• Journal of Digital Contents Society
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• v.18 no.3
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• pp.499-508
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• 2017

With the recent advance of IT technology and the change of education paradigm, vocational training has been also evolved. In the background of mobilization of learning, increase of bite-size contents, and the agility of just-in-time learning, this study surveyed the online learners' motivation, perceptions, and learning behaviour. Total 4,021 learners from 6 distance learning institutions revealed that learners take the e-learning courses due to more for their self-development than the company's supports and policy. Also, they perceived the subject matter in contents are the most important. The results from this study suggest that the development of contents should focus on the subject matter that can be utilized for their jobs immediately. Lastly, the study confirms that learning space and time has been changed in the flexible way to use their spare time between work and life. Irregularity of learning and hasty preparations were one of major characteristics in the aspect of learning behaviour.

• Journal of Digital Convergence
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• v.13 no.9
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• pp.361-368
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• 2015

This research aimed to investigate the effects of neurofeedback training on unilateral neglect and depression in patients with stroke. Fourteen of the subjects were selected from the experimental group and the control group respectively; the following results were obtained. First, experimental group and the control group presented significant statistical difference before and after intervention on neglect. However, there is after intervention no significant statistical among them. Two, experimental group and the control group presented significant statistical difference before and after intervention on depression, and the experimental group demonstrated more decrease than the control group in depression. The results obtained from this research expect us that applying the neurofeedback training for the improvement of neglect and depression, to stroke patients has a positive effect on the rehabilitation of patients.

• Journal of Korea Multimedia Society
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• v.23 no.1
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• pp.15-23
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• 2020

Recently, the increase in the elderly population due to an aging society has led to a relative increase in senile diseases such as vascular dementia or Alzheimer's disease, and the social burden for rehabilitation has increased. In addition, studies have been conducted for the risk assessment and prevention of musculoskeletal disorders. The purpose of this study is to suggest a system that can be used to help with dementia prevention training by tracking the movement of motion and virtual reality contents for the risk factors of musculoskeletal disorders of the elderly. We propose a training method for preventing dementia through musculoskeletal motion analysis algorithm and virtual reality content. Through motion recognition algorithm based on motion region design, we will track and analyze the moving radius of the target joint. The purpose of this study is to calculate and evaluate scores based on the time to accomplish the goals on virtual reality contents for the prevention of musculoskeletal disorders and the support of dementia prevention training, and the degree of difficulty, and to analyze the correlation between the results of performing K-MMSE and VR contents.

• Journal of the Korean Society for Nondestructive Testing
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• v.13 no.2
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• pp.11-19
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• 1993

It is very essential to get the accurate classification of defects in primary pressure vessel weld for the safety of nuclear power plant. The signal analysis using the digital signal processing and pattern recognition is performed to classify UT defects extracting feature vector from ultrasonic signals. The minimum distance classifier and the maximum likelihood classifier based on statistics were applied in this experiment to discriminate ultrasonics data obtained form both the training specimens (slit, hole) and the testing specimens(crack, slag). The classification rate was measured using pattern classifier. Results of this study show the promise in solving the many flaw classification problems that exist today.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.12
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• pp.5087-5102
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• 2015

Rapid popularization of smart cell phone equipped with camera has led to a number of new legal and criminal problems related to multimedia such as digital image, which makes cell phone source identification an important branch of digital image forensics. This paper proposes a classifier combination based source identification strategy for cell phone images. To identify the outlier cell phone models of the training sets in multi-class classifier, a one-class classifier is orderly used in the framework. Feature vectors including color filter array (CFA) interpolation coefficients estimation and multi-feature fusion is employed to verify the effectiveness of the classifier combination strategy. Experimental results demonstrate that for different feature sets, our method presents high accuracy of source identification both for the cell phone in the training sets and the outliers.

• Journal of Digital Convergence
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• v.18 no.1
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• pp.357-368
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• 2020

This study evaluated soccer-specific fitness early and late season to check the conditioning status of K3 league soccer players. Evaluation factors included body composition, agility, quickness, endurance and isokinetic limb muscle strength. As a result, the factors that showed improvement in the late season were skeletal muscle mass, agility and quickness, and body composition, endurance and isokinetic limb muscle strength were not different from each other. The factors that showed improvement in the second half of the season are thought to be due to the learning effect of repetitive training, competition participation during the season. Lastly, endurance and lower extremity strength did not show improvement in the second half of the season due to the fact that no specific training was performed during the season. Taken together, it is necessary to periodically check the fitness status of athletes to develop and apply a fitness training program suitable for competition, transition and preparation period.

• Journal of Digital Convergence
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• v.14 no.8
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• pp.319-329
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• 2016

This study aimed to identify nurses' participation motivation, its influence factors, and their job training need. A survey was conducted on 345 nurses of general hospitals in Gyeonggi-do. Data was collected from October 5th to 18th, 2016 and was analyzed through t-test, ANOVA, Bonferroni post-test, and multiple regressions using SPSS 21.0. Participation motivation was high in 'expertise capability improvement and development' and low in personal gain and job stability. Job training need was the highest in nosocomial infection management and CPR and was the lowest in hospice and rehabilitation nursing. Participation motivation had significant differences depending on age, marital status, educational level, and clinical experience, and was influenced by the job training need of professional nursing and medical knowledge for disease treatment. Therefore, it is necessary to plan medical educational programs to enhance job training effectiveness, establish a strategy to increase participation motivation; and expand various job training support.

• Journal of Korea Multimedia Society
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• v.20 no.2
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• pp.420-428
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• 2017

In recent trends, the first age of digital device usage has been significantly getting low and the using frequencies for younger generation have been gradually increasing. Also, while there were more negative opinions of this trend in the past, the new idea is changing to more needs of training and approaches for children's sound using guidelines for digital device. In fact, people believe the new generation will face more advanced future, called the Fourth Industrial Revolution. The purpose of the paper is first to explain about the Jacques Lacan's concept of desire theory in order to understand the human's unconscious level through His desire theory. Second, the paper identifies how this unconscious level is affected to ethical aspects of new generations whose unconscious level are frequently and early exposed to digital media. Lastly, the paper will present the necessity of digital literacy education as well as future direction. Furthermore, the paper review for what is the ethics and positive guidelines of digital media for children who will become the future citizens in the era of the Fourth Industrial Revolution.

• Journal of Digital Convergence
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• v.13 no.10
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• pp.541-548
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• 2015

The purpose of this study was to examine the effect of Side walking training on the balance (Functional Gait Assessment; FGA, Timed Up & Go Test; TUG) and gait (10 meter Walking Test; 10 mWT) of stroke patients. 28 stroke patients were randomly allocated to an experimental group(side walking Training) and control group(forward walking training) of 14 patients each. both groups received rehabilitative physical therapy for during 4 weeks. The experimental group was asked to participate in Side walking training for 20 minutes per day 3 times per week during 4 weeks. The control group was asked to participate in forward walking training for 20 minutes per day 3 times per week during 4 weeks. There were significantly increase by side walking training in outcome of the balance from the FGA was increase from 16.86 score to 18.64 score(p<.05), TUG was decrease from 26.03 sec to 22.43 sec(p<.05) and 10 mWT was decrease from 21.90 sec to 19.10 sec(p<.05), Therefore side walking training is to promote balance and gait in stroke patients will be able to offer useful training.

• Journal of Biomedical Engineering Research
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• v.30 no.2
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• pp.153-161
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• 2009

Mammogram is one of the important techniques for mass detection, which is the early diagnosis stage of a breast cancer. Especially, the CAD(Computer Aided Diagnosis) using mammogram improves the working performance of radiologists as it offers an effective mass detection. There are two types of CAD systems using mammogram; automatic and semi-automatic CAD systems. However, the automatic segmentation is limited in performance due to the difficulty of obtaining an accurate segmentation since mass occurs in the dense areas of the breast tissue and has smoother boundaries. Semi-automatic CAD systems overcome these limitations, however, they also have problems including high FP (False Positive) rate and a large amount of training data required for training a classifier. The proposed system which overcomes the aforementioned problems to detect mass is composed of the suspected area selection, the level set segmentation and SVM (Support Vector Machine) classification. To assess the efficacy of the system, 60 test images from the FFDM (Full-Field Digital Mammography) are analyzed and compared with the previous semi-automatic system, which uses the ANN classifier. The experimental results of the proposed system indicate higher accuracy of detecting mass in comparison to the previous systems.