• 한국가정과교육학회지
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• 제21권2호
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• pp.45-60
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• 2009

본 연구는 중학교 기술 가정과 옷차림 단원을 위한 e-러닝 시스템을 구현함으로써 학습자의 흥미와 이해를 높여 보다 효과적인 교수 학습활동을 할 수 있게 하고 기술 가정 의생활 영역에 대한 e-러닝 개발의 기초자료가 되고자 하였다. 연구방법으로 구체적인 상황학습의 효과와 보다 현실감 있는 학습 환경을 제공하기 위해 학습내용을 학습자가 직접 클릭해서 조작할 수 있도록 구현하였고 학습자의 주의와 동기를 유발시킬 수 있도록 의류 쇼핑몰의 최신 의복자료를 이용하여 개성 있게 코디하는 방법 등을 제시하고 또래들의 패션 사진을 사례에 맞게 적절히 활용하였다. 연구의 결과를 요약하면 다음과 같다. 첫째, 시뮬레이션 조작과 가시적 관찰을 할 수 있는 학습 자료의 구현으로 보다 쉽게 학습목표에 도달할 수 있도록 하였다. 둘째, 텍스트 보다는 오디오와 이미지, 동영상 자료를 많이 사용하여 보다 효과적인 교수 학습 활동이 이루어지도록 하였다. 셋째, 옷차림 단원 학습은 특히 유행과도 관련이 있는데 멀티미디어가 갖는 현실감 있고 생동적인 교육 자료를 시의 적절하게 제공함으로써 e-러닝의 장점을 최대한 활용하였고 학습내용을 학습자 자신의 실생활과 관련된 사진이나 동영상으로 제시함으로써 학습자의 동기유발이 되도록 하였다. 이상과 같은 연구를 바탕으로 옷차림 단원의 학습에 있어 본 연구에서 사용한 저작도구 뿐 만 아니라 다양한 멀티미디어 저작도구를 활용한 e-러닝 콘텐츠 개발의 추가적 연구 활동과 풍부한 수업자료의 확보를 위한 교수 학습 자료의 DB 구축을 제언한다.

• 기술혁신연구
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• 제12권3호
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• pp.1-24
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• 2004

E-Learning is another way of teaching and learning. E-learning is a networked phenomenon allowing for instant revisions and distribution, and goes beyond training and instruction to the delivery of information and tools to improve performance. The benefits of e-learning are many, including cost-effectiveness, enhanced responsiveness to change, consistency, timely content, flexible accessibility, and providing customer value. The proponents of e-learning stress the importance of using communities of interest to support and enhance the learning process. They also emphasizes that people learn more effectively when they interact and are involved with other people participating in similar endeavors. Although the role of e-learning in higher education has significantly increased, the resistance to new technology by professors and lecturers in university and colleges worldwide remains high. The purpose of this study is to identify the determinants of attitude and planned behavior toward e-learning class in universities. A survey methodology was used to investigate a proposed model of influence, and structural equation modeling was used to analyze the results. The hypothesized model was largely supported by this analysis, and the overall results indicate that attitude toward e-learning systems is mostly influenced by the perceived ease of use as well as the level of perceived usefulness, where both factors are influenced by years of experiences in using cyber system and the technical support level. As in other TAM related research, it can be concluded that the perceived ease of use and perceived usefulness contribute to the future use of e-learning system.

• 대한치과기공학회지
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• 제40권3호
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• pp.163-172
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• 2018

Purpose: The research comprehends learning attitude level of Dental Technology Department students, searches variable element to affect and is trying to provide basic material of method arrangement to induce change of positive learning attitude. Methods: It was conducted survey 410 students, who understand purpose of the research, consentient to involve research, in universities which is located in Daegu area, Daejeon City, Gangwon province from Aug., 1stto Nov.,10th2017, Questionnaires were distributed to 410 students totally. it was finally analyzed 374 questionnaires except 36 questionnaires that answer was not sufficient. Results: The positive answer over 'Average (3)' among study attitude factors was presented highly in order of 'Targeting & Execution' (3.351). 'Effective Content Summary' (3.307), 'Study Plan' (3.173), 'Priority and Self-Management' (3.116), and 'Study Habit & Enhancement' (2.925) showed negative trend under average. The five sub-factors of learning attitude were examined according to general characteristics and there were statistically significant differences according to gender, grade, high school of origin, academic aptitude(p<0.01, p<0.001). Conclusion : As male students show more positive learning attitude than female students, we need to develop more special programs to encourage them. Meanwhile we also need to find out a motive to bring positive effect to change the academic aptitude and learning attitude of female students, or methods to improve their learning attitude in a complementary way by their high school, gender and grade.

• 한국군사과학기술학회지
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• 제23권4호
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• pp.337-345
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• 2020

The Weapon-Target Assignment(WTA) problem can be formulated as an optimization problem that minimize the threat of targets. Existing methods consider the trade-off between optimality and execution time to meet the various mission objectives. We propose a multi-agent reinforcement learning algorithm for WTA based on mean field game to solve the problem in real-time with nearly optimal accuracy. Mean field game is a recent method introduced to relieve the curse of dimensionality in multi-agent learning algorithm. In addition, previous reinforcement learning models for WTA generally do not consider weapon interference, which may be critical in real world operations. Therefore, we modify the reward function to discourage the crossing of weapon trajectories. The feasibility of the proposed method was verified through simulation of a WTA problem with multiple targets in realtime and the proposed algorithm can assign the weapons to all targets without crossing trajectories of weapons.

• The Journal of Asian Finance, Economics and Business
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• 제8권10호
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• pp.385-393
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• 2021

In an effort to find ways to increase the effectiveness of online education, literature and empirical study based on the Technology Acceptance Model (TAM) have addressed a variety of questions, including perceived ease of use (PEU) and perceived usefulness (PU). After TAM, extensive studies have focused on the impact of extrinsic factors on PEU and PU, including Self-efficacy and Perceived Risk. This study aims to analyze the direct, indirect, and moderating effects of Self-efficacy and Perceived Risk on Online Learning Intention (OLI). Data was collected through a survey method from 472 students studying at universities in Vietnam. The collected data was analyzed using the PLS-SEM technique to test the hypotheses. The findings reveal that Technology Self-Efficacy influences the intention to take online courses both directly and indirectly through Perceived Ease of Use and Perceived Usefulness. Besides, Perceived Risk COVID-19 also has a positive effect on online learning intention, and plays a role as a moderating variable on the impact of PU on OLI. These findings suggest that students will have a stronger intention to study online when they are confident in their ability to use technology. When they believe in their ability to use technology, their online learning intention will also increase.

• Journal of Information Processing Systems
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• 제15권5호
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• pp.1179-1191
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• 2019

We design an ingenious view-pooling method named learning-based multiple pooling fusion (LMPF), and apply it to multi-view convolutional neural network (MVCNN) for 3D model classification or retrieval. By this means, multi-view feature maps projected from a 3D model can be compiled as a simple and effective feature descriptor. The LMPF method fuses the max pooling method and the mean pooling method by learning a set of optimal weights. Compared with the hand-crafted approaches such as max pooling and mean pooling, the LMPF method can decrease the information loss effectively because of its "learning" ability. Experiments on ModelNet40 dataset and McGill dataset are presented and the results verify that LMPF can outperform those previous methods to a great extent.

• 디지털산업정보학회논문지
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• 제19권4호
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• pp.45-52
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• 2023

With the advent of deep learning, Artificial Intelligence (AI) technology has experienced rapid advancements, extending its application across various industrial sectors. However, the focus has shifted from the independent use of AI technology to its dispersion and proliferation through the open AI ecosystem. This shift signifies the transition from a phase of research and development to an era where AI technology is becoming widely accessible to the general public. However, as this dispersion continues, there is an increasing demand for the verification of outcomes derived from AI technologies. Causal AI applies the traditional concept of causal inference to AI, allowing not only the analysis of data correlations but also the derivation of the causes of the results, thereby obtaining the optimal output values. Causal AI technology addresses these limitations by applying the theory of causal inference to machine learning and deep learning to derive the basis of the analysis results. This paper analyzes recent cases of causal AI technology and presents the major tasks and directions of causal AI, extracting patterns between data using the correlation between them and presenting the results of the analysis.

• Current Optics and Photonics
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• 제8권3호
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• pp.270-281
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• 2024

Information-hiding technology is introduced into an optical ghost imaging encryption scheme, which can greatly improve the security of the encryption scheme. However, in the current mainstream research on camouflage ghost imaging encryption, information hiding techniques such as digital watermarking can only hide 1/4 resolution information of a cover image, and most secret images are simple binary images. In this paper, we propose an equal-resolution image-hiding encryption scheme based on deep learning and computational ghost imaging. With the equal-resolution image steganography network based on deep learning (ERIS-Net), we can realize the hiding and extraction of equal-resolution natural images and increase the amount of encrypted information from 25% to 100% when transmitting the same size of secret data. To the best of our knowledge, this paper combines image steganography based on deep learning with optical ghost imaging encryption method for the first time. With deep learning experiments and simulation, the feasibility, security, robustness, and high encryption capacity of this scheme are verified, and a new idea for optical ghost imaging encryption is proposed.

• 한국군사과학기술학회지
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• 제27권5호
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• pp.619-627
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• 2024

As AI technology advances, interest in performing multi-robot autonomous missions for manned-unmanned teaming (MUM-T) is increasing. In order to develop autonomous mission performance technology for multiple robots, simulation technology that reflects the characteristics of real robots and can flexibly apply various missions is needed. Additionally, in order to solve complex non-linear tasks, an API must be provided to apply multi-robot reinforcement learning technology, which is currently under active research. In this study, we propose the campaign model to flexibly simulate the missions of multiple robots. We then discuss the results of developing a simulation environment that can be edited and run and provides a reinforcement learning API including acceleration performance. The proposed simulated control module and simulated environment were verified using an enemy infiltration scenario, and parallel processing performance for efficient reinforcement learning was confirmed through experiments.

• 산경연구논집
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• 제5권2호
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• pp.5-12
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• 2014

Purpose - The purpose of this thesis is to assess the product design digital learning status of universities that are currently involved in learning environment projects in manufacture and commerce integration (MCI). Thus, enterprises must keep learning and creating new inventions with revolutionary progress. Research design, data, and methodology - This study not only emphasizes the analysis of technical ability, course concepts, conducting models, and learning environments of every aspect, but also systematically probes the planning of learning, system framework, web learning, environmental activities, data statistics, and digitalized learning, among other aspects. Results - The results of this study help in finally understanding each school's manufacture and commerce integration situation, in order to evaluate product design learning. Consequently, it is essential to evaluate computer learning at schools, thereby affecting communication and the requirements of business education training. Conclusions - It is essential to focus on MCI to promote web teaching to preserve and enhance knowledge disseminating technologies, and immediately share knowledge with learners, while improving work efficiency and cultivating the talent needed by industry.