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September 25, 2023 to September 29, 2023 - Porto, Portugal

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TrendNews 2023 Congress
September 25, 2023 to September 29, 2023 - Porto, Portugal

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November 13, 2023 to November 17, 2023 - Valencia, Spain

SoftNet 2023 Congress
November 13, 2023 to November 17, 2023 - Valencia, Spain

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IARIA Congress 2023, The 2023 IARIA Annual Congress on Frontiers in Science, Technology, Services, and Applications
November 13, 2023 to November 17, 2023 - Valencia, Spain

 

 


ThinkMind // BIOTECHNO 2022, The Fourteenth International Conference on Bioinformatics, Biocomputational Systems and Biotechnologies // View article biotechno_2022_1_40_70018


Heuristic Random Designs for Exact Identification of Positives Using Single Round Non-adaptive Group Testing and Compressed Sensing

Authors:
Catherine Haddad-Zaknoon

Keywords: Group Testing, Pooling Design, Compressive Sensing, COVID19-PCR

Abstract:
Among the challenges that the COVID-19 pandemic outbreak revealed is the problem of reducing the number of tests required for identifying the virus carriers. To cope with this issue, a prevalence testing paradigm based on Group Testing and Compressive Sensing approach or emph{GTCS} was examined. In these settings, a non-adaptive group testing algorithm is designed to rule out sure-negative samples. Then, a compressive sensing algorithm is applied to decode the positives without requiring any further testing. The result is a single-round non-adaptive group testing - compressive sensing algorithm to identify the positive samples. In this paper, we propose a heuristic random method to construct the test design called emph{$alpha-$random row design} or $alpha-$RRD. In the $alpha-$RRD, a random test matrix is constructed such that each test aggregates at most $alpha$ samples in one group test or pool. The pooled tests are heuristically selected one by one such that samples that were previously selected in the same test are less likely to be aggregated together in a new test. We examined the performance of the $alpha-$RRD design within the GTCS paradigm for several values of $alpha$. The experiments were conducted on synthetic data and sensitivity to noise was checked. Our results show that, for some values of $alpha$, a reduction of up to 10 fold in the tests number can be achieved when $alpha-$RRD design is applied in the GTCS paradigm.

Pages: 10 to 16

Copyright: Copyright (c) IARIA, 2022

Publication date: May 22, 2022

Published in: conference

ISSN: 2308-4383

ISBN: 978-1-61208-971-3

Location: Venice, Italy

Dates: from May 22, 2022 to May 26, 2022

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