907 resultados para EDS analysis


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Efficient error-Propagating Block Chaining (EPBC) is a block cipher mode intended to simultaneously provide both confidentiality and integrity protection for messages. Mitchell’s analysis pointed out a weakness in the EPBC integrity mechanism that can be used in a forgery attack. This paper identifies and corrects a flaw in Mitchell’s analysis of EPBC, and presents other attacks on the EPBC integrity mechanism.

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The forthcoming NIST’s Advanced Hash Standard (AHS) competition to select SHA-3 hash function requires that each candidate hash function submission must have at least one construction to support FIPS 198 HMAC application. As part of its evaluation, NIST is aiming to select either a candidate hash function which is more resistant to known side channel attacks (SCA) when plugged into HMAC, or that has an alternative MAC mode which is more resistant to known SCA than the other submitted alternatives. In response to this, we perform differential power analysis (DPA) on the possible smart card implementations of some of the recently proposed MAC alternatives to NMAC (a fully analyzed variant of HMAC) and HMAC algorithms and NMAC/HMAC versions of some recently proposed hash and compression function modes. We show that the recently proposed BNMAC and KMDP MAC schemes are even weaker than NMAC/HMAC against the DPA attacks, whereas multi-lane NMAC, EMD MAC and the keyed wide-pipe hash have similar security to NMAC against the DPA attacks. Our DPA attacks do not work on the NMAC setting of MDC-2, Grindahl and MAME compression functions.

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This chapter discussed the various modes of operation of the Doubly Fed Induction Generator (DFIG) based wind farm system. The impact of a auxiliary damping controller on the different modes of operation for the DFIG based wind generation system is investigated. The co-ordinated tuning of the damping controller to enhance the damping of the oscillatory modes using Bacteria Foraging (BF) technique is presented. The results from eigenvalue analysis are presented to elucidate the effectiveness of the tuned damping controller in the DFIG system under Super/Sub-synchronous speed of operation. The robustness issue of the damping controller is also investigated.

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This chapter provides a theoretical overview of literature that uses conversation analysis (CA) to explore children’s interactions related to trauma and associated mental health matters. The relatively new approach of using CA to understand trauma reveals the importance of talk in the process of recovery, and also how the participants co-construct talk about traumatic experiences. The chapter will explore literature using a CA approach to investigate children’s trauma talk with professionals as well as literature specifically discussing children’s talk about their traumatic experiences with people who are not qualified therapists or psychiatrists. We conclude by calling for more research using a CA approach for investigating children’s traumatic experiences due to the insight it provides into each child’s personal sense making of traumatic events with a range of people.

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Many researchers in the field of civil structural health monitoring have developed and tested their methods on simple to moderately complex laboratory structures such as beams, plates, frames, and trusses. Field work has also been conducted by many researchers and practitioners on more complex operating bridges. Most laboratory structures do not adequately replicate the complexity of truss bridges. This paper presents some preliminary results of experimental modal testing and analysis of the bridge model presented in the companion paper, using the peak picking method, and compares these results with those of a simple numerical model of the structure. Three dominant modes of vibration were experimentally identified under 15 Hz. The mode shapes and order of the modes matched those of the numerical model; however, the frequencies did not match.

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In recent years, many studies have provided evidence that exosomes secreted by cells contain various components, including microRNAs [1]. It is thought that exosomes have important roles in many biological processes. However, the role of exosomes and their components, especially miRNAs, in wound healing is poorly understood. In order to understand whether or not primary human epidermal keratinocytes and dermal fibroblasts, two important cell types contributing to wound healing process, release exosomes and what species of wound healing-associated miRNAs accumulate in these vesicles, this project will use a combination of methods to isolate and characterize exosomes, to profile exosomal cargo’s, especially miRNAs in exosomes. The results showed that keratinocytes and fibroblasts released exosomes into conditioned media and these exosomes contain some target miRNAs.

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There are three distinct categories of air environment to be considered in this chapter. These are as follows: (1) The “ambient” or general outdoors atmosphere to which the members of the population are exposed when they venture out of their homes or offices in industrial, urban or rural environments. (2) Indoor air environments, which occur in buildings such as homes, schools, restaurants, public hospitals and office buildings. This category does not cover factories or workplaces which are otherwise subjected to the provisions of various occupational health standards. (3) Workplace atmospheres, which occur in a variety of industries or factories and for which there are numerous atmospheric concentration limits (or exposure standards) promulgated by appropriate bodies or organisations. Since 2009 setting concentration limits for atmospheric contaminants has been administered by Safe Work Australia. A fourth category of air environment which falls outside this chapter is that which is related to upper atmospheric research, global atmospheric effects and concomitant areas of inquiry and/or debate. Such areas include “greenhouse” gas emissions, ozone depletion, and related matters of atmospheric chemistry and physics. This category is not referred to again in this chapter.

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The mineral fraipontite has been studied by using a combination of scanning electron microscopy with energy dispersive analysis and vibrational spectroscopy (infrared and Raman). Fraipontite is a member of the 1:1 clay minerals of the kaolinite-serpentine group. The mineral contains Zn and Cu and is of formula (Cu,Zn,Al)3(Si,Al)2O5(OH)4. Qualitative chemical analysis of fraipontite shows an aluminium silicate mineral with amounts of Cu and Zn. This kaolinite type mineral has been characterised by Raman and infrared spectroscopy; in this way aspects about the molecular structure of fraipontite clay are elucidated.

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We have undertaken a study of the tellurite mineral sonorite using electron microscopy with EDX combined with vibrational spectroscopy. Chemical analysis shows a homogeneous composition, with predominance of Te, Fe, Ce and In with minor amounts of S. Raman spectroscopy has been used to study the mineral sonoraite an examples of group A(XO3), with hydroxyl and water units in the mineral structure. The free tellurite ion has C3v symmetry and four modes, 2A1 and 2E. An intense Raman band at 734 cm−1 is assigned to the ν1 (TeO3)2− symmetric stretching mode. A band at 636 cm−1 is assigned to the ν3 (TeO3)2− antisymmetric stretching mode. Bands at 350 and 373 cm−1 and the two bands at 425 and 438 cm−1 are assigned to the (TeO3)2−ν2 (A1) bending mode and (TeO3)2−ν4 (E) bending modes. The sharp band at 3283 cm−1 assigned to the OH stretching vibration of the OH units is superimposed upon a broader spectral profile with Raman bands at 3215, 3302, 3349 and 3415 cm−1 are attributed to water stretching bands. The techniques of Raman and infrared spectroscopy are excellent for the study of tellurite minerals.

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Provides an accessible foundation to Bayesian analysis using real world models This book aims to present an introduction to Bayesian modelling and computation, by considering real case studies drawn from diverse fields spanning ecology, health, genetics and finance. Each chapter comprises a description of the problem, the corresponding model, the computational method, results and inferences as well as the issues that arise in the implementation of these approaches. Case Studies in Bayesian Statistical Modelling and Analysis: •Illustrates how to do Bayesian analysis in a clear and concise manner using real-world problems. •Each chapter focuses on a real-world problem and describes the way in which the problem may be analysed using Bayesian methods. •Features approaches that can be used in a wide area of application, such as, health, the environment, genetics, information science, medicine, biology, industry and remote sensing. Case Studies in Bayesian Statistical Modelling and Analysis is aimed at statisticians, researchers and practitioners who have some expertise in statistical modelling and analysis, and some understanding of the basics of Bayesian statistics, but little experience in its application. Graduate students of statistics and biostatistics will also find this book beneficial.

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A description of a computer program to analyse cine angiograms of the heart and pressure waveforms to calculate valve gradients.

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This paper presents an uncertainty quantification study of the performance analysis of the high pressure ratio single stage radial-inflow turbine used in the Sundstrand Power Systems T-100 Multi-purpose Small Power Unit. A deterministic 3D volume-averaged Computational Fluid Dynamics (CFD) solver is coupled with a non-statistical generalized Polynomial Chaos (gPC) representation based on a pseudo-spectral projection method. One of the advantages of this approach is that it does not require any modification of the CFD code for the propagation of random disturbances in the aerodynamic and geometric fields. The stochastic results highlight the importance of the blade thickness and trailing edge tip radius on the total-to-static efficiency of the turbine compared to the angular velocity and trailing edge tip length. From a theoretical point of view, the use of the gPC representation on an arbitrary grid also allows the investigation of the sensitivity of the blade thickness profiles on the turbine efficiency. The gPC approach is also applied to coupled random parameters. The results show that the most influential coupled random variables are trailing edge tip radius coupled with the angular velocity.

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We extended genetic linkage analysis - an analysis widely used in quantitative genetics - to 3D images to analyze single gene effects on brain fiber architecture. We collected 4 Tesla diffusion tensor images (DTI) and genotype data from 258 healthy adult twins and their non-twin siblings. After high-dimensional fluid registration, at each voxel we estimated the genetic linkage between the single nucleotide polymorphism (SNP), Val66Met (dbSNP number rs6265), of the BDNF gene (brain-derived neurotrophic factor) with fractional anisotropy (FA) derived from each subject's DTI scan, by fitting structural equation models (SEM) from quantitative genetics. We also examined how image filtering affects the effect sizes for genetic linkage by examining how the overall significance of voxelwise effects varied with respect to full width at half maximum (FWHM) of the Gaussian smoothing applied to the FA images. Raw FA maps with no smoothing yielded the greatest sensitivity to detect gene effects, when corrected for multiple comparisons using the false discovery rate (FDR) procedure. The BDNF polymorphism significantly contributed to the variation in FA in the posterior cingulate gyrus, where it accounted for around 90-95% of the total variance in FA. Our study generated the first maps to visualize the effect of the BDNF gene on brain fiber integrity, suggesting that common genetic variants may strongly determine white matter integrity.

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We propose a new information-theoretic metric, the symmetric Kullback-Leibler divergence (sKL-divergence), to measure the difference between two water diffusivity profiles in high angular resolution diffusion imaging (HARDI). Water diffusivity profiles are modeled as probability density functions on the unit sphere, and the sKL-divergence is computed from a spherical harmonic series, which greatly reduces computational complexity. Adjustment of the orientation of diffusivity functions is essential when the image is being warped, so we propose a fast algorithm to determine the principal direction of diffusivity functions using principal component analysis (PCA). We compare sKL-divergence with other inner-product based cost functions using synthetic samples and real HARDI data, and show that the sKL-divergence is highly sensitive in detecting small differences between two diffusivity profiles and therefore shows promise for applications in the nonlinear registration and multisubject statistical analysis of HARDI data.