• Journal of Industrial Convergence
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• v.22 no.2
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• pp.13-22
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• 2024

In the current epoch of educational technology (EdTech), the realization of a personalized learning system has become increasingly important. This is due to the growing diversity of today's learners in terms of backgrounds, learning styles, and abilities. Traditional educational methods that deliver the same content to all learners often fail to take this diversity into account. This paper identifies models that comprehensively analyze learners' characteristics, interests, and learning histories to meet the growing demand for learner-centered education. Based on these models, we have designed a personalized learning system. This system is structured to support autonomous learning tailored to the learner's current level and goals by identifying strengths and weaknesses based on the learner's learning history. In addition, the system is designed to extend necessary learning elements without changing its architecture. Through this research, we can identify the essential foundations for constructing a user-tailored learning system and effectively develop a system architecture to support personalized learning.

• Journal of the Economic Geographical Society of Korea
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• v.10 no.4
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• pp.461-480
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• 2007

The purpose of this study is to investigated and differences per lifestyle type according to characteristics of participation in eco-tourism by classifying lifestyle types of university student consumers. Also, the influences exerted on characteristics of participation in eco-tourism by the variables of demographical characteristics, lifestyle types and characteristics of eco-tourism were analyzed. The results indicated by the research can be summarized as follows. First, significant differences were found in terms of sociability inclination factors and leisure inclination factors. In other words, the group of people who had participated in eco-tourism were more of sociability-inclined and leisure-inclined lifestyle types than the group of people who had not participated in eco-tourism. Second, logistic analysis on the types of influences exerted on participation in eco-tourism by demographical characteristics, characteristics of eco-tourism and lifestyle types, it was found that significant influences were exerted by such variables of propensity of learning in eco-tourism, leisure inclination factors and school year. Third, regression analysis on the types of influences exerted on intention to participate in eco-tourism by demographical characteristics, characteristics of eco-tourism and lifestyle types, propensity of awareness on eco-tourism, tendency of preferring eco-tourism, sociability inclination factors and progress inclination factors were selected as significant variables.

• Tunnel and Underground Space
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• v.32 no.2
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• pp.131-143
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• 2022

The lunar exploration autonomous vehicle operates based on the lunar topography information obtained from real-time image characterization. For highly accurate topography characterization, a large number of training images with various background conditions are required. Since the real lunar topography images are difficult to obtain, it should be helpful to be able to generate mimic lunar image data artificially on the basis of the planetary analogs site images and real lunar images available. In this study, we aim to artificially create lunar topography images by using the location information-based style transfer algorithm known as Wavelet Correct Transform (WCT2). We conducted comparative experiments using lunar analog site images and real lunar topography images taken during China's and America's lunar-exploring projects (i.e., Chang'e and Apollo) to assess the efficacy of our suggested approach. The results show that the proposed techniques can create realistic images, which preserve the topography information of the analog site image while still showing the same condition as an image taken on lunar surface. The proposed algorithm also outperforms a conventional algorithm, Deep Photo Style Transfer (DPST) in terms of temporal and visual aspects. For future work, we intend to use the generated styled image data in combination with real image data for training lunar topography objects to be applied for topographic detection and segmentation. It is expected that this approach can significantly improve the performance of detection and segmentation models on real lunar topography images.

• Journal of the Korea Convergence Society
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• v.9 no.12
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• pp.25-32
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• 2018

In the massive online fashion market, it is not easy for consumers to find the fashion style they want by keyword search for their preferred style. It can be resolved into consumer needs based fashion recommendation. Most of the existing online shopping sites have collected cumtomer's preference style using the online quastionnair. In this paper, we propose a simple but effective novel model that resolve the traditional method in fashion profiling for consumer's preference style and needs using implicit profiling method. In addition, we proposed a learning model that reflects the characteristics of the images itself through the deep learning-based intelligent preferred fashion model learned from the collected data. We show that the proposed model gave meaningful results through the qualitative evaluation.

• Journal of KIBIM
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• v.14 no.2
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• pp.13-24
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• 2024

This research suggests a novel visualization approach utilizing Generative AI to render photorealistic architectural alternatives images in the early design phase. Photorealistic rendering intuitively describes alternatives and facilitates clear communication between stakeholders. Nevertheless, the conventional rendering process, utilizing 3D modelling and rendering engines, demands sophisticate model and processing time. In this context, the paper suggests a rendering approach employing the text-to-image method aimed at generating a broader range of intuitive and relevant reference images. Additionally, it employs an Text-to-Image method focused on producing a diverse array of alternatives reflecting architects' styles when visualizing the exteriors of residential buildings from the mass model images. To achieve this, fine-tuning for architects' styles was conducted using the Low-Rank Adaptation (LoRA) method. This approach, supported by fine-tuned models, allows not only single style-applied alternatives, but also the fusion of two or more styles to generate new alternatives. Using the proposed approach, we generated more than 15,000 meaningful images, with each image taking only about 5 seconds to produce. This demonstrates that the Generative AI-based visualization approach significantly reduces the labour and time required in conventional visualization processes, holding significant potential for transforming abstract ideas into tangible images, even in the early stages of design.

• Journal of Educational Research in Mathematics
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• v.23 no.2
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• pp.153-171
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• 2013

The purpose of this study is to investigate characteristics of students' problem solving processes based on their mathematical thinking styles and thus to provide implications for teachers regarding how to employ multiple representations. In order to analyze these characteristics, 202 university freshmen were recruited for a paper-and-pencil survey. The participants were divided into four groups on a mathematical-thinking-style basis. There were two students in each group with a total of eight students being interviewed. Results show that mathematical thinking styles are related to defining a mathematical concept, problem solving in relation to representation, and translating between mathematical representations. These results imply methods of utilizing multiple representations in learning and teaching mathematics by embodying Dienes' perceptual variability principle.

• Journal of Broadcast Engineering
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• v.27 no.5
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• pp.619-628
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• 2022

Although face recognition and face generation have been growing in popularity, the privacy issues of using facial images in the wild have been a concurrent topic. In this paper, we propose a face editing network that can reduce privacy issues by generating face images with various properties from a small number of real face images and facial mask information. Unlike the existing methods of learning face attributes using a lot of real face images, the proposed method generates new facial images using a facial segmentation mask and texture images from five parts as styles. The images are then trained with our network to learn the styles and locations of each reference image. Once the proposed framework is trained, we can generate various face images using only a small number of real face images and segmentation information. In our extensive experiments, we show that the proposed method can not only generate new faces, but also localize facial attribute editing, despite using very few real face images.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.28 no.2
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• pp.1-11
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• 2020

This study was carried out to verify how much instructor's communication skill affects the student pilot's study motivation and satisfaction. The instructor's communication styles are classified into 3 groups by pre-analysis. Three types are cooperative type, control type and professional type. Intellectual cause, performance proficiency cause, social cause and stimulation avoidance cause are extracted and analyzed for the cause of study motivation. Cooperative and control type affected all of 4 factors of student's study motivation by influence analysis. Intellectual cause affected control and cooperative type positively, especially more to cooperative type. Performance proficiency cause also had positive influence to control and cooperative type. Stimulation avoidance cause didn't appear to affect all sub-classified 4 factors of instructor's communication type. Influence analysis of student's study satisfaction from instructor's communication style showed that independent variable affected all sub factors positively. Degree of positive influence affected the control type the most, cooperative type was the 2nd, and professional type was the 3rd.

• Proceedings of the Korean Society of Computer Information Conference
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• 2021.07a
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• pp.549-550
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• 2021

사용자에게 맞춘 개인화된 제품과 서비스를 제공하는 기술의 발전으로 개인화의 수요는 점점 늘어날 것으로 전망하고 있다. 또한 개인 맞춤형으로 전문 스포츠 선수화, 족부 장애우를 위한 정형 제화 등 전문적인 기능 중심의 개인화나 패션을 위한 스타일 중심의 개인화 등 개인 맞춤 제작 신발을 제작할 때 기존의 아날로그적인 방식으로 발 변인을 측정했을 때 각 변인에 대해 기준점이 명확하지 않아서 재현성이 떨어진다. 따라서 본 논문에서는 자를 이용해 간단히 측정 가능한 기본적인 발 변인 이용하여 다른 변인들을 학습하고 딥러닝을 이용해 추정하는 방법에 대해 서술한다. 이를 위해 20개의 발 변인을 휙득 하였고 그 중 6개의 기본적인 발 변인을 이용해 14개 변인을적합 방지를 위해 Dorpout을 적용해 학습하고 학습한 데이터를 이용해 학습하지 않은 데이터를 테스트해 각 변인별 결과를 보여준다.

• The Journal of the Korea Contents Association
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• v.13 no.2
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• pp.19-31
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• 2013

Since the high readable source codes help us to understand and modify the program, it is much easy to maintain them. The readability of source code is not only affected by the complexity of algorithms such as control structures but also affected by the coding styles such as naming and indentation. Although various coding standards have been presented for promoting the readability of source codes, it has been usually lost or ignored in a programming course. One of the reasons is that the coding standard is not a hard-and-false rule since it does not contribute to the performance of software. In this paper, we propose a simple automatic system, namely StyleJigsaw, which checks the style of the source codes written by C/C++ or Java. In this system, the coding style score is calculated and visualized as a jigsaw puzzle. To measure the educational effectiveness of StyleJigsaw, several experiments have been conducted on a class students in C++ programming course. According to the experimental results, the coding style score increased about 8.0 points(10.9%) on average using StyleJigsaw. Further, according to a questionnaire survey targeting the students who attended the programming course, about 88.5% of the students responded that StyleJigsaw was of help to learn the coding standards. We expect that the StyleJigsaw can be effectively used to encourage the students to obey the coding standards, resulting in high readable programs.