1,192 research outputs found

    Contemplative Prayer (The Visions of Thomas Kelly and Thomas Merton)

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    Thrips Species Infesting Tomatoes and Other Host Plants of These Insects in Northern Utah

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    The purpose of this study has been to determine which species of thrips infest tomato plants and fruits in northern Utah, and to find out which other plants occurring in this area also serve as hosts for tomato-infesting thrips. Because of the importance of tomato-infesting thrips to the canning industry, it was decided that more complete knowledge of the species of thrips which are found on tomatoes should be obtained. Because most thrips generally have been difficult to control, it was believed that a general knowledge of the plants on which these thrips occur would enable tomato growers to eliminate many such plants from tomato fields and lands adjacent to them, and that such cultivation would tend to decrease thrips populations on tomato fruits and in tomato fields

    Assessing the Viability of Complex Electrical Impedance Tomography (EIT) with a Spatially Distributed Sensor Array for Imaging of River Bed Morphology: a Proof of Concept (Study)

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    This report was produced as part of a NERC funded ‘Connect A’ project to establish a new collaborative partnership between the University of Worcester (UW) and Q-par Angus Ltd. The project aim was to assess the potential of using complex Electrical Impedance Tomography (EIT) to image river bed morphology. An assessment of the viability of sensors inserted vertically into the channel margins to provide real-time or near real-time monitoring of bed morphology is reported. Funding has enabled UW to carry out a literature review of the use of EIT and existing methods used for river bed surveys, and outline the requirements of potential end-users. Q-par Angus has led technical developments and assessed the viability of EIT for this purpose. EIT is one of a suite of tomographic imaging techniques and has already been used as an imaging tool for medical analysis, industrial processing and geophysical site survey work. The method uses electrodes placed on the margins or boundary of the entity being imaged, and a current is applied to some and measured on the remaining ones. Tomographic reconstruction uses algorithms to estimate the distribution of conductivity within the object and produce an image of this distribution from impedance measurements. The advantages of the use of EIT lie with the inherent simplicity, low cost and portability of the hardware, the high speed of data acquisition for real-time or near real-time monitoring, robust sensors, and the object being monitored is done so in a non-invasive manner. The need for sophisticated image reconstruction algorithms, and providing images with adequate spatial resolution are key challenges. A literature review of the use of EIT suggests that to date, despite its many other applications, to the best of our knowledge only one study has utilised EIT for river survey work (Sambuelli et al 2002). The Sambuelli (2002) study supported the notion that EIT may provide an innovative way of describing river bed morphology in a cost effective way. However this study used an invasive sensor array, and therefore the potential for using EIT in a non-invasive way in a river environment is still to be tested. A review of existing methods to monitor river bed morphology indicates that a plethora of techniques have been applied by a range of disciplines including fluvial geomorphology, ecology and engineering. However, none provide non-invasive, low costs assessments in real-time or near real-time. Therefore, EIT has the potential to meet the requirements of end users that no existing technique can accomplish. Work led by Q-par Angus Ltd. has assessed the technical requirements of the proposed approach, including probe design and deployment, sensor array parameters, data acquisition, image reconstruction and test procedure. Consequently, the success of this collaboration, literature review, identification of the proposed approach and potential applications of this technique have encouraged the authors to seek further funding to test, develop and market this approach through the development of a new environmental sensor

    Bacterial sporulation: Pole-to-pole protein oscillation

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    AbstractSporulating bacteria need to temporally coordinate DNA replication, chromosome partitioning and sporulation initiation. Recent work has shown that one aspect of this coordination lies with the interdependent subcellular localization of two proteins, Spo0J and Soj, and in the Spo0J-dependent spatial oscillation of Soj

    3D visual speech animation using 2D videos

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    In visual speech animation, lip motion accuracy is of paramount importance for speech intelligibility, especially for the hard of hearing or foreign language learners. We present an approach for visual speech animation that uses tracked lip motion in front-view 2D videos of a real speaker to drive the lip motion of a synthetic 3D head. This makes use of a 3D morphable model (3DMM), built using 3D synthetic head poses, with corresponding landmarks identified in the 2D videos and the 3DMM. We show that using a wider range of synthetic head poses for different phoneme intensities to create a 3DMM, as well as a combination of front and side photographs of the real speakers rather than just front photographs to produce initial neutral 3D synthetic head poses, gives better animation results when compared to ground truth data consisting of front-view 2D videos of real speakers

    A Standardised Benchmark for Assessing the Performance of Fixed Radius Near Neighbours

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    Many agent based models require agents to have an awareness of their local peers. The handling of these fixed radius near neighbours (FRNNs) is often a limiting factor of performance. However without a standardised metric to assess the handling of FRNNs, contributions to the field lack the rigorous appraisal necessary to expose their relative benefits. This paper presents a standardised specification of a multi agent based benchmark model. The benchmark model provides a means for the objective assessment of FRNNs performance, through the comparison of implementations. Results collected from implementations of the benchmark model under three agent based modelling frameworks show the 64-bit floating point performance of each framework to scale linearly with agent population, in contrast the GPU accelerated framework’s 32- bit floating point performance only became linear after maximal device utilisation around 100,000 agent

    The impact of the Lombard effect on audio and visual speech recognition systems

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    When producing speech in noisy backgrounds talkers reflexively adapt their speaking style in ways that increase speech-in-noise intelligibility. This adaptation, known as the Lombard effect, is likely to have an adverse effect on the performance of automatic speech recognition systems that have not been designed to anticipate it. However, previous studies of this impact have used very small amounts of data and recognition systems that lack modern adaptation strategies. This paper aims to rectify this by using a new audio-visual Lombard corpus containing speech from 54 different speakers – significantly larger than any previously available – and modern state-of-the-art speech recognition techniques. The paper is organised as three speech-in-noise recognition studies. The first examines the case in which a system is presented with Lombard speech having been exclusively trained on normal speech. It was found that the Lombard mismatch caused a significant decrease in performance even if the level of the Lombard speech was normalised to match the level of normal speech. However, the size of the mismatch was highly speaker-dependent thus explaining conflicting results presented in previous smaller studies. The second study compares systems trained in matched conditions (i.e., training and testing with the same speaking style). Here the Lombard speech affords a large increase in recognition performance. Part of this is due to the greater energy leading to a reduction in noise masking, but performance improvements persist even after the effect of signal-to-noise level difference is compensated. An analysis across speakers shows that the Lombard speech energy is spectro-temporally distributed in a way that reduces energetic masking, and this reduction in masking is associated with an increase in recognition performance. The final study repeats the first two using a recognition system training on visual speech. In the visual domain, performance differences are not confounded by differences in noise masking. It was found that in matched-conditions Lombard speech supports better recognition performance than normal speech. The benefit was consistently present across all speakers but to a varying degree. Surprisingly, the Lombard benefit was observed to a small degree even when training on mismatched non-Lombard visual speech, i.e., the increased clarity of the Lombard speech outweighed the impact of the mismatch. The paper presents two generally applicable conclusions: i) systems that are designed to operate in noise will benefit from being trained on well-matched Lombard speech data, ii) the results of speech recognition evaluations that employ artificial speech and noise mixing need to be treated with caution: they are overly-optimistic to the extent that they ignore a significant source of mismatch but at the same time overly-pessimistic in that they do not anticipate the potential increased intelligibility of the Lombard speaking style
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