Search results for " Time"

Original Supercritical Water Device for Continuous Production of Nanopowders

2011

Well-crystallized ZnO, ZrO2, TiO2, CeO2, Y2O3 and La2O3 nanoparticles are synthesized under supercritical water conditions (T > 647 K and P > 22.1 MPa) using a home-made continuous process. At room temperature, metallic salts with or without aqueous hydroxide solution (KOH or NaOH) are pressurized to 25–30 MPa. Then, the reactant(s) is/are rapidly heated to 673–773 K by mixing with the supercritical water in a patented reactor. Residence time is in the range from 2 to 8 s. XRD, TEM and surface area analyses highlight the production of pure and well-crystallized nanoparticles with a uniform size distribution.

Integrated geophysical survey in the archaeological site of Himera (Northern Sicily)

2005

Millennial-scale phase relationships between ice-core and Mediterranean marine records: insights from high-precision 40Ar/39Ar dating of the Green Tu…

2013

International audience; With the advent of annually-resolved polar ice records extending back to 70 ka, marine and continental paleoclimate studies have now matured into a discipline where high-quality age control is essential for putting on an equal pace layer-counted timescale models and Late Quaternary sedimentary records. High-resolution U-Th dating of speleothem records and 40Ar/39Ar dating of globally recorded geomagnetic excursions have recently improved the time calibration of Quaternary archives, reflecting the cross-disciplinary effort made to synchronize the geologic record at the millennial scale. Yet, tie-points with such an absolute age control remain scarce for paleoclimatic …

PATRIMONIO ARCHITETTONICO E TIMELESS TIME : PER UNA PERMANENZA TEMPORANEA

2018

Com’è avvenuto per le precedenti rivoluzioni industriali, la digitalizzazione non ha sortito effetti soltanto nei processi e nei prodotti tecnologici. Tra le sue dirompenti conseguenze sulla società e sugli individui, l’emergere di una diversa concezione del Tempo sta già condizionando il campo operativo e soprattutto teoretico dell’ambiente costruito connotato da significati culturali. Inusitate forme di memoria mettono in crisi la visione tradizionale di patrimonio, fondata su una visione lineare del tempo che separa nettamente il Passato dal Futuro, lasciando al Presente un mero ruolo da passatore. Superata la presunta immutabilità, ambizione di ormai obsoleti obiettivi conservativi rigi…

Modeling Chickenpox Dynamics with a Discrete Time Bayesian Stochastic Compartmental Model

2018

[EN] We present a Bayesian stochastic susceptible-exposed-infectious-recovered model in discrete time to understand chickenpox transmission in the Valencian Community, Spain. During the last decades, different strategies have been introduced in the routine immunization program in order to reduce the impact of this disease, which remains a public health's great concern. Under this scenario, a model capable of explaining closely the dynamics of chickenpox under the different vaccination strategies is of utter importance to assess their effectiveness. The proposed model takes into account both heterogeneous mixing of individuals in the population and the inherent stochasticity in the transmiss…

Exploiting deep learning algorithms and satellite image time series for deforestation prediction

2022

In recent years, we have witnessed the emergence of Deep Learning (DL) methods, which have led to enormous progress in various fields such as automotive driving, computer vision, medicine, finances, and remote sensing data analysis. The success of these machine learning methods is due to the ever-increasing availability of large amounts of information and the computational power of computers. In the field of remote sensing, we now have considerable volumes of satellite images thanks to the large number of Earth Observation (EO) satellites orbiting the planet. With the revisit time of satellites over an area becoming shorter and shorter, it will probably soon be possible to obtain daily imag…

A neural network-based approach to determine FDTD eigenfunctions in quantum devices

2009

This article combines a Neural Network (NN) algorithm with the Finite Difference Time Domain (FDTD) technique to estimate the eigenfunctions in quantum devices. A NN based on the Least Mean Squares (LMS) algorithm is combined with the FDTD technique to provide a first approach to the confined states in quantum wires. The proposed technique is in good agreement with analytical results and is more efficient than FDTD combined with the Fourier Transform. This technique is used to cal- culate a numerical approximation to the eigenfunctions associated to quan- tum wire potentials. The performance and convergence of the proposed technique are also presented in this article. © 2009 Wiley Periodica…

Speech Emotion Recognition method using time-stretching in the Preprocessing Phase and Artificial Neural Network Classifiers

2020

Human emotions are playing a significant role in the understanding of human behaviour. There are multiple ways of recognizing human emotions, and one of them is through human speech. This paper aims to present an approach for designing a Speech Emotion Recognition (SER) system for an industrial training station. While assembling a product, the end user emotions can be monitored and used as a parameter for adapting the training station. The proposed method is using a phase vocoder for time-stretching and an Artificial Neural Network (ANN) for classification of five typical different emotions. As input for the ANN classifier, features like Mel Frequency Cepstral Coefficients (MFCCs), short-te…

Neural network prediction in a system for optimizing simulations

2002

Neural networks have been widely used for both prediction and classification. Back-propagation is commonly used for training neural networks, although the limitations associated with this technique are well documented. Global search techniques such as simulated annealing, genetic algorithms and tabu search have also been used for this purpose. The developers of these training methods, however, have focused on accuracy rather than training speed in order to assess the merit of new proposals. While speed is not important in settings where training can be done off-line, the situation changes when the neural network must be trained and used on-line. This is the situation when a neural network i…

Estimation of Granger causality through Artificial Neural Networks: applications to physiological systems and chaotic electronic oscillators

2021

One of the most challenging problems in the study of complex dynamical systems is to find the statistical interdependencies among the system components. Granger causality (GC) represents one of the most employed approaches, based on modeling the system dynamics with a linear vector autoregressive (VAR) model and on evaluating the information flow between two processes in terms of prediction error variances. In its most advanced setting, GC analysis is performed through a state-space (SS) representation of the VAR model that allows to compute both conditional and unconditional forms of GC by solving only one regression problem. While this problem is typically solved through Ordinary Least Sq…