• 한국실천공학교육학회논문지
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• 제3권1호
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• pp.69-75
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• 2011

본 논문에서는 유비쿼터스 컴퓨팅 환경에 기반을 둔 e-러닝 모델을 제안하였다. 이를 위해 국내외 대학의 진보된 e-러닝 시스템을 조사 및 분석하였으며, 이를 근간으로 유비쿼터스 환경에 기반을 둔 최적의 e-러닝 모델을 제안하였다. 제안한 모델은 최적의 e-러닝 하드웨어 및 소프트웨어, 그리고 다양한 e-러닝 서비스를 포함하고 있다. 여기에는 출결체크 서비스, 수업운영 서비스, 공용지식 서비스, 성적처리 서비스, 편의시설 서비스, 개인운영 서비스, 신용조회 서비스, 캠퍼스안내 서비스, 강의실운영 서비스 등이 있다. 또한, 실험.실습에 관련된 서비스도 포함하고 있다.

• 서비스연구
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• 제6권4호
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• pp.47-57
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• 2016

오픈소스는 스마트폰의 등장과 함께 놀라운 확산을 하고 있다. 이러닝 분야의 오픈소스인 Moodle 학습관리시스템은, 상용프로그램인 Blackboard를 제외하고 전 세계적으로 가장 많이 사용되고 있는 학습관리시스템이다. 그 이유 중 하나는 교육공학의 이론적 기초가 되며, 이러닝의 핵심 원칙이라 할 수 있는 구성주의 원칙에 따른, 협동학습과 상호작용이 잘 지원되도록 설계되어, 높은 교육적 효과와 장점을 가지기 때문이다. 본 연구에서는 오픈소스인 Moodle 학습관리시스템을 이용한 협동학습 운영 사례를 중심으로, 사용자의 협동학습을 지원하는 구체적 내용을 소개하고, 사례를 통하여 나타난, Moodle 학습관리시스템 협동학습의 장점과 특이점을 살펴본다. 연구 결과 PC와 스마트폰 환경에서 동시에 구현된, Moodle 학습관리시스템의 팀 프로젝트 협동학습을 통하여, 협동학습의 재미와 유용성을 확인하고, 학습자체의 중요성을 넘어 관계의 중요성이 학습자의 협동학습동기를 유발시킨다는 것을 사례를 통하여 확인할 수 있다.

• International Journal of Contents
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• 제12권4호
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• pp.8-16
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• 2016

This research proposes the composition logic of an Active Learning Environment (ALE), to enable discovery by learning through experience, whilst increasing knowledge about modern architectural heritage. Linking information to the historical heritage using Information and Communication Technology (ICT) helps to overcome the limits of previous learning methods, by providing rich learning resources on site. Existing field trips of cultural heritages are created to impart limited experience content from web resources, or receive content at a specific place through humanities Geographic Information System (GIS). Therefore, on the basis of the blended space theory, an augmented space experience method for overcoming these shortages was composed. An ALE space framework is proposed to enable discovery through learning in an expanded space. The operation of ALE space is needed to create full coordination, such as a Content Management System (CMS). It involves a relation network to provide knowledge to the rule engine of the CMS. The application is represented with the Deoksugung Palace Seokjojeon hall example, by describing a user experience scenario.

• The Journal of Asian Finance, Economics and Business
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• 제8권8호
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• pp.637-645
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• 2021

Mobile devices have become attractive learning devices for education. The digitalization of the higher education system in Sri Lanka by 2020 is part of the government's effort to modernize and enhance the country's overall education system particularly in view of the COVID-19 pandemic. Theoretically, this study contributes to the M-Learning model in higher education institutions via the integration of literature on technology adoption (TAM and UTAUT) with the variables of Perceived Usefulness, Perceived Ease of Use, Attitude, Effort Expectancy, Social Influence, and Facilitating Condition. The attitude towards M-Learning amongst higher education students was gauged via an online questionnaire survey. The convenience sample comprised 344 students from the Advanced Technological Institutes (ATI) in Batticaloa District, Sri Lanka. Descriptive statistics, a measurement, and structural model, and hypotheses testing were used to analyze the derived data. The findings indicate that mobile learning is significantly affected by perceived ease of use, social influence, effort expectancy, and facilitating condition, but negatively affected by attitude and perceived usefulness. The exhaustive literature review revealed that there are very few M-Learning studies related to digital learning in the context of higher education in the Batticaloa district.

• 지식경영연구
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• 제15권2호
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• pp.67-88
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• 2014

This study aims to investigate on measuring the success of e-Learning. For this purpose, we proposed a research model that consists of e-Learning contents quality, e-Learning system quality, e-Lecturing quality, sense of e-Learning community factors as independent factors and e-Learning and e-Learning satisfaction as mediators and tested it empirically based on the structural equation model. The empirical results showed that e-Learning contents quality, e-Learning system quality, sense of e-Learning community factors directly lead to e-Learning. The study also found that e-Learning contents quality, e-Lecturing quality, sense of e-Learning community factors bring about higher e-Learning satisfaction and that e-Learning satisfaction has a positive impact on e-Learning. Furthermore, the research discovered that both e-Learning and e-Learning satisfaction have a significant relationship with e-Learning net benefits. This research renders its theoretical contribution to analyzing a positive influence of sense of e-Learning community, a newly suggested variable added to the existing IS success model in this study, on e-Learning. From a practical view, the findings of this study can lead to improving the quality of e-Learning in today's era where the growth of e-Learning industry is quite noticeable.

• 한국경영과학회:학술대회논문집
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• 대한산업공학회/한국경영과학회 1994년도 춘계공동학술대회논문집; 창원대학교; 08월 09일 Apr. 1994
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• pp.611-616
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• 1994

Developing the safety training program has been a major research topic in CBT as well as in traditional teaching and learning. With regard to determining learning control in CBT, it is important to consider not only the characteristics of learning tasks but also student's individual difference. In this regard, the purposes of this study are to develop the CBT program as well as animation program in order to increase the student's performance.

• International Journal of Computer Science & Network Security
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• 제24권4호
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• pp.87-106
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• 2024

Vehicle-to-Home (V2H) and Home Centralized Photovoltaic (HCPV) systems can address various energy storage issues and enhance demand response programs. Renewable energy, such as solar energy and wind turbines, address the energy gap. However, no energy management system is currently available to regulate the uncertainty of renewable energy sources, electric vehicles, and appliance consumption within a smart microgrid. Therefore, this study investigated the impact of solar photovoltaic (PV) panels, electric vehicles, and Micro-Grid (MG) storage on maximum solar radiation hours. Several Deep Learning (DL) algorithms were applied to account for the uncertainty. Moreover, a Reinforcement Learning HCPV (RL-HCPV) algorithm was created for efficient real-time energy scheduling decisions. The proposed algorithm managed the energy demand between PV solar energy generation and vehicle energy storage. RL-HCPV was modeled according to several constraints to meet household electricity demands in sunny and cloudy weather. Simulations demonstrated how the proposed RL-HCPV system could efficiently handle the demand response and how V2H can help to smooth the appliance load profile and reduce power consumption costs with sustainable power generation. The results demonstrated the advantages of utilizing RL and V2H as potential storage technology for smart buildings.

• 디지털산업정보학회논문지
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• 제11권1호
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• pp.135-144
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• 2015

This study aims to propose an evaluation model that enables cooperative learning using e-Learning system. Even if the teacher and the student are not in the same place at the same time, the team project deliverable submitted by the student to the online system can be viewed by the teacher, enabling the teacher to assess the student not only based on the project but also in many other aspects. The proposed e-learning cooperative learning model allows the development of assessment factors, using such factors in assessment of the student's activities which are performed through the e-learning system, and the feedback of the results to the student so that the student is further motivated for learning. The teacher performs a comprehensive assessment of such factors, which is considered in conjunction with the student's assessment. Implementing the cooperative learning model proposed in this study in various e-learning systems such as Moodle is expected to motivate the student for learning, produces better cooperative learning results, provides greater convenience of assessment to the teacher, and improves fairness of assessment by showing the student's activities in real time.

• 디지털산업정보학회논문지
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• 제17권3호
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• pp.9-15
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• 2021

In this paper, the Embedded MEMS system to the power apparatus used Edge Impulse machine learning tools and therefore an improved predictive system design is implemented. The proposed MEMS embedded system is developed based on nRF52840 system and the sensor with 3-Axis Digital Magnetometer, I2C interface and magnetic measurable range ±120 uT, BM1422AGMV which incorporates magneto impedance elements to detect magnetic field and the ARM M4 32-bit processor controller circuit in a small package. The MEMS embedded platform is consisted with Edge Impulse Machine Learning and system driver implementation between hardware and software drivers using SensorQ which is special queue including user application temporary sensor data. In this paper by experimenting, TensorFlow machine learning training output is applied to the power apparatus for analyzing the status such as "Normal, Warning, Hazard" and predicting the performance at level of 99.6% accuracy and 0.01 loss.

• 국제학술발표논문집
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• The 9th International Conference on Construction Engineering and Project Management
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• pp.277-283
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• 2022