38 resultados para Acoustic Component Detection


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Introduction: multimodality environment; requirement for greater understanding of the imaging technologies used, the limitations of these technologies, and how to best interpret the results; dose optimization; introduction of new techniques; current practice and best practice; incidental findings, in low-dose CT images obtained as part of the hybrid imaging process, are an increasing phenomenon with advancing CT technology; resultant ethical and medico-legal dilemmas; understanding limitations of these procedures important when reporting images and recommending follow-up; free-response observer performance study was used to evaluate lesion detection in low-dose CT images obtained during attenuation correction acquisitions for myocardial perfusion imaging, on two hybrid imaging systems.

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Two fluorescent molecular receptor based conjugated polymers were used in the detection of a nitroaliphatic liquid explosive (nitromethane) and an explosive taggant (2,3-dimethyl-2,3-dinitrobutane) in the vapor phase. Results have shown that thin films of both polymers display remarkably high sensitivity and selectivity toward these analytes. Very fast, reproducible, and reversible responses were found. The unique behavior of these supramolecular host systems is ascribed to cooperativity effects developed between the calix[4] arene hosts and the phenylene ethynylene-carbazolylene main chains. The calix[4]-arene hosts create a plethora of host-guest binding sites along the polymer backbone, either in their bowl-shaped cavities or between the outer walls of the cavity, to direct guests to the area of the transduction centers (main chain) at which favorable photoinduced electron transfer to the guest molecules occurs and leads to the observed fluorescence quenching. The high tridimensional porous nature of the polymers imparted by the bis-calixarene moieties concomitantly allows fast diffusion of guest molecules into the polymer thin films.

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We propose a blind method to detect interference in GNSS signals whereby the algorithms do not require knowledge of the interference or channel noise features. A sample covariance matrix is constructed from the received signal and its eigenvalues are computed. The generalized likelihood ratio test (GLRT) and the condition number test (CNT) are developed and compared in the detection of sinusoidal and chirp jamming signals. A computationally-efficient decision threshold was proposed for the CNT.

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Conventional film based X-ray imaging systems are being replaced by their digital equivalents. Different approaches are being followed by considering direct or indirect conversion, with the later technique dominating. The typical, indirect conversion, X-ray panel detector uses a phosphor for X-ray conversion coupled to a large area array of amorphous silicon based optical sensors and a couple of switching thin film transistors (TFT). The pixel information can then be readout by switching the correspondent line and column transistors, routing the signal to an external amplifier. In this work we follow an alternative approach, where the electrical switching performed by the TFT is replaced by optical scanning using a low power laser beam and a sensing/switching PINPIN structure, thus resulting in a simpler device. The optically active device is a PINPIN array, sharing both front and back electrical contacts, deposited over a glass substrate. During X-ray exposure, each sensing side photodiode collects photons generated by the scintillator screen (560 nm), charging its internal capacitance. Subsequently a laser beam (445 nm) scans the switching diodes (back side) retrieving the stored charge in a sequential way, reconstructing the image. In this paper we present recent work on the optoelectronic characterization of the PINPIN structure to be incorporated in the X-ray image sensor. The results from the optoelectronic characterization of the device and the dependence on scanning beam parameters are presented and discussed. Preliminary results of line scans are also presented. (C) 2014 Elsevier B.V. All rights reserved.

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In this paper, a damage-detection approach using the Mahalanobis distance with structural forced dynamic response data, in the form of transmissibility, is proposed. Transmissibility, as a damage-sensitive feature, varies in accordance with the damage level. Besides, Mahalanobis distance can distinguish the damaged structural state condition from the undamaged one by condensing the baseline data. For comparison reasons, the Mahalanobis distance results using transmissibility are compared with those using frequency response functions. The experiment results reveal quite a significant capacity for damage detection, and the comparison between the use of transmissibility and frequency response functions shows that, in both cases, the different damage scenarios could be well detected. Copyright (c) 2015 John Wiley & Sons, Ltd.

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Beam-like structures are the most common components in real engineering, while single side damage is often encountered. In this study, a numerical analysis of single side damage in a free-free beam is analysed with three different finite element models; namely solid, shell and beam models for demonstrating their performance in simulating real structures. Similar to experiment, damage is introduced into one side of the beam, and natural frequencies are extracted from the simulations and compared with experimental and analytical results. Mode shapes are also analysed with modal assurance criterion. The results from simulations reveal a good performance of the three models in extracting natural frequencies, and solid model performs better than shell while shell model performs better than beam model under intact state. For damaged states, the natural frequencies captured from solid model show more sensitivity to damage severity than shell model and shell model performs similar to the beam model in distinguishing damage. The main contribution of this paper is to perform a comparison between three finite element models and experimental data as well as analytical solutions. The finite element results show a relatively well performance.

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Endmember extraction (EE) is a fundamental and crucial task in hyperspectral unmixing. Among other methods vertex component analysis ( VCA) has become a very popular and useful tool to unmix hyperspectral data. VCA is a geometrical based method that extracts endmember signatures from large hyperspectral datasets without the use of any a priori knowledge about the constituent spectra. Many Hyperspectral imagery applications require a response in real time or near-real time. Thus, to met this requirement this paper proposes a parallel implementation of VCA developed for graphics processing units. The impact on the complexity and on the accuracy of the proposed parallel implementation of VCA is examined using both simulated and real hyperspectral datasets.

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This paper introduces a new method to blindly unmix hyperspectral data, termed dependent component analysis (DECA). This method decomposes a hyperspectral images into a collection of reflectance (or radiance) spectra of the materials present in the scene (endmember signatures) and the corresponding abundance fractions at each pixel. DECA assumes that each pixel is a linear mixture of the endmembers signatures weighted by the correspondent abundance fractions. These abudances are modeled as mixtures of Dirichlet densities, thus enforcing the constraints on abundance fractions imposed by the acquisition process, namely non-negativity and constant sum. The mixing matrix is inferred by a generalized expectation-maximization (GEM) type algorithm. This method overcomes the limitations of unmixing methods based on Independent Component Analysis (ICA) and on geometrical based approaches. The effectiveness of the proposed method is illustrated using simulated data based on U.S.G.S. laboratory spectra and real hyperspectral data collected by the AVIRIS sensor over Cuprite, Nevada.