• Journal of Biomedical Engineering Research
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• v.28 no.4
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• pp.461-470
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• 2007

Human can learn how to shape their brain electrical activity in a desired direction through continuous feedback of the electroencephalogram (EEG), and this technique is known as Neurofeedback (or EEG biofeedback), which has been used since the late 1960s in clinical applications. In this study, a portable wireless EEG (named wEEG) has been designed and implemented, which consists of a mobile station (a wireless two-channel EEG acquisition device) and a base station (a bridge between mobile station and computer). Moreover, a SensoriMotor Rhythm (SMR) training system was also implemented with the wEEG for enhancing attention with virtual environment. Experiment results based on 16 volunteers' (8 females and 8 males, average age is $27{\pm}4$) were reported in this paper. The results show that the SMR ratio of 87.5% subjects increased about 0.7% in training status than that in the stable status. With the proposed system, many training protocol scan be designed easily and can be done at home in our daily life conveniently. Additionally, the proposed system will be useful for disabled and aged people.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.46 no.2
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• pp.19-26
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• 2009

This paper studies on the recognition rate change with respect to illumination variance and the confidence level of PCA(Principal Component Analysis) based face recognition by measuring the cumulative match score of CMC(Cumulative Match Characteristic). We studied on the confidence level of the algorithm under illumination changes and selection of training images not only by testing multiple training images per person with illumination variance and single training image and but also by changing the illumination conditions of testing images. The experiment shows that the recognition rate drops for multiple training image case compared to single training image case. We, however, confirmed the confidence level of the algorithm under illumination variance by the fact that the training image which corresponds to the identity of testing image belongs to upper similarity lists regardless of illumination changes and the number of training images.

• International conference on construction engineering and project management
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• 2020.12a
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• pp.137-145
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• 2020

Providing safety training to construction workers is essential to reduce safety accidents at the construction site. With the prosperity of visualization technologies, Immersive Virtual Reality (IVR) has been adopted for construction safety training by providing interactive learning experiences in a virtual environment. Previous research efforts on IVR-based training have found that the level of fidelity of interaction between real and virtual worlds is one of the important factors contributing to the sense of presence that would affect training performance. Various interactive devices that link activities between real and virtual worlds have been applied in IVR-based training, ranging from existing computer input devices (e.g., keyboard, mouse, joystick, etc.) to specially designed devices such as high-end VR simulators. However, the need for high-fidelity interactive devices may hinder the applicability of IVR-based training as they would be more expensive than IVR headsets. In this regard, this study aims to understand the impact of the level of fidelity of interactive devices in the sense of presence in a virtual environment and the training performance during IVR-based forklift safety training. We conducted a comparative study by recruiting sixty participants, splitting them into two groups, and then providing different interactive devices such as a keyboard for a low fidelity group and a steering wheel and pedals for a high-fidelity group. The results showed that there was no significant difference between the two groups in terms of the sense of presence and task performance. These results indicate that the use of low-fidelity interactive devices would be acceptable for IVR-based safety training as safety training focuses on delivering safety knowledge, and thus would be different from skill transferring training that may need more realistic interaction between real and virtual worlds.

• Journal of Korea Multimedia Society
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• v.6 no.4
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• pp.668-675
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• 2003

Now a days many industries and bigger organisation (Indian Railways, Bharat Heavy Electricals Ltd.) are facing difficulties in implementing the new technology because of non-availability of fully trained staff. Also for the employed technical and other staff lot of resistance management has to face to get them trained for adoption of new technology. There are also very less organisations who can design effective training programmes and at the same time develop course material specially multimedia packages and computer base training (CBT) which can satisfy the need of different target groups of industries. Indian Railways was also facing similar situation while implementing the Air Brake System technology In Indian Railways. TTTI Bhopal took that challenge and designed, developed and trained Indian Railways trainer for implementation of the package on different target group. The present paper offers a case study on the same.

• International Journal of Computer Science & Network Security
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• v.24 no.4
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• pp.135-140
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• 2024

The main purpose of the study is to determine the key aspects of the use of electronic educational resources in the training of future specialists in higher education institutions. The importance of using electronic educational resources in the preparation of university students is proven. The relevance of the chosen topic is due to the high rise of globalization in the process of training future specialists in higher education institutions. The theoretical and methodological basis of the article is the fundamental and modern provisions of the theory, the work of scientists and specialists in the management of electronic educational resources in the field of education. Based on the results of the analysis, the main characterizing aspects of the use of electronic educational resources in the training of future specialists in higher education institutions were identified. Further research needs to analyze new, experimental electronic means in the system of student training.

• International Journal of Computer Science & Network Security
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• v.24 no.8
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• pp.21-31
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• 2024

This study investigates the user experience (UX) of first aid training using virtual reality (VR) technology. As VR continues to be adopted for educational and training purposes, it is important to understand how learners perceive and engage with this medium for developing critical skills, such as first aid. In this study, we developed a VR application called "VR First Aid" that includes training modules on three emergency scenarios: heatstroke, shock, and seizure. The application has both tutorial and hands-on training components. We conducted a UX study by administering a questionnaire to participants. The UX of learning through the VR application was then compared to using a traditional e-book format. Results indicate that participants perceived stronger internal behavior control with the e-book but reported better confirmation, engagement, enjoyment, and intention to use when training with the VR system. Gender differences were also explored, revealing that female participants expressed greater interest in learning through the VR platform compared to male participants. These findings provide insights into the strengths and limitations of VR-based first aid training compared to traditional methods. Implications for the design and deployment of VR training systems are discussed, with a focus on optimizing the learner experience and learning outcomes.

• Journal of Advanced Navigation Technology
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• v.16 no.2
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• pp.264-270
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• 2012

e-Training focusing on the experience and practice accelerates actual-active learning and enforces the learning effects against the existing theory based education. The most typical hans-on training system is augmented reality. Especially, in the training field installed augmented reality system, the automobile maintenance trainee experiences effective training with the immediate information, which is indicating the location of parts and the procedure of repairing. The tracking is the core technology of the augmented reality system. The performance of augmented reality system depends on the tracking technology. Therefore, this paper suggests the tracking technology which is proper to the e-Training augmented reality service technology for the car mechanics.

• Journal of IKEEE
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• v.22 no.4
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• pp.948-952
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• 2018

Haze removal is an object of scientific desire due to its various practical applications. Existing algorithms are founded upon histogram equalization, contrast maximization, or the growing trend of applying machine learning in image processing. Since machine learning-based algorithms solve problems based on the data, they usually perform better than those based on traditional image processing/computer vision techniques. However, to achieve such a high performance, one of the requisites is a large and reliable training database, which seems to be unattainable owing to the complexity of real hazy and haze-free images acquisition. As a result, researchers are currently using the synthetic database, obtained by introducing the synthetic haze drawn from the standard uniform distribution into the clear images. In this paper, we propose the enhanced equidistribution, improving upon our previous study on equidistribution, and use it to make a new database for training machine learning-based haze removal algorithms. A large number of experiments verify the effectiveness of our proposed methodology.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.3
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• pp.490-493
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• 2021

This paper proposes an embedded system that detects mask and face recognition based on a microprocessor instead of Nvidia Jetson Board what is popular development kit. We use a class of efficient models called Mobilenets for mobile and embedded vision applications. MobileNets are based on a streamlined architechture that uses depthwise separable convolutions to build light weight deep neural networks. The device used a Maix development board with CNN hardware acceleration function, and the training model used MobileNet_V2 based SSD(Single Shot Multibox Detector) optimized for mobile devices. To make training model, 7553 face data from Kaggle are used. As a result of test dataset, the AUC (Area Under The Curve) value is as high as 0.98.

• Journal of Korea Multimedia Society
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• v.17 no.1
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• pp.1-7
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• 2014

Hippocampus is an important part of brain which is related with early memory storage and spatial navigation. By observing the anatomy of hippocampus, some brain diseases effecting human memory (e.g. Alzheimer, schizophrenia, etc.) can be diagnosed and predicted earlier. The diagnosis process is highly related with hippocampus segmentation. In this paper, hippocampus segmentation using Active Shape Model, which not only works based on image intensity, but also by using prior knowledge of hippocampus shape and intensity from the training images, is proposed. The results show that ASM is applicable in segmenting hippocampus from whole brain MR image. It also shows that adding more images in the training set results in better accuracy of hippocampus segmentation.