Results 11 to 20 of about 707,184 (259)
On Certified Randomness from Fourier Sampling or Random Circuit Sampling [PDF]
QuantumCertified randomness has a long history in quantum information, with many potential applications. Recently Aaronson and Hung proposed a novel public certified randomness protocol based on existing random circuit sampling (RCS) experiments. The security of their protocol, however, relies on non-standard complexity-theoretic conjectures which were not ...
Roozbeh Bassirian +4 more
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Alternative Estimators for Stratified Random Sampling [PDF]
The Egyptian Statistical Journal, 1991 In this paper, two methods of estimation using estimators for stratified random sample are suggested. Two estimators are suggested for a positively correlated auxiliary variable and the other two are suggested for a negatively correlated auxiliary ...
Mounira Hussein
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Inclusive random sampling in graphs and networks
Applied Network Science, 2023 It is often of interest to sample vertices from a graph with a bias towards higher-degree vertices. One well-known method, which we call random neighbor or RN, involves taking a vertex at random and exchanging it for one of its neighbors.
Yitzchak Novick, Amotz Bar-Noy
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Field sampling methods for investigating forest-floor bryophytes: Microcoenose vs. random sampling [PDF]
Archives of Biological Sciences, 2018 Because of the high importance of bryophytes in forest ecosystems, it is necessary to develop standardized field sampling methodologies. The quadrat method is commonly used for bryophyte diversity and distribution pattern surveys.
Ilić Miloš +3 more
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Animals, 2021 Within paratuberculosis control programs Mycobacterium avium subsp. paratuberculosis (MAP)-infected herds have to be detected with minimum effort but with sufficient reliability.
Annika Wichert +4 more
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Biased Boltzmann samplers and generation of extended linear languages with shuffle [PDF]
Discrete Mathematics & Theoretical Computer Science, 2012 This paper is devoted to the construction of Boltzmann samplers according to various distributions, and uses stochastic bias on the parameter of a Boltzmann sampler, to produce a sampler with a different distribution for the size of the output.
Alexis Darrasse +3 more
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Statistical Analysis in the Presence of Spatial Autocorrelation: Selected Sampling Strategy Effects
Stats, 2022 Fundamental to most classical data collection sampling theory development is the random drawings assumption requiring that each targeted population member has a known sample selection (i.e., inclusion) probability.
Daniel A. Griffith, Richard E. Plant
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Quantifying errors without random sampling
BMC Medical Research Methodology, 2003 Background All quantifications of mortality, morbidity, and other health measures involve numerous sources of error. The routine quantification of random sampling error makes it easy to forget that other sources of error can and should be quantified ...
LaPole Luwanna M, Phillips Carl V
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Sampling of Random Data Streams
Advances in Electrical and Electronic Engineering, 2011 Modern telecommunication networks work on the transmission method of common data streams in which data bursts consisting of packets that further consist of particular bits are multiplexed from various traffic sources.
Gustav Cepciansky, Ladislav Schwartz
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Determination of Sample Size and Observation Units
International Journal of Assessment Tools in Education, 2019 The purpose of this study was to write programsto define sampling sizes and observation units by probability sampling methodsand to provide an idea for software developers. Thealgorithms of the programs were written in Python 3.
Tülin Acar
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