• Clean Technology
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• v.27 no.2
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• pp.107-114
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• 2021

Material Life Cycle Assessment (MLCA) was performed to analyze the environmental impact characteristics of the Mg₂NiH_x-5 wt% CaO hydrogen storage composites' manufacturing process. The MLCA was carried out by Gabi software. It was based on Eco-Indicator 99' (EI99) and CML 2001 methodology. The Mg₂NiH_x-5 wt% CaO composites were synthesized by Hydrogen Induced Mechanical Alloying (HIMA). The metallurgical, thermochemical characteristics of the composites were analyzed by using X-ray diffraction (XRD), scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDS), specific surface area analysis (Bruner-Emmett-Teller, BET), and thermogravimetric analysis (TGA). As a result of the CML 2001 methodology, the environmental impact was 78% for Global Warming Potential (GWP) and 22% for Eutrophication Potential (ETP). In addition, as a result of applying the EI 99' methodology, the acidification was the highest at 43%, and the ecotoxicity was 31%. Accordingly, the amount of electricity used in the manufacturing process may have an absolute effect on environmental pollution. Also, it is judged that the leading cause of Mg₂NiH_x-5 wt% CaO is the addition of CaO. Ultimately, it is necessary to research environmental factors by optimizing the process, shortening the manufacturing process time, and exploring eco-friendly alternative materials.

• Korean Journal of Heritage: History & Science
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• v.55 no.2
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• pp.102-111
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• 2022

Termites are a group of social insects that are one of the primary causes of damage to wooden architectural heritage. Since termite damage impairs the authenticity and structural stability of cultural heritage, it is imperative to prevent it. This study examines the extent of termite damage to wooden architectural heritage as part of efforts to prevent termite damage to nationally designated wooden architectural heritage sites across the country. The extent of termite damage to each cultural heritage was assessed qualitatively and quantitatively and comparatively analyzed by region using the results of the "Investigation on Biological Damage to Wooden Architectural Heritages" conducted by the National Research Institute of Cultural Heritage from 2016 to 2019. It involved 362 nationally designated wooden architectural heritages(25 national treasures, 157 treasures, 180 national folklore cultural heritages) and 1,104 buildings. The results were as follows: termite detection dogs reacted at 317(87.6%) of the 362 wooden heritages, with visible termite damage observed in 185 cases(51.1%). Furthermore, termite damage was confirmed using one of two methods(detection dogs or visual inspection) in 324 cases(89.5%). Of the 1,104 buildings, termite detection dogs reacted at 668(60.5%), while 339(30.7%) showed visible termite damage. Employing one of the two methods, damage was confirmed in 702 buildings(63.6%). The country was categorized into nine regions(Seoul Metropolitan Area, Gangwon, Chungbuk, Chungnam, Jeonbuk, Jeonnam, Gyeongbuk, Gyeongnam, and Jeju) to examine the termite damage rate and the degree of damage to each cultural heritage according to location. Termite detection dogs reacted to more than 70% of the cultural heritage in all regions. Visible damage was minimal in the Seoul metropolitan area(32.1%) and Gangwon(21.4%) but severe in Chungnam(65.6%), Jeonnam(67.3%), and Gyeongnam(68.2%). By quantifying the degree of termite damage of each cultural heritage as a ratio of the absence of termite damage among the total absence, the average termite damage of the cultural heritage across the country was 9.2%. Regional variance analysis showed that the cultural heritage in Jeonbuk and Jeonnam showed a statistically significantly higher degree of termite damage than the cultural heritage in the Seoul metropolitan area, Chungbuk, and Gyeongbuk. This paper comprehensively analyzed termite damage to nationally designated wooden architectural heritage. The findings are expected to be valuable in establishing policies for the preservation and management of cultural heritage sites in the future.

• The Journal of the Convergence on Culture Technology
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• v.8 no.4
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• pp.253-261
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• 2022

The purpose of this study is to investigate the relationship between transformative leadership, team cohesion, and team performance of Chinese university taekwondo leaders. Specifically, it is to investigate the effect of transformative leadership on team cohesion and team performance and to verify the mediating effect of team cohesion in the relationship between transformative leadership and team performance. In order to achieve the research purpose, a total of 350 people were sampled after setting taekwondo leaders at Chinese universities as a population. The measurement tool used in this study was a questionnaire consisting of 5 items on demographic characteristics, a total of 19 questions on transformational leadership, 10 questions on team cohesion, and 4 questions on team performance. The validity of the questionnaire was verified through exploratory factor analysis, and the reliability was verified through reliability analysis. The reliability Cronbach's α of the questionnaire was found to be α=0.755-0.799 for transformative leadership, α=0.848, and α=0.740 for team performance. As the data processing method, exploratory factor analysis and reliability analysis, one-way analysis (one-way ANOVA), and multiple regression analysis were used using SPSS WIN. The conclusions derived through the above research methods and procedures are as follows. First, the transformative leadership of Taekwondo leaders at Chinese universities influenced team cohesion. Second, the transformative leadership of Taekwondo leaders at Chinese universities influenced team performance. Third, the team cohesiveness of Taekwondo leaders at Chinese universities influenced team performance. Fourth, the transformative leadership of Taekwondo leaders at Chinese universities not only directly affects team performance, but also indirectly affects team cohesion. Therefore, it is believed that Chinese Taekwondo players will help improve their performance by affecting team cohesion and team performance for the best games through the leader's variable leadership.

• Korean Journal of Psychosomatic Medicine
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• v.31 no.2
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• pp.165-172
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• 2023

Objectives : The purpose of this study is to determine whether there is a significant difference in the neutrophil-to-lymphocyte ratio and platelet-to-lymphocyte ratio according to the history of suicide attempt in patients with psychiatric diseases. Methods : A medical record review was conducted on patients who had been hospitalized in Konyang University Hospital since 2021-03-01 to 2023-02-28 to collect demographic and clinical characteristics. T-test for continuous variables and Chi-square test for categorical variables were performed to determine demographic differences according to the history of suicide attempt, and the ANCOVA test was performed to compare the average value of peripheral inflammatory marker according to the history of suicide attempt with gender and age as covariates. One-way variance analysis was performed to determine whether the number of suicide attempt causes significant difference of the peripheral inflammatory marker. Results : The final analysis target of this study was 266 patients, 101 had history of suicide attempt, and 165 had no history of suicide attempt. The neutrophil-to-lymphocyte ratio (p<0.001) and platelet-to-lymphocyte ratio (p<0.001) were higher in patients with the history of suicide attempt than patients without the history of suicide attempt, but the neutrophil-to-lymphocyte ratio and platelet-to-lymphocyte ratio were not significantly increased depending on the serial increase of number of suicide attempts. Conclusions : This study suggests that peripheral inflammatory markers are meaningful and easily accessible indicators for predicting the risk of suicide attempt in psychiatric patients. We expect that prospective follow-up study will be conducted with more subjects and controlled potential confounding variables.

• Journal of Dental Rehabilitation and Applied Science
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• v.40 no.2
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• pp.55-63
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• 2024

Purpose: This study aimed to assess the antimicrobial efficacy of an 810-nm infrared diode laser with indocyanine green (ICG) against Staphylococcus aureus on sandblasted, large grit, and acid-etched (SLA) titanium surfaces, comparing its effectiveness with alternative chemical decontamination modalities. Materials and Methods: Biofilms of S. aureus ATCC 25923 were cultured on SLA titanium disks for 48 hours. The biofilms were divided into five treatment groups: control, chlorhexidine gluconate (CHX), tetracycline (TC), ICG, and 810-nm infrared diode laser with ICG (ICG-PDT). After treatment, colony-forming units were quantified to assess surviving bacteria, and viability was confirmed through confocal laser-scanning microscope (CLSM) imaging. Results: All treated groups exhibited a statistically significant reduction in S. aureus (P < 0.05), with notable efficacy in the CHX, TC, and ICG-PDT groups (P < 0.01). While no statistical difference was observed between TC and CHX, the ICG-PDT group demonstrated superior bacterial reduction. CLSM images revealed a higher proportion of dead bacteria stained in red within the ICG-PDT groups. Conclusion: Within the limitations, ICG-PDT effectively reduced S. aureus biofilms on SLA titanium surfaces. Further investigations into alternative decontamination methods and the clinical impact of ICG-PDT on peri-implant diseases are warranted.

• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.195-211
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• 2014

Cloud computing services provide IT resources as services on demand. This is considered a key concept, which will lead a shift from an ownership-based paradigm to a new pay-for-use paradigm, which can reduce the fixed cost for IT resources, and improve flexibility and scalability. As IT services, cloud services have evolved from early similar computing concepts such as network computing, utility computing, server-based computing, and grid computing. So research into cloud computing is highly related to and combined with various relevant computing research areas. To seek promising research issues and topics in cloud computing, it is necessary to understand the research trends in cloud computing more comprehensively. In this study, we collect bibliographic information and citation information for cloud computing related research papers published in major international journals from 1994 to 2012, and analyzes macroscopic trends and network changes to citation relationships among papers and the co-occurrence relationships of key words by utilizing social network analysis measures. Through the analysis, we can identify the relationships and connections among research topics in cloud computing related areas, and highlight new potential research topics. In addition, we visualize dynamic changes of research topics relating to cloud computing using a proposed cloud computing "research trend map." A research trend map visualizes positions of research topics in two-dimensional space. Frequencies of key words (X-axis) and the rates of increase in the degree centrality of key words (Y-axis) are used as the two dimensions of the research trend map. Based on the values of the two dimensions, the two dimensional space of a research map is divided into four areas: maturation, growth, promising, and decline. An area with high keyword frequency, but low rates of increase of degree centrality is defined as a mature technology area; the area where both keyword frequency and the increase rate of degree centrality are high is defined as a growth technology area; the area where the keyword frequency is low, but the rate of increase in the degree centrality is high is defined as a promising technology area; and the area where both keyword frequency and the rate of degree centrality are low is defined as a declining technology area. Based on this method, cloud computing research trend maps make it possible to easily grasp the main research trends in cloud computing, and to explain the evolution of research topics. According to the results of an analysis of citation relationships, research papers on security, distributed processing, and optical networking for cloud computing are on the top based on the page-rank measure. From the analysis of key words in research papers, cloud computing and grid computing showed high centrality in 2009, and key words dealing with main elemental technologies such as data outsourcing, error detection methods, and infrastructure construction showed high centrality in 2010~2011. In 2012, security, virtualization, and resource management showed high centrality. Moreover, it was found that the interest in the technical issues of cloud computing increases gradually. From annual cloud computing research trend maps, it was verified that security is located in the promising area, virtualization has moved from the promising area to the growth area, and grid computing and distributed system has moved to the declining area. The study results indicate that distributed systems and grid computing received a lot of attention as similar computing paradigms in the early stage of cloud computing research. The early stage of cloud computing was a period focused on understanding and investigating cloud computing as an emergent technology, linking to relevant established computing concepts. After the early stage, security and virtualization technologies became main issues in cloud computing, which is reflected in the movement of security and virtualization technologies from the promising area to the growth area in the cloud computing research trend maps. Moreover, this study revealed that current research in cloud computing has rapidly transferred from a focus on technical issues to for a focus on application issues, such as SLAs (Service Level Agreements).

• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.39-55
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• 2019

Recently banks and large financial institutions have introduced lots of Robo-Advisor products. Robo-Advisor is a Robot to produce the optimal asset allocation portfolio for investors by using the financial engineering algorithms without any human intervention. Since the first introduction in Wall Street in 2008, the market size has grown to 60 billion dollars and is expected to expand to 2,000 billion dollars by 2020. Since Robo-Advisor algorithms suggest asset allocation output to investors, mathematical or statistical asset allocation strategies are applied. Mean variance optimization model developed by Markowitz is the typical asset allocation model. The model is a simple but quite intuitive portfolio strategy. For example, assets are allocated in order to minimize the risk on the portfolio while maximizing the expected return on the portfolio using optimization techniques. Despite its theoretical background, both academics and practitioners find that the standard mean variance optimization portfolio is very sensitive to the expected returns calculated by past price data. Corner solutions are often found to be allocated only to a few assets. The Black-Litterman Optimization model overcomes these problems by choosing a neutral Capital Asset Pricing Model equilibrium point. Implied equilibrium returns of each asset are derived from equilibrium market portfolio through reverse optimization. The Black-Litterman model uses a Bayesian approach to combine the subjective views on the price forecast of one or more assets with implied equilibrium returns, resulting a new estimates of risk and expected returns. These new estimates can produce optimal portfolio by the well-known Markowitz mean-variance optimization algorithm. If the investor does not have any views on his asset classes, the Black-Litterman optimization model produce the same portfolio as the market portfolio. What if the subjective views are incorrect? A survey on reports of stocks performance recommended by securities analysts show very poor results. Therefore the incorrect views combined with implied equilibrium returns may produce very poor portfolio output to the Black-Litterman model users. This paper suggests an objective investor views model based on Support Vector Machines(SVM), which have showed good performance results in stock price forecasting. SVM is a discriminative classifier defined by a separating hyper plane. The linear, radial basis and polynomial kernel functions are used to learn the hyper planes. Input variables for the SVM are returns, standard deviations, Stochastics %K and price parity degree for each asset class. SVM output returns expected stock price movements and their probabilities, which are used as input variables in the intelligent views model. The stock price movements are categorized by three phases; down, neutral and up. The expected stock returns make P matrix and their probability results are used in Q matrix. Implied equilibrium returns vector is combined with the intelligent views matrix, resulting the Black-Litterman optimal portfolio. For comparisons, Markowitz mean-variance optimization model and risk parity model are used. The value weighted market portfolio and equal weighted market portfolio are used as benchmark indexes. We collect the 8 KOSPI 200 sector indexes from January 2008 to December 2018 including 132 monthly index values. Training period is from 2008 to 2015 and testing period is from 2016 to 2018. Our suggested intelligent view model combined with implied equilibrium returns produced the optimal Black-Litterman portfolio. The out of sample period portfolio showed better performance compared with the well-known Markowitz mean-variance optimization portfolio, risk parity portfolio and market portfolio. The total return from 3 year-period Black-Litterman portfolio records 6.4%, which is the highest value. The maximum draw down is -20.8%, which is also the lowest value. Sharpe Ratio shows the highest value, 0.17. It measures the return to risk ratio. Overall, our suggested view model shows the possibility of replacing subjective analysts's views with objective view model for practitioners to apply the Robo-Advisor asset allocation algorithms in the real trading fields.

• Journal of Intelligence and Information Systems
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• v.17 no.3
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• pp.63-77
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• 2011

The World Wide Web is a very large distributed digital information space. From its origins in 1991, the web has grown to encompass diverse information resources as personal home pasges, online digital libraries and virtual museums. Some estimates suggest that the web currently includes over 500 billion pages in the deep web. The ability to search and retrieve information from the web efficiently and effectively is an enabling technology for realizing its full potential. With powerful workstations and parallel processing technology, efficiency is not a bottleneck. In fact, some existing search tools sift through gigabyte.syze precompiled web indexes in a fraction of a second. But retrieval effectiveness is a different matter. Current search tools retrieve too many documents, of which only a small fraction are relevant to the user query. Furthermore, the most relevant documents do not nessarily appear at the top of the query output order. Also, current search tools can not retrieve the documents related with retrieved document from gigantic amount of documents. The most important problem for lots of current searching systems is to increase the quality of search. It means to provide related documents or decrease the number of unrelated documents as low as possible in the results of search. For this problem, CiteSeer proposed the ACI (Autonomous Citation Indexing) of the articles on the World Wide Web. A "citation index" indexes the links between articles that researchers make when they cite other articles. Citation indexes are very useful for a number of purposes, including literature search and analysis of the academic literature. For details of this work, references contained in academic articles are used to give credit to previous work in the literature and provide a link between the "citing" and "cited" articles. A citation index indexes the citations that an article makes, linking the articleswith the cited works. Citation indexes were originally designed mainly for information retrieval. The citation links allow navigating the literature in unique ways. Papers can be located independent of language, and words in thetitle, keywords or document. A citation index allows navigation backward in time (the list of cited articles) and forwardin time (which subsequent articles cite the current article?) But CiteSeer can not indexes the links between articles that researchers doesn't make. Because it indexes the links between articles that only researchers make when they cite other articles. Also, CiteSeer is not easy to scalability. Because CiteSeer can not indexes the links between articles that researchers doesn't make. All these problems make us orient for designing more effective search system. This paper shows a method that extracts subject and predicate per each sentence in documents. A document will be changed into the tabular form that extracted predicate checked value of possible subject and object. We make a hierarchical graph of a document using the table and then integrate graphs of documents. The graph of entire documents calculates the area of document as compared with integrated documents. We mark relation among the documents as compared with the area of documents. Also it proposes a method for structural integration of documents that retrieves documents from the graph. It makes that the user can find information easier. We compared the performance of the proposed approaches with lucene search engine using the formulas for ranking. As a result, the F.measure is about 60% and it is better as about 15%.

• Proceedings of the KOR-BRONCHOESO Conference
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• 1972.03a
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• pp.5-6
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• 1972

Noise and air pollution, which accompany the development of industry and the increase of population, contribute to the deterioration of urban environment. The air pollution level of Seoul has gradually increased and the city residents are suffering from a high pollution of noise. If no measures were taken against pollution, the amount of emission of pollutant into air would be 36.7 thousand tons per year per square kilometer in 1975, three times more than that of 1970, and it would be the same level as that of United States in 1968. The main sources of air pollution in Seoul are the exhaust has from vehicles and the combustion of bunker-C oil for heating purpose. Thus, it is urgent that an exhaust gas cleaner should be instaled to every car and the fuel substituted by less sulfur-contained-oil to prevent the pollution. Transportation noise (vehicular noise and train noise) is the main component of urban noise problem. The average noise level in downtown area is about 75㏈ with maximum of 85㏈ and the vehicular homing was checked 100㏈ up and down. Therefore, the reduction of the number of bus-stop the strict regulation of homing in downtown area and a better maintenance of car should be an effective measures against noise pollution in urban areas. Within the distance of 200 metres from railroad, the train noise exceeds the limit specified by the pollution control law in Korea. Especially, the level of noise and steam-whistle of train as measured by the ISO evaluation can adversely affect the community activities of residents. To prevent environmental destruction, many developed countries have taken more positive action against worsening pollution and such an action is now urgently required in this country.

• Journal of Korean Home Economics Education Association
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• v.19 no.4
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• pp.37-56
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• 2007

The purpose of this study is to provide basic resources to the first-grade Home Economics Regular Teacher Qualification Program (FGHERTQP) in order to improve its operation plans. For the study, the three methods were carried out: an analysis on the curricula of FGHERTQP over six years since 2000, a questionnaire asking their satisfaction degrees and needs on the programs which was answered by the home economics teachers who were the participants of FGHERTQP, and several statistical analyses such as a descriptive-test, a $X^2$-test, a t-test, and one way ANOVA by using SPSS Win ver 10.0. The results of the study were as follows; Firstly, FGHERTQP has been operated ten times by five training centers during resent six years. Subject matters ($1{\sim}7$), whole numbers of lectures ($11{\sim}29$), and their allotted working hours ($111{\sim}136$) vary with individual training centers and operation years. Secondly, when using 5 point likert scales, Contents and Methods of evaluation marked 3.08 which were the lowest scores, and Qualification Training in General marked 3.72 which was the highest score among five fields of Qualification Training in General, Contents, Organizations, Methods and Evaluation. The overall scores were low. Thirdly, in needs analysis on offering subject matters, the participants wanted to study the field of home economics education more than that of subject contents. Looking about the highest needs classified by domains, Food Principles & Meal Management showed the highest in Foods. And Consumer Issues in Clothing & Textiles in Textiles, Upcoming Housing Cultures in Housing, Family Relationship in Child Development & Family Relationship, Juveniles and their daily life as a consumer in Family & Consumer Resources Management. Fourthly, training centers' lectures available had a significant influence on the satisfaction degrees according to general characteristic variations of the participants. That is, as a training center offers more lectures in the field of subject education than those of subject contents, the participants showed higher satisfaction degrees (p<.05).