• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.6
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• pp.681-687
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• 2023

The selection technique for optimal operation position selection technique is used to present the initial bow and stern draft with minimum resistance, for achievingthat is, the optimal fuel consumption efficiency at a given operating displacement and speed. The main purpose of this studypaper is to develop a program to select the optimal operating position with maximum energy efficiency under given operating conditions based on the effective power data of the target ship. This program was written as a Python-based GUI (Graphic User Interface) usingbased on artificial intelligence techniques sucho that ship owners could easily use the GUIit. In the process, tThe introduction of the target ship, the collection of effective power data through computational fluid dynamics (CFD), the learning method of the effective power model using deep learning, and the program for presenting the optimal operation position using the deep neural network (DNN) model were specifically explained. Ships are loaded and unloaded for each operation, which changes the cargo load and changes the displacement. The shipowners wants to know the optimal operating position with minimum resistance, that is, maximum energy efficiency, according to the given speed of each displacement. The developed GUI can be installed on the ship's tablet PC and application and used to determineselect the optimal operating position.

• Science of Emotion and Sensibility
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• v.26 no.3
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• pp.69-82
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• 2023

High-tech sensibility textile and fashion, in which consumers' emotions and various textile and fashion technologies are converged, is an important industrial group. It is important to develop the ability to apply in practice by gathering the creative by understanding other fields and exchanging ideas through interdisciplinary collaboration in the field of emotional engineering. Through interdisciplinary research and collaboration, talent must be nurtured of individuals who would lead the era of the 4^th Industrial Revolution with the ability to empathize with others as well as the creative convergence-type intellectual ability necessary for the rapidly changing society. To determine content-creation methods, basic research is conducted. Additionally, this study investigates on the current status and educational process of the emotional textile-fashion industry worldwide. To nurture talents in the textile and fashion sensibility science, the basic contents are created to manage the knowledge that delivers sensibility science and the ICT related to this field, as well as in the intensive, PB-style conceptual design based on sensibility. The process from derivation of consumer emotion analysis and product development can be experienced through smart kit practice. Moreover, various methods are developed to set up intellectual property rights generated while developing ICT convergence products as start-ups. The study also covers new knowledge rights to develop emotional textile fashion.

• 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.

• Tunnel and Underground Space
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• v.34 no.3
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• pp.208-217
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• 2024

There is so much research effort for developing and implementing deep learning-based surveillance systems to manage health and safety issues in construction sites. Especially, the development of deep learning-based object detection in various environmental changes has been progressing because those affect decreasing searching performance of the model. Among the various environmental variables, the accuracy of the object detection model is significantly dropped under low illuminance, and consistent object detection accuracy cannot be secured even the model is trained using low-light images. Accordingly, there is a need of low-light enhancement to keep the performance under low illuminance. Therefore, this paper conducts a comparative study of various deep learning-based low-light image enhancement models (GLADNet, KinD, LLFlow, Zero-DCE) using the acquired construction site image data. The low-light enhanced image was visually verified, and it was quantitatively analyzed by adopting image quality evaluation metrics such as PSNR, SSIM, Delta-E. As a result of the experiment, the low-light image enhancement performance of GLADNet showed excellent results in quantitative and qualitative evaluation, and it was analyzed to be suitable as a low-light image enhancement model. If the low-light image enhancement technique is applied as an image preprocessing to the deep learning-based object detection model in the future, it is expected to secure consistent object detection performance in a low-light environment.

• The Journal of the Convergence on Culture Technology
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• v.10 no.2
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• pp.537-545
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• 2024

The importance of University Archives Management is increasing. In this study, we researched cases of collecting and managing educational archival contents in universities. Developed archival contents for software practical education, and implemented it to the Capstone Design course and overseas program. The effect of applying the model was analyzed through surveys and interviews. The Capstone Design Survey, involving 349 participants, indicated the highest satisfaction with the University-Industry Cooperation type. The experience of dissemination and enhancement was aggregated as the second highest satisfaction. In the second survey, 62 students who had participated in the overseas program over the span of two years took part. All nine Likert-type questions showed high satisfaction scores of more than 4 points. The top three satisfaction factors-content, program type, and advanced experience-showed high satisfaction scores of 4.85, 4.74, and 4.71, respectively. Through interviews with professors, mentors, and students, it was also confirmed that instructional methods utilizing archival contents are effective. And the model we developed is applicable for convergence education.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.23 no.3
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• pp.48-66
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• 2024

According to the three amended Laws of the Data Economy and the Data Industry Act of Korea, systems for pseudonymous data integration and Data Safe Zones have been operated separately by selected agencies, eventually causing a burden of use in SMEs, startups, and general users because of complicated and ineffective procedures. An over-stringent pseudonymization policy to prevent data breaches has also compromised data quality. Such trials should be improved to ensure the convenience of use and data quality. This paper proposes a prototype system of the Integrated Data Safe Zone based on redesigned and optimized pseudonymization workflows. Conventional workflows of pseudonymization were redesigned by applying the amended guidelines and selectively revising existing guidelines for business process redesign. The proposed prototype has been shown quantitatively to outperform the conventional one: 6-fold increase in time efficiency, 1.28-fold in cost reduction, and 1.3-fold improvement in data quality.

• Information Systems Review
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• v.26 no.1
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• pp.251-268
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• 2024

In the Fourth Industrial Revolution era, global powers are enhancing R&D support to leverage innovations like AI, IoT, and big data for productivity gains and structural economic and social reforms. Yet, the declining R&D budget growth rate and the forecasted sharp cut in South Korea's R&D budget in 2024 highlight the critical need for national R&D performance management system discussions. Diverging from previous studies focused on quantitative analysis of performance determinants, this research utilizes fuzzy set qualitative comparative analysis(fsQCA) to explore the interplay of factors affecting research institutions' outcomes comprehensively. Analyzing data from 2018 to 2022, it examines three outcome types of research institutions, identifying factor combinations crucial for success. By pinpointing these factors' configurations, the study offers institution-specific performance enhancement guidelines and insights for national R&D policy management and performance evaluation efficiency.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.19 no.4
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• pp.161-182
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• 2024

The study analyzed the rapidly growing food tech startup in South Korea, focusing on industry classification, core technological domains, investment stages, and growth trajectories. Utilizing the ERIS model, two innovative food tech startups, MyChef and CatchTable, were examined as case studies. Results revealed food tech startups are focusing on information technology and smart distribution technology-oriented solutions rather than traditional food production. This study also found that robotics and AI integration were key technology areas. Analyzing the emergence of food tech startups, investment stages, and cumulative investment amounts based on founding years revealed a trend of scaling operations through rounds of funding, especially after securing SERIES A and B funding. The period between 2014 and 2018 saw a dense concentration of food tech startup establishments, likely influenced by favorable conditions for technological innovation amid the Fourth Industrial Revolution. The high rate of strategic mergers and acquisitions and bankruptcy can be interpreted as the complexity inherent in the food tech industry. The case study of MyChef, which grew into HMR manufacturing, and Wad(CatchTable), which expanded into a restaurant reservation platform, derived the entrepreneurs, resources, industry, and strategic factors that served as success factors for food tech startups. This study has practical implications in that it provides entrepreneurs, investors, and policymakers in the food tech industry with insight and direction to develop strategies in line with market trends and technological changes and promote sustainable growth.

• Journal of the Korean Society of Marine Environment & Safety
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• v.24 no.7
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• pp.848-857
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• 2018

Recently, around the world, active development of new renewable energy sources including solar power, waves, and fuel cells, etc. has taken place. Particularly, floating offshore wind farms have been developed for saving costs through large scale production, using high-quality wind power and minimizing noise damage in the ocean area. The development of floating wind farms requires an evaluation of the Maritime Safety Audit Scheme under the Maritime Safety Act in Korea. Floating wind farms shall be assessed by applying the line and area concept for systematic development, management and utilization of specified sea water. The development of appropriate evaluation methods and standards is also required. In this study, proper standards for marine traffic surveys and assessments were established and a systemic treatment was studied for assessing marine spatial area. First, a marine traffic data collector using AIS or radar was designed to conduct marine traffic surveys. In addition, assessment methods were proposed such as historical tracks, traffic density and marine traffic pattern analysis applying the line and area concept. Marine traffic density can be evaluated by spatial and temporal means, with an adjusted grid-cell scale. Marine traffic pattern analysis was proposed for assessing ship movement patterns for transit or work in sea areas. Finally, conceptual design of a Marine Traffic and Safety Assessment Solution (MaTSAS) was competed that can be analyzed automatically to collect and assess the marine traffic data. It could be possible to minimize inaccurate estimation due to human errors such as data omission or misprints through automated and systematic collection, analysis and retrieval of marine traffic data. This study could provides reliable assessment results, reflecting the line and area concept, according to sea area usage.

• Journal of the Korean Society of Food Science and Nutrition
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• v.37 no.7
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• pp.858-868
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• 2008

This study was carried out to investigate the effects of Gastrodiae Rhizoma powder on plasma lipid profiles in elderly volunteers with hyperlipidemia, hypertension, diabetes or heart disease. 32 elderly people, 11 males and 21 females aged $60{\sim}77$ years, were given Gastrodiae Rhizoma powder 15 g twice daily for 6 months. We investigated the antheropometric data, general characteristics and dietary habit by using questionnaires. Fasting blood samples were collected from the subjects before and after this 6 months intervention study. Blood pressure, glucose, hemoglobin and lipid levels of plasma, atherogenic index (AI) and cardiac risk factors (CRF, LHR, HTR) were determined before and after consumption of Gastrodiae Rhizoma powder. The mean body mass index (BMI) of the male and female subjects were 22.4 and 23.6, respectively. The percent of ideal body weight (PIBW) of males and females were 105.6% and 122.3%, respectively. The subjects had decreased intake frequency of fish and meat in their dietary habit. After consumption of Gastrodiae Rhizoma powder, there were no significant differences in blood pressure; however, the blood glucose significantly decreased with Gastrodiae Rhizoma intake in the males. In the subjects, the levels of plasma total cholesterol, triglyceride, and LDL-cholesterol were decreased by the consumption of Gastrodiae Rhizoma powder; while the levels of plasma LDL-cholesterol was significantly decreased in female. Blood pressure and biochemical assessment (blood glucose, hemoglobin, triglyceride, total cholesterol, LDL and HDL-cholesterol) of the subjects were within the normal range. It was found that AI, CRF and LHR were significantly decreased by Gastrodiae Rhizoma intake. The present results indicate that dietary supplementation of Gastrodiae Rhizoma improved lipid metabolism and cardiac risk factor in cardiovascular disease.