• The Journal of the Acoustical Society of Korea
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• v.27 no.2E
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• pp.51-56
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• 2008

In this paper, we propose an effective method for music summarization which automatically extracts a representative part of the music by using signal processing technology. Proposed method uses a vector quantization technique to extract several segments which can be regarded as the most important contents in the music. In general, there is a repetitive pattern in music, and human usually recognizes the most important or catchy tune from the repetitive pattern. Thus the repetition which is extracted using segment similarity is considered to express a music summary. The segments extracted are again combined to generate a complete music summary. Experiments show the proposed method captures the main theme of the music more effectively than conventional methods. The experimental results also show that the proposed method could be used for real-time application since the processing time in generating music summary is much faster than other methods.

• Design & Manufacturing
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• v.16 no.3
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• pp.34-38
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• 2022

Regular expression pattern matching is widely used in applications such as computer virus vaccine, NIDS and DNA sequencing analysis. Hardware-based pattern matching is used when high-performance processing is required due to time constraints. ReCPU, SMPU, and REMP, which are processor-based regular expression matching processors, have been proposed to solve the problem of the hardware-based method that requires resynthesis whenever a pattern is updated. However, these processor-based regular expression matching processors inefficiently handle repetitive operations of regular expressions. In this paper, we propose a new instruction set to improve the inefficient repetitive operations of ReCPU and SMPU. We propose REMPi, a regular expression matching processor that enables efficient iterative operations based on the REMP instruction set. REMPi improves the inefficient method of processing a particularly short sub-pattern as a repeat operation OR, and enables processing with a single instruction. In addition, by using a down counter and a counter stack, nested iterative operations are also efficiently processed. REMPi was described with Verilog and synthesized on Intel Stratix IV FPGA.

• Korean Institute of Interior Design Journal
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• v.17 no.3
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• pp.156-164
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• 2008

Through staggering advancements of technology and network as we know them as digital revolution, we have established a foundation of space in which we can express reality by eliminating the boundaries between expression, space, and movement. There are many ongoing approaches that aim to overcome the physically-fixed property of space where the mathematical-geometric notion of Voronoi Diagram is one of them. Although the repetitive increment based on self-organization during the process in which space is generated by the Voronoi Diagram forms a pattern and focuses on the formation, its pattern is not restricted to a single method of expression but evolves over self-control. The result of having analyzed spaces generated by the Voronoi Diagram in this study can be summarized as follows. First, the Voronoi computation method with self-organization property creates multiple levels, increments, and evolves through feedbacks among changes with the slightest order and in the absence of control. Secondly, after forming a pattern through such feedbacks comes the differentiation phase due to the presence of different properties. Thirdly, a space that has gone through the generation process retransforms through active interaction between changes and it obtains ambiguous boundaries and a repetitive pattern. This leads to an evolution of space through repetitive increments based on self-organization. Such flexible space creation is supported by various digital technologies where we believe a converging application of these studies, sciences, engineering concepts, and space design is and effective and new method in terms of space creation.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2008.06a
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• pp.713-714
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• 2008

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.2
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• pp.524-543
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• 2022

Correct facade image parsing is essential to the semantic understanding of outdoor scenes. Unfortunately, there are often various occlusions in front of buildings, which fails many existing methods. In this paper, we propose an end-to-end deep network for facade parsing with occlusions. The network learns to decompose an input image into visible and invisible parts by occlusion reasoning. Then, a context aggregation module is proposed to collect nonlocal cues for semantic segmentation of the visible part. In addition, considering the regularity of man-made buildings, a repetitive pattern completion branch is designed to infer the contents in the invisible regions by referring to the visible part. Finally, the parsing map of the input facade image is generated by fusing the results of the visible and invisible results. Experiments on both synthetic and real datasets demonstrate that the proposed method outperforms state-of-the-art methods in parsing facades with occlusions. Moreover, we applied our method in applications of image inpainting and 3D semantic modeling.

• Journal of the Korea Society of Computer and Information
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• v.19 no.1
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• pp.23-30
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• 2014

Feature matching using image descriptors is robust method used recently. However, mismatches occur in 3D transformed images, illumination-changed images and repetitive-pattern images. In this paper, we observe that there are a lot of mismatches in the images which have repetitive patterns. We analyze it and propose a method to eliminate these mismatches. MDMF(Multiple Descriptors-based Mismatch Filtering) eliminates mismatches by using descriptors of nearest several features of one specific feature point. In experiments, for geometrical transformation like scale, rotation, affine, we compare the match ratio among SIFT, ASIFT and MDMF, and we show that MDMF can eliminate mismatches successfully.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.9
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• pp.49-55
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• 2019

This paper presents a marker image evaluation method based on analysis of object distribution in images and classification of images with repetitive patterns for effective marker-based augmented reality (AR) system development. We measure the variance of feature point coordinates to distinguish marker images that are vulnerable to occlusion, since object distribution affects object tracking performance according to partial occlusion in the images. Moreover, we propose a method to classify images suitable for object recognition and tracking based on the fact that the distributions of descriptor vectors among general images and repetitive-pattern images are significantly different. Comprehensive experiments for marker images confirm that the proposed marker image evaluation method distinguishes images vulnerable to occlusion and repetitive-pattern images very well. Furthermore, we suggest that scale-invariant feature transform (SIFT) is superior to speeded up robust features (SURF) in terms of object tracking in marker images. The proposed method provides users with suitability information for various images, and it helps AR systems to be realized more effectively.

• Korean Journal of Clinical Laboratory Science
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• v.36 no.1
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• pp.1-6
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• 2004

The enterobacterial repetitive intergenic consensus (ERIC)-PCR is a recently described DNA fingerprinting technique based on amplification of repetitive element distributed in bacteria. We applied of ERIC-PCR to clinical isolates of Vibrio parahaemolyticus and other bacteria associated diarrhea. Twenty isolates of V. parahaemolyticus were used for intragenic genotyping, which were isolated from 2001 to 2002 in Chungbuk National University hospital. For interspecies genotyping, V. vulnificus, V. alginolyticus, V. parahaemolyticus, Escherichia coli, Salmonella and Shigella spp. were used. The genotyping were analyzed by ERIC-PCR. The genotyping of V. parahaemolyticus were grouped two major pattern (A, B) and were subdivided into 10 subtypes (A1, A2, B1-B8) by ERIC-PCR. These method distinctly differentiated bacterial species associated diarrhea. Those results show that ERIC-PCR can be reliable and efficient method for genotyping of V. parahaemolyticus and bacteria associated diarrhea.

• Journal of Plant Biology
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• v.39 no.1
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• pp.49-55
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• 1996

We have studied the DNA of Allium sativum L. with respect to highly repetitive sequences. Fast reassociated DNA fragments expected to be highly repetitive sequences based on $C_{o}t$ curve were isolated and characterized. Their copy numbers were approximately $10^{5}~10^{7}$ per haploid genome. Nucleotide sequences analysis of six candidates reveals that their G/C content were low, 25-40% and typical patterns of repeating sequences exist. Repeat sequences were used as probes to access restriction fragment length polymorphism (RFLP) of genomic DNAs of four local clones, Tanyang, Mungyong, So san, and Uisong. The hybridization pattern were very similar among these four local clones.clones.

• Korean Journal of Food Science and Technology
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• v.37 no.4
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• pp.611-617
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• 2005

Dispersed repetitive DNA elements in genomes of microorganisms differ among and within species. Because distances between repetitive sequences vary depending on bacterial strains, genomic fingerprinting with interspersed repetitive sequence-based probes can be used to distinguish unrelated organisms. Among well-known bacterial repetitive sequences, Repetitive Extragenic Palindromic (REP) sequence has been used to identify environmental bacterial species and strains. We applied REP-PCR to detect and differentiate four major Gram-negative food-borne bacterial pathogens, E. coli, Salmonella, Shigella, and Vibrio. Target DNA fragments of these pathogens were amplified by REP-PCR method. PCR-generated DNA fragments were separated on 1.5% agarose gel. Dendrograms for PCR products of each strain were constructed using photo-documentation system. REP-PCR reactions with primer pairs REP1R-I and REP2-I revealed distinct REP-PCR-derived genomic fingerprinting patterns from E. coli, Salmonella, Shigella, and Vibrio. REP-PCR method provided clear distinctions among different bacterial species containing REP-repetitive elements and can be widely used for typing food-borne Gram-negative strains. Results showed established REP-PCR reaction conditions and generated dendrograms could be used with other supplementary genotyping or phenotyping methods to identify isolates from outbreak and to estimate relative degrees of genetic similarities among isolates from different outbreaks to determine whether they are clonally related.