The exponentiated generalized gamma distribution with application to lifetime data

A four-parameter extension of the generalized gamma distribution capable of modelling a bathtub-shaped hazard rate function is defined and studied. The beauty and importance of this distribution lies in its ability to model monotone and non-monotone failure rate functions, which are quite common in lifetime data analysis and reliability. The new distribution has a number of well-known lifetime special sub-models, such as the exponentiated Weibull, exponentiated generalized half-normal, exponentiated gamma and generalized Rayleigh, among others. We derive two infinite sum representations for its moments. We calculate the density of the order statistics and two expansions for their moments. The method of maximum likelihood is used for estimating the model parameters and the observed information matrix is obtained. Finally, a real data set from the medical area is analysed.

A Log-Linear Regression Model for the Beta-Weibull Distribution

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.

Inorganic surface passivation of PbS nanocrystals resulting in strong photoluminescent emission

Strong photoluminescent emission has been obtained from 3 nm PbS nanocrystals in aqueous colloidal solution, following treatment with CdS precursors. The observed emission can extend across the entire visible spectrum and usually includes a peak near 1.95 eV. We show that much of the visible emission results from absorption by higher-lying excited states above 3.0 eV with subsequent relaxation to and emission from states lying above the observed band-edge of the PbS nanocrystals. The fluorescent lifetimes for this emission are in the nanosecond regime, characteristic of exciton recombination.

Polarized photoluminescence from surface-passivated lead sulfide nanocrystals

Effective surface passivation of lead sulfide (PbS) nanocrystals (NCs) in an aqueous colloidal solution has been achieved following treatment with CdS precursors. The resultant photoluminescent emission displays two distinct components, one originating from the absorption band edge and the other from above the absorption band edge. We show that both of these components are strongly polarized but display distinctly different behaviours. The polarization arising from the band edge shows little dependence on the excitation energy while the polarization of the above-band-edge component is strongly dependent on the excitation energy. In addition, time-resolved polarization spectroscopy reveals that the above-band-edge polarization is restricted to the first couple of nanoseconds, while the band edge polarization is nearly constant over hundreds of nanoseconds. We recognize an incompatibility between the two different polarization behaviours, which enables us to identify two distinct types of surface-passivated PbS NC.

Superchemistry: dynamics of coupled atomic and molecular Bose condensates

We analyze the dynamics of a dilute, trapped Bose-condensed atomic gas coupled to a diatomic molecular Bose gas by coherent Raman transitions. This system is shown to result in a new type of “superchemistry,” in which giant collective oscillations between the atomic and the molecular gas can occur. The phenomenon is caused by stimulated emission of bosonic atoms or molecules into their condensate phases.

Canonical Bose gas simulations with stochastic gauges

A technique to simulate the grand canonical ensembles of interacting Bose gases is presented. Results are generated for many temperatures by averaging over energy-weighted stochastic paths, each corresponding to a solution of coupled Gross-Pitaevskii equations with phase noise. The stochastic gauge method used relies on an off-diagonal coherent-state expansion, thus taking into account all quantum correlations. As an example, the second-order spatial correlation function and momentum distribution for an interacting 1D Bose gas are calculated.

Gauge P-representations for quantum-dynamical problems: Removal of boundary terms

P-representation techniques, which have been very successful in quantum optics and in other fields, are also useful for general bosonic quantum-dynamical many-body calculations such as Bose-Einstein condensation. We introduce a representation called the gauge P representation, which greatly widens the range of tractable problems. Our treatment results in an infinite set of possible time evolution equations, depending on arbitrary gauge functions that can be optimized for a given quantum system. In some cases, previous methods can give erroneous results, due to the usual assumption of vanishing boundary conditions being invalid for those particular systems. Solutions are given to this boundary-term problem for all the cases where it is known to occur: two-photon absorption and the single-mode laser. We also provide some brief guidelines on how to apply the stochastic gauge method to other systems in general, quantify the freedom of choice in the resulting equations, and make a comparison to related recent developments.

Investigation of the role of cadmium sulfide in the surface passivation of lead sulfide quantum dots

Surface passivation of PbS nanocrystals (NC), resulting in strong photoluminescence, can be achieved by the introduction of CdS precursors. The role of CdS in the surface passivation of PbS NCs is uncertain, as the crystalline structure of CdS and PbS are different, which should impede effective epitaxial overgrowth. Absorption spectroscopy is used to show that the CdS precursors strongly interact with the PbS NC surface. Electron microscopy reveals that the introduction of CdS precursors results in an increased particle size, consistent with overcoating. However, we also find the process to be highly non-uniform. Nevertheless, evidence for epitaxial growth is found, suggesting that effective surface passivation may be possible.

Separating fluorescent species of aqueous PbS semiconductor nanocrystals using micro-emulsions

Colloidal PbS nanocrystals over-coated with CdS are prepared in aqueous solutions and exhibit strong photoluminescence with two distinct peaks in the visible regime. A photoluminescence peak is observed at 640 nm, which is attributed to the band edge recombination in the PbS nanocrystals, and another peak at 510 nm, which is above the band edge of the PbS nanocrystals. The two PL peaks are isolated by extracting separate species of nanocrystal based upon their surface morphology. Micro-emulsions of hexane:PVA are used to remove the species containing the PL peak at 640 nm from the solution, leaving a singular peak at 510 nm. We show conclusively that the double-peaked structure observed in the photoluminescence spectra of PbS nanocrystals over-coated with CdS is due to the presence of two distinctly different nanocrystal species.

Entangled States and Collective Nonclassical Effects in Two-Atom Systems

We propose a review of recent developments on entanglement and nonclassical effects in collective two-atom systems and present a uniform physical picture of the many predicted phenomena. The collective effects have brought into sharp focus some of the most basic features of quantum theory, such as nonclassical states of light and entangled states of multiatom systems. The entangled states are linear superpositions of the internal states of the system which cannot be separated into product states of the individual atoms. This property is recognized as entirely quantum-mechanical effect and have played a crucial role in many discussions of the nature of quantum measurements and, in particular, in the developments of quantum communications. Much of the fundamental interest in entangled states is connected with its practical application ranging from quantum computation, information processing, cryptography, and interferometry to atomic spectroscopy.

Experimental Verification of Decoherence-Free Subspaces

Using spontaneous parametric down-conversion, we produce polarization-entangled states of two photons and characterize them using two-photon tomography to measure the density matrix. A controllable decoherence is imposed on the states by passing the photons through thick, adjustable birefringent elements. When the system is subject to collective decoherence, one particular entangled state is seen to be decoherence-free, as predicted by theory. Such decoherence-free systems may have an important role for the future of quantum computation and information processing.

Trace Semantics for the Owicki-Gries Theory Integrated with the Progress Logic from UNITY

The theory of Owicki and Gries has been used as a platform for safety-based verifcation and derivation of concurrent programs. It has also been integrated with the progress logic of UNITY which has allowed newer techniques of progress-based verifcation and derivation to be developed. However, a theoretical basis for the integrated theory has thus far been missing. In this paper, we provide a theoretical background for the logic of Owicki and Gries integrated with the logic of progress from UNITY. An operational semantics for the new framework is provided which is used to prove soundness of the progress logic.

Thermally developing Brinkman–Brinkman forced convection in rectangular ducts with isothermal walls

The Extended Weighted Residuals Method (EWRM) is applied to investigate the effects of viscous dissipation on the thermal development of forced convection in a porous-saturated duct of rectangular cross-section with isothermal boundary condition. The Brinkman flow model is employed for determination of the velocity field. The temperature in the flow field was computed by utilizing the Green’s function solution based on the EWRM. Following the computation of the temperature field, expressions are presented for the local Nusselt number and the bulk temperature as a function of the dimensionless longitudinal coordinate. In addition to the aspect ratio, the other parameters included in this computation are the Darcy number, viscosity ratio, and the Brinkman number.

A power system control scheme based on security visualisation in parameter space

Power system real time security assessment is one of the fundamental modules of the electricity markets. Typically, when a contingency occurs, it is required that security assessment and enhancement module shall be ready for action within about 20 minutes’ time to meet the real time requirement. The recent California black out again highlighted the importance of system security. This paper proposed an approach for power system security assessment and enhancement based on the information provided from the pre-defined system parameter space. The proposed scheme opens up an efficient way for real time security assessment and enhancement in a competitive electricity market for single contingency case

Special issue on advances in data mining and its applications

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).