• Proceedings of the Korean Society of Computer Information Conference
• /
• 2014.01a
• /
• pp.327-332
• /
• 2014

본 논문에서는 Unity 3D 엔진을 이용하여 게임개발을 위한 학습용 앱의 구현 내용을 소개하였다. Unity 엔진을 이용하면 필드의 제작, 캐릭터 애니메이션 세팅, 스크립트 작성, Asset 관리, 레벨 디자인 등 많은 작업을 하나의 통합 환경에서 수행할 수 있다. 또한 컴파일 과정을 거치지 않아도 게임을 제작하는 도중 언제라도 실행해 볼 수 있기 때문에 개발에 걸리는 시간을 단축할 수 있다. 본 연구의 과정은 게임 앱 설계 관련 프로젝트의 수행이나 학습용 게임 개발의 학습 모형을 제시한 사례로 활용할 수 있다.

• Journal of Korea Game Society
• /
• v.21 no.3
• /
• pp.3-12
• /
• 2021

This study is a design study to develop the reading application for English learning courses with fun elements of Gamification incorporating user's immersion. The system is focusing on the story progression of Aesop's fable "Rabbit and Tortoise", which is consisted of chapters in digital technology. We intended to apply the four elements of fun factors by grafting Gamification into the game engine system. The purpose and significance of the study is to present the guideline through evaluation of usability from prototypes by surveying the educator group.

• Human Ecology Research
• /
• v.53 no.2
• /
• pp.219-228
• /
• 2015

This study evaluated the content of Korean vocabulary learning applications with a focus on tablet PC applications. We analyzed 51 Korean vocabulary learning applications. The instruments in this study were developed based on Yoo et al. (2012)' Vocabulary Learning Game Application Evaluation Criteria and Hyun et al. (2013)' Educational Application Evaluation Criteria. Data were analyzed using a t-test and one-way analysis of variance. The main results are as follows. First, each criteria's score was fairly good; the ease of use had the highest scores and the amusement had the lowest scores. Second, there was a significant difference in the interaction by vocabulary teaching approach. Applications based on a whole language-teaching method had higher scores than applications based on a phonics instructional teaching method inducing more operation and with immediate feedback. Third, there was significant difference in the sum of score and each criteria of developmental appropriateness, educational values, amusement, function and interaction by type of learning. Applications of combining type had higher scores in every criteria except for ease of use than applications of description type. These findings provide a preliminary evidence that the systematic Korean vocabulary learning application facilitates preschoolers' vocabulary learning.

• Journal of Elementary Mathematics Education in Korea
• /
• v.17 no.2
• /
• pp.285-299
• /
• 2013

Problem posing activity of which a learner reinterprets an original problem via a new problem suggested, is a learning method which encourages an active participation and approves self-directed learning ability of the learner. Especially gifted students need to get used to a creative attitude to modify or reinterpret various mathematical materials found in everyday usual lives creatively in steady manner via such empirical experience beyond the question making level of the textbook. This paper verifies the possibility of lesson on question making strategy utilization for creativity development of gifted class, and analyzes various cases of students' trials to modify the rules of a board game called Rummikub in application of their own mathematics after learning What-If-Not strategy.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2011.04a
• /
• pp.447-450
• /
• 2011

This paper shows the application of P-N Learning [4] method in the soccer ball detection and improvement for increasing the speed of processing. In the P-N learning, the learning process is guided by positive (P) and negative (N) constraints which restrict the labeling of the unlabeled data, identify examples that have been classified in contradiction with structural constraints and augment the training set with the corrected samples in an iterative process. But for the long-view in the soccer game, P-N learning will produce so many ferns that more time is spent than other methods. We propose that color histogram of each frame is constructed to delete the unnecessary details in order to decreasing the number of feature points. We use the mask to eliminate the gallery region and Line Hough Transform to remove the line and adjust the P-N learning's parameters to optimize accurate and speed.

• Journal of Korea Game Society
• /
• v.7 no.2
• /
• pp.91-100
• /
• 2007

The purpose of this study is to develope a criterion for evaluation on game-style courseware by the application of HCI theory. The HCI theory, which deals with principles or methods for developing systems people can use conveniently and pleasantly, has been applied to overall area of program development. And it also has been widely used to evaluate learning programs. However, there have been few studies on a game-style courseware evaluation on the basis of the HCI theory. Thus, it is necessary to apply the HCI theory to studies on the game-style courseware evaluation. This paper shows that evaluation criteria are developed on three viewpoint bases : usefulness, usability, and affect which are as elements in HCI. The evaluation criteria developed in this paper can be applied to a basis for evaluation on game-style coursewares.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.17 no.3
• /
• pp.754-774
• /
• 2023

Wrestling is one of the popular events for modern sports. It is difficult to quantitatively describe a wrestling game between athletes. And deep learning can help wrestling training by human recognition techniques. Based on the characteristics of latest wrestling competition rules and human recognition technologies, a set of wrestling competition video analysis and retrieval system is proposed. This system uses a combination of literature method, observation method, interview method and mathematical statistics to conduct statistics, analysis, research and discussion on the application of technology. Combined the system application in targeted movement technology. A deep learning-based facial recognition psychological feature analysis method for the training and competition of classical wrestling after the implementation of the new rules is proposed. The experimental results of this paper showed that the proportion of natural emotions of male and female wrestlers was about 50%, indicating that the wrestler's mentality was relatively stable before the intense physical confrontation, and the test of the system also proved the stability of the system.

• Korean Journal of Construction Engineering and Management
• /
• v.15 no.1
• /
• pp.20-27
• /
• 2014

Construction safety training has mostly relied on one-way transference of instructors' knowledge to trainees through traditional media such as textbooks and lecture slides. However, safety knowledge could be more effectively acquired in experiential situations. The authors proposed a serious game to provide a comprehensive safety training environment. Trainees who assume the roles of safety inspectors in the game explore a virtual construction site to identify potential hazards and learn from the contents of feedback created by the game as a result of trainees' input. The paper reports details of the game design and development process. The test results indicated that trainees were motivated to refresh their safety knowledge, increased their learning interests, and enjoyed the learning process. In addition, trainees showed positive attitudes towards using the game scoring as a way of evaluating their safety knowledge. The test results encouraged the continuous development of the game.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.9 no.10
• /
• pp.4177-4190
• /
• 2015

Current research on Internet of Things (IoT) has primarily addressed the means to enhancing smart resource allocation, automatic network operation, and secure service provisioning. In particular, providing satisfactory security service in IoT systems is indispensable to its mission critical applications. However, limited resources prevent full security coverage at all times. Therefore, these limited resources must be deployed intelligently by considering differences in priorities of targets that require security coverage. In this study, we have developed a new application of Cognitive Radio (CR) technology for IoT systems and provide an appropriate security solution that will enable IoT to be more affordable and applicable than it is currently. To resolve the security-related resource allocation problem, game theory is a suitable and effective tool. Based on the Blotto game model, we propose a new strategic power allocation scheme to ensure secure CR communications. A simulation shows that our proposed scheme can effectively respond to current system conditions and perform more effectively than other existing schemes in dynamically changeable IoT environments.

• Proceedings of the Korea Inteligent Information System Society Conference
• /
• 2001.01a
• /
• pp.59-64
• /
• 2001

The robot soccer simulation game is a dynamic multi-agent environment. In this paper we suggest a new reinforcement learning approach to each agent's dynamic positioning in such dynamic environment. Reinforcement learning is the machine learning in which an agent learns from indirect, delayed reward an optimal policy to chose sequences of actions that produce the greatest cumulative reward. Therefore the reinforcement learning is different from supervised learning in the sense that there is no presentation of input pairs as training examples. Furthermore, model-free reinforcement learning algorithms like Q-learning do not require defining or learning any models of the surrounding environment. Nevertheless it can learn the optimal policy if the agent can visit every state- action pair infinitely. However, the biggest problem of monolithic reinforcement learning is that its straightforward applications do not successfully scale up to more complex environments due to the intractable large space of states. In order to address this problem. we suggest Adaptive Mediation-based Modular Q-Learning (AMMQL)as an improvement of the existing Modular Q-Learning (MQL). While simple modular Q-learning combines the results from each learning module in a fixed way, AMMQL combines them in a more flexible way by assigning different weight to each module according to its contribution to rewards. Therefore in addition to resolving the problem of large state effectively, AMMQL can show higher adaptability to environmental changes than pure MQL. This paper introduces the concept of AMMQL and presents details of its application into dynamic positioning of robot soccer agents.