• 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.

• Nuclear Engineering and Technology
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• v.46 no.1
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• pp.11-26
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• 2014

The analyses carried out within the Seismic Probabilistic Risk Assessments (SPRAs) of Nuclear Power Plants (NPPs) are affected by significant aleatory and epistemic uncertainties. These uncertainties have to be represented and quantified coherently with the data, information and knowledge available, to provide reasonable assurance that related decisions can be taken robustly and with confidence. The amount of data, information and knowledge available for seismic risk assessment is typically limited, so that the analysis must strongly rely on expert judgments. In this paper, a Dempster-Shafer Theory (DST) framework for handling uncertainties in NPP SPRAs is proposed and applied to an example case study. The main contributions of this paper are two: (i) applying the complete DST framework to SPRA models, showing how to build the Dempster-Shafer structures of the uncertainty parameters based on industry generic data, and (ii) embedding Bayesian updating based on plant specific data into the framework. The results of the application to a case study show that the approach is feasible and effective in (i) describing and jointly propagating aleatory and epistemic uncertainties in SPRA models and (ii) providing 'conservative' bounds on the safety quantities of interest (i.e. Core Damage Frequency, CDF) that reflect the (limited) state of knowledge of the experts about the system of interest.

• Proceedings of the Korea Information Processing Society Conference
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• 2000.10b
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• pp.1009-1012
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• 2000

본 논문은 현재 개발되고 있는 원격 중환자 관찰 시스템의 부 시스템인 호출 시스템의 호출 매체 결정 알고리즘에 대하여 기술한다. 이 호출 시스템은 중환자실에 입원중인 환자의 상태 변화에 따라 담당 의사나 환자 보호자를 신속하게 연락하는 역할을 담당한다. 전달되는 메시지는 연락 시점과 연락의 긴급성에 따라서 유선전화, 무선전화, 호출기, 전자우편, fax 등의 통신 매체를 한 개 또는 두 개 이상 이용하여 전달된다. 이러한 메시지의 효율적인 전달을 위하여 본 연구에서는 불확실성 추론 방법인 Dempster-Shafer 이론을 이용하여 주어진 상황에서 가장 효과적인 전달 매체를 선택하는 알고리즘을 개발하였다. Dempster-Shafer 이론을 사용함으로서, 불확실한 상황에서 효율적이고 합리적으로 메시지 전달 매체를 결정할 수 있다.

• 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.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.11 no.1
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• pp.19-24
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• 2011

Edges represent significant boundary information between objects or classes. Various methods, which are based on differential operation, such as Sobel, Prewitt, Roberts, Canny, and etc. have been proposed and widely used. The methods are based on a linear convolution of mask with pre-assigned coefficients. In this paper, we propose an edge detection method based on Dempster-Shafer's evidence theory to evaluate edgeness of the given pixel. The effectiveness of the proposed method is shown through experimental results on several test images and compared with conventional methods.

• Science of Emotion and Sensibility
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• v.5 no.1
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• pp.17-24
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• 2002

This research was the first step to develop Expert System for Evaluation of Human Sensibility, where human sensibility can be inferred from objective physiological signals. The study aim was to develop an algorithm in which human arousal level can be judged using measured physiological signals. Fuzzy theory was applied for mathematical handling of the ambiguity related to evaluation of human sensibility, and the degree of belonging to a certain sensibility dimension was quantified by membership function through which the sensibility evaluation was able to be done. Determining membership function was achieved using results from a physiological signal database of arousal/relaxation that was generated from imagination. To induce one final result (arousal level) based on measuring the results of more than 2 physiological signals and the membership function of each physiological signal, Dempster-Shafer's Rule of Combination in Evidence was applied, through which the final arousal level was inferred.

• Proceedings of the Korean Information Science Society Conference
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• 2012.06b
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• pp.510-512
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• 2012

상황인식 서비스 분야에서 불확실한 데이터를 추론하는 것은 매우 어렵고 복잡하다. 이러한 상황정보들에서 얻어지는 데이터는 불확실성을 내포하고 있어서 불확실한 추론 결과를 초래할 수 있다. 비록 불확실성 문제들을 해결하기 위해 퍼지 이론, 뉴런 네트워크, 동적 베이지안 네트워크, 은닉 마르코프 모델과 같은 여러 종류의 방법들이 제시되었지만 이러한 방법들은 가설들을 하나의 숫자에 의해 신뢰의 정도를 표시하기 때문에 많은 어려움이 있다. 본 논문에서는 사용자들이 제공받는 서비스들에 대하여 만족도를 평가한 후 수집된 데이터를 활용하여 사용자들의 상관 관계를 분석한다. 그리고 Dempster-Shafer 이론을 사용하여 사용자들로부터 측정된 믿음 값을 융합한다. 이는 불확실성 값을 낮추어 추론결과의 정확성을 높이고 증거구간을 재설정하여 사용자들에게 신뢰성 있는 적응형 서비스를 제공하게 한다.

• Proceedings of the KIEE Conference
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• 1998.07c
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• pp.896-898
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• 1998

Recent development of the digital computer and communication technology has made the concept of the adaptive protection possible, which is to adapt the operating parameters of the protective devices to the system changes, so that the best protection function can be maintained all the time. In order to achieve the adaptive protection, it is necessary to have the way to determine whether the change of the settings is needed under the certain system change or how good the current protection level is. This paper proposed the protectability index, which is a way to evaluate the protection level of the system under arbitary conditions and the operating strategy of the adaptive protection utilizing this index. It is based on an hierachical evaluation model and the evidence combination rule of the Dempster-Shafer theory.

• Proceedings of the KIEE Conference
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• 1997.07c
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• pp.988-990
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• 1997

In this paper, the design automation system is proposed, which adopts the expert system technology and fuzzy decision making technology. It has a capability of selecting the most desirable protective devices for the industrial power systems.

• International journal of advanced smart convergence
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• v.7 no.4
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• pp.185-196
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• 2018

Based on World Health Organization (WHO) children and adults have a problem with their oral health, such as Dental cavities and periodontal disease. It is not easy to obtain the high convince level of result of the dental and periodontal diseases. Because each of them have different degrees of uncertainty and there have several discounting factors (error rates) in different of survey. To solve this problem we propose the Dezert-Smarandache Theory (DSmT) for efficient combination of uncertain, imprecise and highly conflicting sources of information. Moreover, we apply the SEFP as a context reasoning. Finally, we make the simulation by using 12 surveys and compare Propotional Conflict Redistribution 5 (PCR5) and Dempster-Shafer Theory (DST) to show the belief or probability for the low, a heavy, high and ultra-high risk situation.