Results 211 to 220 of about 217,536 (268)

Blue-green spaces, heat stress, and health-supportive public-space use under urban stress: machine learning and SEM evidence from jogging flow in Fuzhou, China. [PDF]

Front Public Health
Zhang F, Bahn GS, Peng H, Jiang T, Sun J.   +4 more
europepmc   +1 more source

Research on interpretable machine learning modeling and spatial prediction of cross-landform landslide disaster mechanism: A case study of Shaanxi Province. [PDF]

PLoS One
Han M, Yang Y.
europepmc   +1 more source

Different modality-specific mechanisms mediate serial dependence effects in visual and auditory perception. [PDF]

BMC Biol
Togoli I, Fornaciai M, Bueti D.
europepmc   +1 more source

Geographically weighted negative binomial regression for spatial count data: Methodology and application. [PDF]

MethodsX
Saifudin T, Chamidah N, Azizah N, Renianti FS, Carista N, Adyatma IY, Tianda IM.   +6 more
europepmc   +1 more source

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Spatial dependence of dispersion

Magnetic Resonance Imaging, 2003
The use of Pulsed Gradient Spin Echo (PGSE) NMR to investigate flow in porous media is well established. Using two pairs of position-encoding pulses in the PGSE experiment gives the possibility of examining velocity fluctuations, by comparing displacements, during the two encoding intervals.
Alexandre A, Khrapitchev, P T, Callaghan
openaire   +2 more sources

Propagation of HBV with spatial dependence

Mathematical Biosciences, 2007
A mathematical model is proposed to simulate the hepatitis B virus (HBV) infection with spatial dependence. The existence of traveling waves is established via the geometric singular perturbation method. Numerical simulations show that the model admits non-monotone traveling profiles.
Wang, Kaifa, Wang, Wendi
openaire   +3 more sources

Spatial variability clustering for spatially dependent functional data

Statistics and Computing, 2016
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
ROMANO, Elvira, BALZANELLA, Antonio, VERDE, Rosanna   +2 more
openaire   +1 more source

Exploring Dependence with Data on Spatial Lattices

Biometrics, 2009
SummaryThe application of Markov random field models to problems involving spatial data on lattice systems requires decisions regarding a number of important aspects of model structure. Existing exploratory techniques appropriate for spatial data do not provide direct guidance to an investigator about these decisions.
Kaiser, Mark, Caragea, Petruta
openaire   +4 more sources