36 resultados para HALF-NORMAL DISTRIBUTION
em QUB Research Portal - Research Directory and Institutional Repository for Queen's University Belfast
Resumo:
A randomly distributed multi-particle model considering the effects of particle/matrix interface and strengthening mechanisms introduced by the particles has been constructed. Particle shape, distribution, volume fraction and the particles/matrix interface due to the factors including element diffusion were considered in the model. The effects of strengthening mechanisms, caused by the introduction of particles on the mechanical properties of the composites, including grain refinement strengthening, dislocation strengthening and Orowan strengthening, are incorporated. In the model, the particles are assumed to have spheroidal shape, with uniform distribution of the centre, long axis length and inclination angle. The axis ratio follows a right half-normal distribution. Using Monte Carlo method, the location and shape parameters of the spheroids are randomly selected. The particle volume fraction is calculated using the area ratio of the spheroids. Then, the effects of particle/matrix interface and strengthening mechanism on the distribution of Mises stress and equivalent strain and the flow behaviour for the composites are discussed.
Resumo:
The effect of volume shape factor on crystal size distribution (CSD) is usually ignored to simplify the analysis of population balance equation. In the present work, the CSD of fragments generated from a mechanically stirred crystallizer as the result of attrition mechanism has been reported when the volume shape factor conforms to normal distribution. The physical model of GAHN and MERSMANN which relates the attrition resistance of a crystalline substances to its mechanical properties has been employed. The simulation of fragment size distribution was performed by Monte Carlo (MC) technique. The results are compared with those reported by GAHN and MERSMANN.
Resumo:
This brief examines the application of nonlinear statistical process control to the detection and diagnosis of faults in automotive engines. In this statistical framework, the computed score variables may have a complicated nonparametric distri- bution function, which hampers statistical inference, notably for fault detection and diagnosis. This brief shows that introducing the statistical local approach into nonlinear statistical process control produces statistics that follow a normal distribution, thereby enabling a simple statistical inference for fault detection. Further, for fault diagnosis, this brief introduces a compensation scheme that approximates the fault condition signature. Experimental results from a Volkswagen 1.9-L turbo-charged diesel engine are included.
Resumo:
Value-at-risk (VaR) forecasting generally relies on a parametric density function of portfolio returns that ignores higher moments or assumes them constant. In this paper, we propose a simple approach to forecasting of a portfolio VaR. We employ the Gram-Charlier expansion (GCE) augmenting the standard normal distribution with the first four moments, which are allowed to vary over time. In an extensive empirical study, we compare the GCE approach to other models of VaR forecasting and conclude that it provides accurate and robust estimates of the realized VaR. In spite of its simplicity, on our dataset GCE outperforms other estimates that are generated by both constant and time-varying higher-moments models.
Resumo:
Metallographic characterisation is combined with statistical analysis to study the microstructure of a BT16 titanium alloy after different heat treatment processes. It was found that the length, width and aspect ratio of α plates in this alloy follow the three-parameter Weibull distribution. Increasing annealing temperature or time causes the probability distribution of the length and the width of α plates to tend toward a normal distribution. The phase transformation temperature of the BT16 titanium alloy was found to be 875±5°C.
Resumo:
The kinetics of the recovery of the photoinduced transient bleaching of colloidal CdS in the presence of different electron acceptors are examined. In the presence of the zwitterionic viologen, N,N'-dipropyl-2,2'-bipyridinium disulphonate, excitation of colloidal CdS at different flash intensities generates a series of decay profiles which are superimposed when normalized. The shape of the decay curves are as predicted by a first-order activation-controlled model for a log-normal distribution of particles sizes. In contrast, the variation in flash intensity in the presence of a second viologen, N,N'-dipropyl-4,4'-bipyridinium sulphonate, generates normalized decay traces which broaden with increasing flash intensity. This behaviour is predicted by a zero-order diffusion-controlled model for a log-normal distribution of particle radii. The photoreduction of a number of other oxidants sensitized by colloidal CdS is examined and the shape of the decay kinetics interpreted via either the first- or zero-order kinetics models. The rate constants and activation energies derived using these models are consistent with the values expected for an activation- or diffusion-controlled reaction.
Resumo:
This paper compares the applicability of three ground survey methods for modelling terrain: one man electronic tachymetry (TPS), real time kinematic GPS (GPS), and terrestrial laser scanning (TLS). Vertical accuracy of digital terrain models (DTMs) derived from GPS, TLS and airborne laser scanning (ALS) data is assessed. Point elevations acquired by the four methods represent two sections of a mountainous area in Cumbria, England. They were chosen so that the presence of non-terrain features is constrained to the smallest amount. The vertical accuracy of the DTMs was addressed by subtracting each DTM from TPS point elevations. The error was assessed using exploratory measures including statistics, histograms, and normal probability plots. The results showed that the internal measurement accuracy of TPS, GPS, and TLS was below a centimetre. TPS and GPS can be considered equally applicable alternatives for sampling the terrain in areas accessible on foot. The highest DTM vertical accuracy was achieved with GPS data, both on sloped terrain (RMSE 0.16. m) and flat terrain (RMSE 0.02. m). TLS surveying was the most efficient overall but veracity of terrain representation was subject to dense vegetation cover. Therefore, the DTM accuracy was the lowest for the sloped area with dense bracken (RMSE 0.52. m) although it was the second highest on the flat unobscured terrain (RMSE 0.07. m). ALS data represented the sloped terrain more realistically (RMSE 0.23. m) than the TLS. However, due to a systematic bias identified on the flat terrain the DTM accuracy was the lowest (RMSE 0.29. m) which was above the level stated by the data provider. Error distribution models were more closely approximated by normal distribution defined using median and normalized median absolute deviation which supports the use of the robust measures in DEM error modelling and its propagation. © 2012 Elsevier Ltd.
Resumo:
This study presents the findings of an empirical channel characterisation for an ultra-wideband off-body optic fibre-fed multiple-antenna array within an office and corridor environment. The results show that for received power experiments, the office and corridor were best modelled by lognormal and Rician distributions, respectively [for both line of sight (LOS) and non-LOS (NLOS) scenarios]. In the office, LOS measurements for t and tRMS were both described by the Normal distribution for all channels, whereas NLOS measurements for t and t were Nakagami and Weibull distributed, respectively. For the corridor measurements, LOS for t and t were either Nakagami or normally distributed for all channels, with NLOS measurements for t and t being Nakagami and normally distributed, respectively. This work also shows that achievable diversity gain was influenced by both mutual coupling and cross-correlation co-efficients. Although the best diversity gains were 1.8 dB for three-channel selective diversity combining, the authors present recommendations for improving these results. © The Institution of Engineering and Technology 2013.
Resumo:
ABSTRACT BODY: To resolve outstanding questions on heating of coronal loops, we study intensity fluctuations in inter-moss portions of active region core loops as observed with AIA/SDO. The 94Å fluctuations (Figure 1) have structure on timescales shorter than radiative and conductive cooling times. Each of several strong 94Å brightenings is followed after ~8 min by a broader peak in the cooler 335Å emission. This indicates that we see emission from the hot component of the 94Å contribution function. No hotter contributions appear, and we conclude that the 94Å intensity can be used as a proxy for energy injection into the loop plasma. The probability density function of the observed 94Å intensity has 'heavy tails' that approach zero more slowly than the tails of a normal distribution. Hence, large fluctuations dominate the behavior of the system. The resulting 'intermittence' is associated with power-law or exponential scaling of the related variables, and these in turn are associated with turbulent phenomena. The intensity plots in Figure 1 resemble multifractal time series, which are common to various forms of turbulent energy dissipation. In these systems a single fractal dimension is insufficient to describe the dynamics and instead there is a spectrum of fractal dimensions that quantify the self-similar properties. Figure 2 shows the multifractal spectrum from our data to be invariant over timescales from 24 s to 6.4 min. We compare these results to outputs from theoretical energy dissipation models based on MHD turbulence, and in some cases we find substantial agreement, in terms of intermittence, multifractality and scale invariance. Figure 1. Time traces of 94A intensity in the inter-moss portions of four AR core loops. Figure 2. Multifractal spectra showing timescale invariance. The four cases of Figure 1 are included.
Resumo:
Most cryptographic devices should inevitably have a resistance against the threat of side channel attacks. For this, masking and hiding schemes have been proposed since 1999. The security validation of these countermeasures is an ongoing research topic, as a wider range of new and existing attack techniques are tested against these countermeasures. This paper examines the side channel security of the balanced encoding countermeasure, whose aim is to process the secret key-related data under a constant Hamming weight and/or Hamming distance leakage. Unlike previous works, we assume that the leakage model coefficients conform to a normal distribution, producing a model with closer fidelity to real-world implementations. We perform analysis on the balanced encoded PRINCE block cipher with simulated leakage model and also an implementation on an AVR board. We consider both standard correlation power analysis (CPA) and bit-wise CPA. We confirm the resistance of the countermeasure against standard CPA, however, we find with a bit-wise CPA that we can reveal the key with only a few thousands traces.
Resumo:
We have compared the expression of the known measles virus (MV) receptors, membrane cofactor protein (CD46) and the signaling lymphocyte-activation molecule (SLAM), using immunohistochemistry, in a range of normal peripheral tissues (known to be infected by MV) as well as in normal and subacute sclerosing panencephalitis (SSPE) brain. To increase our understanding of how these receptors could be utilized by wild-type or vaccine strains in vivo, the results have been considered with regard to the known route of infection and systemic spread of MV. Strong staining for CD46 was observed in endothelial cells lining blood vessels and in epithelial cells and tissue macrophages in a wide range of peripheral tissues, as well as in Langerhans' and squamous cells in the skin. In lymphoid tissues and blood, subsets of cells were positive for SLAM, in comparison to CD46, which stained all nucleated cell types. Strong CD46 staining was observed on cerebral endothelium throughout the brain and also on ependymal cells lining the ventricles and choroid plexus. Comparatively weaker CD46 staining was observed on subsets of neurons and oligodendrocytes. In SSPE brain sections, the areas distant from lesion sites and negative for MV by immunocytochemistry showed the same distribution for CD46 as in normal brain. However, cells in lesions, positive for MV, were negative for CD46. Normal brain showed no staining for SLAM, and in SSPE brain only subsets of leukocytes in inflammatory infiltrates were positive. None of the cell types most commonly infected by MV show detectable expression of SLAM, whereas CD46 is much more widely expressed and could fulfill a receptor function for some wild-type strains. In the case of wild-type stains, which are unable to use CD46, a further as yet unknown receptor(s) would be necessary to fully explain the pathology of MV infection.
Resumo:
Shigella flexneri causes bacillary dysentery in humans. Essential to the establishment of the disease is the invasion of the colonic epithelial cells. Here we investigated the role of the lipopolysaccharide (LPS) O antigen in the ability of S. flexaeri to adhere to and invade polarized Caco-2 cells. The S. flexneri 2a O antigen has two preferred chain lengths: a short O antigen (S-OAg) regulated by the WzzB protein and a very long O antigen (VL-OAg) regulated by Wzz(pHS2). Mutants with defined deletions of the genes required for O-antigen assembly and polymerization were constructed and assayed for their abilities to adhere to and enter cultured epithelial cells. The results show that both VL- and S-OAg are required for invasion through the basolateral cell membrane. In contrast, the absence of O antigen does not impair adhesion. Purified LPS does not act as a competitor for the invasion of Caco-2 cells by the wild-type strain, suggesting that LPS is not directly involved in the internalization process by epithelial cells.
Resumo:
Conditional Gaussian (CG) distributions allow the inclusion of both discrete and continuous variables in a model assuming that the continuous variable is normally distributed. However, the CG distributions have proved to be unsuitable for survival data which tends to be highly skewed. A new method of analysis is required to take into account continuous variables which are not normally distributed. The aim of this paper is to introduce the more appropriate conditional phase-type (C-Ph) distribution for representing a continuous non-normal variable while also incorporating the causal information in the form of a Bayesian network.