Optimal projection of observations in a Bayesian setting

Optimal dimensionality reduction methods are proposed for the Bayesian inference of a Gaussian linear model with additive noise in presence of overabundant data. Three different optimal projections of the observations are proposed based on information theory: the projection that minimizes the Kullback-Leibler divergence between the posterior distributions of the original and the projected models, the one that minimizes the expected Kullback-Leibler divergence between the same distributions, and the one that maximizes the mutual information between the parameter of interest and the projected observations. The first two optimization problems are formulated as the determination of an optimal subspace and therefore the solution is computed using Riemannian optimization algorithms on the Grassmann manifold. Regarding the maximization of the mutual information, it is shown that there exists an optimal subspace that minimizes the entropy of the posterior distribution of the reduced model; a basis of the subspace can be computed as the solution to a generalized eigenvalue problem; an a priori error estimate on the mutual information is available for this particular solution; and that the dimensionality of the subspace to exactly conserve the mutual information between the input and the output of the models is less than the number of parameters to be inferred. Numerical applications to linear and nonlinear models are used to assess the efficiency of the proposed approaches, and to highlight their advantages compared to standard approaches based on the principal component analysis of the observations

Coordinate Transformation and Polynomial Chaos for the Bayesian Inference of a Gaussian Process with Parametrized Prior Covariance Function

This paper addresses model dimensionality reduction for Bayesian inference based on prior Gaussian fields with uncertainty in the covariance function hyper-parameters. The dimensionality reduction is traditionally achieved using the Karhunen-\Loeve expansion of a prior Gaussian process assuming covariance function with fixed hyper-parameters, despite the fact that these are uncertain in nature. The posterior distribution of the Karhunen-Lo\`{e}ve coordinates is then inferred using available observations. The resulting inferred field is therefore dependent on the assumed hyper-parameters. Here, we seek to efficiently estimate both the field and covariance hyper-parameters using Bayesian inference. To this end, a generalized Karhunen-Lo\`{e}ve expansion is derived using a coordinate transformation to account for the dependence with respect to the covariance hyper-parameters. Polynomial Chaos expansions are employed for the acceleration of the Bayesian inference using similar coordinate transformations, enabling us to avoid expanding explicitly the solution dependence on the uncertain hyper-parameters. We demonstrate the feasibility of the proposed method on a transient diffusion equation by inferring spatially-varying log-diffusivity fields from noisy data. The inferred profiles were found closer to the true profiles when including the hyper-parameters' uncertainty in the inference formulation.Comment: 34 pages, 17 figure

Solving Modal Equations of Motion with Initial Conditions Using MSC/NASTRAN DMAP

By utilizing MSC/NASTRAN DMAP (Direct Matrix Abstraction Program) in an existing NASA Lewis Research Center coupled loads methodology, solving modal equations of motion with initial conditions is possible using either coupled (Newmark-Beta) or uncoupled (exact mode superposition) integration available within module TRD1. Both the coupled and newly developed exact mode superposition methods have been used to perform transient analyses of various space systems. However, experience has shown that in most cases, significant time savings are realized when the equations of motion are integrated using the uncoupled solver instead of the coupled solver. Through the results of a real-world engineering analysis, advantages of using the exact mode superposition methodology are illustrated

Solving modal equations of motion with initial conditions using MSC/NASTRAN DMAP. Part 1: Implementing exact mode superposition

Within the MSC/NASTRAN DMAP (Direct Matrix Abstraction Program) module TRD1, solving physical (coupled) or modal (uncoupled) transient equations of motion is performed using the Newmark-Beta or mode superposition algorithms, respectively. For equations of motion with initial conditions, only the Newmark-Beta integration routine has been available in MSC/NASTRAN solution sequences for solving physical systems and in custom DMAP sequences or alters for solving modal systems. In some cases, one difficulty with using the Newmark-Beta method is that the process of selecting suitable integration time steps for obtaining acceptable results is lengthy. In addition, when very small step sizes are required, a large amount of time can be spent integrating the equations of motion. For certain aerospace applications, a significant time savings can be realized when the equations of motion are solved using an exact integration routine instead of the Newmark-Beta numerical algorithm. In order to solve modal equations of motion with initial conditions and take advantage of efficiencies gained when using uncoupled solution algorithms (like that within TRD1), an exact mode superposition method using MSC/NASTRAN DMAP has been developed and successfully implemented as an enhancement to an existing coupled loads methodology at the NASA Lewis Research Center

Cybervetting Perceptions of Job Seekers in Saudi Arabia

Organizations have leveraged the use of social media (SM) in recruitment and selection to reach a wider pool of job applicants. The purpose of this study is to understand the perceptions of job seekers in Saudi Arabia using the job seekers’ attitudes toward the cybervetting (ATC) scale. This research is a quantitative cross-sectional study in which an online questionnaire was distributed among the target population who were seeking jobs and using social media sites. The ATC was translated to Arabic language and back-translated to English language and administered to a sample of 160 job applicants. The results showed negative perceptions of social media use as a screening and selection tool. Moreover, respondents perceived cybervetting negatively on the three dimensions tested: justice perceptions, privacy invasion, and face validity. The findings of this study have practical implications for human resources managers about the use of social media as an employee selection tool

Improving Flexural Behavior of Textile Reinforced Concrete One Way Slab by Removing Weft Yarns with Different Percentages

Textile reinforced concrete that developed at recent years is composed of the continuous textile fabric incorporated into the cementitious matrix. The geometry of the textile reinforcements has a great influence on the TRC overall behavior since it affects the bond efficiency perfectly. The effect of weft yarns removing on the flexural behavior of (1500 × 500 × 50) mm one way slabs was investigated, eight layers of the carbon fabric were used with (50%, 67% and 75%) removing of weft yarns in addition to one specimen without removing. The four one- way slabs were casted by hand lay-up method, cured for (28) days and tested in flexure using four points method. The bending capacity and the bond efficiency factor were calculated according to the conditions of the equilibrium models by comparing with experimental results. The results revealed that with higher removing proportion there was a perfect improvement in the flexural capacity, higher first crack load, eminent post cracking stiffness, higher average concrete strain and lower ultimate mid span deflection and higher toughness and ductility. Furthermore, the results clarified that there is an optimum percent of weft yarns removing at which the damage occurrence around the weft yarns is significantly reduced, and this negative effect constriction overcome the positive anchoring effect

Thermal Effects on Compressive Strength of Local Limestone and Claystone

Limestone and claystone are widely used in rocky mountainous areas as building materials in Kurdistan region, in particular, the city of Koya. The outbreak of fire in buildings will have a great impact on strengths of building materials. The property performance of these local materials is heavenly understudied. This research investigates the impact of high temperature on the physicomechanical properties of limestone and claystone from Fatha Formation in Koya in Kurdistan region of Iraq. For this purpose, cores were taken from intact rocks; their ends were cut by a mechanical saw to obtain a cylindrical shape and immersed in water for 24 h, and then, subjected to physicomechanical tests of specific gravity, water absorption, porosity, and uniaxial compressive strength. For determining the residual compressive strength, the specimens were taken out from water, surface dried, and exposed to high temperatures of 450, and 650°C for 2 h using an electric oven. The results showed that claystone specimens show more stable mechanical properties than the limestone after exposure to high temperatures, and the high temperature causes lightening in color and significant cracks in both materials

Biotechnological applications of polymeric nanofiber platforms loaded with diverse bioactive materials

This review article highlights the critical research and formative works relating to nanofiber composites loaded with bioactive materials for diverse applications, and discusses the recent research on the use of electrospun nanofiber incorporating bioactive compounds such as essential oils, herbal bioactive components, plant extracts, and metallic nanoparticles. Inevitably, with the common advantages of bioactive components and polymer nanofibers, electrospun nanofibers containing bioactive components have attracted intense interests for their applications in biomedicine and cancer treatment. Many studies have only concentrated on the production and performance of electrospun nanofiber loaded with bioactive components; in this regard, the features of different types of electrospun nanofiber incorporating a wide variety of bioactive compounds and their developing trends are summarized and assessed in the present article, as is the feasible use of nanofiber technology to produce products on an industrial scale in different applications