Search results for "propagation"
showing 10 items of 676 documents
Propagation of Calendula maritima Guss. (Asteraceae) through Biotechnological Techniques for Possible Usage in Phytotherapy
2022
The genus Calendula (Asteraceae) includes several species that are renowned for their therapeutic properties and/or use as ingredients in the preparation of cosmetics. The rare and critically endangered sea marigold, Calendula maritima Guss., an endemic species from Western Sicily, has also been recognized as a potential “farm plant species” for several important compounds used in cosmetics. However, the few remnant populations of this species are currently threatened with extinction because of several factors, such as hybridization with the congeneric species Calendula suffruticosa subsp. fulgida (Raf.) Guadagno and anthropogenic disturbance of its habitat. Therefore, in order to preserve …
Collision de similaritons optiques dans un amplificateur optique fibré Raman
2005
National audience; Nous abordons les aspects théoriques et expérimentaux de la génération et propagation de deux similaritons optiques de fréquences centrales différentes dans un amplificateur optique fibré Raman à dispersion normale. Nous observons les effets intervenant durant la collision des deux similaritons: un battement sinusoïdal apparaît dans la zone de recouvrement temporel des impulsions et des effets de la modulation de phase croisée modifient le spectre des similaritons. Les similaritons retrouvent néanmoins, après collision, leurs caractéristiques paraboliques.
Apparent content curves: description and analytical applications. Resolution of binary mixtures
1992
The apparent content curves and their analytical applications are described. Basing on these curves a mathematical method, which permits the identification of the interfering component present in a binary mixture as well as the determination of the contents of both constituents, is proposed. The existence of considerable interaction coefficients is not an impediment for its application. Besides, the analyte contents in the mixture can be obtained without the use of standard interference solutions. The proposed procedure is applied to the analysis of mixtures of dyes with overlapping absorption spectra.
A second strain gradient elasticity theory with second velocity gradient inertia – Part II: Dynamic behavior
2013
Abstract This paper is the sequel of a companion Part I paper devoted to the constitutive equations and to the quasi-static behavior of a second strain gradient material model with second velocity gradient inertia. In the present Part II paper, a multi-cell homogenization procedure (developed in the Part I paper) is applied to a nonhomogeneous body modelled as a simple material cell system, in conjunction with the principle of virtual work (PVW) for inertial actions (i.e. momenta and inertia forces), which at the macro-scale level takes on the typical format as for a second velocity gradient inertia material model. The latter (macro-scale) PVW is used to determine the equilibrium equations …
Control of Acoustical Quality of Indoor Spaces: Thorough Analysis of the Influence of Façade Typologies
2001
Building shape is of prime importance with regard to the acoustic aspects of achieving adequate indoor environmental quality. This paper presents experimental results obtained in a measurement programme carried out at CSTB, using reduced-scale models. The objectives were to identify the architectural forms of façades' best for noise mitigation, and to address the influence of façade architecture on indoor acoustic quality. Many façade typologies have been assessed in different situations involving combinations of structural and architectural elements, such as balustrades, balconies, loggias, etc. A systematic simulation of real configurations (buildings in front of one another, stacked or …
Artificial Neural Networks to Predict the Power Output of a PV Panel
2014
The paper illustrates an adaptive approach based on different topologies of artificial neural networks (ANNs) for the power energy output forecasting of photovoltaic (PV) modules. The analysis of the PV module’s power output needed detailed local climate data, which was collected by a dedicated weather monitoring system. The Department of Energy, Information Engineering, and Mathematical Models of the University of Palermo (Italy) has built up a weather monitoring system that worked together with a data acquisition system. The power output forecast is obtained using three different types of ANNs: a one hidden layer Multilayer perceptron (MLP), a recursive neural network (RNN), and a gamma m…
Modelling and Analysis of Nonstationary Vehicle-to-Infrastructure Channels with Time-Variant Angles of Arrival
2018
In mobile radio channel modelling, it is generally assumed that the angles of arrival (AOAs) are independent of time. This assumption does not in general agree with real-world channels in which the AOAs vary with the position of a moving receiver. In this paper, we first present a mathematical model for the time-variant AOAs. This model serves as the basis for the development of two nonstationary multipath fading channels models for vehicle-to-infrastructure communications. The statistical properties of both channel models are analysed with emphasis on the time-dependent autocorrelation function (ACF), time-dependent mean Doppler shift, time-dependent Doppler spread, and the Wigner-Ville sp…
Hybrid Particle Swarm Optimization With Genetic Algorithm to Train Artificial Neural Networks for Short-Term Load Forecasting
2019
This research proposes a new training algorithm for artificial neural networks (ANNs) to improve the short-term load forecasting (STLF) performance. The proposed algorithm overcomes the so-called training issue in ANNs, where it traps in local minima, by applying genetic algorithm operations in particle swarm optimization when it converges to local minima. The training ability of the hybridized training algorithm is evaluated using load data gathered by Electricity Generating Authority of Thailand. The ANN is trained using the new training algorithm with one-year data to forecast equal 48 periods of each day in 2013. During the testing phase, a mean absolute percentage error (MAPE) is used …
Tabu and Scatter Search for Artificial Neural Networks
2003
In this paper we address the problem of training multilayer feed-forward neural networks. These networks have been widely used for both prediction and classification in many different areas. Although the most popular method for training these networks is back propagation, other optimization methods such as tabu search or scatter search have been applied to solve this problem. This paper presents a new training algorithm based on the tabu search methodology that incorporates elements for search intensification and diversification by utilizing strategic designs where other previous approaches resort to randomization. Our method considers context and search information, as it is provided by th…
Daily Peak Temperature Forecasting with Elman Neural Networks
2005
This work presents a forecaster based on an Elman artificial neural network trained with resilient backpropagation algorithm for predicting the daily peak temperatures one day ahead. The available time series was recorded at Petrosino (TP), in the west coast of Sicily, Italy and it is composed by temperature (min and max values), the humidity (min and max values) and the rainfall value between January 1st, 1995 and May 14th, 2003. Performances and reliabilities of the proposed model were evaluated by a number of measures, comparing different neural models. Experimental results show very good prediction performances.