997 resultados para Traffic Estimation


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In this paper, we present a method for estimating local thickness distribution in nite element models, applied to injection molded and cast engineering parts. This method features considerable improved performance compared to two previously proposed approaches, and has been validated against thickness measured by di erent human operators. We also demonstrate that the use of this method for assigning a distribution of local thickness in FEM crash simulations results in a much more accurate prediction of the real part performance, thus increasing the bene ts of computer simulations in engineering design by enabling zero-prototyping and thus reducing product development costs. The simulation results have been compared to experimental tests, evidencing the advantage of the proposed method. Thus, the proposed approach to consider local thickness distribution in FEM crash simulations has high potential on the product development process of complex and highly demanding injection molded and casted parts and is currently being used by Ford Motor Company.

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Minimally invasive cardiovascular interventions guided by multiple imaging modalities are rapidly gaining clinical acceptance for the treatment of several cardiovascular diseases. These images are typically fused with richly detailed pre-operative scans through registration techniques, enhancing the intra-operative clinical data and easing the image-guided procedures. Nonetheless, rigid models have been used to align the different modalities, not taking into account the anatomical variations of the cardiac muscle throughout the cardiac cycle. In the current study, we present a novel strategy to compensate the beat-to-beat physiological adaptation of the myocardium. Hereto, we intend to prove that a complete myocardial motion field can be quickly recovered from the displacement field at the myocardial boundaries, therefore being an efficient strategy to locally deform the cardiac muscle. We address this hypothesis by comparing three different strategies to recover a dense myocardial motion field from a sparse one, namely, a diffusion-based approach, thin-plate splines, and multiquadric radial basis functions. Two experimental setups were used to validate the proposed strategy. First, an in silico validation was carried out on synthetic motion fields obtained from two realistic simulated ultrasound sequences. Then, 45 mid-ventricular 2D sequences of cine magnetic resonance imaging were processed to further evaluate the different approaches. The results showed that accurate boundary tracking combined with dense myocardial recovery via interpolation/ diffusion is a potentially viable solution to speed up dense myocardial motion field estimation and, consequently, to deform/compensate the myocardial wall throughout the cardiac cycle. Copyright © 2015 John Wiley & Sons, Ltd.

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The success of dental implant-supported prosthesis is directly linked to the accuracy obtained during implant’s pose estimation (position and orientation). Although traditional impression techniques and recent digital acquisition methods are acceptably accurate, a simultaneously fast, accurate and operator-independent methodology is still lacking. Hereto, an image-based framework is proposed to estimate the patient-specific implant’s pose using cone-beam computed tomography (CBCT) and prior knowledge of implanted model. The pose estimation is accomplished in a threestep approach: (1) a region-of-interest is extracted from the CBCT data using 2 operator-defined points at the implant’s main axis; (2) a simulated CBCT volume of the known implanted model is generated through Feldkamp-Davis-Kress reconstruction and coarsely aligned to the defined axis; and (3) a voxel-based rigid registration is performed to optimally align both patient and simulated CBCT data, extracting the implant’s pose from the optimal transformation. Three experiments were performed to evaluate the framework: (1) an in silico study using 48 implants distributed through 12 tridimensional synthetic mandibular models; (2) an in vitro study using an artificial mandible with 2 dental implants acquired with an i-CAT system; and (3) two clinical case studies. The results shown positional errors of 67±34μm and 108μm, and angular misfits of 0.15±0.08º and 1.4º, for experiment 1 and 2, respectively. Moreover, in experiment 3, visual assessment of clinical data results shown a coherent alignment of the reference implant. Overall, a novel image-based framework for implants’ pose estimation from CBCT data was proposed, showing accurate results in agreement with dental prosthesis modelling requirements.

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In this study, the results of chemical concentrations inside and outside of a Lisbon (Portugal) traffic tunnel were compared, during one week. They were obtained by Instrumental Neutron Activation Analysis (INAA). The tunnel values largely exceed the Air Ambient legislated values and the Pearson Correlations Coefficients point out to soil re-suspension/dispersed road dust (As, Ce, Eu, Hf, Fe, Mo, Sc, Zn), traffic-markers (Ba, Cr), tire wear (Cr, Zn), break wear (Fe, Zn, Ba, Cu, Sb), exhaust and motor oil (Zn) and sea-spray (Br, Na). On all days these elements inside the tunnel were more enriched than outside; significant statistical differences were found for Co (p=0.005), Br (p=0.008), Zn (p=0.01) and Sb (p=0.005), while enrichment factors of As and Sc are statistically identical. The highest values were found for As, Br, Zn and Sb, for both inside and outside the tunnel.

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The portfolio generating the iTraxx EUR index is modeled by coupled Markov chains. Each of the industries of the portfolio evolves according to its own Markov transition matrix. Using a variant of the method of moments, the model parameters are estimated from a data set of Standard and Poor's. Swap spreads are evaluated by Monte-Carlo simulations. Along with an actuarially fair spread, at least squares spread is considered.

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Mathematical Program with Complementarity Constraints (MPCC) finds many applications in fields such as engineering design, economic equilibrium and mathematical programming theory itself. A queueing system model resulting from a single signalized intersection regulated by pre-timed control in traffic network is considered. The model is formulated as an MPCC problem. A MATLAB implementation based on an hyperbolic penalty function is used to solve this practical problem, computing the total average waiting time of the vehicles in all queues and the green split allocation. The problem was codified in AMPL.

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The measurement of room impulse response (RIR) when there are high background noise levels frequently means one must deal with very low signal-to-noise ratios (SNR). if such is the case, the measurement might yield unreliable results, even when synchronous averaging techniques are used. Furthermore, if there are non-linearities in the apparatus or system time variances, the final SNR can be severely degraded. The test signals used in RIR measurement are often disturbed by non-stationary ambient noise components. A novel approach based on the energy analysis of ambient noise - both in the time and in frequency - was considered. A modified maximum length sequence (MLS) measurement technique. referred to herein as the hybrid MLS technique, was developed for use in room acoustics. The technique consists of reducing the noise energy of the captured sequences before applying the averaging technique in order to improve the overall SNRs and frequency response accuracy. Experiments were conducted under real conditions with different types of underlying ambient noises. Results are shown and discussed. Advantages and disadvantages of the hybrid MLS technique over standard MLS technique are evaluated and discussed. Our findings show that the new technique leads to a significant increase in the overall SNR. (C) 2008 Elsevier Ltd. All rights reserved.

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Copyright © 2014 Entomological Society of America.

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This paper presents a novel moving target indicator which is selective with respect to a direction of interest. Preliminary results indicate that the obtained selectivity may have high interest in civil traffic monitoring using single channel SAR data.

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Traffic emissions and tobacco smoke are considered two main sources of polycyclic aromatic hydrocarbons (PAHs) in indoor and outdoor air. In this study, the impact of these sources on the level of fine particulate matter (PM2.5) and on the distribution of 15 PAHs regarded as priority pollutants by the US-EPA on PM2.5 were evaluated and compared. Outdoor and indoor PM2.5 samples were collected during winter 2008 in Oporto city in Portugal, for sampling periods of 12 and 24 hours, respectively. The outdoor PM2.5 were sampled at one site directly influenced by traffic emissions and the indoor PM2.5 samples were collected at one home directly influenced by tobacco smoke and another one without smoke. A methodology based on microwave-assisted extraction and liquid chromatography with fluorescence detection was applied for the efficient PAHs determination in indoor and outdoor PM2.5. PAHs in indoor PM2.5 concentrations were significantly influenced by the presence of traffic and tobacco smoking emissions. The mean of ΣPAHs in the outdoor traffic PM2.5 was not significantly different from the value attained in the indoor without smoking site. The tobacco smoke increased significantly PAHs concentrations on average about 1000 times more, when compared with the outdoor profile samples suggesting that tobacco smoking may be the most important source of indoor PAHs pollution.

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Air pollution represents a serious risk not only to environment and human health, but also to historical heritage. In this study, air pollution of the Oporto Metropolitan Area and its main impacts were characterized. The results showed that levels of CO, PM10 and SO2 have been continuously decreasing in the respective metropolitan area while levels of NOx and NO2 have not changed significantly. Traffic emissions were the main source of the determined polycyclic aromatic hydrocarbons (PAHs; 16 PAHs considered by U.S. EPA as priority pollutants, dibenzo[a,l]pyrene and benzo[j]fluoranthene) in air of the respective metropolitan area. The mean concentration of 18 PAHs in air was 69.9±39.7 ng m−3 with 3–4 rings PAHs accounting for 75% of the total ΣPAHs. The health risk analysis of PAHs in air showed that the estimated values of lifetime lung cancer risks considerably exceeded the health-based guideline level. Analytical results also confirm that historical monuments in urban areas act as passive repositories for air pollutants present in the surrounding atmosphere. FTIR and EDX analyses showed that gypsum was the most important constituent of black crusts of the characterized historical monument Monastery of Serra do Pilar classified as “UNESCO World Cultural Heritage”. In black crusts, 4–6 rings compounds accounted approximately for 85% of ΣPAHs. The diagnostic ratios confirmed that traffic emissions were the major source of PAHs in black crusts; PAH composition profiles were very similar for crusts and PM10 and PM2.5.

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Because polycyclic aromatic hydrocarbons (PAHs) have been proven to be toxic, mutagenic, and/or carcinogenic, there is widespread interest in analyzing and evaluating exposure to PAHs in atmospheric environments influenced by different emission sources. Because traffic emissions are one of the biggest sources of fine particles, more information on carcinogenic PAHs associated with fine particles needs to be provided. Aiming to further understand the impact of traffic particulate matter (PM) on human health, this study evaluated the influence of traffic on PM10 (PM with aerodynamic diameter <10 µm) and PM2.5 (PM with aerodynamic diameter <2.5 µm), considering their concentrations and compositions in carcinogenic PAHs. Samples were collected at one site influenced by traffic emissions and at one reference site using lowvolume samplers. Analysis of PAHs was performed by microwave-assisted extraction combined with liquid chromatography (MAE-LC); 17 PAHs, including 9 carcinogenic ones, were quantified. At the site influenced by traffic emissions, PM10 and PM2.5 concentrations were, respectively, 380 and 390% higher than at the background site. When influenced by traffic emissions, the total concentration of nine carcinogenic compounds (naphthalene, chrysene, benzo(a)anthracene, benzo(b) fluoranthene, benzo(k)fluoranthene, benzo(a)pyrene, dibenzo(a,h)anthracene, indeno(1,2,3-cd)pyrene, and dibenzo(a,l)pyrene) was increased by 2400 and 3000% in PM10 and PM2.5, respectively; these nine carcinogenic compounds represented 68 and 74% of total PAHs (ƩPAHs) for PM10 and PM2.5, respectively. All PAHs, including the carcinogenic compounds, were mainly present in fine particles. Considering the strong influence of these fine particles on human health, these conclusions are relevant for the development of strategies to protect public health.

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The objectives of this work were: (1) to identify an isotherm model to relate the contaminant contents in the gas phase with those in the solid and non-aqueous liquid phases; (2) to develop a methodology for the estimation of the contaminant distribution in the different phases of the soil; and (3) to evaluate the influence of soil water content on the contaminant distribution in soil. For sandy soils with negligible contents of clay and natural organic matter, contaminated with benzene, toluene, ethylbenzene, xylene, trichloroethylene (TCE), and perchloroethylene (PCE), it was concluded that: (1) Freundlich’s model showed to be adequate to relate the contaminant contents in the gas phase with those in the solid and non-aqueous liquid phases; (2) the distribution of the contaminants in the different phases present in the soil could be estimated with differences lower than 10% for 83% of the cases; and (3) an increase of the soil water content led to a decrease of the amount of contaminant in the solid and non-aqueous liquid phases, increasing the amount in the other phases.

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Considering vehicular transport as one of the most health‐relevant emission sources of urban air, and with aim to further understand its negative impact on human health, the objective of this work was to study its influence on levels of particulate‐bound PAHs and to evaluate associated health risks. The 16 PAHs considered by USEPA as priority pollutants, and dibenzo[a, l]pyrene associated with fine (PM2.5) and coarse (PM2.5–10) particles were determined. The samples were collected at one urban site, as well as at a reference place for comparison. The results showed that the air of the urban site was more seriously polluted than at the reference one, with total concentrations of 17 PAHs being 2240% and 640% higher for PM2.5 and PM2.5–10, respectively; vehicular traffic was the major emission source at the urban site. PAHs were predominantly associated with PM2.5 (83% to 94% of ΣPAHs at urban and reference site, respectively) with 5 rings PAHs being the most abundant groups of compounds at both sites. The risks associated with exposure to particulate PAHs were evaluated using the TEF approach. The estimated value of lifetime lung cancer risks exceeded the health‐based guideline levels, thus demonstrating that exposure to PM2.5‐bound PAHs at levels found at urban site might cause potential health risks. Furthermore, the results showed that evaluation of benzo[a] pyrene (regarded as a marker of the genotoxic and carcinogenic PAHs) alone would probably underestimate the carcinogenic potential of the studied PAH mixtures.

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In the last few years, the number of systems and devices that use voice based interaction has grown significantly. For a continued use of these systems, the interface must be reliable and pleasant in order to provide an optimal user experience. However there are currently very few studies that try to evaluate how pleasant is a voice from a perceptual point of view when the final application is a speech based interface. In this paper we present an objective definition for voice pleasantness based on the composition of a representative feature subset and a new automatic voice pleasantness classification and intensity estimation system. Our study is based on a database composed by European Portuguese female voices but the methodology can be extended to male voices or to other languages. In the objective performance evaluation the system achieved a 9.1% error rate for voice pleasantness classification and a 15.7% error rate for voice pleasantness intensity estimation.