• Journal of the Korean Operations Research and Management Science Society
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• v.42 no.3
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• pp.1-12
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• 2017

In this paper, we generalize lifted inequalities to a 0-1 mixed-integer bilinear covering set with linear terms. This work is motivated by the observation that Generalized Bilinear Inequality (GBI) occurs in the Branch and Bound process. We find some conditions and prove the subadditivity of lifting functions for lifting to be sequence-independent. Using the theoretical results, we develop facet-defining inequalities for a GBI-defined set through three steps of lifting.

• Proceedings of the IEEK Conference
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• 2002.07b
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• pp.1015-1018
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• 2002

We show how any discrete wavelet transform or two band subband filtering with finite filters can be decomposed onto a finite sequence of simple filtering steps, which we call lifting steps but that are also known as ladder structures, We present a self-contained derivations, building the decomposition from the basic principles such as the Euclidean algorithm, with a focus on a applying it to wavelet filtering. This factorization provides an alternative for the lattice factorization, with the advantage that it can also be used in the bi-orthogonal, i.e, non-unitary case. Lifting leads to a speed-up when compared to the standard implementation. We show that this lifting scheme can be applied in image compression efficiently

• IEIE Transactions on Smart Processing and Computing
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• v.2 no.1
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• pp.1-10
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• 2013

In JPEG2000, the Cohen-Daubechies-Feauveau (CDF) 9/7-tap wavelet filter is implemented using the conventional lifting scheme. On the other hand, this wavelet filter has two problems: the filter coefficients remain complex, and the conventional lifting scheme does not consider the image edges in the coding process. This paper proposes an effective lifting scheme to solve these problems. For this purpose, optimal 9/7-tap wavelet filters were designed in two steps. In the first step, the appropriate filter coefficients were selected. In the second step, a median operator was employed to consider the image edges. The experimental results with the median lifting scheme and the combination of filter optimization with the median lifting show that the proposed methods outperform the well-known CDF 9/7-tap wavelet filter of JPEG2000 on the edge-dominant images.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.4 no.3
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• pp.263-269
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• 2003

This paper focuses on lossy medical image compression methods for medical images that operate on three-dimensional(3D) irreversible integer wavelet transform. We offer an application of the Set Partitioning in Hierarchical Trees(SPIHT) algorithm〔l-3〕to medical images, using a 3-D wavelet decomposition and a 3-D spatial dependence tree. The wavelet decomposition is accomplished with integer wavelet filters implemented with the lifting method, where careful scaling and truncations keep the integer precision small and the transform unitary. As the compression rate increases, the boundaries between adjacent coding units become increasingly visible. Unlike video, the volume image is examined under static condition, and must not exhibit such boundary artifacts. In order to eliminate them, we utilize overlapping at axial boundaries between adjacent coding units. We have tested our encoder on medical images using different integer filters. Results show that our algorithm with certain filters performs as well. The improvement is visibly manifested as fewer ringing artifacts and noticeably better reconstruction of low contrast.

• Korean Journal of Construction Engineering and Management
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• v.13 no.3
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• pp.34-42
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• 2012

Green frame technology intended to facilitate the remodeling of apartment housing complexes in Korea and extend their service life has been developed. Green frame design is a Rahmen structure using composite precast concrete members and, unlike a bearing-wall structure, lifting and installing structural members accounts for major steps of structural construction. Therefore, if green frame structure construction is to be scheduled appropriately, systematic lifting plan needs to be developed in advance. Development of lifting plan also requires unit lifting process of composite PC members (columns and beams) that consist of green frame to be analyzed first. Therefore, this study attempts to analyze the lifting process of composite PC members used in green frame structure. To that end, lifting procedure and time of composite PC column and beam are estimated and applied to a project case to analyze the lifting cycle of reference floor. Outcomes produced herein will be used as key data for development of lifting plan in subsequent green frame structure construction.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.2395-2398
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• 2003

This paper focuses on lossless medical image compression methods for medical images that operate on two-dimensional(2D) reversible integer wavelet transform. We offer an application of the Set Partitioning in Hierarchical Trees(SPIHT) algorithm [1][3][9] to medical images, using a 2D wavelet decomposition and a 2D spatial dependence tree. The wavelet decomposition is accomplished with integer wavelet filters implemented with the lifting method, where careful scaling and truncations keep the integer precision small and the transform unitary. We have tested our encoder on medical images using different integer filters. Results show that our algorithm with certain filters performs as well and sometimes better in lossless coding than previous coding systems using 2D integer wavelet transforms on medical images.

• Journal of the Society of Naval Architects of Korea
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• v.57 no.2
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• pp.114-123
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• 2020

A high-order potential-based panel method based on Green's theorem, with piecewise-linear dipole strength on triangular panels, is formulated for the analysis of potential flow around a three-dimensional wing. Previous low-order panel methods adopt square panels with piecewise-constant dipole strength, which results in inherent errors. Square panels can not represent a high curvature lifting body, such as propellers, since the four vertices of the square panel do not locate at the same flat plane. Moreover the piecewise-constant dipole strength induces inevitable errors due to the steps in dipole strength between adjacent panels. In this paper a high-order panel method is formulated to improve accuracy by adopting a piecewise linear dipole strength on triangular panels. Firstly, the square panels are replaced by triangular panels in order to increase the geometric accuracy in representing the shape of the object with large curvature. Next, the step difference of the dipole strength between adjacent panels is removed by adopting piecewise-linear dipole strength on the triangular panels. The calculated results by the present method is compared with analytical ones for simple non-lifting geometries, such as ellipsoid. The results for an elliptic wing with zero thickness at finite angle of attack are compared with Jordan's results. The comparison shows reasonable agrements for the both lifting and non-lifting bodies.

• Korean Journal of Remote Sensing
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• v.22 no.1
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• pp.49-61
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• 2006

The lifting scheme has been found to be a flexible method for constructing scalar wavelets with desirable properties. In this paper, it is extended to the UDAR data compression. A newly developed data compression approach to approximate the UDAR surface with a series of non-overlapping triangles has been presented. Generally a Triangulated Irregular Networks (TIN) are the most common form of digital surface model that consists of elevation values with x, y coordinates that make up triangles. But over the years the TIN data representation has become an important research topic for many researchers due its large data size. Compression of TIN is needed for efficient management of large data and good surface visualization. This approach covers following steps: First, by using a Delaunay triangulation, an efficient algorithm is developed to generate TIN, which forms the terrain from an arbitrary set of data. A new interpolation wavelet filter for TIN has been applied in two steps, namely splitting and elevation. In the splitting step, a triangle has been divided into several sub-triangles and the elevation step has been used to 'modify' the point values (point coordinates for geometry) after the splitting. Then, this data set is compressed at the desired locations by using second generation wavelets. The quality of geographical surface representation after using proposed technique is compared with the original UDAR data. The results show that this method can be used for significant reduction of data set.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.9 no.1
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• pp.1-9
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• 2009

In this paper, proposed digital image watermarking technique with lifting wavelet transformation. This watermark technique can be easily extended in video content fields. Therefore, we apply this watermark technique to layered depth image structure that is efficient compression method of multi-view video with depth images. This application steps are very simple, because watermark is inserted only reference image. And watermarks of the other view images borrow from reference image. Each view image of multi-view video may be guaranteed authentication and copyright.

• International Journal of Computer Science & Network Security
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• v.21 no.5
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• pp.256-266
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• 2021

The Convolutional Neural Network (CNN) has recently made potential improvements in face verification applications. In fact, different models based on the CNN have attained commendable progress in the classification rate using a massive amount of data in an uncontrolled environment. However, the enormous computation costs and the considerable use of storage causes a noticeable problem during training. To address these challenges, we focus on relevant data trained within the CNN model by integrating a lifting method for a better tradeoff between the data size and the computational efficiency. Our approach is characterized by the advantage that it does not need any additional space to store the features. Indeed, it makes the model much faster during the training and classification steps. The experimental results on Labeled Faces in the Wild and YouTube Faces datasets confirm that the proposed CNN framework improves performance in terms of precision. Obviously, our model deliberately designs to achieve significant speedup and reduce computational complexity in deep CNNs without any accuracy loss. Compared to the existing architectures, the proposed model achieves competitive results in face recognition tasks