• Journal of Digital Convergence
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• v.20 no.2
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• pp.525-541
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• 2022

This study aimed to develop simulation practice program with PBL (S-PBL) for nursing students and evaluate the effect of the program on their problem solving ability, clinical performance competency, learning satisfaction and confidence. The participants were nursing students who applied for simulation practice courses at an university in J province. The study was a mixed-method design using a nonequivalent one group pretest-posttest design (n=91) and focus group interview (n=12). Quantitative data were analyzed using SPSS 23.0 program and qualitative data thematic analysis. Quantitative data showed S-PBL was effective in improving clinical performance competency, learning satisfaction and confidence of the participants, but not in improving problem solving ability. As a result of the qualitative study, four themes and eight sub-themes were derived, and the themes were "Learn integrated nursing care based on priority", "Experience team cooperation through communication," "Learn vividly critical care" and "Improved nursing competency". The S-PBL could be effective in practical education for nursing students. In further study, it is necessary to develop various simulation practice programs based on PBL through a mixed-method design and apply them to nursing curriculum.

• Journal of the Korean Applied Science and Technology
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• v.40 no.1
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• pp.59-70
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• 2023

This study is a meta-analysis study to comprehensively investigate the effects of flipped learning teaching applied to nursing students in Korea through systematic review. Data collection was conducted by a team of two researchers from November 20 to December 20, 2022. A total of 129 papers were searched through the domestic database, and duplicate papers were removed and the final 9 studies were selected. Flipped learning improved critical thinking disposition of nursing students 0.91(Z=8.36, p<.001), learning self-efficacy 0.35 (Z=2.62, p=.009), self-directed learning ability 0.81(Z=6.53, p<.001), academic achievement 0.60(Z=5.18, p<.001), and self-efficacy 0.66(Z=4.79, p<.001). Based on the results of this study, it was confirmed that flipped learning is an effective teaching method applicable to the domestic nursing education field, and an objective basis was presented for the direction of flipped learning class design. In the future, we suggest repeated studies that comprehensively analyze the effects of various outcome variables that have a positive effect on flipped learning.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.6
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• pp.469-481
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• 2018

DL (Deep Learning) is getting popular in various fields to implement artificial intelligence that resembles human learning and cognition. DL based on complicate structure of the ANN (Artificial Neural Network) requires computing power and computation cost. Variety of DL models with improved performance have been developed with powerful computer specification. The main purpose of this paper is to detect buildings from aerial images and evaluate performance of Mask R-CNN (Region-based Convolutional Neural Network) developed by FAIR (Facebook AI Research) team recently. Mask R-CNN is a R-CNN that is evaluated to be one of the best ANN models in terms of performance for semantic segmentation with pixel-level accuracy. The performance of the DL models is determined by training ability as well as architecture of the ANN. In this paper, we characteristics of the Mask R-CNN with various types of the images and evaluate possibility of the generalization which is the ultimate goal of the DL. As for future study, it is expected that reliability and generalization of DL will be improved by using a variety of spatial information data for training of the DL models.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.48 no.10
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• pp.773-782
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• 2020

The development of joint FE models for deep learning neural network (DLNN)-based hybrid FEA is presented. Material models of bolts and bearings in the front axle of tractor, showing complex behavior induced by various tightening conditions, were replaced with DLNN models. Bolts are modeled as one-dimensional Timoshenko beam elements with six degrees of freedom, and bearings as three-dimensional solid elements. Stress-strain data were extracted from all elements after finite element analysis subjected to various load conditions, and DLNN for bolts and bearing were trained with Tensorflow. The DLNN-based joint models were implemented in the ABAQUS user subroutines where stresses from the next increment are updated and the algorithmic tangent stiffness matrix is calculated. Generalization of the trained DLNN in the FE model was verified by subjecting it to a new loading condition. Finally, the DLNN-based FEA for the front axle of the tractor was conducted and the feasibility was verified by comparing with results of a static structural experiment of the actual tractor.

• The Journal of the Korea Contents Association
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• v.16 no.5
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• pp.561-574
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• 2016

The purpose of this study is to enhance the quality of APEC Edutainment Exchange Program (AEEP) that was developed for Korean multicultural students and implemented in Philippines. Based on literature review and data analysis, we designed and developed edutainment-based contents for their team projects. The participants of the AEEP which was carried out between Aug 12th and 19th in 2012 were 34 elementary and secondary school students with program coordinators. Data collection included survey, video, interview, report and episodes. The data analysis of AEEP activities revealed the features of global experiential learning and edutainment in the K-pop and cooking projects where the Korean-Philippino students exchanged their cultural activities with joyful cooperation. The data also confirmed the Korean students' positive changes toward multi-cultural understandings and attitudes.

• International Journal of Advanced Culture Technology
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• v.12 no.3
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• pp.37-46
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• 2024

This study was designed to identify factors affecting polyclinic (clinical practice) during COVID-19. Fourth-year medical students at K Medical University in Daejeon, South Korea were recruited, and 64 medical students ultimately agreed to participate in a survey about polyclinics in a regional emergency center over 4 weeks. Satisfy answers for 5^th grade and 6^th grade was 15 (53.6%) and 13 (46.4%) respectively. Dissatisfy answers of observation of the ICU for 5^th grade and 6^th grade was 10 (27.8%) and 26 (72.2%) respectively. Thus, there were more satisfy answers in 5^th grade and less satisfy answers in 6^th grade(p<0.05). Based on the results of confirming significance for regression coefficient, several factors influencing the polyclinic were identified, and the following categories showed statistical significance (p<0.05): for 6^th grade, satisfy answers of the clinic hours showed 3.656 times more than dissatisfy answers, exempt from the operation room showed 21.596 times more than dissatisfy answers, observation of the intensive unit care (ICU) showed 0.054 times less than dissatisfy answers, and cares of the COVID-19 patients showed 6.962 times more than dissatisfy answers. We suggest that hybrid or virtual medical education such as the polyclinic utilizing standardized patients (SP) or augmented reality (AR) technologies at the virtual hospital or the real hospital. More medical students would be encouraged to participate the problem-based learning (PBL) or team-based learning (TBL) in so-called 'hybrid or virtual' polyclinic.

• Journal of Korea Multimedia Society
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• v.23 no.8
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• pp.977-985
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• 2020

Aiming at the problem of complex feature extraction and low accuracy in human action recognition, this paper proposed a network structure combining batch normalization algorithm with GoogLeNet network model. Applying Batch Normalization idea in the field of image classification to action recognition field, it improved the algorithm by normalizing the network input training sample by mini-batch. For convolutional network, RGB image was the spatial input, and stacked optical flows was the temporal input. Then, it fused the spatio-temporal networks to get the final action recognition result. It trained and evaluated the architecture on the standard video actions benchmarks of UCF101 and HMDB51, which achieved the accuracy of 93.42% and 67.82%. The results show that the improved convolutional neural network has a significant improvement in improving the recognition rate and has obvious advantages in action recognition.

• International Journal of Automotive Technology
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• v.8 no.4
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• pp.505-512
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• 2007

This paper presents the quantitative evaluation of the fearfulness of the human driver in the case of the short range (time) on the highway. The driving situation is realized by using the driving simulator based on CAVE, which provides three-dimensional stereoscopic immersive visual information. The examinees' responses and personal information are categorized reasonably by applying the competitive learning algorithm. The characteristics of each group are analyzed. The following two situations are also compared: (1) the active approaching situation where the examinee drives the vehicle near the preceding vehicle, and (2) the passive approaching situation where the preceding vehicle nears the examinee's vehicle by gradually decelerating. The range time that the examinee feels fear in the active approaching case tends to be shorter than that in the passive approaching case.

• Proceedings of the Korea Contents Association Conference
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• 2017.05a
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• pp.473-474
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• 2017

본 연구는 TBL에서 학생을 보다 효율적으로 평가하기 위해 학생평가방법에 따른 평가점수 간 관계를 비교하고 그 관대함 정도를 분석하였다. 치위생학과 학생의 구강보건교육학 및 구강보건교육학 실습 교과목에서 학생평가방법에 따른 평가점수 간 관계를 살펴본 결과 지필시험과 팀별평가만 유의미한 중간 정도의 정적 상관관계가 나타났고, 그 외의 관계는 모두 유의하지 않았다. 학생평가방법에 따른 평가점수 간 관대함 정도는 팀원평가, 지필시험, 팀별평가 순으로 관대한 것으로 나타났다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.11
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• pp.510-518
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• 2020

With the promotion of digitalization in the construction industry, BIM has become an indispensable technology. On the other hand, it has not been actively utilized in practice because of the difficulty of BIM modeling. The reason is that 3D modeling is less productive not only because of the difficulty of learning BIM software but also the modeling work is done manually. Therefore, this study proposes a method and system that can improve the productivity of BIM-based modeling. For this reason, in the study, a slit caisson, which is a typical structure of a port, was selected as a development target, and various parameters were derived through interviews with experts so that it could be used in practice. This study presents a UI construction plan that considers user convenience for efficient management and operation of diverse and complex parameters. Based on this, this study used visual programming and Excel VBA to develop a BIM-based design automation system for slit caissons. The developed system can use many parameters to quickly develop slit caisson models suitable for various design conditions that can contribute to BIM-based modeling and productivity improvement.