FUSION OF ALGORITHMS FOR COMPRESSED SENSING

Numerous algorithms have been proposed recently for sparse signal recovery in Compressed Sensing (CS). In practice, the number of measurements can be very limited due to the nature of the problem and/or the underlying statistical distribution of the non-zero elements of the sparse signal may not be known a priori. It has been observed that the performance of any sparse signal recovery algorithm depends on these factors, which makes the selection of a suitable sparse recovery algorithm difficult. To take advantage in such situations, we propose to use a fusion framework using which we employ multiple sparse signal recovery algorithms and fuse their estimates to get a better estimate. Theoretical results justifying the performance improvement are shown. The efficacy of the proposed scheme is demonstrated by Monte Carlo simulations using synthetic sparse signals and ECG signals selected from MIT-BIH database.

pH sensing by single and multi-layer hydrogel coated Fiber Bragg Grating

In this paper we show a novel chemo-mechanical-optical sensing mechanism in single and multi-layer hydrogel coated Fiber Bragg Grating (FBG) and demonstrate specific application in pH activated processes. The sensing device is based on the ionizable monomers inside the hydrogel which reversibly dissociates as a function of the pH and consequently resulting in osmotic pressure difference between the gel and the solution. This pressure gradient causes the hydrogel to deform which in turn induces secondary strain on the FBG sensor resulting in shift in the Bragg wavelength. We also report on the sensitivity factor of single and multilayer hydrogel coated FBG at various different pH.

Modification of Extended Open Frameworks with Fluorescent Tags for Sensing Explosives: Competition between Size Selectivity and Electron Deficiency

Three new electron-rich metal-organic frameworks (MOF-1-MOF-3) have been synthesized by employing ligands bearing aromatic tags. The key role of the chosen aromatic tags is to enhance the -electron density of the luminescent MOFs. Single-crystal X-ray structures have revealed that these MOFs form three-dimensional porous networks with the aromatic tags projecting inwardly into the pores. These highly luminescent electron-rich MOFs have been successfully utilized for the detection of explosive nitroaromatic compounds (NACs) on the basis of fluorescence quenching. Although all of the prepared MOFs can serve as sensors for NACs, MOF-1 and MOF-2 exhibit superior sensitivity towards 4-nitrotoluene (4-NT) and 2,4-dinitrotoluene (DNT) compared to 2,4,6-trinitrotoluene (TNT) and 1,3,5-trinitrobenzene (TNB). MOF-3, on the other hand, shows an order of sensitivity in accordance with the electron deficiencies of the substrates. To understand such anomalous behavior, we have thoroughly analyzed both the steady-state and time-resolved fluorescence quenching associated with these interactions. Determination of static Stern-Volmer constants (K-S) as well as collisional constants (K-C) has revealed that MOF-1 and MOF-2 have higher K-S values with 4-NT than with TNT, whereas for MOF-3 the reverse order is observed. This apparently anomalous phenomenon was well corroborated by theoretical calculations. Moreover, recyclability and sensitivity studies have revealed that these MOFs can be reused several times and that their sensitivities towards TNT solution are at the parts per billion (ppb) level.

Progressive fusion of reconstruction algorithms for low latency applications in compressed sensing

Recently, it has been shown that fusion of the estimates of a set of sparse recovery algorithms result in an estimate better than the best estimate in the set, especially when the number of measurements is very limited. Though these schemes provide better sparse signal recovery performance, the higher computational requirement makes it less attractive for low latency applications. To alleviate this drawback, in this paper, we develop a progressive fusion based scheme for low latency applications in compressed sensing. In progressive fusion, the estimates of the participating algorithms are fused progressively according to the availability of estimates. The availability of estimates depends on computational complexity of the participating algorithms, in turn on their latency requirement. Unlike the other fusion algorithms, the proposed progressive fusion algorithm provides quick interim results and successive refinements during the fusion process, which is highly desirable in low latency applications. We analyse the developed scheme by providing sufficient conditions for improvement of CS reconstruction quality and show the practical efficacy by numerical experiments using synthetic and real-world data. (C) 2013 Elsevier B.V. All rights reserved.

Effect of post-deposition annealing on transverse piezoelectric coefficient and vibration sensing performance of ZnO thin films

The present experimental study investigates the influence of post-deposition annealing on the transverse piezoelectric coefficient (d(31)) value of ZnO thin films deposited on a flexible metal alloy substrate, and its relationship with the vibration sensing performance. Highly c-axis oriented and crystalline ZnO thin films were deposited on flexible Phynox alloy substrate via radio frequency (RF) reactive magnetron sputtering. ZnO thin film samples were annealed at different temperatures ranging from 100 degrees C to 500 degrees C, resulting in the temperature of 300 degrees C determined as the optimum annealing temperature. The crystallinity, morphology, microstructure, and rms surface roughness of annealed ZnO thin films were systematically investigated by X-ray Diffraction (XRD), Scanning Electron Microscopy (SEM), and Atomic Force Microscopy (AFM), respectively. The piezoelectric d(31) coefficient value was measured by 4-point bending method. ZnO thin film annealed at 300 degrees C was highly c-axis oriented, crystalline, possesses fine surface morphology with uniformity in the grain size. This film showed higher d(31) coefficient value of 7.2 pm V-1. A suitable in-house designed and developed experimental set-up, for evaluating the vibration sensing performance of annealed ZnO thin films is discussed. As expected the ZnO thin film annealed at 300 degrees C showed relatively better result for vibration sensing studies. It generates comparatively higher peak output voltage of 147 mV, due to improved structural and morphological properties, and higher piezoelectric d(31) coefficient value. (C) 2014 Elsevier B. V. All rights reserved.

Optical bio-sensing devices based on etched fiber Bragg gratings coated with carbon nanotubes and graphene oxide along with a specific dendrimer

We demonstrate that etched fiber Bragg gratings (eFBGs) coated with single walled carbon nanotubes (SWNTs) and graphene oxide (GO) are highly sensitive and accurate biochemical sensors. Here, for detecting protein concanavalin A (Con A), mannose-functionalized poly(propyl ether imine) (PETIM) dendrimers (DMs) have been attached to the SWNTs (or GO) coated on the surface modified eFBG. The dendrimers act as multivalent ligands, having specificity to detect lectin Con A. The specificity of the sensor is shown by a much weaker response (factor of similar to 2500 for the SWNT and similar to 2000 for the GO coated eFBG) to detect non specific lectin peanut agglutinin. DM molecules functionalized GO coated eFBG sensors showed excellent specificity to Con A even in the presence of excess amount of an interfering protein bovine serum albumin. The shift in the Bragg wavelength (Delta lambda(B)) with respect to the lambda(B) values of SWNT (or GO)-DM coated eFBG for various concentrations of lectin follows Langmuir type adsorption isotherm, giving an affinity constant of similar to 4 x 10(7) M-1 for SWNTs coated eFBG and similar to 3 x 10(8) M-1 for the GO coated eFBG. (C) 2014 Elsevier B.V. All rights reserved.

A Committee Machine Approach for Compressed Sensing Signal Reconstruction

Although many sparse recovery algorithms have been proposed recently in compressed sensing (CS), it is well known that the performance of any sparse recovery algorithm depends on many parameters like dimension of the sparse signal, level of sparsity, and measurement noise power. It has been observed that a satisfactory performance of the sparse recovery algorithms requires a minimum number of measurements. This minimum number is different for different algorithms. In many applications, the number of measurements is unlikely to meet this requirement and any scheme to improve performance with fewer measurements is of significant interest in CS. Empirically, it has also been observed that the performance of the sparse recovery algorithms also depends on the underlying statistical distribution of the nonzero elements of the signal, which may not be known a priori in practice. Interestingly, it can be observed that the performance degradation of the sparse recovery algorithms in these cases does not always imply a complete failure. In this paper, we study this scenario and show that by fusing the estimates of multiple sparse recovery algorithms, which work with different principles, we can improve the sparse signal recovery. We present the theoretical analysis to derive sufficient conditions for performance improvement of the proposed schemes. We demonstrate the advantage of the proposed methods through numerical simulations for both synthetic and real signals.

A MatLAB Based Virtual Phantom for 2D Electrical Impedance Tomography (MatVP2DEIT): Studying the Medical Electrical Impedance Tomography Reconstruction in Computer

Electrical Impedance Tomography (EIT) is a computerized medical imaging technique which reconstructs the electrical impedance images of a domain under test from the boundary voltage-current data measured by an EIT electronic instrumentation using an image reconstruction algorithm. Being a computed tomography technique, EIT injects a constant current to the patient's body through the surface electrodes surrounding the domain to be imaged (Omega) and tries to calculate the spatial distribution of electrical conductivity or resistivity of the closed conducting domain using the potentials developed at the domain boundary (partial derivative Omega). Practical phantoms are essentially required to study, test and calibrate a medical EIT system for certifying the system before applying it on patients for diagnostic imaging. Therefore, the EIT phantoms are essentially required to generate boundary data for studying and assessing the instrumentation and inverse solvers a in EIT. For proper assessment of an inverse solver of a 2D EIT system, a perfect 2D practical phantom is required. As the practical phantoms are the assemblies of the objects with 3D geometries, the developing of a practical 2D-phantom is a great challenge and therefore, the boundary data generated from the practical phantoms with 3D geometry are found inappropriate for assessing a 2D inverse solver. Furthermore, the boundary data errors contributed by the instrumentation are also difficult to separate from the errors developed by the 3D phantoms. Hence, the errorless boundary data are found essential to assess the inverse solver in 2D EIT. In this direction, a MatLAB-based Virtual Phantom for 2D EIT (MatVP2DEIT) is developed to generate accurate boundary data for assessing the 2D-EIT inverse solvers and the image reconstruction accuracy. MatVP2DEIT is a MatLAB-based computer program which simulates a phantom in computer and generates the boundary potential data as the outputs by using the combinations of different phantom parameters as the inputs to the program. Phantom diameter, inhomogeneity geometry (shape, size and position), number of inhomogeneities, applied current magnitude, background resistivity, inhomogeneity resistivity all are set as the phantom variables which are provided as the input parameters to the MatVP2DEIT for simulating different phantom configurations. A constant current injection is simulated at the phantom boundary with different current injection protocols and boundary potential data are calculated. Boundary data sets are generated with different phantom configurations obtained with the different combinations of the phantom variables and the resistivity images are reconstructed using EIDORS. Boundary data of the virtual phantoms, containing inhomogeneities with complex geometries, are also generated for different current injection patterns using MatVP2DEIT and the resistivity imaging is studied. The effect of regularization method on the image reconstruction is also studied with the data generated by MatVP2DEIT. Resistivity images are evaluated by studying the resistivity parameters and contrast parameters estimated from the elemental resistivity profiles of the reconstructed phantom domain. Results show that the MatVP2DEIT generates accurate boundary data for different types of single or multiple objects which are efficient and accurate enough to reconstruct the resistivity images in EIDORS. The spatial resolution studies show that, the resistivity imaging conducted with the boundary data generated by MatVP2DEIT with 2048 elements, can reconstruct two circular inhomogeneities placed with a minimum distance (boundary to boundary) of 2 mm. It is also observed that, in MatVP2DEIT with 2048 elements, the boundary data generated for a phantom with a circular inhomogeneity of a diameter less than 7% of that of the phantom domain can produce resistivity images in EIDORS with a 1968 element mesh. Results also show that the MatVP2DEIT accurately generates the boundary data for neighbouring, opposite reference and trigonometric current patterns which are very suitable for resistivity reconstruction studies. MatVP2DEIT generated data are also found suitable for studying the effect of the different regularization methods on reconstruction process. Comparing the reconstructed image with an original geometry made in MatVP2DEIT, it would be easier to study the resistivity imaging procedures as well as the inverse solver performance. Using the proposed MatVP2DEIT software with modified domains, the cross sectional anatomy of a number of body parts can be simulated in PC and the impedance image reconstruction of human anatomy can be studied.

Going beyond Red with a Tri- and Tetracoordinate Boron Conjugate: Intriguing Near-IR Optical Properties and Applications in Anion Sensing

The design and synthesis of a new tri- and tetracoordinate boron conjugate is reported. The conjugate shows broad near-IR emission (similar to 625-850 nm) and is found to be a selective colorimetric and ratiometric sensor for fluoride ions.

Evaluation. of Transverse Piezoelectric Coefficient of ZnO Thin Films Deposited on Different Flexible Substrates: A Comparative Study on the Vibration Sensing Performance

We report on the systematic comparative study of highly c-axis oriented and crystalline piezoelectric ZnO thin films deposited on four different flexible substrates for vibration sensing application. The flexible substrates employed for present experimental study were namely a metal alloy (Phynox), metal (aluminum), polyimide (Kapton), and polyester (Mylar). ZnO thin films were deposited by an RF reactive magnetron sputtering technique. ZnO thin films of similar thicknesses of 700 +/- 30 nm were deposited on four different flexible substrates to have proper comparative studies. The crystallinity, surface morphology, chemical composition, and roughness of ZnO thin films were evaluated by respective material characterization techniques. The transverse piezoelectric coefficient (d(31)) value for assessing the piezoelectric property of ZnO thin films on different flexible substrates was measured by a four-point bending method. ZnO thin films deposited on Phynox alloy substrate showed relatively better material characterization results and a higher piezoelectric d(31) coefficient value as compared to ZnO films on metal and polymer substrates. In order to experimentally verify the above observations, vibration sensing studies were performed. As expected, the ZnO thin film deposited on Phynox alloy substrate showed better vibration sensing performance. It has generated the highest peak to peak output voltage amplitude of 256 mV as compared to that of aluminum (224 mV), Kapton (144 mV), and Mylar (46 mV). Therefore, metal alloy flexible substrate proves to be a more suitable, advantageous, and versatile choice for integrating ZnO thin films as compared to metal and polymer flexible substrates for vibration sensing applications. The present experimental study is extremely important and helpful for the selection of a suitable flexible substrate for various applications in the field of sensor and actuator technology.

Ultrasonic guided wave sensing properties of PVDF thin film with inter digital electrodes

Ultrasonic strain sensing performance of the large area PVDF with Inter Digital Electrodes (IDE) is studied in this work. Procedure to obtain IDE on a beta-phase PVDF is explained. PVDF film with IDE is bonded on a plate structure and is characterized for its directional sensitivity at different frequencies. Guided waves are induced on the IDE-PVDF sensor from different directions by placing a piezoelectric wafer actuator at different angles. Strain induced on the IDE-PVDF sensor by the guided waves in estimated by using a Laser Doppler Vibrometer (LDV) and a wave propagation model. Using measured voltage response from IDE-PVDF sensor and the strain measurements from LDV the piezoelectric coefficient is estimated in various directions. The variation of 11 e at different angles shows directional sensitivity of the IDE-PVDF sensor to the incident guided waves. The present study provides an effective technique to characterize thin film piezoelectric sensors for ultrasonic strain sensing at very high frequencies of 200 kHz. Often frequency of the guided wave is changed to alter the wavelength to interrogate damages of different sizes in Structural Health Monitoring (SHM) applications. The unique property of directional sensitivity combined with frequency tunability makes the IDE-PVDF sensor most suitable for SHM of structures.

Differentially Selective Chemosensor with Fluorescence Off-On Responses on Cu2+ and Zn2+ Ions in Aqueous Media and Applications in Pyrophosphate Sensing, Live Cell Imaging, and Cytotoxicity

A new benzoyl hydrazone based chemosensor R is synthesized by Schiff base condensation of 2,6-diformyl-4-methylphenol and phenyl carbohydrazide and acts as a highly selective fluorescence sensor for Cu2+ and Zn2+ ions in aqueous media. The reaction of R with CuCl2 or ZnCl2 forms the corresponding dimeric dicopper(II) Cu-2(R)(CH3O)-(NO3)](2)(CH3O)(2) (R-Cu2+) and dizinc(1) Zn-2(R)(2)](NO3)(2) (R-Zn2+) complexes, which are characterized, as R, by conventional techniques including single-crystal X-ray analysis. Electronic absorption and fluorescence titration studies of R with different metal cations in a CH3CN/0.02 M HEPES buffer medium (pH = 7.3) show a highly selective binding affinity only toward Cu(2+)and Zn2+ ions even in the presence of other commonly coexisting ions such as Ne+, K+, Mg2+, Ca2+, Mn2+, Fe2+, Fe3+, Co2+, Ni2+, Cd2+, and Hg2+. Quantification of the fluorescence titration analysis shows that the chemosensor R can indicate the presence of Cu2+ and Zn2+ even at very low concentrations of 17.3 and 16.5 ppb, respectively. R-Zn2+ acts as a selective metal-based fluorescent sensor for inorganic pyrophosphate ion (PPi) even in the presence of other common anions such as F-, Cl-, Br-, I-, CH3COO-, CO32-, HCO3-, N-3(-), SO42-, PPi, AMP, ADP, and ATP in an aqueous medium. The propensity of R as a bioimaging fluorescent probe to detect Cu2+ and Zn2+ ions in human cervical HeLa cancer cell lines and their cytotoxicity against human cervical (HeLa), breast cancer (MCF7), and noncancer breast epithelial (MCF10a) cells have also been investigated. R-Cu2+ shows better cytotoxicity and sensitivity toward cancer cells over noncancer cells than R and R-Zn2+ under identical conditions, with the appearance of apoptotic bodies.

Correlating defect induced ferromagnetism and gas sensing properties of undoped tin oxide sensors

A correlation between gas sensing properties and defect induced Room Temperature Ferromagnetism (RTFM) is demonstrated in non-stoichiometric SnO2 prepared by solution combustion method. The presence of oxygen vacancies (V-O), confirmed by RTFM is identified as the primary factor for enhanced gas sensing effect. The as-prepared SnO2 shows high saturation magnetization of similar to 0.018 emu/g as compared to similar to 0.002 and similar to 0.0005 emu/g in annealed samples and SnO2 prepared by precipitation respectively. The SnO2 prepared by precipitation which is an equilibrium method of synthesis shows lesser defects compared to the combustion product and hence exhibits lesser sensitivity in spite of smaller crystallite size. The study utilizes RTFM as a potential tool to characterize metal oxide gas sensors and recognizes the significance of oxygen vacancies in sensing mechanism over the microstructure. (C) 2014 AIP Publishing LLC.