• Title/Summary/Keyword: two-dimensional search

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A Study on method development of parameter estimation for real-time QRS detection (실시간 QRS 검출을 위한 파라미터 estimation 기법에 관한 연구)

  • Kim, Eung-Suk;Lee, Jeong-Whan;Yoon, Ji-Young;Lee, Myoung-Ho
    • Proceedings of the KOSOMBE Conference
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    • v.1995 no.11
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    • pp.193-196
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    • 1995
  • An algorithm using topological mapping has been developed for a real-time detection of the QRS complexes of ECG signals. As a measurement of QRS complex energy, we used topological mapping from one dimensional sampled ECG signals to two dimensional vectors. These vectors are reconstructed with the sampled ECG signals and the delayed ones. In this method, the detection rates of CRS complex vary with the parameters such as R-R interval average and peak detection threshold coefficient. We use mean, median, and iterative method to determint R-R interval average and peak estimation. We experiment on various value of search back coefficient and peak detection threshold coefficient to find optimal rule.

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A Study on the Fast Block Matching Algorithm (고속 Block Matching 알고리즘에 관한 연구)

  • 이인홍;박래홍
    • Journal of the Korean Institute of Telematics and Electronics
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    • v.24 no.4
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    • pp.667-674
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    • 1987
  • In this paper an effective block matching algorithm is proposed to find the motion vector. There are two approaches to the estimation of the motion vector in MCC (motion compensated coding), i.e., pel(pixel element) recursive algorithm and block matching algorithm. The search algorithm in this paper is based on the block matching method. The advantage of a proposed algorithm using integral projections is the reduction of the computation time. While the conventional block matching methods have to be computed in 2-dimensional arrays, the proposed algorithm using integral projections can be computed in 1-dimensional arrays. In comparison with conventional block matching methods, a computer simulation shows that though the prediction error increases 0.23 db, it is not detectable for human eyes and the average reduction ratio of computation time obtained from the proposed algorithm is about 3-4.

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Vector Approximation Bitmap Indexing Method for High Dimensional Multimedia Database (고차원 멀티미디어 데이터 검색을 위한 벡터 근사 비트맵 색인 방법)

  • Park Joo-Hyoun;Son Dea-On;Nang Jong-Ho;Joo Bok-Gyu
    • The KIPS Transactions:PartD
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    • v.13D no.4 s.107
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    • pp.455-462
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    • 2006
  • Recently, the filtering approach using vector approximation such as VA-file[1] or LPC-file[2] have been proposed to support similarity search in high dimensional data space. This approach filters out many irrelevant vectors by calculating the approximate distance from a query vector using the compact approximations of vectors in database. Accordingly, the total elapsed time for similarity search is reduced because the disk I/O time is eliminated by reading the compact approximations instead of original vectors. However, the search time of the VA-file or LPC-file is not much lessened compared to the brute-force search because it requires a lot of computations for calculating the approximate distance. This paper proposes a new bitmap index structure in order to minimize the calculating time. To improve the calculating speed, a specific value of an object is saved in a bit pattern that shows a spatial position of the feature vector on a data space, and the calculation for a distance between objects is performed by the XOR bit calculation that is much faster than the real vector calculation. According to the experiment, the method that this paper suggests has shortened the total searching time to the extent of about one fourth of the sequential searching time, and to the utmost two times of the existing methods by shortening the great deal of calculating time, although this method has a longer data reading time compared to the existing vector approximation based approach. Consequently, it can be confirmed that we can improve even more the searching performance by shortening the calculating time for filtering of the existing vector approximation methods when the database speed is fast enough.

Dynamic Stall Control Using Aerodynamic Sensitivity Analysis (민감도 해석을 이용한 동적실속 제어)

  • Ahn, Tai-Sul;Kim, Hyoung-Jin;Kim, Chong-Am;Rho, Oh-Hyun
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.30 no.8
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    • pp.10-20
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    • 2002
  • The present paper investigates methods to control dynamic stall using an optimal approach. An unsteady aerodynamic sensitivity analysis code is developed by a direct differentiation method from a two-dimensional unsteady compressible Navier-Stokes solver including a two-equation turbulence model. Dynamic stall control is conducted by minimizing an objective function defined at an instant instead of integrating for a period of time. Unsteady sensitivity derivatives of the objective function are calculated by the sensitivity code, and optimization is carried out using a linear line search method at every physical time step. Numerous examples of dynamic stall control using control parameters such as nose radius, maximum thickness of airfoil, or suction show satisfactory results.

A Design for Efficient Similar Subsequence Search with a Priority Queue and Suffix Tree in Image Sequence Databases (이미지 시퀀스 데이터베이스에서 우선순위 큐와 접미어 트리를 이용한 효율적인 유사 서브시퀀스 검색의 설계)

  • 김인범
    • Journal of the Korea Computer Industry Society
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    • v.4 no.4
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    • pp.613-624
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    • 2003
  • This paper proposes a design for efficient and accurate retrieval of similar image subsequences using the multi-dimensional time warping distance as similarity evaluation tool in image sequence database after building of two indexing structures implemented with priority queue and suffix tree respectively. Receiving query image sequence, at first step, the proposed method searches the candidate set of similar image subsequences in priory queue index structure. If it can not get satisfied results, it retrieves another candidate set in suffix tree index structure at second step. The using of the low-bound distance function can remove the dissimilar subsequence without false dismissals during similarity evaluating process between query image sequence and stored sequences in two index structures.

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Object-Based Video Segmentation Using Spatio-temporal Entropic Thresholding and Camera Panning Compensation (시공간 엔트로피 임계법과 카메라 패닝 보상을 이용한 객체 기반 동영상 분할)

  • 백경환;곽노윤
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.4 no.3
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    • pp.126-133
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    • 2003
  • This paper is related to a morphological segmentation method for extracting the moving object in video sequence using global motion compensation and two-dimensional spatio-temporal entropic thresholding. First, global motion compensation is performed with camera panning vector estimated in the hierarchical pyramid structure constructed by wavelet transform. Secondly, the regions with high possibility to include the moving object between two consecutive frames are extracted block by block from the global motion compensated image using two-dimensional spatio-temporal entropic thresholding. Afterwards, the LUT classifying each block into one among changed block, uncertain block, stationary block according to the results classified by two-dimensional spatio-temporal entropic thresholding is made out. Next, by adaptively selecting the initial search layer and the search range referring to the LUT, the proposed HBMA can effectively carry out fast motion estimation and extract object-included region in the hierarchical pyramid structure. Finally, after we define the thresholded gradient image in the object-included region, and apply the morphological segmentation method to the object-included region pixel by pixel and extract the moving object included in video sequence. As shown in the results of computer simulation, the proposed method provides relatively good segmentation results for moving object and specially comes up with reasonable segmentation results in the edge areas with lower contrast.

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Ship Pipe Layout Optimization using Genetic Algorithm (유전자 알고리듬을 이용한 선박용 파이프 경로 최적화)

  • Park, Cheol-Woo;Cheon, Ho-Jeong
    • Journal of the Korean Society for Precision Engineering
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    • v.29 no.4
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    • pp.469-478
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    • 2012
  • This study aims to discover the optimal pipe layout for a ship, which generally needs a lot of time, efforts and experiences. Genetic algorithm was utilized to search for the optimum. Here the optimum stands for the minimum pipe length between two given points. Genetic algorithm is applied to planar pipe layout problems to confirm plausible and efficiency. Sub-programs are written to find optimal layout for the problems. Obstacles are laid in between the starting point and the terminal point. Pipe is supposed to bypass those obstacles. Optimal layout between the specified two points can be found using the genetic algorithm. Each route was searched for three case models in two-dimensional plane. In consequence of this, it discovered the optimum route with the minimized distance in three case models. Through this study, it is possible to apply optimization of ship pipe route to an actual ship using genetic algorithm.

Two-Dimensional Binary Search on Length Using Bloom Filter for Packet Classification (블룸 필터를 사용한 길이에 대한 2차원 이진검색 패킷 분류 알고리즘)

  • Choe, Young-Ju;Lim, Hye-Sook
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.37 no.4B
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    • pp.245-257
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    • 2012
  • As one of the most challenging tasks in designing the Internet routers, packet classification is required to achieve the wire-speed processing for every incoming packet. Packet classification algorithm which applies binary search on trie levels to the area-based quad-trie is an efficient algorithm. However, it has a problem of unnecessary access to a hash table, even when there is no node in the corresponding level of the trie. In order to avoid the unnecessary off-chip memory access, we proposed an algorithm using Bloom filters along with the binary search on levels to multiple disjoint tries. For ACL, FW, IPC sets with about 1000, 5000, and 10000 rules, performance evaluation result shows that the search performance is improved by 21 to 33 percent by adding Bloom filters.

Design of Distributed Modal Transducer by Optimizing Gain-weights of Interface Circuit (인터페이스 회로의 이득 최적화를 통한 분포형 모달 변환기의 설계)

  • 김지철;황준석;유정규;김승조
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 1998.04a
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    • pp.444-449
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    • 1998
  • A modal transducer in two-dimensional structure can be implemented by varying the distributed transducer's gain spatially. In this paper, a method based on finite element method is developed for optimizing spatial gain distribution of PVDF transducer to create the modal transducer for specific modes. Using this concept, one can design the modal transducer in two-dimensional structure having arbitrary geometry and boundary conditions. As a practical means for implementing this continuous gain distribution without repoling die PVDF film, the gain distribution is approximated by optimizing gain-weights of interface circuit. The whole spatial area of the PVDF film is divided into several electrode segments and the signals from each segment are properly weighted and summed by interface circuit. This corresponds to the approximation of a continuous function using discrete values. The electrode partition is optimized using the genetic algorithm. Gain-weights are optimized using the simplex search method. A modal sensor for first to fourth modes of aluminum plate is designed using PVDF film with gain-weighted interface circuit. Various lamination angles of PVDF film are taken into consideration to utilize the anisotropy of the PVDF film. Performance of the optimized' PVDF sensor is demonstrated by numerical simulations..

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Tabu Search-Genetic Process Mining Algorithm for Discovering Stochastic Process Tree (확률적 프로세스 트리 생성을 위한 타부 검색 -유전자 프로세스 마이닝 알고리즘)

  • Joo, Woo-Min;Choi, Jin Young
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.42 no.4
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    • pp.183-193
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    • 2019
  • Process mining is an analytical technique aimed at obtaining useful information about a process by extracting a process model from events log. However, most existing process models are deterministic because they do not include stochastic elements such as the occurrence probabilities or execution times of activities. Therefore, available information is limited, resulting in the limitations on analyzing and understanding the process. Furthermore, it is also important to develop an efficient methodology to discover the process model. Although genetic process mining algorithm is one of the methods that can handle data with noises, it has a limitation of large computation time when it is applied to data with large capacity. To resolve these issues, in this paper, we define a stochastic process tree and propose a tabu search-genetic process mining (TS-GPM) algorithm for a stochastic process tree. Specifically, we define a two-dimensional array as a chromosome to represent a stochastic process tree, fitness function, a procedure for generating stochastic process tree and a model trace as a string of activities generated from the process tree. Furthermore, by storing and comparing model traces with low fitness values in the tabu list, we can prevent duplicated searches for process trees with low fitness value being performed. In order to verify the performance of the proposed algorithm, we performed a numerical experiment by using two kinds of event log data used in the previous research. The results showed that the suggested TS-GPM algorithm outperformed the GPM algorithm in terms of fitness and computation time.