966 resultados para Crowd density estimation


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The inductively coupled plasma atomic emission, spectrometry (ICP-AES) and its signal characteristics were discussed using modem spectral estimation technique. The power spectra density (PSD) was calculated using the auto-regression (AR) model of modem spectra estimation. The Levinson-Durbin recursion method was used to estimate the model parameters which were used for the PSD computation. The results obtained with actual ICP-AES spectra and measurements showed that the spectral estimation technique was helpful for the better understanding about spectral composition and signal characteristics.

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For two multinormal populations with equal covariance matrices the likelihood ratio discriminant function, an alternative allocation rule to the sample linear discriminant function when n1 ≠ n2 ,is studied analytically. With the assumption of a known covariance matrix its distribution is derived and the expectation of its actual and apparent error rates evaluated and compared with those of the sample linear discriminant function. This comparison indicates that the likelihood ratio allocation rule is robust to unequal sample sizes. The quadratic discriminant function is studied, its distribution reviewed and evaluation of its probabilities of misclassification discussed. For known covariance matrices the distribution of the sample quadratic discriminant function is derived. When the known covariance matrices are proportional exact expressions for the expectation of its actual and apparent error rates are obtained and evaluated. The effectiveness of the sample linear discriminant function for this case is also considered. Estimation of true log-odds for two multinormal populations with equal or unequal covariance matrices is studied. The estimative, Bayesian predictive and a kernel method are compared by evaluating their biases and mean square errors. Some algebraic expressions for these quantities are derived. With equal covariance matrices the predictive method is preferable. Where it derives this superiority is investigated by considering its performance for various levels of fixed true log-odds. It is also shown that the predictive method is sensitive to n1 ≠ n2. For unequal but proportional covariance matrices the unbiased estimative method is preferred. Product Normal kernel density estimates are used to give a kernel estimator of true log-odds. The effect of correlation in the variables with product kernels is considered. With equal covariance matrices the kernel and parametric estimators are compared by simulation. For moderately correlated variables and large dimension sizes the product kernel method is a good estimator of true log-odds.

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Empirical modeling of high-frequency currency market data reveals substantial evidence for nonnormality, stochastic volatility, and other nonlinearities. This paper investigates whether an equilibrium monetary model can account for nonlinearities in weekly data. The model incorporates time-nonseparable preferences and a transaction cost technology. Simulated sample paths are generated using Marcet's parameterized expectations procedure. The paper also develops a new method for estimation of structural economic models. The method forces the model to match (under a GMM criterion) the score function of a nonparametric estimate of the conditional density of observed data. The estimation uses weekly U.S.-German currency market data, 1975-90. © 1995.

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Based on experimental viscosity data collected from the literature and using density data obtained from a predictive method previously proposed by the authors, a group contribution method is proposed to estimate viscosity of imidazolium-, pyridinium-, and pyrrolidinium-based ILs containing hexafluorophosphate (PF6), tetrafluoroborate (BF4), bis(trifluoromethanesulfonyl) amide (Tf2N), chloride (Cl), acetate (CH3COO), methyl sulfate (MeSO4), ethyl sulfate (EtSO4), and trifluoromethanesulfonate (CF3SO3) anions, covering wide ranges of temperature, 293–393 K and viscosity, 4–21,000 cP. It is shown that a good agreement with literature data is obtained. For circa 500 data points of 29 ILs studied, a mean percent deviation (MPD) of 7.7% with a maximum deviation smaller than 28% was observed. 71.1% of the estimated viscosities present deviations smaller than 10% of the experimental values while only 6.4% have deviations larger than 20%. The group contribution method here developed can thus be used to evaluate the viscosity of new ionic liquids in wide ranges of temperatures at atmospheric pressure and, as data for new groups of cations and anions became available, can be extended to a larger range of ionic liquids.

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The limited availability of experimental data and their quality have been preventing the development of predictive methods and Computer Aided Molecular Design (CAMD) of ionic liquids (ILs). Based on experimental speed of sound data collected from the literature, the inter-relationship of surface tension (s), density (?), and speed of sound (u) has been examined for imidazolium based ILs containing hexafluorophosphate (PF6), tetrafluoroborate (BF4), bis(trifluoromethanesulphonyl) amide (NTf2), methyl sulphate (MeSO4), ethyl sulphate (EtSO4), and trifluoromethanesulphonate (CF3SO3) anions, covering wide ranges of temperature, 278.15–343.15 K and speed of sound, 1129.0–1851.0 m s-1. The speed of sound was correlated with a modified Auerbach's relation, by using surface tension and density data obtained from volume based predictive methods previously proposed by the authors. It is shown that a good agreement with literature data is obtained. For 133 data points of 14 ILs studied a mean percent deviation (MPD) of 1.96% with a maximum deviation inferior to 5% was observed. The correlations developed here can thus be used to evaluate the speeds of sound of new ionic liquids.

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The estimation of animal abundance has a central role in wildlife management and research, including the role of badgers Meles meles in bovine tuberculosis transmission to cattle. This is the first study to examine temporal change in the badger population of Northern Ireland over amedium- to long-term time frame of 14-18 years by repeating a national survey first conducted during 1990-1993. A total of 212 1-km2 squares were surveyed during 2007-2008 and the number, type and activity of setts therein recorded. Badgers were widespread with 75% of squares containing at least one sett. The mean density of activemain setts,which was equivalent to badger social group density, was 0.56 (95%CI: 0.46-0.67) active main setts per km2 during 2007-2008. Social group density varied significantly among landclass groups and counties. The total number of social groups was estimated at 7,600 (95%CI: 6,200-9,000) and, not withstanding probable sources of error in estimating social group size, the total abundance of badgers was estimated to be 34,100 (95% CI: 26,200-42,000). There was no significant change in the badger population from that recorded during 1990-1993. A resource selection model provided a relative probability of sett construction at a spatial scale of 25m. Sett locations were negatively associated with elevation and positively associated with slope, aspect, soil sand content, the presence of cover, and the area of improved grassland and arable agriculture within 300 m.

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To optimize the performance of wireless networks, one needs to consider the impact of key factors such as interference from hidden nodes, the capture effect, the network density and network conditions (saturated versus non-saturated). In this research, our goal is to quantify the impact of these factors and to propose effective mechanisms and algorithms for throughput guarantees in multi-hop wireless networks. For this purpose, we have developed a model that takes into account all these key factors, based on which an admission control algorithm and an end-to-end available bandwidth estimation algorithm are proposed. Given the necessary network information and traffic demands as inputs, these algorithms are able to provide predictive control via an iterative approach. Evaluations using analytical comparison with simulations as well as existing research show that the proposed model and algorithms are accurate and effective.

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O presente trabalho aborda o problema da estimação de canal e da estimação de desvio de frequência em sistemas OFDM com múltiplas configurações de antenas no transmissor e no receptor. Nesta tese é apresentado o estudo teórico sobre o impacto da densidade de pilotos no desempenho da estimação de canal em sistemas OFDM e são propostos diversos algoritmos para estimação de canal e estimação de desvio de frequência em sistemas OFDM com antenas únicas no transmissor e receptor, com diversidade de transmissão e MIMO. O estudo teórico culmina com a formulação analítica do erro quadrático médio de um estimador de canal genérico num sistema OFDM que utilize pilotos dedicados, distribuidos no quadro transmitido em padrões bi-dimensionais. A formulação genérica é concretizada para o estimador bi-dimensional LS-DFT, permitindo aferir da exactidão da formulação analítica quando comparada com os valores obtidos por simulação do sistema abordado. Os algoritmos de estimação investigados tiram partido da presença de pilotos dedicados presentes nos quadros transmitidos para estimar com precisão os parâmetros pretendidos. Pela sua baixa complexidade, estes algoritmos revelam-se especialmente adequados para implementação em terminais móveis com capacidade computacional e consumo limitados. O desempenho dos algoritmos propostos foi avaliado por meio de simulação do sistema utilizado, recorrendo a modelos aceites de caracterização do canal móvel multipercurso. A comparação do seu desempenho com algoritmos de referência permitir aferir da sua validade. ABSTRACT: The present work focus on the problem of channel estimation and frequency offset estimation in OFDM systems, with different antenna configurations at both the transmitter and the receiver. This thesis presents the theoretical study of the impact of the pilot density in the performance of the channel estimation in OFDM systems and proposes several channel and frequency offset algorithms for OFDM systems with single antenna at both transmitter and receiver, with transmitter diversity and MIMO. The theoretical study results in the analytical formulation of the mean square error of a generic channel estimator for an OFDM system using dedicated pilots, distributed in the transmitted frame in two-dimensional patterns. The generic formulation is implemented for the two-dimensional LS-DFT estimator to verify the accuracy of the analytical formulation when compared with the values obtained by simulation of the discussed system. The investigated estimation algorithms take advantage of the presence of dedicated pilots present in the transmitted frames to accurately estimate the required parameters. Due to its low complexity, these algorithms are especially suited for implementation in mobile terminals with limited processing power and consumption. The performance of the proposed algorithms was evaluated by simulation of the used system, using accepted multipath mobile channel models. The comparison of its performance with the one of reference algorithms measures its validity.

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In this study, we propose a new semi-nonparametric (SNP) density model for describing the density of portfolio returns. This distribution, which we refer to as the multivariate moments expansion (MME), admits any non-Gaussian (multivariate) distribution as its basis because it is specified directly in terms of the basis density’s moments. To obtain the expansion of the Gaussian density, the MME is a reformulation of the multivariate Gram-Charlier (MGC), but the MME is much simpler and tractable than the MGC when positive transformations are used to produce well-defined densities. As an empirical application, we extend the dynamic conditional equicorrelation (DECO) model to an SNP framework using the MME. The resulting model is parameterized in a feasible manner to admit two-stage consistent estimation and it represents the DECO as well as the salient non-Gaussian features of portfolio return distributions. The in- and out-of-sample performance of a MME-DECO model of a portfolio of 10 assets demonstrate that it can be a useful tool for risk management purposes.

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In this work an adaptive modeling and spectral estimation scheme based on a dual Discrete Kalman Filtering (DKF) is proposed for speech enhancement. Both speech and noise signals are modeled by an autoregressive structure which provides an underlying time frame dependency and improves time-frequency resolution. The model parameters are arranged to obtain a combined state-space model and are also used to calculate instantaneous power spectral density estimates. The speech enhancement is performed by a dual discrete Kalman filter that simultaneously gives estimates for the models and the signals. This approach is particularly useful as a pre-processing module for parametric based speech recognition systems that rely on spectral time dependent models. The system performance has been evaluated by a set of human listeners and by spectral distances. In both cases the use of this pre-processing module has led to improved results.

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Many unit root and cointegration tests require an estimate of the spectral density function at frequency zero at some process. Kernel estimators based on weighted sums of autocovariances constructed using estimated residuals from an AR(1) regression are commonly used. However, it is known that with substantially correlated errors, the OLS estimate of the AR(1) parameter is severely biased. in this paper, we first show that this least squares bias induces a significant increase in the bias and mean-squared error of kernel-based estimators.

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Cette étude teste l’hypothèse que le remodelage osseux dans le deuxième métacarpe peut être utilisé pour estimer l’âge à la mort. Les métacarpes utilisés dans cette analyse proviennent d’un cimetière d’Ontario, incluant des individus d’origine européenne (n=63; 34 hommes; 29 femmes). Leur âge varie de 19 à 61 ans (moyenne: 41,1±11,6). L’âge était connu ou a été estimé indépendamment à partir de la morphologie générale du squelette. À partir de lames minces coupées à la mi-diaphyse, la densité de population des ostéons (OPD; ostéons/mm2 intacts et fragmentaires) a été calculée pour huit colonnes du périoste à l’endoste, deux par quadrant anatomique. Les régressions par calibration classique ont produit une série d’équation pour les estimations de l’âge pour chaque sexe, sexes combinés, et en fonction de la latéralité. La méthode utilisée diminue l’efficacité des estimations mais elle a l’avantage de réduire les biais. Quand les sexes sont combinés, l’OPD est corrélé modérément mais significativement avec l’âge (droit r2= 0,35; gauche r2=0,28). Cependant, quand les hommes et les femmes sont analysés séparément, la corrélation entre l’OPD et l’âge dans l’échantillon féminin est meilleure (droit r2=0,48; gauche r2=0,39) alors que celle des hommes est réduite (droit r2=0,29; gauche r2=0,22). Ce résultat a déjà été observé dans d’autres études, mais n’est pas expliqué. Les résultats démontrent aussi une meilleure corrélation entre l’OPD et l’âge du côté droit que du côté gauche. Tous les résultats présentés ici supportent l’hypothèse que l’OPD du métacarpe est corrélé avec l’âge effectif (c’est-à-dire connu ou estimé), les régressions de l’OPD sur l’âge (droit-gauche combinés ou séparés, sexes combinés ou séparés) étant toutes significatives.

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Ce mémoire porte sur la présentation des estimateurs de Bernstein qui sont des alternatives récentes aux différents estimateurs classiques de fonctions de répartition et de densité. Plus précisément, nous étudions leurs différentes propriétés et les comparons à celles de la fonction de répartition empirique et à celles de l'estimateur par la méthode du noyau. Nous déterminons une expression asymptotique des deux premiers moments de l'estimateur de Bernstein pour la fonction de répartition. Comme pour les estimateurs classiques, nous montrons que cet estimateur vérifie la propriété de Chung-Smirnov sous certaines conditions. Nous montrons ensuite que l'estimateur de Bernstein est meilleur que la fonction de répartition empirique en terme d'erreur quadratique moyenne. En s'intéressant au comportement asymptotique des estimateurs de Bernstein, pour un choix convenable du degré du polynôme, nous montrons que ces estimateurs sont asymptotiquement normaux. Des études numériques sur quelques distributions classiques nous permettent de confirmer que les estimateurs de Bernstein peuvent être préférables aux estimateurs classiques.

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Estimating snow mass at continental scales is difficult but important for understanding landatmosphere interactions, biogeochemical cycles and Northern latitudes’ hydrology. Remote sensing provides the only consistent global observations, but the uncertainty in measurements is poorly understood. Existing techniques for the remote sensing of snow mass are based on the Chang algorithm, which relates the absorption of Earth-emitted microwave radiation by a snow layer to the snow mass within the layer. The absorption also depends on other factors such as the snow grain size and density, which are assumed and fixed within the algorithm. We examine the assumptions, compare them to field measurements made at the NASA Cold Land Processes Experiment (CLPX) Colorado field site in 2002–3, and evaluate the consequences of deviation and variability for snow mass retrieval. The accuracy of the emission model used to devise the algorithm also has an impact on its accuracy, so we test this with the CLPX measurements of snow properties against SSM/I and AMSR-E satellite measurements.

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Accurate estimates for the fall speed of natural hydrometeors are vital if their evolution in clouds is to be understood quantitatively. In this study, laboratory measurements of the terminal velocity vt for a variety of ice particle models settling in viscous fluids, along with wind-tunnel and field measurements of ice particles settling in air, have been analyzed and compared to common methods of computing vt from the literature. It is observed that while these methods work well for a number of particle types, they fail for particles with open geometries, specifically those particles for which the area ratio Ar is small (Ar is defined as the area of the particle projected normal to the flow divided by the area of a circumscribing disc). In particular, the fall speeds of stellar and dendritic crystals, needles, open bullet rosettes, and low-density aggregates are all overestimated. These particle types are important in many cloud types: aggregates in particular often dominate snow precipitation at the ground and vertically pointing Doppler radar measurements. Based on the laboratory data, a simple modification to previous computational methods is proposed, based on the area ratio. This new method collapses the available drag data onto an approximately universal curve, and the resulting errors in the computed fall speeds relative to the tank data are less than 25% in all cases. Comparison with the (much more scattered) measurements of ice particles falling in air show strong support for this new method, with the area ratio bias apparently eliminated.