Correction to: Buckling of magneto-electro-hygro-thermal piezoelectric nanoplates system embedded in a visco-Pasternak medium based on nonlocal theory

Microsystem Technologies - The original version of this article unfortunately contained a mistake. Farzad Ebrahimi was not listed among the authors.     

Postbuckling analysis of piezoelectric multiscale sandwich composite doubly curved porous shallow shells via Homotopy Perturbation Method

In this study postbuckling behaviors of multiscale composite sandwich doubly curved piezoelectric shell with a flexible core and MR layers by employing Homotopy Perturbation Method in hygrothermal environment has been investigated. By using Reddy third shear deformable theory the face sheets and third-order polynomial theory of the flexible core the strains and stresses are obtained. A mathematical model for the multiscale composite layered shell with a flexible core and magnetorheological layer (MR) that incorporates the nonlinearity of the in-plane and the vertical displacements of the core is assumed. Three-phase composite shells with polymer/Carbon nanotube/fiber and polymer/Graphene platelet/fiber either uniformly or non-uniformly based on different patterns according to Halpin–Tsai model have been considered. The governing equations of multiscale shell have been derived by implementing Hamilton’s principle. Meanwhile, simply supported boundary conditions are employed to the shell. For investigating correctness and accuracy, this paper is validated by other previous researches. Finally, different parameters such as temperature rise, various distribution patterns, magnetic fields and curvature ratio are considered in this article. It is found these parameters have significant effect on the frequency–amplitude curves.

     

A two-phase mathematical-programming heuristic for flexible assignment of activities and tasks to work shifts

In the service industry, workers perform work shifts and are assigned to interruptible activities and uninterruptible tasks during their shifts. The work shifts of regular employees are often established several weeks in advance of the operations when the activity and task demands are still uncertain. Just a few days before the operations when these demands are unveiled with more certainty, the planned schedules can be slightly modified and on-call temporary employees can be scheduled to satisfy the demands as best as possible. As acceptable modifications, extending the planned shifts and moving workers’ meal breaks are considered. In this paper, we are interested in the scheduling problem encountered in this second step, which also involves assigning activities and tasks to the scheduled work shifts. To produce good-quality solutions in fast computational times for large-sized instances, we develop a two-phase heuristic. In the first phase, an approximate mixed-integer programming model is used to suggest temporary shifts and extensions to regular shifts and to schedule and assign tasks. In the second phase, a column-generation heuristic embedded in a rolling horizon procedure determines the final shifts and assigns activities to them. Computational results obtained on randomly generated instances are reported to evaluate the validity of the proposed solution method.     

Application of a wire-grid-mirror liquid-crystal light valve in a nonlinear joint transform correlator

We describe the operation of a wire-grid-mirror liquid-crystal light valve and its use for optical pattern recognition. The nonlinear characteristic of the wire-grid-mirror liquid-crystal light valve is used to implement the nonlinear joint transform correlator. Experimental results and computer simulations show that the nonlinear characteristic of the wire-grid-mirror liquid-crystal light valve can produce a well-defined correlation peak and low output background. The performance of the nonlinear joint transform correlator obtained when the wire-grid-mirror liquid-crystal light valve is used is compared with that of the binary joint transform correlator.     

Analysis of image detection based on fourier plane nonlinear filtering in a joint transform correlator

Signal and image and detection systems based on nonlinear operations of Fourier-transformed data often exhibit greater selectivity than standard matched-filtering techniques. One such system is the joint transform correlator. We analyze the performance of the nonlinear joint transform correlator in terms of the output signal-to-noise ratio; this signal-to-noise ratio is evaluated in terms of both output contrast (peak-to-noise floor) and output variability (peak-to-peak standard deviation). The main assumption used is that the signal energy is small relative to that of the additive noise; this assumption is defensible in practice owing to the generally small spatial extent of target images relative to scenes. With respect to the first performance measure, this study is an extension of that in an earlier paper [Appl. Opt. 34, 5218 (1995)]. The previous analysis was carried out under a restriction that the signal and noise spectra were to be similar (actually multiples of one another). In the current study there is no such constraint, and all analysis of the second measure is new. The analysis is supported by simulation. A benefit of analytical rather than simulational study is that conclusions can be drawn with greater confidence. One of the most interesting of these is that the smooth square-root Fourier plane nonlinearity, more usually known as the k-law processor with k = 0.5, offers extremely robust performance with respect to relative noise bandwidth.     

A constrained optimization approach for an adaptive generalized subspace tracking algorithm

In this paper, we present an orthonormal version of the generalized signal subspace tracking. It is based on an interpretation of the generalized signal subspace as the solution of a constrained minimization task. This algorithm, referred to as the CGST algorithm, guarantees the C_x-orthonormality of the estimated generalized signal subspace basis at each iteration which C_x denotes the correlation matrix of the sequence x(t). An efficient implementation of the proposed algorithm enhances applicability of it in real time applications.