• Journal of Energy Engineering
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• v.28 no.3
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• pp.65-79
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• 2019

The study attempted to estimate the optimal facility capacity by combining renewable energy sources that can be connected with gas CHP in industrial complexes. In particular, we reviewed industrial complexes subject to energy use plan from 2013 to 2016. Although the regional designation was excluded, Sejong industrial complex, which has a fuel usage of 38 thousand TOE annually and a high heat density of $92.6Gcal/km^2{\cdot}h$, was selected for research. And we analyzed the optimal operation model of CHP Hybrid System linking fuel cell and photovoltaic power generation using HOMER Pro, a renewable energy hybrid system economic analysis program. In addition, in order to improve the reliability of the research by analyzing not only the heat demand but also the heat demand patterns for the dominant sectors in the thermal energy, the main supply energy source of CHP, the economic benefits were added to compare the relative benefits. As a result, the total indirect heat demand of Sejong industrial complex under construction was 378,282 Gcal per year, of which paper industry accounted for 77.7%, which is 293,754 Gcal per year. For the entire industrial complex indirect heat demand, a single CHP has an optimal capacity of 30,000 kW. In this case, CHP shares 275,707 Gcal and 72.8% of heat production, while peak load boiler PLB shares 103,240 Gcal and 27.2%. In the CHP, fuel cell, and photovoltaic combinations, the optimum capacity is 30,000 kW, 5,000 kW, and 1,980 kW, respectively. At this time, CHP shared 275,940 Gcal, 72.8%, fuel cell 12,390 Gcal, 3.3%, and PLB 90,620 Gcal, 23.9%. The CHP capacity was not reduced because an uneconomical alternative was found that required excessive operation of the PLB for insufficient heat production resulting from the CHP capacity reduction. On the other hand, in terms of indirect heat demand for the paper industry, which is the dominant industry, the optimal capacity of CHP, fuel cell, and photovoltaic combination is 25,000 kW, 5,000 kW, and 2,000 kW. The heat production was analyzed to be CHP 225,053 Gcal, 76.5%, fuel cell 11,215 Gcal, 3.8%, PLB 58,012 Gcal, 19.7%. However, the economic analysis results of the current electricity market and gas market confirm that the return on investment is impossible. However, we confirmed that the CHP Hybrid System, which combines CHP, fuel cell, and solar power, can improve management conditions of about KRW 9.3 billion annually for a single CHP system.

• Journal of Life Science
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• v.31 no.10
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• pp.885-897
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• 2021

Schisandrae Fructus (SF) and Corni Fructus (CF) have been used for a long time for the prevention and treatment of various diseases. Although reports have highlighted the possibility of inhibiting the onset and progression of benign prostatic hyperplasia (BPH), studies on related mechanisms are still lacking. In this study, we investigated the potential of SF and CF in improving BPH by using a dihydrotestosterone (DHT)-induced in vitro BPH model using LNCaP prostate carcinoma cells. According to our results, water and ethanol extracts of SF and CF significantly inhibited the proliferation of LNCaP cells by DHT treatment and markedly downregulated the expression of DHT-induced BPH biomarkers and growth factors. They also regulated the expression of apoptosis regulatory factors and significantly reduced DHT-mediated oxidative stress. In addition, the protective effect on major factors involved in the pathogenesis of BPH was more effective in the ethanol extract treatment group than in the water extract group. Furthermore, the improvement effect on BPH was higher in the 1:1 combined treatment group than in the ethanol extract alone treatment group of SF and CF, and 60% ethanol extracts showed a better effect than 40% ethanol extracts. Therefore, our findings demonstrate that SF and CF can protect against BPH by preventing the hyperproliferation of prostate cells through the inhibition of the androgen signaling pathway, which was correlated with their antioxidant activities. Therefore, SF and CF extracts may be useful in the clinical treatment of BPH, and the combination of these two extracts can be synergistic.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.63-88
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• 2019

The goal of this paper is to investigate changes in North Korea's domestic and foreign policies through automated text analysis over North Korea represented in South Korean mass media. Based on that data, we then analyze the status of text mining research, using a text mining technique to find the topics, methods, and trends of text mining research. We also investigate the characteristics and method of analysis of the text mining techniques, confirmed by analysis of the data. In this study, R program was used to apply the text mining technique. R program is free software for statistical computing and graphics. Also, Text mining methods allow to highlight the most frequently used keywords in a paragraph of texts. One can create a word cloud, also referred as text cloud or tag cloud. This study proposes a procedure to find meaningful tendencies based on a combination of word cloud, and co-occurrence networks. This study aims to more objectively explore the images of North Korea represented in South Korean newspapers by quantitatively reviewing the patterns of language use related to North Korea from 2016. 11. 1 to 2019. 5. 23 newspaper big data. In this study, we divided into three periods considering recent inter - Korean relations. Before January 1, 2018, it was set as a Before Phase of Peace Building. From January 1, 2018 to February 24, 2019, we have set up a Peace Building Phase. The New Year's message of Kim Jong-un and the Olympics of Pyeong Chang formed an atmosphere of peace on the Korean peninsula. After the Hanoi Pease summit, the third period was the silence of the relationship between North Korea and the United States. Therefore, it was called Depression Phase of Peace Building. This study analyzes news articles related to North Korea of the Korea Press Foundation database(www.bigkinds.or.kr) through text mining, to investigate characteristics of the Kim Jong-un regime's South Korea policy and unification discourse. The main results of this study show that trends in the North Korean national policy agenda can be discovered based on clustering and visualization algorithms. In particular, it examines the changes in the international circumstances, domestic conflicts, the living conditions of North Korea, the South's Aid project for the North, the conflicts of the two Koreas, North Korean nuclear issue, and the North Korean refugee problem through the co-occurrence word analysis. It also offers an analysis of South Korean mentality toward North Korea in terms of the semantic prosody. In the Before Phase of Peace Building, the results of the analysis showed the order of 'Missiles', 'North Korea Nuclear', 'Diplomacy', 'Unification', and ' South-North Korean'. The results of Peace Building Phase are extracted the order of 'Panmunjom', 'Unification', 'North Korea Nuclear', 'Diplomacy', and 'Military'. The results of Depression Phase of Peace Building derived the order of 'North Korea Nuclear', 'North and South Korea', 'Missile', 'State Department', and 'International'. There are 16 words adopted in all three periods. The order is as follows: 'missile', 'North Korea Nuclear', 'Diplomacy', 'Unification', 'North and South Korea', 'Military', 'Kaesong Industrial Complex', 'Defense', 'Sanctions', 'Denuclearization', 'Peace', 'Exchange and Cooperation', and 'South Korea'. We expect that the results of this study will contribute to analyze the trends of news content of North Korea associated with North Korea's provocations. And future research on North Korean trends will be conducted based on the results of this study. We will continue to study the model development for North Korea risk measurement that can anticipate and respond to North Korea's behavior in advance. We expect that the text mining analysis method and the scientific data analysis technique will be applied to North Korea and unification research field. Through these academic studies, I hope to see a lot of studies that make important contributions to the nation.

• Tuberculosis and Respiratory Diseases
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• v.82 no.1
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• pp.42-52
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• 2019

Background: Transforming growth factor ${\beta}$ (TGF-${\beta}$), retinoic acid (RA), p38 mitogen-activated protein kinase (MAPK), and MEK signaling play critical roles in cell differentiation, proliferation, and apoptosis. We investigated the effect of RA and the role of these signaling molecules on the phosphorylation of Smad2/3 (p-Smad2/3) induced by TGF-${\beta}1$. Methods: A549 epithelial cells and CCD-11Lu fibroblasts were incubated and stimulated with or without all-trans RA (ATRA) and TGF-${\beta}1$ and with MAPK or MEK inhibitors. The levels of p-Smad2/3 were analyzed by western blotting. For animal models, we studied three experimental mouse groups: control, bleomycin, and bleomycin+ATRA group. Changes in histopathology, lung injury score, and levels of TGF-${\beta}1$ and Smad3 were evaluated at 1 and 3 weeks. Results: When A549 cells were pre-stimulated with TGF-${\beta}1$ prior to RA treatment, RA completely inhibited the p-Smad2/3. However, when A549 cells were pre-treated with RA prior to TGF-${\beta}1$ stimulation, RA did not completely suppress the p-Smad2/3. When A549 cells were pre-treated with MAPK inhibitor, TGF-${\beta}1$ failed to phosphorylate Smad2/3. In fibroblasts, p38 MAPK inhibitor suppressed TGF-${\beta}1$-induced p-Smad2. In a bleomycin-induced lung injury mouse model, RA decreased the expression of TGF-${\beta}1$ and Smad3 at 1 and 3 weeks. Conclusion: RA had inhibitory effects on the phosphorylation of Smad induced by TGF-${\beta}1$ in vitro, and RA also decreased the expression of TGF-${\beta}1$ at 1 and 3 weeks in vivo. Furthermore, pre-treatment with a MAPK inhibitor showed a preventative effect on TGF-${\beta}1$/Smad phosphorylation in epithelial cells. As a result, a combination of RA and MAPK inhibitors may suppress the TGF-${\beta}1$-induced lung injury and fibrosis.

• Korean Journal of Environmental Biology
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• v.39 no.3
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• pp.354-361
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• 2021

Understanding the phytotoxic mechanism of methyl bromide (MB), an essential fumigant during the quarantine and pre-shipment process, is urgently needed to ensure its proper use and reduce international economic losses. In a previous study, two main MB-induced toxic mechanisms such as reactive oxygen species (ROS) and auxin distribution were selected by analyzing transcriptomic analysis. In the study, a 3-week-old A. thaliana was supplied with 1 mM ROS scavengers [N-acetyl-L-cysteine (NAC) or L-glutathione (GSH)] and 1µM indole-3-acetic acid(IAA) three times every 12 h, and visual and gene expression assessments were performed to evaluate the reduction in phytotoxicity by supplements. Phytotoxic effects on the MB-4h exposed group were decreased with GSH application compared to the other single supplements and a combination of supplements at 7 days post fumigation. Among these supplements, GSH at a concentration of 1, 2, and 5mM was suppled to A. thaliana with MB-fumigation. During a long-term observation of 2 weeks after the fumigation, 5 mM GSH application was the most effective in minimizing MB-induced phytotoxic effects with up-regulation of HSP70 expression and increase in main stem length. These results indicated that ROS was a main key factor of MB-induced phytotoxicity and that GSH can be used as a supplement to reduce the phytotoxicity of MB.

• Journal of Intelligence and Information Systems
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• v.27 no.2
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• pp.1-15
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• 2021

If it is difficult for us to make decisions, we ask for advice from friends or people around us. When we decide to buy products online, we read anonymous reviews and buy them. With the advent of the Data-driven era, IT technology's development is spilling out many data from individuals to objects. Companies or individuals have accumulated, processed, and analyzed such a large amount of data that they can now make decisions or execute directly using data that used to depend on experts. Nowadays, the recommender system plays a vital role in determining the user's preferences to purchase goods and uses a recommender system to induce clicks on web services (Facebook, Amazon, Netflix, Youtube). For example, Youtube's recommender system, which is used by 1 billion people worldwide every month, includes videos that users like, "like" and videos they watched. Recommended system research is deeply linked to practical business. Therefore, many researchers are interested in building better solutions. Recommender systems use the information obtained from their users to generate recommendations because the development of the provided recommender systems requires information on items that are likely to be preferred by the user. We began to trust patterns and rules derived from data rather than empirical intuition through the recommender systems. The capacity and development of data have led machine learning to develop deep learning. However, such recommender systems are not all solutions. Proceeding with the recommender systems, there should be no scarcity in all data and a sufficient amount. Also, it requires detailed information about the individual. The recommender systems work correctly when these conditions operate. The recommender systems become a complex problem for both consumers and sellers when the interaction log is insufficient. Because the seller's perspective needs to make recommendations at a personal level to the consumer and receive appropriate recommendations with reliable data from the consumer's perspective. In this paper, to improve the accuracy problem for "appropriate recommendation" to consumers, the recommender systems are proposed in combination with context-based deep learning. This research is to combine user-based data to create hybrid Recommender Systems. The hybrid approach developed is not a collaborative type of Recommender Systems, but a collaborative extension that integrates user data with deep learning. Customer review data were used for the data set. Consumers buy products in online shopping malls and then evaluate product reviews. Rating reviews are based on reviews from buyers who have already purchased, giving users confidence before purchasing the product. However, the recommendation system mainly uses scores or ratings rather than reviews to suggest items purchased by many users. In fact, consumer reviews include product opinions and user sentiment that will be spent on evaluation. By incorporating these parts into the study, this paper aims to improve the recommendation system. This study is an algorithm used when individuals have difficulty in selecting an item. Consumer reviews and record patterns made it possible to rely on recommendations appropriately. The algorithm implements a recommendation system through collaborative filtering. This study's predictive accuracy is measured by Root Mean Squared Error (RMSE) and Mean Absolute Error (MAE). Netflix is strategically using the referral system in its programs through competitions that reduce RMSE every year, making fair use of predictive accuracy. Research on hybrid recommender systems combining the NLP approach for personalization recommender systems, deep learning base, etc. has been increasing. Among NLP studies, sentiment analysis began to take shape in the mid-2000s as user review data increased. Sentiment analysis is a text classification task based on machine learning. The machine learning-based sentiment analysis has a disadvantage in that it is difficult to identify the review's information expression because it is challenging to consider the text's characteristics. In this study, we propose a deep learning recommender system that utilizes BERT's sentiment analysis by minimizing the disadvantages of machine learning. This study offers a deep learning recommender system that uses BERT's sentiment analysis by reducing the disadvantages of machine learning. The comparison model was performed through a recommender system based on Naive-CF(collaborative filtering), SVD(singular value decomposition)-CF, MF(matrix factorization)-CF, BPR-MF(Bayesian personalized ranking matrix factorization)-CF, LSTM, CNN-LSTM, GRU(Gated Recurrent Units). As a result of the experiment, the recommender system based on BERT was the best.

• The Journal of Korean Academy of Sensory Integration
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• v.19 no.1
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• pp.69-82
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• 2021

Objective : This recent work intended to provide basic information for researchers and practitioners related to occupational therapy about Developmental Coordination Disorder (DCD) in South Korea. The previous research of screening DCD and the effects of intervention programs were reviewed. Methods : Peer-reviewed papers relating to DCD and published in Korea from January 1990 to December 2020 were systematically reviewed. The search terms "developmental coordination disorder," "development coordination," and "developmental coordination" were used to identify previous Korean research in this area from three representation database, the Research Information Sharing Service, Korean Studies Information Service System, and Google Scholar. We found a total of 4,878 articles identified through the three search engines and selected seventeen articles for analysis after removing those that corresponded to the overlapping or exclusion criteria. We adopted "the conceptual model" to analyze the selected articles about DCD assessment and intervention. Results : We found that twelve of the 17 studies showed the qualitative level of Level 2 using non-randomized approach between the two groups. The Movement Assessment Battery for Children and its second edition were the most frequently used tools in assessing children for DCD. Among the intervention studies, the eight articles (47%) were adopted a dynamic systems approach; a normative functional skill framework and cognitive neuroscience were each used in 18% of the pieces; and 11% of the articles were applied neurodevelopmental theory. Only one article was used a combination approach of normative functional skill and general abilities. These papers were mainly focused on the movement characteristics of children with DCD and the intervention effect of exercise or sports programs. Conclusion : Most of the reviewed studies investigated the movement characteristics of DCD or explore the effectiveness of particular intervention programs. In the future, it would be useful to investigate the feasibility of different assessment tools and to establish the effectiveness of various interventions used in rehabilitation for better motor performance in children with DCD.

• Journal of Radiopharmaceuticals and Molecular Probes
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• v.9 no.1
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• pp.9-16
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• 2023

Liposomes as drug delivery system have proved useful carrier for various disease, including cancer. In addition, perfluorocarbon cored microbubbles are utilized in conjunction with high-intensity focused-ultrasound (HIFU) to enable simultaneous diagnosis and treatment. However, microbubbles generally exhibit lower drug loading efficiency, so the need for the development of a novel liposome-based drug delivery material that can efficiently load and deliver drugs to targeted areas via HIFU. This study aims to develop a liposome-based drug delivery material by introducing a substance that can burst liposomes using ultrasound energy and confirm the ability to target tumors using PET imaging. Liposomes (Lipo-DOX, Lipo-DOX-Au, Lipo-DOX-Au-RGD) were synthesized with gold nanoparticles using an avidin-biotin bond, and doxorubicin was mounted inside by pH gradient method. The size distribution was measured by DLS, and encapsulation efficiency of doxorubicin was analyzed by UV-vis spectrometer. The target specificity and cytotoxicity of liposomes were assessed in vitro by glioblastoma U87mg cells to HIFU treatment and analyzed using CCK-8 assay, and fluorescence microscopy at 6-hour intervals for up to 24 hours. For the in vivo study, U87mg model mouse were injected intravenously with 1.48 MBq of ⁶⁴Cu-labeled Lipo-DOX-Au and Lipo-DOX-Au-RGD, and PET images were taken at 0, 2, 4, 8, and 24 hours. As a result, the size of liposomes was 108.3 ± 5.0 nm at Lipo-DOX-Au and 94.1 ± 12.2 nm at Lipo-DOX-Au-RGD, and it was observed that doxorubicin was mounted inside the liposome up to 52%. After 6 hours of HIFU treatment, the viability of U87mg cells treated with Lipo-DOX-Au decreased by around 20% compared to Lipo-DOX, and Lipo-DOX-Au-RGD had a higher uptake rate than Lipo-DOX. In vivo study using PET images, it was confirmed that ⁶⁴Cu-Lipo-DOX-Au-RGD was taken up into the tumor immediately after injection and maintained for up to 4 hours. In this study, drugs released from liposomes-gold nanoparticles via ultrasound and RGD targeting were confirmed by non-invasive imaging. In cell-level experiments, HIFU treatment of gold nanoparticle-coupled liposomes significantly decreased tumor survival, while RGD-liposomes exhibited high tumor targeting and rapid release in vivo imaging. It is expected that the combination of these models with ultrasound is served as an effective drug delivery material with therapeutic outcomes.

• Communications of Mathematical Education
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• v.37 no.2
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• pp.233-256
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• 2023

This study conducted foundational research to derive ways to use ChatGPT in mathematics education by analyzing ChatGPT's responses to questions from the National Assessment of Educational Achievement (NAEA) and the College Scholastic Ability Test (CSAT). ChatGPT, a generative artificial intelligence model, has gained attention in various fields, and there is a growing demand for its use in education as the number of users rapidly increases. To the best of our knowledge, there are very few reported cases of educational studies utilizing ChatGPT. In this study, we analyzed ChatGPT 3.5 responses to questions from the three-year National Assessment of Educational Achievement and the College Scholastic Ability Test, categorizing them based on the percentage of correct answers, the accuracy of the solution process, and types of errors. The correct answer rates for ChatGPT in the National Assessment of Educational Achievement and the College Scholastic Ability Test questions were 37.1% and 15.97%, respectively. The accuracy of ChatGPT's solution process was calculated as 3.44 for the National Assessment of Educational Achievement and 2.49 for the College Scholastic Ability Test. Errors in solving math problems with ChatGPT were classified into procedural and functional errors. Procedural errors referred to mistakes in connecting expressions to the next step or in calculations, while functional errors were related to how ChatGPT recognized, judged, and outputted text. This analysis suggests that relying solely on the percentage of correct answers should not be the criterion for assessing ChatGPT's mathematical performance, but rather a combination of the accuracy of the solution process and types of errors should be considered.

• 한국노년학
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• v.39 no.4
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• pp.723-739
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• 2019

This study is to verify the mediated effects of attitudes toward old people and dementia in the influence of elderly couples in the aging society amid the rapidly changing family structure and functions due to the combination of individualization, marital status and divorce rate. In order to carry out such research purposes, data were collected from students of elementary, middle and high schools in Gwangju, through self-subscribed questionnaire. For statistical analysis, the SPSS 20.0 and AMOS 18.0 programs were used and frequency, percentages, technical statistics, correlation, factor analysis, structural model validation, and the Sobel-Test were performed. The results of this study are as follows. First, family intimacy, elderly awareness, and elderly care were the highest among elementary school students, followed by middle school and high school students (P.<.001). Also, in religion, the family intimacy of teenagers with religion was higher than those without religion (p.001). Second, family intimacy directly affected elderly people's attitudes toward dementia and elderly care, old people's attitudes toward dementia and attitudes toward dementia directly affected elderly care. Third, family intimacy (parent-child) was found to be 7.8% for older adults, 20.2% for family intimacy and attitudes toward dementia, and 34.1% for elderly care (p.<.001). Fourth, it has been verified that the absolute value of attitudes toward dementia and elderly people's awareness of elderly people and attitudes between family intimacy and elderly care has been higher than 1.96 and thus acts as a mediating role. These findings are intended to contribute to the welfare of senior citizens' education to improve the quality of life for senior citizens through the resolution of conflicts between generations, as well as the resolution of positive stimulus, by developing various programs such as family friendship, elderly awareness, culture with parents, and various experiences to improve attitudes toward dementia in early adolescence.