Parallel MR image reconstruction using augmented Lagrangian methods

Magnetic resonance image (MRI) reconstruction using SENSitivity Encoding (SENSE) requires regularization to suppress noise and aliasing effects. Edge-preserving and sparsity-based regularization criteria can improve image quality, but they demand computation-intensive nonlinear optimization. In this paper, we present novel methods for regularized MRI reconstruction from undersampled sensitivity encoded data--SENSE-reconstruction--using the augmented Lagrangian (AL) framework for solving large-scale constrained optimization problems. We first formulate regularized SENSE-reconstruction as an unconstrained optimization task and then convert it to a set of (equivalent) constrained problems using variable splitting. We then attack these constrained versions in an AL framework using an alternating minimization method, leading to algorithms that can be implemented easily. The proposed methods are applicable to a general class of regularizers that includes popular edge-preserving (e.g., total-variation) and sparsity-promoting (e.g., l(1)-norm of wavelet coefficients) criteria and combinations thereof. Numerical experiments with synthetic and in vivo human data illustrate that the proposed AL algorithms converge faster than both general-purpose optimization algorithms such as nonlinear conjugate gradient (NCG) and state-of-the-art MFISTA.     

Cyclic Oxidation of P91 by Thermogravimetry and Investigation of Integrity of Scale by “Transient-Mass-Gain” Method

The growth and degradation of the oxide scale on modified 9Cr–1Mo ferritic steel was studied at 1123 K using a thermogravimetric balance by employing the “transient-mass-gain method” in conjunction with the adaptation of a cyclic-oxidation procedure. The total duration of the oxidation was 1000 h. The experiment revealed that the cracking of the scale was initiated when the average thickness was 72 μm. Spallation occurred when the average thickness was 75 μm. The rate of spallation was found to be enhanced as the scale thickens and attained a higher rate after 90 μm. The rate constants for the different stages of oxidation were found to be different. The specimen was examined by SEM, EDS and XRD. The scale morphology revealed outwardly protruded growth, a uniform adherent oxide layer and a spalled region. Four oxide phases were identified; Cr₂O₃, Fe₂O₃, (FeCr)₂O₃ and FeCr₂O₄. The spall contained more (FeCr)₂O₃ whereas the adherent scale was more FeCr₂O₄.     

A novel cross cosine map based medical image cryptosystem using dynamic bit-level diffusion

Multimedia Tools and Applications - Development in networking technology has made the remote diagnosis and treatment of patients a reality through telemedicine. At the same time, storing and...     

Effect of system optimizing conditions on biohydrogen production from herbal wastewater by slaughterhouse sludge

The study evaluates the biohydrogen production from herbal wastewater as the substrate by the enriched mixed slaughterhouse sludge as the seed source. In the following experiments, batch-fermentations are carried out with the optimum substrate concentrations, fermentation pH and fermentation temperature to observe the effects of H₂ production, hydrogen yield and other fermentation end products at different conditions. The hydrogen production is increased as substrate concentration increased up to 8 g COD/L WW, but drastically decreased at 10 g COD/L WW. When the pH of fermentation is controlled to 6.5, a maximum amount of hydrogen yield could be obtained. The hydrogen production is maximum at 50 °C (930 ± 30 mL/L WW) compared to 30 °C (436 ± 16 mL/L WW). Acid-forming pathway with butyric acid as a major metabolite dominated the metabolic flow during the hydrogen production. The experimental results indicated that effective hydrogen production from the herbal wastewater could be obtained by thermophilic acidogenesis at proper operational conditions.     

Application of EIS and SECM Studies for Investigation of Anticorrosion Properties of Epoxy Coatings containing ZrO2 Nanoparticles on Mild Steel in 3.5% NaCl Solution

Journal of Failure Analysis and Prevention - The effect of corrosion protection performance of epoxy coatings containing zirconium oxide (ZrO2) nanoparticles on carbon steel was analyzed using...     

A strategy for scheduling tightly coupled parallel applications on clusters

Although various strategies have been developed for scheduling parallel applications with independent tasks, very little work exists for scheduling tightly coupled parallel applications on cluster environments. In this paper, we compare four different strategies based on performance models of tightly coupled parallel applications for scheduling the applications on clusters. In addition to algorithms based on existing popular optimization techniques, we also propose a new algorithm called Box Elimination that searches the space of performance model parameters to determine the best schedule of machines. By means of real and simulation experiments, we evaluated the algorithms on single cluster and multi‐cluster setups. We show that our Box Elimination algorithm generates up to 80% more efficient schedules than other algorithms. We also show that the execution times of the schedules produced by our algorithm are more robust against the performance modeling errors. Copyright © 2009 John Wiley & Sons, Ltd.