• Journal of Convergence for Information Technology
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• v.9 no.2
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• pp.108-114
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• 2019

In this paper, we propose an intelligent vocabulary recommendation agent that automatically provides vocabulary corresponding to game-based learners' needs and requirements in the mobile education augmented reality game environment. The proposed agent reflects the characteristics of mobile technology and augmented reality technology as much as possible. In addition, this agent includes a vocabulary reasoning module, a single game vocabulary recommendation module, a battle game vocabulary recommendation module, a learning vocabulary list Module, and a thesaurus module. As a result, game-based learners' are generally satisfied. The precision of context vocabulary reasoning and thesaurus is 4.01 and 4.11, respectively, which shows that vocabulary related to situation of game-based learner is extracted. However, In the case of satisfaction, battle game vocabulary(3.86) is relatively low compared to single game vocabulary(3.94) because it recommends vocabulary that can be used jointly among recommendation vocabulary of individual learners.

• International Journal of Computer Science & Network Security
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• v.22 no.7
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• pp.268-282
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• 2022

One of the most important technologies today is augmented reality technology, it allows users to experience the real world using virtual objects that are combined with the real world. This technology is interesting and has become applied in many sectors such as the shopping and medicine, also it has been included in the sector of education. In the field of education, AR technology has become widely used due to its effectiveness. It has many benefits, such as arousing students' interest in learning imaginative concepts that are difficult to understand. On the other hand, studies have proven that collaborative between students increases learning opportunities by exchanging information, and this is known as Collaborative Learning. The use of multimodal creates a distinctive and interesting experience, especially for students, as it increases the interaction of users with the technologies. The research aims at developing collaborative framework for developing achievement of 6th graders through designing a framework that integrated a collaborative framework with a multimodal input "hand-gesture and touch", considering the development of an effective, fun and easy to use framework with a multimodal interaction in AR technology that was applied to reformulate the genetics and traits lesson from the science textbook for the 6th grade, the first semester, the second lesson, in an interactive manner by creating a video based on the science teachers' consultations and a puzzle game in which the game images were inserted. As well, the framework adopted the cooperative between students to solve the questions. The finding showed a significant difference between post-test and pre-test of the experimental group on the mean scores of the science course at the level of remembering, understanding, and applying. Which indicates the success of the framework, in addition to the fact that 43 students preferred to use the framework over traditional education.

• Journal of Advanced Navigation Technology
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• v.15 no.6
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• pp.1047-1052
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• 2011

Various services are created using mobile networks after mobile devices such as smart phones and tablet PCs are propagated rapidly. However, the contents of smart devices are not enough diversity because they depend on games and messaging services primarily. In this paper, we described the study have progressed based on mobile devices and networks using augmented reality technologies about virtual education system.

• Journal of Korea Multimedia Society
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• v.21 no.1
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• pp.69-76
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• 2018

Augmented Reality (AR) technology has rapidly been applied to various application areas including e-learning and e-education. Focusing on the design and development of android tablet application, this study targeted to develop infant music education using AR technology. We used a tablet instead of personal computer because it is more easily accessible and more convenient. Our system allows infant users to play with teaching aids like blocks or puzzles to mimic musical play like game. The user sets the puzzle piece on the playground in front of the tablet and presses the play button. Then, the system extracts a region of interest among the images acquired by internal camera and separates the foreground image from the background image. The block recognition software analyzes, recognizes and shows the result using AR technology. In order to have reasonably working recognition ratio, we did experiments with more than 5,000 frames of actual playing scenarios. We found that the recognition rate can be secured up to 95%, when the threshold values are selected well using various condition parameters.

• Korean Journal of Computational Design and Engineering
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• v.15 no.5
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• pp.375-382
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• 2010

As the workers are getting old, they need to be expert in their fields. Expertise is an invaluable means of shipbuilding industries because of the technological advancements. Therefore, the workers have to attend training seminars and upgrade their technical knowledge. In shipbuilding industries, most workers operate transporters based on experience not on learning from specialization in the shipyard. It is needed for the workers of transporters to be educated technical manual and system. Thus, this research shows that educational system which is interactive and very effective with Augmented Reality(AR) for the non-specialist workers. The educational interactive system based on AR is very supportive and worth for the workers. This study considers the system which makes the workers reduce malfunction of the products and mistakes.

• Journal of Information Technology Applications and Management
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• v.24 no.3
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• pp.51-61
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• 2017

The objective of the study is to examine the acceptance and usability of Augmented Reality (AR) visuals developed for industry analysis of Thai Banks and whether these visuals can outperform the table of numbers in representing financial accounting data. Convenient samples were used and the data were collected with self-assessed questionnaires from 109 users with minimum prior experiences with financial analyses. The results from descriptive statistics indicates that despite having over 80% of respondents with little prior experience in analyzing financial performance of banking industry, the majority of them were able to correctly make prediction (96.4%), identify trend (82.6%) and compare banks' performance (70.6%). Their attitudes and perception towards Bank-AR visuals were above average. Although the overall usability score is average (53%), the respondents rated the Bank-AR visuals to be highly useful and had high intention to use them in the future.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.05a
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• pp.617-620
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• 2010

최근 증강현실(Augmented Reality)에 대한 관심이 증대되고, 이와 관련된 기술들이 발전함에 따라서 증강현실이 다양한 분야에 적용하려는 시도가 늘어나고 이에 대한 활용에도 기대가 모아지고 있다. 본 논문에서는 증강현실을 이용하여 유아용 학습 콘텐츠를 제작하고 구현하였다. 구현한 콘텐츠는 가상세계와 실제세계의 정확한 상호작용을 위하여 도서의 표지에 있는 마커에 유아에게 친숙한 캐릭터를 띄우므로 집중력을 높임과 동시에 학습보조자가 원활하게 콘텐츠를 사용할 수 있도록 하였다. 또한 콘텐츠의 페이지마다 여러 마커를 동시에 두어 콘텐츠의 일부분이 장애물에 의해 가려지더라도 원활한 마커 인식을 할 수 있도록 하였고 상황에 맞게 3D 모델(2D, 동영상 포함)이 증강되는 동시에 사운드가 재생되도록 하여 학습에서의 현존감과 몰입을 높여 학습효과를 극대화하는 결과를 얻을 수 있도록 제작하였다.

• Journal of Information Processing Systems
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• v.17 no.2
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• pp.242-252
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• 2021

Following the intuition that the local information in time instances is hardly incorporated into the posterior sequence in long short-term memory (LSTM), this paper proposes an attention augmented mechanism for fault diagnosis of the complex chemical process data. Unlike conventional fault diagnosis and classification methods, an attention mechanism layer architecture is introduced to detect and focus on local temporal information. The augmented deep network results preserve each local instance's importance and contribution and allow the interpretable feature representation and classification simultaneously. The comprehensive comparative analyses demonstrate that the developed model has a high-quality fault classification rate of 95.49%, on average. The results are comparable to those obtained using various other techniques for the Tennessee Eastman benchmark process.

• Educational Technology International
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• v.20 no.2
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• pp.137-168
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• 2019

This study examined the effects of information volume and distribution on learners' cognitive load and recall in a mobile augmented reality (AR) environment. Information volume refers to the degree of information users are provided in a learning task, while information distribution indicates the way in which information is distributed, either in a virtual or real format. Sixteen undergraduate students participated in the study, which employed a 2 × 3 randomized block factorial design with repeated measures. Information volume and distribution were independent variables, and factors in learners' cognitive load (mental effort, perceived ease of use, and perceived task difficulty) and recall test scores were the dependent variables. Information volume had significant main effects on perceived ease of use and task difficulty, and recall test scores, while information distribution had significant main effects on perceived task difficulty and test scores. A detailed discussion and implications are provided.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.28 no.4
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• pp.847-857
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• 2018

As the number of malicious code increases steeply, cyber attack victims targeting corporations, public institutions, financial institutions, hospitals are also increasing. Accordingly, academia and security industry are conducting various researches on malicious code detection. In recent years, there have been a lot of researches using machine learning techniques including deep learning. In the case of research using Convolutional Neural Network, ResNet, etc. for classification of malicious code, it can be confirmed that the performance improvement is higher than the existing classification method. However, one of the characteristics of the target attack is that it is custom malicious code that makes it operate only for a specific company, so it is not a form spreading widely to a large number of users. Since there are not many malicious codes of this kind, it is difficult to apply the previously studied machine learning or deep learning techniques. In this paper, we propose a method to classify malicious codes when the amount of samples is insufficient such as targeting type malicious code. As a result of the study, we confirmed that the accuracy of 97% can be achieved even with a small amount of data by applying the Memory Augmented Neural Networks model.