• Title/Summary/Keyword: two-dimensional search

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Feature-Based Image Retrieval using SOM-Based R*-Tree

  • Shin, Min-Hwa;Kwon, Chang-Hee;Bae, Sang-Hyun
    • Proceedings of the KAIS Fall Conference
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    • 2003.11a
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    • pp.223-230
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    • 2003
  • Feature-based similarity retrieval has become an important research issue in multimedia database systems. The features of multimedia data are useful for discriminating between multimedia objects (e 'g', documents, images, video, music score, etc.). For example, images are represented by their color histograms, texture vectors, and shape descriptors, and are usually high-dimensional data. The performance of conventional multidimensional data structures(e'g', R- Tree family, K-D-B tree, grid file, TV-tree) tends to deteriorate as the number of dimensions of feature vectors increases. The R*-tree is the most successful variant of the R-tree. In this paper, we propose a SOM-based R*-tree as a new indexing method for high-dimensional feature vectors.The SOM-based R*-tree combines SOM and R*-tree to achieve search performance more scalable to high dimensionalities. Self-Organizing Maps (SOMs) provide mapping from high-dimensional feature vectors onto a two dimensional space. The mapping preserves the topology of the feature vectors. The map is called a topological of the feature map, and preserves the mutual relationship (similarity) in the feature spaces of input data, clustering mutually similar feature vectors in neighboring nodes. Each node of the topological feature map holds a codebook vector. A best-matching-image-list. (BMIL) holds similar images that are closest to each codebook vector. In a topological feature map, there are empty nodes in which no image is classified. When we build an R*-tree, we use codebook vectors of topological feature map which eliminates the empty nodes that cause unnecessary disk access and degrade retrieval performance. We experimentally compare the retrieval time cost of a SOM-based R*-tree with that of an SOM and an R*-tree using color feature vectors extracted from 40, 000 images. The result show that the SOM-based R*-tree outperforms both the SOM and R*-tree due to the reduction of the number of nodes required to build R*-tree and retrieval time cost.

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Anti-Spoofing Method Using Double Peak Detection in the Two-Dimensional C/A Code Search Space (이차원 C/A 코드 검색 공간에서의 이중피크 검출을 이용한 기만신호 대응 기법)

  • Kwon, Keum-Cheol;Yang, Cheol-Kwan;Shim, Duk-Sun
    • Journal of Advanced Navigation Technology
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    • v.17 no.2
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    • pp.157-164
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    • 2013
  • In the presence of spoofing signal the GPS signal having the same PRN with the spoofer is hard to be acquired since the power of spoofing signal is usually stronger than that of GPS signal. If a spoofing signal exists for the same PRN, there are double peaks in two-dimensional space of frequency and code phase in acquisition stage. Using double peak information it is possible to detect spoofing signal and acquire GPS information through separate channel tracking. In this paper we introduce an anti-spoofing method using double peak detection, and thus can acquire GPS navigation data after two-channel tracking for the same PRN as the spoofing signal.

Optimization Algorithm for Energy-Efficiency in the Multi-user Massive MIMO Downlink System with MRT Precoding (MRT 기법 사용 시 다중 사용자 다중 안테나 하향링크 시스템에서의 에너지 효율 향상을 위한 최적화 알고리즘)

  • Lee, Jeongsu;Han, Yonggue;Sim, Dongkyu;Lee, Chungyong
    • Journal of the Institute of Electronics and Information Engineers
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    • v.52 no.8
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    • pp.3-9
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    • 2015
  • Under the maximum transmit power constraint and the minimum rate constraint, we propose the optimal number of transmit antennas and transmit power which maximize energy-efficiency (EE) in multi-user multiple-input multiple-output (MIMO) downlink system with the maximal ratio transmission (MRT) precoding. Because the optimization problem for the instantaneous channel is difficult to solve, we use independence of individual channel, average channel gain and path loss to approximate the objective function. Since the approximated EE optimization problem is two-dimensional search problem, we find the optimal number of transmit antennas and transmit power using Lagrange multipliers and our proposed algorithm. Simulation results show that the number of transmit antennas and power obtained by proposed algorithm are almost identical to the value by the exhaustive search.

A VLSI Array Processor Architecture for High-Speed Processing of Full Search Block Matching Algorithm (완전탐색 블럭정합 알고리즘의 고속 처리를 위한 VLSI 어레이 프로세서의 구조)

  • 이수진;우종호
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.27 no.4A
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    • pp.364-370
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    • 2002
  • In this paper, we propose a VLSI array architecture for high speed processing of FBMA. First of all, the sequential FBMA is transformed into a single assignment code by using the index space expansion, and then the dependance graph is obtained from it. The two dimensional VLSI array is derived by projecting the dependance graph along the optimal direction. Since the candidate blocks in the search range are overlapped with columns as well as rows, the processing elements of the VLSI array are designed to reuse the overlapped data. As the results, the number of data inputs is reduced so that the processing performance is improved. The proposed VLSI array has (N$^2$+1)${\times}$(2p+1) processing elements and (N+2p) input ports where N is the block size and p is the maximum search range. The computation time of the rat reference block is (N$^2$+2(p+1)N+6p), and the block pipeline period is (3N+4p-1).

Two-dimensional Binary Search Tree for Packet Classification at Internet Routers (인터넷 라우터에서의 패킷 분류를 위한 2차원 이진 검색 트리)

  • Lee, Goeun;Lim, Hyesook
    • Journal of the Institute of Electronics and Information Engineers
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    • v.52 no.6
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    • pp.21-31
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    • 2015
  • The Internet users want to get real-time services for various multi-media applications. Network traffic rate has been rapidly increased, and data amounts that the Internet has to carry have been exponentially increased. A packet is the basic unit in transferring data at the Internet, and packet classification is one of the most challenging functionalities that routers should perform at wire-speed. Among various known packet classification algorithms, area-based quad-trie (AQT) algorithm is one of the efficient algorithms which can lookup five header fields simultaneously. As a representative space decomposition algorithm, the AQT requires a small amount of memory in storing classification rules, but it does not provide high-speed classification performance. In this paper, we propose a new packet classification algorithm by applying a binary search for the codewords of the AQT to overcome the issue of the AQT. Throughout simulation, it is shown that the proposed algorithm provides a better performance than the AQT in the number of rule comparisons with each input packet.

A Comparative Study on the PSO and APSO Algorithms for the Optimal Design of Planar Patch Antennas (평면형 패치 안테나의 최적설계를 위한 PSO와 APSO 알고리즘 비교 연구)

  • Kim, Koon-Tae;Kim, Hyeong-Seok
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.62 no.11
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    • pp.1578-1583
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    • 2013
  • In this paper, stochastic optimization algorithms of PSO (Particle Swarm Optimization) and APSO (Adaptive Particle Swam Optimization) are studied and compared. It is revealed that the APSO provides faster convergence and better search efficiency than the conventional PSO when they are adopted to find the global minimum of a two-dimensional function. The advantages of the APSO comes from the ability to control the inertia weight, and acceleration coefficients. To verify that the APSO is working better than the standard PSO, the design of a 10GHz microstrip patch as one of the elements of a high frequency array antenna is taken as a test-case and shows the optimized result with 5 iterations in the APSO and 28 iterations in th PSO.

Development of Similarity-Based Document Clustering System (유사성 계수에 의한 문서 클러스터링 시스템 개발)

  • Woo Hoon-Shik;Yim Dong-Soon
    • Proceedings of the Society of Korea Industrial and System Engineering Conference
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    • 2002.05a
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    • pp.119-124
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    • 2002
  • Clustering of data is of a great interest in many data mining applications. In the field of document clustering, a document is represented as a data in a high dimensional space. Therefore, the document clustering can be accomplished with a general data clustering techniques. In this paper, we introduce a document clustering system based on similarity among documents. The developed system consists of three functions: 1) gatherings documents utilizing a search agent; 2) determining similarity coefficients between any two documents from term frequencies; 3) clustering documents with similarity coefficients. Especially, the document clustering is accomplished by a hybrid algorithm utilizing genetic and K-Means methods.

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Error correction in laser scanner 3D measurement (레이저 스캐너 3차원 계측에 있어서의 오차 보정)

  • 김응규
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.33B no.5
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    • pp.94-101
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    • 1996
  • When objects are scanned spatially by a laser-beam and mechanical mirror scanners, spatial information can be obtained, and then it is improtant to accurately obtain the parameters relating the light source and camera positions, etc.. In this paper, a calibration technique is presented for correction of measuremtn errors in a three-dimensional laser scanner system with two galvanometers. First, a model of the systematic errors is developed based on the geometry of the scanning system. Calibration parameter values are then iteratively adjusted with coarse-fine search in order to minimize errors (evaluation function) between measured and computed distances. It is shown that this correction method results in measurement precision suitable for practical use.

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Structure-based Functional Discovery of Proteins: Structural Proteomics

  • Jung, Jin-Won;Lee, Weon-Tae
    • BMB Reports
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    • v.37 no.1
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    • pp.28-34
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    • 2004
  • The discovery of biochemical and cellular functions of unannotated gene products begins with a database search of proteins with structure/sequence homologues based on known genes. Very recently, a number of frontier groups in structural biology proposed a new paradigm to predict biological functions of an unknown protein on the basis of its three-dimensional structure on a genomic scale. Structural proteomics (genomics), a research area for structure-based functional discovery, aims to complete the protein-folding universe of all gene products in a cell. It would lead us to a complete understanding of a living organism from protein structure. Two major complementary experimental techniques, X-ray crystallography and NMR spectroscopy, combined with recently developed high throughput methods have played a central role in structural proteomics research; however, an integration of these methodologies together with comparative modeling and electron microscopy would speed up the goal for completing a full dictionary of protein folding space in the near future.

Constructing an Interactive Virtual Amusement Land along with 3D characters (3D캐릭터를 이용한 인터렉티브 가상놀이공간 구축)

  • 김보경;조은경;진성아
    • Proceedings of the Korea Contents Association Conference
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    • 2003.05a
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    • pp.111-116
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    • 2003
  • Due to the increase of the Broadband Networks and Internet users culture contents in Virtual Environment such as education entertainment and culture are constantly demanded with respect to usability and effectiveness. Mostly existing virtual amusement land$ tend to retain limitations and shortcomings caused by two dimensional interface. This facts may have users directly search amusement facilities themselves resulting in lots of inconvenience. In the work here, a virtual amusement land led by 3D characters is presented. The interactive contents which users can actively participate in is developed.

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