• Journal of the Korean Society for Marine Environment & Energy
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• v.14 no.2
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• pp.107-113
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• 2011

To evaluate the performance of the hydrodynamic model, we introduced 10 skill assessments that are assorted by two groups: quantitative skill assessments (Absolute Average Error or AAE, Root Mean Squared Error or RMSE, Relative Absolute Average Error or RAAE, Percentage Model Error or PME) and qualitative skill assessments (Correlation Coefficient or CC, Reliability Index or RI, Index of Agreement or IA, Modeling Efficiency or MEF, Cost Function or CF, Coefficient of Residual Mass or CRM). These skill assessments were applied and calculated to evaluate the hydrodynamic modeling at one of Florida estuaries for water level, current, and salinity as comparing measured and simulated values. We found that AAE, RMSE, RAAE, CC, IA, MEF, CF, and CRM are suitable for the error assessment of water level and current, and AAE, RMSE, RAAE, PME, CC, RI, IA, CF, and CRM are good at the salinity error assessment. Quantitative and qualitative skill assessments showed the similar trend in terms of the classification for good and bad performance of model. Furthermore, this paper suggested the criteria of the "good" model performance for water level, current, and salinity. The criteria are RAAE < 10%, CC > 0.95, IA > 0.98, MEF > 0.93, CF < 0.21 for water level, RAAE < 20%, CC > 0.7, IA > 0.8, MEF > 0.5, CF < 0.5 for current, and RAAE < 10%, PME < 10%, CC > 0.9, RI < 1.15, CF < 0.1 for salinity.

• Applied Chemistry for Engineering
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• v.32 no.4
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• pp.361-370
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• 2021

Carbon fiber reinforced polymer (CFRP) is one of the composite materials, which has a unique property that is lightweight but strong. The CFRPs are widely used in various industries where their unique characteristics are required. In particular, electric and unmanned aerial vehicles critically need lightweight parts and bodies with sufficient mechanical strengths. Vehicles using the battery as a power source should simultaneously meet two requirements that the battery has to be safely protected. The vehicle should be light of increasing the mileage. The CFRP has considered as the one that satisfies the requirements and is widely used as battery housing and other vehicle parts. On the other hand, in the battery area, carbon fibers are intensively tested as battery components such as electrodes and/or current collectors. Furthermore, using carbon fibers as both structure reinforcements and battery components to build a structural battery is intensively investigated in Sweden and the USA. This mini-review encompasses recent research trends that cover the classification of structural batteries in terms of functionality of carbon fibers and issues and efforts in the battery and discusses the prospect of structural batteries.

• Journal of the Korea Fashion and Costume Design Association
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• v.24 no.3
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• pp.111-125
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• 2022

Recently, the MZ generation has been leading overall fashion trends, and fashion companies focus on design, marketing, and new products targeting the MZ generation. However, it is expected that a fit problem may occur if the M and Z generations are combined when producing clothing. Therefore, this study aims to analyze the differences between the two groups by comparing the body size according to the classification of the M and Z generations. In addition, this study analyzes whether the body shape of the MZ generation is different from the past generations and analyzes major changes in body size for clothing manufacturing through graphical visualization. As for the research method, a t-test was conducted to verify the significant difference between the measurements for each age group. Generation M was defined as those who are 27-39 years old, and Generation Z was defined as those who are 20-26 years old. In order to examine the changes in body measurements according to the measurement year, the 7th Size Korea and 8th Size Korea data were analyzed. In order to examine the visual changes according to the measurement year and age group, major measurements of clothing construction were analyzed. As a result, it was found that Generation M had a significantly higher height item than Generation Z. Also, in terms of circumference, width, and thickness, Generation M was larger than Generation Z. But the size of the bra cup was larger in Generation Z than Generation M. As a result of analyzing the body size changes, in the height item, the 8th Size Korea measurements were found to be significantly higher in shoulder height and navel level waist height. In the length and circumference items, the 8th Size Korea measurements were larger than the 7th. In the width, thickness, and other items, the 8th measurements were larger than the 7th.

• Journal of The Korean Association For Science Education
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• v.35 no.3
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• pp.343-352
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• 2015

This study is to discover the diverse issues related to Self-Directed Learning Screening (SDLS) and draw implications by analyzing its critical points. Using content analysis and interviews with admission officers, tentative issues were finalized and reviewed by researchers and educators. A Survey was developed based on the 96 issues after having evidence of content validity using the Delphi method. To conduct survey, e-mails were sent to admissions officers in twenty science specialized high schools. They were asked to response to questions about perceptions of critical issues and if there are any issues in their schools. Using mean scores of two factors based on its critical issues and frequencies, a two-dimensional classification table for each type was presented. Four critical issues for each type were discovered. The first type indicates minor issues that include 28 items that were less than the overall mean scores in terms of critical issues and its frequencies. The second type indicates tentative issues that include 29 items that were greater than the mean score in critical issues but less in its frequencies. The third type indicates general issues that include 17 items that were less than the mean score in critical issues but greater in its frequencies. The last type indicates critical issues that include 22 items that were greater than the mean scores in two factors. The discovered results of critical issues and its types in this study can be considered a core part of the screening process in schools, especially, critical issues should play an important role in the process of admission screening planning.

• Korean Journal of Construction Engineering and Management
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• v.22 no.2
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• pp.3-11
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• 2021

Myanmar is an undeveloped country with high development value among Asian countries. Therefore, various countries including the U.S. are considering entering the market. In this respect, demand for real estate development project is forecast to grow on increased inflow of foreigners and Myanmar's economic growth. However, Myanmar is a high-risk country in terms of overseas companies, including national risk. In this study, we conducted an in-depth interview with experts (law, finance, technology, and local experts) after analyzing data on Myanmar to extract risk-causing factors. Through this, 106 risk factors were extracted, and the final risk classification system was established by conducting three-time groupings using the affinity diagramming. And the relative importance of each factor was presented using the analytic hierarchy process (AHP) technique. As a result, the country-related risk, the fund-related risk, and the pre-sale-related risk were highly important. The research results are expected to provide risk management standards to companies entering the Myanmar real estate development type project.

• Environmental and Resource Economics Review
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• v.24 no.1
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• pp.189-224
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• 2015

To meet sectoral emission target by 2020 and prepare for the emission trading scheme from 2015, decomposition analysis of energy consumption and GHG emission is required by 18 subsectors in industry sector where emission targets are established. Log Mean Divisia Index decomposition method was used to analyze factors' effects on energy and emission in the industry sector and by 18 subsectors from 2004 to 2011. Industrial energy consumption was increased due to the production effect and energy intensity effect. However structure effect contributes to the decrease of energy consumption. In terms of emissions (including indirect emission due to electricity consumption) in the industry sector, only structure effect contributed to the emission reduction. Factors' effects by subsectors were different. Cement industry, which is included at Nonmetal shows different results from those of Nonmetal industry and machinery industry, which is a subsector of Fabricated Metal, was also similar. In this regard, we should not apply the policy implications from decomposition analysis of aggregated industry such as Nonmetal or Fabricated Metal to its subsectors uniformly and develop a differentiated policy for each subsector industry.

• Science of Emotion and Sensibility
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• v.23 no.4
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• pp.21-32
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• 2020

The perception of a fashion product may vary depending on the texture and color of its material. Additionally, the product may appear differently in person versus on a digital screen. Therefore, in the present study, we sought to investigate the differences in visual sensibility evaluation between materials in person and on digital screens. In this study, three pairs of visual sensibility adjectives were tested for 60 samples selected as fashion materials. Fashion materials were divided into colors, embossings, and visual clarity categories. Results showed that each color had the same sense during in-person and digital evaluation. In terms of visual sensibility according to embossing, both in-person and digital evaluations of materials with embossings were found to have the same visual sense, whereas those without embossings looked different between in-person and digital evaluations. Assessments based on visual classification showed that both in-person and digital evaluations had the same sensibility. This study is meaningful in suggesting that when evaluating the visual sense of fashion material, the sensation for the digital screen versus in person may be different in some cases.

• Asia Marketing Journal
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• v.13 no.4
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• pp.139-158
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• 2012

This study was intended to classify tie-in promotion tools by the criteria of benefit-fit between consumer and tie-in promotions. Tie-in promotion tools include tie-in price reductions, tie-in coupons, tie-in memberships, tie-in contests, tie-in sweepstakes, tangible and intangible tie-in premiums, tie-in payment terms, tie-in samples, tie-in events(culture event, charity event, experience event) and tie-in fund·rebates. The fit between consumer pursuit benefit and tie-in promotion supplying benefit was used as a classification criteria on the basis of Lee et al.'s study in 2011. For the experiment, one stimuli and 12 scenarioes were developed. 100 pieces of data were obtained for each scenario. As a result, benefit fit was subsequently divided into two factors: hedonic-benefit fit and utilitarian-benefit fit. Tie-in promotion tools were then classified into 4 types: high hedonic benefit-added, high utilitarian benefit-added, low hedonic benefit-added, and low utilitarian benefit-added. In previous research, tie-in promotion type was mainly divided by the evaluative criteria on company's viewpoint such as horizontal/vertical or intra-company/ inter-company, which reflects mutual exclusiveness between two criteria. Whereas, in this study, tie-in promotion type was divided by evaluative criteria on consumer's viewpoint such as hedonic- benefit fit/utilitarian-benefit fit. The classifications in this study practically reflect benefit-added of tie-in promotion type superadded one benefit coexisting two benefits.

• Journal of The Korean Association For Science Education
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• v.44 no.3
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• pp.231-248
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• 2024

This study developed a chatbot for first-year high school students, employing open-source software and the Korean Sentence-BERT model for AI-powered document classification. The chatbot utilizes the Sentence-BERT model to find the six most similar Q&A pairs to a student's query and presents them in a carousel format. The initial dataset, built from online resources, was refined and expanded based on student feedback and usability throughout over the operational period. By the end of the 2023 academic year, the chatbot integrated a total of 30,819 datasets and recorded 3,457 student interactions. Analysis revealed students' inclination to use the chatbot when prompted by teachers during classes and primarily during self-study sessions after school, with an average of 2.1 to 2.2 inquiries per session, mostly via mobile phones. Text mining identified student input terms encompassing not only science-related queries but also aspects of school life such as assessment scope. Topic modeling using BERTopic, based on Sentence-BERT, categorized 88% of student questions into 35 topics, shedding light on common student interests. A year-end survey confirmed the efficacy of the carousel format and the chatbot's role in addressing curiosities beyond integrated science learning objectives. This study underscores the importance of developing chatbots tailored for student use in public education and highlights their educational potential through long-term usage analysis.

• Journal of the Korea Convergence Society
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• v.12 no.9
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• pp.11-19
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• 2021

A software system is required to change during its life cycle due to various requirements such as adding functionalities, fixing bugs, and adjusting to new computing environments. Such program code modification should be considered as carefully as a new system development becase unexpected software errors could be introduced. In addition, when reusing open source programs, we can expect higher quality software if code changes of the open source program are predicted in advance. This paper proposes a Convolutional Neural Network (CNN)-based deep learning model to predict source code changes. In this paper, the prediction of code changes is considered as a kind of a binary classification problem in deep learning and labeled datasets are used for supervised learning. Java projects and code change logs are collected from GitHub for training and testing datasets. Software metrics are computed from the collected Java source code and they are used as input data for the proposed model to detect code changes. The performance of the proposed model has been measured by using evaluation metrics such as precision, recall, F1-score, and accuracy. The experimental results show the proposed CNN model has achieved 95% in terms of F1-Score and outperformed the multilayer percept-based DNN model whose F1-Score is 92%.