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 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.

Sensitivity of simulated climate to latitudinal distribution of solar insolation reduction in solar radiation management

Solar radiation management (SRM) geoengineering has been proposed as a potential option to counteract climate change. We perform a set of idealized geoengineering simulations using Community Atmosphere Model version 3.1 developed at the National Center for Atmospheric Research to investigate the global hydrological implications of varying the latitudinal distribution of solar insolation reduction in SRM methods. To reduce the solar insolation we have prescribed sulfate aerosols in the stratosphere. The radiative forcing in the geoengineering simulations is the net forcing from a doubling of CO2 and the prescribed stratospheric aerosols. We find that for a fixed total mass of sulfate aerosols (12.6 Mt of SO4), relative to a uniform distribution which nearly offsets changes in global mean temperature from a doubling of CO2, global mean radiative forcing is larger when aerosol concentration is maximum at the poles leading to a warmer global mean climate and consequently an intensified hydrological cycle. Opposite changes are simulated when aerosol concentration is maximized in the tropics. We obtain a range of 1 K in global mean temperature and 3% in precipitation changes by varying the distribution pattern in our simulations: this range is about 50% of the climate change from a doubling of CO2. Hence, our study demonstrates that a range of global mean climate states, determined by the global mean radiative forcing, are possible for a fixed total amount of aerosols but with differing latitudinal distribution. However, it is important to note that this is an idealized study and thus not all important realistic climate processes are modeled.

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.

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.

A phylogeny of the only ground-dwelling radiation of Cyrtodactylus (Squamata, Gekkonidae): diversification of Geckoella across peninsular India and Sri Lanka

The subgenus Geckoella, the only ground-dwelling radiation within Cyrtodactylus, closely overlaps in distribution with brookii group Hemidactylus in peninsular India and Sri Lanka. Both groups have Oligocene origins, the latter with over thrice as many described species. The striking difference in species richness led us to believe that Geckoella diversity is underestimated, and we sampled for Geckoella across peninsular India. A multi-locus phylogeny reveals Geckoella diversity is hugely underestimated, with at least seven undescribed species, doubling previously known richness. Strikingly, the new species correspond to cryptic lineages within described Indian species (complexes); a number of these endemic lineages from the hills of peninsular India outside the Western Ghats, highlighting the undocumented diversity of the Indian dry zone. The Geckoella phylogeny demonstrates deep splits between the Indian species and Sri Lankan G. triedrus, and between Indian dry and wet zone clades, dating back to the late Oligocene. Geckoella and brookii group Hemidactylus show contrasting diversification patterns. Geckoella shows signals of niche conservatism and appears to have retained its ancestral forest habitat. The late Miocene burst in speciation in Geckoella may be linked to the expansion of rain forests during the mid-Miocene climatic optimum and subsequent fragmentation with increasing late Miocene aridification. (C) 2014 Elsevier Inc. All rights reserved.

Highly Sensitive Carbon Nanotubes Coated Etched Fiber Bragg Grating Sensor for Humidity Sensing

The sensing of relative humidity (RH) at room temperature has potential applications in several areas ranging from biomedical to horticulture, paper, and textile industries. In this paper, a highly sensitive humidity sensor based on carbon nanotubes (CNTs) coated on the surface of an etched fiber Bragg grating (EFBG) sensor has been demonstrated, for detecting RH over a wide range of 20%-90% at room temperature. When water molecules interact with the CNT coated EFBG, the effective refractive index of the fiber core changes, resulting in a shift in the Bragg wavelength. It has been possible to achieve a high sensitivity of similar to 31 pm/% RH, which is the highest compared with many of the existing FBG-based humidity sensors. The limit of detection in the CNT coated EFBG has been found to be similar to 0.03 RH. The experimental data shows a linear response of Bragg wavelength shift with increase in humidity. This novel method of incorporating CNTs on to the FBG sensor for humidity sensing has not been reported before.

Sparse Representation Based Acoustic Rangefinders: From Sensor Platforms to Mobile Devices

Acoustic rangerfinders are a promising technology for accurate proximity detection, a critical requirement for many emerging mobile computing applications. While state-of-the-art systems deliver robust ranging performance, the computational intensiveness of their detection mechanism expedites the energy depletion of the associated devices that are typically powered by batteries. The contribution of this article is fourfold. First, it outlines the common factors that are important for ranging. Second, it presents a review of acoustic rangers and identifies their potential problems. Third, it explores the design of an information processing framework based on sparse representation that could potentially address existing challenges, especially for mobile devices. Finally, it presents mu-BeepBeep: a low energy acoustic ranging service for mobile devices, and empirically evaluates its benefits.

Energy-efficient, delay-constrained, QoS-aware broadcast for cooperative wireless sensor networks

The problem of delay-constrained, energy-efficient broadcast in cooperative wireless networks is NP-complete. While centralised setting allows some heuristic solutions, designing heuristics in distributed implementation poses significant challenges. This is more so in wireless sensor networks (WSNs) where nodes are deployed randomly and topology changes dynamically due to node failure/join and environment conditions. This paper demonstrates that careful design of network infrastructure can achieve guaranteed delay bounds and energy-efficiency, and even meet quality of service requirements during broadcast. The paper makes three prime contributions. First, we present an optimal lower bound on energy consumption for broadcast that is tighter than what has been previously proposed. Next, iSteiner, a lightweight, distributed and deterministic algorithm for creation of network infrastructure is discussed. iPercolate is the algorithm that exploits this structure to cooperatively broadcast information with guaranteed delivery and delay bounds, while allowing real-time traffic to pass undisturbed.

Fabrication and Experimentation of a Cantilever Beam Based Piezoelectric Actuator and Sensor for Vibration Energy Harvesting

In the immediate surroundings of our daily life, we can find a lot of places where the energy in the form of vibration is being wasted. Therefore, we have enormous opportunities to utilize the same. Piezoelectric character of matter enables us to convert this mechanical vibration energy into electrical energy which can be stored and used to power other device, instead of being wasted. This work is done to realize both actuator and sensor in a cantilever beam based on piezoelectricity. The sensor part is called vibration energy harvester. The numerical analyses were performed for the cantilever beam using the commercial package ANSYS and MATLAB. The cantilever beam is realized by taking a plate and fixing its one end between two massive plates. Two PZT patches were glued to the beam on its two faces. Experiments were performed using data acquisition system (DAQ) and LABVIEW software for actuating and sensing the vibration of the cantilever beam.

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.

Adaptive Sleep-Wake Control using Reinforcement Learning in Sensor Networks

The aim in this paper is to allocate the `sleep time' of the individual sensors in an intrusion detection application so that the energy consumption from the sensors is reduced, while keeping the tracking error to a minimum. We propose two novel reinforcement learning (RL) based algorithms that attempt to minimize a certain long-run average cost objective. Both our algorithms incorporate feature-based representations to handle the curse of dimensionality associated with the underlying partially-observable Markov decision process (POMDP). Further, the feature selection scheme used in our algorithms intelligently manages the energy cost and tracking cost factors, which in turn assists the search for the optimal sleeping policy. We also extend these algorithms to a setting where the intruder's mobility model is not known by incorporating a stochastic iterative scheme for estimating the mobility model. The simulation results on a synthetic 2-d network setting are encouraging.