983 resultados para Random Variable
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Site-specific geotechnical data are always random and variable in space. In the present study, a procedure for quantifying the variability in geotechnical characterization and design parameters is discussed using the site-specific cone tip resistance data (qc) obtained from static cone penetration test (SCPT). The parameters for the spatial variability modeling of geotechnical parameters i.e. (i) existing trend function in the in situ qc data; (ii) second moment statistics i.e. analysis of mean, variance, and auto-correlation structure of the soil strength and stiffness parameters; and (iii) inputs from the spatial correlation analysis, are utilized in the numerical modeling procedures using the finite difference numerical code FLAC 5.0. The influence of consideration of spatially variable soil parameters on the reliability-based geotechnical deign is studied for the two cases i.e. (a) bearing capacity analysis of a shallow foundation resting on a clayey soil, and (b) analysis of stability and deformation pattern of a cohesive-frictional soil slope. The study highlights the procedure for conducting a site-specific study using field test data such as SCPT in geotechnical analysis and demonstrates that a few additional computations involving soil variability provide a better insight into the role of variability in designs.
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First, the non-linear response of a gyrostabilized platform to a small constant input torque is analyzed in respect to the effect of the time delay (inherent or deliberately introduced) in the correction torque supplied by the servomotor, which itself may be non-linear to a certain extent. The equation of motion of the platform system is a third order nonlinear non-homogeneous differential equation. An approximate analytical method of solution of this equation is utilized. The value of the delay at which the platform response becomes unstable has been calculated by using this approximate analytical method. The procedure is illustrated by means of a numerical example. Second, the non-linear response of the platform to a random input has been obtained. The effects of several types of non-linearity on reducing the level of the mean square response have been investigated, by applying the technique of equivalent linearization and solving the resulting integral equations by using laguerre or Gaussian integration techniques. The mean square responses to white noise and band limited white noise, for various values of the non-linear parameter and for different types of non-linearity function, have been obtained. For positive values of the non-linear parameter the levels of the non-linear mean square responses to both white noise and band-limited white noise are low as compared to the linear mean square response. For negative values of the non-linear parameter the level of the non-linear mean square response at first increases slowly with increasing values of the non-linear parameter and then suddenly jumps to a high level, at a certain value of the non-linearity parameter.
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In [8], we recently presented two computationally efficient algorithms named B-RED and P-RED for random early detection. In this letter, we present the mathematical proof of convergence of these algorithms under general conditions to local minima.
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Multimetric ecological condition assessment has become an important biodiversity management tool. This study was the first to examine the reliability of these ecological surrogates across variable environments, and the implications for surrogate efficacy. It was demonstrated that through strategic application and design of the multimetric ecological condition index, the effects of environmental gradients and disturbance regimes can be mitigated, and that ecological condition assessment may serve as a scientifically rigorous approach for conservation planning.
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Geometric and structural constraints greatly restrict the selection of folds adapted by protein backbones, and yet, folded proteins show an astounding diversity in functionality. For structure to have any bearing on function, it is thus imperative that, apart from the protein backbone, other tunable degrees of freedom be accountable. Here, we focus on side-chain interactions, which non-covalently link amino acids in folded proteins to form a network structure. At a coarse-grained level, we show that the network conforms remarkably well to realizations of random graphs and displays associated percolation behavior. Thus, within the rigid framework of the protein backbone that restricts the structure space, the side-chain interactions exhibit an element of randomness, which account for the functional flexibility and diversity shown by proteins. However, at a finer level, the network exhibits deviations from these random graphs which, as we demonstrate for a few specific examples, reflect the intrinsic uniqueness in the structure and stability, and perhaps specificity in the functioning of biological proteins.
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Crystal structure determination at room temperature [292 (2) K] of racemic 1,1'-binaphthalene-2,2'-diyl diethyl bis(carbonate), C26H22O6, showed that one of the terminal carbon-carbon bond lengths is very short [Csp(3)-Csp(3) = 1.327 (6) angstrom]. The reason for such a short bond length has been analysed by collecting data sets on the same crystal at 393, 150 and 90 K. The values of the corrected bond lengths clearly suggest that the shortening is mainly due to positional disorder at two sites, with minor perturbations arising as a result of thermal vibrations. The positional disorder has been resolved in the analysis of the 90 K data following the changes in the unit-cell parameters for the data sets at 150 and 90 K, which appear to be an artifact of a near centre of symmetry relationship between the two independent molecules in the space group P (1) over bar at these temperatures. Indeed, the unit cell at low temperature (150 and 90 K) is a supercell of the room-temperature unit cell.
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Security in a mobile communication environment is always a matter for concern, even after deploying many security techniques at device, network, and application levels. The end-to-end security for mobile applications can be made robust by developing dynamic schemes at application level which makes use of the existing security techniques varying in terms of space, time, and attacks complexities. In this paper we present a security techniques selection scheme for mobile transactions, called the Transactions-Based Security Scheme (TBSS). The TBSS uses intelligence to study, and analyzes the security implications of transactions under execution based on certain criterion such as user behaviors, transaction sensitivity levels, and credibility factors computed over the previous transactions by the users, network vulnerability, and device characteristics. The TBSS identifies a suitable level of security techniques from the repository, which consists of symmetric, and asymmetric types of security algorithms arranged in three complexity levels, covering various encryption/decryption techniques, digital signature schemes, andhashing techniques. From this identified level, one of the techniques is deployed randomly. The results shows that, there is a considerable reduction in security cost compared to static schemes, which employ pre-fixed security techniques to secure the transactions data.
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We deal with a single conservation law with discontinuous convex-concave type fluxes which arise while considering sign changing flux coefficients. The main difficulty is that a weak solution may not exist as the Rankine-Hugoniot condition at the interface may not be satisfied for certain choice of the initial data. We develop the concept of generalized entropy solutions for such equations by replacing the Rankine-Hugoniot condition by a generalized Rankine-Hugoniot condition. The uniqueness of solutions is shown by proving that the generalized entropy solutions form a contractive semi-group in L-1. Existence follows by showing that a Godunov type finite difference scheme converges to the generalized entropy solution. The scheme is based on solutions of the associated Riemann problem and is neither consistent nor conservative. The analysis developed here enables to treat the cases of fluxes having at most one extrema in the domain of definition completely. Numerical results reporting the performance of the scheme are presented. (C) 2006 Elsevier B.V. All rights reserved.
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Randomness in the source condition other than the heterogeneity in the system parameters can also be a major source of uncertainty in the concentration field. Hence, a more general form of the problem formulation is necessary to consider randomness in both source condition and system parameters. When the source varies with time, the unsteady problem, can be solved using the unit response function. In the case of random system parameters, the response function becomes a random function and depends on the randomness in the system parameters. In the present study, the source is modelled as a random discrete process with either a fixed interval or a random interval (the Poisson process). In this study, an attempt is made to assess the relative effects of various types of source uncertainties on the probabilistic behaviour of the concentration in a porous medium while the system parameters are also modelled as random fields. Analytical expressions of mean and covariance of concentration due to random discrete source are derived in terms of mean and covariance of unit response function. The probabilistic behaviour of the random response function is obtained by using a perturbation-based stochastic finite element method (SFEM), which performs well for mild heterogeneity. The proposed method is applied for analysing both the 1-D as well as the 3-D solute transport problems. The results obtained with SFEM are compared with the Monte Carlo simulation for 1-D problems.
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Phase-singular solid solutions of La0.6Sr0.4Mn1-yMeyO3 (0 <= y <= 0.3) [Me=Li1+, Mg2+, Al3+, Ti4+, Nb5+, Mo6+ or W6+] [LSMey] perovskite of rhombohedral symmetry (space group: R (3) over barc) have been prepared wherein the valence of the diamagnetic substituent at Mn site ranged from 1 to 6. With increasing y-content in LSMey, the metal-insulator (TM-I) transition in resistivity-temperature rho(T) curves shifted to low temperatures. The magnetization studies M(H) as well as the M(T) indicated two groups for LSMey. (1) Group A with Me=Mg, Al, Ti, or Nb which are paramagnetic insulators (PIs) at room temperature with low values of M (< 0.5 mu(B)/Mn); the magnetic transition [ferromagnetic insulator (FMI)-PI] temperature (T-C) shifts to low temperatures and nearly coincides with that of TM-I and the maximum magnetoresistance (MR) of similar to 50% prevails near T-C (approximate to TM-I). (2) Group-B samples with Me=Li, Mo, or W which are FMIs with M-s=3.3-3.58 mu(B)/Mn and marginal reduction in T-C similar to 350 K as compared to the undoped LSMO (T-C similar to 378 K). The latter samples show large temperature differences Delta T=T-c-TM-I, reaching up to similar to 288 K. The maximum MR (similar to 60%) prevails at low temperatures corresponding to the M-I transition TM-I rather than around T-C. High resolution lattice images as well as microscopy analysis revealed the prevalence of inhomogeneous phase mixtures of randomly distributed charge ordered-insulating (COI) bistripes (similar to 3-5 nm width) within FMI charge-disordered regions, yet maintaining crystallographically single phase with no secondary precipitate formation. The averaged ionic radius < r(B)>, valency, or charge/radius ratio < CRR > cannot be correlated with that of large Delta T; hence cannot be used to parametrize the discrepancy between T-C and TM-I. The M-I transition is controlled by the charge conduction within the electronically heterogeneous mixtures (COI bistripes+FMI charge disordered); large MR at TM-I suggests that the spin-ordered FM-insulating regions assist the charge transport, whereas the T-C is associated with the bulk spin ordered regions corresponding to the FMI phase of higher volume fraction of which anchors the T-C to higher temperatures. The present analysis showed that the double-exchange model alone cannot account for the wide bifurcation of the magnetic and electric transitions, contributions from the charge as well as lattice degrees of freedom to be separated from spin/orbital ordering. The heterogeneous phase mixtures (COI+FMI) cannot be treated as of granular composite behavior. (c) 2008 American Institute of Physics.
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A second DNA binding protein from stationary-phase cells of Mycobacterium smegmatis (MsDps2) has been identified from the bacterial genome. It was cloned, expressed and characterised and its crystal structure was determined. The core dodecameric structure of MsDps2 is the same as that of the Dps from the organism described earlier (MsDps1). However, MsDps2 possesses a long N-terminal tail instead of the C-terminal tail in MsDps1. This tail appears to be involved in DNA binding. It is also intimately involved in stabilizing the dodecamer. Partly on account of this factor, MsDps2 assembles straightway into the dodecamer, while MsDps1 does so on incubation after going through an intermediate trimeric stage. The ferroxidation centre is similar in the two proteins, while the pores leading to it exhibit some difference. The mode of sequestration of DNA in the crystalline array of molecules, as evidenced by the crystal structures, appears to be different in MsDps1 and MsDps2, highlighting the variability in the mode of Dps–DNA complexation. A sequence search led to the identification of 300 Dps molecules in bacteria with known genome sequences. Fifty bacteria contain two or more types of Dps molecules each, while 195 contain only one type. Some bacteria, notably some pathogenic ones, do not contain Dps. A sequence signature for Dps could also be derived from the analysis.
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In this article we study the one-dimensional random geometric (random interval) graph when the location of the nodes are independent and exponentially distributed. We derive exact results and limit theorems for the connectivity and other properties associated with this random graph. We show that the asymptotic properties of a graph with a truncated exponential distribution can be obtained using the exponential random geometric graph. © 2007 Wiley Periodicals, Inc. Random Struct. Alg., 2008.
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Time-dependent backgrounds in string theory provide a natural testing ground for physics concerning dynamical phenomena which cannot be reliably addressed in usual quantum field theories and cosmology. A good, tractable example to study is the rolling tachyon background, which describes the decay of an unstable brane in bosonic and supersymmetric Type II string theories. In this thesis I use boundary conformal field theory along with random matrix theory and Coulomb gas thermodynamics techniques to study open and closed string scattering amplitudes off the decaying brane. The calculation of the simplest example, the tree-level amplitude of n open strings, would give us the emission rate of the open strings. However, even this has been unknown. I will organize the open string scattering computations in a more coherent manner and will argue how to make further progress.
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Deep convolutional neural networks (DCNNs) have been employed in many computer vision tasks with great success due to their robustness in feature learning. One of the advantages of DCNNs is their representation robustness to object locations, which is useful for object recognition tasks. However, this also discards spatial information, which is useful when dealing with topological information of the image (e.g. scene labeling, face recognition). In this paper, we propose a deeper and wider network architecture to tackle the scene labeling task. The depth is achieved by incorporating predictions from multiple early layers of the DCNN. The width is achieved by combining multiple outputs of the network. We then further refine the parsing task by adopting graphical models (GMs) as a post-processing step to incorporate spatial and contextual information into the network. The new strategy for a deeper, wider convolutional network coupled with graphical models has shown promising results on the PASCAL-Context dataset.
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As an extension to an activity introducing Year 5 students to the practice of statistics, the software TinkerPlots made it possible to collect repeated random samples from a finite population to informally explore students’ capacity to begin reasoning with a distribution of sample statistics. This article provides background for the sampling process and reports on the success of students in making predictions for the population from the collection of simulated samples and in explaining their strategies. The activity provided an application of the numeracy skill of using percentages, the numerical summary of the data, rather than graphing data in the analysis of samples to make decisions on a statistical question. About 70% of students made what were considered at least moderately good predictions of the population percentages for five yes–no questions, and the correlation between predictions and explanations was 0.78.