149 resultados para quantum cascade laser
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The output harmonic quality of N series connected full-bridge dc-ac inverters is investigated. The inverters are pulse width modulated using a common reference signal but randomly phased carrier signals. Through analysis and simulation, probability distributions for inverter output harmonics and vector representations of N carrier phases are combined and assessed. It is concluded that a low total harmonic distortion is most likely to occur and will decrease further as N increases.
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YBCO thin films were fabricated by laser deposition, in situ on MgO substrates, using both O2 and N2O as process gas. Films with Tc above 90 K and jc of 106 A/cm2 at 77 K were grown in oxygen at a substrate temperature of 765 °C. Using N2O, the optimum substrate temperature was 745 °C, giving a Tc of 87 K. At lower temperatures, the films made in N2O had higher Tc (79 K) than the films made in oxygen (66 K). SEM and STM investigations of the film surfaces showed the films to consist of a comparatively smooth background surface and a distribution of larger particles. Both the particle size and the distribution density depended on the substrate temperature.
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PURPOSE To investigate the utility of using non-contact laser-scanning confocal microscopy (NC-LSCM), compared with the more conventional contact laser-scanning confocal microscopy (C-LSCM), for examining corneal substructures in vivo. METHODS An attempt was made to capture representative images from the tear film and all layers of the cornea of a healthy, 35 year old female, using both NC-LSCM and C-LSCM, on separate days. RESULTS Using NC-LSCM, good quality images were obtained of the tear film, stroma, and a section of endothelium, but the corneal depth of the images of these various substructures could not be ascertained. Using C-LSCM, good quality, full-field images were obtained of the epithelium, subbasal nerve plexus, stroma, and endothelium, and the corneal depth of each of the captured images could be ascertained. CONCLUSIONS NC-LSCM may find general use for clinical examination of the tear film, stroma and endothelium, with the caveat that the depth of stromal images cannot be determined when using this technique. This technique also facilitates image capture of oblique sections of multiple corneal layers. The inability to clearly and consistently image thin corneal substructures - such as the tear film, subbasal nerve plexus and endothelium - is a key limitation of NC-LSCM.
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This work considers the problem of building high-fidelity 3D representations of the environment from sensor data acquired by mobile robots. Multi-sensor data fusion allows for more complete and accurate representations, and for more reliable perception, especially when different sensing modalities are used. In this paper, we propose a thorough experimental analysis of the performance of 3D surface reconstruction from laser and mm-wave radar data using Gaussian Process Implicit Surfaces (GPIS), in a realistic field robotics scenario. We first analyse the performance of GPIS using raw laser data alone and raw radar data alone, respectively, with different choices of covariance matrices and different resolutions of the input data. We then evaluate and compare the performance of two different GPIS fusion approaches. The first, state-of-the-art approach directly fuses raw data from laser and radar. The alternative approach proposed in this paper first computes an initial estimate of the surface from each single source of data, and then fuses these two estimates. We show that this method outperforms the state of the art, especially in situations where the sensors react differently to the targets they perceive.
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Field robots often rely on laser range finders (LRFs) to detect obstacles and navigate autonomously. Despite recent progress in sensing technology and perception algorithms, adverse environmental conditions, such as the presence of smoke, remain a challenging issue for these robots. In this paper, we investigate the possibility to improve laser-based perception applications by anticipating situations when laser data are affected by smoke, using supervised learning and state-of-the-art visual image quality analysis. We propose to train a k-nearest-neighbour (kNN) classifier to recognise situations where a laser scan is likely to be affected by smoke, based on visual data quality features. This method is evaluated experimentally using a mobile robot equipped with LRFs and a visual camera. The strengths and limitations of the technique are identified and discussed, and we show that the method is beneficial if conservative decisions are the most appropriate.
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This paper presents an approach to promote the integrity of perception systems for outdoor unmanned ground vehicles (UGV) operating in challenging environmental conditions (presence of dust or smoke). The proposed technique automatically evaluates the consistency of the data provided by two sensing modalities: a 2D laser range finder and a millimetre-wave radar, allowing for perceptual failure mitigation. Experimental results, obtained with a UGV operating in rural environments, and an error analysis validate the approach.
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Camera-laser calibration is necessary for many robotics and computer vision applications. However, existing calibration toolboxes still require laborious effort from the operator in order to achieve reliable and accurate results. This paper proposes algorithms that augment two existing trustful calibration methods with an automatic extraction of the calibration object from the sensor data. The result is a complete procedure that allows for automatic camera-laser calibration. The first stage of the procedure is automatic camera calibration which is useful in its own right for many applications. The chessboard extraction algorithm it provides is shown to outperform openly available techniques. The second stage completes the procedure by providing automatic camera-laser calibration. The procedure has been verified by extensive experimental tests with the proposed algorithms providing a major reduction in time required from an operator in comparison to manual methods.
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This work aims to promote integrity in autonomous perceptual systems, with a focus on outdoor unmanned ground vehicles equipped with a camera and a 2D laser range finder. A method to check for inconsistencies between the data provided by these two heterogeneous sensors is proposed and discussed. First, uncertainties in the estimated transformation between the laser and camera frames are evaluated and propagated up to the projection of the laser points onto the image. Then, for each pair of laser scan-camera image acquired, the information at corners of the laser scan is compared with the content of the image, resulting in a likelihood of correspondence. The result of this process is then used to validate segments of the laser scan that are found to be consistent with the image, while inconsistent segments are rejected. Experimental results illustrate how this technique can improve the reliability of perception in challenging environmental conditions, such as in the presence of airborne dust.
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The ultraviolet photodissociation of gas-phase N-methylpyridinium ions is studied at room temperature using laser photodissociation mass spectrometry and structurally diagnostic ion-molecule reaction kinetics. The C5H5N-CH3+ (m/z 94), C5H5N-CD3+ (m/z 97), and C5D5N-CH3+(m/z 99) isotopologues are investigated, and it is shown that the N-methylpyridinium ion photodissociates by the loss of methane in the 36 000 - 43 000 cm(-1) (280 - 230 nm) region. The dissociation likely occurs on the ground state surface following internal conversion from the SI state. For each isotopologue, by monitoring the photofragmentation yield as a function of photon wavenumber, a broad vibronically featured band is recorded with origin (0-0) transitions assigned at 38 130, 38 140 and 38 320 cm(-1) for C5H5N-CH3+ C5H5N-CD3+ and C5D5N-CH3+, respectively. With the aid of quantum chemical calculations (CASSCF(6,6)/aug-cc-pVDZ), most of the observed vibronic detail is assigned to two in-plane ring deformation modes. Finally, using ion-molecule reactions, the methane coproduct at m/z 78 is confirmed as a 2-pyridinylium ion.
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In this paper we modeled a quantum dot at near proximity to a gap plasmon waveguide to study the quantum dot-plasmon interactions. Assuming that the waveguide is single mode, this paper is concerned about the dependence of spontaneous emission rate of the quantum dot on waveguide dimensions such as width and height. We compare coupling efficiency of a gap waveguide with symmetric configuration and asymmetric configuration illustrating that symmetric waveguide has a better coupling efficiency to the quantum dot. We also demonstrate that optimally placed quantum dot near a symmetric waveguide with 50 nm x 50 nm cross section can capture 80% of the spontaneous emission into a guided plasmon mode.
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We propose to use a simple and effective way to achieve secure quantum direct secret sharing. The proposed scheme uses the properties of fountain codes to allow a realization of the physical conditions necessary for the implementation of no-cloning principle for eavesdropping-check and authentication. In our scheme, to achieve a variety of security purposes, nonorthogonal state particles are inserted in the transmitted sequence carrying the secret shares to disorder it. However, the positions of the inserted nonorthogonal state particles are not announced directly, but are obtained by sending degrees and positions of a sequence that are pre-shared between Alice and each Bob. Moreover, they can confirm that whether there exists an eavesdropper without exchanging classical messages. Most importantly, without knowing the positions of the inserted nonorthogonal state particles and the sequence constituted by the first particles from every EPR pair, the proposed scheme is shown to be secure.
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A known limitation of the Probability Ranking Principle (PRP) is that it does not cater for dependence between documents. Recently, the Quantum Probability Ranking Principle (QPRP) has been proposed, which implicitly captures dependencies between documents through “quantum interference”. This paper explores whether this new ranking principle leads to improved performance for subtopic retrieval, where novelty and diversity is required. In a thorough empirical investigation, models based on the PRP, as well as other recently proposed ranking strategies for subtopic retrieval (i.e. Maximal Marginal Relevance (MMR) and Portfolio Theory(PT)), are compared against the QPRP. On the given task, it is shown that the QPRP outperforms these other ranking strategies. And unlike MMR and PT, one of the main advantages of the QPRP is that no parameter estimation/tuning is required; making the QPRP both simple and effective. This research demonstrates that the application of quantum theory to problems within information retrieval can lead to significant improvements.
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In this paper we introduce a formalization of Logical Imaging applied to IR in terms of Quantum Theory through the use of an analogy between states of a quantum system and terms in text documents. Our formalization relies upon the Schrodinger Picture, creating an analogy between the dynamics of a physical system and the kinematics of probabilities generated by Logical Imaging. By using Quantum Theory, it is possible to model more precisely contextual information in a seamless and principled fashion within the Logical Imaging process. While further work is needed to empirically validate this, the foundations for doing so are provided.
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Social tagging systems are shown to evidence a well known cognitive heuristic, the guppy effect, which arises from the combination of different concepts. We present some empirical evidence of this effect, drawn from a popular social tagging Web service. The guppy effect is then described using a quantum inspired formalism that has been already successfully applied to model conjunction fallacy and probability judgement errors. Key to the formalism is the concept of interference, which is able to capture and quantify the strength of the guppy effect.