275 resultados para Player detection


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MEMS systems are technologically developed from integrated circuit industry to create miniature sensors and actuators. Originally these semiconductor processes and materials were used to build electrical and mechanical systems, but expanded to include biological, optical fluidic magnetic and other systems 12]. Here a novel approach is suggested where in two different fields are integrated via moems, micro fluidics and ring resonators. It is well known at any preliminary stage of disease onset, many physiological changes occur in the body fluids like saliva, blood, urine etc. The drawback till now was that current calibrations are not sensitive enough to detect the minor physiological changes. This is overcome using optical detector techniques 1]. The basic concepts of ring resonators, with slight variations can be used for optical detection of these minute disease markers. A well known fact of ring resonators is that a change in refractive index will trigger a shift in the resonant wavelength 5]. The trigger for the wavelength shift in the case discussed will be the presence of disease agents. To trap the disease agents specific antibody has to be used (e. g. BSA).

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The importance of developing effective assays to diagnose, monitor and evaluate human lymphatic filariasis has been emphasized by the World Health Organization. Presently, few immunodiagnostics are available for filarial monitoring programmes. The Wuchereria bancrofti (Wb) SXP-1 parasite protein, with 84% homology to Brugia malayi (Bm) SXP-1, was found to be highly immunogenic. WbSXP-1 is one among the diagnostic candidate molecules that were used for developing a rapid-antibody-flow-through diagnostic kit for filariasis. Studies were initiated with the aim of developing monoclonal antibodies against recombinant WbSXP-1 and prospective applications for the detection of both circulating Wb and Bm antigens in serum samples from infected individuals. The monoclones 1A6C2 of subclass IgG1k, and 2A12F8 of class IgM, specifically detected Wb and Bm microfilaria isolated from patients and did not show cross-reactivity with other filarial recombinant antigens. We anticipate that this work will address the problems faced in the rapid diagnosis of human lymphatic filariasis in endemic areas in developing countries.

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FDDI (Fibre Distributed Data Interface) is a 100 Mbit/s token ring network with two counter rotating optical rings. In this paper various possible faults (like lost token, link failures, etc.) are considered, and fault detection and the ring recovery process in case of a failure and the reliability mechanisms provided are studied. We suggest a new method to improve the fault detection and ring recovery process. The performance improvement in terms of station queue length and the average delay is compared with the performance of the existing fault detection and ring recovery process through simulation. We also suggest a modification for the physical configuration of the FDDI networks within the guidelines set by the standard to make the network more reliable. It is shown that, unlike the existing FDDI network, full connectivity is maintained among the stations even when multiple single link failures occur. A distributed algorithm is proposed for link reconfiguration of the modified FDDI network when many successive as well as simultaneous link failures occur. The performance of the modified FDDI network under link failures is studied through simulation and compared with that of the existing FDDI network.

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Large MIMO systems with tens of antennas in each communication terminal using full-rate non-orthogonal space-time block codes (STBC) from Cyclic Division Algebras (CDA) can achieve the benefits of both transmit diversity as well as high spectral efficiencies. Maximum-likelihood (ML) or near-ML decoding of these large-sized STBCs at low complexities, however, has been a challenge. In this paper, we establish that near-ML decoding of these large STBCs is possible at practically affordable low complexities. We show that the likelihood ascent search (LAS) detector, reported earlier by us for V-BLAST, is able to achieve near-ML uncoded BER performance in decoding a 32x32 STBC from CDA, which employs 32 transmit antennas and sends 32(2) = 1024 complex data symbols in 32 time slots in one STBC matrix (i.e., 32 data symbols sent per channel use). In terms of coded BER, with a 16x16 STBC, rate-3/4 turbo code and 4-QAM (i.e., 24 bps/Hz), the LAS detector performs close to within just about 4 dB from the theoretical MIMO capacity. Our results further show that, with LAS detection, information lossless (ILL) STBCs perform almost as good as full-diversity ILL (FD-ILL) STBCs. Such low-complexity detectors can potentially enable implementation of high spectral efficiency large MIMO systems that could be considered in wireless standards.

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In this paper, we are concerned with low-complexity detection in large multiple-input multiple-output (MIMO) systems with tens of transmit/receive antennas. Our new contributions in this paper are two-fold. First, we propose a low-complexity algorithm for large-MIMO detection based on a layered low-complexity local neighborhood search. Second, we obtain a lower bound on the maximum-likelihood (ML) bit error performance using the local neighborhood search. The advantages of the proposed ML lower bound are i) it is easily obtained for MIMO systems with large number of antennas because of the inherent low complexity of the search algorithm, ii) it is tight at moderate-to-high SNRs, and iii) it can be tightened at low SNRs by increasing the number of symbols in the neighborhood definition. Interestingly, the proposed detection algorithm based on the layered local search achieves bit error performances which are quite close to this lower bound for large number of antennas and higher-order QAM. For e. g., in a 32 x 32 V-BLAST MIMO system, the proposed detection algorithm performs close to within 1.7 dB of the proposed ML lower bound at 10(-3) BER for 16-QAM (128 bps/Hz), and close to within 4.5 dB of the bound for 64-QAM (192 bps/Hz).

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The impulse response of a typical wireless multipath channel can be modeled as a tapped delay line filter whose non-zero components are sparse relative to the channel delay spread. In this paper, a novel method of estimating such sparse multipath fading channels for OFDM systems is explored. In particular, Sparse Bayesian Learning (SBL) techniques are applied to jointly estimate the sparse channel and its second order statistics, and a new Bayesian Cramer-Rao bound is derived for the SBL algorithm. Further, in the context of OFDM channel estimation, an enhancement to the SBL algorithm is proposed, which uses an Expectation Maximization (EM) framework to jointly estimate the sparse channel, unknown data symbols and the second order statistics of the channel. The EM-SBL algorithm is able to recover the support as well as the channel taps more efficiently, and/or using fewer pilot symbols, than the SBL algorithm. To further improve the performance of the EM-SBL, a threshold-based pruning of the estimated second order statistics that are input to the algorithm is proposed, and its mean square error and symbol error rate performance is illustrated through Monte-Carlo simulations. Thus, the algorithms proposed in this paper are capable of obtaining efficient sparse channel estimates even in the presence of a small number of pilots.

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Recently, we reported a low-complexity likelihood ascent search (LAS) detection algorithm for large MIMO systems with several tens of antennas that can achieve high spectral efficiencies of the order of tens to hundreds of bps/Hz. Through simulations, we showed that this algorithm achieves increasingly near SISO AWGN performance for increasing number of antennas in Lid. Rayleigh fading. However, no bit error performance analysis of the algorithm was reported. In this paper, we extend our work on this low-complexity large MIMO detector in two directions: i) We report an asymptotic bit error probability analysis of the LAS algorithm in the large system limit, where N-t, N-r -> infinity keeping N-t = N-r, where N-t and N-r are the number of transmit and receive antennas, respectively. Specifically, we prove that the error performance of the LAS detector for V-BLAST with 4-QAM in i.i.d. Rayleigh fading converges to that of the maximum-likelihood (ML) detector as N-t, N-r -> infinity keeping N-t = N-r ii) We present simulated BER and nearness to capacity results for V-BLAST as well as high-rate non-orthogonal STBC from Division Algebras (DA), in a more realistic spatially correlated MIMO channel model. Our simulation results show that a) at an uncoded BER of 10(-3), the performance of the LAS detector in decoding 16 x 16 STBC from DA with N-t = = 16 and 16-QAM degrades in spatially correlated fading by about 7 dB compared to that in i.i.d. fading, and 19) with a rate-3/4 outer turbo code and 48 bps/Hz spectral efficiency, the performance degrades by about 6 dB at a coded BER of 10(-4). Our results further show that providing asymmetry in number of antennas such that N-r > N-t keeping the total receiver array length same as that for N-r = N-t, the detector is able to pick up the extra receive diversity thereby significantly improving the BER performance.

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Thirteen terrestrial psychrotrophic bacteria from Antarctica were screened for the presence of a thermolabile ribonuclease (RNAase-HL). The enzyme was detected in three isolates of Pseudomonas fluorescens and one isolate of Pseudomonas syringae. It was purified from one P. Fluorescens isolate and the molecular mass of the enzyme as determined by SDS-PAGE was 16 kDa. RNAase-HL exhibited optimum activity around 40 degrees C at pH 7.4. It could hydrolyse Escherichia coli RNA and the synthetic substrates poly(A), poly(C), poly(U) and poly(A-U). Unlike the crude RNAase from mesophilic P. Fluorescens and pure bovine pancreatic RNAase A which were active even at 65 degrees C, RNAase-HL was totally and irreversibly inactivated at 65 degrees C.

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Nitrogen-fixing bacterial isolate from the intercellular spaces of tomato root cortical cells was studied for the location of nif genes on the chromosomal or plasmid DNA. The bacterial isolate showed two plasmids of approximate molecular sizes of 220 and 120 kb. Klebsiella pneumoniae nif HDK probe hybridized with the chromosomal DNA and not with the plasmid DNA thereby showing that nif genes are localised on the chromosomal DNA.

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Leak detection in the fuel channels is one of the challenging problems during the in-service inspection (ISI) of Pressurised Heavy Water Reactors (PHWRs). In this paper, the use of an acoustic emission (AE) technique together with AE signal analysis is described, to detect a leak that was ncountered in one (or more) of the 306 fuel channels of the Madras Atomic Power Station (PHWR), Unit I. The paper describes the problems encountered during the ISI, the experimental methods adopted and the results obtained. Results obtained using acoustic emission signal analysis are compared with those obtained from other leak detection methods used in such cases.

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The application of nucleic acid probes, in the detection of pathogenic micro-organisms, has become an integral part of diagnostic technologies. In this study, Plasmodium vivax-specific DNA probes have been identified by carrying out genomic subtractive hybridization. In this approach, the recombinant clones from a P. vivax genomic library are screened with radiolabelled human and P. falciparum DNA. The colonies which react with labelled P. falciparum and human DNA are eliminated and those which do not produce any autoradiographic signal have been subjected to further screening procedures. Three Fl vivax specific DNA probes have been obtained by these repeated screenings. Further analyses indicate that these probes are specific and sensitive enough to detect P. vivax infection in clinical blood samples when used in a non-radioactive DNA hybridization assay. (C) 1995 Academic Press Limited

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The paper examines the suitability of the generalized data rule in training artificial neural networks (ANN) for damage identification in structures. Several multilayer perceptron architectures are investigated for a typical bridge truss structure with simulated damage stares generated randomly. The training samples have been generated in terms of measurable structural parameters (displacements and strains) at suitable selected locations in the structure. Issues related to the performance of the network with reference to hidden layers and hidden. neurons are examined. Some heuristics are proposed for the design of neural networks for damage identification in structures. These are further supported by an investigation conducted on five other bridge truss configurations.

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A link failure in the path of a virtual circuit in a packet data network will lead to premature disconnection of the circuit by the end-points. A soft failure will result in degraded throughput over the virtual circuit. If these failures can be detected quickly and reliably, then appropriate rerouteing strategies can automatically reroute the virtual circuits that use the failed facility. In this paper, we develop a methodology for analysing and designing failure detection schemes for digital facilities. Based on errored second data, we develop a Markov model for the error and failure behaviour of a T1 trunk. The performance of a detection scheme is characterized by its false alarm probability and the detection delay. Using the Markov model, we analyse the performance of detection schemes that use physical layer or link layer information. The schemes basically rely upon detecting the occurrence of severely errored seconds (SESs). A failure is declared when a counter, that is driven by the occurrence of SESs, reaches a certain threshold.For hard failures, the design problem reduces to a proper choice;of the threshold at which failure is declared, and on the connection reattempt parameters of the virtual circuit end-point session recovery procedures. For soft failures, the performance of a detection scheme depends, in addition, on how long and how frequent the error bursts are in a given failure mode. We also propose and analyse a novel Level 2 detection scheme that relies only upon anomalies observable at Level 2, i.e. CRC failures and idle-fill flag errors. Our results suggest that Level 2 schemes that perform as well as Level 1 schemes are possible.

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The problem of sensor-network-based distributed intrusion detection in the presence of clutter is considered. It is argued that sensing is best regarded as a local phenomenon in that only sensors in the immediate vicinity of an intruder are triggered. In such a setting, lack of knowledge of intruder location gives rise to correlated sensor readings. A signal-space view-point is introduced in which the noise-free sensor readings associated to intruder and clutter appear as surfaces f(s) and f(g) and the problem reduces to one of determining in distributed fashion, whether the current noisy sensor reading is best classified as intruder or clutter. Two approaches to distributed detection are pursued. In the first, a decision surface separating f(s) and f(g) is identified using Neyman-Pearson criteria. Thereafter, the individual sensor nodes interactively exchange bits to determine whether the sensor readings are on one side or the other of the decision surface. Bounds on the number of bits needed to be exchanged are derived, based on communication-complexity (CC) theory. A lower bound derived for the two-party average case CC of general functions is compared against the performance of a greedy algorithm. Extensions to the multi-party case is straightforward and is briefly discussed. The average case CC of the relevant greaterthan (CT) function is characterized within two bits. Under the second approach, each sensor node broadcasts a single bit arising from appropriate two-level quantization of its own sensor reading, keeping in mind the fusion rule to be subsequently applied at a local fusion center. The optimality of a threshold test as a quantization rule is proved under simplifying assumptions. Finally, results from a QualNet simulation of the algorithms are presented that include intruder tracking using a naive polynomial-regression algorithm. 2010 Elsevier B.V. All rights reserved.

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Polyaniline (PANI) is one of the most extensively used conjugated polymers in the design of electrochemical sensors. In this study, we report electrochemical dye detection based on PANI for the adsorption of both anionic and cationic dyes from solution. The inherent property of PANI to adsorb dyes has been explored for the development of electrochemical detection of dye in solution. The PANI film was grown on electrode via electrochemical polymerization. The as grown PANI film could easily adsorb the dye in the electrolyte solution and form an insulating layer on the PANI coated electrode. As a result, the current intensity of the PANI film was significantly altered. Furthermore, PANI coated stainless steel (SS) electrodes show a change in the current intensity of Fe2+/Fe3+ redox peaks due to the addition of dye in electrolyte solution. PANI films coated on both Pt electrodes and non-expensive SS electrodes showed the concentration of dye adsorbed is directly proportional to the current intensity or potential shift and thus can be used for the quantitative detection of textile dyes at very low concentrations. (C) 2011 Elsevier B.V. All rights reserved.