Applying semantics to grid middleware

Scheduling parallel and distributed applications efficiently onto grid environments is a difficult task and a great variety of scheduling heuristics has been developed aiming to address this issue. A successful grid resource allocation depends, among other things, on the quality of the available information about software artifacts and grid resources. In this article, we propose a semantic approach to integrate selection of equivalent resources and selection of equivalent software artifacts to improve the scheduling of resources suitable for a given set of application execution requirements. We also describe a prototype implementation of our approach based on the Integrade grid middleware and experimental results that illustrate its benefits. Copyright (C) 2009 John Wiley & Sons, Ltd.

Lightning-Induced Voltages on Overhead Lines-Application of the Extended Rusck Model

Lightning-induced overvoltages have a considerable impact on the power quality of overhead distribution and telecommunications systems, and various models have been developed for the computation of the electromagnetic transients caused by indirect strokes. The most adequate has been shown to be the one proposed by Agrawal et al.; the Rusck model can be visualized as a particular case, as both models are equivalent when the lightning channel is perpendicular to the ground plane. In this paper, an extension of the Rusck model that enables the calculation of lightning-induced transients considering flashes to nearby elevated structures and realistic line configurations is tested against data obtained from both natural lightning and scale model experiments. The latter, performed under controlled conditions, can be used also to verify the validity of other coupling models and relevant codes. The so-called Extended Rusck Model, which is shown to be sufficiently accurate, is applied to the analysis of lightning-induced voltages on lines with a shield wire and/or surge arresters. The investigation conducted indicates that the ratio between the peak values of the voltages induced by typical first and subsequent strokes can be either greater or smaller than the unity, depending on the line configuration.

On the Filtering Problem for Continuous-Time Markov Jump Linear Systems with no Observation of the Markov Chain

We consider in this paper the optimal stationary dynamic linear filtering problem for continuous-time linear systems subject to Markovian jumps in the parameters (LSMJP) and additive noise (Wiener process). It is assumed that only an output of the system is available and therefore the values of the jump parameter are not accessible. It is a well known fact that in this setting the optimal nonlinear filter is infinite dimensional, which makes the linear filtering a natural numerically, treatable choice. The goal is to design a dynamic linear filter such that the closed loop system is mean square stable and minimizes the stationary expected value of the mean square estimation error. It is shown that an explicit analytical solution to this optimal filtering problem is obtained from the stationary solution associated to a certain Riccati equation. It is also shown that the problem can be formulated using a linear matrix inequalities (LMI) approach, which can be extended to consider convex polytopic uncertainties on the parameters of the possible modes of operation of the system and on the transition rate matrix of the Markov process. As far as the authors are aware of this is the first time that this stationary filtering problem (exact and robust versions) for LSMJP with no knowledge of the Markov jump parameters is considered in the literature. Finally, we illustrate the results with an example.

Reachability of the synchronous state in a mutually connected PLL network

Second-order phase locked loops (PLLs) are devices that are able to provide synchronization between the nodes in a network even under severe quality restrictions in the signal propagation. Consequently, they are widely used in telecommunication and control. Conventional master-slave (M-S) clock-distribution systems are being, replaced by mutually connected (MC) ones due to their good potential to be used in new types of application such as wireless sensor networks, distributed computation and communication systems. Here, by using an analytical reasoning, a nonlinear algebraic system of equations is proposed to establish the existence conditions for the synchronous state in an MC PLL network. Numerical experiments confirm the analytical results and provide ideas about how the network parameters affect the reachability of the synchronous state. The phase-difference oscillation amplitudes are related to the node parameters helping to design PLL neural networks. Furthermore, estimation of the acquisition time depending on the node parameters allows the performance evaluation of time distribution systems and neural networks based on phase-locked techniques. (c) 2008 Elsevier GmbH. All rights reserved.

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.

Multiple synchronous states in static delay-free mutually connected PLL networks

In many engineering applications, the time coordination of geographically separated events is of fundamental importance, as in digital telecommunications and integrated digital circuits. Mutually connected (MC) networks are very good candidates for some new types of application, such as wireless sensor networks. This paper presents a study on the behavior of MC networks of digital phase-locked loops (DPLLs). Analytical results are derived showing that, even for static networks without delays, different synchronous states may exist for the network. An upper bound for the number of such states is also presented. Numerical simulations are used to show the following results: (i) the synchronization precision in MC DPLLs networks; (ii) the existence of synchronous states for the network does not guarantee its achievement and (iii) different synchronous states may be achieved for different initial conditions. These results are important in the neural computation context. as in this case, each synchronous state may be associated to a different analog memory information. (C) 2010 Elsevier B.V. All rights reserved.

Resource use pattern analysis for predicting resource availability in opportunistic grids

This work presents a method for predicting resource availability in opportunistic grids by means of use pattern analysis (UPA), a technique based on non-supervised learning methods. This prediction method is based on the assumption of the existence of several classes of computational resource use patterns, which can be used to predict the resource availability. Trace-driven simulations validate this basic assumptions, which also provide the parameter settings for the accurate learning of resource use patterns. Experiments made with an implementation of the UPA method show the feasibility of its use in the scheduling of grid tasks with very little overhead. The experiments also demonstrate the method`s superiority over other predictive and non-predictive methods. An adaptative prediction method is suggested to deal with the lack of training data at initialization. Further adaptative behaviour is motivated by experiments which show that, in some special environments, reliable resource use patterns may not always be detected. Copyright (C) 2009 John Wiley & Sons, Ltd.

A modified epidemiological model for computer viruses

Since the computer viruses pose a serious problem to individual and corporative computer systems, a lot of effort has been dedicated to study how to avoid their deleterious actions, trying to create anti-virus programs acting as vaccines in personal computers or in strategic network nodes. Another way to combat viruses propagation is to establish preventive policies based on the whole operation of a system that can be modeled with population models, similar to those that are used in epidemiological studies. Here, a modified version of the SIR (Susceptible-Infected-Removed) model is presented and how its parameters are related to network characteristics is explained. Then, disease-free and endemic equilibrium points are calculated, stability and bifurcation conditions are derived and some numerical simulations are shown. The relations among the model parameters in the several bifurcation conditions allow a network design minimizing viruses risks. (C) 2009 Elsevier Inc. All rights reserved.

Influence diagnostics for polyhazard models in the presence of covariates

In this paper, we present various diagnostic methods for polyhazard models. Polyhazard models are a flexible family for fitting lifetime data. Their main advantage over the single hazard models, such as the Weibull and the log-logistic models, is to include a large amount of nonmonotone hazard shapes, as bathtub and multimodal curves. Some influence methods, such as the local influence and total local influence of an individual are derived, analyzed and discussed. A discussion of the computation of the likelihood displacement as well as the normal curvature in the local influence method are presented. Finally, an example with real data is given for illustration.

General results for the beta-modified Weibull distribution

We study in detail the so-called beta-modified Weibull distribution, motivated by the wide use of the Weibull distribution in practice, and also for the fact that the generalization provides a continuous crossover towards cases with different shapes. The new distribution is important since it contains as special sub-models some widely-known distributions, such as the generalized modified Weibull, beta Weibull, exponentiated Weibull, beta exponential, modified Weibull and Weibull distributions, among several others. It also provides more flexibility to analyse complex real data. Various mathematical properties of this distribution are derived, including its moments and moment generating function. We examine the asymptotic distributions of the extreme values. Explicit expressions are also derived for the chf, mean deviations, Bonferroni and Lorenz curves, reliability and entropies. The estimation of parameters is approached by two methods: moments and maximum likelihood. We compare by simulation the performances of the estimates from these methods. We obtain the expected information matrix. Two applications are presented to illustrate the proposed distribution.

The exponentiated generalized gamma distribution with application to lifetime data

A four-parameter extension of the generalized gamma distribution capable of modelling a bathtub-shaped hazard rate function is defined and studied. The beauty and importance of this distribution lies in its ability to model monotone and non-monotone failure rate functions, which are quite common in lifetime data analysis and reliability. The new distribution has a number of well-known lifetime special sub-models, such as the exponentiated Weibull, exponentiated generalized half-normal, exponentiated gamma and generalized Rayleigh, among others. We derive two infinite sum representations for its moments. We calculate the density of the order statistics and two expansions for their moments. The method of maximum likelihood is used for estimating the model parameters and the observed information matrix is obtained. Finally, a real data set from the medical area is analysed.

A Log-Linear Regression Model for the Beta-Weibull Distribution

We introduce the log-beta Weibull regression model based on the beta Weibull distribution (Famoye et al., 2005; Lee et al., 2007). We derive expansions for the moment generating function which do not depend on complicated functions. The new regression model represents a parametric family of models that includes as sub-models several widely known regression models that can be applied to censored survival data. We employ a frequentist analysis, a jackknife estimator, and a parametric bootstrap for the parameters of the proposed model. We derive the appropriate matrices for assessing local influences on the parameter estimates under different perturbation schemes and present some ways to assess global influences. Further, for different parameter settings, sample sizes, and censoring percentages, several simulations are performed. In addition, the empirical distribution of some modified residuals are displayed and compared with the standard normal distribution. These studies suggest that the residual analysis usually performed in normal linear regression models can be extended to a modified deviance residual in the proposed regression model applied to censored data. We define martingale and deviance residuals to evaluate the model assumptions. The extended regression model is very useful for the analysis of real data and could give more realistic fits than other special regression models.

Dehydromonocrotaline induces cyclosporine A-insensitive mitochondrial permeability transition/cytochrome c release

Monocrotaline (MCT) is a pyrrolizidine alkaloid present in plants of the genus Crotalaria that causes cytotoxicity and genotoxicity in animals and humans. It is well established that the toxicity of MCT results from its hepatic bioactivation to dehydromonocrotaline (DHM), an alkylating agent, but the exact mechanism of action remains unknown. In a previous study, we demonstrated DHM`s inhibition of mitochondrial NADH-dehydrogenase activity at micromolar concentrations, which is an effect associated with a significant reduction in ATP synthesis. As a follow-up study, we have evaluated the ability of DHM to induce mitochondrial permeability transition (MPT) and its associated processes in isolated rat liver mitochondria. In the presence of 10 mu M Ca(2+), DHM (50-250 mu M) elicited MPT in a concentration-dependent, but cyclosporine A-independent manner, as assessed by mitochondrial swelling, which is associated with mitochondrial Ca(2+) efflux and cytochrome c release. DHM (50-250 mu M) did not cause hydrogen peroxide accumulation but did deplete endogenous glutathione and NAD(P)H, while oxidizing protein thiol groups. These results potentially indicate the involvement of mitochondria, via apoptosis, in the well-documented cytotoxicity of monocrotaline. (C) 2009 Elsevier Ltd. All rights reserved.

Habitual physical activity and physical activity intensity: their relation to body composition in 5.0-10.5 year old children

Background: Concerns of a decrease in physical activity levels (PALs) of children and a concurrent increase in childhood obesity exist worldwide. The exact relation between these two parameters however has as yet to be fully defined in children. Objective: This study examined the relation in 47 children, aged 5–10.5 y (mean age 8.4plusminus0.9 y) between habitual physical activity, minutes spent in moderate, vigorous and hard intensity activity and body composition parameters. Design: Total energy expenditure (TEE) was calculated using the doubly labelled water technique and basal metabolic rate (BMR) was predicted from Schofield's equations. PAL was determined by PAL=TEE/BMR. Time spent in moderate, vigorous and hard intensity activity was determined by accelerometry, using the Tritrac-R3D. Body fatness and body mass index (BMI) were used as the two measures of body composition. Results: Body fat and BMI were significantly inversely correlated with PAL (r=-0.43, P=0.002 and r=-0.45, P=0.001). Times spent in vigorous activity and hard activity were significantly correlated to percentage body fat (r=-0.44, P=0.004 and r=-0.39, P=0.014), but not BMI. Children who were in the top tertiles for both vigorous activity and hard activity had significantly lower body fat percentages than those in the middle and lowest tertiles. Moderate intensity activity was not correlated with measures of body composition. Conclusions: As well as showing a significant relation between PAL and body composition, these data intimate that there may be a threshold of intensity of physical activity that is influential on body fatness. In light of world trends showing increasing childhood obesity, this study supports the need to further investigate the importance of physical activity for children.

Dissolution of a solid sphere in an unbounded, stagnant liquid

An exact analytical solution is obtained for the transient dissolution of solid spheres in a diffusion-controlled environment. This result provides a useful reference point for drug testing in humans. The dimensionless solution is expressed in terms of a single parameter, which accounts for solubility, bulk flow, and stagnant fluid composition. A simple, explicit and exact expression was found to predict time-to-complete dissolution (TCD). An approximate solution was also found which tracks the exact case for low solubility conditions.