Search results for "NOISE"
showing 10 items of 1375 documents
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 …
SAN plot: A graphical representation of the signal, noise, and artifacts content of spectra
2019
The signal-to-noise ratio is an important property of NMR spectra. It allows to compare the sensitivity of experiments, the performance of hardware, etc. Its measurement is usually done in a rudimentary manner involving manual operation of selecting separately a region of the spectrum with signal and noise, respectively, applying some operation and returning the signal-to-noise ratio. We introduce here a simple method based on the analysis of the distribution of point intensities in one- and two-dimensional spectra. The signal/artifact/noise plots, (SAN plots) allows one to present in a graphical manner qualitative and quantitative information about spectra. It will be shown that besides me…
A Review of Kernel Methods in Remote Sensing Data Analysis
2011
Kernel methods have proven effective in the analysis of images of the Earth acquired by airborne and satellite sensors. Kernel methods provide a consistent and well-founded theoretical framework for developing nonlinear techniques and have useful properties when dealing with low number of (potentially high dimensional) training samples, the presence of heterogenous multimodalities, and different noise sources in the data. These properties are particularly appropriate for remote sensing data analysis. In fact, kernel methods have improved results of parametric linear methods and neural networks in applications such as natural resource control, detection and monitoring of anthropic infrastruc…
An Adaptive Global-Local Memetic Algorithm to Discover Resources in P2P Networks
2007
This paper proposes a neural network based approach for solving the resource discovery problem in Peer to Peer (P2P) networks and an Adaptive Global Local Memetic Algorithm (AGLMA) for performing the training of the neural network. This training is very challenging due to the large number of weights and noise caused by the dynamic neural network testing. The AGLMA is a memetic algorithm consisting of an evolutionary framework which adaptively employs two local searchers having different exploration logic and pivot rules. Furthermore, the AGLMA makes an adaptive noise compensation by means of explicit averaging on the fitness values and a dynamic population sizing which aims to follow the ne…
Automatic Identification of Watermarks and Watermarking Robustness Using Machine Learning Techniques
2021
The goal of this article is to propose a framework for automatic identification of watermarks from modified host images. The framework can be used with any watermark embedding/extraction system and is based on models built using machine learning (ML) techniques. Any supervised ML approach can be theoretically chosen. An important part of our framework consists in building a stand-alone module, independent of the watermarking system, for generating two types of watermarks datasets. The first type of datasets, that we will name artificially datasets, is generated from the original images by adding noise with an imposed maximum level of noise. The second type contains altered watermarked image…
A Neural Architecture for 3D Segmentation
2003
An original neural scheme for segmentation of range data is presented, which is part of a more general 3D vision system for robotic applications. The entire process relies on a neural architecture aimed to perform first order image irradiance analysis, that is local estimation of magnitude and orientation of the image irradiance gradient.
Filter approach to the stochastic analysis of MDOF wind-excited structures
1999
Abstract In this paper, an approach useful for stochastic analysis of the Gaussian and non-Gaussian behavior of the response of multi-degree-of-freedom (MDOF) wind-excited structures is presented. This approach is based on a particular model of the multivariate stochastic wind field based upon a particular diagonalization of the power spectral density (PSD) matrix of the fluctuating part of wind velocity. This diagonalization is performed in the space of eigenvectors and eigenvalues that are called here wind-eigenvalues and wind-eigenvectors, respectively. From the examination of these quantities it can be recognized that the wind-eigenvectors change slowly with frequency while the first wi…
Correlated X-ray spectral and timing variability of the Be/X-ray binary V0332+53/BQ Camelopardalis during a type II outburst
2005
We have used INTEGRAL & RXTE data to investigate the timing properties of the source in correlation with its spectral states as defined by different positions in the colour-colour diagram. The source shows two distinct branches in the colour-colour diagram that resemble those of the Z sources. The hard branch (similar to the horizontal branch of Z sources) is characterised by a low-amplitude change of the hard colour compared to the change in the soft colour. In the soft branch (analogue to the normal branch) the amplitude of variability of the hard colour is about three times larger than that of the soft colour. As the count rate decreases the source moves up gradually through the soft…
Thermal remote sensing of land surface temperature from satellites: Current status and future prospects
1995
Abstract In this paper we review the current status for deriving land surface temperatures (LSTs) by remote sensing from satellites in the thermal infrared. Because of its widespread use and global applicability, we concentrate on the Advanced Very High Resolution Radiometer (AVHRR). The theoretical framework and methodologies used to derive LSTs are reviewed and amplified. Practical algorithms are described and their accuracy and application critically evaluated through sensitivity studies and by inter‐comparison. The important effects of the atmosphere, surface emissivity and instrument noise are considered and the current practice for removing these effects is specified. The accuracy cur…
Land surface temperature retrieval from thermal infrared data: An assessment in the context of the Surface Processes and Ecosystem Changes Through Re…
2005
[1] SPECTRA (Surface Processes and Ecosystem Changes Through Response Analysis) is one of the core candidate missions which is being proposed for implementation in the European Space Agency (ESA) Earth Explorer program of research oriented missions. The scientific objective of the SPECTRA mission is to describe, understand, and model the role of terrestrial vegetation in the global carbon cycle and its response to climate variability under the increasing pressure of human activity. The SPECTRA satellite will embark an optical hyperspectral payload covering the solar spectral range (0.4 to 2.4 μm) and thermal infrared region (10.3 to 12.3 μm). This paper is focused on the land surface temper…