• Title/Summary/Keyword: Cross-matching

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A Study on Clustering and Identifying Gene Sequences using Suffix Tree Clustering Method and BLAST (서픽스트리 클러스터링 방법과 블라스트를 통합한 유전자 서열의 클러스터링과 기능검색에 관한 연구)

  • Han, Sang-Il;Lee, Sung-Gun;Kim, Kyung-Hoon;Lee, Ju-Yeong;Kim, Young-Han;Hwang, Kyu-Suk
    • Journal of Institute of Control, Robotics and Systems
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    • v.11 no.10
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    • pp.851-856
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    • 2005
  • The DNA and protein data of diverse species have been daily discovered and deposited in the public archives according to each established format. Database systems in the public archives provide not only an easy-to-use, flexible interface to the public, but also in silico analysis tools of unidentified sequence data. Of such in silico analysis tools, multiple sequence alignment [1] methods relying on pairwise alignment and Smith-Waterman algorithm [2] enable us to identify unknown DNA, protein sequences or phylogenetic relation among several species. However, in the existing multiple alignment method as the number of sequences increases, the runtime increases exponentially. In order to remedy this problem, we adopted a parallel processing suffix tree algorithm that is able to search for common subsequences at one time without pairwise alignment. Also, the cross-matching subsequences triggering inexact-matching among the searched common subsequences might be produced. So, the cross-matching masking process was suggested in this paper. To identify the function of the clusters generated by suffix tree clustering, BLAST was combined with a clustering tool. Our clustering and annotating tool is summarized as the following steps: (1) construction of suffix tree; (2) masking of cross-matching pairs; (3) clustering of gene sequences and (4) annotating gene clusters by BLAST search. The system was successfully evaluated with 22 gene sequences in the pyrubate pathway of bacteria, clustering 7 clusters and finding out representative common subsequences of each cluster

A Study of Fuel Gauge System Matching Method Using Characteristic Chart to Fuel Consumption Ratio in Vehicles (특성 선도를 이용한 자동차용 연료 지침계의 연료 소비율에 따른 시스템 제어 방법에 관한 연구)

  • Lee, Seon-Bong;Lee, Boo-Youn
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.32 no.2
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    • pp.194-201
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    • 2008
  • In the present study, fuel system matching was analyzed, and a characteristic chart for common use for design-related parts is presented. Based on the characteristic chart thus presented, controlled fuel system matching was tested for a 35-liter fuel system, and actual mass product movement coils were applied to validate the test. The keynote of the present research is the use of the characteristic chart to devise a preferred fuel system matching method. Through the present study, it will be possible to design standard parts for efficient fuel system matching in the near future.

Joint Template Matching Algorithm for Associated Multi-object Detection

  • Xie, Jianbin;Liu, Tong;Chen, Zhangyong;Zhuang, Zhaowen
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.6 no.1
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    • pp.395-405
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    • 2012
  • A joint template matching algorithm is proposed in this paper to reduce the high rate of miss-detection and false-alarm caused by the traditional template matching algorithm during the process of multi-object detection. The proposed algorithm can reduce the influence on each object by matching all objects together according to the correlation information among different objects. Moreover, the rate of miss-detection and false-alarm in the process of single-template matching is also reduced based on the algorithm. In this paper, firstly, joint template is created from the information of relative positions among different objects. Then, matching criterion according to normalized cross correlation is generated for multi-object matching. Finally, the proposed algorithm is applied to the detection of watermarks in bill. The experiments show that the proposed algorithm has lower miss-detection and false-alarm rate comparing to the traditional NCC algorithm during the process of multi-object detection.

Development and Application of High-resolution 3-D Volume PIV System by Cross-Correlation (해상도 3차원 상호상관 Volume PIV 시스템 개발 및 적용)

  • Kim Mi-Young;Choi Jang-Woon;Lee Hyun;Lee Young-Ho
    • Proceedings of the KSME Conference
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    • 2002.08a
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    • pp.507-510
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    • 2002
  • An algorithm of 3-D particle image velocimetry(3D-PIV) was developed for the measurement of 3-D velocity Held of complex flows. The measurement system consists of two or three CCD camera and one RGB image grabber. Flows size is $1500{\times}100{\times}180(mm)$, particle is Nylon12(1mm) and illuminator is Hollogen type lamp(100w). The stereo photogrammetry is adopted for the three dimensional geometrical mesurement of tracer particle. For the stereo-pair matching, the camera parameters should be decide in advance by a camera calibration. Camera parameter calculation equation is collinearity equation. In order to calculate the particle 3-D position based on the stereo photograrnrnetry, the eleven parameters of each camera should be obtained by the calibration of the camera. Epipolar line is used for stereo pair matching. The 3-D position of particle is calculated from the three camera parameters, centers of projection of the three cameras, and photographic coordinates of a particle, which is based on the collinear condition. To find velocity vector used 3-D position data of the first frame and the second frame. To extract error vector applied continuity equation. This study developed of various 3D-PIV animation technique.

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Gene Sequences Clustering for the Prediction of Functional Domain (기능 도메인 예측을 위한 유전자 서열 클러스터링)

  • Han Sang-Il;Lee Sung-Gun;Hou Bo-Kyeng;Byun Yoon-Sup;Hwang Kyu-Suk
    • Journal of Institute of Control, Robotics and Systems
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    • v.12 no.10
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    • pp.1044-1049
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    • 2006
  • Multiple sequence alignment is a method to compare two or more DNA or protein sequences. Most of multiple sequence alignment tools rely on pairwise alignment and Smith-Waterman algorithm to generate an alignment hierarchy. Therefore, in the existing multiple alignment method as the number of sequences increases, the runtime increases exponentially. In order to remedy this problem, we adopted a parallel processing suffix tree algorithm that is able to search for common subsequences at one time without pairwise alignment. Also, the cross-matching subsequences triggering inexact-matching among the searched common subsequences might be produced. So, the cross-matching masking process was suggested in this paper. To identify the function of the clusters generated by suffix tree clustering, BLAST and CDD (Conserved Domain Database)search were combined with a clustering tool. Our clustering and annotating tool consists of constructing suffix tree, overlapping common subsequences, clustering gene sequences and annotating gene clusters by BLAST and CDD search. The system was successfully evaluated with 36 gene sequences in the pentose phosphate pathway, clustering 10 clusters, finding out representative common subsequences, and finally identifying functional domains by searching CDD database.

Automatic In-Text Keyword Tagging based on Information Retrieval

  • Kim, Jin-Suk;Jin, Du-Seok;Kim, Kwang-Young;Choe, Ho-Seop
    • Journal of Information Processing Systems
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    • v.5 no.3
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    • pp.159-166
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    • 2009
  • As shown in Wikipedia, tagging or cross-linking through major keywords in a document collection improves not only the readability of documents but also responsive and adaptive navigation among related documents. In recent years, the Semantic Web has increased the importance of social tagging as a key feature of the Web 2.0 and, as its crucial phenotype, Tag Cloud has emerged to the public. In this paper we provide an efficient method of automated in-text keyword tagging based on large-scale controlled term collection or keyword dictionary, where the computational complexity of O(mN) - if a pattern matching algorithm is used - can be reduced to O(mlogN) - if an Information Retrieval technique is adopted - while m is the length of target document and N is the total number of candidate terms to be tagged. The result shows that automatic in-text tagging with keywords filtered by Information Retrieval speeds up to about 6 $\sim$ 40 times compared with the fastest pattern matching algorithm.

Cross-Talk: D2D Potentiality Based Resource Borrowing Schema for Ultra-Low Latency Transmission in Cellular Network

  • Sun, Guolin;Dingana, Timothy;Adolphe, Sebakara Samuel Rene;Boateng, Gordon Owusu
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.13 no.5
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    • pp.2258-2276
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    • 2019
  • Resource sharing is one of the main goals achieved by network virtualization technology to enhance network resource utilization and enable resource customization. Though resource sharing can improve network efficiency by accommodating various users in a network, limited infrastructure capacity is still a challenge to ultra-low latency service operators. In this paper, we propose an inter-slice resource borrowing schema based on the device-to-device (D2D) potentiality especially for ultra-low latency transmission in cellular networks. An extended and modified Kuhn-Munkres bipartite matching algorithm is developed to optimally achieve inter-slice resource borrowing. Simulation results show that, proper D2D user matching can be achieved, satisfying ultra-low latency (ULL) users' quality of service (QoS) requirements and resource utilization in various scenarios.

Ontology Matching Method Based on Word Embedding and Structural Similarity

  • Hongzhou Duan;Yuxiang Sun;Yongju Lee
    • International journal of advanced smart convergence
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    • v.12 no.3
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    • pp.75-88
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    • 2023
  • In a specific domain, experts have different understanding of domain knowledge or different purpose of constructing ontology. These will lead to multiple different ontologies in the domain. This phenomenon is called the ontology heterogeneity. For research fields that require cross-ontology operations such as knowledge fusion and knowledge reasoning, the ontology heterogeneity has caused certain difficulties for research. In this paper, we propose a novel ontology matching model that combines word embedding and a concatenated continuous bag-of-words model. Our goal is to improve word vectors and distinguish the semantic similarity and descriptive associations. Moreover, we make the most of textual and structural information from the ontology and external resources. We represent the ontology as a graph and use the SimRank algorithm to calculate the structural similarity. Our approach employs a similarity queue to achieve one-to-many matching results which provide a wider range of insights for subsequent mining and analysis. This enhances and refines the methodology used in ontology matching.

Terrain Referenced Navigation Simulation using Area-based Matching Method and TERCOM (영역기반 정합 기법 및 TERCOM에 기반한 지형 참조 항법 시뮬레이션)

  • Lee, Bo-Mi;Kwon, Jay-Hyoun
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.28 no.1
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    • pp.73-82
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    • 2010
  • TERCOM(TERrain COntour Matching), which is the one of the Terrain Referenced Navigation and used in the cruise missile navigation system, is still under development. In this study, the TERCOM based on area-based matching algorithm and extended Kalman filter is analysed through simulation. In area-based matching, the mean square difference (MSD) and cross-correlation matching algorithms are applied. The simulation supposes that the barometric altimeter, radar altimeter and SRTM DTM loaded on board. Also, it navigates along the square track for 545 seconds with the velocity of 1000km per hour. The MSD and cross-correlation matching algorithms show the standard deviation of position error of 99.6m and 34.3m, respectively. The correlation matching algorithm is appeared to be less sensitive than the MSD algorithm to the topographic undulation and the position accuracy of the both algorithms is extremely depends on the terrain. Therefore, it is necessary to develop an algorithm that is more sensitive to less terrain undulation for reliable terrain referenced navigation. Furthermore, studies on the determination of proper matching window size in long-term flight and the determination of the best terrain database resolution needed by the flight velocity and area should be conducted.

Highly Dense 3D Surface Generation Using Multi-image Matching

  • Noh, Myoung-Jong;Cho, Woo-Sug;Bang, Ki-In
    • ETRI Journal
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    • v.34 no.1
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    • pp.87-97
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    • 2012
  • This study presents an automatic matching method for generating a dense, accurate, and discontinuity-preserved digital surface model (DSM) using multiple images acquired by an aerial digital frame camera. The proposed method consists of two main procedures: area-based multi-image matching (AMIM) and stereo-pair epipolar line matching (SELM). AMIM evaluates the sum of the normalized cross correlation of corresponding image points from multiple images to determine the optimal height of an object point. A novel method is introduced for determining the search height range and incremental height, which are necessary for the vertical line locus used in the AMIM. This procedure also includes the means to select the best reference and target images for each strip so that multi-image matching can resolve the common problem over occlusion areas. The SELM extracts densely positioned distinct points along epipolar lines from the multiple images and generates a discontinuity-preserved DSM using geometric and radiometric constraints. The matched points derived by the AMIM are used as anchor points between overlapped images to find conjugate distinct points using epipolar geometry. The performance of the proposed method was evaluated for several different test areas, including urban areas.