Search results for " modeling"
showing 10 items of 2411 documents
Field run-up measurements: Calibration of a physically based lagrangian shoreline model
2012
In the present contribution a measurement technique based on video imaging has been selected for the assessment of the maximum run-up. Such measurements have been used for the calibration of a numerical model and of an empirical formulation. The on-site run-up measurements have been carried out at “Lido Signorino” beach, near Marsala, Italy. The positions of the swash have been localized on a transect, normal to the shore, constituted by stakes placed at 0.5 m intervals each other. The video camera was placed orthogonally to the line of the stakes. For the numerical simulations a 1DH Boussinesq-type of model for breaking waves has been applied which takes into account the wave run-up by a L…
Dynamic Regret Analysis for Online Tracking of Time-varying Structural Equation Model Topologies
2020
Identifying dependencies among variables in a complex system is an important problem in network science. Structural equation models (SEM) have been used widely in many fields for topology inference, because they are tractable and incorporate exogenous influences in the model. Topology identification based on static SEM is useful in stationary environments; however, in many applications a time-varying underlying topology is sought. This paper presents an online algorithm to track sparse time-varying topologies in dynamic environments and most importantly, performs a detailed analysis on the performance guarantees. The tracking capability is characterized in terms of a bound on the dynamic re…
Active Learning Methods for Efficient Hybrid Biophysical Variable Retrieval
2016
Kernel-based machine learning regression algorithms (MLRAs) are potentially powerful methods for being implemented into operational biophysical variable retrieval schemes. However, they face difficulties in coping with large training data sets. With the increasing amount of optical remote sensing data made available for analysis and the possibility of using a large amount of simulated data from radiative transfer models (RTMs) to train kernel MLRAs, efficient data reduction techniques will need to be implemented. Active learning (AL) methods enable to select the most informative samples in a data set. This letter introduces six AL methods for achieving optimized biophysical variable estimat…
Toward a Collective Agenda on AI for Earth Science Data Analysis
2021
In the last years we have witnessed the fields of geosciences and remote sensing and artificial intelligence to become closer. Thanks to both the massive availability of observational data, improved simulations, and algorithmic advances, these disciplines have found common objectives and challenges to advance the modeling and understanding of the Earth system. Despite such great opportunities, we also observed a worrying tendency to remain in disciplinary comfort zones applying recent advances from artificial intelligence on well resolved remote sensing problems. Here we take a position on research directions where we think the interface between these fields will have the most impact and be…
Signal reconstruction, modeling and simulation of a vehicle full-scale crash test based on Morlet wavelets
2012
Creating a mathematical model of a vehicle crash is a task which involves considerations and analysis of different areas which need to be addressed because of the mathematical complexity of a crash event representation. Therefore, to simplify the analysis and enhance the modeling process, in this paper a novel wavelet-based approach is introduced to reproduce acceleration pulse of a vehicle involved in a crash event. The acceleration of a colliding vehicle is measured in its center of gravity-this crash pulse contains detailed information about vehicle behavior throughout a collision. Three types of signal analysis are elaborated here: time domain analysis (i.e. description of kinematics of…
Applicability of LES turbulence modeling for CZ silicon crystal growth systems with traveling magnetic field
2010
Abstract To examine the applicability of LES turbulence modeling for CZ silicon crystal growth systems with traveling magnetic fields, LES calculations with Smagorinsky–Lilly turbulence model and van Driest damping at the solid walls are carried out. The program package for the calculations was developed on the basis of the open-source code library OpenFOAM ® . A previously published laboratory model with low temperature melt InGaSn, a 20” crucible, and process parameters corresponding to industrial Czochralski silicon systems is considered. Flow regimes with two crystal and crucible rotation rates and with different strengths of the traveling magnetic field “down” are analyzed. The calcula…
Electrochemical analysis of the first Polish coins using voltammetry of immobilized particles
2017
[EN] A series of 20 denarii from Boleslaus the Brave (992-1025) and Mieszko II Lambert (1025-1034), corresponding to the beginning of the Polish state were studied using the voltammetry of immobilized particles (VIMP) methodology. VIMP experiments, applied to nanosamples of the corrosion layers of the coins in contact with aqueous acetate buffer, provided well-defined responses mainly corresponding to the corrosion products of copper and lead. Such voltammetric responses, combined with X-ray fluorescence (XRF) spectroscopy experiments performed on the same set of coins, and complemented by focusing ion beam-field emission scanning electron microscope (FIB-FESEM) on silver coins from the 19t…
Views selection for SIFT based object modeling and recognition
2016
In this paper we focus on automatically learning object models in the framework of keypoint based object recognition. The proposed method uses a collection of views of the objects to build the model. For each object the collection is composed of N×M views obtained rotating the object around its vertical and horizontal axis. As keypoint based object recognition using a complete set of views is computationally expensive, we focused on the definition of a selection method that creates, for each object, a subset of the initial views that visually summarize the characteristics of the object and should be suited for recognition. We select the views by determining maxima and minima of a function, …
Performance Prevision of a Turbocharged Natural Gas Fuelled S.I. Engine
2008
Natural gas represents today maybe the most valid alternative to conventional fuels for road vehicles propulsion. The main constituent of natural gas, methane, is characterized by a high autoignition temperature, which makes the fuel highly resistant to knocking: this allows a considerable downsizing of the engine by means of supercharging even under high compression ratio. Starting from these considerations, the authors realized a thermodynamic model of a 4-cilynder s.i. engine for the prevision of in-cylinder pressure, employing a two-zone approach for the combustion and adding sub-models to account for gas properties change and knocking occurrence. An extensive experimental campaign has …
3D objects descriptors methods: Overview and trends
2017
International audience; Object recognition or object's category recognition under varying conditions is one of the most astonishing capabilities of human visual system. The scientists in computer vision have been trying for decades to reproduce this ability by implementing algorithms and providing computers with appropriate tools. Hence, several intelligent systems have been proposed. To act in this field, numerous approaches have been proposed. In this paper we present an overview of the current trend in 3D objects recognition and describe some representative state of the art methods, highlighting their limits and complexity.