Bayes estimators for reliability measures in geometric distribution model using masked system life test data

This paper presents Bayes estimators for the reliability measures of the individual components in a multi-component systems in the presence of masked system life test data. The life time distributions of the system components are assumed to be geometric with different parameters. Two-sided Bayesian probability intervals of the parameters are also derived. Numerical simulation study is given in order to: (i) explain how one can apply the theoretical results obtained, (ii) study the influence of the sample size and masking level on the accuracy of point estimates.     

Influence of Aging Parameters on the Tensile Properties and Quality Index of Al-9?Pct Si-1.8?Pct Cu-0.5?Pct Mg 354-Type Casting Alloys

The current study was carried out with a view to investigating the influence of age-hardening parameters, aging temperature and time, on the tensile properties and quality indices of a high-strength Al-9 pct Si casting alloy, namely, 354-Al-9 pct Si-1.8 pct Cu-0.5 pct Mg. Quality charts were used as an evaluation tool for selecting the optimum conditions to be applied, in practice, in order to develop high strength and optimum quality in 354 casting alloy. Aging at a low temperature of 428 K (155 °C) was observed to produce the greatest strength and optimum quality in the 354-type castings compared to aging at higher temperatures. The peak strength observed for 354 alloy may be attained after shorter aging times on the condition that the aging temperature is increased. The aging times required for reaching peak strength in 354 alloys are 72 hours, 40 hours, 8 hours, 1 hour, and 15 minutes at aging temperatures of 428 K, 443 K, 468 K, 493 K, and 518 K (155 °C, 170 °C, 195 °C, 220 °C, and 245 °C), respectively. Aging treatment at higher temperatures is accompanied by a reduction in the tensile properties and quality index values of the castings; however, it also introduces the possibility of a significant economical strategy for minimizing the time and the cost of this same treatment. Aging treatment at a lower temperature of 428 K (155 °C) produces fine and dense precipitates displaying smaller interparticle spacing, while at higher aging temperatures, such as 518 K (245 °C), the precipitates are coarser in size, less dense, and more widely dispersed. The quality charts developed in the course of the current research facilitate the interpretation and evaluation of the tensile properties of the 354 alloy. Such charts provide a logical evaluation tool, from the metallurgical point of view, for an accurate prediction of the influence of aging parameters studied on the properties of the alloys. Depending on the required level of tensile properties and based on the quality charts developed, it is possible to make a rigorous selection as to the most suitable aging parameters to be applied to the 354 alloy so as to obtain the best possible cost-effective compromise between alloy strength and quality.     

Genetic algorithm-based improved DOA estimation using fourth-order cumulants

Genetic algorithm (GA)-based direction of arrival (DOA) estimation is proposed using fourth-order cumulants (FOC) and ESPRIT principle which results in Multiple Invariance Cumulant ESPRIT algorithm. In the existing FOC ESPRIT formulations, only one invariance is utilised to estimate DOAs. The unused multiple invariances (MIs) must be exploited simultaneously in order to improve the estimation accuracy. In this paper, a fitness function based on a carefully designed cumulant matrix is developed which incorporates MIs present in the sensor array. Better DOA estimation can be achieved by minimising this fitness function. Moreover, the effectiveness of Newton’s method as well as GA for this optimisation problem has been illustrated. Simulation results show that the proposed algorithm provides improved estimation accuracy compared to existing algorithms, especially in the case of low SNR, less number of snapshots, closely spaced sources and high signal and noise correlation. Moreover, it is observed that the optimisation using Newton’s method is more likely to converge to false local optima resulting in erroneous results. However, GA-based optimisation has been found attractive due to its global optimisation capability.     

A scenario-based reliability analysis approach for component-based software

This paper introduces a reliability model, and a reliability analysis technique for component-based software. The technique is named Scenario-Based Reliability Analysis (SBRA). Using scenarios of component interactions, we construct a probabilistic model named Component-Dependency Graph (CDG). Based on CDG, a reliability analysis algorithm is developed to analyze the reliability of the system as a function of reliabilities of its architectural constituents. An extension of the proposed model and algorithm is also developed for distributed software systems. The proposed approach has the following benefits: 1) It is used to analyze the impact of variations and uncertainties in the reliability of individual components, subsystems, and links between components on the overall reliability estimate of the software system. This is particularly useful when the system is built partially or fully from existing off-the-shelf components; 2) It is suitable for analyzing the reliability of distributed software systems because it incorporates link and delivery channel reliabilities; 3) The technique is used to identify critical components, interfaces, and subsystems; and to investigate the sensitivity of the application reliability to these elements; 4) The approach is applicable early in the development lifecycle, at the architecture level. Early detection of critical architecture elements, those that affect the overall reliability of the system the most, is useful in delegating resources in later development phases.     

A Scalable Framework For Segmenting Magnetic Resonance Images

A fast, accurate and fully automatic method of segmenting magnetic resonance images of the human brain is introduced. The approach scales well allowing fast segmentations of fine resolution images. The approach is based on modifications of the soft clustering algorithm, fuzzy c-means, that enable it to scale to large data sets. Two types of modifications to create incremental versions of fuzzy c-means are discussed. They are much faster when compared to fuzzy c-means for medium to extremely large data sets because they work on successive subsets of the data. They are comparable in quality to application of fuzzy c-means to all of the data. The clustering algorithms coupled with inhomogeneity correction and smoothing are used to create a framework for automatically segmenting magnetic resonance images of the human brain. The framework is applied to a set of normal human brain volumes acquired from different magnetic resonance scanners using different head coils, acquisition parameters and field strengths. Results are compared to those from two widely used magnetic resonance image segmentation programs, Statistical Parametric Mapping and the FMRIB Software Library (FSL). The results are comparable to FSL while providing significant speed-up and better scalability to larger volumes of data.     

UtilisatIon D’un Processus de Renormalisation Pour L’étude Électromagnétique des Structures Fractales Bidimensionnelles

In this article, we apply the renormalization technique, used possibly in theorical physics, for electromagnetic studying of bi dimensional fractal structures. A recurrence relation based on the auto-similar nature of structures and on the model of the surface impedance, has permitted, thanks to the convergence to a fixed point, to determine the input impedance of these structures at any scale. Though, the suggested method has been validated by calculus of one-dimensional structures (Iris de Cantor) it may be applied easily to the analysis of planar circuits as the Sierpensky antenna.     

Improvement of the cell performance in the ZnS/Cu(In,Ga)Se2 solar cells by the sputter deposition of a bilayer ZnO : Al film

ZnS is a candidate to replace CdS as the buffer layer in Cu(In,Ga)Se₂ (CIGS) solar cells for Cd‐free commercial product. However, the resistance of ZnS is too large, and the photoconductivity is too small. Therefore, the thickness of the ZnS should be as thin as possible. However, a CIGS solar cell with a very thin ZnS buffer layer is vulnerable to the sputtering power of the ZnO : Al window layer deposition because of plasma damage. To improve the efficiency of CIGS solar cells with a chemical‐bath‐deposited ZnS buffer layer, the effect of the plasma damage by the sputter deposition of the ZnO : Al window layer should be understood. We have found that the efficiency of a CIGS solar cell consistently decreases with an increase in the sputtering power for the ZnO : Al window layer deposition onto the ZnS buffer layer because of plasma damage. To protect the ZnS/CIGS interface, a bilayer ZnO : Al film was developed. It consists of a 50‐nm‐thick ZnO : Al plasma protection layer deposited at a sputtering power of 50 W and a 100‐nm‐thick ZnO : Al conducting layer deposited at a sputtering power of 200 W. The introduction of a 50‐nm‐thick ZnO : Al layer deposited at 50 W prevented plasma damage by sputtering, resulting in a high open‐circuit voltage, a large fill factor, and shunt resistance. The ZnS/CIGS solar cell with the bilayer ZnO : Al film yielded a cell efficiency of 14.68%. Therefore, the application of bilayer ZnO : Al film to the window layer is suitable for CIGS solar cells with a ZnS buffer layer. Copyright © 2012 John Wiley & Sons, Ltd.     

Blind Channel Identifiability for Generic Linear Space-Time Block Codes

Linear space-time block codes (STBCs) have proven their effectiveness in performance improvement of wireless multiple-input multiple-output communication systems. Their successful decoding, however, requires reliable channel knowledge at the receiver. In this paper, we present a semiblind channel estimation method for linear STBC without the usual code orthogonality condition. We provide a set of identification conditions that are mostly verifiable a priori in terms of code parameters and antenna array configuration. We also present a simple channel estimation algorithm. Finally, we provide simulation results that illustrate the performance of the proposed scheme     

Reducible rank codes and their applications to cryptography

We present a new family of so-called reducible rank codes which are a generalization of rank product codes . This family includes maximal rank distance (MRD) codes for lengths n>N in the field F/sub N/. We give methods for encoding and decoding reducible rank codes. A public key cryptosystem based on these codes and on the idea of a column scrambler is proposed. The column scrambler "mixes" columns of a generator (parity-check) matrix of a code. It makes the system more resistant to structural attacks such as Gibson's attacks. Possible attacks on the system are thoroughly studied. The system is found to be secure against known attacks for public keys of about 16 kbits and greater.