420 research outputs found

    Creating a Flexible IT Organization

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    In 2004, the nearly billion dollar software company Business Objects undertook a major acquisition. Now, the business is looking to improve operations and position itself as a major player in the business intelligence market. This paper focuses on how Business Objects can create a flexible IT organization that can evolve with changing corporate strategies in today\u27s competitive markets. The analysis section completes a SWOT analysis and reviews business strategy, organizational strategy and IT strategy. The analysis concludes that increased legislated process and broad geographic reach in a truly flexible IT organization are not feasible. However, action can be taken to balance control and flexibility that will make IT an enabler for the business. Recommendations include appointment of a CIO, hybrid organizational structure and establishment of performance metrics. As part of implementation strategy, a gradual change management approach is recommended with a dedicated team to monitor progress and adapt the plan as the environment evolves

    Learning word vector representations based on acoustic counts

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    Barriers to infection of human cells by feline leukemia virus: insights into resistance to zoonosis

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    The human genome displays a rich fossil record of past gamma-retrovirus infections, yet no current epidemic is evident, despite environmental exposure to viruses that infect human cells in vitro. Feline leukemia viruses (FeLVs) rank high on this list, but domestic or workplace exposure has not been associated with detectable serological responses. Non-specific inactivation of gamma-retroviruses by serum factors appears insufficient to explain these observations. To investigate further we explored the susceptibility of primary and established human cell lines to FeLV-B, the most likely zoonotic variant. Fully permissive infection was common in cancer-derived cell lines, but was also a feature of non-transformed keratinocytes and lung fibroblasts. Cells of haematopoietic origin were less generally permissive and formed discrete groups on the basis of high or low intracellular protein expression and virion release. Potent repression was observed in primary human blood mononuclear cells and a subset of leukemia cell lines. However, the early steps of reverse transcription and integration appear to be unimpaired in non-permissive cells. FeLV-B was subject to G->A hypermutation with a predominant APOBEC3G signature in partially permissive cells but was not mutated in permissive cells or in non-permissive cells that block secondary viral spread. Distinct cellular barriers that protect primary human blood cells are likely to be important in protection against zoonotic infection with FeLV

    Quantifying the differences in avian attack rates on reptiles between an infrastructure and a control site

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    Acknowledgements We would like to thank Professor Bob Furness for his comments on an earlier draft of this manuscript, and the staff of Camster Wind Farm for their cooperation. Two anonymous reviewers provided comments that greatly improved the text.Peer reviewedPostprin

    Predicting pairwise preferences between TTS audio stimuli using parallel ratings data and anti-symmetric twin neural networks

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    Automatically predicting the outcome of subjective listening tests is a challenging task. Ratings may vary from person to person even if preferences are consistent across listeners. While previous work has focused on predicting listeners' ratings (mean opinion scores) of individual stimuli, we focus on the simpler task of predicting subjective preference given two speech stimuli for the same text. We propose a model based on anti-symmetric twin neural networks, trained on pairs of waveforms and their corresponding preference scores. We explore both attention and recurrent neural nets to account for the fact that stimuli in a pair are not time aligned. To obtain a large training set we convert listeners' ratings from MUSHRA tests to values that reflect how often one stimulus in the pair was rated higher than the other. Specifically, we evaluate performance on data obtained from twelve MUSHRA evaluations conducted over five years, containing different TTS systems, built from data of different speakers. Our results compare favourably to a state-of-the-art model trained to predict MOS scores

    Parallel and cascaded deep neural networks for text-to-speech synthesis

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