• ETRI Journal
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• v.38 no.1
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• pp.149-158
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• 2016

In the field of augmented reality technologies, commercial optical see-through-type wearable displays have difficulty providing immersive visual experiences, because users perceive different depths between virtual views on display surfaces and see-through views to the real world. Many cases of augmented reality applications have adopted eyeglasses-type displays (EGDs) for visualizing simple 2D information, or video see-through-type displays for minimizing virtual- and real-scene mismatch errors. In this paper, we introduce an innovative optical see-through-type wearable display hardware, called an EGD. In contrast to common head-mounted displays, which are intended for a wide field of view, our EGD provides more comfortable visual feedback at close range. Users of an EGD device can accurately manipulate close-range virtual objects and expand their view to distant real environments. To verify the feasibility of the EGD technology, subject-based experiments and analysis are performed. The analysis results and EGD-related application examples show that EGD is useful for visually expanding immersive 3D augmented environments consisting of multiple displays.

• Journal of the Korea Society of Computer and Information
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• v.28 no.10
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• pp.67-76
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• 2023

Although deep learning models are making innovative achievements in the field of computer vision, the problem of vulnerability to adversarial examples continues to be raised. Adversarial examples are attack methods that inject fine noise into images to induce misclassification, which can pose a serious threat to the application of deep learning models in the real world. In this paper, we propose a model that detects adversarial examples using differences in predictive values between edge-learned classification models and underlying classification models. The simple process of extracting the edges of the objects and reflecting them in learning can increase the robustness of the classification model, and economical and efficient detection is possible by detecting adversarial examples through differences in predictions between models. In our experiments, the general model showed accuracy of {49.9%, 29.84%, 18.46%, 4.95%, 3.36%} for adversarial examples (eps={0.02, 0.05, 0.1, 0.2, 0.3}), whereas the Canny edge model showed accuracy of {82.58%, 65.96%, 46.71%, 24.94%, 13.41%} and other edge models showed a similar level of accuracy also, indicating that the edge model was more robust against adversarial examples. In addition, adversarial example detection using differences in predictions between models revealed detection rates of {85.47%, 84.64%, 91.44%, 95.47%, and 87.61%} for each epsilon-specific adversarial example. It is expected that this study will contribute to improving the reliability of deep learning models in related research and application industries such as medical, autonomous driving, security, and national defense.

• Korean Institute of Interior Design Journal
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• v.19 no.5
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• pp.3-10
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• 2010

In the history of art and architecture, there are different characteristics in relationship between light and space. Among them, two characteristics seem to be fundamental : The first is that contrast between light and darkness is more articulated. Direct sunlight penetrates into the dark interior space made by heavy masonry structure. This is generally found in the traditional western religious buildings. The second is that light is mixed with darkness and becomes shade. Shade is different from shadow that is usually perceived as the opposite of light. Sunlight is filtered under through the big horizontal roof and rice paper walls in the traditional far-east Asian architecture and becomes weak ambient light. In this shade, there is no strong contrast between light and darkness. This difference is not only originated from the architectural differences, but also originated from the conceptual differences about light, space, and the world in two cultures. This paper tries to study the philosophical, aesthetical backgrounds as well as case examples in art and architecture of two characteristics. Based on the case studies, this paper aims to analyze the main perceptual structure. Finding the relationship between light, space, and human body by making three dimensional models is the crucial analysis method of this research. Although in real life and experiencing the world, these two characteristics are not clearly separated, comparative study based on different cultures gives opportunity to think of diverse perspectives on light and space.

• Research in Mathematical Education
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• v.15 no.3
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• pp.251-259
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• 2011

Metaphor is the main representations of teachers' practical knowledge, which can help students to understand mathematics better. Through the recording and quantitative analysis of video cases of expert teachers in mathematics classroom, there are some results after analysis: 1) Teachers use many metaphors in the classroom and most of that are structural-ontological metaphors, which takes a certain period of time. 2) Teachers use the metaphors mainly in the teaching process of introduce and explore by the form of question-answer. 3) During the process of concept teaching, the metaphors from the real-world examples can promote the students have more motivation to study. During the process of procedure teaching, the metaphors from similar materials can promote the students to understand the operational skill better.

• School Mathematics
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• v.3 no.2
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• pp.373-399
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• 2001

The function is a basic and key concept to understand mathematical problems. However, many students have difficulties to expand the knowledge to other related concepts and to transfer the knowledge to real world problems. The reasons for the problem may be that the concept of function is taught by simplified and abstracted formula without fully understanding of the reasoning process. Also, the examples for the concepts are artificial and not related to students' experiences. Situated learning theory provides great implications to solve these problems. So, this study was designed to teach the concept of function more meaningful to students by appling situated learning theory. Thirty-eight middle school students were participated in this study. Students were provided the instruction designed according to the principles of situated learning theory. Then, they were asked to complete attitude survey questionnair and a performance assessment task. The result showed that the instruction based on situated learning theory was useful to Promote students' understanding and motivation for learning. More implications of the study was provided in the paper.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2000.10a
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• pp.272-277
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• 2000

The classical queuing analysis has been tremendously useful in doing capacity planning and performance prediction, However, in many real-world cases. it has found that the predicted results form a queuing analysis differ substantially hem the actual observed performance. Specially, in recent years, a number of studies have demonstrated that for some environments, the traffic pattern is self-similar rather than Poisson. In this paper, we study these self-similar traffic characteristics and the definition of self-similar stochastic processes. Then, we consider the examples of self-similar data traffic, which is reported from recent measurement studies. Finally, we wish you that it makes out about the characteristics of actual data traffic more easily.

• Journal of applied mathematics & informatics
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• v.4 no.1
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• pp.135-135
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• 1997

Times series modeling plays an important role in the field of engineering, Statistics, Biomedicine etc. Model identification is one of crucial steps in the modeling of an AutoRegreesive Moving Average(ARMA(p, q)) process for real world problems. Many techniques have been developed in the literature (Salas et al., McLeod et al. etc.) for the identification of an ARMA(p, q) Model. In this paper, a new technique called The Generalised Parameters Technique is formulated for seasonal and non-seasonal ARMA model identification. This technique is very simple and can e applied to any given time series. Initial estimates of the AR parameters of the ARMA model are also obtained by this method. This model identification technique is validated through many theoretical and simulated examples.

• Structural Engineering and Mechanics
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• v.52 no.4
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• pp.815-827
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• 2014

Buckling optimization of laminated composite plates is significant as they fail because of buckling under in-plane compressive loading. The plate is usually modeled without cutout so that the buckling strength is found analytically using classical laminate plate theory (CLPT). However in real world applications, the composite plates are modeled with cutouts for getting them assembled and to offer the provisions like windows, doors and control system. Finite element analysis (FEA) is used to analyze the buckling strength of the plate with cutouts and it leads to high computational cost when the plate is optimized. In this article, a genetic algorithm based optimization technique is used to optimize the composite plate with cutout. The computational time is highly reduced by replacing FEA with artificial neural network (ANN). The effectiveness of the proposed method is explored with two numerical examples.

• International Journal of Reliability and Applications
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• v.12 no.1
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• pp.49-60
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• 2011

The geometric process (GP) has been widely used for modeling failure and repair time sequences of repairable systems. The GP is mathematically tractable but restrictive in reliability applications since it actually assumes that the mean function of inter-failure times sequence asymptotically decreases to zero; and the mean function of successive repair times sequence asymptotically increases to infinity. This is generally unrealistic from an engineering perspective. This paper presents three extended GP models for modeling reliability deterioration and improvement (or growth) process. The extensions maintain the advantage of mathematical tractability of GP model. Their usefulness and appropriateness are illustrated with three real-world examples.

• Journal of Educational Research in Mathematics
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• v.12 no.1
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• pp.17-27
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• 2002

To solve the addition word problems provides young children the chance to learn about and exercise in problem solving. This paper focuses on two aspects to be considered in addition word problems: the homogeneity of objects and the variety of contexts. The homogeneity of objects involved in addition word problems has to be kept in the following reasons: concept of unit, effectiveness of information, prevention of inappropriate variety, inconsistency of mathematics with real world, continuity between elementary and secondary mathematics. And for the variety of contexts, the additive structure proposed by G. Vergnaud, can be considered: composition, transformation, relation of comparison, composition of two transformations, composition of two relations, transformation of a relation. According to this structure, some examples, which contain homogeneous objects, were extracted from the elementary school mathematics textbooks.