Evaluation of 2D image reconstruction using fan-beam FBP algorithm with no backprojection weight from WLP completed truncated projection data

This paper presents the image reconstruction using the fan-beam filtered backprojection (FBP) algorithm with no backprojection weight from windowed linear prediction (WLP) completed truncated projection data. The image reconstruction from truncated projections aims to reconstruct the object accurately from the available limited projection data. Due to the incomplete projection data, the reconstructed image contains truncation artifacts which extends into the region of interest (ROI) making the reconstructed image unsuitable for further use. Data completion techniques have been shown to be effective in such situations. We use windowed linear prediction technique for projection completion and then use the fan-beam FBP algorithm with no backprojection weight for the 2-D image reconstruction. We evaluate the quality of the reconstructed image using fan-beam FBP algorithm with no backprojection weight after WLP completion.

Cation-templated 2-D Mn(II)-oxalate framework with an acyclic tetrameric water cluster

The single-crystal X-ray structure of a cation-templated manganese-oxalate coordination polymer [NH(C2H5)(3)][Mn-2(ox)(3)]center dot(5H(2)O)] (1) is reported. In 1, triethylammonium cation is entrapped between the cavities of 2-D honeycomb layers constructed by oxalate and water. The acyclic tetrameric water clusters and discrete water assemble the parallel 2-D honeycomb oxalate layers via an intricate array of hydrogen bonds into an overall 3-D network. The magnetic susceptibility, with and without the water cluster, are reported with infrared and EPR studies.

A multichannel sampling method for 2-D finite-rate-of-innovation signals

We address the problem of sampling and reconstruction of two-dimensional (2-D) finite-rate-of-innovation (FRI) signals. We propose a three-channel sampling method for efficiently solving the problem. We consider the sampling of a stream of 2-D Dirac impulses and a sum of 2-D unit-step functions. We propose a 2-D causal exponential function as the sampling kernel. By causality in 2-D, we mean that the function has its support restricted to the first quadrant. The advantage of using a multichannel sampling method with causal exponential sampling kernel is that standard annihilating filter or root-finding algorithms are not required. Further, the proposed method has inexpensive hardware implementation and is numerically stable as the number of Dirac impulses increases.

Constraining complex aquifer geometry with geophysics (2-D ERT and MRS measurements) for stochastic modelling of groundwater flow

Stochastic modelling is a useful way of simulating complex hard-rock aquifers as hydrological properties (permeability, porosity etc.) can be described using random variables with known statistics. However, very few studies have assessed the influence of topological uncertainty (i.e. the variability of thickness of conductive zones in the aquifer), probably because it is not easy to retrieve accurate statistics of the aquifer geometry, especially in hard rock context. In this paper, we assessed the potential of using geophysical surveys to describe the geometry of a hard rock-aquifer in a stochastic modelling framework. The study site was a small experimental watershed in South India, where the aquifer consisted of a clayey to loamy-sandy zone (regolith) underlain by a conductive fissured rock layer (protolith) and the unweathered gneiss (bedrock) at the bottom. The spatial variability of the thickness of the regolith and fissured layers was estimated by electrical resistivity tomography (ERT) profiles, which were performed along a few cross sections in the watershed. For stochastic analysis using Monte Carlo simulation, the generated random layer thickness was made conditional to the available data from the geophysics. In order to simulate steady state flow in the irregular domain with variable geometry, we used an isoparametric finite element method to discretize the flow equation over an unstructured grid with irregular hexahedral elements. The results indicated that the spatial variability of the layer thickness had a significant effect on reducing the simulated effective steady seepage flux and that using the conditional simulations reduced the uncertainty of the simulated seepage flux. As a conclusion, combining information on the aquifer geometry obtained from geophysical surveys with stochastic modelling is a promising methodology to improve the simulation of groundwater flow in complex hard-rock aquifers. (C) 2013 Elsevier B.V. All rights reserved.

On 2-D Non-Adjacent-Error Channel Models

In this work, we consider two-dimensional (2-D) binary channels in which the 2-D error patterns are constrained so that errors cannot occur in adjacent horizontal or vertical positions. We consider probabilistic and combinatorial models for such channels. A probabilistic model is obtained from a 2-D random field defined by Roth, Siegel and Wolf (2001). Based on the conjectured ergodicity of this random field, we obtain an expression for the capacity of the 2-D non-adjacent-errors channel. We also derive an upper bound for the asymptotic coding rate in the combinatorial model.

Germanane: a Low Effective Mass and High Bandgap 2-D Channel Material for Future FETs

We investigate the electronic properties of Germanane and analyze its importance as 2-D channel material in switching devices. Considering two types of morphologies, namely, chair and boat, we study the real band structure, the effective mass variation, and the complex band structure of unstrained Germanane by density-functional theory. The chair morphology turns out to be a more effective channel material for switching devices than the boat morphology. Furthermore, we study the effect of elastic strain, van der Waals force, and vertical electric field on these band structure properties. Due to its very low effective mass with relatively high-energy bandgap, in comparison with the other 2-D materials, Germanane appears to provide superior performance in switching device applications.

Exact Phase Retrieval for a Class of 2-D Parametric Signals

We address the problem of two-dimensional (2-D) phase retrieval from magnitude of the Fourier spectrum. We consider 2-D signals that are characterized by first-order difference equations, which have a parametric representation in the Fourier domain. We show that, under appropriate stability conditions, such signals can be reconstructed uniquely from the Fourier transform magnitude. We formulate the phase retrieval problem as one of computing the parameters that uniquely determine the signal. We show that the problem can be solved by employing the annihilating filter method, particularly for the case when the parameters are distinct. For the more general case of the repeating parameters, the annihilating filter method is not applicable. We circumvent the problem by employing the algebraically coupled matrix pencil (ACMP) method. In the noiseless measurement setup, exact phase retrieval is possible. We also establish a link between the proposed analysis and 2-D cepstrum. In the noisy case, we derive Cramer-Rao lower bounds (CRLBs) on the estimates of the parameters and present Monte Carlo performance analysis as a function of the noise level. Comparisons with state-of-the-art techniques in terms of signal reconstruction accuracy show that the proposed technique outperforms the Fienup and relaxed averaged alternating reflections (RAAR) algorithms in the presence of noise.

Timing Recovery Algorithms and Architectures for 2-D Magnetic Recording Systems

We investigate the problem of timing recovery for 2-D magnetic recording (TDMR) channels. We develop a timing error model for TDMR channel considering the phase and frequency offsets with noise. We propose a 2-D data-aided phase-locked loop (PLL) architecture for tracking variations in the position and movement of the read head in the down-track and cross-track directions and analyze the convergence of the algorithm under non-separable timing errors. We further develop a 2-D interpolation-based timing recovery scheme that works in conjunction with the 2-D PLL. We quantify the efficiency of our proposed algorithms by simulations over a 2-D magnetic recording channel with timing errors.

Perturbational Finite Volume Method For The Solution of 2-D Navier-Stokes Equations on Unstructured and Structured Colocated Meshes

Based on the first-order upwind and second-order central type of finite volume( UFV and CFV) scheme, upwind and central type of perturbation finite volume ( UPFV and CPFV) schemes of the Navier-Stokes equations were developed. In PFV method, the mass fluxes of across the cell faces of the control volume (CV) were expanded into power series of the grid spacing and the coefficients of the power series were determined by means of the conservation equation itself. The UPFV and CPFV scheme respectively uses the same nodes and expressions as those of the normal first-order upwind and second-order central scheme, which is apt to programming. The results of numerical experiments about the flow in a lid-driven cavity and the problem of transport of a scalar quantity in a known velocity field show that compared to the first-order UFV and second-order CFV schemes, upwind PFV scheme is higher accuracy and resolution, especially better robustness. The numerical computation to flow in a lid-driven cavity shows that the under-relaxation factor can be arbitrarily selected ranging from 0.3 to 0. 8 and convergence perform excellent with Reynolds number variation from 102 to 104.

Symmetrical 2-D Hermite-Gaussian square launch for high bit rate transmission in multimode fiber links

A 2-D Hermite-Gaussian square launch is demonstrated to show improved systems capacity over multimode fiber links. It shows a bandwidth improvement over both center and offset launches and exhibits ±5 μm misalignment tolerance. © 2011 Optical Society of America.