• Title/Summary/Keyword: Binary Method

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A bootstrap approach for factor numbers in binary data (붓스트랩 방법을 이용한 이항분포자료에 대한 요인수 결정에 관한 연구)

  • 김성호;정미숙
    • The Korean Journal of Applied Statistics
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    • v.8 no.2
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    • pp.201-216
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    • 1995
  • A method of determining the factor numbers is explored in this paper, when data and the factors are binary. We applied a bootstrap approach and proposed a criterion for the method. Simulation results suggest that the proposed method in this paper is very useful in determining the factor numbers for binary data and factors.

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Binary Tree Vector Quantization Using Spatial Masking Effect (공간 마스킹 효과를 적용한 이진트리 벡터양자화)

  • 유성필;곽내정;윤태승;안재형
    • Proceedings of the IEEK Conference
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    • 2003.11a
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    • pp.369-372
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    • 2003
  • In this paper, we propose impr oved binary tree vector quantization based on spatial sensitivity which is one of the human visual properties. We combine the weights based on spatial masking effect according to changes of three primary colors in blocks of images with the process of splitting nodes using eigenvector in binary tree vector quantization. The test results show that the proposed method generates the quantized images with fine color and performs better than the conventional method in terms of clustering the similar regions. Also the proposed method can get the better result in subjective qualify test and PSNR.

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Finger Vein Recognition Using Generalized Local Line Binary Pattern

  • Lu, Yu;Yoon, Sook;Xie, Shan Juan;Yang, Jucheng;Wang, Zhihui;Park, Dong Sun
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.8 no.5
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    • pp.1766-1784
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    • 2014
  • Finger vein images contain rich oriented features. Local line binary pattern (LLBP) is a good oriented feature representation method extended from local binary pattern (LBP), but it is limited in that it can only extract horizontal and vertical line patterns, so effective information in an image may not be exploited and fully utilized. In this paper, an orientation-selectable LLBP method, called generalized local line binary pattern (GLLBP), is proposed for finger vein recognition. GLLBP extends LLBP for line pattern extraction into any orientation. To effectually improve the matching accuracy, the soft power metric is employed to calculate the matching score. Furthermore, to fully utilize the oriented features in an image, the matching scores from the line patterns with the best discriminative ability are fused using the Hamacher rule to achieve the final matching score for the last recognition. Experimental results on our database, MMCBNU_6000, show that the proposed method performs much better than state-of-the-art algorithms that use the oriented features and local features, such as LBP, LLBP, Gabor filter, steerable filter and local direction code (LDC).

Cross-architecture Binary Function Similarity Detection based on Composite Feature Model

  • Xiaonan Li;Guimin Zhang;Qingbao Li;Ping Zhang;Zhifeng Chen;Jinjin Liu;Shudan Yue
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.17 no.8
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    • pp.2101-2123
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    • 2023
  • Recent studies have shown that the neural network-based binary code similarity detection technology performs well in vulnerability mining, plagiarism detection, and malicious code analysis. However, existing cross-architecture methods still suffer from insufficient feature characterization and low discrimination accuracy. To address these issues, this paper proposes a cross-architecture binary function similarity detection method based on composite feature model (SDCFM). Firstly, the binary function is converted into vector representation according to the proposed composite feature model, which is composed of instruction statistical features, control flow graph structural features, and application program interface calling behavioral features. Then, the composite features are embedded by the proposed hierarchical embedding network based on a graph neural network. In which, the block-level features and the function-level features are processed separately and finally fused into the embedding. In addition, to make the trained model more accurate and stable, our method utilizes the embeddings of predecessor nodes to modify the node embedding in the iterative updating process of the graph neural network. To assess the effectiveness of composite feature model, we contrast SDCFM with the state of art method on benchmark datasets. The experimental results show that SDCFM has good performance both on the area under the curve in the binary function similarity detection task and the vulnerable candidate function ranking in vulnerability search task.

An efficient search of binary tree for huffman decoding based on numeric interpretation of codewords

  • Kim, Byeong-Il;Chang, Tae-Gyu;Jeong, Jong-Hoon
    • Proceedings of the IEEK Conference
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    • 2002.07a
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    • pp.133-136
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    • 2002
  • This paper presents a new method of Huffman decoding which gives a significant improvement of processing efficiency based on the reconstruction of an efficient one-dimensional array data structure incorporating the numeric interpretation of the accrued codewords in the binary tree. In the Proposed search method, the branching address is directly obtained by the arithematic operation with the incoming digit value eliminating the compare instruction needed in the binary tree search. The proposed search method gives 30% of improved Processing efficiency and the memory space of the reconstructed Huffman table is reduced to one third compared to the ordinary ‘compare and jump’ based binary tree. The experimental result with the six MPEG-2 AAC test files also shows about 198% of performance improvement compared to those of the widely used conventional sequential search method.

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VARIABLE TIME-STEPPING HYBRID FINITE DIFFERENCE METHODS FOR PRICING BINARY OPTIONS

  • Kim, Hong-Joong;Moon, Kyoung-Sook
    • Bulletin of the Korean Mathematical Society
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    • v.48 no.2
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    • pp.413-426
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    • 2011
  • Two types of new methods with variable time steps are proposed in order to valuate binary options efficiently. Type I changes adaptively the size of the time step at each time based on the magnitude of the local error, while Type II combines two uniform meshes. The new methods are hybrid finite difference methods, namely starting the computation with a fully implicit finite difference method for a few time steps for accuracy then performing a ${\theta}$-method during the rest of computation for efficiency. Numerical experiments for standard European vanilla, binary and American options show that both Type I and II variable time step methods are much more efficient than the fully implicit method or hybrid methods with uniform time steps.

A SUCCESSIVE QUADRATIC PROGRAMMING ALGORITHM FOR SDP RELAXATION OF THE BINARY QUADRATIC PROGRAMMING

  • MU XUEWEN;LID SANYANG;ZHANG YALING
    • Bulletin of the Korean Mathematical Society
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    • v.42 no.4
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    • pp.837-849
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    • 2005
  • In this paper, we obtain a successive quadratic programming algorithm for solving the semidefinite programming (SDP) relaxation of the binary quadratic programming. Combining with a randomized method of Goemans and Williamson, it provides an efficient approximation for the binary quadratic programming. Furthermore, its convergence result is given. At last, We report some numerical examples to compare our method with the interior-point method on Maxcut problem.

Numerical Study on the Droplet Flows in a Cross-Junction Channel Using the Lattice Boltzmann Method (Lattice Boltzmann 법을 이용한 Cross-Junction 채널 내의 droplet 유동에 관한 수치해석적 연구)

  • Park, Jae-Hyoun;Suh, Young-Kweon
    • Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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    • 2006.11a
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    • pp.407-410
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    • 2006
  • This study describes a simulation of two-dimensional bubble forming and motion by the Lattice Boltzmann Method with the phase field equation. The free energy model is used to treat the interfacial force and deformation of binary fluids system, drawn into a T-junction the micro channel. A numerical simulation of a binary flow in a cross-junction channel is carried out by using the parallel computation method. The aim in this investigation is to examine the applicability of LBM to numerical analysis of binary fluid separation and motion in the micro channel.

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BINARIES IN OPEN STAR CLUSTERS: PHOTOMETRIC APPROACH WITH APPLICATION TO THE HYADES

  • ALAWY A. EL-BASSUNY;KORANY B. A.;HAROON A. A.;ISMAIL H. A.;SHARAF M. A.
    • Journal of The Korean Astronomical Society
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    • v.37 no.3
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    • pp.119-129
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    • 2004
  • A new method has been developed to solve the star cluster membership problem. It is based on synthetic photometry employing the Black Body concept as stellar radiation simulator. Synthetic color-magnitude diagram is constructed showing the main sequence band and the positions of binary star systems of combinations of various components through different photometric tracks. The method has been applied to the Hyades. The cluster membership problem has been re-appraised for the cluster (both single and binary) stars. For the binary members, the components' spectral types have been derived by the method. The results obtained agree very well with those found in literature, The method is simpler than the others and can be developed to undertake other cases as multiple star systems.

A Data Hiding Method of Binary Images Using Pixel-value Weighting (이진 이미지에 대한 픽셀값 가중치를 이용한 자료 은닉 기법 연구)

  • Jung, Ki-Hyun
    • Journal of the Korea Institute of Military Science and Technology
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    • v.11 no.4
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    • pp.68-75
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    • 2008
  • This paper proposes a new data hiding method for binary images using the weighting value of pixel-value differencing. The binary cover image is partitioned into non-overlapping sub-blocks and find the most suitable position to embed a secret bit for each sub-block. The proposed method calculates the weighted value for a sub-block to pivot a pixel to be changed. This improves the image quality of the stego-image. The experimental results show that the proposed method achieves a good visual quality and high capacity.