• Title/Summary/Keyword: non-additive measures

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Interval-valued Choquet Integrals and applications in pricing risks (구간치 쇼케이적분과 위험률 가격 측정에서의 응용)

  • Jang, Lee-Chae
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2007.04a
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    • pp.209-212
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    • 2007
  • Non-additive measures and their corresponding Choquet integrals are very useful tools which are used in both insurance and financial markets. In both markets, it is important to to update prices to account for additional information. The update price is represented by the Choquet integral with respect to the conditioned non-additive measure. In this paper, we consider a price functional H on interval-valued risks defined by interval-valued Choquet integral with respect to a non-additive measure. In particular, we prove that if an interval-valued pricing functional H satisfies the properties of monotonicity, comonotonic additivity, and continuity, then there exists an two non-additive measures ${\mu}_1,\;{\mu}_2$ such that it is represented by interval-valued choquet integral on interval-valued risks.

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Interval-valued Choquet integrals and applications in pricing risks (구간치 쇼케이적분과 위험률 가격 측정에서의 응용)

  • Jang, Lee-Chae
    • Journal of the Korean Institute of Intelligent Systems
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    • v.17 no.4
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    • pp.451-454
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    • 2007
  • Non-additive measures and their corresponding Choquet integrals are very useful tools which are used in both insurance and financial markets. In both markets, it is important to update prices to account for additional information. The update price is represented by the Choquet integral with respect to the conditioned non-additive measure. In this paper, we consider a price functional H on interval-valued risks defined by interval-valued Choquet integral with respect to a non-additive measure. In particular, we prove that if an interval-valued pricing functional H satisfies the properties of monotonicity, comonotonic additivity, and continuity, then there exists an two non-additive measures ${\mu}1,\;{\mu}2$ such that it is represented by interval-valued choquet integral on interval-valued risks.

Non-Additive Ranking of Release Scenarios in a Low and Intermediate Waste Repository

  • Kim, Seong-Ho;Kim, Tae-Woon;Jaejoo Ha
    • Proceedings of the Korean Radioactive Waste Society Conference
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    • 2004.06a
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    • pp.188-188
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    • 2004
  • In the present study, a multicriteria decision-making (MCDM) problem of ranking of important radionuclide release scenarios in a low and intermediate radioactive waste repository is to treat on the basis of non-additive fuzzy measures and fuzzy integral theory. Ranking of important scenarios can lead to the provision of more effective safety measure in a design stage of the repository. The ranking is determined by a relative degree of appropriateness of scenario alternatives.(omitted)

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A study on interval-valued necessity measures through the Choquet integral criterian (쇼케이 적분 기준을 통한 구간치 필요측도에 관한 연구)

  • Jang, Lee-Chae;Kim, Tae-Kyun
    • Journal of the Korean Institute of Intelligent Systems
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    • v.19 no.3
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    • pp.350-354
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    • 2009
  • Y. R$\acute{e}$ball$\acute{e}$[Fuzzy Sets and Systems, vol.157, pp.3025-2039, 2006] discussed the representation of necessity measure through the Choquet integral criterian. He also considered a decision maker who ranks necessity measures related with Choquet integral representation. Our motivation of this paper is that a decision maker have an "ambiguity" necessity measure to present preferences. In this paper, we discuss the representation of interval-valued necessity measures through the Choquet integral criterian.

Choquet integrals and interval-valued necessity measures (쇼케이 적분과 구간치 필요측도)

  • Jang, Lee-Chae;Kim, Tae-Kyun
    • Journal of the Korean Institute of Intelligent Systems
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    • v.19 no.4
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    • pp.499-503
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    • 2009
  • Y. R$\acute{e}$ball$\acute{e}$ [11] discussed the representation of necessity measure through the Choquet integral criterian. He also consider a decision maker who ranks necessity measures related with Choquet integral representation. In this paper, we consider a decision maker have an "ambiguity"(say, interval-valued) necessity measure according to their Choquet's expected utility. Furthermore, we prove two theorems which are weak Choquet integral representation of preferences with a monotone set function for interval-valued necessity measures and strong Choquet integral representation of preferences with an interval-valued utility function for necessity measures.

Wavelet Based Non-Local Means Filtering for Speckle Noise Reduction of SAR Images (SAR 영상에서 웨이블렛 기반 Non-Local Means 필터를 이용한 스펙클 잡음 제거)

  • Lee, Dea-Gun;Park, Min-Jea;Kim, Jeong-Uk;Kim, Do-Yun;Kim, Dong-Wook;Lim, Dong-Hoon
    • The Korean Journal of Applied Statistics
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    • v.23 no.3
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    • pp.595-607
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    • 2010
  • This paper addresses the problem of reducing the speckle noise in SAR images by wavelet transformation, using a non-local means(NLM) filter originated for Gaussian noise removal. Log-transformed SAR image makes multiplicative speckle noise additive. Thus, non-local means filtering and wavelet thresholding are used to reduce the additive noise, followed by an exponential transformation. NLM filter is an image denoising method that replaces each pixel by a weighted average of all the similarly pixels in the image. But the NLM filter takes an acceptable amount of time to perform the process for all possible pairs of pixels. This paper, also proposes an alternative strategy that uses the t-test more efficiently to eliminate pixel pairs that are dissimilar. Extensive simulations showed that the proposed filter outperforms many existing filters terms of quantitative measures such as PSNR and DSSIM as well as qualitative judgments of image quality and the computational time required to restore images.

Healthcare Systems and COVID-19 Mortality in Selected OECD Countries: A Panel Quantile Regression Analysis

  • Jalil Safaei;Andisheh Saliminezhad
    • Journal of Preventive Medicine and Public Health
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    • v.56 no.6
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    • pp.515-522
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    • 2023
  • Objectives: The pandemic caused by coronavirus disease 2019 (COVID-19) has exerted an unprecedented impact on the health of populations worldwide. However, the adverse health consequences of the pandemic in terms of infection and mortality rates have varied across countries. In this study, we investigate whether COVID-19 mortality rates across a group of developed nations are associated with characteristics of their healthcare systems, beyond the differential policy responses in those countries. Methods: To achieve the study objective, we distinguished healthcare systems based on the extent of healthcare decommodification. Using available daily data from 2020, 2021, and 2022, we applied quantile regression with non-additive fixed effects to estimate mortality rates across quantiles. Our analysis began prior to vaccine development (in 2020) and continued after the vaccines were introduced (throughout 2021 and part of 2022). Results: The findings indicate that higher testing rates, coupled with more stringent containment and public health measures, had a significant negative impact on the death rate in both pre-vaccination and post-vaccination models. The data from the post-vaccination model demonstrate that higher vaccination rates were associated with significant decreases in fatalities. Additionally, our research indicates that countries with healthcare systems characterized by high and medium levels of decommodification experienced lower mortality rates than those with healthcare systems involving low decommodification. Conclusions: The results of this study indicate that stronger public health infrastructure and more inclusive social protections have mitigated the severity of the pandemic's adverse health impacts, more so than emergency containment measures and social restrictions.

Extended Temporal Ordinal Measurement Using Spatially Normalized Mean for Video Copy Detection

  • Lee, Heung-Kyu;Kim, June
    • ETRI Journal
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    • v.32 no.3
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    • pp.490-492
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    • 2010
  • This letter proposes a robust feature extraction method using a spatially normalized mean for temporal ordinal measurement. Before computing a rank matrix from the mean values of non-overlapped blocks, each block mean is normalized so that it obeys the invariance property against linear additive and subtractive noise effects and is insensitive against multiplied and divided noise effects. Then, the temporal ordinal measures of spatially normalized mean values are computed for the feature matching. The performance of the proposed method showed about 95% accuracy in both precision and recall rates on various distortion environments, which represents the 2.7% higher performance on average compared to the temporal ordinal measurement.