• Journal of the Korean School Mathematics Society
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• v.14 no.4
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• pp.443-458
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• 2011

There has been a lively discussion on improving Korean students' academic achievement and the imbalance in their recognition of the value of mathematics. In this context, there is a need for a program that enables the majority students who regards mathematics as a subject for the entrance examination to recognize the practicality and historicity of mathematics. Educational books on mathematics in everyday life or the history of mathematics are also expected to serve as an effective tool. In addition, Web 2.0 Map is another means of representing mathematics in everyday life and the history of mathematics in connection with the practical context. The active storytelling process in which mathematics in the practical context in mathematical educational books is represented in Web 2.0 Map is expected to help to understand in depth the practicality and historicity of mathematics. Nevertheless, mathematical educational books and Web 2.0 Map may lead to a considerable variety of outcomes and speeds if carrying out tasks depending on the student's competence and may have practical difficulties in being operated in class. These concerns, however, can be resolved through the creative activity programs adopted in conformance with the 2009 revised curriculum. Therefore, this study intends to develop a program for creating mathematical story maps through mathematical educational books and the Mashup of Web 2.0 Map in accordance with the process of developing activity programs. This study also intends to determine its effectiveness in enabling students to recognize the practical and historical values of mathematics.

• Journal of the Korea institute for structural maintenance and inspection
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• v.16 no.5
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• pp.148-160
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• 2012

This study proposed more reasonable prediction models on compressive strength and carbonation of concrete structure and developed a more effective tunnel safety diagnosis and maintenance method through field application of the proposed prediction models. For this study, the Seoul Metro's Line 1 through Line 4 were selected as target structures because they were built more than 30 years ago and have accumulated numerous diagnosis and maintenance data for about 15 years. As a result of the analysis of compressive strength and carbonation, we were able to draw prediction models with accuracy of more than 80% and confirmed the prediction model's reliability by comparing it with the existing models. We've also confirmed field suitability of the prediction models by applying field, the average error of an estimate on compressive strength and carbonation depth was about 20%, which showed an accuracy of more than 80%. We developed a more effective maintenance method using durability prediction Map before field inspection. With the durability prediction Map, diagnostic engineers and structure managers can easily detect the vulnerable points, which might have failed to reach the standard of designed strength or have a high probability of corrosion due to carbonation, therefore, it is expected to make it possible for them to diagnose and maintain tunnels more effectively and efficiently.

• Electronics and Telecommunications Trends
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• v.35 no.5
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• pp.112-122
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• 2020

In 3D computer graphics, a depth map is an image that provides information related to the distance from the viewpoint to the subject's surface. Stereo sensors, depth cameras, and imaging systems using an active illumination system and a time-resolved detector can perform accurate depth measurements with their own light sources. The 3D image information obtained through the depth map is useful in 3D modeling, autonomous vehicle navigation, object recognition and remote gesture detection, resolution-enhanced medical images, aviation and defense technology, and robotics. In addition, the depth map information is important data used for extracting and restoring multi-view images, and extracting phase information required for digital hologram synthesis. This study is oriented toward a recent research trend in deep learning-based 3D data analysis methods and depth map information extraction technology using a convolutional neural network. Further, the study focuses on 3D image processing technology related to digital hologram and multi-view image extraction/reconstruction, which are becoming more popular as the computing power of hardware rapidly increases.

• Journal of Broadcast Engineering
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• v.26 no.6
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• pp.714-724
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• 2021

The point cloud content is immersive content recorded by acquiring points and colors corresponding to the real environment and objects having three-dimensional location information. When a point cloud content consisting of three-dimensional points having position and color information is enlarged and rendered, the gap between the points widens and an empty hole occurs. In this paper, we propose a method for improving the quality of point cloud contents through inverse transformation-based interpolation using depth information for holes by finding holes that occur due to the gap between points when expanding the point cloud. The points on the back are rendered between the holes created by the gap between the points, acting as a hindrance to applying the interpolation method. To solve this, remove the points corresponding to the back side of the point cloud. Next, a depth map at the point in time when an empty hole is generated is extracted. Finally, inverse transform is performed to extract pixels from the original data. As a result of rendering content by the proposed method, the rendering quality improved by 1.2 dB in terms of average PSNR compared to the conventional method of increasing the size to fill the blank area.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.41 no.11
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• pp.1011-1020
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• 2017

This study was conducted to investigate the material properties of stainless steel 316L specimens of untreated and UNSM treated material, hydrogen attacked material(100 bar, $300^{\circ}C$ at 120 h) and UNSM treated hydrogen attacked material at room temperature. Results demonstrated that the hydrogen attacked materials showed a tendency toward a slightly decreased fatigue strength, while the hydrogen embrittlement effect was smaller than the S-N curve of conventional untreated material. As compared to untreated material, the fatigue limit of the UNSM treated material increased by 43.8%, while it was 57.1％ higher in the UNSM treated hydrogen attacked material than in untreated hydrogen attacked material. The plastic deformation layer was ${\sim}152{\mu}m$ thick, as confirmed by maps showing the level of local plastic deformation affected by the UNSM treatment in three ways: an image quality map, inverse pole figure map, and kernel average misorientation map captured via electron back scatter diffraction. Owing to hydrogen embrittlement, about 90％ of surface cracks were smaller than the average grain size of $35{\mu}m$.

• Tunnel and Underground Space
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• v.33 no.6
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• pp.508-518
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• 2023

This paper presents a new approach for the automatic mapping of discontinuities in a tunnel face based on its 3D digital model reconstructed by LiDAR scan or photogrammetry techniques. The main idea revolves around the identification of discontinuity areas in the 3D digital model of a tunnel face by segmenting its 2D projected images using a deep-learning semantic segmentation model called U-Net. The proposed deep learning model integrates various features including the projected RGB image, depth map image, and local surface properties-based images i.e., normal vector and curvature images to effectively segment areas of discontinuity in the images. Subsequently, the segmentation results are projected back onto the 3D model using depth maps and projection matrices to obtain an accurate representation of the location and extent of discontinuities within the 3D space. The performance of the segmentation model is evaluated by comparing the segmented results with their corresponding ground truths, which demonstrates the high accuracy of segmentation results with the intersection-over-union metric of approximately 0.8. Despite still being limited in training data, this method exhibits promising potential to address the limitations of conventional approaches, which only rely on normal vectors and unsupervised machine learning algorithms for grouping points in the 3D model into distinct sets of discontinuities.

• Journal of Korea Multimedia Society
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• v.15 no.6
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• pp.827-836
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• 2012

After successful advent of Microsoft's Kinect, many interactive contents that control user's 3D avatar motions in realtime have been created. However, due to the Kinect's intrinsic IR projection problem, users are restricted to face the sensor directly forward and to perform all motions in a standing-still position. These constraints are main reasons that make it almost impossible for the 3D character to navigate the virtual environment, which is one of the most required functionalities in games. This paper proposes a new method that makes 3D character navigate the virtual environment with highly realistic motions. First, in order to find out the user's intention of navigating the virtual environment, the method recognizes walking-in-place motion. Second, the algorithm applies the motion splicing technique which segments the upper and the lower motions of character automatically and then switches the lower motion with pre-processed motion capture data naturally. Since the proposed algorithm can synthesize realistic lower-body walking motion while using motion capture data as well as capturing upper body motion on-line puppetry manner, it allows the 3D character to navigate the virtual environment realistically.

• Journal of Korea Multimedia Society
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• v.9 no.2
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• pp.244-254
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• 2006

This paper presents an efficient hybrid technique to compact the trie indexing the huge forward table small enough to be stored into cache for speeding up IP lookup. It combines two techniques, an encoding scheme called bit-map and a controlled-prefix expanding scheme to replace slow memory search with few fast-memory accesses and computations. For compaction, the bit-map represents each index and child pointer with one bit respectively. For example, when one node denotes n bits, the bit-map gives a high compression rate by consumes $2^{n-1}$ bits for $2^n$ index and child link pointers branched out of the node. The controlled-prefix expanding scheme determines the number of address bits represented by all root node of each trie's level. At this time, controlled-prefix scheme use a dynamic programming technique to get a smallest trie memory size with given number of trie's level. This paper proposes standard that can choose suitable trie structure depending on memory size of system and the required IP lookup speed presenting optimal memory size and the lookup speed according to trie level number.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.9
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• pp.1214-1219
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• 2018

A variety of VR contents are being introduced as of 2017. VR contents are concentrated in the genre of games and interactive because of the difficulty of $360^{\circ}$ shooting production environment. Live action $360^{\circ}$ VR content has many problems due to the difficulty of the production environment. In this paper, a three - dimensional information value is generated in binocular disparity of a real image by using a re-light technique based on real image data. The generated 3D information values are combined with a technique of converting the depth information into a depth map and a re-light technique by installing virtual lighting on the surface formed in the 3D space. In order to solve the problem of lighting exposure, we apply the technique of re-lighting to the VR production pipeline by comparing and analyzing the result image of actual image and virtual image data.

• Journal of Broadcast Engineering
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• v.21 no.2
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• pp.252-260
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• 2016

The performance of human detection system is affected by camera location and view angle. In 2D image acquired from such camera settings, humans are displayed in different sizes. Detecting all the humans with diverse sizes poses a difficulty in realizing a real-time system. However, if the size of a human in an image can be predicted, the processing time of human detection would be greatly reduced. In this paper, we propose a method that estimates human size by constructing an indoor scene in 3D space. Since the human has constant size everywhere in 3D space, it is possible to estimate accurate human size in 2D image by projecting 3D human into the image space. Experimental results validate that a human size can be predicted from the proposed method and that machine-learning based detection methods can yield the reduction of the processing time.