilities play an important role in improving performance. Second, for KOSDAQ companies featuring limited capital resources, open innovation that integrates external knowledge is valuable. In order to increase synergistic effects, it is necessary to develop dynamic capabilities accordingly. Third, since resources are constrained, managers must determine the type or level of capabilities and open innovation in accordance with supply uncertainty. Since this study has limitations in analyzing survey data, it is necessary to collect secondary data or longitudinal data. It is also necessary to further analyze the internal and external factors that have a significant impact on supply chain performance.

• Korean Journal of Remote Sensing
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• v.36 no.5_3
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• pp.1109-1123
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• 2020

In South Korea with forest as a major land cover class (over 60% of the country), many wildfires occur every year. Wildfires weaken the shear strength of the soil, forming a layer of soil that is vulnerable to landslides. It is important to identify the severity of a wildfire as well as the burned area to sustainably manage the forest. Although satellite remote sensing has been widely used to map wildfire severity, it is often difficult to determine the severity using only the temporal change of satellite-derived indices such as Normalized Difference Vegetation Index (NDVI) and Normalized Burn Ratio (NBR). In this study, we proposed an approach for determining wildfire severity based on machine learning through the synergistic use of Sentinel-1A Synthetic Aperture Radar-C data and Sentinel-2A Multi Spectral Instrument data. Three wildfire cases-Samcheok in May 2017, Gangreung·Donghae in April 2019, and Gosung·Sokcho in April 2019-were used for developing wildfire severity mapping models with three machine learning algorithms (i.e., Random Forest, Logistic Regression, and Support Vector Machine). The results showed that the random forest model yielded the best performance, resulting in an overall accuracy of 82.3%. The cross-site validation to examine the spatiotemporal transferability of the machine learning models showed that the models were highly sensitive to temporal differences between the training and validation sites, especially in the early growing season. This implies that a more robust model with high spatiotemporal transferability can be developed when more wildfire cases with different seasons and areas are added in the future.