Newton-based stochastic optimization using q-Gaussian smoothed functional algorithms

We present the first q-Gaussian smoothed functional (SF) estimator of the Hessian and the first Newton-based stochastic optimization algorithm that estimates both the Hessian and the gradient of the objective function using q-Gaussian perturbations. Our algorithm requires only two system simulations (regardless of the parameter dimension) and estimates both the gradient and the Hessian at each update epoch using these. We also present a proof of convergence of the proposed algorithm. In a related recent work (Ghoshdastidar, Dukkipati, & Bhatnagar, 2014), we presented gradient SF algorithms based on the q-Gaussian perturbations. Our work extends prior work on SF algorithms by generalizing the class of perturbation distributions as most distributions reported in the literature for which SF algorithms are known to work turn out to be special cases of the q-Gaussian distribution. Besides studying the convergence properties of our algorithm analytically, we also show the results of numerical simulations on a model of a queuing network, that illustrate the significance of the proposed method. In particular, we observe that our algorithm performs better in most cases, over a wide range of q-values, in comparison to Newton SF algorithms with the Gaussian and Cauchy perturbations, as well as the gradient q-Gaussian SF algorithms. (C) 2014 Elsevier Ltd. All rights reserved.

A bottom-up approach for optimization of friction stir processing parameters; a study on aluminium 2024-T3 alloy

Friction stir processing (FSP) is emerging as one of the most competent severe plastic deformation (SPD) method for producing bulk ultra-fine grained materials with improved properties. Optimizing the process parameters for a defect free process is one of the challenging aspects of FSP to mark its commercial use. For the commercial aluminium alloy 2024-T3 plate of 6 mm thickness, a bottom-up approach has been attempted to optimize major independent parameters of the process such as plunge depth, tool rotation speed and traverse speed. Tensile properties of the optimum friction stir processed sample were correlated with the microstructural characterization done using Scanning Electron Microscope (SEM) and Electron Back-Scattered Diffraction (EBSD). Optimum parameters from the bottom-up approach have led to a defect free FSP having a maximum strength of 93% the base material strength. Micro tensile testing of the samples taken from the center of processed zone has shown an increased strength of 1.3 times the base material. Measured maximum longitudinal residual stress on the processed surface was only 30 MPa which was attributed to the solid state nature of FSP. Microstructural observation reveals significant grain refinement with less variation in the grain size across the thickness and a large amount of grain boundary precipitation compared to the base metal. The proposed experimental bottom-up approach can be applied as an effective method for optimizing parameters during FSP of aluminium alloys, which is otherwise difficult through analytical methods due to the complex interactions between work-piece, tool and process parameters. Precipitation mechanisms during FSP were responsible for the fine grained microstructure in the nugget zone that provided better mechanical properties than the base metal. (C) 2014 Elsevier Ltd. All rights reserved.

Formation of hierarchical structures of Fe2O3 by the liquid-liquid interface technique

We report the formation of dendritic hierarchical structures of alpha-Fe2O3 and nanostructures of Fe2O3 by the simple liquid-liquid interface method. The morphology of thin films determined by high-resolution scanning electron microscopy shows nanorods, nanosheets and dendritic Fe2O3. The identification of phases of iron oxide structures is carried out by using XRD and XPS studies. XRD and XPS measurements point out the highly crystalline dendritic alpha-Fe2O3 phase and the mixed phase of alpha- and gamma-Fe2O3 nanostructures. The magnetic measurement also suggests the presence of a mixed phase in the sample grown for 72 hours.

Optimal error estimate using mesh equidistribution technique for singularly perturbed system of reaction-diffusion boundary-value problems

In this article, we study the problem of determining an appropriate grading of meshes for a system of coupled singularly perturbed reaction-diffusion problems having diffusion parameters with different magnitudes. The central difference scheme is used to discretize the problem on adaptively generated mesh where the mesh equation is derived using an equidistribution principle. An a priori monitor function is obtained from the error estimate. A suitable a posteriori analogue of this monitor function is also derived for the mesh construction which will lead to an optimal second-order parameter uniform convergence. We present the results of numerical experiments for linear and semilinear reaction-diffusion systems to support the effectiveness of our preferred monitor function obtained from theoretical analysis. (C) 2014 Elsevier Inc. All rights reserved.

Simultaneous Perturbation Newton Algorithms for Simulation Optimization

We present a new Hessian estimator based on the simultaneous perturbation procedure, that requires three system simulations regardless of the parameter dimension. We then present two Newton-based simulation optimization algorithms that incorporate this Hessian estimator. The two algorithms differ primarily in the manner in which the Hessian estimate is used. Both our algorithms do not compute the inverse Hessian explicitly, thereby saving on computational effort. While our first algorithm directly obtains the product of the inverse Hessian with the gradient of the objective, our second algorithm makes use of the Sherman-Morrison matrix inversion lemma to recursively estimate the inverse Hessian. We provide proofs of convergence for both our algorithms. Next, we consider an interesting application of our algorithms on a problem of road traffic control. Our algorithms are seen to exhibit better performance than two Newton algorithms from a recent prior work.

Optimal control of grinding mill circuit using model predictive static programming: A new nonlinear MPC paradigm

The recently developed reference-command tracking version of model predictive static programming (MPSP) is successfully applied to a single-stage closed grinding mill circuit. MPSP is an innovative optimal control technique that combines the philosophies of model predictive control (MPC) and approximate dynamic programming. The performance of the proposed MPSP control technique, which can be viewed as a `new paradigm' under the nonlinear MPC philosophy, is compared to the performance of a standard nonlinear MPC technique applied to the same plant for the same conditions. Results show that the MPSP control technique is more than capable of tracking the desired set-point in the presence of model-plant mismatch, disturbances and measurement noise. The performance of MPSP and nonlinear MPC compare very well, with definite advantages offered by MPSP. The computational speed of MPSP is increased through a sequence of innovations such as the conversion of the dynamic optimization problem to a low-dimensional static optimization problem, the recursive computation of sensitivity matrices and using a closed form expression to update the control. To alleviate the burden on the optimization procedure in standard MPC, the control horizon is normally restricted. However, in the MPSP technique the control horizon is extended to the prediction horizon with a minor increase in the computational time. Furthermore, the MPSP technique generally takes only a couple of iterations to converge, even when input constraints are applied. Therefore, MPSP can be regarded as a potential candidate for online applications of the nonlinear MPC philosophy to real-world industrial process plants. (C) 2014 Elsevier Ltd. All rights reserved.

Multispectral Bayesian reconstruction technique for real-time two color fluorescence microscopy

We have developed a real-time imaging method for two-color wide-field fluorescence microscopy using a combined approach that integrates multi-spectral imaging and Bayesian image reconstruction technique. To enable simultaneous observation of two dyes (primary and secondary), we exploit their spectral properties that allow parallel recording in both the channels. The key advantage of this technique is the use of a single wavelength of light to excite both the primary dye and the secondary dye. The primary and secondary dyes respectively give rise to fluorescence and bleed-through signal, which after normalization were merged to obtain two-color 3D images. To realize real-time imaging, we employed maximum likelihood (ML) and maximum a posteriori (MAP) techniques on a high-performance computing platform (GPU). The results show two-fold improvement in contrast while the signal-to-background ratio (SBR) is improved by a factor of 4. We report a speed boost of 52 and 350 for 2D and 3D images respectively. Using this system, we have studied the real-time protein aggregation in yeast cells and HeLa cells that exhibits dot-like protein distribution. The proposed technique has the ability to temporally resolve rapidly occurring biological events.

Image-Segmentation Technique to Analyze Deformation Profiles in Different Direct Shear Tests

Results from interface shear tests on sand-geosynthetic interfaces are examined in light of surface roughness of the interacting geosynthetic material. Three different types of interface shear tests carried out in the frame of direct shear-test setup are compared to understand the effect of parameters like box fixity and symmetry on the interface shear characteristics. Formation of shear bands close to the interface is visualized in the tests and the bands are analyzed using image-segmentation techniques in MATLAB. A woven geotextile with moderate roughness and a geomembrane with minimal roughness are used in the tests. The effect of surface roughness of the geosynthetic material on the formation of shear bands, movement of sand particles, and interface shear parameters are studied and compared through visual observations, image analyses, and image-segmentation techniques.

Space-Vector-Based Hybrid PWM Technique to Reduce Peak-to-Peak Torque Ripple in Induction Motor Drives

Special switching sequences involving division of active state time are used in space-vector-based generation of pulse width modulation (PWM) waveforms. This paper proposes a hybrid PWM technique which is a combination of the conventional and special switching sequences. The proposed hybrid PWM technique reduces the peak-to-peak torque ripple at high speeds of an induction motor drive. Supporting simulation and experimental results are presented from a closed-loop controlled motor drive.

Unraveling the nature of electric field- and stress- induced structural transformations in soft PZT by a new powder poling technique

A `powder-poling' technique was developed to study electric field induced structural transformations in ferroelectrics exhibiting a morphotropic phase boundary (MPB). The technique was employed on soft PZT exhibiting a large longitudinal piezoelectric response (d(33) similar to 650 pCN(-1)). It was found that electric poling brings about a considerable degree of irreversible tetragonal to monoclinic transformation. The same transformation was achieved after subjecting the specimen to mechanical stress, which suggests an equivalence of stress and electric field with regard to the structural mechanism in MPB compositions. The electric field induced structural transformation was also found to be accompanied by a decrease in the spatial coherence of polarization.

Manipulating Crystallographic Texture of Sn Coatings by Optimization of Electrodeposition Process Conditions to Suppress Growth of Whiskers

The effects of two major electrodeposition process conditions, electrolyte bath temperature and current density, on the microstructure and crystallographic texture of pure tin coatings on brass and, ultimately, on the extent of whisker formation have been examined. The grain size of the deposited coatings increased with increasing electrolyte bath temperature and current density, which significantly affected the dominant texture: (211) or (420) was the dominant texture at low current densities whereas, depending on deposition temperature, (200) or (220) became the dominant texture at high current densities. After deposition, coatings were subjected to different environmental conditions, for example isothermal aging (room temperature, 50A degrees C, or 150A degrees C) for up to 90 days and thermal cycling between -25A degrees C and 85A degrees C for 100 cycles, and whisker growth was studied. The Sn coatings with low Miller index planes, for example (200) and (220), and with moderate aging temperature were more prone to whiskering than coating with high Miller index planes, for example (420), and high aging temperature. A processing route involving the optimum combination of current density and deposition temperature is proposed for suppressing whisker growth.

Validation of polyvinylidene fluoride nasal sensor to assess nasal obstruction in comparison with subjective technique

Objective: The aim of this study is to validate the applicability of the PolyVinyliDene Fluoride (PVDF) nasal sensor to assess the nasal airflow, in healthy subjects and patients with nasal obstruction and to correlate the results with the score of Visual Analogue Scale (VAS). Methods: PVDF nasal sensor and VAS measurements were carried out in 50 subjects (25-healthy subjects and 25 patients). The VAS score of nasal obstruction and peak-to-peak amplitude (Vp-p) of nasal cycle measured by PVDF nasal sensors were analyzed for right nostril (RN) and left nostril (LN) in both the groups. Spearman's rho correlation was calculated. The relationship between PVDF nasal sensor measurements and severity of nasal obstruction (VAS score) were assessed by ANOVA. Results: In healthy group, the measurement of nasal airflow by PVDF nasal sensor for RN and LN were found to be 51.14 +/- 5.87% and 48.85 +/- 5.87%, respectively. In patient group, PVDF nasal sensor indicated lesser nasal airflow in the blocked nostrils (RN: 23.33 +/- 10.54% and LN: 32.24 +/- 11.54%). Moderate correlation was observed in healthy group (r = 0.710, p < 0.001 for RN and r = 0.651, p < 0.001 for LN), and moderate to strong correlation in patient group (r = 0.751, p < 0.01 for RN and r = 0.885, p < 0.0001 for LN). Conclusion: PVDF nasal sensor method is a newly developed technique for measuring the nasal airflow. Moderate to strong correlation was observed between PVDF nasal sensor data and VAS scores for nasal obstruction. In our present study, PVDF nasal sensor technique successfully differentiated between healthy subjects and patients with nasal obstruction. Additionally, it can also assess severity of nasal obstruction in comparison with VAS. Thus, we propose that the PVDF nasal sensor technique could be used as a new diagnostic method to evaluate nasal obstruction in routine clinical practice. (C) 2015 Elsevier Inc. All rights reserved.

Spatial filter based light-sheet laser interference technique for three-dimensional nanolithography

We propose a laser interference technique for the fabrication of 3D nano-structures. This is possible with the introduction of specialized spatial filter in a 2 pi cylindrical lens system (consists of two opposing cylindrical lens sharing a common geometrical focus). The spatial filter at the back-aperture of a cylindrical lens gives rise to multiple light-sheet patterns. Two such interfering counter-propagating light-sheet pattern result in periodic 3D nano-pillar structure. This technique overcomes the existing slow point-by-point scanning, and has the ability to pattern selectively over a large volume. The proposed technique allows large-scale fabrication of periodic structures. Computational study shows a field-of-view (patterning volume) of approximately 12: 2mm(3) with the pillar-size of 80 nm and inter-pillar separation of 180 nm. Applications are in nano-waveguides, 3D nano-electronics, photonic crystals, and optical microscopy. (C) 2015 AIP Publishing LLC.

A Digital Frequency Multiplication Technique for Energy Efficient Transmitters

A logic gate-based digital frequency multiplication technique for low-power frequency synthesis is presented. The proposed digital edge combining approach offers broadband operation with low-power and low-area advantages and is a promising candidate for low-power frequency synthesis in deep submicrometer CMOS technologies. Chip prototype of the proposed frequency multiplication-based 2.4-GHz binary frequency-shift-keying (BFSK)/amplitude shift keying (ASK) transmitter (TX) was fabricated in 0.13-mu m CMOS technology. The TX achieves maximum data rates of 3 and 20 Mb/s for BFSK and ASK modulations, respectively, consuming a 14-mA current from 1.3 V supply voltage. The corresponding energy efficiencies of the TX are 3.6 nJ/bit for BFSK and 0.91 nJ/bit for ASK modulations.

MRT Letter: A Unified Accelerated Maximum Likelihood Technique for Widefield, Confocal, and Super-Resolution 4Pi Microscopy

We propose an algorithmic technique for accelerating maximum likelihood (ML) algorithm for image reconstruction in fluorescence microscopy. This is made possible by integrating Biggs-Andrews (BA) method with ML approach. The results on widefield, confocal, and super-resolution 4Pi microscopy reveal substantial improvement in the speed of 3D image reconstruction (the number of iterations has reduced by approximately one-half). Moreover, the quality of reconstruction obtained using accelerated ML closely resembles with nonaccelerated ML method. The proposed technique is a step closer to realize real-time reconstruction in 3D fluorescence microscopy. Microsc. Res. Tech. 78:331-335, 2015. (c) 2015 Wiley Periodicals, Inc.