• Korean journal of aerospace and environmental medicine
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• v.31 no.1
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• pp.24-30
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• 2021

Purpose: The purpose of this study is to consider ways to strengthen it through comparison and curriculum while recognizing the importance of global competencies in liberal arts education in universities. Methods: In order to explore ways to reinforce the sub-competence of global competencies, this study was conducted at a four-year university in Chungcheong-do for one year in 2019, such as 'Global Culture Talk', 'Global Travel', 'Global Nanta', and 'Making Global Friends'. Cases of comparison and application of educational programs were analyzed. The program was attended by the Department of Business Administration, Department of Aviation Service, Department of Design, Department of Manga Animation, Department of Broadcasting and Film, and foreign exchange students. The competency-centered curriculum not only has clear educational goals, but is also very advantageous in establishing a feedback system by measuring its performance. This study will assess the effectiveness of the education plan by diagnosing the change in competencies before and after the comparison and curriculum is operated. Results: The overall global competency has increased by 0.2 points compared to 2017. By subsector, it was found that the flexibility increased by 1.4 points. In the field of cross-cultural understanding, it rose 0.6 points, and in the field of global understanding, it rose 2.2 points, showing the largest increase in the sub-fields. Nevertheless, the field of global interest remains at a low level. This is considerably low compared to flexibility and ability to understand other cultures, and it is expected that measures for improvement should be continuously sought. Since the understanding of other cultures has already exceeded 60 points, it is expected that the global competency of the university will be strengthened if the level is consistently maintained and the emphasis is placed on enhancing flexibility and improving global understanding. Conclusion: The importance of strengthening global capabilities is steadily rising. Universities are also reorganizing the curriculum by analyzing the needs and satisfaction of education consumers to respond to this. The programs operated and analyzed in this study were also made as part of this effort. However, since there are various factors that affect global competency, it cannot be but admitted that it is not easy to gauge the change in competency with only a few programs and short-term efforts. However, if the efforts pursued by this study are accumulated and supplemented through feedback from a long-term perspective, it can be expected that there are not a lot of contributions to strengthening global competencies in liberal arts education.

• Journal of the Korea Society of Computer and Information
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• v.27 no.9
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• pp.1-12
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• 2022

Traditional methods of measuring corneal ulcers were difficult to present objective basis for diagnosis because of the subjective judgment of the medical staff through photographs taken with special equipment. In this paper, we propose a method to detect the ulcer area on a pixel basis in corneal ulcer images using a semantic segmentation model. In order to solve this problem, we performed the experiment to detect the ulcer area based on the DeepLab model which has the highest performance in semantic segmentation model. For the experiment, the training and test data were selected and the backbone network of DeepLab model which set as Xception and ResNet, respectively were evaluated and compared the performances. We used Dice similarity coefficient and IoU value as an indicator to evaluate the performances. Experimental results show that when 'crop & resized' images are added to the dataset, it segment the ulcer area with an average accuracy about 93% of Dice similarity coefficient on the DeepLab model with ResNet101 as the backbone network. This study shows that the semantic segmentation model used for object detection also has an ability to make significant results when classifying objects with irregular shapes such as corneal ulcers. Ultimately, we will perform the extension of datasets and experiment with adaptive learning methods through future studies so that they can be implemented in real medical diagnosis environment.

• 한국노년학
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• v.40 no.3
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• pp.429-442
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• 2020

The purpose of this research was to examine changes in the physical fitness, activities of daily living performance, and cognitive status of the frail elderly by combined exercise programs. The combined exercise program consisted of an aerobic exercise for the elderly and a four-color ladder exercise for improving of cognitive ability and physical fitness. Twenty-one frail elderly participated in this study, they were divided into 12 exercise groups and nine control groups. The exercise group conducted the combined exercise program of 60 minutes, twice a week, for10 weeks, while the control group maintained their normal lives. Strength, flexibility, agility, coordination, ADL and MMSE-K were measured. Exercise group showed significant improvement in grip strength compared to control group. In addition, ADL showed significant improvement only in the exercise group. The results of this study showed that participation in the combined exercise program of the el derl y was effective in improving the grip strength, and in preventing various physical functions and cognitive conditions decline.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.4
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• pp.251-260
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• 2022

Although the number of trees affected by pine wilt disease is decreasing, the affected area is expanding across the country. Recently, with the development of deep learning technology, it is being rapidly applied to the detection study of pine wilt nematodes and dead trees. The purpose of this study is to efficiently acquire deep learning training data and acquire accurate true values to further improve the detection ability of U-Net models through learning. To achieve this purpose, by using a filtering method applying a step-by-step deep learning algorithm the ambiguous analysis basis of the deep learning model is minimized, enabling efficient analysis and judgment. As a result of the analysis the U-Net model using the true values analyzed by period in the detection and performance improvement of dead pine trees of wilt nematode using the U-Net algorithm had a recall rate of -0.5%p than the U-Net model using the previously provided true values, precision was 7.6%p and F-1 score was 4.1%p. In the future, it is judged that there is a possibility to increase the precision of wilt detection by applying various filtering techniques, and it is judged that the drone surveillance method using drone orthographic images and artificial intelligence can be used in the pine wilt nematode disaster prevention project.

• Journal of Life Science
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• v.32 no.8
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• pp.611-621
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• 2022

Dimethyl sulfoxide (DMSO) is commonly used as control or vehicle solvent in preclinical research of neurodegenerative diseases such as amyotrophic lateral sclerosis (ALS) due to its ability to dissolve lipophilic compounds and cross the blood brain barrier. However, the biochemical effects of DMSO on the outcomes of preclinical research are often overlooked. In the present study, we investigated whether the long-term oral administration of 5% DMSO affects the neurological, functional, and histological disease phenotype of the copper/zinc superoxide dismutase glycine 93 to alanine mutation (SOD1-G93A) mouse model of amyotrophic lateral sclerosis. SOD1-G93A transgenic mice showed shortened survival time and reduced motor function. We found that administration with DMSO led to increased mean survival time, reduced neurological scores, and improved motor performance tested using the rotarod and grip strength tests. On the other hand, DMSO treatment did not attenuate motor neuron loss in the spinal cord and denervation of neuromuscular junctions in the skeletal muscle. These results suggest that DMSO administration could improve the quality of life of the SOD1-G93A mouse model of ALS without affecting motor neuron denervation. In conclusion, the use of DMSO as control or vehicle solvent in preclinical research may affect the behavioral outcomes in the SOD1-G93A mouse model. The effect of the vehicle should be thoroughly considered when interpreting therapeutic efficacy of candidate drugs in preclinical research.

• Journal of the Korean Crystal Growth and Crystal Technology
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• v.33 no.1
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• pp.22-30
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• 2023

Currently, almost all product development in the jewelry industry utilizes 3D CAD and 3D printing. In this situation, 3D CAD modeling and 3D printing ability units in colleges, Tomorrow Learning Card Education, and Course Evaluation-type jewelry design related education are conducted with developed curriculum based on the standards for training standards, training hours, training equipment, and practice materials presented by NCS. Accordingly, this study analyzes 3D CAD modeling and 3D printing training facilities, training hours, training equipment, etc into three categories of NCS precious metal processing and jewelry design, and studies the development of educational systems such as 3D CAD/3D printing curriculum and various environments that meet these standards. Education using this 3D CAD/3D printing education system will enable us to continuously supply professional talent with practical skills not only in the jewelry industry but also in the entire 3D CAD/3D printing manufacturing industry, which is called as one of the pillars of the 4th Industry. The quality of employment of trainees receiving education and the long-term retention rate after employed can also have a positive effect. In addition, excellent educational performance will help improve the recruitment rate of new students in jewelry jobs or manufacturing-related departments, which are difficult to recruit new students in recent years.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.6
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• pp.87-96
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• 2022

The traffic vulnerable, including elderly pedestrians, have a relatively low walking speed and slow cognitive response time due to reduced physical ability. Although a smart crossing system has been developed and operated to improve problem, it is difficult to operate a signal that reflects the appropriate walking speed for each pedestrian. In this study, a neural network model and a multiple regression model-based traversing speed estimation model were developed using image information collected in an area with a high percentage of traffic vulnerability. to support the provision of optimal walking signals according to real-time traffic weakness. actual traffic data collected from the urban traffic network of Paju-si, Gyeonggi-do were used. The performance of the model was evaluated through seven selected indicators, including correlation coefficient and mean absolute error. The multiple linear regression model had a correlation coefficient of 0.652 and 0.182; the neural network model had a correlation coefficient of 0.823 and 0.105. The neural network model showed higher predictive power.

• Journal of Intelligence and Information Systems
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• v.29 no.3
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• pp.419-437
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• 2023

As the number of thin filers in Korea surpasses 12 million, there is a growing interest in enhancing the accuracy of assessing their credit default risk to generate additional revenue. Specifically, researchers are actively pursuing the development of default prediction models using machine learning and deep learning algorithms, in contrast to traditional statistical default prediction methods, which struggle to capture nonlinearity. Among these efforts, Graph Neural Network (GNN) architecture is noteworthy for predicting default in situations with limited data on thin filers. This is due to their ability to incorporate network information between borrowers alongside conventional credit-related data. However, prior research employing graph neural networks has faced limitations in effectively handling diverse categorical variables present in credit information. In this study, we introduce the Transformer embedded Graph Convolutional Network (TeGCN), which aims to address these limitations and enable effective default prediction for thin filers. TeGCN combines the TabTransformer, capable of extracting contextual information from categorical variables, with the Graph Convolutional Network, which captures network information between borrowers. Our TeGCN model surpasses the baseline model's performance across both the general borrower dataset and the thin filer dataset. Specially, our model performs outstanding results in thin filer default prediction. This study achieves high default prediction accuracy by a model structure tailored to characteristics of credit information containing numerous categorical variables, especially in the context of thin filers with limited data. Our study can contribute to resolving the financial exclusion issues faced by thin filers and facilitate additional revenue within the financial industry.

• Journal of the Korean Applied Science and Technology
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• v.40 no.3
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• pp.521-533
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• 2023

The purpose of this study was to investigate the effect on the clinical competence by the face-to-face, non-face-to-face clinical practice stress and the stress coping. A survey was conducted among nursing students of university in Seoul and Chungcheong City from June 10 to July 10, 2021. 201 copies were included in the final data analysis, Pearson's correlation coefficient and hierarchical regressions was used. As a result, in the first stage, nursing students grades, major satisfaction, and face-to-face practice satisfaction explained 19.4% of their clinical performance ability, in the second step, stress coping was added to increase explanatory power by 19.6% allowing a total of 39.0% of randomness to be explained. Therefore, this study could be used as a basic data for the counseling, development, and education programs for stress coping to increase clinical competence.

• Journal of Korea Entertainment Industry Association
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• v.13 no.8
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• pp.541-549
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• 2019

The purpose of this study was to test the effects of flip learning-based simulation practice education on the learning flow, learning confidence, communication skills, and clinical competence ability of nursing student. This study used a one group, pre-post test design. We collected the data from 65 4th grade nursing students. Flip learning-based simulation practice education was conducted from March 5th to April 17th, 2019. The collected data were analyzed using SPSS WIN 21.0 program. The result of study were follows. After the flip learning-based simulation practice education, there were significant increased in learning flow(t=-7.548, p<.001), learning confidence(t=-9.163, p<.001), communication skills(t=-6.506, p<.001) and clinical competence(t=-6.733, p<.001). After the flip learning-based simulation practice, clinical performance was found to be positively correlated with learning flow(r=.627, p<.001), learning confidence(r=.513, p<.001) and communication skills(r=.328, p<.008). learning flow and learning confidence(r=.528, p<.001), communication skills and learning flow(r=.332, p<.007) also showed a positive correlation. Therefore, flip learning-based simulation practice education for nursing student could be effective nursing education method.