Search results for "Context"
showing 10 items of 6304 documents
Cloud screening with combined MERIS and AATSR images
2009
This paper presents a cloud screening algorithm based on ensemble methods that exploits the combined information from both MERIS and AATSR instruments on board ENVISAT in order to improve current cloud masking products for both sensors. The first step is to analyze the synergistic use of MERIS and AATSR images in order to extract some physically-based features increasing the separability of clouds and surface. Then, several artificial neural networks are trained using different sets of input features and different sets of training samples depending on acquisition and surface conditions. Finally, outputs of the trained neural networks are combined at the decision level to construct a more ac…
Deep learning strategies for automatic fault diagnosis in photovoltaic systems by thermographic images
2021
Abstract Losses of electricity production in photovoltaic systems are mainly caused by the presence of faults that affect the efficiency of the systems. The identification of any overheating in a photovoltaic module, through the thermographic non-destructive test, may be essential to maintain the correct functioning of the photovoltaic system quickly and cost-effectively, without interrupting its normal operation. This work proposes a system for the automatic classification of thermographic images using a convolutional neural network, developed via open-source libraries. To reduce image noise, various pre-processing strategies were evaluated, including normalization and homogenization of pi…
Combining a context aware neural network with a denoising autoencoder for measuring string similarities
2020
Abstract Measuring similarities between strings is central for many established and fast-growing research areas, including information retrieval, biology, and natural-language processing. The traditional approach to string similarity measurements is to define a metric with respect to a word space that quantifies and sums up the differences between characters in two strings; surprisingly, these metrics have not evolved a great deal over the past few decades. Indeed, the majority of them are still based on making a simple comparison between character and character distributions without considering the words context. This paper proposes a string metric that encompasses similarities between str…
Artificial Neural Networks in Sports: New Concepts and Approaches
2001
Artificial neural networks are tools, which - similar to natural neural networks - can learn to recognize and classify patterns, and so can help to optimise context depending acting. These abilitie...
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…
Discovering representative models in large time series databases
2004
The discovery of frequently occurring patterns in a time series could be important in several application contexts. As an example, the analysis of frequent patterns in biomedical observations could allow to perform diagnosis and/or prognosis. Moreover, the efficient discovery of frequent patterns may play an important role in several data mining tasks such as association rule discovery, clustering and classification. However, in order to identify interesting repetitions, it is necessary to allow errors in the matching patterns; in this context, it is difficult to select one pattern particularly suited to represent the set of similar ones, whereas modelling this set with a single model could…
The hyperfine structure in the rotational spectrum of CF+
2012
Context. CF+ has recently been detected in the Horsehead and Orion Bar photo-dissociation regions. The J=1-0 line in the Horsehead is double-peaked in contrast to other millimeter lines. The origin of this double-peak profile may be kinematic or spectroscopic. Aims. We investigate the effect of hyperfine interactions due to the fluorine nucleus in CF+ on the rotational transitions. Methods. We compute the fluorine spin rotation constant of CF+ using high-level quantum chemical methods and determine the relative positions and intensities of each hyperfine component. This information is used to fit the theoretical hyperfine components to the observed CF+ line profiles, thereby employing the h…
Three-neutrino mixing after the first results from K2K and KamLAND
2003
We analyze the impact of the data on long baseline \nu_\mu disappearance from the K2K experiment and reactor \bar\nu_e disappearance from the KamLAND experiment on the determination of the leptonic three-generation mixing parameters. Performing an up-to-date global analysis of solar, atmospheric, reactor and long baseline neutrino data in the context of three-neutrino oscillations, we determine the presently allowed ranges of masses and mixing and we consistently derive the allowed magnitude of the elements of the leptonic mixing matrix. We also quantify the maximum allowed contribution of \Delta m^2_{21} oscillations to CP-odd and CP-even observables at future long baseline experiments.
Measuring the deviation of the 2–3 lepton mixing from maximal with atmospheric neutrinos
2004
The measurement of the deviation of the 2-3 leptonic mixing from maximal, D_23 = 1/2 - sin^2(theta_23), is one of the key issues for understanding the origin of the neutrino masses and mixing. In the three-neutrino context we study the dependence of various observables in the atmospheric neutrinos on D_23. We perform a global three-neutrino analysis of the atmospheric and reactor neutrino data taking into account the effects of both the oscillations driven by the "solar" parameters (Delta_m_21^2 and theta_12) and the 1-3 mixing. The departure from the one-dominant mass scale approximation results into the shift of the 2-3 mixing from maximal by Delta_sin^2(theta_23) ~ 0.04, so that D_23 ~ 0…
Critical energy flux and mass in solvable theories of 2D dilaton gravity
1998
In this paper we address the issue of determining the semiclassical threshold for black hole formation in the context of a one-parameter family of theories which continuously interpolates between the RST and BPP models. We find that the results depend significantly on the initial static configuration of the spacetime geometry before the influx of matter is turned on. In some cases there is a critical energy density, given by the Hawking rate of evaporation, as well as a critical mass $m_{cr}$ (eventually vanishing). In others there is neither $m_{cr}$ nor a critical flux.