• The KIPS Transactions:PartD
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• v.15D no.2
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• pp.155-162
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• 2008

Biological sequences such as DNA sequences and amino acid sequences typically contain a large number of items. They have contiguous sequences that ordinarily consist of hundreds of frequent items. In biological sequences analysis(BSA), a frequent contiguous sequence search is one of the most important operations. Many studies have been done for mining sequential patterns efficiently. Most of the existing methods for mining sequential patterns are based on the Apriori algorithm. In particular, the prefixSpan algorithm is one of the most efficient sequential pattern mining schemes based on the Apriori algorithm. However, since the algorithm expands the sequential patterns from frequent patterns with length-1, it is not suitable for biological dataset with long frequent contiguous sequences. In recent years, the MacosVSpan algorithm was proposed based on the idea of the prefixSpan algorithm to significantly reduce its recursive process. However, the algorithm is still inefficient for mining frequent contiguous sequences from long biological data sequences. In this paper, we propose an efficient method to mine maximal frequent contiguous sequences in large biological data sequences by constructing the spanning tree with the fixed length. To verify the superiority of the proposed method, we perform experiments in various environments. As the result, the experiments show that the proposed method is much more efficient than MacosVSpan in terms of retrieval performance.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.2
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• pp.272-277
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• 2008

Symmerge is a stable minimum storage merging algorithm that needs $O(m{\log}{\frac{n}{m}})$ element comparisons, where in and n are the sizes of the input sequences with $m{\leq}n$. Hence, according to the lower bound for merging, the algorithm is asymptotically optimal regarding the number of comparisons. The Symmerge algorithm is based on the standard recursive technique of "divide and conquer". The objective of this paper is to consider the relationship between m and n for the degenerated case where the recursion depth reaches m-1.

• Journal of Multimedia Information System
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• v.8 no.3
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• pp.147-158
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• 2021

Versatile Video Coding (VVC) is the latest video coding standard developed by Joint Video Exploration Team (JVET). In VVC, the quadtree plus multi-type tree (QT+MTT) structure of coding unit (CU) partition is adopted, and its computational complexity is considerably high due to the brute-force search for recursive rate-distortion (RD) optimization. In this paper, we aim to reduce the time complexity of inter-picture prediction mode since the inter prediction accounts for a large portion of the total encoding time. The problem can be defined as classifying the split mode of each CU. To classify the split mode effectively, a novel convolutional neural network (CNN) called multi-level tree (MLT-CNN) architecture is introduced. For boosting classification performance, we utilize additional information including inter-picture information while training the CNN. The overall algorithm including the MLT-CNN inference process is implemented on VVC Test Model (VTM) 11.0. The CUs of size 128×128 can be the inputs of the CNN. The sequences are encoded at the random access (RA) configuration with five QP values {22, 27, 32, 37, 42}. The experimental results show that the proposed algorithm can reduce the computational complexity by 11.53% on average, and 26.14% for the maximum with an average 1.01% of the increase in Bjøntegaard delta bit rate (BDBR). Especially, the proposed method shows higher performance on the sequences of the A and B classes, reducing 9.81%~26.14% of encoding time with 0.95%~3.28% of the BDBR increase.

• The Journal of the Korea institute of electronic communication sciences
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• v.7 no.6
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• pp.1369-1375
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• 2012

One of important problems in the theory of sequences is to determine the values and number of occurrences of each value taken on by the cross-correlation. In this paper, we find the values and the number of occurrences of each value of cross-correlation between an m-sequence u(t) of period $2^n-1$ and its decimation $u(dt)(0{\leq}t{\leq}2^n-2)$ where n=2m, 2s|m and $d=(2^{2m}+2^{2s+1}-2^{m+s+1}-1)/(2^s-1)$. Also we show that a family of decimations leads to a four-valued cross-correlation.

• Journal of Broadcast Engineering
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• v.4 no.2
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• pp.144-154
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• 1999

The binomial sequences are family of orthogonal sequences that can be generated with remarkable simplicity-no multiplications are necessary. This paper introduces a class of non-recursive multidimensional filters for frequency-selective image processing without multiplication operations. The magnitude responses are narrow-band. approximately gaussian-shaped with center frequencies which can be positioned to yield low-pass. band-pass. or high-pass filtering. Algorithms for the efficient implementation of these filters in software or in hardware are described. Also. we show that the binomial QMFs are the maximally flat magnitude square Perfect Reconstruction paraunitary filters with good compression capability and these are shown to be wavelet filters as well. In wavelet transform the original image is decomposed at different scales using a pyramidal algorithm architecture. The decomposition is along the vertical and horizontal direction and maintains constant the number of pixels required to describe the images. An efficient perfect reconstruction binomial QMF-Wavelet signal decomposition structure is proposed. The technique provides a set of filter solutions with very good amplitude responses and band split. The proposed binomial QMF-filter structure is efficient, simple to implement on VLSl. and suitable for multi-resolution signal decomposition and coding applications.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.16 no.7 s.98
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• pp.697-708
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• 2005

The forward link of the 3G CDMA system may become limited under the increasing of the number of users. The conventional channelization code, Walsh code, has not enough sizes f3r much possible users, therefore, the quasi orthogonal function(QOF), which process optimal crosscorrelation with Walsh code, is considered. In this paper, we investigate quasi orthogonal function on Jacket matrices, which can lead lower correlations values and better performance in 3G CDMA system. Moreover, to simplify the detector and improve the BER performance, a novel detection for QOF CDMA system is proposed. Finally, the simple recursive generation of the bent sequences for QOF mask function is discussed.

• Bulletin of the Korean Mathematical Society
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• v.46 no.2
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• pp.331-346
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• 2009

Let ${\alpha}$ = (${\alpha}_1,\;{\alpha}_2$,...) and ${\beta}$ = (${\beta}_1,\;{\beta}_2$,...) be two sequences with ${\alpha}_1$ = ${\beta}_1$ and k and n be natural numbers. We denote by $A^{(k,{\pm})}_{{\alpha},{\beta}}(n)$ the matrix of order n with coefficients ${\alpha}_{i,j}$ by setting ${\alpha}_{1,i}$ = ${\alpha}_i,\;{\alpha}_{i,1}$ = ${\beta}_i$ for 1 ${\leq}$ i ${\leq}$ n and $${\alpha}_{i,j}=\{{\alpha}_{i-1,j-1}+{\alpha}_{i-1,j}\;if\;j{\equiv}$$2,3,4,..., k + 1 (mod 2k) $$\{{\alpha}_{i-1,j-1}-{\alpha}_{i-1,j}\;if\;j{\equiv}$$ k + 2,..., 2k + 1 (mod 2k) for 2 ${\leq}$ i, j ${\leq}$ n. The aim of this paper is to study the determinants of such matrices related to certain sequence ${\alpha}$ and ${\beta}$ and some natural numbers k.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.5
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• pp.2141-2155
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• 2020

In order to meet the requirements of background change, illumination variation, moving shadow interference and high accuracy in object detection of moving camera, and strive for real-time and high efficiency, this paper presents an object detection algorithm based on sparse approximation recursion and sparse coding migration in subspace. First, low-rank sparse decomposition is used to reduce the dimension of the data. Combining with dictionary sparse representation, the computational model is established by the recursive formula of sparse approximation with the video sequences taken as subspace sets. And the moving object is calculated by the background difference method, which effectively reduces the computational complexity and running time. According to the idea of sparse coding migration, the above operations are carried out in the down-sampling space to further reduce the requirements of computational complexity and memory storage, and this will be adapt to multi-scale target objects and overcome the impact of large anomaly areas. Finally, experiments are carried out on VDAO datasets containing 59 sets of videos. The experimental results show that the algorithm can detect moving object effectively in the moving camera with uniform speed, not only in terms of low computational complexity but also in terms of low storage requirements, so that our proposed algorithm is suitable for detection systems with high real-time requirements.

• Journal of Korea Multimedia Society
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• v.20 no.2
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• pp.244-253
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• 2017

Reversible DNA watermarking is capable of continuous DNA storage and forgery prevention, and has the advantage of being able to analyze biological mutation processes by external watermarking by iterative process of concealment and restoration. In this paper, we propose a reversible DNA watermarking method based on histogram multiple shifting of noncoding DNA sequence that can prevent false start codon, maintain original sequence length, maintain high watermark capacity without biologic mutation. The proposed method transforms the non-coding region DNA sequence to the n-th code coefficients and embeds the multiple bits of the n-th code coefficients by the non-recursive histogram multiple shifting method. The multi-bit embedding process prevents the false start codon generation through comparison search between adjacent concealed nucleotide sequences. From the experimental results, it was confirmed that the proposed method has higher watermark capacity of 0.004-0.382 bpn than the conventional method and has higher watermark capacity than the additional data. Also, it was confirmed that false start codon was not generated unlike the conventional method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.6C
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• pp.624-633
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• 2003

We propose a novel method of selecting key VOPs from MPEG-4 compressed domain without fully decoding the compressed data. Approximated shapes of VOPs are obtained from the shape coding mode and then VOPs are clustered by shape similarity to generate key VOPs. The proposed method reduces the computation time of shape approximation, compared with Erol's method. Nevertheless, the resulting VOPs have a good summarizing capability of a video sequence. NMHD (normalized mean Hausdorff distance) values are 2-means clustered to generate key VOPs. In the video search, the MHD of a query VOP from key VOPs are computed and the VOP with the lowest distance is returned. Tests on standard MPEG-4 test sequences show that the computational complexity is very low. Recursive clustering proved to be very effective for generating suitable key VOPs.