• Journal of Environmental Impact Assessment
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• v.32 no.4
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• pp.214-229
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• 2023

This study was aimed to derive the following regional characteristics and implications by reviewing the effects of local communities and overseas cases through agricultural heritage and related systems to prepare rural regeneration measures using agricultural and rural heritage. First, The study was examined to improve the awareness to improve awareness of the value and preservation of heritage through the designation of agricultural heritage. However, it was found that it was necessary to prepare for social problems such as the aging population in the future. Second, most of the residents' perceptions showed a positive perception of the designation of agricultural heritage, but they were somewhat less recognized in terms of economics, so it was found that regeneration measures were needed to compensate for this. Third, as a result of applying the effect measurement model, the preservation and management effect that meets the purpose of the system is high, and the effect varies depending on projects such as local governments and residents' councils. Fourth, as a result of examining rural regeneration measures through overseas cases, it was found that rather than large-scale development, various cultural and natural resources and activation measures were prepared by expanding the scope to surrounding areas. This study was conducted only on agricultural heritage areas, but it is meaningful that agricultural and rural heritage should be reviewed from various perspectives suitable for the current trend, and it is meaningful in that it considers not only local residents' perception but also regional effects and revitalization measures.

• The Journal of Internal Korean Medicine
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• v.44 no.3
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• pp.402-417
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• 2023

Objective: Liver fibrosis is a highly conserved wound-healing response and the final common pathway of chronic inflammatory injury. This study aimed to evaluate the potential anti-fibrotic effect of the combination of Rhei Radix et Rhizoma water extract (RW) and silymarin in a thioacetamide (TAA)-induced liver fibrosis model. Methods: The liver fibrosis mouse model was established through the intraperitoneal injection of TAA (1 week 100 mg/kg, 2-3 weeks 200 mg/kg, 4-8 weeks 400 mg/kg) three times per week for eight weeks. Animal experiments were conducted in five groups; Normal, Control (TAA-induced liver fibrosis mice), Sily (silymarin 50 mg/kg), RSL (RW 50 mg/kg+silymarin 50 mg/kg), and RSH (RW 100 mg/kg+silymarin 50 mg/kg). Biochemical analyses were measured in serum, including aspartate aminotransferase (AST), alanine aminotransferase (ALT), malondialdehyde (MDA), and ammonia levels. Liver inflammatory cytokines and fibrous biomarkers were measured by Western blot analysis, and liver histopathology was evaluated through tissue staining. Results: A significant decrease in the liver function markers AST and ALT and a reduction in ammonia and total bilirubin were observed in the group treated with RSL and RSH. Measurement of reactive oxygen species and MDA revealed a significant decrease in the RSL and RSH administration group compared to the TAA induction group. The expression of extracellular matrix-related proteins, such as transforming growth factor β1, α-smooth muscle actin, and collagen type I alpha 1, was likewise significantly decreased. All drug-administered groups had increased matrix metalloproteinase-9 but a decreasing tissue inhibitor of matrix metalloproteinase-1. RSL and RSH exerted a significant upregulation of NADPH oxidase 2, p22^phox, and p47^phox, which are oxidative stress-related factors. Furthermore, pro-inflammatory proteins such as cyclooxygenase 2 and interleukin-1β were markedly suppressed through the inhibition of nuclear factor kappa B activation. Conclusions: The administration of RW and silymarin suppressed the NADPH oxidase factor protein level and showed a tendency to reduce inflammation-related enzymes. These results suggest that the combined administration of RW and silymarin improves acute liver injury induced by TAA.

• Applied Chemistry for Engineering
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• v.35 no.1
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• pp.16-22
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• 2024

Polymer electrolyte membrane fuel cells have the advantage of low operating temperatures and fast startup and response characteristics compared to others. Simulation studies are actively researched because their cost and time benefits. In this study, the resistance of water residual in the gas diffusion layer (GDL) of the unit cell was added to the existing equation to compare the actual data with the model data. The experiments were conducted with a 25 cm² unit cell, and the samples were separated into stopping times of 0, 10, and 60 minutes following primary impedance measurement, activation, and polarization curve data acquisition. This gives 0, 10, and 60 minutes for the residual water in the GDL to evaporate. Without the rest period, the magnitude of the performance improvement was not significantly different at the same potential and flow rate, but the rest period did improve the performance of the membrane electrode assembly when measuring impedance. By changing the magnitude of the resistance reduction to an overvoltage, the voltage difference between the fuel cell model with and without residual water was compared, and the error rate in the high current density region, which is dominated by concentration losses, was reduced.

• The Transactions of the Korea Information Processing Society
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• v.13 no.4
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• pp.199-207
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• 2024

Local reservoirs are crucial sources for agricultural water supply, necessitating stable water level management to prepare for extreme climate conditions such as droughts. Water level prediction is significantly influenced by local climate characteristics, such as localized rainfall, as well as seasonal factors including cropping times, making it essential to understand the correlation between input and output data as much as selecting an appropriate prediction model. In this study, extensive multivariate data from over 400 reservoirs in Jeollabuk-do from 1991 to 2022 was utilized to train and validate a water level prediction model that comprehensively reflects the complex hydrological and climatological environmental factors of each reservoir, and to analyze the impact of each input feature on the prediction performance of water levels. Instead of focusing on improvements in water level performance through neural network structures, the study adopts a basic Feedforward Neural Network composed of fully connected layers, batch normalization, dropout, and activation functions, focusing on the correlation between multivariate input data and prediction performance. Additionally, most existing studies only present short-term prediction performance on a daily basis, which is not suitable for practical environments that require medium to long-term predictions, such as 10 days or a month. Therefore, this study measured the water level prediction performance up to one month ahead through a recursive method that uses daily prediction values as the next input. The experiment identified performance changes according to the prediction period and analyzed the impact of each input feature on the overall performance based on an Ablation study.

• Cartoon and Animation Studies
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• s.26
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• pp.131-156
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• 2012

As the Global Age has arrived, the domain of festivals has expanded to fulfill the role of being not only a tourist attraction but of being a factor that determines the image and identity of cities, and the factor of enhancing the brand value of a particular city is being focused upon. The city of Bucheon, which aims to be a culture oriented city, is attempting to utilize the Bucheon International Comics Festival as a cultural asset for the revitalization of the city. This study has as its purpose the development of an evaluation index model on the brand value of the Bucheon International Comics Festival and research being conducted based on the developed evaluation index model on the awareness level of the citizens of Bucheon of the festival. In regards to this, the theoretical background was examined and the index model was developed based on precedent research. Based on this, a survey of 1,000 citizens of Bucheon was conducted in this study. This study conducted a survey targeting 500 persons, dividing them into 2 groups according to whether they participated in the festival. The survey of this study established 9 evaluation categories for the International Comics Festival evaluation index model which consists of demographic research and participation motivation, value of comics, festival brand awareness and association image, perceived product quality and loyalty for the festival, internationality of the festival and urban activation. Each survey question is composed of 5 points scale measurement. As a result of the survey, 'for an education of children' was the highest for the participation motivation, and 'not knowing of the festival information' was the highest for the reason of not having participated. The industrial value was evaluated as the highest among the value of comics by the both two groups, and it was studied that there was perception gap for the festival according to whether they participated in the festival for each survey question. It was revealed that the level of awareness of the Bucheon International Comics Festival was "normal," the "city revitalization" index and the "value of comics" index were relatively high and the "international character of the festival" index was the lowest. Furthermore, it was shown that there were differences in the awareness of the established categories of the developed evaluation index model based on whether or not there was participation in the festival. This study comprehensively organizes these analytical results and derives implications which can be used as data for the criteria of the development of future strategy for the Bucheon International Comics Festival.

• Journal of Chest Surgery
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• v.32 no.7
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• pp.603-612
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• 1999

Background : It has been documented that brief repetitive periods of ischemia and reperfusion (ischemic preconditioning, IP) enhances the recovery of post-ischemic contractile function and reduces infarct size after a longer period of ischemia. Many mechanisms have been proposed to explain this process. Recent studies have suggested that transient increase in the intracellular calcium may have triggered the activation of protein kinase C(PKC); however, there are still many controversies. Accordingly, the author performed the present study to test the hypothesis that preconditioning with high concentration of calcium before sustained subsequent ischemia(calcium preconditioning) mimics IP by PKC activation. Material and Method : The isolated hearts from the New Zealand White rabbits(1.5∼2.0 kg body weight) Method: The isolated hearts from the New Zealand White rabbits(1.5∼2.0 kg body weight) were perfused with Tyrode solution by Langendorff technique. After stabilization of baseline hemodynamics, the hearts were subjected to 45-minute global ischemia followed by a 120-minute reperfusion with IP(IP group, n=13) or without IP(ischemic control, n=10). IP was induced by single episode of 5-minute global ischemia and 10-minute reperfusion. In the Ca2+ preconditioned group, perfusate containing 10(n=10) or 20 mM(n=11) CaCl2 was perfused for 10 minutes after 5-minute ischemia followed by a 45-minute global ischemia and a 120-minute reperfusion. Baseline PKC was measured after 50-minute perfusion without any treatment(n=5). Left ventricular function including developed pressure(LVDP), dP/dt, heart rate, left ventricular end-diastolic pressure(LVEDP) and coronary flow(CF) was measured. Myo car ial cytosolic and membrane PKC activities were measured by 32P-${\gamma}$-ATP incorporation into PKC-specific pepetide. The infarct size was determined using the TTC (tetrazolium salt) staining and planimetry. Data were analyzed using one-way analysis of variance(ANOVA) variance(ANOVA) and Tukey's post-hoc test. Result: IP increased the functional recovery including LVDP, dP/dt and CF(p<0.05) and lowered the ascending range of LVEDP(p<0.05); it also reduced the infarct size from 38% to 20%(p<0.05). In both of the Ca2+ preconditioned group, functional recovery was not significantly different in comparison with the ischemic control, however, the infarct size was reduced to 19∼23%(p<0.05). In comparison with the baseline(7.31 0.31 nmol/g tissue), the activities of the cytosolic PKC tended to decrease in both the IP and Ca2+ preconditioned groups, particularly in the 10 mM Ca2+ preconditioned group(4.19 0.39 nmol/g tissue, p<0.01); the activity of membrane PKC was significantly increased in both IP and 10 mM Ca2+ preconditioned group (p<0.05; 1.84 0.21, 4.00 0.14, and 4.02 0.70 nmol/g tissue in the baseline, IP, and 10 mM Ca2+ preconditioned group, respectively). However, the activity of both PKC fractions were not significantly different between the baseline and the ischemic control. Conclusion: These results indicate that in isolated Langendorff-perfused rabbit heart model, calcium preconditioning with high concentration of calcium does not improve post-ischemic functional recovery. However, it does have an effect of limiting(reducing) the infart size by ischemic preconditioning, and this cardioprotective effect, at least in part, may have resulted from the activation of PKC by calcium which acts as a messenger(or trigger) to activate membrane PKC.

• Journal of the Korean Institute of Landscape Architecture
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• v.45 no.6
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• pp.10-27
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• 2017

Recently, the importance of recognizing the natural environment and the need for its conservation are increasing due to rapid urbanization. Suncheon Bay, designated as Scenic Site No. 41 and one of the World's Five Greatest Coastal Wetlands, is the only tideland among the tidal flats in Korea, which has salt marsh reserves. It has high conservation value from the ecological aspect. In addition to the Suncheon Bay National Garden, it provides various benefits not only to visitors but to local residents as well in terms of economics, environmental issues, and history and cultural aspects. Two million tourists visit the site annually, which has constantly highlighted the limits of ecological capacity. The valuation of the Suncheon Bay wetland is more important for the sustainability of the Suncheon Bay wetland than for its value as a tourism resource for the activation of the local economy. This study used the Logit model, which is commonly used among probabilistic choice models, to evaluate the economic value of Suncheon Bay wetland with the contingent valuation method(CVM). Applying the conservation value of the Suncheon Bay wetland to the benefit of KRW 8,200 for 1 person and 1 day, the benefit from exploration is KRW 2,050, the management and conservation value is KRW 3,034, and the heritage value is KRW 3,116. The results of this study are that benefit from the annual exploration of Suncheon Bay wetland was KRW 44.3 in billion, the management and conservation value was KRW 6.55 in billion, and the heritage value was KRW 6.73 in billion. When converted to the number of paying visitors per year, the conservation value is about KRW 177.1 billion. This study was conducted to evaluate the use and conservation aspects of the economic value of Suncheon Bay wetland. Based on the latent value of the Suncheon Bay wetland, it provides basic data about the efficient management and policy establishment of Suncheon Bay wetland. The study is significant in that the ecological sustainability of the Suncheon bay wetland and the value of non-marketable were evaluated based on the recognition of 'benefit through exploration', 'management and conservation value' and 'value of heritage'. It can be used as policy decision data on the integrated collection of the admission fee of the Suncheon Bay wetland and Suncheon Bay National Garden.

• Journal of Intelligence and Information Systems
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• v.21 no.3
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• pp.37-52
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• 2015

The recent global trends display expansion and growing solidity in both cooperative collaboration between industry, education, and research and R&D network systems. A greater support for the network and cooperative research sector would open greater possibilities for the evolution of new scholar and industrial fields and the development of new theories evoked from synergized educational research. Similarly, the national need for a strategy that can most efficiently and effectively support R&D network that are established through the government's R&D project research is on the rise. Despite the growing urgency, due to the habitual dependency on simple individual personal information data regarding R&D industry participants and generalized statistical data references, the policies concerning network system are disappointing and inadequate. Accordingly, analyses of the relationships involved for each subject who is participating in the R&D industry was conducted and on the foundation of an educational-industrial-research network system, possible changes within and of the network that may arise were predicted. To predict the R&D network transitions, Common Neighbor and Jaccard's Coefficient models were designated as the basic foundational models, upon which a new prediction model was proposed to address the limitations of the two aforementioned former models and to increase the accuracy of Link Prediction, with which a comparative analysis was made between the two models. Through the effective predictions regarding R&D network changes and transitions, such study result serves as a stepping-stone for an establishment of a prospective strategy that supports a desirable educational-industrial-research network and proposes a measure to promote the national policy to one that can effectively and efficiently sponsor integrated R&D industries. Though both weighted applications of Common Neighbor and Jaccard's Coefficient models provided positive outcomes, improved accuracy was comparatively more prevalent in the weighted Common Neighbor. An un-weighted Common Neighbor model predicted 650 out of 4,136 whereas a weighted Common Neighbor model predicted 50 more results at a total of 700 predictions. While the Jaccard's model demonstrated slight performance improvements in numeric terms, the differences were found to be insignificant.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.103-128
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• 2021

Recently, investors' interest and the influence of stock-related information dissemination are being considered as significant factors that explain stock returns and volume. Besides, companies that develop, distribute, or utilize innovative new technologies such as artificial intelligence have a problem that it is difficult to accurately predict a company's future stock returns and volatility due to macro-environment and market uncertainty. Market uncertainty is recognized as an obstacle to the activation and spread of artificial intelligence technology, so research is needed to mitigate this. Hence, the purpose of this study is to propose a machine learning model that predicts the volatility of a company's stock price by using the internet search volume of artificial intelligence-related technology keywords as a measure of the interest of investors. To this end, for predicting the stock market, we using the VAR(Vector Auto Regression) and deep neural network LSTM (Long Short-Term Memory). And the stock price prediction performance using keyword search volume is compared according to the technology's social acceptance stage. In addition, we also conduct the analysis of sub-technology of artificial intelligence technology to examine the change in the search volume of detailed technology keywords according to the technology acceptance stage and the effect of interest in specific technology on the stock market forecast. To this end, in this study, the words artificial intelligence, deep learning, machine learning were selected as keywords. Next, we investigated how many keywords each week appeared in online documents for five years from January 1, 2015, to December 31, 2019. The stock price and transaction volume data of KOSDAQ listed companies were also collected and used for analysis. As a result, we found that the keyword search volume for artificial intelligence technology increased as the social acceptance of artificial intelligence technology increased. In particular, starting from AlphaGo Shock, the keyword search volume for artificial intelligence itself and detailed technologies such as machine learning and deep learning appeared to increase. Also, the keyword search volume for artificial intelligence technology increases as the social acceptance stage progresses. It showed high accuracy, and it was confirmed that the acceptance stages showing the best prediction performance were different for each keyword. As a result of stock price prediction based on keyword search volume for each social acceptance stage of artificial intelligence technologies classified in this study, the awareness stage's prediction accuracy was found to be the highest. The prediction accuracy was different according to the keywords used in the stock price prediction model for each social acceptance stage. Therefore, when constructing a stock price prediction model using technology keywords, it is necessary to consider social acceptance of the technology and sub-technology classification. The results of this study provide the following implications. First, to predict the return on investment for companies based on innovative technology, it is most important to capture the recognition stage in which public interest rapidly increases in social acceptance of the technology. Second, the change in keyword search volume and the accuracy of the prediction model varies according to the social acceptance of technology should be considered in developing a Decision Support System for investment such as the big data-based Robo-advisor recently introduced by the financial sector.

• Journal of Life Science
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• v.32 no.7
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• pp.532-541
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• 2022

Obesity induced by high-fat diet (HFD) is verified as a strong risk factor and negative prognostic factor for prostate cancer in several genetically engineered mice although it was not examined in the normal mice. To investigate whether HFD-induced obesity can affect the development and progression of cancer in the prostate of normal mice, alterations in the weight and histological structure of the prostate as well as the expression of cancer-related proteins were analyzed in obese C57BL/6N mice fed with 60% HFD for 16 weeks. First, HFD-induced obesity, including an increase in organ weight, body weight, fat accumulation, and serum lipid profile, was successfully induced in C57BL/6N mice after HFD treatment. The total weight of the prostate significantly increased HFD-induced obesity in the model mice compared with the control group. Among the four lobes of the prostate, the weight of the ventral prostate (VP) and anterior prostate (AP) were higher in HFD-induced obesity model mice than in the control group, although the weights of the lateral prostate (DLP) and seminal vesicle (SV) were constantly maintained. In addition, the incidences of hyperplasia and non-hodgkin's lymphoma (NHL) in the histological structure were remarkably increased in HFD-induced obesity model mice, while the epithelial thickness was higher in the same group. A significant increase in the phosphorylation levels of key proteins in the AKT (protein kinase B) signaling pathway was detected in HFD-induced obesity model mice. Therefore, these results suggest that HFD-induced obesity can promote hyperplasia and NHL in the prostates of C57BL/6N mice through the activation of the AKT signaling pathway.