• Journal of The Korean Society of Agricultural Engineers
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• v.64 no.1
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• pp.39-50
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• 2022

In this study, we suggested the optimal training period for predicting the streamflow using the LSTM (Long Short-Term Memory) model based on the deep learning and CMIP5 (The fifth phase of the Couple Model Intercomparison Project) future climate scenarios. To validate the model performance of LSTM, the Jinan-gun (Seongsan-ri) site was selected in this study. We comfirmed that the LSTM-based streamflow was highly comparable to the measurements during the calibration (2000 to 2002/2014 to 2015) and validation (2003 to 2005/2016 to 2017) periods. Additionally, we compared the LSTM-based streamflow to the SWAT-based output during the calibration (2000~2015) and validation (2016~2019) periods. The results supported that the LSTM model also performed well in simulating streamflow during the long-term period, although small uncertainties exist. Then the SWAT-based daily streamflow was forecasted using the CMIP5 climate scenario forcing data in 2011~2100. We tested and determined the optimal training period for the LSTM model by comparing the LSTM-/SWAT-based streamflow with various scenarios. Note that the SWAT-based streamflow values were assumed as the observation because of no measurements in future (2011~2100). Our results showed that the LSTM-based streamflow was similar to the SWAT-based streamflow when the training data over the 30 years were used. These findings indicated that training periods more than 30 years were required to obtain LSTM-based reliable streamflow forecasts using climate change scenarios.

• The Journal of Korea Robotics Society
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• v.16 no.1
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• pp.41-48
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• 2021

In this paper, we review papers which report to the all solid-state electroactive polymer-based tunable lens. Since electroactive polymer-based tunable lenses change their focal length by responding to electric stimuli, it can be minimized the size and weight of optical modules. Thus, it has been received attention in the robot, mobile device and display industry. The all solid-state electroactive polymer-based tunable lenses can be classified into two categories depending on the classification of materials: ionic electroactive polymer-based lenses and non-ionic electroactive polymer-based lenses. Most of the ionic electroactive polymer-based tunable lenses are fabricated with ionic polymer-metal composite. So, the ionic electroactive polymer-based tunable lenses can be operated under low electric voltage. But small force, slow recovery time and environmental limitation for operation has been pointed to the disadvantage of the lenses. The non-ionic electroactive polymer-based tunable lenses are classified again into two categories: dielectric polymer-based tunable lenses and polyvinylchloride gel-based tunable lenses. The advantage of the dielectric polymer-based tunable lenses is fast response to electric stimuli. But the essential flexible electrodes degrade performance of the lens. Polyvinylchloride gel-based tunable lens has reported impressive performance without flexible electrodes.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.12
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• pp.211-222
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• 2021

Green economy, also known as sustainable economy, is a current development trend in which consumers prefer products that are wholly or partly derived from materials of biological origin since they have become more concerned about their health and the environment in which they live. This study aims to examine consumer behavior toward bio-based products with three key goals in mind. First, it helps to understand the perception of consumers toward Bio-based products. Second, it properly helps consumers be aware of products derived from materials of biological origin so that the consumer can make purchasing decisions to protect their health and contribute to the protection of the environment. Third, the study on consumer behavior towards bio-based products will provide a more accurate view and assessment to companies looking to develop Bio-based products. Based on that, the research is carried out through surveying, collecting data from consumers, and then using the deductive approach, descriptive statistics, and quantitative method analysis. The results demonstrated that a positive relationship and a direct impact are established between the variables of Attitude and Social Norms and the Purchase Intention toward Bio-based products. Furthermore, the findings reveal that customers have positive feelings towards bio-based products in terms of trust, knowledge, and the environment.

• Dementia and Neurocognitive Disorders
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• v.22 no.4
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• pp.130-138
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• 2023

Background and Purpose: Growing evidence has shown that cognitive interventions can mitigate cognitive decline in patients with mild cognitive impairment (MCI). However, most previous cognitive interventions have been group-based programs. Due to their intrinsic limitations, group-based programs are not widely used in clinical practice. Therefore, we have developed a tablet-based cognitive intervention program. This preliminary study investigated the feasibility and effects of a 12-week structured tablet-based program on cognitive function in patients with MCI. Methods: We performed a single-arm study on 24 patients with MCI. The participants underwent a tablet-based cognitive intervention program 5 times a week over a 12-week period. The primary outcome was changes in cognitive function, measured using the Korean version of the Consortium to Establish a Registry for Alzheimer's Disease Assessment Packet (CERAD-K). Outcomes were evaluated at baseline, within two weeks of the last program (post-intervention), and at the six-month follow-up session. Results: The completion rate of the tablet-based program was 83.3% in patients with MCI. The program improved cognitive function based on the CERAD-K total score (p=0.026), which was maintained for at least three months (p=0.004). There was also an improvement in the depression scale score (p=0.002), which persisted for three months (p=0.027). Conclusions: Our 12-week structured tablet-based program is feasible for patients with MCI. Furthermore, although further studies with a double-arm design are required, the program appears to be an effective strategy to prevent cognitive decline in patients with MCI.

• Proceedings of the Korea Contents Association Conference
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• 2006.11a
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• pp.355-359
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• 2006

Mobile network evolution and development of USN technologies introduce new business model based on context awareness. Cellular operators provide friend finding service using cell based location information and telematics service using GPS location information. Recently cellular operators provide yellow page service based cell based location information. In this paper, we develop mobile tour application on WIPI platform based on location information. Mobile tour information services provide the best information based on context awareness using user location information from LBSP (Location Based Service Platform), season, weather conditions, time from Web server, and personal preference information stored in database. Mobile tour information service application is developed on WIPI platform.

• Nutrition Research and Practice
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• v.9 no.1
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• pp.87-91
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• 2015

BACKGROUND/OBJECTIVES: This research was conducted to compare lecture- and experience-based methods of nutritional education as well as provide fundamental data for developing an effective nutritional education program in elementary schools. SUBJECTS/METHODS: A total of 110 students in three elementary schools in Jeollanam-do were recruited and randomly distributed in lecture- and experience-based groups. The effects of education on students' dietary knowledge, dietary behaviors, and dietary habits were analyzed using a pre/post-test. RESULTS: Lecture- and experience-based methods did not significantly alter total scores for dietary knowledge in any group, although lecture-based method led to improvement for some detailed questions. In the experience-based group, subjects showed significant alteration of dietary behaviors, whereas lecture-based method showed alteration of dietary habits. CONCLUSIONS: These outcomes suggest that lecture- and experience-based methods led to differential improvement of students' dietary habits, behaviors, and knowledge. To obtain better nutritional education results, both lectures and experiential activities need to be considered.

• Journal of Korea Multimedia Society
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• v.24 no.9
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• pp.1224-1241
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• 2021

Recent development of deep learning techniques for image generation has led to straightforward generation of sophisticated deepfakes. However, as a result, privacy violations through deepfakes has also became increased. To solve this issue, a number of techniques for deepfake detection have been proposed, which are mainly focused on RGB channel-based analysis. Although existing studies have suggested the effectiveness of other color model-based analysis (i.e., Grayscale), their effectiveness has not been quantitatively validated yet. Thus, in this paper, we compare the effectiveness of Grayscale channel-based analysis with RGB channel-based analysis in deepfake detection. Based on the selected CNN-based models and deepfake datasets, we measured the performance of each color model-based analysis in terms of accuracy and time. The evaluation results confirmed that Grayscale channel-based analysis performs better than RGB-channel analysis in several cases.

• Journal of Power Electronics
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• v.19 no.2
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• pp.549-559
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• 2019

This paper proposes an adaptive sliding mode control (ASMC) strategy with an enhanced optimal reaching law (EORL) for the robust current tracking control of the boost converter based hybrid power source (HPS) in an electric vehicle (EV). A conventional ASMC strategy based on state observers and the hysteresis control method is used to realize the current tracking control for the boost converter based HPS. Then a novel enhanced exponential reaching law is proposed to improve the ASMC. Moreover, an enhanced exponential reaching law is optimized by particle swarm optimization. Finally, the adaptive control factor is redesigned based on the EORL. Simulations and experiments are established to validate the ASMC strategy with the EORL. Results show that the ASMC strategy with the EORL has an excellent current tracking control effect for the boost converter based HPS. When compared with the conventional ASMC strategy, the convergence time of the ASMC strategy with the EORL can be effectively improved. In EV applications, the ASMC strategy with the EORL can achieve robust current tracking control of the boost converter based HPS. It can guarantee the active and stable power distribution for boost converter based HPS.

• Steel and Composite Structures
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• v.42 no.5
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• pp.685-697
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• 2022

In this paper, a vibration-based method using the change ratios of modal data and the experience-based learning algorithm is presented for quantifying the position, size, and interface layer of delamination in laminated composites. Three types of objective functions are examined and compared, including the ones using frequency changes only, mode shape changes only, and their combination. A fine three-dimensional FE model with constraint equations is utilized to extract modal data. A series of numerical experiments is carried out on an eight-layer quasi-isotropic symmetric (0/-45/45/90)s composited beam for investigating the influence of the objective function, the number of modal data, the noise level, and the optimization algorithms. Numerical results confirm that the frequency-and-mode-shape-changes-based technique yields excellent results in all the three delamination variables of the composites and the addition of mode shape information greatly improves the accuracy of interface layer prediction. Moreover, the EBL outperforms the other three state-of-the-art optimization algorithms for vibration-based delamination detection of composites. A laboratory test on six CFRP beams validates the frequency-and-mode-shape-changes-based technique and confirms again its superiority for delamination detection of composites.

• Psychiatry investigation
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• v.15 no.11
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• pp.1071-1078
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• 2018

Objective We developed easily accessible imagery-based treatment program for patients with post-traumatic stress disorder (PTSD) related to workplace accidents and investigated the effects of the program on various PTSD related symptoms. Methods The program was based on an online platform and consisted of eight 15-min sessions that included script-guided imagery and supportive music. Thirty-five patients with workplace-related PTSD participated in this program 4 days per week for 4 weeks. Its effects were examined using self-report questionnaires before and after the take-home online treatment sessions. Results After completing the 4-week treatment program, patients showed significant improvements in depressed mood (t=3.642, p=0.001) based on the Patient Health Questionnaire-9 (PHQ-9), anxiety (t=3.198, p=0.003) based on the Generalized Anxiety Disorder seven-item (GAD-7) scale, and PTSD symptoms (t=5.363, p<0.001) based on the Posttraumatic Stress Disorder Check List (PCL). In particular, patients with adverse childhood experiences exhibited a greater degree of relief related to anxiety and PTSD symptoms than those without adverse childhood experiences. Conclusion The present results demonstrated that the relatively short online imagery-based treatment program developed for this study had beneficial effects for patients with workplace-related PTSD.