• Korean Journal of Comparative Education
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• v.28 no.2
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• pp.123-151
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• 2018

The purposes of this study were to examine the current status of ICT in all ASEAN countries and to provide implications for Korea to find appropriate ways to support and collaborate with HEIs in ASEAN countries. To achieve these purposes, ASEAN countries were categorized into 3 groups based on the development stages of ICT, and the key ICT initiatives, current facts about ICT, and related issues were analyzed. The results of the study were as follows: Group 1 countries, Brunei, Malaysia, and Singapore, with relatively well-established ICT infrastructure, have established their own ICT policies and initiated e-learning programs. Group 2 countries, Indonesia, Philippines, Thailand, and Vietnam, which have relatively well-developed ICT infrastructure with existing regional gaps, showed different uses of ICT in higher education. Philippines and Thailand established their own policies based on national ICT master plans while Indonesia focused on MOOCs and Vietnam initiated cyber university projects. Group 3 countries, Cambodia, Lao PDR, and Myanmar, with the least developed ICT infrastructure in ASEAN, have also tried to develop national level strategies to utilize ICT in higher education. However, insufficient and inadequate ICT infrastructure created issues and challenges for these countries to successfully initiate ICT policies. This study suggested that it is necessary to take into serious consideration the national differences when collaborating with and supporting ASEAN countries due to the variation of ICT development stages and different levels of using ICT in higher education among ASEAN countries.

• Journal of the Society of Disaster Information
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• v.17 no.2
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• pp.351-364
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• 2021

Purpose: Fire load analysis was conducted to secure basic data for evaluating fire risk of educational facilities. In order to calculate the fire load through a preliminary survey, basic data related to the fire load of school facilities were collected. Method: The basic data were the definition and types of fire loads, combustion heat data for the calculation of fire loads. The fire load was evaluated by multiplying the combustion heat by the weight of the combustibles in the compartment when calculating the fire load. Result: As for the fixed combustible materials of A-elementary school, the floor was mainly made of wood, in consideration of emotion and safety in the classroom, music room, and school office, and the rest of the compartments were made of stone. The ceiling and walls were made of gypsum board and concrete, so they were not combustible. The typical inflammable items in each room were desks, chairs, and lockers in the classroom, and the laboratory equipment box and experimental tool box were the main components in the science room, and books, bookshelves, and reading equipment occupied a large proportion in the library room. Conclusion: 'The fire loads of A-elementary' schools according to the combustibles loaded were in the order of library, computer room, English learning room, teacher's office, general classroom, science hall, and music room.

• Journal of Christian Education in Korea
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• v.74
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• pp.273-294
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• 2023

The purpose of this study is to use K-MOOC, which has limitations in utilization because it is centered on theory delivery, to derive tasks to activate the teaching methods of instructors, and to implement the derived tasks using the metaverse platform. to develop a prototype. According to the purpose of the study, the study was conducted as follows. First, from October 4 to November 15, 2022, a Delphi survey was conducted on 21 experts with experience of consulting, research, class development, and operation related to the K-MOOC project. Second, in order to realize the tasks in the teaching method field derived from the Delphi survey, matching with the teaching method class model elements to result of Delphi survey was applied was carried out. Finally, based on the results of expert Delphi and the elements of the class model applicable to the metaverse platform, a teaching method was developed. Through the process of the study, a total of 16 detailed items were derived for the teaching method-related tasks for the activation of K-MOOC: support strategic tasks, teaching method competency, aspect of class design, evaluation and sharing of learning outcomes. By applying the metaverse, the teaching model elements for K-MOOC revitalization were derived from four categories: self-directed repetition, individualized problem solving, practice opportunity expansion, and immediate feedback, and matched with the first 16 detailed items. A four-step teaching model was completed: course attendance (step 1), mission analysis by individual level (step 2), sharing of mission solutions (step 3), and mission evaluation and feedback (step 4). Through the results of this study, the possibility of using the metaverse as a teaching practice platform was confirmed even in terms of the introduction and development of specialized techniques.

• Information Systems Review
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• v.22 no.1
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• pp.59-72
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• 2020

Artificial Intelligence is establishing itself as a familiar tool from an intractable concept. In this trend, financial sector is also looking to improve the problem of existing system which includes Fraud Detection System (FDS). It is being difficult to detect sophisticated cyber financial fraud using original rule-based FDS. This is because diversification of payment environment and increasing number of electronic financial transactions has been emerged. In order to overcome present FDS, this paper suggests 3 types of artificial intelligence models, Generative Adversarial Network (GAN), Deep Neural Network (DNN), and Convolutional Neural Network (CNN). GAN proves how data imbalance problem can be developed while DNN and CNN show how abnormal financial trading patterns can be precisely detected. In conclusion, among the experiments on this paper, WGAN has the highest improvement effects on data imbalance problem. DNN model reflects more effects on fraud classification comparatively.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.1
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• pp.317-326
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• 2024

Biometric recognition is a technology that determines whether a person is identified by extracting information on a person's biometric and behavioral characteristics with a specific device. Cyber threats such as forgery, duplication, and hacking of biometric characteristics are increasing in the field of biometrics. In response, the security system is strengthened and complex, and it is becoming difficult for individuals to use. To this end, multiple biometric models are being studied. Existing studies have suggested feature fusion methods, but comparisons between feature fusion methods are insufficient. Therefore, in this paper, we compared and evaluated the fusion method of multiple biometric models using fingerprint, face, and iris images. VGG-16, ResNet-50, EfficientNet-B1, EfficientNet-B4, EfficientNet-B7, and Inception-v3 were used for feature extraction, and the fusion methods of 'Sensor-Level', 'Feature-Level', 'Score-Level', and 'Rank-Level' were compared and evaluated for feature fusion. As a result of the comparative evaluation, the EfficientNet-B7 model showed 98.51% accuracy and high stability in the 'Feature-Level' fusion method. However, because the EfficietnNet-B7 model is large in size, model lightweight studies are needed for biocharacteristic fusion.

• Journal of Korean Public Health Nursing
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• v.19 no.1
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• pp.74-94
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• 2005

The purpose of this study was to compare the effect of education between CAI(Computer Assisted Instruction) and lectures for smoking cessation among male students who attended vocational high schools. Conducted from February 24th to April 26th, 2003, the study design was quasi-experimental with nonequivalent control group pretest-posttest design. The study subjects were 60 male students in K vocational high school in Daegu city, who were present smokers and had more than 7.0 ppm concentration level of carbon monoxide. Thirty students were randomly chosen as the experimental group which applied CAI education method for smoking cessation. The other 30 students served as the control group which received lecture education method of 40 minutes on four consecutive days. CAI education for smoking cessation was composed of ready-made individual learning contents, counseling by using cyber-communication, writing a letter to stop smoking, and writing a written agreement for smoking cessation. Lecture education for smoking cessation was composed of a ready-prepared lecture for the group, writing a letter to stop smoking, and writing a written agreement for smoking cessation. To measure smoking related knowledge, Jeong Ree Roh(1996)'s smoking related knowledge scale$(Cronbach's\;{\alpha}=0.84)$ was modified and used by the researcher. To measure smoking related attitude, Jeong Ree Roh(1996)'s smoking related attitude scale$(Cronbach's\;{\alpha}=0.91)$ was modified and used by the researcher. Smoking related knowledge scale's Cronbach's $\alpha$ was 0.83 in the pilot study and 0.93 in this study. Smoking related attitude scale's Cronbach's a was 0.80 in the pilot study and 0.98 in this study. To determine the smoking amount, the number of cigarettes smoked per day was checked. The concentration level of CO in the exhaled breath was measured (Micro CO Cat. No. MCO2, UK). Data was analyzed by $x^2-test$, t-test, repeated measures ANOVA. simple main effects, and time contrast test with SPSS/Win 11.0 program. The results of this study were as follows: 1. The first hypothesis. that 'Smoking-related knowledge score in the experimental group by using CAI education for smoking cessation will be higher than that in the control group by using lecture education for smoking cessation', was not supported. 2. The second hypothesis, that 'Smoking-related attitude in the experimental group by using CAI education for smoking cessation will be higher than that in the control group by using lecture education for smoking cessation'. was supported(F=6490.79. p=0.000). 3. The third hypothesis. that 'Smoking amount in the experimental group by using CAI education for smoking cessation will be less than that in the control group by using lecture education for smoking cessation'. was supported. 1) The third-1st sub-hypothesis. that 'The number of cigarettes smoked per day in the experimental group by using CAI education for smoking cessation will be less than that in the control group by using lecture education for smoking cessation'. was supported(F=134.19. p=0.000). 2) The third-2nd sub-hypothesis. that 'The concentration level of CO by ppm per one exhaled breath in the experimental group by using CAI education for smoking cessation will be lower than that in the control group by using lecture education for smoking cessation"' was supported(F=268.55. p=0.000). From the above results. CAI education can be an effective intervention to improve smoking-related knowledge and attitude. and to reduce the number of cigarettes smoked per day and the concentration level of CO by ppm per one exhaled breath. Lecture education can be effective to improve smoking-related knowledge. In the future, when CAI education and lecture education for smoking cessation are applied on the school nursing field. the students can gain a comprehensive understanding of smoking cessation, changes in smoking-related knowledge. smoking-related attitude and reducing smoking amount. Furthermore, CAI education for smoking cessation could be developed as an individual self initiative program and could give a guideline to apply CAI education for smoking cessation in other field.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.10
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• pp.6234-6241
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• 2014

The purpose of this study was to examine the status of medical staff stress and accommodating manners on the death of patients in a hospital setting for serving the basic information to develop a death education program of medical personnel from April 1 to April 30, 2014. A survey was performed on 353 medical personnel at K university hospital, located in Daejeon metropolitan city. Frequency analysis, chi-square test, and independent t-test were used to analyze the data. The results showed that 'to understand the value of the time and preparedness of a meaningful future' were the most important perspectives on the contents of death education (p<0.05), 'in order to change perceptions and attitudes toward death positively' was the most important reason why they required death education'(p<0.05), 'case-based teaching and problem-based learning' was the most effective way of death education (p<0.05), 'negative or hostile response of a patient's guardian to medical personnel' was the largest stress that medical personnel confront upon witnessing a death'(p<0.05). An understanding of the death of patients by medical personnel and an awareness of the need for death education will help improve the understanding of the patient, their guardian, and medical personnel themselves. The main findings will contribute to the development of a specific death education program on the medical personnel in a hospital setting.

• Korean Journal of Remote Sensing
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• v.38 no.3
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• pp.265-282
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• 2022

Sea surface temperature (SST) is a factor that greatly influences ocean circulation and ecosystems in the Earth system. As global warming causes changes in the SST near the Korean Peninsula, abnormal water temperature phenomena (high water temperature, low water temperature) occurs, causing continuous damage to the marine ecosystem and the fishery industry. Therefore, this study proposes a methodology to predict the SST near the Korean Peninsula and prevent damage by predicting abnormal water temperature phenomena. The study area was set near the Korean Peninsula, and ERA5 data from the European Center for Medium-Range Weather Forecasts (ECMWF) was used to utilize SST data at the same time period. As a research method, Long Short-Term Memory (LSTM) algorithm specialized for time series data prediction among deep learning models was used in consideration of the time series characteristics of SST data. The prediction model predicts the SST near the Korean Peninsula after 1- to 7-days and predicts the high water temperature or low water temperature phenomenon. To evaluate the accuracy of SST prediction, Coefficient of determination (R²), Root Mean Squared Error (RMSE), and Mean Absolute Percentage Error (MAPE) indicators were used. The summer (JAS) 1-day prediction result of the prediction model, R²=0.996, RMSE=0.119℃, MAPE=0.352% and the winter (JFM) 1-day prediction result is R²=0.999, RMSE=0.063℃, MAPE=0.646%. Using the predicted SST, the accuracy of abnormal sea surface temperature prediction was evaluated with an F1 Score (F1 Score=0.98 for high water temperature prediction in summer (2021/08/05), F1 Score=1.0 for low water temperature prediction in winter (2021/02/19)). As the prediction period increased, the prediction model showed a tendency to underestimate the SST, which also reduced the accuracy of the abnormal water temperature prediction. Therefore, it is judged that it is necessary to analyze the cause of underestimation of the predictive model in the future and study to improve the prediction accuracy.