• Journal of the Korean Applied Science and Technology
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• v.38 no.6
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• pp.1466-1475
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• 2021

Compound K (20-O-β-(_D-glucopyranosyl)-20(S)-protopanaxadiol) is an active ingredient of ginsenosides. Compound K has been known to produce from biotransformation by β-glucosidase action of human intestinal microbes after oral admistration of ginseng. We have investigated the cytotoxicity of compound K obtained from bio-converted ginseng extract. As a result, compound K showed no significant cytotoxicity in the concentration of 0.001 to 1 ㎍/mL and inhibited the production of TNF-α, MCP-1, IL-6 and NO in RAW 264.7 cells induced by LPS inflamation. In the same concentration, HaCaT cells induced by inflammation with TNF-α and IFN-γ decreased IL-8 production due to compound K treatment. In the brine shrimp lethality assay, the LC₅₀ of compound K was 0.37 mg/mL indicating some toxicity, but the bioconverted product containing 35% compound K showed relatively low toxicity with an LC₅₀ of 0.87 mg/mL. These results suggest that the compound K enriched extract is a potential functional material for acne relief cosmetic products.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.4
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• pp.276-292
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• 2018

This study was conducted to investigate the trends in domestic and international disaster-related research through a systematic review of the literature and to establish a basis for future disaster-related countermeasures and development directions. A related literature search was conducted through the domestic and foreign databases through the combination of disaster-related terms from 2000 until February 28, 2017, and 79 articles were used in the analysis based on selection and exclusion criteria of 177 total documents. As a result of the research, 31.6% of disaster research type was quantitative studies, and 29.1% of the major disciplines were medical research. In addition, there were engineering(18.9%), public administration(13.9%), and nursing(11.4%). In foreign literature, there are many triage studies for the classification of patients in multiple lesions. On the other hand, only 30.4% of total triage studies in Korea were detected. Most of them were related to triage development, triage evaluation, triage research, and reviews. In addition, according to the disaster nursing capacity framework of the International Council of Nurses, 72.3% of studies were related to the response phase. Future research on disasters requires interdisciplinary convergence, patient classification, and technology integration to improve the survival rate of multiple injuries, and an integrated system based on the results of collaborative research among interdisciplinary groups is needed.

• Journal of the Korean Crystal Growth and Crystal Technology
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• v.33 no.6
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• pp.255-260
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• 2023

As demanding the detection of explosive molecules, it is required to develop rapidly and precisely responsive sensors with ultra-high sensitivity. Since two-dimensional semiconductors have an atomically thin body nature where mobile carriers accumulate, the abrupt modulation carrier in the thin body channel can be expected. To investigate the effectiveness of WSe₂ semiconductor materials as a detection material for TNT (Trinitrotoluene) explosives, WSe₂ was synthesized using thermal chemical vapor deposition, and afterward, WSe₂ FETs (Field Effect Transistors) were fabricated using standard photo-lithograph processes. Raman Spectrum and FT-IR (Fourier-transform infrared) spectroscopy reveal that the adsorption of TNT molecules induces the structural transition of WSe₂ crystalline. The electrical properties before and after adsorption of TNT molecules on the WSe₂ surface were compared; as -50 V was applied as the back gate bias, 0.02 μA was recorded in the bare state, and the drain current increased to 0.41 μA with a dropping 0.6% (w/v) TNT while maintaining the p-type behavior. Afterward, the electrical characteristics were additionally evaluated by comparing the carrier mobility, hysteresis, and on/off ratio. Consequently, the present report provides the milestone for developing ultra-sensitive sensors with rapid response and high precision.

• The Journal of the Convergence on Culture Technology
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• v.6 no.1
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• pp.135-145
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• 2020

This research is mainly aimed at finding out about the effects of the safety and health management system on corporate performance through systematic operation by efficiently allocating material and human resources within the company by participating all employees and stakeholders in order to prevent and maintain industrial accidents and the optimal working environment, and how to maintain and activate the safety and health management system at the center of electric contractors.The analysis results are as follows. First, management, organizational management and resource preparation will have a positive impact on the management capability of the electric power corporation. It was assessed that the more well-transmitted and understood within the organization, the better the construction plan, the better the equipment management status, the more positively the management capability of electric works was to be achieved. Second, management, organizational management and resource preparation will have a positive impact on corporate management performance.This seems to have a positive effect on a company's business performance when the standards of OHSAS are met with construction plan and construction equipment management are high as related information such as industrial safety and health laws are strengthened and companies' safety and health activities, advanced safety and culture are released to facilitate organizational management.Third, the management ability of the electric power corporation will have a mediated effect on the effect of management, organization management and resource preparation on the performance of the enterprise. This means that the direct effect of the independent variable management organization on corporate management performance is .401 The indirect effect is .168.658 shows that the direct effect of resource preparation on corporate management performance is .423, the indirect effect is .178 and the total effect.It was analyzed at 643.

• Korean Journal of Remote Sensing
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• v.39 no.5_3
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• pp.949-965
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• 2023

In this study, we propose a method to monitor the surface area of agricultural reservoirs in South Korea using Sentinel-1 synthetic aperture radar images and the deep learning model, Swin Transformer. Utilizing the Google Earth Engine platform, datasets from 2017 to 2021 were constructed for seven agricultural reservoirs, categorized into 700 K-ton, 900 K-ton, and 1.5 M-ton capacities. For four of the reservoirs, a total of 1,283 images were used for model training through shuffling and 5-fold cross-validation techniques. Upon evaluation, the Swin Transformer Large model, configured with a window size of 12, demonstrated superior semantic segmentation performance, showing an average accuracy of 99.54% and a mean intersection over union (mIoU) of 95.15% for all folds. When the best-performing model was applied to the datasets of the remaining three reservoirsfor validation, it achieved an accuracy of over 99% and mIoU of over 94% for all reservoirs. These results indicate that the Swin Transformer model can effectively monitor the surface area of agricultural reservoirs in South Korea.

• Clean Technology
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• v.17 no.3
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• pp.215-224
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• 2011

It is an important issue to develop quality assessing system for biofuel for the purpose of accelerating the mass production of biofuel. It is particularly challenging to conduct testing method in the mass production of bioethanol while meeting quality specifications such as ASTM (American Society for Testing & Materials) D4806-10. In order to address this challenge, this paper proposes on-line spectroscopic quality assesment system based on Near Infrared spectrum and Partial Least Squares method in Chemometrics. As a result of testing a number of preprocessing methods and Partial Least Squares, it was found out that Savitzky-Golay method showed the best performance in terms of spectrum correction, noise reduction, and model maintenance. The proposed system allows us to assess multiple quality components continuously using spectroscopic facilities with the cheap cost. Since the value of R2 is more than 0.99, it is possible to replace the laboratory analysis.

• Journal of the Korea institute for structural maintenance and inspection
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• v.27 no.2
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• pp.25-32
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• 2023

In this study, a double wall system is introduced, which was invented to simplify the complicated manufacturing process of the existing precast concrete (PC) double wall systems and to remove defects such as laitance that may occur during the production of concrete panels. An experimental study was conducted to investigate the tensile resisting capacity of the steel tube which is embedded in the precast concrete panel to keep the spacing between PC panels and to prevent damage of the PC panels during transportation and casting concrete onsite. The experiment was planned to determine the detail of effective steel tube connection considering the steel plate treatment method according to the formation of the opening, the presence of embedded concrete, and the reinforcement welding for additional dowel action as key variables. As a result, the ultimate tensile strength increased by 20-30% compared to the control specimen (ST) except for the steel tube specimen (ST_CP) which has steel plates bent inward at the end part of the steel tube. Since the specimen (ST_CON) filled with concrete inside the control specimen has no additional process and cost for the steel tube connections compared to the control specimen during the production of the developed double wall system, it is determined to be the appropriate detail of steel tube connection.

• Journal of the Korean Geotechnical Society
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• v.37 no.2
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• pp.5-17
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• 2021

The Moon has been an attractive planet as an outpost for deep space exploration since He-3 and water ice which can be used as energy resources were discovered. In-Situ Resource Utilization (ISRU) construction material fabrication method is required for sustainable space planet exploration. In this paper, the possibility of microwave sintering technology for construction material fabrication was evaluated using lunar regolith that can be easily collected from the Moon surface. Experimental assessment of the influence factors on microwave sintering was conducted using a hybrid sintering system for efficient processing. The heat distribution in the furnace was observed using thermal paper that is coated with a material formulated to change color when exposed to heat. Based on this result, sintered cylindrical KLS-1s with a diameter of 1 cm and a height of 2 cm were fabricated. Densities were measured for the sintered KLS-1s under rotating turntable conditions that have an effect of microwave dispersion. The more dielectrics were arranged, the more microwaves were dispersed reducing the heat concentration, and thus a uniformity of sintered KLS-1s was enhanced.

• Journal of Technology Innovation
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• v.29 no.4
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• pp.1-30
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• 2021

Due to the recent development of system semiconductors, technical innovation for the electric devices of the automobile industry is rapidly progressing. In particular, the electric device of automobiles is accelerating technology development competition among automobile parts makers, and the development cycle is also changing rapidly. Due to these changes, the importance of strategic planning for R&D is further strengthened. Due to the paradigm shift in the automobile industry, the Product-Technical Roadmap (P/TRM), one of the R&D strategies, analyzes technology forecasting, technology level evaluation, and technology acquisition method (Make/Collaborate/Buy) at the planning stage. The product-technical roadmap is a tool that identifies customer needs of products and technologies, selects technologies and sets development directions. However, most companies are developing the product-technical roadmap through a qualitative method that mainly relies on the technical papers, patent analysis, and expert Delphi method. In this study, empirical research was conducted through simulations that can supplement and strengthen the product-technical roadmap centered on the automobile industry by fusing Gartner's hype cycle, cumulative moving average-based data preprocessing, and deep learning (LSTM) time series analysis techniques. The empirical study presented in this paper can be used not only in the automobile industry but also in other manufacturing fields in general. In addition, from the corporate point of view, it is considered that it will become a foundation for moving forward as a leading company by providing products to the market in a timely manner through a more accurate product-technical roadmap, breaking away from the roadmap preparation method that has relied on qualitative methods.

• Journal of Intelligence and Information Systems
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• v.18 no.3
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• pp.79-96
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• 2012

As the pace of competition dramatically accelerates and the complexity of change grows, a variety of research have been conducted to improve firms' short-term performance and to enhance firms' long-term survival. In particular, researchers and practitioners have paid their attention to identify promising technologies that lead competitive advantage to a firm. Discovery of promising technology depends on how a firm evaluates the value of technologies, thus many evaluating methods have been proposed. Experts' opinion based approaches have been widely accepted to predict the value of technologies. Whereas this approach provides in-depth analysis and ensures validity of analysis results, it is usually cost-and time-ineffective and is limited to qualitative evaluation. Considerable studies attempt to forecast the value of technology by using patent information to overcome the limitation of experts' opinion based approach. Patent based technology evaluation has served as a valuable assessment approach of the technological forecasting because it contains a full and practical description of technology with uniform structure. Furthermore, it provides information that is not divulged in any other sources. Although patent information based approach has contributed to our understanding of prediction of promising technologies, it has some limitations because prediction has been made based on the past patent information, and the interpretations of patent analyses are not consistent. In order to fill this gap, this study proposes a technology forecasting methodology by integrating patent information approach and artificial intelligence method. The methodology consists of three modules : evaluation of technologies promising, implementation of technologies value prediction model, and recommendation of promising technologies. In the first module, technologies promising is evaluated from three different and complementary dimensions; impact, fusion, and diffusion perspectives. The impact of technologies refers to their influence on future technologies development and improvement, and is also clearly associated with their monetary value. The fusion of technologies denotes the extent to which a technology fuses different technologies, and represents the breadth of search underlying the technology. The fusion of technologies can be calculated based on technology or patent, thus this study measures two types of fusion index; fusion index per technology and fusion index per patent. Finally, the diffusion of technologies denotes their degree of applicability across scientific and technological fields. In the same vein, diffusion index per technology and diffusion index per patent are considered respectively. In the second module, technologies value prediction model is implemented using artificial intelligence method. This studies use the values of five indexes (i.e., impact index, fusion index per technology, fusion index per patent, diffusion index per technology and diffusion index per patent) at different time (e.g., t-n, t-n-1, t-n-2, ${\cdots}$) as input variables. The out variables are values of five indexes at time t, which is used for learning. The learning method adopted in this study is backpropagation algorithm. In the third module, this study recommends final promising technologies based on analytic hierarchy process. AHP provides relative importance of each index, leading to final promising index for technology. Applicability of the proposed methodology is tested by using U.S. patents in international patent class G06F (i.e., electronic digital data processing) from 2000 to 2008. The results show that mean absolute error value for prediction produced by the proposed methodology is lower than the value produced by multiple regression analysis in cases of fusion indexes. However, mean absolute error value of the proposed methodology is slightly higher than the value of multiple regression analysis. These unexpected results may be explained, in part, by small number of patents. Since this study only uses patent data in class G06F, number of sample patent data is relatively small, leading to incomplete learning to satisfy complex artificial intelligence structure. In addition, fusion index per technology and impact index are found to be important criteria to predict promising technology. This study attempts to extend the existing knowledge by proposing a new methodology for prediction technology value by integrating patent information analysis and artificial intelligence network. It helps managers who want to technology develop planning and policy maker who want to implement technology policy by providing quantitative prediction methodology. In addition, this study could help other researchers by proving a deeper understanding of the complex technological forecasting field.