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We propose an approach to spatial modeling of extreme rainfall, based on max-stable processes fitted using partial duration series and a censored threshold likelihood function. The resulting models are coherent with classical extreme-value theory and allow ...
radiance scene files and metric results generated from high quality referece images for an office building near LAX. contents of lci_tempate.tar.gz: ALLSKIES: 4294 sky conditions generated by write_skydefs.py based on LAX.epw, all ...
The problem of autonomously mapping highly cluttered environments, such as urban and natural canyons, is intractable with the current UAV technology. The reason lies in the absence or unreliability of GNSS signals due to partial sky occlusion or multi-path ...
A thermomechanical model is presented for predicting the time-dependent deflections of cellular FRP slab elements subjected to mechanical loading and fire from one side. The model comprises temperature-dependent mechanical property sub-models for the Young ...
We have measured the rovibrational levels in the electronic ground state of the water molecule at the previously inaccessible energies above 26000 cm-1. The use of laser double-resonance overtone excitation combined with laser-induced fluorescence (LIF) ph ...
Water vapor is a fundamental constituent of the atmosphere and is the most abundant green house gas thus having an important influence on climate. It is as well a key prognostic variable for numerical weather prediction models (NWP). Currently, the vertica ...
The paper focuses on the energy management of a single-phase PV-BESS hybrid distributed system sized for residential applications, using a CHB converter topology as grid interface. The CHB is driven with a hierarchical energy management architecture, with ...
The development of oceanography and meteorology has greatly benefited from satellite-based data of Earth's atmosphere and ocean. Traditional Earth observation missions have utilised Sun-synchronous orbits with repeat ground tracks due to their advantages i ...
In this work we consider the problem of learning an Erdos-Renyi graph over a diffusion network when: i) data from only a limited subset of nodes are available (partial observation); ii) and the inferential goal is to discover the graph of interconnections ...
We present an algorithm using principal component analysis (PCA) to subtract galaxies from imaging data and also two algorithms to find strong, galaxy-scale gravitational lenses in the resulting residual image. The combined method is optimised to find full ...