48 resultados para Optical detection systems


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Information forms the basis of modern technology. To meet the ever-increasing demand for information, means have to be devised for a more efficient and better-equipped technology to intelligibly process data. Advances in photonics have made their impact on each of the four key applications in information processing, i.e., acquisition, transmission, storage and processing of information. The inherent advantages of ultrahigh bandwidth, high speed and low-loss transmission has already established fiber-optics as the backbone of communication technology. However, the optics to electronics inter-conversion at the transmitter and receiver ends severely limits both the speed and bit rate of lightwave communication systems. As the trend towards still faster and higher capacity systems continues, it has become increasingly necessary to perform more and more signal-processing operations in the optical domain itself, i.e., with all-optical components and devices that possess a high bandwidth and can perform parallel processing functions to eliminate the electronic bottleneck.

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Composite T-joints are commonly used in modern composite airframe, pressure vessels and piping structures, mainly to increase the bending strength of the joint and prevents buckling of plates and shells, and in multi-cell thin-walled structures. Here we report a detailed study on the propagation of guided ultrasonic wave modes in a composite T-joint and their interactions with delamination in the co-cured co-bonded flange. A well designed guiding path is employed wherein the waves undergo a two step mode conversion process, one is due to the web and joint filler on the back face of the flange and the other is due to the delamination edges close to underneath the accessible surface of the flange. A 3D Laser Doppler Vibrometer is used to obtain the three components of surface displacements/velocities of the accessible face of the flange of the T-joint. The waves are launched by a piezo ceramic wafer bonded on to the back surface of the flange. What is novel in the proposed method is that the location of any change in material/geometric properties can be traced by computing a frequency domain power flow along a scan line. The scan line can be chosen over a grid either during scan or during post-processing of the scan data off-line. The proposed technique eliminates the necessity of baseline data and disassembly of structure for structural interrogation.

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A Monte Carlo model of ultrasound modulation of multiply scattered coherent light in a highly scattering media has been carried out for estimating the phase shift experienced by a photon beam on its transit through US insonified region. The phase shift is related to the tissue stiffness, thereby opening an avenue for possible breast tumor detection. When the scattering centers in the tissue medium is exposed to a deterministic forcing with the help of a focused ultrasound (US) beam, due to the fact that US-induced oscillation is almost along particular direction, the direction defined by the transducer axis, the scattering events increase, thereby increasing the phase shift experienced by light that traverses through the medium. The phase shift is found to increase with increase in anisotropy g of the medium. However, as the size of the focused region which is the region of interest (ROI) increases, a large number of scattering events take place within the ROI, the ensemble average of the phase shift (Delta phi) becomes very close to zero. The phase of the individual photon is randomly distributed over 2 pi when the scattered photon path crosses a large number of ultrasound wavelengths in the focused region. This is true at high ultrasound frequency (1 MHz) when mean free path length of photon l(s) is comparable to wavelength of US beam. However, at much lower US frequencies (100 Hz), the wavelength of sound is orders of magnitude larger than l(s), and with a high value of g (g 0.9), there is a distinct measurable phase difference for the photon that traverses through the insonified region. Experiments are carried out for validation of simulation results.

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Biopolymer used for the production of nanoparticles (NPs) has attracted increasing attention. In the presence article we use aqueous solution of polysaccharide Cyamopsis tetragonaloba commonly known as guar gum (GG), from plants. GG acts as reductive preparation of silver nanoparticles which are found to be <10. nm in size. The uniformity of the NPs size was measured by the SEM and TEM, while a face centered cubic structure of crystalline silver nanoparticles was characterized using powder X-ray diffraction technique. Aqueous ammonia sensing study of polymer/silver nanoparticles nanocomposite (GG/AgNPs NC) was performed by optical method based on surface plasmon resonance (SPR). The performances of optical sensor were investigated which provide the excellent result. The response time of 2-3. s and the detection limit of ammonia solution, 1. ppm were found at room temperature. Thus, in future this room temperature optical ammonia sensor can be used for clinical and medical diagnosis for detecting low ammonia level in biological fluids, such as plasma, sweat, saliva, cerebrospinal liquid or biological samples in general for various biomedical applications in human. © 2012 Elsevier B.V.

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In this paper, we employ message passing algorithms over graphical models to jointly detect and decode symbols transmitted over large multiple-input multiple-output (MIMO) channels with low density parity check (LDPC) coded bits. We adopt a factor graph based technique to integrate the detection and decoding operations. A Gaussian approximation of spatial interference is used for detection. This serves as a low complexity joint detection/decoding approach for large dimensional MIMO systems coded with LDPC codes of large block lengths. This joint processing achieves significantly better performance than the individual detection and decoding scheme.

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We report the encapsulation of optical brightening agent (OBA) into hollow microcapsules prepared by the controlled Layer- by-Layer (LbL) self-assembly process, achieved by the sequential adsorption of oppositely charged polyelectrolytes using negatively charged silica template. Loading takes place by spontaneous deposition method which was proved by confocal laser scanning microscopy (CLSM) using rhodamine 6G (Rd6G) as a fluorescent probe. The loading of the OBA into the microcapsules was found to be dependent on the feeding concentration, pH of the medium, and loading temperature. The encapsulation efficiency of OBA decreased on increasing feeding concentration. Maximum loading was observed at pH 4 and amount of OBA loaded decreased with increase in pH. The loaded OBA was released in a sustained manner for 8 h. No degradation of the OBA was observed during the process of encapsulation and release. Polyelectrolyte capsules potentially offer an innovative way of encapsulating large amounts of active materials for a variety of applications. (c) 2012 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 127: 1609-1614, 2013

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In this paper, we are interested in high spectral efficiency multicode CDMA systems with large number of users employing single/multiple transmit antennas and higher-order modulation. In particular, we consider a local neighborhood search based multiuser detection algorithm which offers very good performance and complexity, suited for systems with large number of users employing M-QAM/M-PSK. We apply the algorithm on the chip matched filter output vector. We demonstrate near-single user (SU) performance of the algorithm in CDMA systems with large number of users using 4-QAM/16-QAM/64-QAM/8-PSK on AWGN, frequency-flat, and frequency-selective fading channels. We further show that the algorithm performs very well in multicode multiple-input multiple-output (MIMO) CDMA systems as well, outperforming other linear detectors and interference cancelers reported in the literature for such systems. The per-symbol complexity of the search algorithm is O(K2n2tn2cM), K: number of users, nt: number of transmit antennas at each user, nc: number of spreading codes multiplexed on each transmit antenna, M: modulation alphabet size, making the algorithm attractive for multiuser detection in large-dimension multicode MIMO-CDMA systems with M-QAM.

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This paper proposes an algorithm for joint data detection and tracking of the dominant singular mode of a time varying channel at the transmitter and receiver of a time division duplex multiple input multiple output beamforming system. The method proposed is a modified expectation maximization algorithm which utilizes an initial estimate to track the dominant modes of the channel at the transmitter and the receiver blindly; and simultaneously detects the un known data. Furthermore, the estimates are constrained to be within a confidence interval of the previous estimate in order to improve the tracking performance and mitigate the effect of error propagation. Monte-Carlo simulation results of the symbol error rate and the mean square inner product between the estimated and the true singular vector are plotted to show the performance benefits offered by the proposed method compared to existing techniques.

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The Wheeler-Feynman (WF) absorber theory of radiation though no more of interest in explaining self interaction of an electron, can be very useful in today's research in small scale optical systems. The significance of the WF absorber is the use of time-symmetrical solution of Maxwell's equations as opposed to only the retarded solution. The radiative coupling of emitters to nano wires in the near field and change in their lifetimes due to small mode volume enclosures have been elucidated with the retarded solutions before. These solutions have also been shown to agree with quantum electrodynamics, thus allowing for classical electromagnetic approaches in such problems. It is here assumed that the radiative coupling of the emitter with a body is in proportion to its contribution to the classical force of radiative reaction as derived in the WF absorber theory. Representing such nano structures as a partial WF absorber acting on the emitter makes the computations considerably easier than conventional electromagnetic solutions for full boundary conditions.

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A wave propagation based approach for the detection of damage in components of structures having periodic damage has been proposed. Periodic damage pattern may arise in a structure due to periodicity in geometry and in loading. The method exploits the Block-Floquet band formation mechanism, a feature specific to structures with periodicity, to identify propagation bands (pass bands) and attenuation bands (stop bands) at different frequency ranges. The presence of damage modifies the wave propagation behaviour forming these bands. With proper positioning of sensors a damage force indicator (DFI) method can be used to locate the defect at an accuracy level of sensor to sensor distance. A wide range of transducer frequency may be used to obtain further information about the shape and size of the damage. The methodology is demonstrated using a few 1-D structures with different kinds of periodicity and damage. For this purpose, dynamic stiffness matrix is formed for the periodic elements to obtain the dispersion relationship using frequency domain spectral element and spectral super element method. The sensitivity of the damage force indicator for different types of periodic damages is also analysed.

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In this paper, we propose a low-complexity algorithm based on Markov chain Monte Carlo (MCMC) technique for signal detection on the uplink in large scale multiuser multiple input multiple output (MIMO) systems with tens to hundreds of antennas at the base station (BS) and similar number of uplink users. The algorithm employs a randomized sampling method (which makes a probabilistic choice between Gibbs sampling and random sampling in each iteration) for detection. The proposed algorithm alleviates the stalling problem encountered at high SNRs in conventional MCMC algorithm and achieves near-optimal performance in large systems with M-QAM. A novel ingredient in the algorithm that is responsible for achieving near-optimal performance at low complexities is the joint use of a randomized MCMC (R-MCMC) strategy coupled with a multiple restart strategy with an efficient restart criterion. Near-optimal detection performance is demonstrated for large number of BS antennas and users (e.g., 64, 128, 256 BS antennas/users).

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In this paper, we consider signal detection in nt × nr underdetermined MIMO (UD-MIMO) systems, where i) nt >; nr with a overload factor α = nt over nr >; 1, ii) nt symbols are transmitted per channel use through spatial multiplexing, and iii) nt, nr are large (in the range of tens). A low-complexity detection algorithm based on reactive tabu search is considered. A variable threshold based stopping criterion is proposed which offers near-optimal performance in large UD-MIMO systems at low complexities. A lower bound on the maximum likelihood (ML) bit error performance of large UD-MIMO systems is also obtained for comparison. The proposed algorithm is shown to achieve BER performance close to the ML lower bound within 0.6 dB at an uncoded BER of 10-2 in 16 × 8 V-BLAST UD-MIMO system with 4-QAM (32 bps/Hz). Similar near-ML performance results are shown for 32 × 16, 32 × 24 V-BLAST UD-MIMO with 4-QAM/16-QAM as well. A performance and complexity comparison between the proposed algorithm and the λ-generalized sphere decoder (λ-GSD) algorithm for UD-MIMO shows that the proposed algorithm achieves almost the same performance of λ-GSD but at a significantly lesser complexity.

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Lattice reduction (LR) aided detection algorithms are known to achieve the same diversity order as that of maximum-likelihood (ML) detection at low complexity. However, they suffer SNR loss compared to ML performance. The SNR loss is mainly due to imperfect orthogonalization and imperfect nearest neighbor quantization. In this paper, we propose an improved LR-aided (ILR) detection algorithm, where we specifically target to reduce the effects of both imperfect orthogonalization and imperfect nearest neighbor quantization. The proposed ILR detection algorithm is shown to achieve near-ML performance in large-MIMO systems and outperform other LR-aided detection algorithms in the literature. Specifically, the SNR loss incurred by the proposed ILR algorithm compared to ML performance is just 0.1 dB for 4-QAM and < 0.5 dB for 16-QAM in 16 x 16 V-BLAST MIMO system. This performance is superior compared to those of other LR-aided detection algorithms, whose SNR losses are in the 2 dB to 9 dB range.

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Detection of pathogens from infected biological samples through conventional process involves cell lysis and purification. The main objective of this work is to minimize the time and sample loss, as well as to increase the efficiency of detection of biomolecules. Electrical lysis of medical sample is performed in a closed microfluidic channel in a single integrated platform where the downstream analysis of the sample is possible. The device functions involve, in a sequence, flow of lysate from lysis chamber passed through a thermal denaturation counter where dsDNA is denatured to ssDNA, which is controlled by heater unit. A functionalized binding chamber of ssDNA is prepared by using ZnO nanorods as the matrix and functionalized with bifunctional carboxylic acid, 16-(2-pyridyldithiol) hexadecanoic acid (PDHA) which is further attached to a linker molecule 1-ethyl-3-(3-dimethylaminopropyl) (EDC). Linker moeity is then covalently bound to photoreactive protoporphyrin (PPP) molecule. The photolabile molecule protoporphyrin interacts with -NH2 labeled single stranded DNA (ssDNA) which thus acts as a probe to detect complimentary ssDNA from target organisms. Thereafter the bound DNA with protoporphyrin is exposed to an LED of particular wavelength for a definite period of time and DNA was eluted and analyzed. UV/Vis spectroscopic analysis at 260/280 nm wavelength confirms the purity and peak at 260 nm is reconfirmed for the elution of target DNA. Quantitative and qualitative data obtained from the current experiments show highly selective detection of biomolecule such as DNA which have large number of future applications in Point-of-Care devices.

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It is well known that the impulse response of a wide-band wireless channel is approximately sparse, in the sense that it has a small number of significant components relative to the channel delay spread. In this paper, we consider the estimation of the unknown channel coefficients and its support in OFDM systems using a sparse Bayesian learning (SBL) framework for exact inference. In a quasi-static, block-fading scenario, we employ the SBL algorithm for channel estimation and propose a joint SBL (J-SBL) and a low-complexity recursive J-SBL algorithm for joint channel estimation and data detection. In a time-varying scenario, we use a first-order autoregressive model for the wireless channel and propose a novel, recursive, low-complexity Kalman filtering-based SBL (KSBL) algorithm for channel estimation. We generalize the KSBL algorithm to obtain the recursive joint KSBL algorithm that performs joint channel estimation and data detection. Our algorithms can efficiently recover a group of approximately sparse vectors even when the measurement matrix is partially unknown due to the presence of unknown data symbols. Moreover, the algorithms can fully exploit the correlation structure in the multiple measurements. Monte Carlo simulations illustrate the efficacy of the proposed techniques in terms of the mean-square error and bit error rate performance.