• Smart Structures and Systems
• /
• v.32 no.2
• /
• pp.111-121
• /
• 2023

This study proposes an automated assembly performance evaluation method for prefabricated steel structures (PSSs) using machine learning methods. Assembly component images were segmented using a modified version of the receptive field pyramid. By factorizing channel modulation and the receptive field exploration layers of the convolution pyramid, highly accurate segmentation results were obtained. After completing segmentation, the positions of the bolt holes were calculated using various image processing techniques, such as fuzzy-based edge detection, Hough's line detection, and image perspective transformation. By calculating the distance ratio between bolt holes, the assembly performance of the PSS was estimated using the k-nearest neighbors (kNN) algorithm. The effectiveness of the proposed framework was validated using a 3D PSS printing model and a field test. The results indicated that this approach could recognize assembly components with an intersection over union (IoU) of 95% and evaluate assembly performance with an error of less than 5%.

• Journal of Fisheries and Marine Sciences Education
• /
• v.25 no.4
• /
• pp.915-927
• /
• 2013

This study aimed to discover the affective ability of students by applying a thematic project model concerning the marine field unit of science for third grade middle school students from among diverse methods of realizing STEAM education. Also, based on this, STEAM education is a new type of learning including the process of exploring by oneself, presenting, discussing and mutually evaluating by becoming an independent person in learning As the results of the study are as follows: First, the STEAM class applied with a thematic project model was discovered to promote a learning attitude toward science by learners. Second, the STEAM class applied with a thematic project model was shown to be effective in improving the self-directed learning characteristics of learners. Third, STEAM education applied with a thematic project model was found to promote learners' motivation for learning science. This may be an effective method for learners who have felt difficulty in the science curriculum or have not been interested in the curriculum by triggering voluntary motivation.

• International Journal of Advanced Culture Technology
• /
• v.11 no.1
• /
• pp.283-289
• /
• 2023

AI is bringing about drastic changes not only in the aspect of technologies but also in society and culture. Medical AI based on deep learning have developed rapidly. Especially, the field of medical image analysis has been proven that AI can identify the characteristics of medical images more accurately and quickly than clinicians. Evaluating the latest results of the AI-based medical image processing is important for the implication for the development direction of medical AI. In this paper, we analyze and evaluate the latest trends in AI-based medical image analysis, which is showing great achievements in the field of medical AI in the healthcare industry. We analyze deep learning models for medical image analysis and AI-based medical image segmentation for quantitative analysis. Also, we evaluate the future development direction in terms of marketability as well as the size and characteristics of the medical AI market and the restrictions to market growth. For evaluating the latest trend in the deep learning-based medical image processing, we analyze the latest research results on the deep learning-based medical image processing and data of medical AI market. The analyzed trends provide the overall views and implication for the developing deep learning in the medical fields.

• Educational Technology International
• /
• v.11 no.1
• /
• pp.47-68
• /
• 2010

The purpose of this study was to analyze majors trends and issues of e-Learning curriculum for human resource development in the corporate context. The e-Learning curriculum was chosen as the subject of research consists of 2,710 lectures that were given from 2007 to July 2009 for the recent three years by providing at Ministry of Labor and Korea Research Institute for Vocational Education & Training. In order to investigate trends and issues, it was employed theme analysis which is one of the types of document analysis that approach a qualitative research methodology. As a result of this research, 7 major trends and issues in e-Learning curriculum for HRD in the field of corporate education were drawn; ① Strengthening expertise through learning of job related professional knowledge, ② Cultivation of common & essential knowledge for a job to increase work performance efficiency ③ Organizational management strategy for improving performance, ④ Organizational management and operational strategy for actively responding to environmental changes, ⑤ Leadership as a strategy for cultivating core personnel and field-centered practical leadership. ⑥ Creating a happy workplace through the work-life balance, ⑦ Strengthening global communication skill. Based on these analysis, practicals and theoretical implications of e-Learning professionals and HR researchers for HRD were suggested.

• Journal of Practical Engineering Education
• /
• v.15 no.2
• /
• pp.373-379
• /
• 2023

With the 4th Industrial Revolution, VR/AR technology is developing, and since COVID-19, the use of VR/AR technology is increasing and is being used in various environments. In particular, AR technology can be used in various educational fields and the perception of VR in the educational field and learning satisfaction, problem-solving ability, and self-directed learning ability when using VR were analyzed. It was analyzed that perception of VR and learning satisfaction had a significant correlation at the significance level of 0.001, and problem-solving competency had a significant correlation between learning satisfaction and self-directed learning ability at the significance level of 0.05.

• Geophysics and Geophysical Exploration
• /
• v.26 no.2
• /
• pp.84-93
• /
• 2023

The supervised learning-based deep-learning seismic inversion techniques have demonstrated successful performance in synthetic data examples targeting small-scale areas. The supervised learning-based deep-learning seismic inversion uses time-domain wavefields as input and subsurface velocity models as output. Because the time-domain wavefields contain various types of wave information, the data size is considerably large. Therefore, research applying supervised learning-based deep-learning seismic inversion trained with a significant amount of field-scale data has not yet been conducted. In this study, we predict subsurface velocity models using Laplace-domain wavefields as input instead of time-domain wavefields to apply a supervised learning-based deep-learning seismic inversion technique to field-scale data. Using Laplace-domain wavefields instead of time-domain wavefields significantly reduces the size of the input data, thereby accelerating the neural network training, although the resolution of the results is reduced. Additionally, a large grid interval can be used to efficiently predict the velocity model of the field data size, and the results obtained can be used as the initial model for subsequent inversions. The neural network is trained using only synthetic data by generating a massive synthetic velocity model and Laplace-domain wavefields of the same size as the field-scale data. In addition, we adopt a towed-streamer acquisition geometry to simulate a marine seismic survey. Testing the trained network on numerical examples using the test data and a benchmark model yielded appropriate background velocity models.

• Hwankyungkyoyuk
• /
• v.21 no.3
• /
• pp.1-12
• /
• 2008

This study is aimed at suggesting ways to develop field trip or learning materials focusing on environment of Jeju seashore in order to make an effective field trip. To perform these purposes, the contents and concepts were analyzed from environment-related 'geological unit' of elementary science textbook. Afterwards, the places having the geological features in coincidence with them are chosen, and investigated, and these regions can develop into geological teaming places for field trip. Each teaming spot focuses on understanding and finding out the characteristic geological environment of rock shore, gravel shore, sand shore, shellfish shore, and tideland shore among Jeju shores. When field trip is conducted at the preparatory stage, students can get advance knowledge on geological concepts from textbook. The activity record paper is presented at the field trip stage where students observe geological phenomena on their own. After field trip is finished, the summary stage is given to solve some problems on the basis of the observed contents. The developed data from this research have its regional limits, but is surely useful for teachers who try to plan field trip when they especially choose the right field trip spots, or plan to make the process for field trip preparation of the environmental education. Furthermore, with this survey and activities, students can take the chance to improve the learning effect through their own experience on environment of Jeju seashore.

• Journal of Korean Ophthalmic Optics Society
• /
• v.12 no.1
• /
• pp.75-84
• /
• 2007

In this study, I developed a teaching-learning model using project learning model which makes the most of PIM(Peer & Instructor Mentoring), Presentation contest, and unification of courses on the field ophthalmic optics. There were several conclusion as followings;. The teaching-learning model considering the unification and organic connections among subjects was efficient to the students' academic achievement. Peer & instructor mentoring system was helpful for students to accomplish their own learning projects. Project learning model with collaboration was useful for the development of students' self-controled learning ability and communicative ability. Project learning model gave its driving force to the better motivation and to the goal achievement. Project learning model was instructive for building up the related theories and concepts on the students' major. In conclusion, project learning model mixed subjects with festival, can be a alternative teaching-learning model.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.13 no.4
• /
• pp.283-292
• /
• 2020

Artificial intelligence, which is one of the representative images of the 4th industrial revolution, has been highly recognized since 2016. This paper analyzed domestic paper trends for 'Artificial Intelligence', 'Machine Learning', and 'Deep Learning' among the domestic papers provided by the Korea Academic Education and Information Service. There are approximately 10,000 searched papers, and word count analysis, topic modeling and semantic network is used to analyze paper's trends. As a result of analyzing the extracted papers, compared to 2015, in 2016, it increased 600% in the field of artificial intelligence, 176% in machine learning, and 316% in the field of deep learning. In machine learning, a support vector machine model has been studied, and in deep learning, convolutional neural networks using TensorFlow are widely used in deep learning. This paper can provide help in setting future research directions in the fields of 'artificial intelligence', 'machine learning', and 'deep learning'.

• Journal of Korean Elementary Science Education
• /
• v.38 no.1
• /
• pp.43-54
• /
• 2019

In order to organize various places for science experience study, this study gathered and analyzed prior research on science experience study and various science experience perated in school. To that end, a total of 162 relevant prior studies of literature published from 2000 to 2016 were collected and 2,201 cases of science experience study conducted in 2015 were collected and analyzed. The place where the science experiential learning was done is divided into three areas of natural ecology, cultural history, facility experiential learning study, and the characteristics of participating subjects are examined. In terms of the number of articles published in the field of science-related experiential learning areas, 83 ecological experience study sites (51.2%), facilities institution experience study sites 56 (34.6%), and cultural history experience study books 23 (14.2%). Through this study, it was found out that research tendency to analyze science - related attitudes became prominent by setting study subjects using natural objects around and learning to play while playing and playing in nature. There was also an analysis by subjects of participation in science related experience learning centers. Cultural history experiential learning field was significantly lower than previous studies. In the lower grades, nature ecological experience learning was mainly performed. Combining the above findings, it can provide implications for the development of science-related experience activities. First, it is necessary to develop a technology-related experience learning center using local community resources. Second, it is necessary to expand the culture and history experience learning center related to science. Third, we need an education support center to support the expansion and operation of such a technology-related cultural history learning center.