• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.4
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• pp.1738-1764
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• 2019

With the advent of big data, deep learning technology has become an important research direction in the field of machine learning, which has been widely applied in the image processing, natural language processing, speech recognition and online advertising and so on. This paper introduces deep learning techniques from various aspects, including common models of deep learning and their optimization methods, commonly used open source frameworks, existing problems and future research directions. Firstly, we introduce the applications of deep learning; Secondly, we introduce several common models of deep learning and optimization methods; Thirdly, we describe several common frameworks and platforms of deep learning; Finally, we introduce the latest acceleration technology of deep learning and highlight the future work of deep learning.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.648-651
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• 1997

This paper proposes methods for the cooperative control of multiple mobile robots and constructs a robotic soccer system in which the cooperation will be implemented as a pass play of two robots. To play a soccer game, elementary actions such as shooting and moving have been designed, and Q-learning, which is one of the popular methods for reinforcement learning, is used to determine what actions to take. Through simulation, learning is successful in case of deliberate initial arrangements of ball and robots, thereby cooperative work can be accomplished.

• Korean Journal of Remote Sensing
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• v.39 no.4
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• pp.371-393
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• 2023

Crack detection in structures plays a vital role in ensuring their safety, durability, and reliability. Traditional crack detection methods sometimes need significant manual inspections, which are laborious, expensive, and prone to error by humans. Deep learning algorithms, which can learn intricate features from large-scale datasets, have emerged as a viable option for automated crack detection recently. This study presents an in-depth review of crack detection methods used till now, like image processing, traditional machine learning, and deep learning methods. Specifically, it will provide a comparative analysis of crack detection methods using deep learning, aiming to provide insights into the advancements, challenges, and future directions in this field. To facilitate comparative analysis, this study surveys publicly available crack detection datasets and benchmarks commonly used in deep learning research. Evaluation metrics employed to check the performance of different models are discussed, with emphasis on accuracy, precision, recall, and F1-score. Moreover, this study provides an in-depth analysis of recent studies and highlights key findings, including state-of-the-art techniques, novel architectures, and innovative approaches to address the shortcomings of the existing methods. Finally, this study provides a summary of the key insights gained from the comparative analysis, highlighting the potential of deep learning in revolutionizing methodologies for crack detection. The findings of this research will serve as a valuable resource for researchers in the field, aiding them in selecting appropriate methods for crack detection and inspiring further advancements in this domain.

• Journal of Digital Convergence
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• v.11 no.2
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• pp.51-58
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• 2013

There is an increasing discussion about new teaching and learning methods in smart education environment due to the dissemination of smart devices. In this trend, in order to understand the smart education system, this study analyzed the domestic and foreign cases in K-12 smart education based on CTLA (Creation Teaching Learning Assessment) model through access to educational contents, environments, methods, and its curriculums. The teaching and learning methods in smart education are analyzed in foreign cases, domestic cases, and teaching-learning models presenting the positive part of the currently being implemented smart education and the further research for its improvement. Accordingly this study contributes to the specific formulation and successful realization of smart education.

• Journal of Korean Biological Nursing Science
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• v.20 no.2
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• pp.92-102
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• 2018

Purpose: The purpose of this study was to analyze the current status of studies related to the learning methods of biological nursing subjects in Korea. Methods: Five databases (KoreaMed, KMbase, NDSL, KISS, KiSTi) and grey literature were searched prior to February 2018. A total 12 studies met the inclusion criteria including 11 articles and 1 proceeding. Results: We included five experimental studies, five non-experimental studies, and two mixed method studies. First, most of the studies that applied a learning method focused on the subject of human anatomy and physiology; team-based learning was the method that was utilized the most. Second, the necessity of well-designed research was confirmed because the quality of included studies was low. Third, the research variables identified were mainly concentrated on the affective domain, and included satisfaction, motivation, self-efficacy, self-directed learning, confidence, attitude. We confirmed the need to develop a learning program that can also improve the cognitive and psychomotor domain variables in future research. Conclusion: The results of this study suggest that further research should be conducted with consideration the domain of research variables evenly. In addition, future studies should apply various learning methods and included randomized controlled trials.

• Journal of the Korea Society of Computer and Information
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• v.23 no.6
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• pp.15-21
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• 2018

The purpose of this study is to design a Content-based Korean Class model using Flipped learning for foreign students. The class model that presents on this paper will lead the language learning through content learning, also it will be enable the student more active and to have an initiative in the class. Prior to designing a Content-based Korean Class model using Flipped learning, the concepts and educational significance and characteristics of flip learning were reviewed through previous studies. Then, It emphasizes the necessity of teaching method adapting Flipped learning to Content-based teaching method in Korean language education. It also suggests standards and principles of composition in Contents-based teaching method using Flipped learning. After designing the instructional model based on the suggested standards and principles, it presents a course of instruction about how learning methods, contents and activities should be done step by step. The Content-based Korean class model using the Flipped learning will be an alternative approach to overcome the limitations of teacher-centered teaching methods and lecture-teaching methods which are the dominant of present classroom environment.

• Journal of Technologic Dentistry
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• v.44 no.4
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• pp.132-143
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• 2022

Purpose: The study aims to analyze differences in the satisfaction level of dental technology students regarding in-person and online classes. It also aims to provide fundamental resources for the improvement of major subject class methods that will improve students' self-directed learning abilities, thereby affecting their class satisfaction. Methods: In this study, a self-administered questionnaire was conducted from November 8 to November 30, 2021, for 256 dental technology students. The collected data were analyzed using the IBM SPSS Statistics ver. 21.0 statistical program. Frequency and percentage, mean, standard deviation, t-test, ANOVA, post-hoc test, correlation analysis, and linear regression analysis were performed to analyze the data. Results: In the self-directed learning abilities, the attitude of the learners was shown to have the highest positive (+) correlation in both in-person and online classes, with a statistically significant effect (p<0.001) on class satisfaction in major subject classes. Moreover, the explanatory power of the model was 52.2% and 39.7%, respectively. Conclusion: We concluded from the study that there is a need for professors to improve teaching methods to increase learners' self-directed learning competence, through problem-based learning, discussion learning, team-based collaborative learning, and mentor-mentee learning, thereby enabling learners to lead classes themselves.

• Journal of Digital Convergence
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• v.7 no.3
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• pp.49-60
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• 2009

The aim of this study was to develop a model for teaching-teaming by applying Ubiquitous at a learning experience field, in which connect characteristics of both ubiquitous application learning and experience teaming, making use of them. A literature survey of concepts was conducted, with the main areas to find out relationships between ubiquitous application learning and experience learning. Experience learning by applying ubiquitous learning methods maximizes its efficiency of experience learning in considering ubiquitous learning methods's characteristics of dynamic, interaction, sharing. Also it makes communications through positive participation and active interaction, and leads to a process of internal examination. The research data suggests that critical factors of experiencing learning applying ubiquitous are acquiring information and memory, information integration and exquisiteness, emotional and social activity, producing activity, help activity.

• Journal of Engineering Education Research
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• v.23 no.6
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• pp.40-50
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• 2020

This paper proposes learning modules as a kind of integrated instruction model for soft skills program outcomes to enable CEA. Learning modules consist of course learning objectives(outcomes) described in detail, learning content(elements), learning activities(teaching learning methods), evaluation methods, evaluation rubrics so that they can be evaluated based on the performance criteria of the program learning outcomes. The unit of time for the learning module is 50 minutes. If this learning module is applied, it is expected that the soft skill program outcomes can be evaluated in the technical course. As a result of the expert feasibility study, the positive answers were much higher than the negative answers in most of the questions about the composition of the learning module or the method of managing the class.

• Journal of Digital Convergence
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• v.14 no.10
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• pp.339-348
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• 2016

The purpose of this study was to identify the Kolb's learning style and preference for instructional methods of undergraduate nursing students. Data were collected from 174 students at a university in D city using a structured questionnaire from October 19 to October 21 2015. Learning style ratio of nursing students was accommodator 34.5%, converger 33.9%, assimilator 16.1%, diverger 15.5% and preference scores for instructional methods were discussion 7.27, direct instruction 7.26, peer teaching 7.22, independent study 6.54, project 6.25, instruction through technology 5.77, game 5.45, simulation 4.23. A significant difference was found in experience of flipped learning between four learning styles groups of nursing students. However, there was no significant difference in the preference of instructional methods between the four learning styles groups. Most of the students were in the middle range of the learning styles. The assessment of nursing students' learning styles is expected to help educator to plan teaching strategies.