A Profilometric Approach to 3D Face Reconstruction and Its Application to Face Recognition

3D Face Recognition is an active area of research for past several years. For a 3D face recognition system one would like to have an accurate as well as low cost setup for constructing 3D face model. In this paper, we use Profilometry approach to obtain a 3D face model.This method gives a low cost solution to the problem of acquiring 3D data and the 3D face models generated by this method are sufficiently accurate. We also develop an algorithm that can use the 3D face model generated by the above method for the recognition purpose.

An Accurate Model for EESM and its Application to Analysis of CQI Feedback Schemes and Scheduling in LTE

The Effective Exponential SNR Mapping (EESM) is an indispensable tool for analyzing and simulating next generation orthogonal frequency division multiplexing (OFDM) based wireless systems. It converts the different gains of multiple subchannels, over which a codeword is transmitted, into a single effective flat-fading gain with the same codeword error rate. It facilitates link adaptation by helping each user to compute an accurate channel quality indicator (CQI), which is fed back to the base station to enable downlink rate adaptation and scheduling. However, the highly non-linear nature of EESM makes a performance analysis of adaptation and scheduling difficult; even the probability distribution of EESM is not known in closed-form. This paper shows that EESM can be accurately modeled as a lognormal random variable when the subchannel gains are Rayleigh distributed. The model is also valid when the subchannel gains are correlated in frequency or space. With some simplifying assumptions, the paper then develops a novel analysis of the performance of LTE's two CQI feedback schemes that use EESM to generate CQI. The comprehensive model and analysis quantify the joint effect of several critical components such as scheduler, multiple antenna mode, CQI feedback scheme, and EESM-based feedback averaging on the overall system throughput.

Analysis of light‐induced processes in bacteriorhodopsin and its application for spatial light modulation

A simplified energy‐level scheme is proposed for the photochemical cycle of the bacteriorhodopsin molecule. Rate equations are solved for the detailed light‐induced processes based on this model and the intensity‐induced population densities in various states of the molecule at steady state are computed which are used to obtain an analytic expression for the absorption coefficient of the modulation beam. Modulation of the probe laser‐beam transmission by the modulation‐laser‐beam intensity‐induced population changes is analyzed. It is predicted that for a probe beam at 412 nm up to 82% modulation can be achieved using a laser beam intensity of 3.2 W/cm2 at 570 nm. For temperatures ∼77 K, the transmission at 610 nm can be switched from zero to 81% for modulating laser intensity of 11 W/cm2. Construction of a spatial light modulator based on bacteriorhodopsin molecules is proposed and some of its features are discussed.

Cyclopentac]thiophene oligomers based solution processable D-A copolymers and their application as FET materials

Two new solution processable, low band gap donor-acceptor (D-A) copolymers (P1 and P2) comprising a cyclopentac] thiophene (CPT) based oligomers as donors and benzoc]1,2,5] selenadiazole (BDS) and 2-dodecyl1,2,3]-benzotriazole (BTAz) as acceptors were synthesized and characterized and their field effect transistor properties were studied. The internal charge transfer interaction between the electron-donating CPT based oligothiophene and the electron-accepting BDS or BTAz unit effectively reduces the band gap in polymers to 1.3 and 1.66 eV with low lying highest occupied molecular orbital (HOMO). The absorption spectrum of P1 was found to be more red shifted than that of P2 because of incorporation of the more electron-withdrawing BDS unit. The color of neutral P1 was found to be green in both solution and film states with two major bands in the absorption spectra; however, neutral P2 revealed one dominant absorption exhibiting red color in both solution and film state which could be attributed to the less electron-withdrawing effect of the BTAz unit. The polymers were further characterized by GPC, TGA, DSC and cyclic voltammetry. P1 and P2 exhibited charge carrier mobilities as high as 9 x 10(-3) cm(2) V-1 s(-1) and 2.56 x 10(-3) cm 2 V-1 s(-1), respectively with the current on/off ratio (I-on/I-off) in the order of 10(2).

Naphthylhydrazone based selective and sensitive chemosensors for Cu2+ and their application in bioimaging

Two new hydroxynaphthyl-hydrazone based fluorogenic chemosensors R-1 and R-2 have been synthesized by Schiff base condensation of Tris(4-formylphenyl)amine with 1-hydroxynaphthalene-2-hydrazide and 1-hydroxynaphthalene-2-carbohydrazone, respectively. They are examined as highly selective and sensitive receptors for Cu2+ ions in aqueous medium. Electronic absorption as well as fluorescence titration studies of receptors R-1 and R-2 with different metal cations in H2O/CH3CN medium showed highly selective and very rapid (< 2 min) binding affinity towards Cu2+ ions even in the presence of other commonly coexisting metal ions such as Na+, K+, Mg2+, Ca2+, Mn2+, Fe2+, Co2+, Ni2+, Zn2+, Cd2+ and Hg2+. Quantification of the fluorescence titration analysis indicated that these newly synthesized receptors (R-1 and R-2) can indicate the presence of Cu2+ ions even at very low concentrations of 598 and 676 ppt, respectively. In addition, the propensity of these receptors as bio-imaging fluorescent probes to detect Cu2+ ions in human cervical HeLa cancer cell lines and their cytotoxicity against HeLa cells have been investigated.

A phenanthrene based highly selective fluorogenic and visual sensor for Cu2+ ion with nanomolar detection limit and its application in live cell imaging

A new phenanthrene based chemosensor has been synthesized and investigated to act as highly selective fluorescence and visual sensor for Cu2+ ion with very low detection limit of 1.58 nM: this has also been used to image Cu2+ in human cervical HeLa cancer cells. (C) 2012 Elsevier B.V. All rights reserved.

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.

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.

Generalized model predictive static programming and its application to 3D impact angle constrained guidance of air-to-surface missiles

A new `generalized model predictive static programming (G-MPSP)' technique is presented in this paper in the continuous time framework for rapidly solving a class of finite-horizon nonlinear optimal control problems with hard terminal constraints. A key feature of the technique is backward propagation of a small-dimensional weight matrix dynamics, using which the control history gets updated. This feature, as well as the fact that it leads to a static optimization problem, are the reasons for its high computational efficiency. It has been shown that under Euler integration, it is equivalent to the existing model predictive static programming technique, which operates on a discrete-time approximation of the problem. Performance of the proposed technique is demonstrated by solving a challenging three-dimensional impact angle constrained missile guidance problem. The problem demands that the missile must meet constraints on both azimuth and elevation angles in addition to achieving near zero miss distance, while minimizing the lateral acceleration demand throughout its flight path. Both stationary and maneuvering ground targets are considered in the simulation studies. Effectiveness of the proposed guidance has been verified by considering first order autopilot lag as well as various target maneuvers.

Analysis of modified microstrip line and its application

Analysis of a microstrip line with a symmetrically located aperture in its ground plane is reported in this paper. The solution is based on conformal mapping technique. Conformal mapping has been used to determine the characteristic impedance and effective permittivity of the line. The accuracy of results is within 5% error. An low pass filter has been designed based on the electrical parameters obtained using the proposed method.

Facile hydrothermal synthesis of carbon nanoparticles and possible application as white light phosphors and catalysts for the reduction of nitrophenol

We report a simple hydrothermal synthesis of highly reproducible carbon nanoparticles in a size range between 2 and 7 nmfroma single precursor sucrose without either surface passivating agents or acids and bases. The carbon nanoparticles can be used as white light phosphors, especially for ultraviolet light emitting diodes and metal-free catalyst for the reduction of nitrophenol.

Toward a Scalable Working Set Size Estimation Method and Its Application for Chip Multiprocessors

It is essential to accurately estimate the working set size (WSS) of an application for various optimizations such as to partition cache among virtual machines or reduce leakage power dissipated in an over-allocated cache by switching it OFF. However, the state-of-the-art heuristics such as average memory access latency (AMAL) or cache miss ratio (CMR) are poorly correlated to the WSS of an application due to 1) over-sized caches and 2) their dispersed nature. Past studies focus on estimating WSS of an application executing on a uniprocessor platform. Estimating the same for a chip multiprocessor (CMP) with a large dispersed cache is challenging due to the presence of concurrently executing threads/processes. Hence, we propose a scalable, highly accurate method to estimate WSS of an application. We call this method ``tagged WSS (TWSS)'' estimation method. We demonstrate the use of TWSS to switch-OFF the over-allocated cache ways in Static and Dynamic NonUniform Cache Architectures (SNUCA, DNUCA) on a tiled CMP. In our implementation of adaptable way SNUCA and DNUCA caches, decision of altering associativity is taken by each L2 controller. Hence, this approach scales better with the number of cores present on a CMP. It gives overall (geometric mean) 26% and 19% higher energy-delay product savings compared to AMAL and CMR heuristics on SNUCA, respectively.