• Journal of The Korean Association of Information Education
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• v.13 no.1
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• pp.23-30
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• 2009

In this study, we proposed a pre-service teacher training program that assists efficiently the conceptual comprehension and teaching skill development of computer science education. The program is integrated with Protype Theory and Example Theory based on cognitive psychology. And also the real teaching activities based on Unplugged Learning are provided for conceptual comprehension of computer science education as well as for learning computer science. This program was applied to 31 pre-service teachers for one semester. The results show that this program is very effective for pre-service teacher training of computer science education.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.3
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• pp.958-979
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• 2023

Due to laws, regulations, privacy, etc., between 70-90 percent of providers do not share medical data, forming a "data island". It is essential to collaborate across multiple institutions without sharing patient data. Most existing methods adopt distributed learning and centralized federal architecture to solve this problem, but there are problems of resource heterogeneity and data heterogeneity in the practical application process. This paper proposes a collaborative deep learning modelling method based on the blockchain network. The training process uses encryption parameters to replace the original remote source data transmission to protect privacy. Hyperledger Fabric blockchain is adopted to realize that the parties are not restricted by the third-party authoritative verification end. To a certain extent, the distrust and single point of failure caused by the centralized system are avoided. The aggregation algorithm uses the FedProx algorithm to solve the problem of device heterogeneity and data heterogeneity. The experiments show that the maximum improvement of segmentation accuracy in the collaborative training mode proposed in this paper is 11.179% compared to local training. In the sequential training mode, the average accuracy improvement is greater than 7%. In the parallel training mode, the average accuracy improvement is greater than 8%. The experimental results show that the model proposed in this paper can solve the current problem of centralized modelling of multicenter data. In particular, it provides ideas to solve privacy protection and break "data silos", and protects all data.

• Journal of Acupuncture Research
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• v.40 no.1
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• pp.44-52
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• 2023

Background: Previous studies have investigated technology-aided needling training systems for acupuncture on phantom models using various measurement techniques. In this study, we developed and validated a vision-based needling training system (noncontact measurement) and compared its training effectiveness with that of the traditional training method. Methods: Needle displacements during manipulation were analyzed using OpenCV to derive three parameters, i.e., needle insertion speed, needle insertion angle (needle tip direction), and needle insertion length. The system was validated in a laboratory setting and a needling training course. The performances of the novices (students) before and after training were compared with the experts. The technology-aided training method was also compared with the traditional training method. Results: Before the training, a significant difference in needle insertion speed was found between experts and novices. After the training, the novices approached the speed of the experts. Both training methods could improve the insertion speed of the novices after 10 training sessions. However, the technology-aided training group already showed improvement after five training sessions. Students and teachers showed positive attitudes toward the system. Conclusion: The results suggest that the technology-aided method using computer vision has similar training effectiveness to the traditional one and can potentially be used to speed up needling training.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.254-257
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• 2009

In this paper, we propose a learning-based super-resolution algorithm. In the proposed algorithm, a multi-resolution wavelet approach is adopted to perform the synthesis of local high-frequency features. To obtain a high-resolution image, wavelet coefficients of two dominant LH- and HL-bands are estimated based on wavelet frames. In order to prepare more efficient training sets, the proposed algorithm utilizes the LH-band and transposed HL-band. The training sets are then used for the estimation of wavelet coefficients for both LH- and HL-bands. Using the estimated high frequency bands, a high resolution image is reconstructed via the wavelet transform. Experimental results demonstrate that the proposed scheme can synthesize high-quality images.

• Physical Therapy Rehabilitation Science
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• v.2 no.1
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• pp.7-11
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• 2013

Objective: Final goal of nerve advancement therapy is to provide maximum ability to function independently in life to patients. This paper appraises and describes basic concepts of the virtual reality (VR) based exercise program to improve functional movement for neurologically impaired patients. Design: Review article. Methods: Stroke patients from the physical therapy department while wearing comfortable clothing receive therapy and also VR based motion therapy administered by the therapist in charge. After evaluation of stroke patients, therapy includes an exercise program that is suitable for use with stroke patients; stroke patients wear head-mounted display while in front of the computer, where the camera is located; they follow the action on the screen and the computer perceives the operation of the stroke patients according to subject accomplishment. Results: According to obstacle condition of stroke patients using the method, which is various environments after setting, in stroke patients, there is a possibility of presenting suitable therapeutic environments. The display presentation of the method, which is identical, causes difficulty for all stroke patients. According to subject accomplishment; stroke patients result in execution of repetition training and deepening study, which leads to mobility. Conclusions: The VR based rehabilitation training programs is a difference of the existing video training program, is immediate feedback and compensation method. It will provide rehabilitation training services for the family of the patient whose condition could be improved with rehabilitative therapy where it is a continuous circumstance as a matter of the social welfare facility therapy.

• Journal of Korea Entertainment Industry Association
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• v.13 no.6
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• pp.277-286
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• 2019

The aim of this study was to investigate the effects of computer-based cognitive rehabilitation and traditional cognitive training on the working memory and executive function of patients with mild traumatic brain injury. The sample consisted of 20 patients with mild traumatic brain injury who had received rehabilitation treatment in a rehabilitation unit. The subjects were assigned to either the experimental (n = 10) or control group (n = 10). The experimental group received computer-based cognitive rehabilitation and traditional cognitive training for 60 minutes, whereas the control group received only traditional cognitive training for 60 minutes. Both the groups received their respective interventions for 60 minutes a day and 5 times per week across a period of 4 weeks. Working memory and executive function were assessed using the digit span test (forward and backward), visual memory 1 and 2 of the Motor-free Visual Perception Test-3, trail making test, and Stroop test (A and B) both before and after the intervention. The experimental group showed a significantly greater improvement in visual memory and performance on the Stroop test A than the control group. These findings suggest that computer-based cognitive rehabilitation and traditional cognitive training are more effective in promoting positive changes in the working memory and executive function of individuals with mild traumatic brain injury than traditional cognitive training.

• International Journal of Computer Science & Network Security
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• v.22 no.11
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• pp.115-120
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• 2022

The main purpose of the study is to identify the key aspects of the use of innovative distance learning technologies in the training of biology students. Currently, there is a modernization, the evolution of the education system from a classical university to a virtual one, from lecture material teaching to computer educational programs, from a book library to a computer one, from multi-volume paper encyclopedias to modern search databases. During studies in higher education, distance learning ensures the delivery of information in an interactive mode through the use of information and communication technologies. The main disadvantage of distance learning is the emotional interaction of the teacher with students. It is necessary to increase the level of methodological developments for independent studies of students. The methodology includes a number of theoretical methods. Based on the results of the study, the main elements of the use of innovative distance learning technologies in the training of biology students were identified.

• Journal of the Korea Computer Graphics Society
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• v.24 no.3
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• pp.83-92
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• 2018

In this paper, we propose a system to a criminal profiling simulation training and assessment with virtual reality technology. Profiling has emerged as the incidence of violent crime has increased by 45.2 % in the country over the past decade. However, the number of profilers in Korea is 36, due to the problem of existing courses. "Criminal Reproduction Learning" is the common way to profiling training, but there are numerous constraints that prevent practical training. Thus, the system used virtual reality technology to overcome existing constraints. Users can receive simulation training and assessment of profiling at crime scene that have been implemented as virtual reality, with an immersive experience through interaction. We expect this system to contribute to the activation of profiling education in many institutions and to the development of good profilers with diverse training.

• 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.