• 제목/요약/키워드: nearest neighbor

검색결과 848건 처리시간 0.028초

이동객체 방향정보를 이용한 연속궤적최근접질의 (Continuous Trajectory Nearest Neighbor Query using the Direction Information of Moving Objects)

  • 조진연;이언배
    • 한국정보처리학회:학술대회논문집
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    • 한국정보처리학회 2006년도 춘계학술발표대회
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    • pp.59-62
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    • 2006
  • 최근접 질의 (NN: Nearest Neighbor Query)는 질의 요청자와 가장 가까운 곳에 위치한 대상 객체를 검색하기 위한 질의로서, 이 질의 방법을 실세계 이동 객체에 바로 적용하였을 경우, 실세계의 도로정보를 고려하지 않아 적절한 결과를 제공하지 못한다. 예를 들어, 사용자의 이동 방향과는 반대 방향에 위치한 객체가 질의 결과로 반환 될 경우, 사용자가 검색된 객체에 접근하기 위한 시간과 비용이 증가하는 문제가 발생한다. 또한 질의 객체와 대상 객체가 모두 이동할 경우에는 일정시점에서 질의한 결과는 조금만 시간이 지나면 유효하지 않게 된다. 이러한 문제를 해결하기 위하여 질의 객체와 데이터 객체가 모두 이동 객체인 경우에 적합하게 사용될 수 있도록 이동체의 궤적 정보를 방향정보 가중치로 환산한 근접 질의처리 방법을 제안한다.

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Dynamic threshold location algorithm based on fingerprinting method

  • Ding, Xuxing;Wang, Bingbing;Wang, Zaijian
    • ETRI Journal
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    • 제40권4호
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    • pp.531-536
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    • 2018
  • The weighted K-nearest neighbor (WKNN) algorithm is used to reduce positioning accuracy, as it uses a fixed number of neighbors to estimate the position. In this paper, we propose a dynamic threshold location algorithm (DH-KNN) to improve positioning accuracy. The proposed algorithm is designed based on a dynamic threshold to determine the number of neighbors and filter out singular reference points (RPs). We compare its performance with the WKNN and Enhanced K-Nearest Neighbor (EKNN) algorithms in test spaces of networks with dimensions of $20m{\times}20m$, $30m{\times}30m$, $40m{\times}40m$ and $50m{\times}50m$. Simulation results show that the maximum position accuracy of DH-KNN improves by 31.1%, and its maximum position error decreases by 23.5%. The results demonstrate that our proposed method achieves better performance than other well-known algorithms.

Detection and Classification of Bearing Flaking Defects by Using Kullback Discrimination Information (KDI)

  • Kim, Tae-Gu;Takabumi Fukuda;Hisaji Shimizu
    • International Journal of Safety
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    • 제1권1호
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    • pp.28-35
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    • 2002
  • Kullback Discrimination Information (KDI) is one of the pattern recognition methods. KDI defined as a measure of the mutual dissimilarity computed between two time series was studied for detection and classification of bearing flaking on outer-race and inner-races. To model the damages, the bearings in normal condition, outer-race flaking condition and inner-races flaking condition were provided. The vibration sensor was attached by the bearing housing. This produced the total 25 pieces of data each condition, and we chose the standard data and measure of distance between standard and tested data. It is difficult to detect the flaking because similar pulses come out when balls pass the defection point. The detection and classification method for inner and outer races are defected by KDI and nearest neighbor classification rule is proposed and its high performance is also shown.

An Efficient Multidimensional Index Structure for Parallel Environments

  • Bok Koung-Soo;Song Seok-Il;Yoo Jae-Soo
    • International Journal of Contents
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    • 제1권1호
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    • pp.50-58
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    • 2005
  • Generally, multidimensional data such as image and spatial data require large amount of storage space. There is a limit to store and manage those large amounts of data in single workstation. If we manage the data on parallel computing environment which is being actively researched these days, we can get highly improved performance. In this paper, we propose a parallel multidimensional index structure that exploits the parallelism of the parallel computing environment. The proposed index structure is nP(processor)-nxmD(disk) architecture which is the hybrid type of nP-nD and 1P-nD. Its node structure in-creases fan-out and reduces the height of an index. Also, a range search algorithm that maximizes I/O parallelism is devised, and it is applied to k-nearest neighbor queries. Through various experiments, it is shown that the proposed method outperforms other parallel index structures.

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디지털 스캔 이미지의 보간방법에 관한 연구 (A study on the Interpolation method of Digital scan image)

  • 이성형;조가람;구철희
    • 한국인쇄학회지
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    • 제16권3호
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    • pp.81-95
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    • 1998
  • If a image doesn't include sufficient data of output size and resolution, we will scan again the image. Interpolation generates a new pixel by methematical average of processing. In the interpolation method, there are nearest neighbor interpolation, bilinear interpolation and bicubic interpolation etc. This study was carried out for the purpose of researching compatible method to digital scan image caused by only different interpolation methods. Nearest neighbor interpolation show superior effect in the drawing image. Bilinear interpolation show reduction in detail and contrast. Bicubic interpolation show superior effect in the digital photo image USM(Unsharp Mask) application after extension by interpolation show better than extension by interpolation after USM(unsharp mask) application.

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방범용 CCTV를 위한 배회행위 탐지 솔루션 (Loitering Detection Solution for CCTV Security System)

  • 강주형;곽수영
    • 한국멀티미디어학회논문지
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    • 제17권1호
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    • pp.15-25
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    • 2014
  • 본 논문에서는 지능형 감시 시스템을 위해 공간적 확률 분포와 방향 서술자를 이용하여 다양한 배회행위를 검출하는 방법을 제안한다. 적응적 배경 모델링 기법을 이용하여 움직이는 객체를 검출하고, 검출된 객체로부터 움직임의 정보를 추출한다. 추출된 객체의 움직임 정보는 이동 궤적과 방향에 대해 특징벡터를 생성한다. 생성된 특징벡터는 k-Nearest Neighbor를 통해 최종적으로 배회행위를 검출하게 된다. 제안한 방법을 실내외 다양한 환경에서 테스트하여 배회 행위를 검출하는 결과를 나타내었으며 이는 실시간으로 검출되는 것을 확인하였다.

Combining Different Distance Measurements Methods with Dempster-Shafer-Theory for Recognition of Urdu Character Script

  • Khan, Yunus;Nagar, Chetan;Kaushal, Devendra S.
    • International Journal of Ocean System Engineering
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    • 제2권1호
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    • pp.16-23
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    • 2012
  • In this paper we discussed a new methodology for Urdu Character Recognition system using Dempster-Shafer theory which can powerfully estimate the similarity ratings between a recognized character and sampling characters in the character database. Recognition of character is done by five probability calculation methods such as (similarity, hamming, linear correlation, cross-correlation, nearest neighbor) with Dempster-Shafer theory of belief functions. The main objective of this paper is to Recognition of Urdu letters and numerals through five similarity and dissimilarity algorithms to find the similarity between the given image and the standard template in the character recognition system. In this paper we develop a method to combine the results of the different distance measurement methods using the Dempster-Shafer theory. This idea enables us to obtain a single precision result. It was observed that the combination of these results ultimately enhanced the success rate.

신경망과 그래픽 기법을 이용한 심전도 결과지 이미징 시스템 (An ECG Document Imaging System based on Neural Network and Graphic Techniques)

  • 김진상;최상열;배인호;김윤년
    • 한국지능시스템학회:학술대회논문집
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    • 한국퍼지및지능시스템학회 2006년도 춘계학술대회 학술발표 논문집 제16권 제1호
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    • pp.269-272
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    • 2006
  • 병원의 각종 측정 장비에서 출력되는 결과지나 의사들이 작성한 기록지를 스캔하여 이미지형태로 저장하는 이미징 시스템 개발이 크게 요구되고 있다. 본 논문에서는 신경망과 그래픽 기법을 사용하여 대학병원 심전도실에서 사용되는 여섯 종류의 심전도 출력지를 이미지 형태로 저장하고 검색하는 이미징 시스템의 설계와 구현에 대해 논하였다. 구현된 시스템은 여섯 종류의 심전도 출력지를 분류하고, 분류된 각 출력지에 인쇄된 중요한 측정 데이터를 인식하여 데이터베이스에 저장한다. 심전도 출력지의 분류는 각 샘플 서식들의 평균 히스토그램을 구한 다음 새로운 출력지가 들어올 때 평균 히스토그램과의 거리가 가장 가까운 출력지로 분류하는 nearest-neighbor 방법을 사용하였다. 출력지에 인쇄된 데이터의 인식을 위해 먼저 XML로 작성한 출력지별 추출 정보를 기반으로 스캔한 이미지의 영역 분할 작업을 수행한다. 분할된 영역들은 신경망을 이용해 문자 인식을 하고, 인식된 문자들이 데이터베이스의 해당 속성값으로 저장된다. 스캔한 출력지는 의사들이 주석을 붙이거나 조건 검색을 위해 이미지 형태로 저장된다.

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Client-Side Caching for Nearest Neighbor Queries

  • Park Kwangjin;Hwang Chong-Sun
    • Journal of Communications and Networks
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    • 제7권4호
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    • pp.417-428
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    • 2005
  • The Voronoi diagram (VD) is the most suitable mechanism to find the nearest neighbor (NN) for mobile clients. In NN query processing, it is important to reduce the query response time, since a late query response may contain out-of-date information. In this paper, we study the issue of location dependent information services (LDISs) using a VD. To begin our study, we first introduce a broadcast-based spatial query processing methods designed to support NN query processing. In further sections, we introduce a generic method for location-dependent sequential prefetching and caching. The performance of this scheme is studied in different simulated environments. The core contribution of this research resides in our analytical proof and experimental results.

코호넨 신경회로망을 이용한 ULTC 변압기와 STACOM의 협조제어 (Coordination Control of ULTC Transformer and STACOM using Kohonen Neural Network)

  • 김광원;이흥재
    • 대한전기학회논문지:전력기술부문A
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    • 제48권9호
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    • pp.1103-1111
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    • 1999
  • STACOM will be utilized to control substation voltage in the near future. Although STACOM shows good voltage regulation performance owing to its rapid and continuous response, it needs additional reactive power compensation device to keep control margin for emergency such as fault. ULTC transformer is one of good candidates. This paper presents a Kohonen Neural Network (KNN) based coordination control scheme of ULTC transformer and STACOM. In this paper, the objective function of the coordination control is minimization of both STACOM output and the number of switchings of ULTC transformer while maintaining substation voltage magnitude to the predefined constant value. This coordination, control is performed based on reactive load trend of the substation and KNN which offers optimal tap position in view of STACOM output minimization. The input variables of KNN are active and reactive power of the substation, current tap position, and current STACOM output. The KNN is trained by effective Iterative Condensed Nearest Neighbor (ICNN) rule. This coordination control applied to IEEE 14 bus system and shows satisfactory results.

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