AN ITERATIVE ALGORITHM FOR PHASE RETRIEVAL WITH SPARSITY CONSTRAINTS: APPLICATION TO FREQUENCY DOMAIN OPTICAL COHERENCE TOMOGRAPHY

We address the problem of phase retrieval, which is frequently encountered in optical imaging. The measured quantity is the magnitude of the Fourier spectrum of a function (in optics, the function is also referred to as an object). The goal is to recover the object based on the magnitude measurements. In doing so, the standard assumptions are that the object is compactly supported and positive. In this paper, we consider objects that admit a sparse representation in some orthonormal basis. We develop a variant of the Fienup algorithm to incorporate the condition of sparsity and to successively estimate and refine the phase starting from the magnitude measurements. We show that the proposed iterative algorithm possesses Cauchy convergence properties. As far as the modality is concerned, we work with measurements obtained using a frequency-domain optical-coherence tomography experimental setup. The experimental results on real measured data show that the proposed technique exhibits good reconstruction performance even with fewer coefficients taken into account for reconstruction. It also suppresses the autocorrelation artifacts to a significant extent since it estimates the phase accurately.

Application of Artificial Neural Networks and Particle Swarm Optimization for the Management of Groundwater Resources

Ground management problems are typically solved by the simulation-optimization approach where complex numerical models are used to simulate the groundwater flow and/or contamination transport. These numerical models take a lot of time to solve the management problems and hence become computationally expensive. In this study, Artificial Neural Network (ANN) and Particle Swarm Optimization (PSO) models were developed and coupled for the management of groundwater of Dore river basin in France. The Analytic Element Method (AEM) based flow model was developed and used to generate the dataset for the training and testing of the ANN model. This developed ANN-PSO model was applied to minimize the pumping cost of the wells, including cost of the pipe line. The discharge and location of the pumping wells were taken as the decision variable and the ANN-PSO model was applied to find out the optimal location of the wells. The results of the ANN-PSO model are found similar to the results obtained by AEM-PSO model. The results show that the ANN model can reduce the computational burden significantly as it is able to analyze different scenarios, and the ANN-PSO model is capable of identifying the optimal location of wells efficiently.

Incentive Compatible Influence Maximization in Social Networks with Application to Viral Marketing

Information diffusion and influence maximization are important and extensively studied problems in social networks. Various models and algorithms have been proposed in the literature in the context of the influence maximization problem. A crucial assumption in all these studies is that the influence probabilities are known to the social planner. This assumption is unrealistic since the influence probabilities are usually private information of the individual agents and strategic agents may not reveal them truthfully. Moreover, the influence probabilities could vary significantly with the type of the information flowing in the network and the time at which the information is propagating in the network. In this paper, we use a mechanism design approach to elicit influence probabilities truthfully from the agents. Our main contribution is to design a scoring rule based mechanism in the context of the influencer-influencee model. In particular, we show the incentive compatibility of the mechanisms and propose a reverse weighted scoring rule based mechanism as an appropriate mechanism to use.

Review of trend detection methods and their application to detect temperature changes in India

Present study performs the spatial and temporal trend analysis of annual, monthly and seasonal maximum and minimum temperatures (t(max), t(min)) in India. Recent trends in annual, monthly, winter, pre-monsoon, monsoon and post-monsoon extreme temperatures (t(max), t(min)) have been analyzed for three time slots viz. 1901-2003,1948-2003 and 1970-2003. For this purpose, time series of extreme temperatures of India as a whole and seven homogeneous regions, viz. Western Himalaya (WH), Northwest (NW), Northeast (NE), North Central (NC), East coast (EC), West coast (WC) and Interior Peninsula (IP) are considered. Rigorous trend detection analysis has been exercised using variety of non-parametric methods which consider the effect of serial correlation during analysis. During the last three decades minimum temperature trend is present in All India as well as in all temperature homogeneous regions of India either at annual or at any seasonal level (winter, pre-monsoon, monsoon, post-monsoon). Results agree with the earlier observation that the trend in minimum temperature is significant in the last three decades over India (Kothawale et al., 2010). Sequential MK test reveals that most of the trend both in maximum and minimum temperature began after 1970 either in annual or seasonal levels. (C) 2012 Elsevier B.V. All rights reserved.

A game theoretic approach for feature clustering and its application to feature selection

In this paper, we develop a game theoretic approach for clustering features in a learning problem. Feature clustering can serve as an important preprocessing step in many problems such as feature selection, dimensionality reduction, etc. In this approach, we view features as rational players of a coalitional game where they form coalitions (or clusters) among themselves in order to maximize their individual payoffs. We show how Nash Stable Partition (NSP), a well known concept in the coalitional game theory, provides a natural way of clustering features. Through this approach, one can obtain some desirable properties of the clusters by choosing appropriate payoff functions. For a small number of features, the NSP based clustering can be found by solving an integer linear program (ILP). However, for large number of features, the ILP based approach does not scale well and hence we propose a hierarchical approach. Interestingly, a key result that we prove on the equivalence between a k-size NSP of a coalitional game and minimum k-cut of an appropriately constructed graph comes in handy for large scale problems. In this paper, we use feature selection problem (in a classification setting) as a running example to illustrate our approach. We conduct experiments to illustrate the efficacy of our approach.

A Huber-loss-driven clustering technique and its application to robust cell detection in confocal microscopy images

We address the problem of detecting cells in biological images. The problem is important in many automated image analysis applications. We identify the problem as one of clustering and formulate it within the framework of robust estimation using loss functions. We show how suitable loss functions may be chosen based on a priori knowledge of the noise distribution. Specifically, in the context of biological images, since the measurement noise is not Gaussian, quadratic loss functions yield suboptimal results. We show that by incorporating the Huber loss function, cells can be detected robustly and accurately. To initialize the algorithm, we also propose a seed selection approach. Simulation results show that Huber loss exhibits better performance compared with some standard loss functions. We also provide experimental results on confocal images of yeast cells. The proposed technique exhibits good detection performance even when the signal-to-noise ratio is low.

Design and Application of a new Multiscale Multidirectional Non-subsampled Filter Bank

We propose a new method for design of computationally efficient nonsubsampled multiscale multidirectional filter bank with perfect reconstruction (PR). This filter bank is composed of two nonsubsampled filter banks, for multiscale decomposition and for directional expansion. For multiscale decomposition, we transform the 1-D equivalent subband filters directly into 2-D equivalent subband filters. The computational cost is considerably reduced by avoiding the computation of 2-D convolutions. The multidirectional decomposition utilizes fan filters. A new method for design of 2-D zero phase FIR fan filter transformation function is developed. This method also aids the transformation of a 1-D filter bank to a 2-D multidirectional filter bank. The potential application of the proposed filter bank is illustrated by comparing the image denoising performance of the proposed filter bank with other design method that exist in available literature.

Application of a modified jogged-screw model for creep of titanium aluminides: evaluation of the key substructural parameters

A modification of the jogged-screw model has been adopted recently by the authors to explain observations of 1/2[110]-type jogged-screw dislocations in equiaxed Ti-48Al under creep conditions. The aim of this study has been to verify and validate the parameters and functional dependencies that have been assumed in this previous work. The original solution has been reformulated to take into account the finite length of the moving jog. This is a better approximation of the tall jog. The substructural model parameters have been further investigated in light of the Finite Length Moving Line (FLML) source approximation. The original model assumes that the critical jog height (beyond which the jog is not dragged) is inversely proportional to the applied stress. By accounting for the fact that there are three competing mechanisms (jog dragging, dipole dragging, dipole bypass) possible, we can arrive at a modified critical jog height. The critical jog height was found to be more strongly stress dependent than assumed previously. The original model assumes the jog spacing to be invariant over the stress range. However, dynamic simulation using a line tension model has shown that the jog spacing is inversely proportional to the applied stress. This has also been confirmed by TEM measurements of jog spacings over a range of stresses. Taylor's expression assumed previously to provide the dependence of dislocation density on the applied stress, has now been confirmed by actual dislocation density measurements. Combining all of these parameters and dependencies, derived both from experiment and theory, leads to an excellent prediction of creep rates and stress exponents. The further application of this model to other materials, and the important role of atomistic and dislocation dynamics simulations in its continued development is also discussed.

Experimental investigation on switching characteristics of IGBTs for traction application

In traction application, inverters need to have high reliability on account of wide variation in operating conditions, extreme ambient conditions, thermal cycling and varying DC link voltage. Hence it is important to have a good knowledge of switching characteristics of the devices used. The focus of this paper is to investigate and compare switching characteristics and losses of IGBT modules for traction application. Dependence of device transition times and switching energy losses on dc link voltage, device current and operating temperature is studied experimentally.

Flexible Phynox Alloy with Integrated Piezoelectric Thin Film for Micro Actuation Application

In this paper, we report on the application aspect of piezoelectric ZnO thin film deposited on flexible phynox alloy substrate. Highly crystalline piezoelectric ZnO thin films were deposited by RF reactive magnetron sputtering and were characterized by XRD, SEM, AFM analysis. Also, the effective d(33) coefficient value measurement was performed. The actuator element is a circular diaphragm of phynox alloy on to which piezoelectric ZnO thin film was deposited. ZnO film deposited actuator element was firmly fixed inside a suitable concave perspex mounting designed specifically for micro actuation purpose. The actuator element was excited at different frequencies for the supply voltages of 2V, 5V and 8V. Maximum deflection of the ZnO film deposited diaphragm was measured to be 1.25 mu m at 100 Hz for the supply voltage of 8V. The developed micro actuator has the potential to be used as a micro pump for pumping nano liters to micro liters of fluids per minute for numerous biomedical and aerospace applications.

Spectral zero-crossings: localization properties and application to epoch extraction in speech signals

We analyze the spectral zero-crossing rate (SZCR) properties of transient signals and show that SZCR contains accurate localization information about the transient. For a train of pulses containing transient events, the SZCR computed on a sliding window basis is useful in locating the impulse locations accurately. We present the properties of SZCR on standard stylized signal models and then show how it may be used to estimate the epochs in speech signals. We also present comparisons with some state-of-the-art techniques that are based on the group-delay function. Experiments on real speech show that the proposed SZCR technique is better than other group-delay-based epoch detectors. In the presence of noise, a comparison with the zero-frequency filtering technique (ZFF) and Dynamic programming projected Phase-Slope Algorithm (DYPSA) showed that performance of the SZCR technique is better than DYPSA and inferior to that of ZFF. For highpass-filtered speech, where ZFF performance suffers drastically, the identification rates of SZCR are better than those of DYPSA.

Bilateral smoothing of gradient vector field and application to image segmentation

Medical image segmentation finds application in computer-aided diagnosis, computer-guided surgery, measuring tissue volumes, locating tumors, and pathologies. One approach to segmentation is to use active contours or snakes. Active contours start from an initialization (often manually specified) and are guided by image-dependent forces to the object boundary. Snakes may also be guided by gradient vector fields associated with an image. The first main result in this direction is that of Xu and Prince, who proposed the notion of gradient vector flow (GVF), which is computed iteratively. We propose a new formalism to compute the vector flow based on the notion of bilateral filtering of the gradient field associated with the edge map - we refer to it as the bilateral vector flow (BVF). The range kernel definition that we employ is different from the one employed in the standard Gaussian bilateral filter. The advantage of the BVF formalism is that smooth gradient vector flow fields with enhanced edge information can be computed noniteratively. The quality of image segmentation turned out to be on par with that obtained using the GVF and in some cases better than the GVF.

Low temperature growth of SnO2 nanowires by electron beam evaporation and their application in UV light detection

For the first time, high quality tin oxide (SnO2) nanowires have been synthesized at a low substrate temperature of 450 degrees C via vapor-liquid-solid mechanism using an electron beam evaporation technique. The grown nanowires have shown length of 2-4 mu m and diameter of 20-60 nm. High resolution transmission electron microscope studies on the grown nanowires have shown the single crystalline nature of the SnO2 nanowires. We investigated the effect of growth temperature and oxygen partial pressure on SnO2 nanowires growth. Variation of substrate temperature at a constant oxygen partial pressure of 4 x 10(-4) mbar suggested that a temperature equal to or greater than 450 degrees C was the best condition for phase pure SnO2 nanowires growth. The SnO2 nanowires grown on a SiO2 substrate were subjected to UV photo detection. The responsivity and quantum efficiency of SnO2 NWs photo detector (at 10V applied bias) was 12 A/W and 45, respectively, for 12 mu W/cm(2) UV lamp (330 nm) intensity on the photo detector.

Synthesis and characterization of porous flowerlike alpha-Fe2O3 nanostructures for supercapacitor application

Porous flower-like alpha-Fe2O3 nanostructures synthesized by an ethylene glycol mediated self-assembly process are crystalline and porous with BET surface area of 64.6 m(2) g(-1). The discharge capacitance is 127 F g(-1) when the electrodes are cycled in 0.5 M Na2SO3 at a current density of 1 A g(-1). Capacitance retention after 1000 cycles is about 80% of the initial capacitance. The high discharge capacitance and its retention are attributed to high surface area and porosity of the iron oxide. As the iron oxides are inexpensive, the nano alpha-Fe2O3 is expected to be of potential use for supercapacitor application.

Process control of cantilever deflection for sensor application based on optical waveguides

This paper reports on the fabrication of cantilever silicon-on-insulator (SOI) optical waveguides and presents solutions to the challenges of using a very thin 260-nm active silicon layer in the SOI structure to enable single-transverse-mode operation of the waveguide with minimal optical transmission losses. In particular, to ameliorate the anchor effect caused by the mean stress difference between the active silicon layer and buried oxide layer, a cantilever flattening process based on Ar plasma treatment is developed and presented. Vertical deflections of 0.5 mu m for 70-mu m-long cantilevers are mitigated to within few nanometers. Experimental investigations of cantilever mechanical resonance characteristics confirm the absence of significant detrimental side effects. Optical and mechanical modeling is extensively used to supplement experimental observations. This approach can satisfy the requirements for on-chip simultaneous readout of many integrated cantilever sensors in which the displacement or resonant frequency changes induced by analyte absorption are measured using an optical-waveguide-based division multiplexed system.