• The Journal of Korean society of community based occupational therapy
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• v.8 no.3
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• pp.69-76
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• 2018

Objective : The study was to investigate the neurophysiological approach to the effect of complex exercise on memory, one of brain functions, and the degree of sleep disorder using experimental animals with sleep disorders. Methods : This study carried out a complex exercise that designed in an animal laboratory for 4 days to 16 sleep - disordered model rats. After the exercise, brain function was confirmed with the changes of BDNF in the hippocampus and the change of sleep level was confirmed with the concentration of melatonin in the blood. Results : First, the effect of the complex exercise program on brain function was significantly increased in the experimental group(p<0.01). Second, the effect of complex exercise program on sleep disturbance was significantly increased in the experimental group and control group(p<0.01)(p<0.05). Conclusion : The rate of increase of the elderly in the community is rapidly increasing, and the sleep disorder of the elderly can affect the quality of life of these elderly people. Secondary memory impairment due to sleep disturbances can also be a problem. Although there are many ways to improve sleep disturbance, it has been scientifically proven through experimental animals that sleep and memory can be improved with complex exercise that is not economically, spatially burdensome.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.29 no.3
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• pp.491-501
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• 2019

In side-channel analysis, which exploit physical leakage from a cryptographic device, deep learning based attack has been significantly interested in recent years. However, most of the state-of-the-art methods have been focused on classifying side-channel information in a profiled scenario where attackers can obtain label of training data. In this paper, we propose a new method based on deep learning to improve non-profiling side-channel attack such as Differential Power Analysis and Correlation Power Analysis. The proposed method is a signal preprocessing technique that reduces the noise in a trace by modifying Auto-Encoder framework to the context of side-channel analysis. Previous work on Denoising Auto-Encoder was trained through randomly added noise by an attacker. In this paper, the proposed model trains Auto-Encoder through the noise from real data using the noise-reduced-label. Also, the proposed method permits to perform non-profiled attack by training only a single neural network. We validate the performance of the noise reduction of the proposed method on real traces collected from ChipWhisperer board. We demonstrate that the proposed method outperforms classic preprocessing methods such as Principal Component Analysis and Linear Discriminant Analysis.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.1
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• pp.184-188
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• 2019

The purpose of this paper is to investigate the effectiveness of Google Classroom (GC) and to examine the satisfaction of professors using GC as an online environment at a Mongolian University. Fourteen professors designed the lecture model and provided lessons using GC at D University for four weeks. GC provides new learning opportunities that are more efficient than face-to-face learning, because it can overcome the limitations of time and space. The results of the survey conducted with the professors who participated in the class to explore the effectiveness of GC show that the system provides: cooperation: 100% (strongly agree=7, Agree=7), personal learning opportunity: 100% (strongly agree=10, Agree=4), ease in learning: 100% (strongly agree=11, Agree=3), suitability: 100% (strongly agree=8, Agree=6), feedback opportunities: 100% (strongly agree=7, Agree=7), connection: 100% (strongly agree=7, Agree=7), accessibility: 100% (strongly agree=7, Agree=7), learning effectiveness: 100% (strongly agree=9, Agree=5), paperless experience: 100% (strongly agree=8, Agree=6). The professors who attended the class reacted positively to the use of GC, proving that the application of GC at this Mongolian University was appropriate and efficient. The use of GC is expected to help educational institutions strengthen and improve online learning, especially by breaking from traditional learning, and opening new paths for professors and students in Mongolia.

• The Journal of the Korea Contents Association
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• v.19 no.2
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• pp.619-628
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• 2019

This study is an explanatory research conducted to analyze the influencing factors of treatment adherence in kidney transplant recipients. The subjects were 132 renal transplant recipients who visited the outpatient department in a university hospital. Data were collected from July 17, 2017, to August 22, 2017, and analyzed using SPSS WIN 24.0. Frequency, percentage, mean and standard deviation, variance analysis, correlation, and regression analysis were performed. The results of the study showed that there was a significant difference in the treatment adherence based on the age, religion, and the time passed since kidney transplantation. The study also found that the treatment adherence had significant positive correlations with social support (r=.54, p<.001), family support (r=.43, p<.001), health provider's support (r=.57, p<.001), and self-care knowledge (r=.21, p=.015). The factors influencing the treatment adherence were health provider's support, the time passed since kidney transplantation, spouse, and religion. The final explanatory power of the model was 41.9%. In conclusion, intervention strategies should be introduced to promote the support of healthcare providers in order to improve the adherence of the kidney transplantation patients.

• 한국노년학
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• v.37 no.3
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• pp.527-547
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• 2017

The purpose of this study is to investigate how depression, death anxiety, and social support can exert influence on the psychological well-being of elderly living alone through a parameter of resilience. A survey was conducted involving 988 elderly over the age of 65 living alone in the Daejeon metropolitan area and Chungcheongnam-do and the data were analyzed using structure equation model. The results were as follows. First, in the measurement of variables according to demographic characteristics, depression showed significant differences depending on gender, level of education, health, and financial condition, while death anxiety differed depending on gender, and level of education. Social support was significantly different by gender, age, level of education, region, health, and financial condition. The level of resilience was significantly different by gender, age, level of education, health, and financial condition. Psychological well-being varied according to gender, level of education, health, and financial condition. Second, the effects of depression, death anxiety and social support on psychological well-being were examined. It was found that depression had a negative influence and social support had a positive impact while death anxiety showed no influence. Third, with regard to the effects of depression, death anxiety, social support on resilience, depression was found having negative influence, whereas social support having positive influence. Forth, psychological well-being was positively affected by resilience. Also, through the mediated pathway of resilience, their psychological well-being seemed to totally improve when the negative factors were reduced and the positive ones promoted. This study may have some significance in reference to examine the factors affecting the psychological well-being of elderly living alone and to develop social welfare service programs and policies in the field.

• Journal of Climate Change Research
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• v.2 no.2
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• pp.115-131
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• 2011

Out of all the possible actions that can be taken to respond to greenhouse gas reduction, including development of greenhouse gas reduction technology, infrastructure, actions to improve energy saving and efficiency, and offset with carbon emission reductions (CERs), this study shall focus on the investment on CERs. This study will take a look at risks involved with investing in CERs such as UN registration refusal risk and CERs price fluctuation, and will design risk management model which shall be verified. The goal of this paper is to provide optimized CERs investment strategies for different types of investors, such as general trading companies seeking for investment opportunities and financial companies with plans for green products development and investment by preparation for carbon market. It is expected that the global competitiveness of domestic financial companies shall be improved by taking actions on carbon market instead of previous passive response to climate change and that Korea, the number two Carbon Emissions supplier and number one derivatives market in terms of volume, shall be able to lead the worldwide carbon market.

• Korean Journal of Family Social Work
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• no.55
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• pp.91-128
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• 2017

The purpose of this study is to develop an effective intervention strategy for marriage migrant woman in family therapy. For this purpose, we collected counseling cases of professional counselors who successfully completed counseling and attempted the qualitative analysis of treatment intervention strategies and effects. The results of the study were obtained by dividing the meaning units in the immigrant woman's statements made during the counseling process composed of a total of 6 sessions. The counselors were analyzed to have tried the following intervention strategies. They attempted the following six strategies: Helping emotional differentiation by searching for unresolved emotional problems, dealing with undifferentiation due to family projection process and love triangle, dealing with multi-generational transfer process of the original family relationship patterns and coping mechanism, shedding lihgt on ineffectiveness of inconsistent communication due to emotional oppression applying a communication model of MRI, switching client's awareness through reorganization, suggesting a way of communication that leads to real self. Such counselors' attempts resulted in positive changes and treatment effects were found to include first, cognitive insights and motivation for change, second, improved communication skills and third, anxiety reduction and self-differentiation. Due to their husbands' refusal to participate in counseling, marriage migrant women often get involved in counseling alone, so they tend to worry that the effectiveness of family therapy may be low but it was found that the proper intervention of the counselor could improve the ability of the wife to resolve conflicts, which would be a great help in solving problems such as family violence and this study is meaningful in that it provided the appropriate therapeutic intervention strategies needed.

• Journal of Digital Convergence
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• v.16 no.12
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• pp.1-10
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• 2018

For local festivals to be successful, it is important to cooperate with various entities and effectively utilize festival-related resources. Recently, many efforts have been made to improve the operation and management performance of local festivals in Korea, but systematic management and IT support have been insufficient. In this study, the factors affecting the IT governance of local festivals were derived through a literature review and the relationship to the festival performance was analyzed empirically. A survey was conducted with local festival organizers and stake holders, and the research model was verified using the regression analysis with total 109 samples. According to the results of the analysis, it was confirmed that marketing, processes and service management have a significant effect on festival performance within IT governance. The effect of festival performance on resource management was not statistically significant. This study demonstrates that the systematic operation and management of local festivals using IT governance is necessary for local festivals. It will be more meaningful if further study discuss the IT utilization guidelines and success cases through the innovative use of IT for local festivals.

• Journal of Broadcast Engineering
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• v.23 no.6
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• pp.855-865
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• 2018

Sound event detection is one of the research areas to model human auditory cognitive characteristics by recognizing events in an environment with multiple acoustic events and determining the onset and offset time for each event. DCASE, a research group on acoustic scene classification and sound event detection, is proceeding challenges to encourage participation of researchers and to activate sound event detection research. However, the size of the dataset provided by the DCASE Challenge is relatively small compared to ImageNet, which is a representative dataset for visual object recognition, and there are not many open sources for the acoustic dataset. In this study, the sound events that can occur in indoor and outdoor are collected on a larger scale and annotated for dataset construction. Furthermore, to improve the performance of the sound event detection task, we developed a dual CNN structured sound event detection system by adding a supplementary neural network to a convolutional neural network to determine the presence of sound events. Finally, we conducted a comparative experiment with both baseline systems of the DCASE 2016 and 2017.

• Korean Journal of Remote Sensing
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• v.34 no.6_3
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• pp.1415-1425
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• 2018

Kompsat-5 is the first Earth Observation Satellite which is equipped with an SAR in Korea. SAR images are generated by receiving signals reflected from an object by microwaves emitted from a SAR antenna. Because the wavelengths of microwaves are longer than the size of particles in the atmosphere, it can penetrate clouds and fog, and high-resolution images can be obtained without distinction between day and night. However, there is no color information in SAR images. To overcome these limitations of SAR images, colorization of SAR images using Cycle GAN, a deep learning model developed for domain translation, was conducted. Training of Cycle GAN is unstable due to the unsupervised learning based on unpaired dataset. Therefore, we proposed MS Cycle GAN applying multi-scale discriminator to solve the training instability of Cycle GAN and to improve the performance of colorization in this paper. To compare colorization performance of MS Cycle GAN and Cycle GAN, generated images by both models were compared qualitatively and quantitatively. Training Cycle GAN with multi-scale discriminator shows the losses of generators and discriminators are significantly reduced compared to the conventional Cycle GAN, and we identified that generated images by MS Cycle GAN are well-matched with the characteristics of regions such as leaves, rivers, and land.