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International Journal for Uncertainty Quantification

Published 6 issues per year

ISSN Print: 2152-5080

ISSN Online: 2152-5099

The Impact Factor measures the average number of citations received in a particular year by papers published in the journal during the two preceding years. 2017 Journal Citation Reports (Clarivate Analytics, 2018) IF: 1.7 To calculate the five year Impact Factor, citations are counted in 2017 to the previous five years and divided by the source items published in the previous five years. 2017 Journal Citation Reports (Clarivate Analytics, 2018) 5-Year IF: 1.9 The Immediacy Index is the average number of times an article is cited in the year it is published. The journal Immediacy Index indicates how quickly articles in a journal are cited. Immediacy Index: 0.5 The Eigenfactor score, developed by Jevin West and Carl Bergstrom at the University of Washington, is a rating of the total importance of a scientific journal. Journals are rated according to the number of incoming citations, with citations from highly ranked journals weighted to make a larger contribution to the eigenfactor than those from poorly ranked journals. Eigenfactor: 0.0007 The Journal Citation Indicator (JCI) is a single measurement of the field-normalized citation impact of journals in the Web of Science Core Collection across disciplines. The key words here are that the metric is normalized and cross-disciplinary. JCI: 0.5 SJR: 0.584 SNIP: 0.676 CiteScore™:: 3 H-Index: 25

Indexed in

SURROGATE MODELING OF INDOOR DOWN-LINK HUMAN EXPOSURE BASED ON SPARSE POLYNOMIAL CHAOS EXPANSION

Volume 10, Issue 2, 2020, pp. 145-163
DOI: 10.1615/Int.J.UncertaintyQuantification.2020031452
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ABSTRACT

Human exposure induced by wireless communication systems increasingly draws the public attention. Here, an indoor down-link scenario is concerned and the exposure level is statistically analyzed. The electromagnetic field emitted by a WiFi box is measured and electromagnetic dosimetry features are evaluated from the whole-body specific absorption rate as computed with a finite-difference time-domain (a.k.a. FDTD) code. Due to computational cost, a statistical analysis is performed based on a surrogate model, which is constructed by means of so-called sparse polynomial chaos expansion, where the inner cross validation (ICV) is used to select the optimal hyperparameters during the model construction and assess the model performance. However, the model assessment based on ICV tends to be overly optimistic with small data sets. The method of cross-model validation is used and outer cross validation is carried out for the model assessment. The effects of the data preprocessing are investigated as well. On the basis of the surrogate model, the global sensitivity of the exposure to input parameters is analyzed from Sobol' indices.

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CITED BY
  1. Belen Aysu, Günes Filiz, Palandoken Merih, Tari Ozlem, Belen Mehmet A., Mahouti Peyman, 3D EM data driven surrogate based design optimization of traveling wave antennas for beam scanning in X-band: an application example, Wireless Networks, 28, 4, 2022. Crossref

  2. Lüthen Nora, Marelli Stefano, Sudret Bruno, Sparse Polynomial Chaos Expansions: Literature Survey and Benchmark, SIAM/ASA Journal on Uncertainty Quantification, 9, 2, 2021. Crossref

  3. Masumnia-Bisheh Khadijeh, Furse Cynthia, Variability in Specific Absorption Rate From Variation in Tissue Properties, IEEE Journal on Multiscale and Multiphysics Computational Techniques, 7, 2022. Crossref

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