Jointly multi-user detection and channel estimation with genetic algorithm

This work aims at proposing the use of the evolutionary computation methodology in order to jointly solve the multiuser channel estimation (MuChE) and detection problems at its maximum-likelihood, both related to the direct sequence code division multiple access (DS/CDMA). The effectiveness of the proposed heuristic approach is proven by comparing performance and complexity merit figures with that obtained by traditional methods found in literature. Simulation results considering genetic algorithm (GA) applied to multipath, DS/CDMA and MuChE and multi-user detection (MuD) show that the proposed genetic algorithm multi-user channel estimation (GAMuChE) yields a normalized mean square error estimation (nMSE) inferior to 11%, under slowly varying multipath fading channels, large range of Doppler frequencies and medium system load, it exhibits lower complexity when compared to both maximum likelihood multi-user channel estimation (MLMuChE) and gradient descent method (GrdDsc). A near-optimum multi-user detector (MuD) based on the genetic algorithm (GAMuD), also proposed in this work, provides a significant reduction in the computational complexity when compared to the optimum multi-user detector (OMuD). In addition, the complexity of the GAMuChE and GAMuD algorithms were (jointly) analyzed in terms of number of operations necessary to reach the convergence, and compared to other jointly MuChE and MuD strategies. The joint GAMuChE-GAMuD scheme can be regarded as a promising alternative for implementing third-generation (3G) and fourth-generation (4G) wireless systems in the near future. Copyright (C) 2010 John Wiley & Sons, Ltd.

Singular Perturbation for the Discounted Continuous Control of Piecewise Deterministic Markov Processes

This paper deals with the expected discounted continuous control of piecewise deterministic Markov processes (PDMP`s) using a singular perturbation approach for dealing with rapidly oscillating parameters. The state space of the PDMP is written as the product of a finite set and a subset of the Euclidean space a""e (n) . The discrete part of the state, called the regime, characterizes the mode of operation of the physical system under consideration, and is supposed to have a fast (associated to a small parameter epsilon > 0) and a slow behavior. By using a similar approach as developed in Yin and Zhang (Continuous-Time Markov Chains and Applications: A Singular Perturbation Approach, Applications of Mathematics, vol. 37, Springer, New York, 1998, Chaps. 1 and 3) the idea in this paper is to reduce the number of regimes by considering an averaged model in which the regimes within the same class are aggregated through the quasi-stationary distribution so that the different states in this class are replaced by a single one. The main goal is to show that the value function of the control problem for the system driven by the perturbed Markov chain converges to the value function of this limit control problem as epsilon goes to zero. This convergence is obtained by, roughly speaking, showing that the infimum and supremum limits of the value functions satisfy two optimality inequalities as epsilon goes to zero. This enables us to show the result by invoking a uniqueness argument, without needing any kind of Lipschitz continuity condition.

Linear minimum mean square filter for discrete-time linear systems with Markov jumps and multiplicative noises

In this paper we obtain the linear minimum mean square estimator (LMMSE) for discrete-time linear systems subject to state and measurement multiplicative noises and Markov jumps on the parameters. It is assumed that the Markov chain is not available. By using geometric arguments we obtain a Kalman type filter conveniently implementable in a recurrence form. The stationary case is also studied and a proof for the convergence of the error covariance matrix of the LMMSE to a stationary value under the assumption of mean square stability of the system and ergodicity of the associated Markov chain is obtained. It is shown that there exists a unique positive semi-definite solution for the stationary Riccati-like filter equation and, moreover, this solution is the limit of the error covariance matrix of the LMMSE. The advantage of this scheme is that it is very easy to implement and all calculations can be performed offline. (c) 2011 Elsevier Ltd. All rights reserved.

The Poisson-exponential lifetime distribution

In this paper we proposed a new two-parameters lifetime distribution with increasing failure rate. The new distribution arises on a latent complementary risk problem base. The properties of the proposed distribution are discussed, including a formal proof of its probability density function and explicit algebraic formulae for its reliability and failure rate functions, quantiles and moments, including the mean and variance. A simple EM-type algorithm for iteratively computing maximum likelihood estimates is presented. The Fisher information matrix is derived analytically in order to obtaining the asymptotic covariance matrix. The methodology is illustrated on a real data set. (C) 2010 Elsevier B.V. All rights reserved.

Particle-Image Velocimetry Study of a Pediatric Ventricular Assist Device

Particle-image velocimetry (PIV) was used to visualize the flow within an optically transparent pediatric ventricular assist device (PVAD) under development in our laboratory The device studied is a diaphragm type pulsatile pump with an ejection volume of 30 ml per beating cycle intended for temporary cardiac assistance as a bridge to transplantation or recovery in children. Of particular interest was the identification of flow patterns, including regions of stagnation and/or strong turbulence that often promote thrombus formation and hemolysis, which can degrade the usefulness of such devices. For this purpose, phase-locked PIV measurements were performed in planes parallel to the diaphram that drives the flow in the device. The test fluid was seeded with 10 Am polystyrene spheres, and the motion of these particles was used to determine the instantaneous flow velocity distribution in the illumination plane. These measurements revealed that flow velocities up to 1.0 m/s can occur within the PVAD. Phase-averaged velocity fields revealed the fixed vortices that drive the bulk flow within the device, though significant cycle-to-cycle variability was also quite apparent in the instantaneous velocity distributions, most notably during the filling phase. This cycle-to-cycle variability can generate strong turbulence that may contribute to greater hemolysis. Stagnation regions have also been observed between the input and output branches of the prototype, which can increase the likelihood of thrombus formation. [DOI: 10.1115/1.4001252]

Variability on red blood cell transfusion practices among Brazilian neonatal intensive care units

BACKGROUND: Guidelines for red blood cell (RBC) transfusions exist; however, transfusion practices vary among centers. This study aimed to analyze transfusion practices and the impact of patients and institutional characteristics on the indications of RBC transfusions in preterm infants. STUDY DESIGN AND METHODS: RBC transfusion practices were investigated in a multicenter prospective cohort of preterm infants with a birth weight of less than 1500 g born at eight public university neonatal intensive care units of the Brazilian Network on Neonatal Research. Variables associated with any RBC transfusions were analyzed by logistic regression analysis. RESULTS: Of 952 very-low-birth-weight infants, 532 (55.9%) received at least one RBC transfusion. The percentages of transfused neonates were 48.9, 54.5, 56.0, 61.2, 56.3, 47.8, 75.4, and 44.7%, respectively, for Centers 1 through 8. The number of transfusions during the first 28 days of life was higher in Center 4 and 7 than in other centers. After 28 days, the number of transfusions decreased, except for Center 7. Multivariate logistic regression analysis showed higher likelihood of transfusion in infants with late onset sepsis (odds ratio [OR], 2.8; 95% confidence interval [CI], 1.8-4.4), intraventricular hemorrhage (OR, 9.4; 95% CI, 3.3-26.8), intubation at birth (OR, 1.7; 95% CI, 1.0-2.8), need for umbilical catheter (OR, 2.4; 95% CI, 1.3-4.4), days on mechanical ventilation (OR, 1.1; 95% CI, 1.0-1.2), oxygen therapy (OR, 1.1; 95% CI, 1.0-1.1), parenteral nutrition (OR, 1.1; 95% CI, 1.0-1.1), and birth center (p < 0.001). CONCLUSIONS: The need of RBC transfusions in very-low-birth-weight preterm infants was associated with clinical conditions and birth center. The distribution of the number of transfusions during hospital stay may be used as a measure of neonatal care quality.

A new genus and species of rodent from the Brazilian Atlantic Forest (Rodentia: Cricetidae: Sigmodontinae: Oryzomyini), with comments on oryzomyine biogeography

We describe in this paper a new genus and species of cricetid rodent from the Atlantic Forest of Brazil, one of the most endangered eco-regions of the world. The new form displays some but not all synapomorphies of the tribe Oryzomyini, but a suite of unique characteristics is also observed. This new forest rat possesses anatomical characteristics of arboreal taxa, such as very developed plantar pads, but was collected almost exclusively in pitfall traps. Phylogenetic analyses of morphological (integument, soft tissue, cranial, and dental characters) and molecular [nuclear - Interphotoreceptor retinoid binding protein (Irbp) - and mitochondrial - cytochrome b - genes] datasets using maximum likelihood and cladistic parsimony approaches corroborate the inclusion of the new taxon within oryzomyines. The analyses also place the new form as sister species to Eremoryzomys polius, an Andean rat endemic to the Maranon valley. This biogeographical pattern is unusual amongst small terrestrial vertebrates, as a review of the literature points to few other similar examples of Andean-Atlantic Forest pairings, in hylid frogs, Pionus parrots, and other sigmodontine rodents. (C) 2011 The Linnean Society of London, Zoological Journal of the Linnean Society, 2011, 161, 357-390. doi:10.1111/j.1096-3642.2010.00643.x

The generalized inverse Weibull distribution

The inverse Weibull distribution has the ability to model failure rates which are quite common in reliability and biological studies. A three-parameter generalized inverse Weibull distribution with decreasing and unimodal failure rate is introduced and studied. We provide a comprehensive treatment of the mathematical properties of the new distribution including expressions for the moment generating function and the rth generalized moment. The mixture model of two generalized inverse Weibull distributions is investigated. The identifiability property of the mixture model is demonstrated. For the first time, we propose a location-scale regression model based on the log-generalized inverse Weibull distribution for modeling lifetime data. In addition, we develop some diagnostic tools for sensitivity analysis. Two applications of real data are given to illustrate the potentiality of the proposed regression model.

A frailty modeling approach for parental effects in animal breeding

Survival models involving frailties are commonly applied in studies where correlated event time data arise due to natural or artificial clustering. In this paper we present an application of such models in the animal breeding field. Specifically, a mixed survival model with a multivariate correlated frailty term is proposed for the analysis of data from over 3611 Brazilian Nellore cattle. The primary aim is to evaluate parental genetic effects on the trait length in days that their progeny need to gain a commercially specified standard weight gain. This trait is not measured directly but can be estimated from growth data. Results point to the importance of genetic effects and suggest that these models constitute a valuable data analysis tool for beef cattle breeding.

The Kumaraswamy Weibull distribution with application to failure data

For the first time, we introduce and study some mathematical properties of the Kumaraswamy Weibull distribution that is a quite flexible model in analyzing positive data. It contains as special sub-models the exponentiated Weibull, exponentiated Rayleigh, exponentiated exponential, Weibull and also the new Kumaraswamy exponential distribution. We provide explicit expressions for the moments and moment generating function. We examine the asymptotic distributions of the extreme values. Explicit expressions are derived for the mean deviations, Bonferroni and Lorenz curves, reliability and Renyi entropy. The moments of the order statistics are calculated. We also discuss the estimation of the parameters by maximum likelihood. We obtain the expected information matrix. We provide applications involving two real data sets on failure times. Finally, some multivariate generalizations of the Kumaraswamy Weibull distribution are discussed. (C) 2010 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.

The beta modified Weibull distribution

A five-parameter distribution so-called the beta modified Weibull distribution is defined and studied. The new distribution contains, as special submodels, several important distributions discussed in the literature, such as the generalized modified Weibull, beta Weibull, exponentiated Weibull, beta exponential, modified Weibull and Weibull distributions, among others. The new distribution can be used effectively in the analysis of survival data since it accommodates monotone, unimodal and bathtub-shaped hazard functions. We derive the moments and examine the order statistics and their moments. We propose the method of maximum likelihood for estimating the model parameters and obtain the observed information matrix. A real data set is used to illustrate the importance and flexibility of the new distribution.

A log-extended Weibull regression model

A bathtub-shaped failure rate function is very useful in survival analysis and reliability studies. The well-known lifetime distributions do not have this property. For the first time, we propose a location-scale regression model based on the logarithm of an extended Weibull distribution which has the ability to deal with bathtub-shaped failure rate functions. We use the method of maximum likelihood to estimate the model parameters and some inferential procedures are presented. We reanalyze a real data set under the new model and the log-modified Weibull regression model. We perform a model check based on martingale-type residuals and generated envelopes and the statistics AIC and BIC to select appropriate models. (C) 2009 Elsevier B.V. All rights reserved.

The generalized log-gamma mixture model with covariates: local influence and residual analysis

In a sample of censored survival times, the presence of an immune proportion of individuals who are not subject to death, failure or relapse, may be indicated by a relatively high number of individuals with large censored survival times. In this paper the generalized log-gamma model is modified for the possibility that long-term survivors may be present in the data. The model attempts to separately estimate the effects of covariates on the surviving fraction, that is, the proportion of the population for which the event never occurs. The logistic function is used for the regression model of the surviving fraction. Inference for the model parameters is considered via maximum likelihood. Some influence methods, such as the local influence and total local influence of an individual are derived, analyzed and discussed. Finally, a data set from the medical area is analyzed under the log-gamma generalized mixture model. A residual analysis is performed in order to select an appropriate model.

Different Approaches for Modeling Grouped Survival Data: A Mango Tree Study

Interval-censored survival data, in which the event of interest is not observed exactly but is only known to occur within some time interval, occur very frequently. In some situations, event times might be censored into different, possibly overlapping intervals of variable widths; however, in other situations, information is available for all units at the same observed visit time. In the latter cases, interval-censored data are termed grouped survival data. Here we present alternative approaches for analyzing interval-censored data. We illustrate these techniques using a survival data set involving mango tree lifetimes. This study is an example of grouped survival data.

A generalized modified Weibull distribution for lifetime modeling

A four parameter generalization of the Weibull distribution capable of modeling a bathtub-shaped hazard rate function is defined and studied. The beauty and importance of this distribution lies in its ability to model monotone as well as non-monotone failure rates, which are quite common in lifetime problems and reliability. The new distribution has a number of well-known lifetime special sub-models, such as the Weibull, extreme value, exponentiated Weibull, generalized Rayleigh and modified Weibull distributions, among others. We derive two infinite sum representations for its moments. The density of the order statistics is obtained. The method of maximum likelihood is used for estimating the model parameters. Also, the observed information matrix is obtained. Two applications are presented to illustrate the proposed distribution. (C) 2008 Elsevier B.V. All rights reserved.