• Journal of Digital Convergence
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• v.16 no.11
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• pp.221-230
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• 2018

Most of researchers and business futurists agree that traditional organizational designs are inadequate for coping with today's turbulent and increasingly networked world. Executives in small firms find that their organizations must tap into an extended network of partners to achieve the scale and power needed to succeed in industries dominated by large, global firms. As they attempt to build lean yet agile businesses, these executives are finding that they no longer rely on gut instinct alone. Neither can they simply copy organizational model that worked in the past. They must understand how organizational design choices influence operational efficiency and flexibility and, even more important, how to best align the organization with the environment and the strategy chosen to quickly and effectively sense and respond to opportunities and threats This research examines the capabilities required to build businesses that can survive and prosper in today's fast-faced and uncertain environment. The insights presented in this research have emerged from over 30 years of work with hundreds of executives and entrepreneurs as they struggled to build businesses that could cope with the demands of a rapidly changing, networked global economy. The insights from this research suggest that IT is an important enabler for developing the best capabilities required for success.

• Journal of Navigation and Port Research
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• v.43 no.1
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• pp.72-78
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• 2019

The second-hand ship market provides immediate access to the freight market for shipping investors. When introducing second-hand vessels, the precise estimate of the price is crucial to the decision-making process because it directly affects the burden of capital cost to investors in the future. Previous studies on the second-hand market have mainly focused on the market efficiency. The number of papers on the estimation of second-hand vessel values is very limited. This study proposes an artificial neural network model that has not been attempted in previous studies. Six factors, freight, new-building price, orderbook, scrap price, age and vessel size, that affect the second-hand ship price were identified through literature review. The employed data is 366 real trading records of Panamax second-hand vessels reported to Clarkson between January 2016 and December 2018. Statistical filtering was carried out through correlation analysis and stepwise regression analysis, and three parameters, which are freight, age and size, were selected. Ten-fold cross validation was used to estimate the hyper-parameters of the artificial neural network model. The result of this study confirmed that the performance of the artificial neural network model is better than that of simple stepwise regression analysis. The application of the statistical verification process and artificial neural network model differentiates this paper from others. In addition, it is expected that a scientific model that satisfies both statistical rationality and accuracy of the results will make a contribution to real-life practices.

• Journal of The Korean Association For Science Education
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• v.39 no.1
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• pp.59-72
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• 2019

The purpose of this study is to show that epistemic considerations can be used meaningfully in the argumentation of elementary students, and to provide data on students' epistemic considerations that will be the basis for designing and evaluating scientific argumentation. The epistemic considerations in students' small group argumentations were explored based on Epistemic Considerations in Students' Epistemologies in Practice: EIP' suggested by Berland et al. (2016). The major results of this study are as follows: First, epistemic considerations in elementary school students' small group argumentation appeared in all four aspects: Nature, generality, justification and audience. The epistemic considerations varied according to context in each discussion situation. Second, epistemic considerations did not exist independently. They influenced each other and helped to reveal new types of considerations. The results of this study confirmed that argumentation can be used in elementary school science class. Understanding how students are involved in argumentation and how these epistemic considerations can affect students' argumentation can be helpful to teachers who design and evaluate small group argumentation. Students' achievement level affected epistemic considerations but learning approach types did not affect on. In addition, epistemic considerations may have a positive or negative effect on each other depending on the discussion situation in the process of interaction. So consideration of normative argumentation rules and teaching strategies should be considered in order for epistemic considerations to positively affect each other.

• Journal of The Korean Association For Science Education
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• v.39 no.1
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• pp.45-57
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• 2019

NOS education through the history of science is regarded effective. However, science teaching has been criticized for not considering the interest of the learners enough and providing the context of learning themes that hinder the understanding of NOS. This study intends to convey the NOS element through the rich context of storytelling. The theme of the story is the history of continental drift, in which, the debate of many scientists and Wegener's creativity are prominent. Of the various media that deliver storytelling, the most powerful medium that leads to personal immersion is computer games, and among many kinds of games, the main genre of storytelling is role-playing games (RPGs). We developed the science history role-playing game (SHRPG) focusing on continental drift. The game development procedure followed Kim's 4F process (2017), which consists of the Figure Out, Focus, Fun Design, and Finalize. The story was constructed based on the NOS elements of Lederman et al. (2002), namely creativity and imagination demand, subjectivity, socio-cultural personality and tentativeness, which are all present in the story of the continental drift theory. The mechanics and rules of the RPG included quests, rewards, quizzes, NOS scores, and rankings. In the final phase of development, the game developed was pilot tested four times. The results of the tests showed that students' understanding of NOS through SHRPG has increased, especially in the creativity domain. The students' satisfaction with the fun, sympathy, and immersion during the game was very high.

• Journal of the Korea Society of Computer and Information
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• v.26 no.4
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• pp.105-112
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• 2021

In the era of big data, interest in data is exploding. In particular, the development of the Internet and social media has led to the creation of new data, enabling the realization of the era of big data and artificial intelligence and opening a new chapter in convergence technology. Also, in the past, there are many demands for analysis of data that could not be handled by programs. In this paper, an analysis model was designed and verified for classification of unstructured data, which is often required in the era of big data. Data crawled DBPia's thesis summary, main words, and sub-keyword, and created a database using KoNLP's data dictionary, and tokenized words through morpheme analysis. In addition, nouns were extracted using KAIST's 9 part-of-speech classification system, TF-IDF values were generated, and an analysis dataset was created by combining training data and Y values. Finally, The adequacy of classification was measured by applying three analysis algorithms(random forest, SVM, decision tree) to the generated analysis dataset. The classification model technique proposed in this paper can be usefully used in various fields such as civil complaint classification analysis and text-related analysis in addition to thesis classification.

• Korean Chemical Engineering Research
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• v.59 no.2
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• pp.209-218
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• 2021

First principle-based modeling studies have been performed to improve the heat exchange efficiency of ORV and optimize operation, but the heat transfer coefficient of ORV is an irregular system according to time and location, and it undergoes a complex modeling process. In this study, FNN, LSTM, and AutoML-based modeling were performed to confirm the effectiveness of data-based modeling for complex systems. The prediction accuracy indicated high performance in the order of LSTM > AutoML > FNN in MSE. The performance of AutoML, an automatic design method for machine learning models, was superior to developed FNN, and the total time required for model development was 1/15 compared to LSTM, showing the possibility of using AutoML. The prediction of NG and seawater discharged temperatures using LSTM and AutoML showed an error of less than 0.5K. Using the predictive model, real-time optimization of the amount of LNG vaporized that can be processed using ORV in winter is performed, confirming that up to 23.5% of LNG can be additionally processed, and an ORV optimal operation guideline based on the developed dynamic prediction model was presented.

• Journal of the Korean Recycled Construction Resources Institute
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• v.9 no.3
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• pp.303-310
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• 2021

Cracks in bridges are important factors that indicate the condition of bridges and should be monitored periodically. However, a visual inspection conducted by a human expert has problems in cost, time, and reliability. Therefore, in recent years, researches to apply a deep learning model are started to be conducted. Deep learning requires sufficient data on the situations to be predicted, but bridge crack data is relatively difficult to obtain. In particular, it is difficult to collect a large amount of crack data in a specific situation because the shape of bridge cracks may vary depending on the bridge's design, location, and construction method. This study developed a crack detection model that generates and trains insufficient crack data through a Generative Adversarial Network. GAN successfully generated data statistically similar to the given crack data, and accordingly, crack detection was possible with about 3% higher accuracy when using the generated image than when the generated image was not used. This approach is expected to effectively improve the performance of the detection model as it is applied when crack detection on bridges is required, though there is not enough data, also when there is relatively little or much data f or one class.

• Journal of the Korea Convergence Society
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• v.11 no.12
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• pp.177-186
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• 2020

Entrepreneurship education has been emphasized worldwide and the number of universities that open related subjects have been increasing. K University, located in Gyeonggi-do, was selected as one of the leading universities in entrepreneurship in 2014, and has continued to grow quantitatively by providing support and education related to entrepreneurship on and off campus. In addition, major issues in entrepreneurship education were derived by conducting written or face-to-face interviews and advisory meetings with instructors, field experts, and education demanders for environmental analysis. Based on this, three major tracks(venture start-up, entrepreneurship convergence, and social venture activation) were derived, and major competency and learning goals for each track were presented. On the other hand, in order for this study to be more effectively accepted, it is necessary to present the objectives of each track, the capabilities pursued, and the courses that help students' progress. Therefore, in the future research, it is necessary to design and present the goals for each track, the curriculum road map, and the detailed curriculum of the convergence major, and at the same time, research to match the appropriate teaching method for each newly opened subject will be required to increase educational effectiveness.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.1
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• pp.1-8
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• 2021

This study developed low-cost and high-efficiency pavement condition monitoring technology to produce the key information required for pavement management. A noise and artificial intelligence-based monitoring system was devised to compensate for the shortcomings of existing high-end equipment that relies on visual information and high-end sensors. From idea establishment to system development, functional definition, information flow, architecture design, and finally, on-site field evaluations were carried out. As a result, confidence in the high level of artificial intelligence evaluation was secured. In addition, hardware and software elements and well-organized guidelines on system utilization were developed. The on-site evaluation process confirmed that non-experts could easily and quickly investigate and visualized the data. The evaluation results could support the management works of road managers. Furthermore, it could improve the completeness of the technologies, such as prior discriminating techniques for external conditions that are not considered in AI learning, system simplification, and variable speed response techniques. This paper presents a new paradigm for pavement monitoring technology that has lasted since the 1960s.

• The Mathematical Education
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• v.61 no.4
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• pp.597-612
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• 2022

Recently, large-scale mathematics assessments are shifting from traditional paper-based tests to computer-based tests, nationally and internationally. This study explored the mode effect (the difference in student achievement by the change of test mode) according to the types of test items, the technological function reflected in the items, the characteristics of students' computer use, and the computer-based test environment. To this end, we analyzed the results of the 2020 national assessment of educational achievement of high school mathematics conducted on a paper and computer basis. As a result, firstly, the mode effect induced by the mode transition was generally insignificant, but the mode effect was larger in the extended response type than other types. Secondly, there were differences in the mode effect according to the transition to test with computer mode where innovative items were added. Thirdly, the difference between mode effects was statistically significant according to the student's sense of efficacy in computer use. The results of this study suggest that innovative items should be introduced deliberately according to the targeted content and competency in evaluation, and that assessment design and environment preparation need to be carefully developed so that nonessential abilities other than students' mathematical ability or incidental situation do not distort the assessment results.