990 resultados para Local special collections
Resumo:
The dynamic plastic response of a simply supported circular plate is analysed. Emphasis is given to the plate behaviour after it has broken free from the supports due to a local material failure. The theoretical rigid plastic analysis predicts various features of the response such as the time to failure, residual kinetic energy and the critical velocity at failure. The residual kinetic energy of the plate could be significant enough to cause secondary impact damage. It is shown that the shape of the plate changes after breaking free from the supports, which is important for forensic investigations. The solution for various cases were proven to be exact in the context of the upper and lower bounds theorems of the theory of plasticity. (C) 2009 Elsevier Ltd. All rights reserved.
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In this work, a wide analysis of local search multiuser detection (LS-MUD) for direct sequence/code division multiple access (DS/CDMA) systems under multipath channels is carried out considering the performance-complexity trade-off. It is verified the robustness of the LS-MUD to variations in loading, E(b)/N(0), near-far effect, number of fingers of the Rake receiver and errors in the channel coefficients estimates. A compared analysis of the bit error rate (BER) and complexity trade-off is accomplished among LS, genetic algorithm (GA) and particle swarm optimization (PSO). Based on the deterministic behavior of the LS algorithm, it is also proposed simplifications over the cost function calculation, obtaining more efficient algorithms (simplified and combined LS-MUD versions) and creating new perspectives for the MUD implementation. The computational complexity is expressed in terms of the number of operations in order to converge. Our conclusion pointed out that the simplified LS (s-LS) method is always more efficient, independent of the system conditions, achieving a better performance with a lower complexity than the others heuristics detectors. Associated to this, the deterministic strategy and absence of input parameters made the s-LS algorithm the most appropriate for the MUD problem. (C) 2008 Elsevier GmbH. All rights reserved.
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The recent claim that the exit probability (EP) of a slightly modified version of the Sznadj model is a continuous function of the initial magnetization is questioned. This result has been obtained analytically and confirmed by Monte Carlo simulations, simultaneously and independently by two different groups (EPL, 82 (2008) 18006; 18007). It stands at odds with an earlier result which yielded a step function for the EP (Europhys. Lett., 70 (2005) 705). The dispute is investigated by proving that the continuous shape of the EP is a direct outcome of a mean-field treatment for the analytical result. As such, it is most likely to be caused by finite-size effects in the simulations. The improbable alternative would be a signature of the irrelevance of fluctuations in this system. Indeed, evidence is provided in support of the stepwise shape as going beyond the mean-field level. These findings yield new insight in the physics of one-dimensional systems with respect to the validity of a true equilibrium state when using solely local update rules. The suitability and the significance to perform numerical simulations in those cases is discussed. To conclude, a great deal of caution is required when applying updates rules to describe any system especially social systems. Copyright (C) EPLA, 2011
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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.
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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.
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Purpose Among environmental factors governing innumerous processes that are active in estuarine environments, those of edaphic character have received special attention in recent studies. With the objectives of determining the spatial patterns of soil attributes and components across different mangrove forest landscapes and obtaining additional information on the cause-effect relationships between these variables and position within the estuary, we analyzed several soil attributes in 31 mangrove soil profiles from the state of So Paulo (Guaruja, Brazil). Materials and methods Soil samples were collected at low tide along two transects within the CrumahA(0) mangrove forest. Samples were analyzed to determine pH, Eh, salinity, and the percentages of sand, silt, clay, total organic carbon (TOC), and total S. Mineralogy of the clay fraction (< 2 mm) was also studied by X-ray diffraction analysis, and partitioning of solid-phase Fe was performed by sequential extraction. Results and discussion The results obtained indicate important differences in soil composition at different depths and landscape positions, causing variations in physicochemical parameters, clay mineralogy, TOC contents, and iron geochemistry. The results also indicate that physicochemical conditions may vary in terms of different local microtopographies. Soil salinity was determined by relative position in relation to flood tide and transition areas with highlands. The proportions of TOC and total S are conditioned by the sedimentation of organic matter derived from vegetation and by the prevailing redox conditions, which clearly favored intense sulfate reduction in the soils (similar to 80% of the total Fe is Fe-pyrite). Particle-size distribution is conditioned by erosive/deposition processes (present and past) and probably by the positioning of ancient and reworked sandy ridges. The existing physicochemical conditions appear to contribute to the synthesis (smectite) and transformation (kaolinite) of clay minerals. Conclusions The results demonstrate that the position of soils in the estuary greatly affects soil attributes. Differences occur even at small scales (meters), indicating that both edaphic (soil classification, soil mineralogy, and soil genesis) and environmental (contamination and carbon stock) studies should take such variability into account.
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Few marine hybrid zones have been studied extensively, the major exception being the hybrid zone between the mussels Mytilus edulis and M. galloprovincialis in southwestern Europe. Here, we focus on two less studied hybrid zones that also involve Mytilus spp.; M. edulis and M. trossulus are sympatric and hybridize on both western and eastern coasts of the Atlantic Ocean. We review the dynamics of hybridization in these two hybrid zones and evaluate the role of local adaptation for maintaining species boundaries. In Scandinavia, hybridization and gene introgression is so extensive that no individuals with pure M. trossulus genotypes have been found. However, M. trossulus alleles are maintained at high frequencies in the extremely low salinity Baltic Sea for some allozyme genes. A synthesis of reciprocal transplantation experiments between different salinity regimes shows that unlinked Gpi and Pgm alleles change frequency following transplantation, such that post-transplantation allelic composition resembles native populations found in the same salinity. These experiments provide strong evidence for salinity adaptation at Gpi and Pgm (or genes linked to them). In the Canadian Maritimes, pure M. edulis and M. trossulus individuals are abundant, and limited data suggest that M. edulis predominates in low salinity and sheltered conditions, whereas M. trossulus are more abundant on the wave-exposed open coasts. We suggest that these conflicting patterns of species segregation are, in part, caused by local adaptation of Scandinavian M. trossulus to the extremely low salinity Baltic Sea environment.
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We show that quantum mechanics predicts a contradiction with local hidden variable theories for photon number measurements which have limited resolving power, to the point of imposing an uncertainty in the photon number result which is macroscopic in absolute terms. We show how this can be interpreted as a failure of a new premise, macroscopic local realism.
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Data mining is the process to identify valid, implicit, previously unknown, potentially useful and understandable information from large databases. It is an important step in the process of knowledge discovery in databases, (Olaru & Wehenkel, 1999). In a data mining process, input data can be structured, seme-structured, or unstructured. Data can be in text, categorical or numerical values. One of the important characteristics of data mining is its ability to deal data with large volume, distributed, time variant, noisy, and high dimensionality. A large number of data mining algorithms have been developed for different applications. For example, association rules mining can be useful for market basket problems, clustering algorithms can be used to discover trends in unsupervised learning problems, classification algorithms can be applied in decision-making problems, and sequential and time series mining algorithms can be used in predicting events, fault detection, and other supervised learning problems (Vapnik, 1999). Classification is among the most important tasks in the data mining, particularly for data mining applications into engineering fields. Together with regression, classification is mainly for predictive modelling. So far, there have been a number of classification algorithms in practice. According to (Sebastiani, 2002), the main classification algorithms can be categorized as: decision tree and rule based approach such as C4.5 (Quinlan, 1996); probability methods such as Bayesian classifier (Lewis, 1998); on-line methods such as Winnow (Littlestone, 1988) and CVFDT (Hulten 2001), neural networks methods (Rumelhart, Hinton & Wiliams, 1986); example-based methods such as k-nearest neighbors (Duda & Hart, 1973), and SVM (Cortes & Vapnik, 1995). Other important techniques for classification tasks include Associative Classification (Liu et al, 1998) and Ensemble Classification (Tumer, 1996).
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OctVCE is a cartesian cell CFD code produced especially for numerical simulations of shock and blast wave interactions with complex geometries, in particular, from explosions. Virtual Cell Embedding (VCE) was chosen as its cartesian cell kernel for its simplicity and sufficiency for practical engineering design problems. The code uses a finite-volume formulation of the unsteady Euler equations with a second order explicit Runge-Kutta Godonov (MUSCL) scheme. Gradients are calculated using a least-squares method with a minmod limiter. Flux solvers used are AUSM, AUSMDV and EFM. No fluid-structure coupling or chemical reactions are allowed, but gas models can be perfect gas and JWL or JWLB for the explosive products. This report also describes the code’s ‘octree’ mesh adaptive capability and point-inclusion query procedures for the VCE geometry engine. Finally, some space will also be devoted to describing code parallelization using the shared-memory OpenMP paradigm. The user manual to the code is to be found in the companion report 2007/13.