• Journal of Information Processing Systems
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• v.16 no.3
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• pp.572-587
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• 2020

Experience API provides a learner-centered model for learning data collection and learning process recording. In particular, it can record learning data from multiple data sources. Therefore, Experience API provides very good support for ubiquitous learning. In this paper, we put forward the architecture of ubiquitous learning system and the method of reading the learning record from the ubiquitous learning system. We analyze students' learning behavior from two aspects: horizontal and vertical, and give the analysis results. The system can provide personalized suggestions for learners according to the results of learning analysis. According to the feedback from learners, we can see that this u-learning system can greatly improve learning interest and quality of learners.

• Journal of the Korea Society of Computer and Information
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• v.11 no.3
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• pp.221-229
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• 2006

Information communication technology ultimately pursues ubiquitous environment where people and devices are connected in networks and exchange of information are possible. However there have not been sufficient studies on the technology in spite of higher enthusiasm about education and remarkable educational potentials of ubiquitous technology. In order to effectively utilize the ubiquitous technology, this thesis explored field trip through a constructivism approach and examined ways how to use and integrate ubiquitous technology in developing educational model and system.

• IEMEK Journal of Embedded Systems and Applications
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• v.17 no.5
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• pp.289-296
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• 2022

In this paper, we developed a deep learning-based recyclable object detection model. The model is developed based on YOLOv5 that is a one-stage detector. The deep learning model detects and classifies the recyclable object into 7 categories: paper, carton, can, glass, pet, plastic, and vinyl. We propose two methods for recyclable object detection models to solve problems during training. Bounding Box CutMix solved the no-objects training images problem of Mosaic, a data augmentation used in YOLOv5. Standardized Distance-based IoU replaced DIoU using a normalization factor that is not affected by the center point distance of the bounding boxes. The recyclable object detection model showed a final mAP performance of 0.91978 with Bounding Box CutMix and 0.91149 with Standardized Distance-based IoU.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.9
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• pp.2031-2039
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• 2010

This article first defines the concept of ubiquitous learning, and then examine ways to design the educational environment for e-Learning and u-Learning. Next, identifies some disadvantages before seeking possible solutions. Finally, the article explores visions of how ubiquitous learning might look in the future. With the advent of information, communication and computer technologies, the needs and demands for ubiquitous learning are largely emerging, enabling students to easily access everything they want anytime, anywhere. In particular, the advance of high-speed broadband networks such as DMB, WiBro and WCDMA and the proliferation of portable digital devices including DMB, PDA and high-performance mobile phones will encourage the widespread adoption of u-Learning.

• International Journal of Contents
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• v.4 no.4
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• pp.18-23
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• 2008

With the development of information communication and network technologies, ubiquitous era that supports various services regardless of places and time has been advancing. The development of such technologies has a great influence on educational environments. As a result, e-learning concepts that learners use learning contents in anywhere and anytime have been proposed. The various learning contents authoring systems that consider the e-learning environments have also been developed. However, since most of the existing authoring systems support only PC environments, they are not suitable for various ubiquitous mobile devices. In this paper, we design and implement a contents authoring system based on learning activities for u-learning environments. Our authoring system significantly improves the efficiency for authoring contents and supports various ubiquitous devices as well as PCs.

• Proceedings of the Korean Society of Computer Information Conference
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• 2012.07a
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• pp.13-14
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• 2012

본 논문에서는 멀티 터치 테이블을 중심으로 u-Learning 시스템을 제안한다. 멀티 터치 테이블에서 수업 진행 중 교사는 모바일로 멀티 터치 테이블을 제어함으로써 수업을 진행 및 관리하고, 학생들은 마커를 이용하여 멀티 터치 테이블과의 인터랙션을 통해 웹과 자동화된 과제 시스템을 이용함으로써 능동적인 학습참여를 할 수 있게 된다.

• Journal of Digital Convergence
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• v.9 no.4
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• pp.281-289
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• 2011

This paper provides the emerging flow of new communication technology using ubiquitous learning (u-Learning). In the intelligent Ubiquitous environment, humans and devices with computing abilities become interoperable. u-Learning will lead students to open their minds to the world and motivate self-learning, which may lead them to learn and communicate more efficiently, and save time, cost and energy. Through case research, regarding education, learning attitude, custom and, personal relations, one must solve the fundamental issues of misuse and outflow problems regarding personal information that will be widely collected in detail than the present condition, and in order for this not to happen, further support of the law and system, plus ethical perspectives must be considered in order to progress.

• Journal of the Korea Computer Industry Society
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• v.6 no.5
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• pp.749-756
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• 2005

In the near future, we can access the information whenever we want, wherever we use because almost devices in ubiquitous environment are connected by either wired or wirelss networks. Especially, u-Learning which emphasizes on pedagogical property is enable to improve learning abilities. As researches of the previous u-Learning, there have been learning by mobile devices such as PDAs as well as the smart classroom which makes the remote students participate in the existing class. However, these researches have not satisfied pedagogical, cooperative and ubiquitous properties yet. Thus we suggest the framework for both local and mobile classroom, which can make the properties easy to satisfy.

• Journal of Internet Computing and Services
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• v.20 no.5
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• pp.79-86
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• 2019

This paper is an overview of key elements of Korea National Open University's smart mobile learning system, and an attempt to evaluate its main services relative to the FRAME model and the Mobile Learning Development Model for distance learning in higher education. KNOU improved its system architecture to one based on xMOOC e-learning content delivery while also upgrading its PC-based online/mobile learning services to facilitate an easier and more convenient access to lectures and for better interactivity. From the users' viewpoint, the upgraded 'U-KNOU Campus' allows for a more integrated search capability coupled with better course recommendations and a customized notification service. Using the new system, the students can access not only the school- and peer-issued messages via online bulletin boards but also share information and pose questions to others including to the school faculty/officials and system administrators. Additionally, a new mobile payment method has been incorporated into the system so that the students can select and pay for additional courses from anywhere. In spite of these advances, the issue of device usability and content development remain; specifically U-KNOU Campus needs to improve its instructor-learner and learner-to-learner interactivity and mobile evaluation interface.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.4
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• pp.251-260
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• 2022

Although the number of trees affected by pine wilt disease is decreasing, the affected area is expanding across the country. Recently, with the development of deep learning technology, it is being rapidly applied to the detection study of pine wilt nematodes and dead trees. The purpose of this study is to efficiently acquire deep learning training data and acquire accurate true values to further improve the detection ability of U-Net models through learning. To achieve this purpose, by using a filtering method applying a step-by-step deep learning algorithm the ambiguous analysis basis of the deep learning model is minimized, enabling efficient analysis and judgment. As a result of the analysis the U-Net model using the true values analyzed by period in the detection and performance improvement of dead pine trees of wilt nematode using the U-Net algorithm had a recall rate of -0.5%p than the U-Net model using the previously provided true values, precision was 7.6%p and F-1 score was 4.1%p. In the future, it is judged that there is a possibility to increase the precision of wilt detection by applying various filtering techniques, and it is judged that the drone surveillance method using drone orthographic images and artificial intelligence can be used in the pine wilt nematode disaster prevention project.