• Journal of the Korea Computer Graphics Society
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• v.25 no.3
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• pp.85-92
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• 2019

A 3D virtual character playing a role in a digital story-telling has a unique style in its appearance and motion. Because the style reflects the unique personality of the character, it is very important to preserve the style and keep its consistency. However, when the character's motion is directly controlled by a user's motion who is wearing motion sensors, the unique style can be discarded. We present a novel character motion control method that uses only a small amount of animation data created only for the character to preserve the style of the character motion. Instead of machine learning approaches requiring a large amount of training data, we suggest a search-based method, which directly searches the most similar character pose from the animation data to the current user's pose. To show the usability of our method, we conducted our experiments with a character model and its animation data created by an expert designer for a virtual reality game. To prove that our method preserves well the original motion style of the character, we compared our result with the result obtained by using general human motion capture data. In addition, to show the scalability of our method, we presented experimental results with different numbers of motion sensors.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.06a
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• pp.167-168
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• 2022

선박을 운항함에 있어 최적항로를 결정하는 것은 항해시간과 연료 소모를 줄이는 중요한 요인 중의 하나이다. 기존에는 항로를 결정하기 위해 항해사의 전문적인 지식이 요구되지만 이러한 방법은 최적의 항로라고 판단하기 어렵다. 따라서 연료비 절감과 선박의 안전을 고려한 최적의 항로를 생성할 필요가 있다. 연료 소모량 혹은 항해시간을 최소화하기 위해서 에이스타 알고리즘, Dijkstra 알고리즘을 적용한 연구가 있다. 하지만 이러한 연구들은 최단거리만 구할 뿐 선박의 안전, 해상상태 등을 고려하지 못한다. 이를 보완하기 위해 본 연구에서는 강화학습 알고리즘을 적용하고자한다. 강화학습 알고리즘은 앞으로 누적 될 보상을 최대화 하는 행동으로 정책을 찾는 방법으로, 본 연구에서는 강화학습 알고리즘의 하나인 Q-learning을 사용하여 선박의 안전을 고려한 최적의 항로를 생성하는 기법을 제안 하고자 한다.

• Journal of Internet Computing and Services
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• v.23 no.4
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• pp.35-43
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• 2022

Makeup is the most common way to improve a person's appearance. However, since makeup styles are very diverse, there are many time and cost problems for an individual to apply makeup directly to himself/herself.. Accordingly, the need for makeup automation is increasing. Makeup transfer is being studied for makeup automation. Makeup transfer is a field of applying makeup style to a face image without makeup. Makeup transfer can be divided into a traditional image processing-based method and a deep learning-based method. In particular, in deep learning-based methods, many studies based on Generative Adversarial Networks have been performed. However, both methods have disadvantages in that the resulting image is unnatural, the result of makeup conversion is not clear, and it is smeared or heavily influenced by the makeup style face image. In order to express the clear boundary of makeup and to alleviate the influence of makeup style facial images, this study divides the makeup area and calculates the loss function using HoG (Histogram of Gradient). HoG is a method of extracting image features through the size and directionality of edges present in the image. Through this, we propose a makeup transfer network that performs robust learning on edges.By comparing the image generated through the proposed model with the image generated through BeautyGAN used as the base model, it was confirmed that the performance of the model proposed in this study was superior, and the method of using facial information that can be additionally presented as a future study.

• Journal of Christian Education in Korea
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• v.77
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• pp.251-276
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• 2024

This study aimed to enhance the educational competencies of instructors and improve the quality of higher education by identifying instructing types, developing an assessment diagnostic tool, and designing a customized faculty training curriculum for each type. To achieve this, a literature review and Delphi research were conducted. The results are summarized as follows: First, instructing types such as 'Star Lecturer', 'Learning Mentor', and 'Designer' were identified through the analysis of previous studies. Second, a diagnostic tool for determining an instructor's type was developed by modifying and enhancing Grasha's Teaching Style Inventory, which is widely used both domestically and internationally. This tool comprises 24 questions, with 8 questions for each type. Third, a curriculum was designed for each instructing type, consisting of common courses necessary for all types and specialized courses tailored to the characteristics of each type. The common courses cover essentials for lesson design, implementation, and evaluation, while the specialized courses cater to the unique needs of each instructing type. Fourth, the developed model, tools, and curriculum underwent validation. A Delphi method was employed with a group of 10 experts, leading to revisions and finalizations based on their feedback. This study has laid the groundwork for instructors to identify their own teaching styles and receive customized training, thereby enhancing their teaching effectiveness and overall educational quality. However, further research is necessary to develop systems and mechanisms for the operationalization of these findings, including incentives for instructors and strategies for disseminating information among participants.

• Journal of the Korea Society of Computer and Information
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• v.11 no.4 s.42
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• pp.109-117
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• 2006

E-learning method has many advantages that supplement the shortfalls of offline education. For this reason, today's offline educational institutions adopted the online education technique to improve learning effectiveness. Recently, general universities have partially adopted online learning. As a result, a study is searching for ways to improve the effectiveness of education by copying the merits of the existing offline education onto the online education. Thus a proper evaluation of learners and a feedback provision are considered necessary to improve the effectiveness of online learning. This study aims to suggest a model that will improve learning efficiency by adapting the advantages of offline education to online learning. To evaluate properly, this study conducted Item Response Test to examine the learners and finally ensure them an adequate level of education. Also, this study suggested a way to enhance learning efficiency by finding out each learner's study habits and to address the weaknesses of online learning. It is expected that the suggested method would be helpful in bettering learner's ability to study in school environment.

• Proceedings of the Korea Society of Design Studies Conference
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• 2000.11a
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• pp.124-125
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• 2000

과거의 자동차 인테리어 디자인은 스타일링이나 인간공학적 측면을 주로 배려하여 디자인되어 왔다. 그러나 시간의 흐름에 따른 사용자의 가치 및 요구(needs)의 다양화, 흑은 관련 기술의 발전에 따라 "주행" 중 "제어"해야하는 많은 기능들이 추가됨에 따라 이러한 다양한 조작 대상들을 동시에 조작하거나 조작하기 위한 학습이 점점 더 어려워지고 있는 실태이다. (중략)

• Journal of Korean Home Economics Education Association
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• v.28 no.3
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• pp.33-45
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• 2016

The purposes of this study were to develop PBL programs for class, and to examine the effects of PBL. The 2 PBL experiencing the roles of "fashion editor" and "fashion stylist" were conducted in "Fashion & Social Culture" and "Fashion Design" parts. The objects were 29 students in Home Economics Education Department. The effects of PBL were observed through contents analysis to reflective journals. Also, self assessment and learning satisfaction were analyzed. The effectiveness of PBL presented in reflective journals were 'understanding of cooperative learning', 'related knowledge adaption', 'real experience', 'self-examination & changed self', 'problem solving ability'. Also students' self-assessment and learning satisfaction were very high in two PBL programs. However, they had difficulties in co-working and lack of time.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.9
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• pp.1682-1688
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• 2008

The Counterpropagation algorithm(CP) is a combination of Kohonen competition network as a hidden layer and the outstar structure of Grossberg as an output layer. CP has been used in many real applications for pattern matching, classification, data compression and statistical analysis since its learning speed is faster than other network models. However, due to the Kohonen layer's winner-takes-all strategy, it often causes instable learning and/or incorrect pattern classification when patterns are relatively diverse. Also, it is often criticized by the sensitivity of performance on the learning rate. In this paper, we propose an enhanced CP that has multiple Kohonen layers and dynamic controlling facility of learning rate using the frequency of winner neurons and the difference between input vector and the representative of winner neurons for stable learning and momentum learning for controlling weights of output links. A real world application experiment - pattern recognition from passport information - is designed for the performance evaluation of this enhanced CP and it shows that our proposed algorithm improves the conventional CP in learning and recognition performance.

• Journal of the Korean Geographical Society
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• v.49 no.4
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• pp.615-632
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• 2014

This study aims to explore 'bluffing', one of the most important topics in order to ensure the objectivity, validity, reliability of scoring of constructed-response items. The author identifies the conception of bluffing, and classifies major types of bluffing on the basis of previous studies on the theoretical level. Next, the author analyzes empirically the bluffing strategies and types of learners on key terms of Korean Geography subject. Compared with the existing research reports, the result of this study shows a significantly lower average bluffing score. On the other hand, it is consistent in results of previous studies reported that average bluffing score is similar between genders and that those students who got highest grades did least bluffing. Actually bluffing types are classified into four categories: 'repeating the question' type, 'depending on a well-known or existing knowledge' type, 'applying some basic concepts regardless of understanding' type, and 'inducing scorer's basic beliefs' type. Some comments and suggestions are as follows. First, it is necessary to continue researches of the relations among bluffing and age, gender, grade, intelligence and learning styles. Second, it is required for scorers who score constructed-response items to develop and supply the scoring guide including analysis contents of bluffing types and cases, and increase opportunity for training. Third, we need to inquire the domain-specific bluffing types in geography subject based on the generalizable sample size.

• Journal of Korea Game Society
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• v.12 no.5
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• pp.5-12
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• 2012

The information represented by graphic is preferred more than by text to the game generation familiar to computer games in the cognitive style. The learning to solve the math problems represented by graphic is significantly effective to improve learner's problem-solving power in math education. In this paper, we proposed a method of graphic representation of mathematical sentences for effective learning of the game generation. The proposed method arranges the unit informations in the logical structure and represent the logical interrelation between the informations by symbols, line segments, or arrows using the graphic elements with good visibility for the game generation to recognize easily and to understand accurately the logical meaning. The proposed method is able to represent accurately the math sentences until the detail level that appears the tense and the voice of the sentences differently from the previous graphic representation method's ability. The proposed method could be used as learning tools and used widely to represent graphically mathematical informations for the instructional scaffolding of an educational game in oder that the game generation could learn effectively.