• 한국공간구조학회논문집
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• 제24권2호
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• pp.53-63
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• 2024

The cultural heritage of fortresses is often exposed to external elements, leading to significant damage from stone weathering and natural disasters. However, due to the nature of cultural heritage, dismantling and restoration are often impractical. Therefore, the stability of fortress cultural heritage was evaluated through non-destructive testing. The durability of masonry cultural heritages is greatly influenced by the physical characteristics of the back-fille material. Dynamic characteristics were assessed, and endoscopy was used to inspect internal fillings. Additionally, a finite element analysis model was developed considering the surrounding ground through elastic wave exploration. The analysis showed that the loss of internal fillings in the target cultural heritage site could lead to further deformation in the future, emphasizing the need for careful observation.

• The Journal of Asian Finance, Economics and Business
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• 제5권2호
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• pp.81-94
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• 2018

The purpose of this study is to substantiate the affecting factors of informal learning outcomes for professions in various dimensions of an individual and organization. In specific, the study analyzed the effects of learning motivation, job characteristics, and a supportive learning environment which have on task-related knowledge acquisition, adapting to organization and understanding contexts, relationship formation, and improving self-development-ability. The participants of the study were 261 professionals working at four major accounting firms in South Korea. Multiple regression models were applied step by step for analysis. In this study, the informal learning of professionals working at four major accounting firms is influenced by various factors of learning motivation, job characteristics, and a supportive learning environment. The detailed analysis results were as follows. Firstly, peer-support showed the most positive effect on task-related knowledge acquisition. Secondly, for adapting to organization and understanding contexts, task autonomy showed the greatest effect. Thirdly, peer-support was found to be the most important factor for relationship formation. Fourthly, for improving self-development ability, learning goal orientation showed to be the most important factor. The various factors facilitated the professional learning by empirical identification. The study presented practical implications for creating an effective informal learning support environment.

• 한국정보통신학회논문지
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• 제22권12호
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• pp.1618-1624
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• 2018

플립러닝을 기반으로 학부중심 학사 구조가 4차 산업혁명시대 대학교육의 변화를 통해 학생들은 문제 해결능력을 기반으로 가치창출 능력을 배양하는 필수화 과정이 되어야 한다. 이를 위해 창안된 프로젝트기반 학습법(Project Based Learning)과 MOOC를 결합한 거꾸로 학습법(Flipped Learning)을 과감하게 도입 및 확산하고, 날로 고도화되어 가는 AI기반의 학습컨설팅(E-Advisor)의 도입과 확산에 따라 4차 산업혁명에 부합하는 "개인 맞춤교육"으로의 전환이 이루어져야 한다.

• 한국도서관정보학회지
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• 제31권1호
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• pp.209-228
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• 2000

Information technology is affecting most areas of society in information society, schools are facing with the change of learning methods by computer and internet. The purpose of this study is to apply internet technology to school library, for maximizing the function of school library in information age. This study designed and implemented th ISLMC(Internet School Library Media Center) using the WWW, that gathers, processes and stores the useful information resources on the internet and effectively provides these to teachers, students and their parents of the learning activities.

• Korean Journal of Radiology
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• 제22권10호
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• pp.1597-1608
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• 2021

Cardiovascular computed tomography (CT) is among the most active fields with ongoing technical innovation related to image acquisition and analysis. Artificial intelligence can be incorporated into various clinical applications of cardiovascular CT, including imaging of the heart valves and coronary arteries, as well as imaging to evaluate myocardial function and congenital heart disease. This review summarizes the latest research on the application of deep learning to cardiovascular CT. The areas covered range from image quality improvement to automatic analysis of CT images, including methods such as calcium scoring, image segmentation, and coronary artery evaluation.

• 한국산학기술학회논문지
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• 제12권11호
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• pp.4788-4795
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• 2011

본 연구는 전통적인 방식으로부터 U-Learning으로 학습 패러다임을 전환하는 효과 및 가능성을 검토하고 제안하기 위한 것이며, E-Learning으로부터 M-Learning 및 U-Learning으로의 교수법 플랫폼 전환을 고려하기 위한 것이다. 개인별 학습 프로세스에 학습 환경이 어떤 영향을 미치는가에 대한 적절한 연구없이는 양질의 교육을 제공하기 어려울 것이다. 현대는 언제 어디서나 교육을 받을 수 있는 새로운 학습 환경 시대를 맞이하고 있으며, 누구나 평생교육을 받을 수 있게 되었다. 이러한 경향의 장점을 최대화하고, 양질의 교육을 진행하기 위한 제한 사항들을 확인하여야 하는데, 이들 요소들은 U-Learning 및 이를 가능하게 하는 기술과 함께 논의되어야 한다. 보급교육 혹은 평생교육은 많은 연구기관의 관심을 받고 있는바, 본 논문에서는 학습 모드 및 학습 양상의 유형에 대한 논의도 포함하였다.

• 한국간호교육학회지
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• 제19권3호
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• pp.371-383
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• 2013

Purpose: The purpose of this study was to develop a module for infants in pediatric nursing based on problem-based learning (PBL) and to analyze its effect. Methods: The data used in the study was collected from 79 junior nursing students. For the analysis of the module effect, one group post-test design was applied for measurement of academic achievement. Results: The module for infants is comprised of a 4-hour PBL module. The academic achievement tests are composed of formative (tutor evaluation, self-evaluation) and summative evaluations. The self-evaluation revealed the strong need for PBL and the importance of PBL in the problem solving process and integrative thinking. The mean score of the subjects' learning satisfaction, problem solving process and concept map assessments were all above 50 percent. There was no significant difference in the mean score between the infant PBL and other teaching methods. Conclusion: The PBL proved to be a useful learning method to promote the critical and integrative thinking process.

• 공학교육연구
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• 제15권6호
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• pp.80-85
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• 2012

This study investigates significant factors regarding college freshman engineering students and analyses each factors influence on student satisfaction in the College of Engineering core curriculum. We carried out a survey targeting 505 students who completed their fundamental education for major course learning in the 2011 academic year while attending one college in Gwangju and ruled out inadequate respondents. A total sample size 437 students were analyzed. The seven independent variables are academic fees, academic term period, academic environment of the classroom, learning material content, time of lecture, student sincerity and student need for the program. The dependent variable is fundamental education satisfaction level. As a result of multiple regression analysis, the following factors were found to be significant in the following order: learning material content, time of lecture, student sincerity, student need for the program, academic fees and academic environment of the classroom. On the other side academic term period was not significant. For improving fundamental education satisfaction, there is a need for prudent consideration regarding learning material development and lecture times. Also further investigation should take place for policies necessary for increasing learner motivation and sincerity, and expand appropriate conditions for learners to become self-aware of the education they need within their major.

• Journal of Communications and Networks
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• 제14권5호
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• pp.471-480
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• 2012

Reliable detection of primary user activity increases the opportunity to access temporarily unused bands and prevents harmful interference to the primary system. By extracting a global decision from local sensing results, cooperative sensing achieves high reliability against multipath fading. For the effective combining of sensing results, which is generalized by a likelihood ratio test, the fusion center should learn some parameters, such as the probabilities of primary transmission, false alarm, and detection at the local sensors. During the training period in supervised learning, the on/off log of primary transmission serves as the output label of decision statistics from the local sensor. In this paper, we extend unsupervised learning techniques with an expectation maximization algorithm for cooperative spectrum sensing, which does not require an external primary transmission log. Local sensors report binary hard decisions to the fusion center and adjust their operating points to enhance learning performance. Increasing the number of sensors, the joint-expectation step makes a confident classification on the primary transmission as in the supervised learning. Thereby, the proposed scheme provides accurate parameter estimates and a fast convergence rate even in low signal-to-noise ratio regimes, where the primary signal is dominated by the noise at the local sensors.

• Journal of Information Processing Systems
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• 제15권5호
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• pp.1179-1191
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• 2019

We design an ingenious view-pooling method named learning-based multiple pooling fusion (LMPF), and apply it to multi-view convolutional neural network (MVCNN) for 3D model classification or retrieval. By this means, multi-view feature maps projected from a 3D model can be compiled as a simple and effective feature descriptor. The LMPF method fuses the max pooling method and the mean pooling method by learning a set of optimal weights. Compared with the hand-crafted approaches such as max pooling and mean pooling, the LMPF method can decrease the information loss effectively because of its "learning" ability. Experiments on ModelNet40 dataset and McGill dataset are presented and the results verify that LMPF can outperform those previous methods to a great extent.