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Yong-Dao Zhou

Bio: Yong-Dao Zhou is an academic researcher from Nankai University. The author has contributed to research in topics: Fractional factorial design & Optimal design. The author has an hindex of 12, co-authored 41 publications receiving 392 citations. Previous affiliations of Yong-Dao Zhou include United International College & Sichuan University.

Papers
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TL;DR: A new discrepancy, called the mixture discrepancy (MD), is proposed, which is more reasonable than CD and WD for measuring the uniformity from different aspects such as the intuitive view, the Uniformity of subdimension projection, the curse of dimensionality and the geometric property of the kernel function.

80 citations

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TL;DR: In this article, the authors studied the space-filling properties of fractional factorial designs under two commonly used space filling measures, discrepancy and maximin distance, and derived several novel relationships between distance distribution and generalized word length pattern.
Abstract: Fractional factorial designs are widely used in various scientific investigations and industrial applications. Level permutation of factors could alter their geometrical structures and statistical properties. This article studies space-filling properties of fractional factorial designs under two commonly used space-filling measures, discrepancy and maximin distance. When all possible level permutations are considered, the average discrepancy is expressed as a linear combination of generalized word length pattern for fractional factorial designs with any number of levels and any discrepancy defined by a reproducing kernel. Generalized minimum aberration designs are shown to have good space-filling properties on average in terms of both discrepancy and distance. Several novel relationships between distance distribution and generalized word length pattern are derived. It is also shown that level permutations can improve space-filling properties for many existing saturated designs. A two-step construction pro...

57 citations

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TL;DR: In this article, a new discrepancy based on the Lee distance, Lee discrepancy, is proposed and its computational formula is given, which can expand the relationships between the discrete discrepancy and some criteria for factorial designs with multiple levels.

51 citations

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TL;DR: It is shown that linear level permutation does not decrease the minimum distance for good lattice point sets, and several classes of such sets with large minimum distance are identified.
Abstract: We study space-filling properties of good lattice point sets and obtain some general theoretical results. We show that linear level permutation does not decrease the minimum distance for good lattice point sets, and we identify several classes of such sets with large minimum distance. Based on good lattice point sets, some maximin distance designs are also constructed.

38 citations


Cited by
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Journal ArticleDOI
TL;DR: Most patients presented with a mild infection in this retrospective cohort study, but the imaging pattern of multifocal peripheral ground glass or mixed opacity with predominance in the lower lung is highly suspicious of COVID-19 in the first week of disease onset.

768 citations

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TL;DR: Graphical methods for evaluating design performance for several important response surface problems are discussed and it is shown how these techniques can be used to compare competing designs.

185 citations

Journal Article
TL;DR: In this article, small composite designs for fitting second-order response surfaces have been proposed, where the number of runs is reduced as much as possible while maintaining the ability to estimate all of the terms in the model.
Abstract: Standard composite designs for fitting second-order response surfaces typically have a fairly large number of points, especially when k is large. In some circumstances, it is desirable to reduce the number of runs as much as possible while maintaining the ability to estimate all of the terms in the model. We first review prior work on small composite designs and then suggest some alternatives for k ≤ 10 factors. In some cases, even minimal-point designs are possible.

135 citations

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TL;DR: The impact of connecting building characteristics and designs with its performance by data mining techniques, hence the appropriateness of a room in relation to energy efficiency is investigated, to further assist building energy management decision-making.

86 citations

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TL;DR: The scenarios evaluated here through data-driven simulations indicate that measures aimed at reducing individuals’ flow are much less effective than others intended for early case identification and isolation, and resources should be directed towards detecting as many and as fast as possible the new cases and isolate them.
Abstract: We are currently experiencing an unprecedented challenge, managing and containing an outbreak of a new coronavirus disease known as COVID-19. While China—where the outbreak started—seems to have been able to contain the growth of the epidemic, different outbreaks are nowadays present in multiple countries. Nonetheless, authorities have taken action and implemented containment measures, even if not everything is known. To facilitate this task, we have studied the effect of different containment strategies that can be put into effect. Our work referred initially to the situation in Spain as of February 28, 2020, where a few dozens of cases had been detected, but has been updated to match the current situation as of 13 April. We implemented an SEIR metapopulation model that allows tracing explicitly the spatial spread of the disease through data-driven stochastic simulations. Our results are in line with the most recent recommendations from the World Health Organization, namely, that the best strategy is the early detection and isolation of individuals with symptoms, followed by interventions and public recommendations aimed at reducing the transmissibility of the disease, which, although might not be sufficient for disease eradication, would produce as a second order effect a delay of several days in the raise of the number of infected cases. Many quantitative aspects of the natural history of the disease are still unknown, such as the amount of possible asymptomatic spreading or the role of age in both the susceptibility and mortality of the disease. However, preparedness plans and mitigation interventions should be ready for quick and efficacious deployment globally. The scenarios evaluated here through data-driven simulations indicate that measures aimed at reducing individuals’ flow are much less effective than others intended for early case identification and isolation. Therefore, resources should be directed towards detecting as many and as fast as possible the new cases and isolate them.

79 citations