• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.7
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• pp.1521-1528
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• 2010

This paper examines technical writing and teaching methods based on the perspectives of the complex learning system theory. So, the paper first discusses the constituent elements and characteristics of the complex learning system theory and continues to examine the potential of applying the complex learning system theory to new teaching methods. As a result, not only did the research expand the approach methods of providing technical writing education but also confirmed the potential of actual implementation. Such results will provide a leeway to start applying new teaching methods for technical writing education. Furthermore, the paper proposes more detailed case studies related to this topic as well as development of this research to produce textbooks and other higher level researches.

• Communications for Statistical Applications and Methods
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• v.29 no.2
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• pp.177-191
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• 2022

This paper addresses the use of machine learning methods for causal estimation of treatment effects from observational data. Even though conducting randomized experimental trials is a gold standard to reveal potential causal relationships, observational study is another rich source for investigation of exposure effects, for example, in the research of comparative effectiveness and safety of treatments, where the causal effect can be identified if covariates contain all confounding variables. In this context, statistical regression models for the expected outcome and the probability of treatment are often imposed, which can be combined in a clever way to yield more efficient and robust causal estimators. Recently, targeted maximum likelihood estimation and causal random forest is proposed and extensively studied for the use of data-adaptive regression in estimation of causal inference parameters. Machine learning methods are a natural choice in these settings to improve the quality of the final estimate of the treatment effect. We explore how we can adapt the design and training of several machine learning algorithms for causal inference and study their finite-sample performance through simulation experiments under various scenarios. Application to the percutaneous coronary intervention (PCI) data shows that these adaptations can improve simple linear regression-based methods.

• Korean Journal of Radiology
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• v.22 no.10
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• pp.1697-1707
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• 2021

The recent introduction of various high-dimensional modeling methods, such as radiomics and deep learning, has created a much greater diversity in modeling approaches for survival prediction (or, more generally, time-to-event prediction). The newness of the recent modeling approaches and unfamiliarity with the model outputs may confuse some researchers and practitioners about the evaluation of the performance of such models. Methodological literacy to critically appraise the performance evaluation of the models and, ideally, the ability to conduct such an evaluation would be needed for those who want to develop models or apply them in practice. This article intends to provide intuitive, conceptual, and practical explanations of the statistical methods for evaluating the performance of survival prediction models with minimal usage of mathematical descriptions. It covers from conventional to deep learning methods, and emphasis has been placed on recent modeling approaches. This review article includes straightforward explanations of C indices (Harrell's C index, etc.), time-dependent receiver operating characteristic curve analysis, calibration plot, other methods for evaluating the calibration performance, and Brier score.

• Journal of Digital Convergence
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• v.18 no.6
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• pp.45-52
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• 2020

This study ranked the degree to which flipped learning contributes to each learning area and, in contrast, to quantitatively examine how effectively these learning methods are used in flipped learning, had four-year university computer majors receive flipped learning. Existing flipped learning experiments have proven effectiveness, while there are also negative effects on effectiveness, which has led to a lot of debate. Effective experiments and classes therefore require more research and an accurate understanding of flipped learning. Analysis of the 123 samples recruited shows that flipped learning contributes to learning is in order of self-directing, collaboration, watching videos, and learning by teachers. Regression analysis of the degree to which learning method affects flipped learning effectiveness resulted in order of self-directed learning, lecture videos, and collaborative learning. This shows that flipped learning not only has the greatest influence on self-directed learning, but also self-directed learning has the greatest influence on flipped learning. It can also see that a collaborative learning and the role of video to prior learning tool is important. Through this study, we hope to understand flipped learning correctly and set learning methods and achievement goals. It is necessary to analyze the interaction between flipped learning and subdivided classroom activities.

• Journal of the Korean Society of School Health
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• v.25 no.1
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• pp.122-132
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• 2012

Purpose: The purpose of this study is to determine the effectiveness of cooperative learner-centered methods of sex education. Methods: This study was carried out on 5th grade elementary school students in D-district. Nine classes were divided into 3 groups using each different teaching methods: group A (a cooperative learning), group B (a lecture) and group C (a control group for a comparison). The study period was from Oct. 17 to Dec. 2 in 2011. Both groups A and B received sex education lessons for 40 minutes for 4 weeks and were tested their sex knowledge and attitude to compare the differences. Results: The scores of sex knowledge for all three groups were increased and their sex attitude was increased as well. The points of sex knowledge between pre and post test in group A are greater than the group B's. Thus, the cooperative learning approach with Group A was more effective to improve student's sex knowledge. But the difference between the sex attitude scores was not statistically significant. Group A and B showed a positive improvement in both their sex knowledge and attitudes compared with the control group. Conclusion: This experiment shows that an active teaching methods is more effective to improve student sex knowledge than a passive approach. Thus, a cooperative learning method results in increases of both student's sex knowledge and interests in learning sex education. It needs to develop more diverse teaching methods and programs on sex education that are more systematic and tailored.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1072-1075
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• 2005

This paper presents that TD method is applied to the human adaptive devices for smart home with context awareness (or recognition) technique. For smart home, the very important problem is how the appliances (or devices) can adapt to user. Since there are many humans to manage home appliances (or devices), managing the appliances automatically is difficult. Moreover, making the users be satisfied by the automatically managed devices is much more difficult. In order to do so, we can use several methods, fuzzy controller, neural network, reinforcement learning, etc. Though the some methods could be used, in this case (in dynamic environment), reinforcement learning is appropriate. Among some reinforcement learning methods, we select the Temporal Difference learning method as a core algorithm for adapting the devices to user. Since this paper assumes the environment is a smart home, we simply explained about the context awareness. Also, we treated with the TD method briefly and implement an example by VC++. Thereafter, we dealt with how the devices can be applied to this problem.

• Journal of the Semiconductor & Display Technology
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• v.9 no.4
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• pp.99-102
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• 2010

In this study, the 3- dimensional (3-D) learning contents are suggested using 'Augmented Reality' instead of existing 2-dimensional (2-D) learning methods. At the present, there are some 2-D learning methods using texts, image, pictures, and videos called e-learning. However, these one-way 2-D methods have some disadvantages such as declining learner's immersion and concentration. Thus, the 3-D learning contents using 'Augmented Reality' are suggested to compensate the disadvantages. According to the development of information technology (IT), the augmented reality has many applications to the era of ubiquitous. However, there are some disadvantages when learners use these contents as following; non-augmenting by partially hiding from makers and declining concentration by patterns of the makers. In this study, the beneficial marker which can solve this non-augmenting phenomenon is suggested.

• Journal of the Society of Naval Architects of Korea
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• v.56 no.6
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• pp.473-479
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• 2019

Welding is one of the most popular joining methods and most welding quality estimation methods are executed using joined material. This paper propose welding quality estimation methods using dynamic current, voltage and resistance which are obtained during welding in real time. There are many kinds of welding method. Among them, we focused on the projection welding and gathered dynamic characteristics from two different types of projection welding. For image learning, graphs are drawn using obtained current, voltage and resistance, and the graphs are converted to images. The images are labeled with two sub-categories - normal and defect. For deep learning of images obtained from welding, Convolutional Neural Network (CNN) is applied, and Tensorflow was used as a framework for deep learning. With two resistance welding test datasets, we conclude that the Convolutional Neural Network helps in predicting the welding quality.

• Proceedings of the Korean Institute of Interior Design Conference
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• 2005.05a
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• pp.281-282
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• 2005

The present design, which is the result of English Zone Project for 'I' Girls' High School in Yeonsu dong, Incheon, purposed to produce atmosphere like a cafe so that students can attempt more comfortable and diverse learning methods, breaking away from the structure and atmosphere of traditional language labs while providing functions such as experiential learning, teaching learning and native speaker conversation. In addition, it applied colors close to primary colors so that students throw away their fixed idea of language lab as a special class and access it easily at any time. Moreover, it was designed for the maximum changeability using foldable and portable furniture so that various types of group study can be performed. Ultimately the design project is expected to suggest methods of experiential learning distinguished from existing knowledge delivering education as it provides teaching learning methods beyond simple interior design.

• Journal of Fisheries and Marine Sciences Education
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• v.23 no.1
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• pp.92-104
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• 2011

Korea is a high level of ICT infrastructure Construction in the OECD's PISA 2006. However, the purpose using of ICT was analyzed for the sake of the interest. They have been emphasized a algorithm-based computer education in conference that it was attended by government, industry and university officials. We designed an algorithm curriculum by analyze a case in international ICT training courses and research. And we were proposed various methods, such as web-based contents, play-based programs, outdoor activities and educational programming language learning for algorithm learning at levels of elementary and middle school students.