Search results for " Optics"
showing 10 items of 5880 documents
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…
New Objective Refraction Metric Based on Sphere Fitting to the Wavefront
2017
Purpose. To develop an objective refraction formula based on the ocular wavefront error (WFE) expressed in terms of Zernike coefficients and pupil radius, which would be an accurate predictor of subjective spherical equivalent (SE) for different pupil sizes.Methods. A sphere is fitted to the ocular wavefront at the center and at a variable distance,t. The optimal fitting distance,topt, is obtained empirically from a dataset of 308 eyes as a function of objective refraction pupil radius,r0, and used to define the formula of a new wavefront refraction metric (MTR). The metric is tested in another, independent dataset of 200 eyes.Results. For pupil radiir0≤2 mm, the new metric predicts the equ…
Midinfrared FT-IR as a Tool for Monitoring Herbaceous Biomass Composition and Its Conversion to Furfural
2015
A semiquantitative analysis by means of midinfrared FT-IR spectroscopy was tuned for the simultaneous determination of cellulose, hemicellulose, and lignin in industrial crops such as giant reed (Arundo donaxL.) and switchgrass (Panicum virgatumL.). Ternary mixtures of pure cellulose, hemicellulose, and lignin were prepared and a direct correlation area/concentration was achieved for cellulose and lignin, whereas indirect correlations were found for hemicellulose quantification. Good correspondences between the values derived from our model and those reported in the literature or obtained according to the official Van Soest method were ascertained. Average contents of 40–45% of cellulose, 2…
Assessment of the Operating Temperature of Crystalline PV Modules Based on Real Use Conditions
2014
Determining the operating temperatureTcof photovoltaic panelsPVis important in evaluating the actual performance of these systems. In the literature, different correlations exist, in either explicit or implicit forms, which often do not account for the electrical behaviour of panels; in this way, estimatingTcis based only on the passive behaviour of thePV. In this paper, the authors propose a new implicit correlation that takes into account the standard weather variables and the electricity production regimes of aPVpanel in terms of the proximity to the maximum power points. To validate its reliability, the new correlation was tested on two different PV panels (Sanyo and Kyocera panels) and…
Study of ambient light influence for three-dimensional scanners based on structured light
2007
Ambient light in a scene can introduce errors into range data from most commercial three-dimensional range scanners, particularly scanners that are based on projected patterns and structured lighting. We study the effects of ambient light on a specific commercial scanner. We further present a method for characterizing the range accuracy as a function of ambient light distortions. After a brief review of related research, we first describe the capabilities of the scanner we used and define the experimental setup for our study. Then we present the results of the range characterization relative to ambient light. In these results, we note a systematic error source that appears to be an artifact…
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…
A 4K-Input High-Speed Winner-Take-All (WTA) Circuit with Single-Winner Selection for Change-Driven Vision Sensors
2019
Winner-Take-All (WTA) circuits play an important role in applications where a single element must be selected according to its relevance. They have been successfully applied in neural networks and vision sensors. These applications usually require a large number of inputs for the WTA circuit, especially for vision applications where thousands to millions of pixels may compete to be selected. WTA circuits usually exhibit poor response-time scaling with the number of competitors, and most of the current WTA implementations are designed to work with less than 100 inputs. Another problem related to the large number of inputs is the difficulty to select just one winner, since many competitors ma…
Problems of coding stereo images in human memory
2010
This paper discusses the memorization and recall by man of a sequence of planar or stereoscopic images, including six frames that contain a planar strip (8×8 positions of the stimulus) or a volume strip (8×4×2 positions). At the recall stage, the subject chose between the stimulus and three distractors in each frame. It is shown that the times for recognition and recall are less for volume stimuli, while the percent of correct responses is greater for planar stimuli. For volume stimuli, the distribution of errors depends on the disparity between the target and the selected distractor. A model based on a heteroassociative neural network reproduces the error distribution for planar but not fo…
The FRAM robotic telescope for atmospheric monitoring at the Pierre Auger Observatory
2021
FRAM (F/Photometric Robotic Atmospheric Monitor) is a robotic telescope operated at the Pierre Auger Observatory in Argentina for the purposes of atmospheric monitoring using stellar photometry. As a passive system which does not produce any light that could interfere with the observations of the fluorescence telescopes of the observatory, it complements the active monitoring systems that use lasers. We discuss the applications of stellar photometry for atmospheric monitoring at optical observatories in general and the particular modes of operation employed by the Auger FRAM. We describe in detail the technical aspects of FRAM, the hardware and software requirements for a successful operati…
Theory and implications of neutrino mass
1989
Abstract I briefly review the basic theory of neutrino mass from the point of view of modern gauge theories. Some of the implications of neutrino masses for particle physics, nuclear physics, cosmology and astrophysics are discussed.