• Journal of Information Processing Systems
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• v.15 no.5
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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.

• The Korean Journal of Pain
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• v.28 no.2
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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.

• Journal of Information Processing Systems
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• v.11 no.4
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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.

• Journal of the Korean Society for information Management
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• v.32 no.1
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• pp.7-22
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• 2015

This paper describes a Web search optimization study that investigates both static and dynamic tuning methods for optimizing system performance. We extended the conventional fusion approach by introducing the "dynamic tuning" process with which to optimize the fusion formula that combines the contributions of diverse sources of evidence on the Web. By engaging in iterative dynamic tuning process, where we successively fine-tuned the fusion parameters based on the cognitive analysis of immediate system feedback, we were able to significantly increase the retrieval performance. Our results show that exploiting the richness of Web search environment by combining multiple sources of evidence is an effective strategy.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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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.

• Journal of Korean Library and Information Science Society
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• v.45 no.3
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• pp.5-36
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• 2014

The Web is rich with various sources of information that go beyond the contents of documents, such as hyperlinks and manually classified directories of Web documents such as Yahoo. This research extends past fusion IR studies, which have repeatedly shown that combining multiple sources of evidence (i.e. fusion) can improve retrieval performance, by investigating the effects of combining three distinct retrieval approaches for Web IR: the text-based approach that leverages document texts, the link-based approach that leverages hyperlinks, and the classification-based approach that leverages Yahoo categories. Retrieval results of text-, link-, and classification-based methods were combined using variations of the linear combination formula to produce fusion results, which were compared to individual retrieval results using traditional retrieval evaluation metrics. Fusion results were also examined to ascertain the significance of overlap (i.e. the number of systems that retrieve a document) in fusion. The analysis of results suggests that the solution spaces of text-, link-, and classification-based retrieval methods are diverse enough for fusion to be beneficial while revealing important characteristics of the fusion environment, such as effects of system parameters and relationship between overlap, document ranking and relevance.

• 한국HCI학회:학술대회논문집
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• 2008.02a
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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.

• Proceedings of the Korean Radioactive Waste Society Conference
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• 2005.11a
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• pp.189-190
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• 2005

• Korean Journal of Remote Sensing
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• v.22 no.1
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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.

• Korean Journal of Remote Sensing
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• v.21 no.2
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• pp.145-162
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• 2005

To improve the accuracy of land-cover discrimination in SAB data classification, this paper presents a methodology that includes feature extraction and fusion steps with multi-temporal SAR data. Three features including average backscattering coefficient, temporal variability and coherence are extracted from multi-temporal SAR data by considering the temporal behaviors of backscattering characteristics of SAR sensors. Dempster-Shafer theory of evidence(D-S theory) and fuzzy logic are applied to effectively integrate those features. Especially, a feature-driven heuristic approach to mass function assignment in D-S theory is applied and various fuzzy combination operators are tested in fuzzy logic fusion. As experimental results on a multi-temporal Radarsat-1 data set, the features considered in this paper could provide complementary information and thus effectively discriminated water, paddy and urban areas. However, it was difficult to discriminate forest and dry fields. From an information fusion methodological point of view, the D-S theory and fuzzy combination operators except the fuzzy Max and Algebraic Sum operators showed similar land-cover accuracy statistics.