On maximum entropy and minimum KL-divergence optimization by Grobner basis methods

In this paper we study constrained maximum entropy and minimum divergence optimization problems, in the cases where integer valued sufficient statistics exists, using tools from computational commutative algebra. We show that the estimation of parametric statistical models in this case can be transformed to solving a system of polynomial equations. We give an implicit description of maximum entropy models by embedding them in algebraic varieties for which we give a Grobner basis method to compute it. In the cases of minimum KL-divergence models we show that implicitization preserves specialization of prior distribution. This result leads us to a Grobner basis method to embed minimum KL-divergence models in algebraic varieties. (C) 2012 Elsevier Inc. All rights reserved.

Dual functional performance of fiber Bragg gratings coated with metals using flash evaporation technique

Metallic and other type of coatings on fiber Bragg grating (FBG) sensors alter their sensitivity with thermal and mechanical stress while protecting the fragile optical fiber in harsh sensing surroundings. The behavior of the coated materials is unique in their response to thermal and mechanical stress depending on the thickness and the mode of coating. The thermal stress during the coating affects the temperature sensitivity of FBG sensors. We have explored the thermal response of FBGs coated with Al and Pb to an average thickness of 80 nm using flash evaporation technique where the FBG sensor is mounted in a region at room temperature in an evacuated chamber having a pressure of 10(6) Torr which will minimize any thermal stress during the coating process. The coating thickness is chosen in the nanometer region with the aim to study thermal behavior of nanocoatings and their effect on FBG sensitivity. The sensitivity of FBGs is evaluated from the wavelengths recorded using an optical sensing interrogator sm 130 (Micron Optics) from room temperature to 300 degrees C both during heating and cooling. It is observed that the sensitivity of the metal coated fibers is better than the reference FBG with no coating for the entire range of temperature. For a coating thickness of 80 nm, Al coated FBG is more sensitive than the one coated with Pb up to 170 degrees C and it reverses at higher temperatures. This point is identified as a reversible phase transition in Pb monolayers as the 2-dimensional aspects of the metal layers are dominant in the nanocoatings of Pb. On cooling, the phase transition reverses and the FBGs return to the original state and for repeated cycles of heating and cooling the same pattern is observed. Thus the FBG functions as a sensor of the phase transitions of the coatings also. (C) 2012 Elsevier Inc. All rights reserved.

An experimental study on cracking evolution in concrete and cement mortar by the b-value analysis of acoustic emission technique

Notched three point bend (TPB) specimens made with plain concrete and cement mortar were tested under crack mouth opening displacement (CMOD) control at a rate of 0.0004 mm/s and simultaneously acoustic emissions (AE) released were recorded during the experiments. Amplitude distribution analysis of AE released during concrete was carried out to study the development of fracture process in concrete and mortar specimens. The slope of the log-linear frequency-amplitude distribution of AE is known as the AE based b-value. The AE based b-value was computed in terms of physical process of time varying applied load using cumulative frequency distribution (Gutenberg-Richter relationship) and discrete frequency distribution (Aki's method) of AE released during concrete fracture. AE characteristics of plain concrete and cement mortar were studied and discussed and it was observed that the AE based b-value analysis serves as a tool to identify the damage in concrete structural members. (C) 2012 Elsevier Ltd. All rights reserved.

A Technique to Compute Smooth Amplitude, Phase, and Frequency Modulations From the Analytic Signal

Gabor's analytic signal (AS) is a unique complex signal corresponding to a real signal, but in general, it admits infinitely-many combinations of amplitude and frequency modulations (AM and FM, respectively). The standard approach is to enforce a non-negativity constraint on the AM, but this results in discontinuities in the corresponding phase modulation (PM), and hence, an FM with discontinuities particularly when the underlying AM-FM signal is over-modulated. In this letter, we analyze the phase discontinuities and propose a technique to compute smooth AM and FM from the AS, by relaxing the non-negativity constraint on the AM. The proposed technique is effective at handling over-modulated signals. We present simulation results to support the theoretical calculations.

AIWIN - A fast and jigless inspection technique for machined parts

Precision inspection of manufactured components having multiple complex surfaces and variable tolerance definition is an involved, complex and time-consuming function. In routine practice, a jig is used to present the part in a known reference frame to carry out the inspection process. Jigs involve both time and cost in their development, manufacture and use. This paper describes 'as is where is inspection' (AIWIN), a new automated inspection technique that accelerates the inspection process by carrying out a fast registration procedure and establishing a quick correspondence between the part to inspect and its CAD geometry. The main challenge in doing away with a jig is that the inspection reference frame could be far removed from the CAD frame. Traditional techniques based on iterative closest point (ICP) or Newton methods require either a large number of iterations for convergence or fail in such a situation. A two-step coarse registration process is proposed to provide a good initial guess for a modified ICP algorithm developed earlier (Ravishankar et al., Int J Adv Manuf Technol 46(1-4):227-236, 2010). The first step uses a calibrated sphere for local hard registration and fixing the translation error. This transformation locates the centre for the sphere in the CAD frame. In the second step, the inverse transformation (involving pure rotation about multiple axes) required to align the inspection points measured on the manufactured part with the CAD point dataset of the model is determined and enforced. This completes the coarse registration enabling fast convergence of the modified ICP algorithm. The new technique has been implemented on complex freeform machined components and the inspection results clearly show that the process is precise and reliable with rapid convergence. © 2011 Springer-Verlag London Limited.

Effect of doping concentration on the structural and optical properties of pure and tin doped zinc oxide thin films by nebulizer spray pyrolysis (NSP) technique

Pure and tin doped zinc oxide (Sn:ZnO) thin films were prepared for the first time by NSP technique using aqueous solutions of zinc acetate dehydrate, tin (IV) chloride fendahydrate and methanol. X-ray diffraction patterns confirm that the films are polycrystalline in nature exhibiting hexagonal wurtzite type, with (0 0 2) as preferred orientation. The structural parameters such as lattice constant ('a' and `c'), crystallite size, dislocation density, micro strain, stress and texture coefficient were calculated from X-ray diffraction studies. Surface morphology was found to be modified with increasing Sn doping concentration. The ZnO films have high transmittance 85% in the visible region, and the transmittance is found to be decreased with the increase of Sn doping concentration. The corresponding optical band gap decreases from 3.25 to 3.08 eV. Room temperature photoluminescence reveals the sharp emission of strong UV peak at 400 nm (3.10 eV) and a strong sharp green luminescence at 528 nm (2.34 eV) in the Sn doped ZnO films. The electrical resistivity is found to be 10(6) Omega-cm at higher temperature and 10(5) Omega-cm at lower temperature. (C) 2012 Elsevier Ltd. All rights reserved.

Data-resolution based optimization of the data-collection strategy for near infrared diffuse optical tomography

Purpose: To optimize the data-collection strategy for diffuse optical tomography and to obtain a set of independent measurements among the total measurements using the model based data-resolution matrix characteristics. Methods: The data-resolution matrix is computed based on the sensitivity matrix and the regularization scheme used in the reconstruction procedure by matching the predicted data with the actual one. The diagonal values of data-resolution matrix show the importance of a particular measurement and the magnitude of off-diagonal entries shows the dependence among measurements. Based on the closeness of diagonal value magnitude to off-diagonal entries, the independent measurements choice is made. The reconstruction results obtained using all measurements were compared to the ones obtained using only independent measurements in both numerical and experimental phantom cases. The traditional singular value analysis was also performed to compare the results obtained using the proposed method. Results: The results indicate that choosing only independent measurements based on data-resolution matrix characteristics for the image reconstruction does not compromise the reconstructed image quality significantly, in turn reduces the data-collection time associated with the procedure. When the same number of measurements (equivalent to independent ones) are chosen at random, the reconstruction results were having poor quality with major boundary artifacts. The number of independent measurements obtained using data-resolution matrix analysis is much higher compared to that obtained using the singular value analysis. Conclusions: The data-resolution matrix analysis is able to provide the high level of optimization needed for effective data-collection in diffuse optical imaging. The analysis itself is independent of noise characteristics in the data, resulting in an universal framework to characterize and optimize a given data-collection strategy. (C) 2012 American Association of Physicists in Medicine. http://dx.doi.org/10.1118/1.4736820]

Optimization of thermoacoustic primemover using response surface methodology

Thermoacoustic engines are energy conversion devices that convert thermal energy from a high-temperature heat source into useful work in the form of acoustic power while diverting waste heat into a cold sink; it can be used as a drive for cryocoolers and refrigerators. Though the devices are simple to fabricate, it is very challenging to design an optimized thermoacoustic primemover with better performance. The study presented here aims to optimize the thermoacoustic primemover using response surface methodology. The influence of stack position and its length, resonator length, plate thickness, and plate spacing on pressure amplitude and frequency in a thermoacoustic primemover is investigated in this study. For the desired frequency of 207 Hz, the optimized value of the above parameters suggested by the response surface methodology has been conducted experimentally, and simulations are also performed using DeltaEC. The experimental and simulation results showed similar output performance.

Variation of Snowline and Mass Balance of Glaciers of Warwan and Bhut Basins of Western Himalaya Using Remote Sensing Technique

Glaciers are natural reservoirs of fresh water in frozen state and sensitive indicators of climate change. Among all the mountainous glaciated regions, glaciers of Himalayas form one of the largest concentrations of ice outside the Polar Regions. Almost all the major rivers of northern India originate from these glaciers and sustain perennial flow. Therefore, in view of the importance and role of the glaciers in sustaining the life on the Earth, monitoring the health of glaciers is necessary. Glacier's health is monitored in two ways (i) by mapping the change in extent of glaciers (ii) by finding variation in the annual mass balance. This paper has been discussed the later approach for monitoring the health of glaciers of Warwan and Bhut basins. Mass balance of glaciers of these two basins was determined based on the extraction of snow line at the end of ablation season. A series of satellite images of AWiFS sensor were analysed for extraction of snowline on the glaciers for the period of 2005, 2006 and 2007. The snow line at the end of ablation season is used to compute accumulation area ratio (AAR = Accumulation area/Glacier area) for each glacier of basins. An approach based on relationship of AAR to specific mass balance (computed in field) for glaciers of Basapa basin was employed in the present study. Mean of specific mass balance of individual glacier for the year 2005, 2006 and 2007 of Warwan basin was found to be -ve 0.19 m, -ve 0.27 m and -ve 0.2 m respectively. It is 0.05 m, -ve 0.11 m and -ve 0.19 m for Bhut basin. The analysis suggests a loss of 4.3 and 0.83 kmA(3) of glacier in the monitoring period of 3 years for Warwan and Bhut basins respectively. The overall results suggest that the glaciers of Warwan basin and Bhut basins have suffered more loss of ice than gain in the monitoring period of 3 years.

MPI-based parallel synchronous vector evaluated particle swarm optimization for multi-objective design optimization of composite structures

This paper presents a decentralized/peer-to-peer architecture-based parallel version of the vector evaluated particle swarm optimization (VEPSO) algorithm for multi-objective design optimization of laminated composite plates using message passing interface (MPI). The design optimization of laminated composite plates being a combinatorially explosive constrained non-linear optimization problem (CNOP), with many design variables and a vast solution space, warrants the use of non-parametric and heuristic optimization algorithms like PSO. Optimization requires minimizing both the weight and cost of these composite plates, simultaneously, which renders the problem multi-objective. Hence VEPSO, a multi-objective variant of the PSO algorithm, is used. Despite the use of such a heuristic, the application problem, being computationally intensive, suffers from long execution times due to sequential computation. Hence, a parallel version of the PSO algorithm for the problem has been developed to run on several nodes of an IBM P720 cluster. The proposed parallel algorithm, using MPI's collective communication directives, establishes a peer-to-peer relationship between the constituent parallel processes, deviating from the more common master-slave approach, in achieving reduction of computation time by factor of up to 10. Finally we show the effectiveness of the proposed parallel algorithm by comparing it with a serial implementation of VEPSO and a parallel implementation of the vector evaluated genetic algorithm (VEGA) for the same design problem. (c) 2012 Elsevier Ltd. All rights reserved.

Space-vector-based hybrid pulse width modulation technique to reduce line current distortion in induction motor drives

Pulse width modulation (PWM) techniques involving different switching sequences are used in space vector-based PWM generation for reducing line current ripple in induction motor drives. This study proposes a hybrid PWM technique employing five switching sequences. The proposed technique is a combination of continuous PWM, discontinuous PWM (DPWM) and advanced bus clamping PWM methods. Performance of the proposed PWM technique is evaluated and compared with those of the existing techniques on a constant volts per hertz induction motor drive. In terms of total harmonic distortion in the line current, the proposed method is shown to be superior to both conventional space vector PWM (CSVPWM) and DPWM over a fundamental frequency range of 32-50 Hz at a given average switching frequency. The reduction in harmonic distortion is about 42% over CSVPWM at the rated speed of the drive.

A high precision instrument to measure angular and binocular deviation introduced by aircraft windscreens by using a shadow casting technique

Objects viewed through transparent sheets with residual non-parallelism and irregularity appear shifted and distorted. This distortion is measured in terms of angular and binocular deviation of an object viewed through the transparent sheet. The angular and binocular deviations introduced are particularly important in the context of aircraft windscreens and canopies as they can interfere with decision making of pilots especially while landing, leading to accidents. In this work, we have developed an instrument to measure both the angular and binocular deviations introduced by transparent sheets. This instrument is especially useful in the qualification of aircraft windscreens and canopies. It measures the deviation in the geometrical shadow cast by a periodic dot pattern trans-illuminated by the distorted light beam from the transparent test specimen compared to the reference pattern. Accurate quantification of the shift in the pattern is obtained by cross-correlating the reference shadow pattern with the specimen shadow pattern and measuring the location of the correlation peak. The developed instrument is handy to use and computes both angular and binocular deviation with an accuracy of less than +/- 0.1 mrad (approximate to 0.036 mrad) and has an excellent repeatability with an error of less than 2%. (C) 2012 American Institute of Physics. http://dx.doi.org/10.1063/1.4769756]

q-Gaussian based Smoothed Functional Algorithms for Stochastic Optimization

The q-Gaussian distribution results from maximizing certain generalizations of Shannon entropy under some constraints. The importance of q-Gaussian distributions stems from the fact that they exhibit power-law behavior, and also generalize Gaussian distributions. In this paper, we propose a Smoothed Functional (SF) scheme for gradient estimation using q-Gaussian distribution, and also propose an algorithm for optimization based on the above scheme. Convergence results of the algorithm are presented. Performance of the proposed algorithm is shown by simulation results on a queuing model.

Switching of a Sixteen Electrode Array for Wireless EIT System Using a RF-Based 8-Bit Digital Data Transmission Technique

Surface electrode switching of 16-electrode wireless EIT is studied using a Radio Frequency (RF) based digital data transmission technique operating with 8 channel encoder/decoder ICs. An electrode switching module is developed the analog multiplexers and switched with 8-bit parallel digital data transferred by transmitter/receiver module developed with radio frequency technology. 8-bit parallel digital data collected from the receiver module are converted to 16-bit digital data by using binary adder circuits and then used for switching the electrodes in opposite current injection protocol. 8-bit parallel digital data are generated using NI USB 6251 DAQ card in LabVIEW software and sent to the transmission module which transmits the digital data bits to the receiver end. Receiver module supplies the parallel digital bits to the binary adder circuits and adder circuit outputs are fed to the multiplexers of the electrode switching module for surface electrode switching. 1 mA, 50 kHz sinusoidal constant current is injected at the phantom boundary using opposite current injection protocol. The boundary potentials developed at the voltage electrodes are measured and studied to assess the wireless data transmission.

A UNIFIED APPROACH FOR OPTIMIZATION OF SNAKUSCULES AND OVUSCULES

Automated image segmentation techniques are useful tools in biological image analysis and are an essential step in tracking applications. Typically, snakes or active contours are used for segmentation and they evolve under the influence of certain internal and external forces. Recently, a new class of shape-specific active contours have been introduced, which are known as Snakuscules and Ovuscules. These contours are based on a pair of concentric circles and ellipses as the shape templates, and the optimization is carried out by maximizing a contrast function between the outer and inner templates. In this paper, we present a unified approach to the formulation and optimization of Snakuscules and Ovuscules by considering a specific form of affine transformations acting on a pair of concentric circles. We show how the parameters of the affine transformation may be optimized for, to generate either Snakuscules or Ovuscules. Our approach allows for a unified formulation and relies only on generic regularization terms and not shape-specific regularization functions. We show how the calculations of the partial derivatives may be made efficient thanks to the Green's theorem. Results on synthesized as well as real data are presented.