42 resultados para High-speed-image technology
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We present fast (72 ms) spectroscopy of AM Her obtained at an intermediate brightness state just before a rise to high state. Interesting features in the line behaviour of AM Her are noted and the variability spectrum is presented and compared to that of SS Cyg.
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A ferroelectric liquid crystal spatial light modulator is used to generate up to 24 independently controllable traps in a holographic optical tweezers system using time-multiplexed Fresnel zone plates. For use in biological applications, helical zone plates are used to generate Laguerre-Gaussian laser modes. The high speed switching of the ferroelectric device together with recent advances in computer technology enable fast, smooth movement of traps that can be independently controlled in real time. This is demonstrated by the trapping and manipulation of yeast cells and fungal spores. (c) 2006 Optical Society of America.
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We present observations of a poleward propagating substorm-disturbed region which was observed by the European Incoherent SCATter (EISCAT) radar and the Svalbard International Monitor for Auroral Geomagnetic Effects (IMAGE) magnetometers in the postmidnight sector. The expansion of the disturbance was launched by a substorm intensification which started similar to 25 min after the initial onset, and similar to 10 min before the disturbance arrived over Svalbard. In association with the magnetic disturbance, a poleward expanding enduring enhancement in the F region electron temperature was observed, indicative of soft electron precipitation, with a narrow band of enhanced ion temperature straddling its poleward edge, indicative of fast ion flows and ion-neutral collisional heating. This electron temperature boundary was coincident with the poleward propagating electrojet current system detected by the high-latitude IMAGE magnetometer stations and is taken to be a proxy for the observation of a substorm auroral bulge. The electron temperature boundary is inferred to have a width comparable or less than one radar range gate (similar to 60 km transverse to the magnetic field), while the region of high ion temperature was found to be approximately three gates wide, extending approximately two gates (similar to 120 km) poleward of the electron temperature boundary, and approximately one gate (similar to 60 km) equatorward. The two-beam radar line-of-sight velocity data are found to be consistent with the existence of a layer of high-speed flow in the boundary, peaking at values similar to1.5-3 km s(-1), roughly consistent with the ion temperature data. The flow is directed either east or west along the boundary depending on the direction of the flow in the poleward region. We infer that the flow is deflected along and around the boundary of the substorm-disturbed region due to the high conductivity of the latter. Variations in the flow poleward of the boundary produced no discernible magnetic effects on the ground, confirming the low conductivity of the preboundary ionosphere.
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We present a first overview of flows in the high latitude ionosphere observed at 15 s resolution using the U.K.-Polar EISCAT experiment. Data are described from experiments conducted on two days, 27 October 1984 and 29 August 1985, which together span the local times between about 0200 and 2130MLT and cover five different regions of ionospheric flow. With increasing local time, these are: the dawn auroral zone flow cell, the dayside region of low background flows equatorward of the flow cells, the dusk auroral zone flow cell, the boundary region between the dusk auroral zone and the polar cap, and the evening polar cap. Flows in both the equatorward and poleward portions of the auroral zone cells appear to be relatively smooth, while in the central region of high speed flow considerable variations are generally present. These have the form of irregular fluctuations on a wide range of time scales in the early morning dawn cell, and impulsive wave-like variations with periods of a few minutes in the afternoon dusk cell. In the dayside region between the flow cells, the ionosphere is often essentially stagnant for long intervals, but low amplitude ULF waves with a period of about 5 min can also occur and persist for many cycles. These conditions are punctuated at one to two hour intervals by sudden ‘flow burst’ events with impulsively generated damped wave trains. Initial burst flows are generally directed poleward and can peak at line-of-sight speeds in excess of 1 km s^{−1} after perhaps 45 s. Flows in the polar cap are reasonably smooth on time scales of a few minutes and show no evidence for the presence of ULF waves. Under most, but not all, of the above conditions, the beam-swinging algorithm used to determine background vector flows should produce meaningful results. Comparison of these flow data with simultaneous plasma and magnetic field measurements in the solar wind, made by the AMPTE IRM and UKS spacecraft, emphasizes the strong control exerted on high latitude flows by the north-south component of the IMF.
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In this paper, we introduce a novel high-level visual content descriptor which is devised for performing semantic-based image classification and retrieval. The work can be treated as an attempt to bridge the so called “semantic gap”. The proposed image feature vector model is fundamentally underpinned by the image labelling framework, called Collaterally Confirmed Labelling (CCL), which incorporates the collateral knowledge extracted from the collateral texts of the images with the state-of-the-art low-level image processing and visual feature extraction techniques for automatically assigning linguistic keywords to image regions. Two different high-level image feature vector models are developed based on the CCL labelling of results for the purposes of image data clustering and retrieval respectively. A subset of the Corel image collection has been used for evaluating our proposed method. The experimental results to-date already indicates that our proposed semantic-based visual content descriptors outperform both traditional visual and textual image feature models.
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Matrix-assisted laser desorption/ionization (MALDI) is a key technique in mass spectrometry (MS)-based proteomics. MALDI MS is extremely sensitive, easy-to-apply, and relatively tolerant to contaminants. Its high-speed data acquisition and large-scale, off-line sample preparation has made it once again the focus for high-throughput proteomic analyses. These and other unique properties of MALDI offer new possibilities in applications such as rapid molecular profiling and imaging by MS. Proteomics and its employment in Systems Biology and other areas that require sensitive and high-throughput bioanalytical techniques greatly depend on these methodologies. This chapter provides a basic introduction to the MALDI methodology and its general application in proteomic research. It describes the basic MALDI sample preparation steps and two easy-to-follow examples for protein identification including extensive notes on these topics with practical tips that are often not available in the Subheadings 2 and 3 of research articles.
Determination of digesta flow entering the omasal canal of dairy cows using different marker systems
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Four studies were conducted to compare the effect of four indigestible markers (LiCoEDTA, Yb-acetate, Cr-mordanted straw and indigestible neutral-detergent fibre (INDF)) and three marker systems on the flow of digesta entering the omasal canal of lactating dairy cows. Samples of digesta aspirated from the omasal canal were pooled and separated using filtration and high-speed centrifugation into three fractions defined as the liquid phase, small particulate and large particulate matter. Co was primarily associated with the liquid phase, Yb was concentrated in small particulate matter, whilst Cr and INDF were associated with large particles. Digesta flow was calculated based on single markers or using the reconstitution system based on combinations of two (Co + Yb, Co + Cr and Co + INDF) or three markers (Co + Yb + Cr and Co + Yb + INDF). Use of single markers resulted in large differences between estimates of organic matter (OM) flow entering the omasal canal suggesting that samples were not representative of true digesta. Digesta appeared to consist of at least three phases that tended to separate during sampling. OM was concentrated in particulate matter, whilst the liquid phase consisted mainly of volatile fatty acids and inorganic matter. Yb was intimately associated with nitrogenous compounds, whereas Cr and INDF were concentrated in fibrous material. Current data indicated that marker systems based on Yb in combination with Cr or INDF are required for the accurate determination of OM, N and neutral-detergent fibre flow. In cases where the flow of water-soluble nutrients entering the omasal canal is also required, the marker system should also include Co.
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A Fractal Quantizer is proposed that replaces the expensive division operation for the computation of scalar quantization by more modest and available multiplication, addition and shift operations. Although the proposed method is iterative in nature, simulations prove a virtually undetectable distortion to the naked eve for JPEG compressed images using a single iteration. The method requires a change to the usual tables used in JPEG algorithins but of similar size. For practical purposes, performing quantization is reduced to a multiplication plus addition operation easily programmed in either low-end embedded processors and suitable for efficient and very high speed implementation in ASIC or FPGA hardware. FPGA hardware implementation shows up to x15 area-time savingscompared to standars solutions for devices with dedicated multipliers. The method can be also immediately extended to perform adaptive quantization(1).
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A novel framework for multimodal semantic-associative collateral image labelling, aiming at associating image regions with textual keywords, is described. Both the primary image and collateral textual modalities are exploited in a cooperative and complementary fashion. The collateral content and context based knowledge is used to bias the mapping from the low-level region-based visual primitives to the high-level visual concepts defined in a visual vocabulary. We introduce the notion of collateral context, which is represented as a co-occurrence matrix, of the visual keywords, A collaborative mapping scheme is devised using statistical methods like Gaussian distribution or Euclidean distance together with collateral content and context-driven inference mechanism. Finally, we use Self Organising Maps to examine the classification and retrieval effectiveness of the proposed high-level image feature vector model which is constructed based on the image labelling results.
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An approach to the automatic generation of efficient Field Programmable Gate Arrays (FPGAs) circuits for the Regular Expression-based (RegEx) Pattern Matching problems is presented. Using a novel design strategy, as proposed, circuits that are highly area-and-time-efficient can be automatically generated for arbitrary sets of regular expressions. This makes the technique suitable for applications that must handle very large sets of patterns at high speed, such as in the network security and intrusion detection application domains. We have combined several existing techniques to optimise our solution for such domains and proposed the way the whole process of dynamic generation of FPGAs for RegEX pattern matching could be automated efficiently.
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A novel framework referred to as collaterally confirmed labelling (CCL) is proposed, aiming at localising the visual semantics to regions of interest in images with textual keywords. Both the primary image and collateral textual modalities are exploited in a mutually co-referencing and complementary fashion. The collateral content and context-based knowledge is used to bias the mapping from the low-level region-based visual primitives to the high-level visual concepts defined in a visual vocabulary. We introduce the notion of collateral context, which is represented as a co-occurrence matrix of the visual keywords. A collaborative mapping scheme is devised using statistical methods like Gaussian distribution or Euclidean distance together with collateral content and context-driven inference mechanism. We introduce a novel high-level visual content descriptor that is devised for performing semantic-based image classification and retrieval. The proposed image feature vector model is fundamentally underpinned by the CCL framework. Two different high-level image feature vector models are developed based on the CCL labelling of results for the purposes of image data clustering and retrieval, respectively. A subset of the Corel image collection has been used for evaluating our proposed method. The experimental results to-date already indicate that the proposed semantic-based visual content descriptors outperform both traditional visual and textual image feature models. (C) 2007 Elsevier B.V. All rights reserved.
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This paper describes the design, implementation and testing of a high speed controlled stereo “head/eye” platform which facilitates the rapid redirection of gaze in response to visual input. It details the mechanical device, which is based around geared DC motors, and describes hardware aspects of the controller and vision system, which are implemented on a reconfigurable network of general purpose parallel processors. The servo-controller is described in detail and higher level gaze and vision constructs outlined. The paper gives performance figures gained both from mechanical tests on the platform alone, and from closed loop tests on the entire system using visual feedback from a feature detector.
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The objective of a Visual Telepresence System is to provide the operator with a high fidelity image from a remote stereo camera pair linked to a pan/tilt device such that the operator may reorient the camera position by use of head movement. Systems such as these which utilise virtual reality style helmet mounted displays have a number of limitations. The geometry of the camera positions and of the displays is generally fixed and is most suitable only for viewing elements of a scene at a particular distance. To address such limitations, a prototype system has been developed where the geometry of the displays and cameras is dynamically controlled by the eye movement of the operator. This paper explores why it is necessary to actively adjust the display system as well as the cameras and justifies the use of mechanical adjustment of the displays as an alternative to adjustment by electronic or image processing methods. The electronic and mechanical design is described including optical arrangements and control algorithms. The performance and accuracy of the system is assessed with respect to eye movement.
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It took the solar polar passage of Ulysses in the early 1990s to establish the global structure of the solar wind speed during solar minimum. However, it remains unclear if the solar wind is composed of two distinct populations of solar wind from different sources (e.g., closed loops which open up to produce the slow solar wind) or if the fast and slow solar wind rely on the superradial expansion of the magnetic field to account for the observed solar wind speed variation. We investigate the solar wind in the inner corona using the Wang-Sheeley-Arge (WSA) coronal model incorporating a new empirical magnetic topology–velocity relationship calibrated for use at 0.1 AU. In this study the empirical solar wind speed relationship was determined by using Helios perihelion observations, along with results from Riley et al. (2003) and Schwadron et al. (2005) as constraints. The new relationship was tested by using it to drive the ENLIL 3-D MHD solar wind model and obtain solar wind parameters at Earth (1.0 AU) and Ulysses (1.4 AU). The improvements in speed, its variability, and the occurrence of high-speed enhancements provide confidence that the new velocity relationship better determines the solar wind speed in the outer corona (0.1 AU). An analysis of this improved velocity field within the WSA model suggests the existence of two distinct mechanisms of the solar wind generation, one for fast and one for slow solar wind, implying that a combination of present theories may be necessary to explain solar wind observations.
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This paper describes the novel use of cluster analysis in the field of industrial process control. The severe multivariable process problems encountered in manufacturing have often led to machine shutdowns, where the need for corrective actions arises in order to resume operation. Production faults which are caused by processes running in less efficient regions may be prevented or diagnosed using a reasoning based on cluster analysis. Indeed the intemal complexity of a production machinery may be depicted in clusters of multidimensional data points which characterise the manufacturing process. The application of a Mean-Tracking cluster algorithm (developed in Reading) to field data acquired from a high-speed machinery will be discussed. The objective of such an application is to illustrate how machine behaviour can be studied, in particular how regions of erroneous and stable running behaviour can be identified.