• Journal of the Korean Applied Science and Technology
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• v.36 no.1
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• pp.324-332
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• 2019

Most countries including Korea and Indonesia have strong policy for implementing biofuels like biodiesel. Shortage of the oil feedstock is the main barrier for increasing the supply of biodiesel fuel. In this study, in order to improve the stability of feedstock supply and lower the biodiesel production cost, the feasibility of biodiesel production using two types of Indonesian tropical crop oils, pressed at different harvesting times, were investigated. R. Trisperma oils, a high productive non-edible feedstocks, were investigated to produce biodiesel by esterification and transesterification because of it's high impurity and free fatty acid contents. the kindly provided oils from Indonesia were required to perform the filtering and water removal process to increase the efficiency of the esterificaton and transesterification reactions. The esterification used heterogeneous acid catalyst, Amberlyst-15. Before the reaction, the acid value of two types oil were 41, 17 mg KOH/g respectively. After the pre-esterification reaction, the acid value of oils were 3.7, 1.8 mg KOH/g respectively, the conversions were about 90%. Free fatty acid content was reduced to below 2%. Afterwards, the transesterification was performed using KOH as the base catalyst for transesterification. The prepared biodiesel showed about 93% of FAME content, and the total glycerol content was 0.43%. It did not meet the quality specification(FAME 96.5% and Total glycerol 0.24%) since the tested oils were identified to have a uncommon fatty acid, generally not found in vegetable oils, ${\alpha}$-eleostearic acid with much contents of 10.7~33.4%. So, it is required to perform the further research on reaction optimization and product purification to meet the fuel quality standards. So if the biodiesel production technology using un-utilized non-edible feedstock oils is successfully developed, stable supply of the feedstock for biodiesel production may be possible in the future.

• Journal of the Korea Organic Resources Recycling Association
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• v.29 no.3
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• pp.41-48
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• 2021

This study aimed to develop an alternative organic fertilizer to castor oil cake-based fertilizers. To assess the nutrient effect of the developed fermented mixed organic fertilizers, the yield of lettuce and soil characteristics after growth were analyzed and compared to those of a trial using a mixed expeller cake fertilizer. Two fermented mixed organic fertilizers, FA and FB, each containing 5.0% nitrogen, 2.6% phosphate, and 1.4% potassium, were produced by mixing different ratios of rice bran, dried distillers grains, sesame oil meal, and fish meal. This study was conducted with six trials: untreated, mixed expeller cake fertilizer, and the fermented mixed organic fertilizers FA and FB. Based on the amount of nitrogen fertilization (70 kg ha^-1) on the lettuce, the fermented mixed organic fertilizers FA and FB were applied at 100% and 150%, respectively, and the mixed oil cake was applied at 100%. As the amount of treatment increased, there was no significant difference except the number of leaves in FA treatment. The yields from the FA100 and FB100 treatments were 38.2 and 40.8 Mg ha^-1, respectively, which was not significantly different from that of the mixed expeller cake fertilizer treatment at 38.3 Mg ha^-1. In addition, the nitrogen uptake and utilization efficiency of the lettuce were not significantly different between mixed expeller cake fertilizer and fermented mixed organic fertilizer treatments. Analysis of the chemical properties of the soil after the trial showed that he mixed expeller cake fertilizer treatment showed the lowest pH. There were no significant differences in electrical conductivity, content of soil organic matter, available phosphate, and exchangeable cation among the fertilizer treatments. However, the bacterial and actinomyces density was higher in the soil from the fertilizer trials than in the non-fertilizer trials. These results indicated that the two tested fermented mixed organic fertilizers had nourishing effects and soil characteristics that were similar to those of the mixed expeller cake fertilizer. Thus, farmers can use these fermented mixed organic fertilizers as alternatives to castor oil cakes for the cultivation of organic lettuce.

• Clean Technology
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• v.26 no.4
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• pp.329-335
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• 2020

Methanol synthesized from renewable hydrogen and captured CO2 has recently attracted great interest as a sustainable energy carrier for large-scale renewable energy storage. In this study, molten carbonate fuel cell's performance was investigated with the direct conversion of methanol into syngas inside the anode chamber of the cell. The internal reforming of methanol may significantly improve system efficiency since the heat generated from the electrochemical reaction can be used directly for the endothermic reforming reaction. The porous Ni-10 wt%Cr anode was sufficient for the methanol steam reforming reaction under the fuel cell operating condition. The direct supply of methanol into the anode chamber resulted in somewhat lower cell performance, especially at high current density. Recycling of the product gas into the anode gas inlet significantly improved the cell performance. The analysis based on material balance revealed that, with increasing current density and gas recycling ratio, the methanol steam reforming reaction rate likewise increased. A methanol conversion more significant than 90% was achieved with gas recycling. The results showed the feasibility of electricity and syngas co-production using the molten carbonate fuel cell. Further research is needed to optimize the fuel cell operating conditions for simultaneous production of electricity and syngas, considering both material and energy balances in the fuel cell.

• Clean Technology
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• v.28 no.1
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• pp.79-93
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• 2022

In this study, an electronics industrial wastewater activated sludge model (e-ASM) to be used as a Water Digital Twin was calibrated based on real high-tech electronics industrial wastewater treatment measurements from lab-scale and pilot-scale reactors, and examined for its treatment performance, effluent quality prediction, and optimal process selection. For specialized modeling of a high-tech electronics industrial wastewater treatment system, the kinetic parameters of the e-ASM were identified by a sensitivity analysis and calibrated by the multiple response surface method (MRS). The calibrated e-ASM showed a high compatibility of more than 90% with the experimental data from the lab-scale and pilot-scale processes. Four electronics industrial wastewater treatment processes-MLE, A2/O, 4-stage MLE-MBR, and Bardenpo-MBR-were implemented with the proposed Water Digital Twin to compare their removal efficiencies according to various electronics industrial wastewater characteristics. Bardenpo-MBR stably removed more than 90% of the chemical oxygen demand (COD) and showed the highest nitrogen removal efficiency. Furthermore, a high concentration of 1,800 mg L^-1 T MAH influent could be 98% removed when the HRT of the Bardenpho-MBR process was more than 3 days. Hence, it is expected that the e-ASM in this study can be used as a Water Digital Twin platform with high compatibility in a variety of situations, including plant optimization, Water AI, and the selection of best available technology (BAT) for a sustainable high-tech electronics industry.

• Journal of Intelligence and Information Systems
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• v.27 no.4
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• pp.23-48
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• 2021

The Korean economy has achieved continuous economic growth for the past several decades thanks to the government's export strategy policy. This increase in exports is playing a leading role in driving Korea's economic growth by improving economic efficiency, creating jobs, and promoting technology development. Traditionally, the main factors affecting Korea's exports can be found from two perspectives: economic factors and industrial structural factors. First, economic factors are related to exchange rates and global economic fluctuations. The impact of the exchange rate on Korea's exports depends on the exchange rate level and exchange rate volatility. Global economic fluctuations affect global import demand, which is an absolute factor influencing Korea's exports. Second, industrial structural factors are unique characteristics that occur depending on industries or products, such as slow international division of labor, increased domestic substitution of certain imported goods by China, and changes in overseas production patterns of major export industries. Looking at the most recent studies related to global exchanges, several literatures show the importance of cultural aspects as well as economic and industrial structural factors. Therefore, this study attempted to develop a forecasting model by considering cultural factors along with economic and industrial structural factors in calculating the import volume of each country from Korea. In particular, this study approaches the influence of cultural factors on imports of Korean products from the perspective of PUSH-PULL framework. The PUSH dimension is a perspective that Korea develops and actively promotes its own brand and can be defined as the degree of interest in each country for Korean brands represented by K-POP, K-FOOD, and K-CULTURE. In addition, the PULL dimension is a perspective centered on the cultural and psychological characteristics of the people of each country. This can be defined as how much they are inclined to accept Korean Flow as each country's cultural code represented by the country's governance system, masculinity, risk avoidance, and short-term/long-term orientation. The unique feature of this study is that the proposed final prediction model can be selected based on Design Principles. The design principles we presented are as follows. 1) A model was developed to reflect interest in Korea and cultural characteristics through newly added data sources. 2) It was designed in a practical and convenient way so that the forecast value can be immediately recalled by inputting changes in economic factors, item code and country code. 3) In order to derive theoretically meaningful results, an algorithm was selected that can interpret the relationship between the input and the target variable. This study can suggest meaningful implications from the technical, economic and policy aspects, and is expected to make a meaningful contribution to the export support strategies of small and medium-sized enterprises by using the import forecasting model.

• Journal of Bio-Environment Control
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• v.31 no.4
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• pp.468-475
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• 2022

This study was conducted to find out the efficiency of heating initiative temperature and carbon dioxide fertilization in summer squash (Cucurbita moschata D.). The heating start temperature experiment was performed at 9℃, 12℃, and 15℃ using an electric heater and operated when the temperature was lower than the target temperature. The CO₂ fertilization concentration experiment was performed from 7 to 12 with the control, 500 µmol·mol^-1, and 800 µmol·mol^-1 using liquefied carbon dioxide. Investigation items were plant height, stem diameter, number of leaves, leaf area, fresh weight, dry weight, also economic analysis was conducted by surveying only fruits exceeding 100 g. Photosynthesis was measured for the upper leaf position to calculate the saturation point according to the control. The photo saturation point was 587 µmol·m^-2·s^-1, and the CO₂ saturation point was 702 µmol·mol^-1. A_max values by carbon dioxide were 13.4, 17.8, 17.2, 19.6, and 17.5 µmolCO₂·m^-2·s^-1 in the order of 9℃, 12℃, 15℃, 500 µmol·mol^-1, and 800 µmol·mol^-1. In the temperature experiment, 9℃ in growth did not grow normally and no fruiting was performed. 12℃ and 15℃ were higher than 9℃, but there was no significant difference in growth and production. The CO₂ fertilization experiment showed no significant difference between the treatment in growth, but the productivity of 800 µmol·mol^-1 was the best. Comprehensively, the heating initiative temperature of 15℃ was good for crop growth and production, but there is no significant difference from 12℃, so it is good to set the heating start temperature to 12℃ economically, and maintaining of 800 µmol·mol^-1 is effective in increasing production.

• Journal of Life Science
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• v.32 no.11
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• pp.872-881
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• 2022

In this study, we optimized the composition of the indole-3-acetic acid (IAA) production medium using response surface methodology on Pantoea agglomerans SRCM 119864 isolated from soil. IAA-producing P. aglomerans SRCM 119864 was identified by 16S rRNA gene sequencing. There are 11 intermediate components known to affect IAA production, hence the effect of each component on IAA production was investigated using a Plackett-Burman design (PBD). Based on the PBD, sucrose, tryptone, and sodium chloride were selected as the main factors that enhanced the IAA production at optimal L-tryptophan concentration. The predicted maximum IAA production (64.34 mg/l) was obtained for a concentration of sucrose of 13.38 g/l, of tryptone of 18.34 g/l, of sodium chloride of 9.71 g/l, and of L-tryptophan of 6.25 g/l using a the hybrid design experimental model. In the experiment, the nutrient broth medium supplemented with 0.1% L-tryptophan as the basal medium produced 45.24 mg/l of IAA, whereas the optimized medium produced 65.40 mg/l of IAA, resulting in a 44.56% increase in efficiency. It was confirmed that the IAA production of the designed optimal composition medium was very similar to the predicted IAA production. The statistical significance and suitability of the experimental model were verified through analysis of variance (ANOVA). Therefore, in this study, we determined the optimal growth medium concentration for the maximum production of IAA, which can contribute to sustainable agriculture and increase crop yield.

• Resources Recycling
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• v.31 no.1
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• pp.65-77
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• 2022

A study was conducted in Korea on the leaching behavior and possibility of recovery of vanadium and other valuable metals from domestic vanadium titanomagnetite (VTM) by direct acid leaching. In this study, a VTM concentrate containing 0.8% V₂O₅ was used, and the ratio of magnetite to ilmenite was calculated as 1.9:1 by using the HSC program. The leaching behavior of vanadium from the VTM was similar to that of iron, and it was affected by the concentration of sulfuric acid and temperature. Further, titanium could be leached in the form of TiOSO₄ at a temperature higher than 75℃. To improve the leaching efficiency of V, Fe, and Ti in VTM, reductive sulfuric acid and oxidative sulfuric acid leaching were performed. When Na₂SO₃ was used as a reducing agent, the leaching rate of vanadium was 80% of that in that case of leaching by sulfuric acid. Similarly, the leaching rate of titanium increased from 20% to 50%. When Na₂S₂O₈ was used as an oxidation agent, most of the vanadium was leached, and the main residue found by XRD analysis was ilmenite. In studies on the possibility of recovering valuable metals, the selective extraction of metals is hardly achieved by solvent extraction from oxidation leaching solutions; however, in this study, Cyanex 923, a solvation extractant from reductive leaching solutions, could selectively extract Ti.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.9
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• pp.317-322
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• 2022

The rapid development of information technology is also bringing about many changes in the medical environment. In particular, it is leading the rapid change of medical image information systems using big data and artificial intelligence (AI). The prescription delivery system (OCS), which consists of an electronic medical record (EMR) and a medical image storage and transmission system (PACS), has rapidly changed the medical environment from analog to digital. When combined with multiple solutions, PACS represents a new direction for advancement in security, interoperability, efficiency and automation. Among them, the combination with artificial intelligence (AI) using big data that can improve the quality of images is actively progressing. In particular, AI PACS, a system that can assist in reading medical images using deep learning technology, was developed in cooperation with universities and industries and is being used in hospitals. As such, in line with the rapid changes in the medical image information system in the medical environment, structural changes in the medical market and changes in medical policies to cope with them are also necessary. On the other hand, medical image information is based on a digital medical image transmission device (DICOM) format method, and is divided into a tomographic volume image, a volume image, and a cross-sectional image, a two-dimensional image, according to a generation method. In addition, recently, many medical institutions are rushing to introduce the next-generation integrated medical information system by promoting smart hospital services. The next-generation integrated medical information system is built as a solution that integrates EMR, electronic consent, big data, AI, precision medicine, and interworking with external institutions. It aims to realize research. Korea's medical image information system is at a world-class level thanks to advanced IT technology and government policies. In particular, the PACS solution is the only field exporting medical information technology to the world. In this study, along with the analysis of the medical image information system using big data, the current trend was grasped based on the historical background of the introduction of the medical image information system in Korea, and the future development direction was predicted. In the future, based on DICOM big data accumulated over 20 years, we plan to conduct research that can increase the image read rate by using AI and deep learning algorithms.

• The Mathematical Education
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• v.62 no.3
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• pp.435-455
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• 2023

This study primarily focused on the development of an Explainable Artificial Intelligence (XAI) model to discern and analyze papers with significant impact in the field of mathematics education. To achieve this, meta-information from 29 domestic and international mathematics education journals was utilized to construct a comprehensive academic research network in mathematics education. This academic network was built by integrating five sub-networks: 'paper and its citation network', 'paper and author network', 'paper and journal network', 'co-authorship network', and 'author and affiliation network'. The Random Forest machine learning model was employed to evaluate the impact of individual papers within the mathematics education research network. The SHAP, an XAI model, was used to analyze the reasons behind the AI's assessment of impactful papers. Key features identified for determining impactful papers in the field of mathematics education through the XAI included 'paper network PageRank', 'changes in citations per paper', 'total citations', 'changes in the author's h-index', and 'citations per paper of the journal'. It became evident that papers, authors, and journals play significant roles when evaluating individual papers. When analyzing and comparing domestic and international mathematics education research, variations in these discernment patterns were observed. Notably, the significance of 'co-authorship network PageRank' was emphasized in domestic mathematics education research. The XAI model proposed in this study serves as a tool for determining the impact of papers using AI, providing researchers with strategic direction when writing papers. For instance, expanding the paper network, presenting at academic conferences, and activating the author network through co-authorship were identified as major elements enhancing the impact of a paper. Based on these findings, researchers can have a clear understanding of how their work is perceived and evaluated in academia and identify the key factors influencing these evaluations. This study offers a novel approach to evaluating the impact of mathematics education papers using an explainable AI model, traditionally a process that consumed significant time and resources. This approach not only presents a new paradigm that can be applied to evaluations in various academic fields beyond mathematics education but also is expected to substantially enhance the efficiency and effectiveness of research activities.