• Journal of the Korea institute for structural maintenance and inspection
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• v.15 no.5
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• pp.92-100
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• 2011

This paper describes a numerical modeling for deflection calculation using the natural frequency response that is measured acceleration response for concrete bridges. In the formulation of the dynamic deflection, the change amounts and the transformed responses about six kinds of free vibration responses are defined totally. The predicted response can be obtained from the measured acceleration data without requiring the knowledge of the initial velocity and displacement information. The relationship between the predicted response and the actual deflection is derived using the mathematical modeling that is induced by the process of a acceleration test data. In this study, in order to apply the proposed response predicted model to the integration scheme of the natural frequency domain, the Fourier Fast Transform of the deflection response is separated into the frequency component of the measured data. The feasibility for field application of the proposed calculation method is tested by the mode superposition method using the PSC-I bridges superstructures under several cases of moving load and results are compared with the actually measured deflections using transducers. It has been observed that the proposed method can asses the deflection responses successfully when the measured acceleration signals include the vehicle loading state and the free vibration behavior.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.27 no.6
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• pp.605-613
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• 2014

Epistemic uncertainty, the lack of knowledge, is often more important than aleatory uncertainty, variability, in estimating reliability of a system. While the probability theory is widely used for modeling aleatory uncertainty, there is no dominant approach to model epistemic uncertainty. Different approaches have been developed to handle epistemic uncertainties using various theories, such as probability theory, fuzzy sets, evidence theory and possibility theory. However, since these methods are developed from different statistics theories, it is difficult to interpret the result from one method to the other. The goal of this paper is to compare different methods in handling epistemic uncertainty in the view point of calculating the probability of failure. In particular, four different methods are compared; the probability method, the combined distribution method, interval analysis method, and the evidence theory. Characteristics of individual methods are compared in the view point of reliability analysis.

• Journal of The Korean Association of Information Education
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• v.23 no.5
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• pp.469-480
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• 2019

One of the goals of the new 2015 revised curriculum is to cultivate the creativity of students who will live in the era of the Fourth Industrial Revolution to create new things through diverse ideas and challenges based on basic learning skills. Accordingly, in order to solve the given problems rationally, the convergence problem solving ability that can process and utilize various areas of knowledge and information is becoming important. Therefore, in this study, we designed the integrative education using a 3D printer based on Tinkercad modeling and applied it to the class to investigate the effect on the improvement of computing thinking ability of elementary school students. To verify the contents of the study, two classes of 25 sixth-grade elementary school students were divided into an experimental group and a controlled group. For the experimental group, 12 classes of convergence education programs using a 3D printer were applied for about three months, and the same amount of general curriculum was conducted for the control group. After that, the t-tests were carried out using the pre-post test to measure the effectiveness of the computational thinking ability. After the application of the program, the experimental group showed statistically significant improvement in computational thinking ability, but the controlled group showed no statistically significant difference. The results show that convergence education using the Tinkercad modeling-based 3D printer has a positive effect on the improvement of computing thinking ability of elementary school students.

• The Journal of the Korea Contents Association
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• v.21 no.4
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• pp.26-37
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• 2021

This study conducted a big data analysis on news to identify the agenda of media literacy, which has been socially discussed, and on which relevant policy directions will be proposed. To this end 1,336 articles from January 1, 2019 to September 30, 2020 were collected and a topic modeling analysis was conducted according to four periods. Five topics for each period were derived through the analysis, and implications based on the results are as follows. First, the government should implement a nation-level systematic approach to media literacy education according to life cycle stages to generate economic and cultural value. Second, local communities and schools should provide systematic support and education guidance activities to ensure a sustainable ecosystem for media literacy and prevent an educational gap and loss in learning. Third, efforts should be made in various aspects to minimize the side effects resulting from constantly providing media literacy education; furthermore a culture of desirable media application should be established. Finally, a research environment for scientific research on media literacy, active exchange of experience and value obtained in the field, and long-term accumulation of research results should be encouraged to develop a robust knowledge exchange culture.

• The Journal of the Korea Contents Association
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• v.21 no.4
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• pp.38-49
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• 2021

This study analyzed the trend of the term 'false and exaggerated advertisement' in 5,141 newspaper articles from 1990 to 2019 using text mining methodology. First of all, we identified the most frequent keywords of false and exaggerated advertisements through frequency analysis for all newspaper articles, and understood the context between the extracted keywords. Next, to examine how false and exaggerated advertisements have changed, the frequency analysis was performed by separating articles by 10 years, and the tendency of the keyword that became an issue was identified by comparing the number of academic papers on the subject of the highest keywords of each year. Finally, we identified trends in false and exaggerated advertisements based on the detailed keywords in the topic using the topic modeling. In our results, it was confirmed that the topic that became an issue at a specific time was extracted as the frequent keywords, and the keyword trends by period changed in connection with social and environmental factors. This study is meaningful in helping consumers spend wisely by cultivating background knowledge about unfair advertising. Furthermore, it is expected that the core keyword extraction will provide the true purpose of advertising and deliver its implications to companies and related employees who commit misconduct.

• Journal of Digital Convergence
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• v.19 no.11
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• pp.517-523
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• 2021

The outcome of the consultation is important to both the counselor and the researcher. Analyzing the trends of research on the results of counseling that have been carried out so far will help to comprehensively structure the results of consultations. The purpose of this research is to analyze research trends in Korea, focusing on research related to the outcomes of counseling published in 「Korean Journal of Counseling」 from 2011 to 2021, which is one of the well-known academic journals in the field of counseling in Korea. This is to explore the direction of future research by navigating the knowledge structure of research. There were 197 studies used for analysis, and the final 339 keyword were extracted during the node extraction process and used for analysis. As a result of extracting potential topics using the LDA algorithm, "Measurement and evaluation of counseling outcomes", "emotions and mediate factors affecting interpersonal relationships", and "career stress and coping strategies" are the main topics. Identifying major topics through trend analysis of counseling performance research contributed to structuring counseling performance. In-depth research on these topics needs to continue thereafter.

• Journal of Korean Library and Information Science Society
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• v.54 no.3
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• pp.321-346
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• 2023

A data paper describing research data helps credit researchers producing the data while helping other researchers verify previous research and start new research by reusing the data. Publishing a data paper and depositing data to a public data repository are increasing with these benefits. A domestic academic society that plans to publish data papers faces challenges, including timely acquiring tremendous knowledge concerning data paper structures and templates, peer review policy and process, and trustworthy data repositories, as a data paper has different characteristics, unlike a research paper. However, the need for more research and information concerning the critical elements of data paper and the peer-review process makes it difficult to operate for data paper review and publication. To address these issues, we propose essential concepts of the data paper and the data paper peer-review, including the process model of the peer-review with in-depth analysis of five data journals' data paper templates, articles, and other guides worldwide. Academic societies intending to publish or add data papers as a new type of paper may establish policies and define a peer-review process by adopting the proposed conceptual models, effectively streamlining the preparation of data paper publication.

• Journal of Ecology and Environment
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• v.47 no.4
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• pp.228-240
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• 2023

Growing complexity in ecosystem structure and functions, under impacts of climate and land-use changes, requires interdisciplinary understandings of processes and the whole-system, and accurate estimates of the changing functions. In the last three decades, observation networks for biodiversity, ecosystems, and ecosystem functions under climate change, have been developed by interested scientists, research institutions and universities. In this paper we will review (1) the development and on-going activities of those observation networks, (2) some outcomes from forest carbon cycle studies at our super-site "Takayama site" in Japan, and (3) a few ideas how we connect in-situ and satellite observations as well as fill observation gaps in the Asia-Oceania region. There have been many intensive research and networking efforts to promote investigations for ecosystem change and functions (e.g., Long-Term Ecological Research Network), measurements of greenhouse gas, heat, and water fluxes (flux network), and biodiversity from genetic to ecosystem level (Biodiversity Observation Network). Combining those in-situ field research data with modeling analysis and satellite remote sensing allows the research communities to up-scale spatially from local to global, and temporally from the past to future. These observation networks oftern use different methodologies and target different scientific disciplines. However growing needs for comprehensive observations to understand the response of biodiversity and ecosystem functions to climate and societal changes at local, national, regional, and global scales are providing opportunities and expectations to network these networks. Among the challenges to produce and share integrated knowledge on climate, ecosystem functions and biodiversity, filling scale-gaps in space and time among the phenomena is crucial. To showcase such efforts, interdisciplinary research at 'Takayama super-site' was reviewed by focusing on studies on forest carbon cycle and phenology. A key approach to respond to multidisciplinary questions is to integrate in-situ field research, ecosystem modeling, and satellite remote sensing by developing cross-scale methodologies at long-term observation field sites called "super-sites". The research approach at 'Takayama site' in Japan showcases this response to the needs of multidisciplinary questions and further development of terrestrial ecosystem research to address environmental change issues from local to national, regional and global scales.

• Korean Chemical Engineering Research
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• v.62 no.3
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• pp.214-224
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• 2024

Valves play an essential role in a chemical plant such as regulating fluid flow and pressure. Therefore, optimal selection of the valve size and type is essential task. Valve size and type have been selected based on theoretical formulas about calculating valve sizing coefficient (Cv). However, this approach has limitations such as requiring expert knowledge and consuming substantial time and costs. Herein, this study developed a model for predicting valve sizes and types using machine learning. We developed models using four algorithms: ANN, Random Forest, XGBoost, and Catboost and model performances were evaluated using NRMSE & R² score for size prediction and F1 score for type prediction. Additionally, a case study was conducted to explore the impact of phases on valve selection, using four datasets: total fluids, liquids, gases, and steam. As a result of the study, for valve size prediction, total fluid, liquid, and gas dataset demonstrated the best performance with Catboost (Based on R², total: 0.99216, liquid: 0.98602, gas: 0.99300. Based on NRMSE, total: 0.04072, liquid: 0.04886, gas: 0.03619) and steam dataset showed the best performance with RandomForest (R²: 0.99028, NRMSE: 0.03493). For valve type prediction, Catboost outperformed all datasets with the highest F1 scores (total: 0.95766, liquids: 0.96264, gases: 0.95770, steam: 1.0000). In Engineering Procurement Construction industry, the proposed fluid-specific machine learning-based model is expected to guide the selection of suitable valves based on given process conditions and facilitate faster decision-making.

• The Journal of Korean Society for School & Community Health Education
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• v.9 no.1
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• pp.63-83
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• 2008

Objectives: This study was to examine HIV/AIDS knowledge of transmission, attitudes toward homosexuals on stigma of HIV/AIDS and discriminatory attitudes towards person with HIV/AIDS (PWHAs) by middle and high school students in Seoul, Korea. Methods: The population of this study is middle and high school students in Seoul, Korea. Eight junior high schools and eight senior high schools were selected randomly. Three thousand and one hundred thirty-one students (1704 males and 1397 males) from 16 schools participated in the survey, and 2.977 cases were analyzed. A self-administered questionnaire measuring socio-demographic variables, HIV/AIDS knowledge of transmission, sigma of HIV/AIDS (3 items, 5-point Likert-type scale) and discriminatory attitudes PWHAs (5 items, 5-point Likert-type scale) was utilized. The Structural Equation Modeling was employed to investigate the research Model. Results: The empirical study shows that a number of statistical hypotheses are significant. The stigma and discriminatory attitudes PWHAs were significantly different by middle and high school students. The attitudes toward homosexuals and HIV/AIDS knowledge of transmission were important factors on stigma and discriminatory attitudes PWHAs. Socio-demographical variables such as sex was related to the stigma and discriminatory attitudes PWHAs. Conclusion: Therefore, it is important to design HIV prevention strategies that increase in positive attitudes towards PWHAs.