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Advanced Engineering Materials, EarlyView.This article presents the design, modeling, and characterization of air‐pressure–actuated programmable vibroacoustic metamaterials (PVAMM). The study focuses on leveraging air pressure to dynamically tune resonance frequencies for effective noise attenuation.
William Kaal +2 more
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Effects of Histamine H<sub>3</sub> Receptor Antagonist/Inverse Agonist Pitolisant on Temporal Prediction, Spatial Switching, and Spontaneous Locomotion in Mice. [PDF]
Neuropsychopharmacol RepKaneko S, Hayashi K, Yamada K, Toda K.
europepmc +1 more source
Spatiotemporal modeling of regional short-term pertussis transmission risk using a propagation-enhanced prediction framework. [PDF]
Front Public HealthZhang S +5 more
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Early Apple Yield Prediction Based on Flowering Stage Image Thinning Simulation Characteristics. [PDF]
Plants (Basel)Yang Q, Liu L.
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A Survey on Spatial Prediction Methods
IEEE Transactions on Knowledge and Data Engineering, 2019With the advancement of GPS and remote sensing technologies, large amounts of geospatial data are being collected from various domains, driving the need for effective and efficient prediction methods. Given spatial data samples with explanatory features and targeted responses (categorical or continuous) at a set of locations, the spatial prediction ...
Zhe Jiang
exaly +2 more sources
Spatial prediction of counts and rates
Statistics in Medicine, 2003AbstractIn this paper we provide both theoretical and empirical comparisons of marginal and conditional methods for analysing spatial count data. We focus on methods for spatial prediction developed from a generalized linear mixed model framework and compare them with the traditional linear (kriging) predictor.
Carol A, Gotway, Russell D, Wolfinger
exaly +3 more sources
Technometrics, 2011
Under a general loss function, we develop a hypothesis test to determine whether a significant difference in the spatial predictions produced by two competing models exists on average across the entire spatial domain of interest. The null hypothesis is that of no difference, and a spatial loss differential is created based on the observed data, the two
Amanda S. Hering, Marc G. Genton
openaire +2 more sources
Under a general loss function, we develop a hypothesis test to determine whether a significant difference in the spatial predictions produced by two competing models exists on average across the entire spatial domain of interest. The null hypothesis is that of no difference, and a spatial loss differential is created based on the observed data, the two
Amanda S. Hering, Marc G. Genton
openaire +2 more sources
Nonparametric Spatial Prediction
Statistical Inference for Stochastic Processes, 2004zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Biau, Gérard, Cadre, Benoît
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2015 16th IEEE International Conference on Mobile Data Management, 2015
In this seminar, we address spatial predictive queries both in Euclidian spaces and over road networks. We provide a definition for various types of spatial predictive queries, describe current research trends, and envision future directions. We present practical application scenarios and emphasize the roadblocks that are holding industry back from the
Abdeltawab M. Hendawi, Mohamed H. Ali
openaire +1 more source
In this seminar, we address spatial predictive queries both in Euclidian spaces and over road networks. We provide a definition for various types of spatial predictive queries, describe current research trends, and envision future directions. We present practical application scenarios and emphasize the roadblocks that are holding industry back from the
Abdeltawab M. Hendawi, Mohamed H. Ali
openaire +1 more source