Accurate point matching based on multi-objective Genetic Algorithm for multi-sensor satellite imagery

This paper investigates a novel approach for point matching of multi-sensor satellite imagery. The feature (corner) points extracted using an improved version of the Harris Corner Detector (HCD) is matched using multi-objective optimization based on a Genetic Algorithm (GA). An objective switching approach to optimization that incorporates an angle criterion, distance condition and point matching condition in the multi-objective fitness function is applied to match corresponding corner-points between the reference image and the sensed image. The matched points obtained in this way are used to align the sensed image with a reference image by applying an affine transformation. From the results obtained, the performance of the image registration is evaluated and compared with existing methods, namely Nearest Neighbor-Random SAmple Consensus (NN-Ran-SAC) and multi-objective Discrete Particle Swarm Optimization (DPSO). From the performed experiments it can be concluded that the proposed approach is an accurate method for registration of multi-sensor satellite imagery. (C) 2014 Elsevier Inc. All rights reserved.

Colorimetric anion sensor based on receptor having indole- and thiourea-binding sites

A new colorimetric sensor L containing nitro-substituted indole and bisthiocarbonohydrazone units for selective fluoride and acetate ions is designed and synthesized. The receptor L shows well-defined color change in the visible region of the spectrum with an absorption band at similar to 515 nm and 506 nm, respectively, for the F- and CH3COO- ions in an acetonitrile solution. Job's plots indicated the formation of 1 : 1 (L with CH3COO-) and 1 : 2 (L with F-) complexes. The interaction of L with the F- ion undergoes a deprotonation process and release of HX2](-), whereas with the CH3COO- ion, it forms a stable LH2(...)X](-) complex. The relative affinities of the anions with L are rationalized using computational studies.

Exploring Transfer Learning Approaches for Head Pose Classification from Multi-view Surveillance Images

Head pose classification from surveillance images acquired with distant, large field-of-view cameras is difficult as faces are captured at low-resolution and have a blurred appearance. Domain adaptation approaches are useful for transferring knowledge from the training (source) to the test (target) data when they have different attributes, minimizing target data labeling efforts in the process. This paper examines the use of transfer learning for efficient multi-view head pose classification with minimal target training data under three challenging situations: (i) where the range of head poses in the source and target images is different, (ii) where source images capture a stationary person while target images capture a moving person whose facial appearance varies under motion due to changing perspective, scale and (iii) a combination of (i) and (ii). On the whole, the presented methods represent novel transfer learning solutions employed in the context of multi-view head pose classification. We demonstrate that the proposed solutions considerably outperform the state-of-the-art through extensive experimental validation. Finally, the DPOSE dataset compiled for benchmarking head pose classification performance with moving persons, and to aid behavioral understanding applications is presented in this work.

Influence of film thickness on the properties of sprayed ZnO thin films for gas sensor applications

Transparent conducting ZnO films were prepared at substrate temperature 400 degrees C with different film thicknesses by nebulizer spray pyrolysis method on glass substrates. XRD studies reveal that the films are polycrystalline in nature having hexagonal crystal structure with preferred grain orientations along (0 0 2) and (1 0 1) directions. The crystallite size increases along (0 0 2) plane with the thickness increase and attains a maximum 109 nm for 913 nm film thickness. Analysis of structural parameters indicates that the films having thickness 913 nm are found to have minimum dislocation density and strain values. The HRSEM measurements show that the surface morphology of the films also changes with film thickness. EDAX estimates the average atomic percentage ratio of Zn and O in the ZnO films. Optical studies reveal the band gap energy decrease from 3.27 to 3.14 eV with increase of film thickness. Room temperature PL spectra show the near-band-edge emission and deep-level emission due to the presence of defects in the ZnO thin films. Impedance spectroscopy analysis indicates that grain boundary resistance decreases with the increasing ammonia concentration up to 500 ppm and the maximum sensitivity is found to be 1.7 for 500 ppm of ammonia. (C) 2014 Elsevier Ltd. All rights reserved.

Conducting polymer-carbon black nanocomposite sensor for volatile organic compounds and correlating sensor response by molecular dynamics

Volatile organic compounds (VOCs) are present in our every day used products such as plastics, cosmetics, air fresheners, paint, etc. The determination of amount of VOC present in atmosphere can be carried out via various sensors. In this work a nanocomposite of a novel thiophene based conducting polymer and carbon black is used as a volatile organic compound sensor. The fabricated 2 lead chemiresistor sensor was tested for vapours of toluene, acetone, cylcohexane, and carbon tetrachloride. The sensor responds to all the vapours, however, exhibit maximum response to toluene vapours. The sensor was evaluated for various concentrations of toluene. The lower limit of detection of the sensor is 15 +/- 10 ppm. The study of the effect of humidity on senor response to toluene showed that the response decreases at higher humidity conditions. The surface morphology of the nanocomposite was characterized by scanning electron microscopy. Diffuse reflectance spectroscopy was used to investigate the absorption of vapours by the nanocomposite film. Contact angle measurements were used to present the effect of water vapour on the toluene response of nanocomposite film. Solubility parameter of the conducting polymer is predicted by molecular dynamics. The sensing behaviour of the conducting polymer is correlated with solubility parameter of the polymer. Dispersion interaction of conducting polymer with toluene is believed to be the reason for the selective response towards toluene. (C) 2014 Elsevier B.V. All rights reserved.

A radial differential mobility analyzer for the size-classification of gas-phase synthesized nanoparticles at low pressures

Differential mobility analyzers (DMAs) are commonly used to generate monodisperse nanoparticle aerosols. Commercial DMAs operate at quasi-atmospheric pressures and are therefore not designed to be vacuum-tight. In certain particle synthesis methods, the use of a vacuum-compatible DMA is a requirement as a process step for producing high-purity metallic particles. A vacuum-tight radial DMA (RDMA) has been developed and tested at low pressures. Its performance has been evaluated by using a commercial NANO-DMA as the reference. The performance of this low-pressure RDMA (LP-RDMA) in terms of the width of its transfer function is found to be comparable with that of other NANO-DMAs at atmospheric pressure and is almost independent of the pressure down to 30 mbar. It is shown that LP-RDMA can be used for the classification of nanometer-sized particles (5-20 nm) under low pressure condition (30 mbar) and has been successfully applied to nanoparticles produced by ablating FeNi at low pressures.

Phylogenetic relationships and classification of thiolases and thiolase-like proteins of Mycobacterium tuberculosis and Mycobacterium smegmatis

Thiolases are enzymes involved in lipid metabolism. Thiolases remove the acetyl-CoA moiety from 3-ketoacyl-CoAs in the degradative reaction. They can also catalyze the reverse Claisen condensation reaction, which is the first step of biosynthetic processes such as the biosynthesis of sterols and ketone bodies. In human, six distinct thiolases have been identified. Each of these thiolases is different from the other with respect to sequence, oligomeric state, substrate specificity and subcellular localization. Four sequence fingerprints, identifying catalytic loops of thiolases, have been described. In this study genome searches of two mycobacterial species (Mycobacterium tuberculosis and Mycobacterium smegmatis), were carried out, using the six human thiolase sequences as queries. Eight and thirteen different thiolase sequences were identified in M. tuberculosis and M. smegmatis, respectively. In addition, thiolase-like proteins (one encoded in the Mtb and two in the Msm genome) were found. The purpose of this study is to classify these mostly uncharacterized thiolases and thiolase-like proteins. Several other sequences obtained by searches of genome databases of bacteria, mammals and the parasitic protist family of the Trypanosomatidae were included in the analysis. Thiolase-like proteins were also found in the trypanosomatid genomes, but not in those of mammals. In order to study the phylogenetic relationships at a high confidence level, additional thiolase sequences were included such that a total of 130 thiolases and thiolase-like protein sequences were used for the multiple sequence alignment. The resulting phylogenetic tree identifies 12 classes of sequences, each possessing a characteristic set of sequence fingerprints for the catalytic loops. From this analysis it is now possible to assign the mycobacterial thiolases to corresponding homologues in other kingdoms of life. The results of this bioinformatics analysis also show interesting differences between the distributions of M. tuberculosis and M. smegmatis thiolases over the 12 different classes. (C) 2014 Elsevier Ltd. All rights reserved.

Graphene as a sensor

Graphene has emerged as one of the strongest candidates for post-silicon technologies. One of the most important applications of graphene in the foreseeable future is sensing of particles of gas molecules, biomolecules or different chemicals or sensing of radiation of particles like alpha, gamma or cosmic particles. Several unique properties of graphene such as its extremely small thickness, very low mass, large surface to volume ratio, very high absorption coefficient, high mobility of charge carriers, high mechanical strength and high Young's modulus make it exceptionally suitable for making sensors. In this article we review the state-of-the-art in the application of graphene as a material and radiation detector, focusing on the current experimental status, challenges and the excitement ahead.

A shortest path tree based algorithm for relay placement in a wireless sensor network and its performance analysis

In this paper, we study a problem of designing a multi-hop wireless network for interconnecting sensors (hereafter called source nodes) to a Base Station (BS), by deploying a minimum number of relay nodes at a subset of given potential locations, while meeting a quality of service (QoS) objective specified as a hop count bound for paths from the sources to the BS. The hop count bound suffices to ensure a certain probability of the data being delivered to the BS within a given maximum delay under a light traffic model. We observe that the problem is NP-Hard. For this problem, we propose a polynomial time approximation algorithm based on iteratively constructing shortest path trees and heuristically pruning away the relay nodes used until the hop count bound is violated. Results show that the algorithm performs efficiently in various randomly generated network scenarios; in over 90% of the tested scenarios, it gave solutions that were either optimal or were worse than optimal by just one relay. We then use random graph techniques to obtain, under a certain stochastic setting, an upper bound on the average case approximation ratio of a class of algorithms (including the proposed algorithm) for this problem as a function of the number of source nodes, and the hop count bound. To the best of our knowledge, the average case analysis is the first of its kind in the relay placement literature. Since the design is based on a light traffic model, we also provide simulation results (using models for the IEEE 802.15.4 physical layer and medium access control) to assess the traffic levels up to which the QoS objectives continue to be met. (C) 2014 Elsevier B.V. All rights reserved.

Iminodiacetic acid functionalized polypyrrole modified electrode as Pb(II) sensor: Synthesis and DPASV studies

An electrochemical lead ion sensor has been developed by modification of carbon paste electrode (CPE) using polypyrrole functionalized with iminodiacetic acid (IDA-PPy) containing carboxyl group. The electrochemical response of Pb2+ ion on the IDA-PPy modified CPE has been evaluated and the controling parameters have been optimized using differential pulse anodic stripping voltammetry (DPASV). The IDA-PPy modified CPE shows a linear correlation for Pb2+ concentrations in the range of 1 x 10(-6) to 5 x 10(-9) M and the lower detection limit of Pb2+ has been found to be 9.6 x 10(-9) M concentration. Other tested metal ions, namely Cu2+, Cd2+, Co2+, Hg2+, Ni2+ and Zn2+, do not exhibit any voltammetric stripping response below 1 x 10(-7) M concentration. However, the Pb2+ response is affected in the presence of molar equivalents or higher concentrations of Cu2+, Cd2+ and Co2+ ions in binary systems with Pb2+, consequent to their ability to bind with iminodiacetic acid, while Hg2+, Ni2+ and Zn2+ do not interfere at all. A good correlation has been observed between the lead concentrations as analyzed by DPASV using IDA-PPy modified CPE and atomic absorption spectrophotometry for a lead containing industrial effluent sample. (C) 2014 Elsevier Ltd. All rights reserved.

N-Alkyl derivative of 1,9-pyrazoloanthrone as a sensor for picric acid

The N-alkyl derivative of 1,9-pyrazoloanthrone has been synthesized, characterized and evaluated as a potent sensor for picric acid.

Design, Development and Calibration of HTS Wire Based LOX Level Sensor Probe

For space applications, the weight of the liquid level sensors are of major concern as they affect the payload fraction and hence the cost. An attempt is made to design and test a light weight High Temperature Superconductor (HTS) wire based liquid level sensor for Liquid Oxygen (LOX) tank used in the cryostage of the spacecraft. The total resistance value measured of the HTS wire is inversely proportional to the liquid level. A HTS wire (SF12100) of 12mm width and 2.76m length without copper stabilizer has been used in the level sensor. The developed HTS wire based LOX level sensor is calibrated against a discrete diode array type level sensor. Liquid Nitrogen (LN2) and LOX has been used as cryogenic fluid for the calibration purpose. The automatic data logging for the system has been done using LabVIEW11. The net weight of the developed sensor is less than 1 kg.

Two timescale convergent Q-learning for sleep-scheduling in wireless sensor networks

In this paper, we consider an intrusion detection application for Wireless Sensor Networks. We study the problem of scheduling the sleep times of the individual sensors, where the objective is to maximize the network lifetime while keeping the tracking error to a minimum. We formulate this problem as a partially-observable Markov decision process (POMDP) with continuous stateaction spaces, in a manner similar to Fuemmeler and Veeravalli (IEEE Trans Signal Process 56(5), 2091-2101, 2008). However, unlike their formulation, we consider infinite horizon discounted and average cost objectives as performance criteria. For each criterion, we propose a convergent on-policy Q-learning algorithm that operates on two timescales, while employing function approximation. Feature-based representations and function approximation is necessary to handle the curse of dimensionality associated with the underlying POMDP. Our proposed algorithm incorporates a policy gradient update using a one-simulation simultaneous perturbation stochastic approximation estimate on the faster timescale, while the Q-value parameter (arising from a linear function approximation architecture for the Q-values) is updated in an on-policy temporal difference algorithm-like fashion on the slower timescale. The feature selection scheme employed in each of our algorithms manages the energy and tracking components in a manner that assists the search for the optimal sleep-scheduling policy. For the sake of comparison, in both discounted and average settings, we also develop a function approximation analogue of the Q-learning algorithm. This algorithm, unlike the two-timescale variant, does not possess theoretical convergence guarantees. Finally, we also adapt our algorithms to include a stochastic iterative estimation scheme for the intruder's mobility model and this is useful in settings where the latter is not known. Our simulation results on a synthetic 2-dimensional network setting suggest that our algorithms result in better tracking accuracy at the cost of only a few additional sensors, in comparison to a recent prior work.

CLAP: A web-server for automatic classification of proteins with special reference to multi-domain proteins

Background: The function of a protein can be deciphered with higher accuracy from its structure than from its amino acid sequence. Due to the huge gap in the available protein sequence and structural space, tools that can generate functionally homogeneous clusters using only the sequence information, hold great importance. For this, traditional alignment-based tools work well in most cases and clustering is performed on the basis of sequence similarity. But, in the case of multi-domain proteins, the alignment quality might be poor due to varied lengths of the proteins, domain shuffling or circular permutations. Multi-domain proteins are ubiquitous in nature, hence alignment-free tools, which overcome the shortcomings of alignment-based protein comparison methods, are required. Further, existing tools classify proteins using only domain-level information and hence miss out on the information encoded in the tethered regions or accessory domains. Our method, on the other hand, takes into account the full-length sequence of a protein, consolidating the complete sequence information to understand a given protein better. Results: Our web-server, CLAP (Classification of Proteins), is one such alignment-free software for automatic classification of protein sequences. It utilizes a pattern-matching algorithm that assigns local matching scores (LMS) to residues that are a part of the matched patterns between two sequences being compared. CLAP works on full-length sequences and does not require prior domain definitions. Pilot studies undertaken previously on protein kinases and immunoglobulins have shown that CLAP yields clusters, which have high functional and domain architectural similarity. Moreover, parsing at a statistically determined cut-off resulted in clusters that corroborated with the sub-family level classification of that particular domain family. Conclusions: CLAP is a useful protein-clustering tool, independent of domain assignment, domain order, sequence length and domain diversity. Our method can be used for any set of protein sequences, yielding functionally relevant clusters with high domain architectural homogeneity. The CLAP web server is freely available for academic use at http://nslab.mbu.iisc.ernet.in/clap/.

A non-resonant mass sensor to eliminate the ``missing mass'' effect during mass measurement of biological materials

Resonant sensors and crystal oscillators for mass detection need to be excited at very high natural frequencies (MHz). Use of such systems to measure mass of biological materials affects the accuracy of mass measurement due to their viscous and/or viscoelastic properties. The measurement limitation of such sensor system is the difficulty in accounting for the ``missing mass'' of the biological specimen in question. A sensor system has been developed in this work, to be operated in the stiffness controlled region at very low frequencies as compared to its fundamental natural frequency. The resulting reduction in the sensitivity due to non-resonant mode of operation of this sensor is compensated by the high resolution of the sensor. The mass of different aged drosophila melanogaster (fruit fly) is measured. The difference in its mass measurement during resonant mode of operation is also presented. That, viscosity effects do not affect the working of this non-resonant mass sensor is clearly established by direct comparison. (C) 2014 AIP Publishing LLC.