• Proceedings of the KOR-KST Conference
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• 2001.02a
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• pp.101-132
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• 2001

• Korean Journal of Computational Design and Engineering
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• v.18 no.3
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• pp.155-166
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• 2013

We present recent human-vehicle interaction (HVI) research conducted in the area of defense and military application. Research topics discussed in this paper include: training simulation for overland navigation tasks; expertise effects in overland navigation performance and scan patterns; pilot's perception and confidence on an overland navigation task; effects of UAV (Unmanned Aerial Vehicle) supervisory control on F-18 formation flight performance in a simulator environment; autonomy balancing in a manned-unmanned teaming (MUT) swarm attack, enabling visual detection of IED (Improvised Explosive Device) indicators through Perceptual Learning Assessment and Training; usability test on DaViTo (Data Visualization Tool); and modeling peripheral vision for moving target search and detection. Diverse and leading HVI study in the defense domain suggests future research direction in other HVI emerging areas such as automotive industry and aviation domain.

• Educational Technology International
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• v.21 no.2
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• pp.125-153
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• 2020

The advancement of virtual reality technology offers various locomotion options that support users' navigation behaviors in a virtual reality environment. This study was aimed at examining the effects of two navigation methods-joystick-controlling and walking-around-on users' perceived usability, behavioral engagement, and virtual presence. Fifty South Korean college students were recruited in the study, and they were assigned randomly to one of the two navigation conditions. Participants from each group were asked to observe a 3D object and complete the surveys. They were then asked to repeat the procedure with a 2D image. Using repeated-measures ANOVAs and MANOVA, we found that users using joystick-controlling reported higher usability and showed superior performance to the walking-around group on two tasks. Participants reported a higher behavioral engagement when observing the 2D image. Besides, they perceived a significantly higher virtual presence when observing the 2D image. Finally, we discussed the implications of the findings for the navigation method design.

• Journal of Advanced Navigation Technology
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• v.14 no.6
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• pp.874-881
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• 2010

A automatic flight control system(AFCS) of UAS needs to control its flight path along target path exactly as adjusts flight coefficient itself depending on static or dynamic changes of airplane's features such as type, size or weight. In this paper, we propose system which tunes control gain autonomously depending on change of airplane's feature in flight as adding MLM(Machine Learning Module) on AFCS. MLM is designed with Linear Regression algorithm and Reinforcement Learning and it includes EvM(Evaluation Module) which evaluates learned control gain from MLM and verified system. This system is tested on beaver FDC simulator and we present its analysed result.

• Journal of Fisheries and Marine Sciences Education
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• v.11 no.1
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• pp.43-58
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• 1999

To instruct in accordance with learner's trait & preceding knowledge, letting the learner control the learning activities is the important task of educator & major goal of the Education Department this year. This article intends to provide useful Instructional Model for the teachers in fisheries marine high school, when they design the individualized teaching model using motivation. One of the major reason for the fisheries marine high school students' low learning achievement is due to the neglecting motivation elements in teaching - learning processes. Recently, with assistance of the information communication technology development, various teaching methods such as Individualized Multimedia Mediated Instruction, Internet Instruction, have come to the major method in activating motivation and computer-mediated instruction considering the learner's individual difference is the useful tools for the instructional efficiency. Because current navigation text book of fisheries marine high school have special characteristic considering the spacial context & time series from departing port to entering port, Teachers can maximize learner's learning accomplishment by using individualized multimedia & providing similar situation like a real navigation(simulating), representing this text characteristics. Thus this paper searches for the specifications of Keller's Motivation Model & Sweeter's Tutorial Model to solve instructional efficiency problems in fisheries marine high school & developed an efficient instructional design by integrating two models.

• Journal of Advanced Navigation Technology
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• v.25 no.6
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• pp.569-575
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• 2021

Deep learning shows differences in prediction performance depending on data quality and model. This study uses various input data and multiple deep learning models to build an optimal deep learning model for predicting solar radiation, which has the most influence on power generation prediction. did. As the input data, the weather data of the Korea Meteorological Administration and the clairvoyant meteorological image were used by segmenting the image of the Korea Meteorological Agency. , comparative evaluation, and predicting solar radiation by constructing multiple deep learning models connecting the models with the best error rate in each model. As an experimental result, the RMSE of model A, which is a multiple deep learning model, was 0.0637, the RMSE of model B was 0.07062, and the RMSE of model C was 0.06052, so the error rate of model A and model C was better than that of a single model. In this study, the model that connected two or more models through experiments showed improved prediction rates and stable learning results.

• Journal of The Korean Association of Information Education
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• v.7 no.1
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• pp.1-10
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• 2003

Web provides a rich learning environment for learners mainly due to the hypertext technology and the high interactivity. It provides a learner-centered learning environment. In this environment, students are to develop their own paths in non-sequential and flexible ways according to their needs and their demands. However, in many cases students who use this environment are easily exposed to difficulties in their choices of learning paths, disorientation, and cognitive overload in the cyberspace. Consequently, they have trouble in maintaining their motivation and interest in their learning. This study presents the design and the use of 3D-based space navigation system in order to maintain student's interest in educational web contents.

• Science of Emotion and Sensibility
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• v.13 no.1
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• pp.197-206
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• 2010

For an emotion retrieval system implementation to support pedestrian navigation, coordinating the pedestrian emotion model with the system user's emotion is considered a key component. This study proposes a new method for capturing the user's model that corresponds to the pedestrian emotion model and examines the validity of the method. In the first phase, a database comprising a set of interior images that represent hypothetical destinations was developed. In the second phase, 10 subjects were recruited and asked to evaluate on navigation and satisfaction toward each interior image in five rounds of navigation experiments. In the last phase, the subjects' feedback data was used for of the pedestrian emotion model, which is called ‘learning' in this study. After evaluations by the subjects, the learning effect was analyzed by the following aspects: recall ratio, precision ratio, retrieval ranking, and satisfaction. Findings of the analysis verify that all four aspects significantly were improved after the learning. This study demonstrates the effectiveness of the learning algorithm for the proposed pedestrian emotion model. Furthermore, this study demonstrates the potential of such pedestrian emotion model to be well applicable in the development of various mobile contents service systems dealing with visual images such as commercial interiors in the future.

• The Journal of Korean Association of Computer Education
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• v.4 no.1
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• pp.175-181
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• 2001

WBI provides new opportunities to realize the flexible learning environment based on hypermedia and to support distance learning with a diverse interaction. The instructors or learners in WBI claim to be able to resolve reluctant fluctuations such as disorientation and cognitive overload. To overcome these phenomena, a supplementary tool able to manage a learning space organized by the instructor's or learner's own way and offer effective navigation techniques is presented in this paper. A learning space management and navigation tool called HyperMap dynamically represents the learning space in the form of a two-dimensional labeled graph. This HyperMap also can be used for an instruction design tool, learners portfolio for the exchange of learning experiences, and the assessment of WBI.

• Journal of Advanced Navigation Technology
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• v.28 no.3
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• pp.262-271
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• 2024

In this paper, by applying deep learning, one of the A.I. techniques, through angle information, which is optical observation data generated when observing satellites at observatories, distance information from observatories is learned to predict range data, thereby increasing the precision of satellite's orbit determination. To this end, we generated observational data from GMAT, reduced the learning data error of deep learning through preprocessing of the generated observational data, and conducted deep learning through MATLAB. Based on the predicted distance information from learning, trajectory determination was performed using an extended Kalman filter, one of the filtering techniques for trajectory determination, through GMAT. The reliability of the model was verified by comparing and analyzing the orbital determination with angular information without distance information and the orbital determination result with predicted distance information from the model.