• Journal of The Korean Association For Science Education
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• v.26 no.4
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• pp.546-558
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• 2006

The purpose of this study was to identify heuristically how abduction was used in a context of solving an earth-environmental problem. Thirty two groups of participants with different institutional backgrounds, i,e., inservice earth science teachers, preservice science teachers, and high school students, solved an open-ended earth-environmental problem and produced group texts in which their ways of solving the problem were written, The inferential processes in the texts were rearranged according to the syllogistic form of abduction and then analyzed iteratively so as to find thinking strategies used in the abductive reasoning. The result showed that abduction was employed in the process of solving the earth-environmental problem and that several thinking strategies were used for inferring rules from which abductive conclusions were drawn. The strategies found included data reconstruction, chained abduction, adapting novel information, model construction and manipulation, causal combination, elimination, case-based analogy, and existential strategy. It was suggested that abductive problems could be used to enhance students' thinking abilities and their understanding of the nature of earth science and earth-environmental problems.

• The Journal of the Convergence on Culture Technology
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• v.10 no.1
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• pp.603-608
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• 2024

Nonresponse and missing values are caused by sample dropouts and avoidance of answers to surveys. In this case, problems with the possibility of information loss and biased reasoning arise, and a replacement of missing values with appropriate values is required. In this paper, as an alternative to missing values imputation, we compare several replacement methods, which use mean, linear regression, random forest, K-nearest neighbor, autoencoder and denoising autoencoder based on deep learning. These methods of imputing missing values are explained, and each method is compared by using continuous simulation data and real data. The comparison results confirm that in most cases, the performance of the random forest imputation method and the denoising autoencoder imputation method are better than the others.

• Journal of the Korea Computer Graphics Society
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• v.23 no.3
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• pp.19-29
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• 2017

When a fixed-sized memory allocation method is used for sparse volume data, a considerable memory space is in general wasted, which becomes more serious for a large volume of high resolution. In this paper, in order to reduce such unnecessary memory consumption, we propose a volume representation method to store mostly voxels that represent valid information rather than all voxels in a fixed volume space. Then our method is compared with the conventional static memory allocation method, an octree-based representation, and a voxel hashing method in terms of memory usage and computation speed. In particular, we compare the proposed method and the voxel hashing method with respect to implementation of the GPU-based Marching Cubes algorithm.

• The Journal of the Acoustical Society of Korea
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• v.13 no.2E
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• pp.26-31
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• 1994

A new feature extraction technique utilizing strange attractor and artificial neural network for speaker recognition is presented. Since many signals change their characteristics over long periods of time, simple time-domain processing techniques should e capable of providing useful information of signal features. In many cases, normal time series can be viewed as a dynamical system with a low-dimensional attractor that can be reconstructed from the time series using time delay. The reconstruction of strange attractor is described. In the technique, the raw signal will be reproduced into a geometric three dimensional attractor. Classification decision for speaker recognition is based upon the processing or sets of feature vectors that are derived from the attractor. Three different methods for feature extraction will be discussed. The methods include box-counting dimension, natural measure with regular hexahedron and plank-type box. An artificial neural network is designed for training the feature data generated by the method. The recognition rates are about 82%-96% depending on the extraction method.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.6
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• pp.81-87
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• 1998

This paper proposes an efficient face recognition system using phase difference between the face images. We use a Karhunen-Loeve transform for image compression and reconstruction, and obtain the phase difference by using normalized inner product of the two compressed images. The proposed system is rotation and light-invariant due to using the normalized phase difference, and somewhat shift-invariant due to applying the cosine function. The faster recognition than the conventional system and incremental training is possible in the proposed system. Simulations are conducted on the ORL images of 40 persons, in which each person has 10 facial images, and the result shows that the faster recognition than conventional recognizer using convolution network under the same recognition error rate of 8% does.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.1
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• pp.65-74
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• 2012

In this paper, we explore the application of 2-D dual-tree discrete wavelet transform (DDWT), which is a directional and redundant transform, for image coding. DDWT introduces limited redundancy and allows the transform to provide approximate shift invariance and directionally selective filters while preserving the usual properties of perfect reconstruction and computational efficiency with good well-balanced frequency responses. Also, quincunx lattice yields a non separable 2D-wavelet transform, which is also symmetric in both horizontal and vertical direction. And non-separable wavelet transformation can generate sub-images of multiple degrees rotated versions. The proposed 2-D non-separable DDWT can provide efficient approximation for directional features of images schemes, such as edges and contours in images that are not aligned with the horizontal or vertical direction. Finally, non-separable image processing using DDWT services good performance.

• 전자공학회논문지 IE
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• v.43 no.4
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• pp.105-114
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• 2006

In this paper, 3D input and output systems for a web-based real-time 3D video communication system using IEEE 1394 digital cameras, Intel Xeon Server system and Microsoft Directshow library is proposed. And some conditions for optimizing the operations of the stereo camera, 3D display and signal processing system are analyzed. Input & output systems are carefully selected, which can satisfy the required optimization conditions and the final 3D video communication system is implemented by using three optimized devices. The overall control system is developed with Microsoft Visual C++.Net and Microsoft DirectX 9.1 SDK. Some experimental results show that the observer can feel the natural presence from multi-view(4-view) 3D video of server system in real-time and also can feel the natural presence from 3D video of client system and finally suggest an application possibility of the proposed web-based real-time 3D video communication in real fields.

• Journal of KIISE:Computer Systems and Theory
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• v.34 no.8
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• pp.327-336
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• 2007

Lots of effort toward design optimizations have been paid for a cost-effective system design in various ways from a transistor level to RTL designs. In this paper, we propose a bit level optimization of an adder design for expanding its design space. For the bit-level optimization, a heterogeneous adder organization utilizing a mixture of carry propagation schemes is proposed to design a delay-area efficient adder which were not available in an ordinary design space. Then, we develop an optimization method based on Integer Linear Programming to search the expanded design space of the heterogeneous adder. The novelty of the Proposed architecture and optimization method is introducing a bit level reconstruction/recombination of IPs which have same functionality but different speed and area characteristics for producing more find-grained delay-area optimization.

• Journal of the Institute of Convergence Signal Processing
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• v.8 no.1
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• pp.15-21
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• 2007

We propose a 3D modeling method for surface inspection of non-constant velocity moving object. 1'lie laser lines reflect tile surface curvature. We can acquire 3D surface information by analyzing projected laser lines on object. In this paper, we use multi-line laser to improve the single stripe method and high speed of single frame. Binarization and edge extraction of frame image were proposed for robust laser each line extraction. A new labeling method was used for laser line labeling. We acquired some feature points for image matching from the frame data and juxtaposed the frames data to obtain a 3D shape image. We verified the superiority of proposed method by applying it to inspect container's damages.

• The KIPS Transactions:PartA
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• v.10A no.2
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• pp.149-156
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• 2003

In the latest medical world, the attempt of reconstructing anatomical human body system using computer graphics technology awakes people's interests. Actually, this trial has been made in dentistry too. There are a lot of practicable technology fields using computer graphics in dentistry For example, 3D visualization and measurement of dental data, detection of implant location, surface reconstruction for restoring artificial teeth in prostheses and relocation of teeth in orthodontics can be applied. In this paper, we propose methods for definitely detecting the geometric features of teeth such as cusp, ridge, fissure and pit, which have been used as most important characteristics in dental applications. The proposed methods are based on the approximate curvatures that are measured on a 3D tooth model made by scanning an impression. We also give examples of the geometric features detected by using the proposed methods. Comparing to other traditional methods visually, the methods are very useful in detecting more accurate geometric features.