• Science of Emotion and Sensibility
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• v.20 no.3
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• pp.119-130
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• 2017

The purpose of the study is discovering the effects of virtual competitors on user in AR (Augment Reality) home training system. Specifically, the current research examined their effects on immersion, perceived competition, and leaning motivation. The paper tested three unexplored relationship. First, introducing virtual competitors in home training system will enhance user's immersion. Second, presenting virtual competitors in home training system will increase user's perceived competition. Third, virtual competitors in home training system will raise user's learning motivation. For empirical analysis, we developed home training system, which could check and give feedback automatically, based on user's posture. Using this AR home training system, the study empirically shows how and why virtual competitors affect users. The results give implications not only on service design; but also on the idea that virtual other could affect user's behavior.

• The Journal of Korea Robotics Society
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• v.14 no.2
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• pp.122-130
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• 2019

Collecting a rich but meaningful training data plays a key role in machine learning and deep learning researches for a self-driving vehicle. This paper introduces a detailed overview of existing open-source simulators which could be used for training self-driving vehicles. After reviewing the simulators, we propose a new effective approach to make a synthetic autonomous vehicle simulation platform suitable for learning and training artificial intelligence algorithms. Specially, we develop a synthetic simulator with various realistic situations and weather conditions which make the autonomous shuttle to learn more realistic situations and handle some unexpected events. The virtual environment is the mimics of the activity of a genuine shuttle vehicle on a physical world. Instead of doing the whole experiment of training in the real physical world, scenarios in 3D virtual worlds are made to calculate the parameters and training the model. From the simulator, the user can obtain data for the various situation and utilize it for the training purpose. Flexible options are available to choose sensors, monitor the output and implement any autonomous driving algorithm. Finally, we verify the effectiveness of the developed simulator by implementing an end-to-end CNN algorithm for training a self-driving shuttle.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2002.11a
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• pp.193-196
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• 2002

Successful rehabilitation with respect to the activities of daily living (ADL) requires accurate and effective assessment and training. A number of studies have emphasized the requirement for rehabilitation methods that are both relevant to the patients real world environment, and that can also be transferred to other daily living tasks. Virtual reality (VR) has a many advantage over other ADL rehabilitation techniques, and offers the potential to develop a human performance testing and training environment. Therefore, in this study, the virtual supermarket was developed and the possibility of using a VR system to assess and train cognitive ability in ADL investigated. This study demonstrates that, VR technology offers great promise in the field of ADL training.

• Journal of Digital Convergence
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• v.14 no.11
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• pp.357-367
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• 2016

In this study, we examined the impact on balance ability and jump performance of soccer players with functional ankle instability using virtual reality based neuromuscular posture control fusion training. Soccer players were divided into 15 people of virtual reality-based neuromuscular posture control fusion training group and 15 people of common treadmill training group and performed for 30 minutes three times a week for 8 weeks. In order to evaluate the balance of ability, using biorescue, it measured surface area, whole path length, limit of stability. In order to measure jump performance, it measured counter movement jump with arm swing and standing long jump. The results showed the statistically significant difference in the balance comparison of surface area, whole path length, limited of stability and the jump performance comparison of counter movement jump with arm swing, standing long jump. As a result, virtual reality-based neuromuscular posture control fusion training was found to be more effective to improve its balance ability and jump performance than common treadmill training.

• The Journal of Korean Physical Therapy
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• v.26 no.6
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• pp.430-435
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• 2014

Purpose: The objective of this study was a virtual reality-based balance training program effective for improvement in physical function, examined the balance ability and fall efficacy of elderly women with experienced falls, intending to examine the program's usefulness as an exercise program to prevent the recurrence of a fall. Methods: The participants were 30 elderly women aged 65 or older who met the conditions. The participants were randomly assigned to either a balance training group (BT) or a virtual reality-based balance training group (VT) and received the training three times per week, 30 minutes per day, for six weeks. To measure static balance, the Tetrax Portable Multiple System (Tetrax Ltd, Israel) were used. To measure dynamic balance, the Berg Balance Scale (BBS) and functional reach test (FRT) was used, and regarding fall efficacy, the Korean Fall Efficacy Scale (K-FES) was used. Results: Tetrax significantly improved after the intervention in both the BT group and the VT group (p<0.05). The comparison between the two groups was not significantly. BBS and FRT result significantly improved after the intervention in both the BT and VT groups (p<0.001), while K-FES was significantly ameliorated in the VT group only (p<.05). Comparing the groups, there were more significant changes in the BBS (p<0.05) and FRT (p<0.01) result of the VT group than the BT group. Conclusion: A virtual reality-based balance training program is considered to be usable as an exercise program to prevent recurrence of falls in elderly women.

• The Journal of Korean Physical Therapy
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• v.21 no.2
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• pp.31-38
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• 2009

Purpose: This study was examined the effect of training using a Virtual Reality System on the sitting balance and Activities of Daily Living for patients with a spinal cord injury. Methods: The subjects were divided into an experimental (6 persons) and control group (5 persons). The experimental group trained the 5 programs, three times per week for 6 weeks using the Virtual Reality System and five days for week using conventional physical therapy. The control group trained five days for a week using conventional physical therapy. Results: The difference in the mean Spinal Cord Independence Measurement (SCIM) score in the experimental and control groups was increased to 8.33 and 6.60 (p=0.79), respectively. The difference in the mean functional reaching test in experimental and control group increased to 4.21 and 1.09 (p=0.25), respectively. The difference in the mean sitting time in experimental and control group increased to 41.05 and 10.33 (p=0.66), respectively. There was a difference in the mean of all variances but these differences were not statistically significant. Conclusion: These results suggest that training using the Virtual Reality System increased the SCIM, functional reaching test and sitting time in people with a spinal cord injury.

• ETRI Journal
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• v.44 no.2
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• pp.327-338
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• 2022

Classification models for human action recognition require robust features and large training sets for good generalization. However, data augmentation methods are employed for imbalanced training sets to achieve higher accuracy. These samples generated using data augmentation only reflect existing samples within the training set, their feature representations are less diverse and hence, contribute to less precise classification. This paper presents new data augmentation and action representation approaches to grow training sets. The proposed approach is based on two fundamental concepts: virtual video generation for augmentation and representation of the action videos through robust features. Virtual videos are generated from the motion history templates of action videos, which are convolved using a convolutional neural network, to generate deep features. Furthermore, by observing an objective function of the genetic algorithm, the spatiotemporal features of different samples are combined, to generate the representations of the virtual videos and then classified through an extreme learning machine classifier on MuHAVi-Uncut, iXMAS, and IAVID-1 datasets.

• Korean Journal of Computational Design and Engineering
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• v.19 no.4
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• pp.423-433
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• 2014

For the proper decision making and responsibility enhancement for an unexpected accident in large-scale facilities, it is important to train operators or first responders to minimize potential human errors and consequences resulted from them. Simulation technologies, including human-computer interaction and virtual reality, enables personnel to participate in simulated hazardous situations with a safe, interactive, repetitive way to perform these training activities. For the development of accident response training simulator, it is necessary to define components comprising the simulator and to integrate them for the given training purpose. In this paper, we analyze requirements of the training simulator, derive key components, and design the training simulator. Based on the design, we developed a prototype training simulator and verified the simulator through experiments.

• Journal of the Korea Computer Graphics Society
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• v.26 no.3
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• pp.111-121
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• 2020

Realistic training contents utilizing intensive immersion of virtual reality are being used in various fields such as industry, education, and medical care. High-risk, high-cost education training, in particular, is difficult to conduct in reality, but it can be applied with the latest virtual reality technology that enhances educational effectiveness by efficiently and safely experiencing it in an environment similar to reality. This study introduces a management system that systematically manages realistic virtual training contents and visualizes training results in schematic pictures based on defined evaluation elements. The management system can store the information generated from the content in the database and manage the training records of each trainee in a practical way. In addition, a content-based scenario can be created in multiple scenarios by setting training goals, number of participants, and methods for applying evaluation elements. This paper describes the management system's production method and the results based on the virtual reality training content as an application example.

• Journal of the Korea Safety Management & Science
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• v.2 no.2
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• pp.21-28
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• 2000

In the real environment, it is not easy to get the effective training or to simulate several hazard situations for safety because of the direct exposure to the hazards of the actual system. But the virtual environment(VE) can help the users to get the effective training or to simulate all kind of possible situations without the exposure to the harzards of the actual system. Therefore, the number of virtual reality(VR) application for safety will be increased dramatically in the future. This paper proposes a category of VR applications and also the steps to develope the VE for emergency management.