• 제목/요약/키워드: Multiple method

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Procedures for Detecting Multiple Outliers in Linear Regression Using R

  • Kwon, Soon-Sun;Lee, Gwi-Hyun;Park, Sung-Hyun
    • 한국통계학회:학술대회논문집
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    • 한국통계학회 2005년도 추계 학술발표회 논문집
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    • pp.13-17
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    • 2005
  • In recent years, many people use R as a statistics system. R is frequently updated by many R project teams. We are interested in the method of multiple outlier detection and know that R is not supplied the method of multiple outlier detection. In this talk, we review these procedures for detecting multiple outliers and provide more efficient procedures combined with direct methods and indirect methods using R.

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TDOA기법 기반의 다중 재머 위치 추정 알고리즘 설계 (A Design of Multiple Jammers Localization Algorithm Based on TDOA Method)

  • 강희원;임덕원;허문범
    • 한국군사과학기술학회지
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    • 제15권6호
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    • pp.729-737
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    • 2012
  • In case that multiple jammers are transmitting the signals which are the same type a general algorithm based on TDOA method cannot estimate the positions of multiple jammers because there are many TDOA measurements including true and false values. This paper, therefore, designs a new algorithm based on TDOA method to localize multiple jammers. In this algorithm, TDOA measurements are obtained by rotating the reference sensor, and then the positions of multiple jammers can be estimated by detecting congregated point among the multiple estimated positions from TDOA measurements. Through computer simulations, it is verified that this algorithm localizes the multiple jammers well. The performance of the algorithm are also analysed by changing the distance between sensors and jammer, and sampling frequency.

유비쿼터스 환경에서 다중 상황 적응적인 효과적인 권유 기법 (Effective Recommendation Method Adaptive to Multiple Contexts in Ubiquitous Environments)

  • 권준희
    • 한국콘텐츠학회논문지
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    • 제6권5호
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    • pp.1-8
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    • 2006
  • 유비쿼터스 환경 하에서 다중 상황 기반 권유 서비스에 대한 요구가 증대하고 있다. 이러한 환경에서는 상황의 수가 증가함에 따라 권유 정보의 양이 크게 증가하게 되어 효과적인 정보 제공이 어려워진다는 문제를 가진다. 이를 위해 본 논문에서는 유비쿼터스 환경에서 다중 상황 적응적인 효과적인 권유 기법을 제안한다. 본 제안 기법에서는 상황별로 의미 있는 정보를 제공할 수 있도록 하기 위해 사용자들의 상황별 선호도와 행위를 권유 정보의 양을 결정하는 가중치 요소로서 사용한다. 이를 위해 권유 기법과 시나리오를 제시하고, 본 논문에서 제안하는 기법의 효과성을 실험을 통해 평가한다.

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A Method for Local Collision-free Motion Coordination of Multiple Mobile Robots

  • Ko, Nak-Yong;Seo, Dong-Jin;Kim, Koung-Suk
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2003년도 ICCAS
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    • pp.1609-1614
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    • 2003
  • This paper presents a new method driving multiple robots to their goal position without collision. To consider the movement of the robots in a work area, we adopt the concept of avoidability measure. To implement the concept in collision avoidance of multiple robots, relative distance between the robots is proposed. The relative distance is a virtual distance between robots indicating the threat of collision between the robots. Based on the relative distance, the method calculates repulsive force against a robot from the other robots. Also, attractive force toward the goal position is calculated in terms of the relative distance. The proposed method is simulated for several cases. The results show that the proposed method steers robots to open space anticipating the approach of other robots. The proposed method works as a local collision-free motion coordination method in conjunction with higher level of task planning and path planning method for multiple robots to do a collaborative job.

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INS 속도와 다중 상관기를 이용한 고속 항체용 GPS 수신기의 빠른 신호 획득 기법 (A Fast GPS Signal Acquisition Method for High Speed Vehicles Using INS Velocity and Multiple Correlators)

  • 정호철;김정원;황동환;이상정;이태규;송기원
    • 제어로봇시스템학회논문지
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    • 제14권6호
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    • pp.603-607
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    • 2008
  • This paper proposes a fast acquisition method using INS velocity and multiple correlators for high speed vehicles. In order to reduce acquisition time in GPS receiver, the method utilizes inertial velocity information and multiple correlators. Search range of the Doppler frequency is reduced by using INS velocity and the number of cells at one search can be increased by using multiple correlators. By using both multiple correlators and the INS velocity in the acquisition, search space can be greatly reduced. Experimental results show that the method gives faster signal acquisition performance than the conventional method.

만족도 함수의 편향과 산포를 고려한 다중반응표면최적화 기법 개발 (Development of a Multiple Response Surface Method Considering Bias and Variance of Desirability Functions)

  • 정기효;이상기
    • 대한산업공학회지
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    • 제38권1호
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    • pp.25-30
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    • 2012
  • Desirability approaches have been proposed to find an optimum of multiple response problem. The existing desirability approaches use either of mean or min of individual desirability in aggregation of multiple responses. However, in order to find an optimum having high mean and low dispersion among individual desirability, the dispersion needs to be simultaneously considered with its mean. This study proposes bias and variance (BV) method which aggregates bias (ideal target-mean) and variance of individual desirability in multiple response optimization. The proposed BV method was applied to an example to evaluate its usefulness by comparing with existing methods. Evaluation results showed that the solution of BV method was a fairly good compared with DS (Derringer and Suich, 1980) and KL (Kim and Lin, 2000) methods. The BV method can be utilized to multiple response surface problems when decision makers want to find an optimum having high mean and low variance among responses.

A MULTIPHASE LEVEL SET FRAMEWORK FOR IMAGE SEGMENTATION USING GLOBAL AND LOCAL IMAGE FITTING ENERGY

  • TERBISH, DULTUYA;ADIYA, ENKHBOLOR;KANG, MYUNGJOO
    • Journal of the Korean Society for Industrial and Applied Mathematics
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    • 제21권2호
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    • pp.63-73
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    • 2017
  • Segmenting the image into multiple regions is at the core of image processing. Many segmentation formulations of an images with multiple regions have been suggested over the years. We consider segmentation algorithm based on the multi-phase level set method in this work. Proposed method gives the best result upon other methods found in the references. Moreover it can segment images with intensity inhomogeneity and have multiple junction. We extend our method (GLIF) in [T. Dultuya, and M. Kang, Segmentation with shape prior using global and local image fitting energy, J.KSIAM Vol.18, No.3, 225-244, 2014.] using a multiphase level set formulation to segment images with multiple regions and junction. We test our method on different images and compare the method to other existing methods.

Multiple fault diagnosis method using a neural network

  • Lee, Sanggyu;Park, Sunwon
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1993년도 한국자동제어학술회의논문집(국제학술편); Seoul National University, Seoul; 20-22 Oct. 1993
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    • pp.109-114
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    • 1993
  • It is well known that neural networks can be used to diagnose multiple faults to some limited extent. In this work we present a Multiple Fault Diagnosis Method (MFDM) via neural network which can effectively diagnose multiple faults. To diagnose multiple fault, the proposed method finds the maximum value in the output nodes of the neural network and decreases the node value by changing the hidden node values. This method can find the other faults by computing again with the changed hidden node values. The effectiveness of this method is explored through a neural-network-based fault diagnosis case study of a fluidized catalytic cracking unit (FCCU).

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랜덤화 블록 모형에서 정렬 방법을 이용한 비모수 다중비교법 (Nonparametric Multiple Comparison Procedure Using Alignment Method Under Randomized Block Design)

  • 한지웅;김동재
    • 응용통계연구
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    • 제19권3호
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    • pp.555-564
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    • 2006
  • 랜덤화 블록 모형하에서의 비모수 다중비교방법으로는 Friedman 순위합 다중비교 방법(McDonald와 Thompson, 1967)이 있다. 이 방법은 블록내 순위를 이용하여 블록간 정보를 이용하지 못하였다. 이런 단점을 보완하기 위하여 본 논문에서는 Hodges와 Lehmann(1962)이 제안한 정렬방법을 이용한 새로운 비모수 다중비교방법을 제안한다. 또한 모의실험을 통하여 여러 다중비교방법의 검정력을 비교하였다.

반도체 웨이퍼 ID 인식을 위한 다중템플릿형 영상분할 알고리즘 개발 (Development of a Multi-template type Image Segmentation Algorithm for the Recognition of Semiconductor Wafer ID)

  • 안인모
    • 전기학회논문지P
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    • 제55권4호
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    • pp.167-175
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    • 2006
  • This paper presents a method to segment semiconductor wafer ID on poor quality images. The method is based on multiple templates and normalized gray-level correlation (NGC) method. If the lighting condition is not so good and hence, we can not control the image quality, target image to be inspected presents poor quality ID and it is not easy to identify and then recognize the ID characters. Conventional several method to segment the interesting ID regions fails on the bad quality images. In this paper, we propose a multiple template method, which uses combinational relation of multiple templates from model templates to match several characters of the inspection images. To find out the optimal solution of multiple template model in ID regions, we introduce newly-developed snake algorithm. Experimental results using images from real FA environment are presented.