• 제목/요약/키워드: evidence fusion

검색결과 103건 처리시간 0.022초

Multi-Level Fusion Processing Algorithm for Complex Radar Signals Based on Evidence Theory

  • Tian, Runlan;Zhao, Rupeng;Wang, Xiaofeng
    • Journal of Information Processing Systems
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    • 제15권5호
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    • pp.1243-1257
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    • 2019
  • As current algorithms unable to perform effective fusion processing of unknown complex radar signals lacking database, and the result is unstable, this paper presents a multi-level fusion processing algorithm for complex radar signals based on evidence theory as a solution to this problem. Specifically, the real-time database is initially established, accompanied by similarity model based on parameter type, and then similarity matrix is calculated. D-S evidence theory is subsequently applied to exercise fusion processing on the similarity of parameters concerning each signal and the trust value concerning target framework of each signal in order. The signals are ultimately combined and perfected. The results of simulation experiment reveal that the proposed algorithm can exert favorable effect on the fusion of unknown complex radar signals, with higher efficiency and less time, maintaining stable processing even of considerable samples.

What is the Role of Epidural Injections in the Treatment of Lumbar Discogenic Pain: A Systematic Review of Comparative Analysis with Fusion

  • Manchikanti, Laxmaiah;Staats, Peter S.;Nampiaparampil, Devi E.;Hirsch, Joshua A.
    • The Korean Journal of Pain
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    • 제28권2호
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    • pp.75-87
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    • 2015
  • Background: Lumbar discogenic pain without pain mediated by a disc herniation, facet joints, or the sacroiliac joints, is common and often results in chronic, persistent pain and disability. After conservative treatment failure, injection therapy, such as an epidural injection, is frequently the next step considered in managing discogenic pain. The objective of this systematic review is to determine the efficacy of lumbar epidural injections in managing discogenic pain without radiculopathy, and compare this approach to lumbar fusion or disc arthroplasty surgery. Methods: A systematic review of randomized trials published from 1966 through October 2014 of all types of epidural injections and lumbar fusion or disc arthroplasty in managing lumbar discogenic pain was performed with methodological quality assessment and grading of evidence. The level of evidence was based on the grading of evidence criteria which, was conducted using 5 levels of evidence ranging from levels I to V. Results: Based on a qualitative assessment of the evidence for both approaches, there is Level II evidence for epidural injections, either caudal or lumbar interlaminar. Conclusions: The available evidence suggests fluoroscopically directed epidural injections provide long-term improvement in back and lower extremity pain for patients with lumbar discogenic pain. There is also limited evidence showing the potential effectiveness of surgical interventions compared to nonsurgical treatments.

Improved Dynamic Subjective Logic Model with Evidence Driven

  • Qiang, Jiao-Hong;Xin, Wang-Xin;Feng, Tian-Jun
    • Journal of Information Processing Systems
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    • 제11권4호
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    • pp.630-642
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    • 2015
  • In Jøsang's subjective logic, the fusion operator is not able to fuse three or more opinions at a time and it cannot consider the effect of time factors on fusion. Also, the base rate (a) and non-informative prior weight (C) could not change dynamically. In this paper, we propose an Improved Subjective Logic Model with Evidence Driven (ISLM-ED) that expands and enriches the subjective logic theory. It includes the multi-agent unified fusion operator and the dynamic function for the base rate (a) and the non-informative prior weight (C) through the changes in evidence. The multi-agent unified fusion operator not only meets the commutative and associative law but is also consistent with the researchers's cognitive rules. A strict mathematical proof was given by this paper. Finally, through the simulation experiments, the results show that the ISLM-ED is more reasonable and effective and that it can be better adapted to the changing environment.

웹 검색 성능 최적화를 위한 융합적 방식 (Fusion Approach for Optimizing Web Search Performance)

  • 양기덕
    • 정보관리학회지
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    • 제32권1호
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    • pp.7-22
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    • 2015
  • 이 논문은 시스템 성능을 최적화하기 위해 정적 및 동적 튜닝 방법을 이용한 웹 융합검색 연구의 내용을 보고합니다. 기존의 융합 방식을 넘어선 "다이나믹 튜닝"이라는 과정을 도입하여 웹의 다양한 정보소스의 기여를 최적화 시킬 수 있는 융합 공식을 생성하는 방법을 조사한 이 연구의 결과는 웹 검색 환경의 풍요로운 여러 데이터 소스를 활용하는 것이 효과적인 전략이라는 것을 보여주었습니다. 본 연구에서는 즉각적인 시스템 피드백 인지분석을 기반으로 융합 매개 변수를 미세 조정하는 반복적 인 다이나믹 튜닝 과정을 통해 크게 검색 성능을 향상시킬 수 있었습니다.

Multimodal Data Fusion for Alzheimers Patients Using Dempster-Shafer Theory of Evidence

  • Majumder, Dwijesh Dutta;Bhattacharya, Nahua
    • 한국지능시스템학회:학술대회논문집
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    • 한국퍼지및지능시스템학회 1998년도 The Third Asian Fuzzy Systems Symposium
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    • pp.713-718
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    • 1998
  • The paper is part of an investigation by the authors on development of a knowledge based frame work for multimodal medical image in collaboration with the All India Institute of Medical Science, new Delhi. After presenting the key aspects of the Dempster-Shafer Evidence theory we have presented implementation of registration and fusion of T₁and T₂ weighted MR images and CT images of the brain of an Alzheimer's patient for minimising the uncertainty and increasing the reliability for dianostics and therapeutic planning.

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Combining Multiple Sources of Evidence to Enhance Web Search Performance

  • Yang, Kiduk
    • 한국도서관정보학회지
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    • 제45권3호
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    • pp.5-36
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    • 2014
  • 웹은 하이퍼링크 및 야후와 같이 수동으로 분류된 웹 디렉토리 처럼 문서의 콘텐츠를 넘어선 다양한 정보의 소스가 풍부하다. 이 연구는 웹문서 내용을 활용한 텍스트기반의 검색 방식, 하이퍼 링크를 활용한 링크 기반의 검색 방식, 그리고 야후의 카테고리를 활용한 분류 기반의 검색 방식을 융합하므로서 여러 정보소스를 결합하면 검색 성능을 향상시킬 수 있다는 기존 융합검색연구들을 확장시켰다. 텍스트, 링크, 분류 기반 검색 결과를 여러가지 선형조합식으로 생성한 융합결과를 기존의 검색 평가 지표를 사용하여 각각의 검색 결과와 비교 한 후, 검색결과 오버랩의 중요성 또한 조사 하였다. 본 연구는 텍스트, 링크, 분류 기반 검색의 솔루션 스패이스들의 다양성이 융합검색의 적합성을 제시한다는 결론과 더불어 시스템 파라미터의 영향, 그리고 오버랩, 문서순위, 관련성들의 상호 관계 같은 융합 환경의 중요한 특성들을 분석하였다.

Evidence gathering for line based recognition by real plane

  • 이재규;류문욱;이장원
    • 한국HCI학회:학술대회논문집
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    • 한국HCI학회 2008년도 학술대회 1부
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    • pp.195-199
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    • 2008
  • We present an approach to detect real plane for line base recognition and pose estimation Given 3D line segments, we set up reference plane for each line pair and measure the normal distance from the end point to the reference plane. And then, normal distances are measured between remains of line endpoints and reference plane to decide whether these lines are coplanar with respect to the reference plane. After we conduct this coplanarity test, we initiate visibility test using z-buffer value to prune out ambiguous planes from reference planes. We applied this algorithm to real images, and the results are found useful for evidence fusion and probabilistic verification to assist the line based recognition as well as 3D pose estimation.

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Evidential Fusion of Multsensor Multichannel Imagery

  • Lee Sang-Hoon
    • 대한원격탐사학회지
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    • 제22권1호
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    • pp.75-85
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    • 2006
  • This paper has dealt with a data fusion for the problem of land-cover classification using multisensor imagery. Dempster-Shafer evidence theory has been employed to combine the information extracted from the multiple data of same site. The Dempster-Shafer's approach has two important advantages for remote sensing application: one is that it enables to consider a compound class which consists of several land-cover types and the other is that the incompleteness of each sensor data due to cloud-cover can be modeled for the fusion process. The image classification based on the Dempster-Shafer theory usually assumes that each sensor is represented by a single channel. The evidential approach to image classification, which utilizes a mass function obtained under the assumption of class-independent beta distribution, has been discussed for the multiple sets of mutichannel data acquired from different sensors. The proposed method has applied to the KOMPSAT-1 EOC panchromatic imagery and LANDSAT ETM+ data, which were acquired over Yongin/Nuengpyung area of Korean peninsula. The experiment has shown that it is greatly effective on the applications in which it is hard to find homogeneous regions represented by a single land-cover type in training process.

다중 시기 SAR 자료를 이용한 토지 피복 구분을 위한 특징 추출과 융합 (Feature Extraction and Fusion for land-Cover Discrimination with Multi-Temporal SAR Data)

  • 박노욱;이훈열;지광훈
    • 대한원격탐사학회지
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    • 제21권2호
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    • pp.145-162
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    • 2005
  • SAR 자료의 분류에서 토지 피복 구분 분류 정확도의 향상을 위해 이 논문은 다중 시기 SAR 자료를 이용한 분류에서의 특징 추출과 정보 융합 방법론을 제시하였다. 다중 시기 SAR 센서의 산란 특성을 고려하여 평균 후방 산란계수, 시간적 변이도와 긴밀도를 특징으로서 추출하였다. 이렇게 추출된 특징의 효율적인 응합을 위해 Dempster-Shafer theory of evidence(D-S 이론)와 퍼지 논리를 적용하였다. 특히 D-S 이론의 적용시 특징 기반 mass function 할당을 제안하였고, 퍼지 논리의 적용시 다양한 퍼지 결합 연산자의 결과를 비교하였다. 다중 시기 Radarsat-1 자료에의 적용 결과, 추출된 특징들은 서로 상호 보완적인 정보를 제공할 수 있으며 수계, 논과 도심지를 효율적으로 구분할 수 있었다. 그러나 산림과 밭은 구분이 애매한 경우가 나타났다. 정보 융합 방법론 측면에서, D-S 이론과 퍼지 Max와 Algebraic Sum 연산자를 제외한 다른 퍼지 연산자는 서로 유사한 분류 정확도를 나타내었다.