The Experts below are selected from a list of 462303 Experts worldwide ranked by ideXlab platform
Eric Bibeau - One of the best experts on this subject based on the ideXlab platform.
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optimal design of hybrid renewable Energy systems in buildings with low to high renewable Energy Ratio
Renewable Energy, 2015Co-Authors: Masoud Sharafi, Tarek Y Elmekkawy, Eric BibeauAbstract:We develop a simulation-based meta-heuristic approach that determines the optimal size of a hybrid renewable Energy system for residential buildings. This multi-objective optimization problem requires the advancement of a dynamic multi-objective particle swarm optimization algorithm that maximizes the renewable Energy Ratio of buildings and minimizes total net present cost and CO2 emission for required system changes. Three proven performance metrics evaluate the quality of the Pareto front generated by the proposed approach. The obtained results are compared against two reported multi-objective optimization algorithms in the related literature. Finally, an existing residential apartment located in a cold Canadian climate provides a test case to apply the proposed model and optimally size a hybrid renewable Energy system. In this test application, the model investigates the potential use of a heat pump, a biomass boiler, wind turbines, solar heat collectors, photovoltaic panels, and a heat storage tank to produce renewable Energy for the building. Furthermore, the utilization of plug-in electric vehicles for transportation reduces gasoline use where all power is generated by the building, and the utility provides the means to match intermittent renewable geneRation from solar and wind to the building electrical loads. Model results show that under the chosen meteorological conditions and building parameters a wind turbine, and plug-in electric vehicle technologies are consistently the optimal option to achieve a target renewable Energy Ratio. In particular, the optimization result shows that the renewable Energy Ratio can achieve near 100% by installing a 73 kW wind turbine, a 200 kW biomass boiler, and using plug-in electric vehicles. This option has a net present cost of C$705,180 and results in total CO2 emission of 2.4 ton/year. Finally, a sensitivity analysis is performed to investigate the impact of economic constants on net present cost of the obtained non-dominated solutions.
Yoichi Haneda - One of the best experts on this subject based on the ideXlab platform.
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estimating direct to reverberant Energy Ratio using d r spatial correlation matrix model
IEEE Transactions on Audio Speech and Language Processing, 2011Co-Authors: Yusuke Hioka, Kenta Niwa, Sumitaka Sakauchi, Kenichi Furuya, Yoichi HanedaAbstract:We present a method for estimating the direct-to-reverberant Energy Ratio (DRR) that uses a direct and reverberant sound spatial correlation matrix model (Hereafter referred to as the spatial correlation model). This model expresses the spatial correlation matrix of an array input signal as two spatial correlation matrices, one for direct sound and one for reverbeRation. The direct sound propagates from the direction of the sound source but the reverbeRation arrives from every direction uniformly. The DRR is calculated from the power spectra of the direct sound and reverbeRation that are estimated from the spatial correlation matrix of the measured signal using the spatial correlation model. The results of experiment and simulation confirm that the proposed method gives mostly correct DRR estimates unless the sound source is far from the microphone array, in which circumstance the direct sound picked up by the microphone array is very small. The method was also evaluated using various scales in simulated and actual acoustical environments, and its limitations revealed. We estimated the sound source distance using a small microphone array, which is an example of application of the proposed DRR estimation method.
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estimating direct to reverberant Energy Ratio based on spatial correlation model segregating direct sound and reverbeRation
International Conference on Acoustics Speech and Signal Processing, 2010Co-Authors: Yusuke Hioka, Kenta Niwa, Sumitaka Sakauchi, Kenichi Furuya, Yoichi HanedaAbstract:A new approach for estimating the direct-to-reverberant Energy Ratio (DRR) using a microphone array is proposed. The method is based on amodel of a spatial correlation matrix that segregates direct sound and reverbeRation. It estimates DRR from the power spectra of both components, which are derived from the correlation matrix of the observed signal. In experiments performed in simulated and actual reverberant environments, the proposed method mostly succeeded in estimating DRR accurately. We also present speech enhancement using binary masking as an example of an application of the estimated DRR. By utilization of the DRR as a factor to discriminate the distances of speakers, sepaRation of speech signals whose sources were located in the same direction but at different distances was achieved.
Norbert Kopco - One of the best experts on this subject based on the ideXlab platform.
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cortical auditory distance representation based on direct to reverberant Energy Ratio
NeuroImage, 2020Co-Authors: Norbert Kopco, Keerthi Kumar Doreswamy, Samantha Huang, Stephanie Rossi, Jyrki AhveninenAbstract:Abstract Auditory distance perception and its neuronal mechanisms are poorly understood, mainly because 1) it is difficult to separate distance processing from intensity processing, 2) multiple intensity-independent distance cues are often available, and 3) the cues are combined in a context-dependent way. A recent fMRI study identified human auditory cortical area representing intensity-independent distance for sources presented along the interaural axis (Kopco et al. PNAS, 109, 11019-11024). For these sources, two intensity-independent cues are available, interaural level difference (ILD) and direct-to-reverberant Energy Ratio (DRR). Thus, the observed activations may have been contributed by not only distance-related, but also direction-encoding neuron populations sensitive to ILD. Here, the paradigm from the previous study was used to examine DRR-based distance representation for sounds originating in front of the listener, where ILD is not available. In a virtual environment, we performed behavioral and fMRI experiments, combined with computational analyses to identify the neural representation of distance based on DRR. The stimuli varied in distance (15–100 cm) while their received intensity was varied randomly and independently of distance. Behavioral performance showed that intensity-independent distance discrimination is accurate for frontal stimuli, even though it is worse than for lateral stimuli. fMRI activations for sounds varying in frontal distance, as compared to varying only in intensity, increased bilaterally in the posterior banks of Heschl’s gyri, the planum temporale, and posterior superior temporal gyrus regions. Taken together, these results suggest that posterior human auditory cortex areas contain neuron populations that are sensitive to distance independent of intensity and of binaural cues relevant for directional hearing.
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cortical auditory distance representation based on direct to reverberant Energy Ratio
bioRxiv, 2019Co-Authors: Norbert Kopco, Keerthi Kumar Doreswamy, Samantha Huang, Stephanie Rossi, Jyrki AhveninenAbstract:Abstract Auditory distance perception and its neuronal mechanisms are poorly understood, mainly because 1) it is difficult to separate distance processing from intensity processing, 2) multiple intensity-independent distance cues are often available, and 3) the cues are combined in a context-dependent way. A recent fMRI study identified human auditory cortical area representing intensity-independent distance for sources presented along the interaural axis (Kopco et al., PNAS, 109, 11019-11024). For these sources, two intensity-independent cues are available, interaural level difference (ILD) and direct-to-reverberant Energy Ratio (DRR). Thus, the observed activations may have been contributed by not only distance-related, but also direction-encoding neuron populations sensitive to ILD. Here, the paradigm from the previous study was used to examine DRR-based distance representation for sounds originating in front of the listener, where ILD is not available. In a virtual environment, we performed behavioral and fMRI experiments, combined with computational analyses to identify the neural representation of distance based on DRR. The stimuli varied in distance (15-100 cm) while their received intensity was varied randomly and independently of distance. Behavioral performance showed that intensity-independent distance discrimination is accurate for frontal stimuli, even though it is worse than for lateral stimuli. fMRI activations for sounds varying in frontal distance, as compared to varying only in intensity, increased bilaterally in the posterior banks of Heschl9s gyri, the planum temporale, and posterior superior temporal gyrus regions. Taken together, these results suggest that posterior human auditory cortex areas contain neuron populations that are sensitive to distance independent of intensity and of binaural cues relevant for directional hearing. Highlights Posterior auditory cortices (AC) are sensitive to frontally presented distance cues These effects are independent of intensity- and direction-related binaural cues fMRI activations to frontal distance cues are found in the right and left AC The frontal reverbeRation-related auditory distance cues are behaviorally relevant
Masoud Sharafi - One of the best experts on this subject based on the ideXlab platform.
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optimal design of hybrid renewable Energy systems in buildings with low to high renewable Energy Ratio
Renewable Energy, 2015Co-Authors: Masoud Sharafi, Tarek Y Elmekkawy, Eric BibeauAbstract:We develop a simulation-based meta-heuristic approach that determines the optimal size of a hybrid renewable Energy system for residential buildings. This multi-objective optimization problem requires the advancement of a dynamic multi-objective particle swarm optimization algorithm that maximizes the renewable Energy Ratio of buildings and minimizes total net present cost and CO2 emission for required system changes. Three proven performance metrics evaluate the quality of the Pareto front generated by the proposed approach. The obtained results are compared against two reported multi-objective optimization algorithms in the related literature. Finally, an existing residential apartment located in a cold Canadian climate provides a test case to apply the proposed model and optimally size a hybrid renewable Energy system. In this test application, the model investigates the potential use of a heat pump, a biomass boiler, wind turbines, solar heat collectors, photovoltaic panels, and a heat storage tank to produce renewable Energy for the building. Furthermore, the utilization of plug-in electric vehicles for transportation reduces gasoline use where all power is generated by the building, and the utility provides the means to match intermittent renewable geneRation from solar and wind to the building electrical loads. Model results show that under the chosen meteorological conditions and building parameters a wind turbine, and plug-in electric vehicle technologies are consistently the optimal option to achieve a target renewable Energy Ratio. In particular, the optimization result shows that the renewable Energy Ratio can achieve near 100% by installing a 73 kW wind turbine, a 200 kW biomass boiler, and using plug-in electric vehicles. This option has a net present cost of C$705,180 and results in total CO2 emission of 2.4 ton/year. Finally, a sensitivity analysis is performed to investigate the impact of economic constants on net present cost of the obtained non-dominated solutions.
M Cooke - One of the best experts on this subject based on the ideXlab platform.
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binaural estimation of sound source distance via the direct to reverberant Energy Ratio for static and moving sources
IEEE Transactions on Audio Speech and Language Processing, 2010Co-Authors: Yanchen Lu, M CookeAbstract:One of the principal cues believed to be used by listeners to estimate the distance to a sound source is the Ratio of energies along the direct and indirect paths to the receiver. In essence, this “direct-to-reverberant” Energy Ratio reveals the absolute distance component of the direct Energy by normalizing by what is assumed to be distance-independent reverberant Energy. Earlier approaches to direct-to-reverberant Energy Ratio calculation made use of the estimated room impulse response, but these techniques are computationally expensive and inaccurate in practice. This paper proposes and evaluates an alternative approach which uses binaural signals to segregate Energy arriving from the estimated direction of the direct source from that arriving from other directions, employing a novel binaural equalization-cancellation technique. The system is integrated with a probabilistic inference framework, particle filtering, to handle the nonstationarity of Energy-based measurements. The algorithm is capable of using reverbeRation to estimate source distance in large rooms with errors of less than 1 m for static sources and 1.5-3.5 m for sources with varying degrees of motion complexity. Model performance can be accounted for largely in terms of a competition between auditory horizon and source Energy fluctuation effects.