Search results for "Signal Processing"
showing 10 items of 2451 documents
Life cycle energy performances and environmental impacts of a prefabricated building module
2018
Abstract The paper explores the energy performances and environmental impacts of a prefabricated building module located in Messina (Sicily, Italy) through an approach that combines both the non-steady state building simulation and the Life Cycle Assessment methodology. The building uses renewable energy technologies and is usable in emergency situations or as simply temporary housing. Results show that the building module causes the emission of 1.5 t of CO2eq/m2 and consumes 29.2 GJ/m2 of primary energy during its life cycle. The building achieves the Net Zero Energy Building target even if it has relevant environmental impacts in the materials production stage (72% on average of the total…
Energy Barrier: Focus on the Essential: Extracting the Decisive Energy Barrier of a Complex Process (Adv. Mater. Interfaces 20/2019)
2019
Contribution to modeling the viscosity Arrhenius-type equation for some solvents by statistical correlations analysis
2014
Abstract Estimation and knowledge of transport properties of fluids are essential for heat and mass flow. Viscosity is one of the important properties which are affected by temperature and pressure. In the present work, based on the use of econometric and statistical techniques for parametric and non-parametric regression analysis and statistical correlation tests, we propose an equation modeling the relationship between the two parameters of viscosity Arrhenius-type equation, such as the Arrhenius energy ( E a ) or the pre-exponential factor ( A s ). In addition, we introduce a third interesting parameter called Arrhenius temperature ( T A ), to enrich the discussion. Empirical validation …
Energy-efficient routing control algorithm in large-scale WSN for water environment monitoring with application to Three Gorges Reservoir area
2013
Published version of an article in the journal: The Scientific World Journal. Also available from the publisher at: http://dx.doi.org/10.1155/2014/802915 Open Access The typical application backgrounds of large-scale WSN (wireless sensor networks) for the water environment monitoring in the Three Gorges Reservoir are large coverage area and wide distribution. To maximally prolong lifetime of large-scale WSN, a new energy-saving routing algorithm has been proposed, using the method of maximum energy-welfare optimization clustering. Firstly, temporary clusters are formed based on two main parameters, the remaining energy of nodes and the distance between a node and the base station. Secondly,…
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…
Illumination Correction on MR Images
2006
Objective. An important artifact corrupting Magnetic Resonance Images is the rf inhomogeneity, also called bias artifact. This anomaly produces an abnormal illumination fluctuation on the image, due to variations of the device magnetic field. This artifact is particularly strong on images acquired with a device specialized on upper and lower limbs due to their coil configuration. A method based on homomorphic filtering aimed to suppress this artifact was proposed by Guillemaud. This filter has two faults: it doesnt provide an indication about the cutoff frequency (cf) and introduces another illumination artifact on the edges of the foreground. This work is an improvement to this method because i…
FastEMD–CCA algorithm for unsupervised and fast removal of eyeblink artifacts from electroencephalogram
2020
Abstract Online detection and removal of eye blink (EB) artifacts from electroencephalogram (EEG) would be very useful in medical diagnosis and brain computer interface (BCI). In this work, approaches that combine unsupervised eyeblink artifact detection with empirical mode decomposition (EMD), and canonical correlation analysis (CCA), are proposed to automatically identify eyeblink artifacts and remove them in an online manner. First eyeblink artifact regions are automatically identified and an eyeblink artifact template is extracted via EMD, which incorporates an alternate interpolation technique, the Akima spline interpolation. The removal of eyeblink artifact components relies on the el…
Online detection and removal of eye blink artifacts from electroencephalogram
2021
Abstract The most prominent type of artifact contaminating electroencephalogram (EEG) signals are the eye blink (EB) artifacts, which could potentially lead to misinterpretation of the EEG signal. Online identification and elimination of eye blink artifacts are crucial in applications such a Brain-Computer Interfaces (BCI), neurofeedback, and epilepsy diagnosis. In this paper, algorithms that combine unsupervised eye blink artifact detection (eADA) with modified Empirical Mode Decomposition (FastEMD) and Canonical Correlation Analysis (CCA) are proposed, i.e., FastEMD-CCA2 and FastCCA, to automatically identify eye blink artifacts and remove them in an online setting. The average accuracy, …
An offline/real-time artifact rejection strategy to improve the classification of multi-channel evoked potentials
2008
The primary goal of this paper is to improve the classification of multi-channel evoked potentials (EPs) by introducing a temporal domain artifact detection strategy and using this strategy to (a) evaluate how the performance of classifiers is affected by artifacts and (b) show how the performance can be improved by detecting and rejecting artifacts in offline and real-time classification experiments. Using a pattern recognition approach, an artifact is defined in this study as any signal that may lead to inaccurate classifier parameter estimation and inaccurate testing. The temporal domain artifact detection tests include: a within-channel standard deviation (STD) test that can detect sign…