Titlebook: Landing Votes; Representation and L Nancy D. Lapp Book 2004 Palgrave Macmillan, a division of Nature America Inc. 2004 democratization.gove

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Automated Bug Triaging in a Global Software Development Environment: An Industry ExperienceReciprocal Rank (MRR) in 3% compared with our previous work. More significantly, the new method reduces the model’s training time from 5 h to 22 min. These results were validated in a real-world dataset composed of 410,631 bug reports obtained from the projects of a global smartphone manufacturer.

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Connor Morrow Kerns Ph.D.,Philip C. Kendallnics, to predict functional status (dichotomized mRS score) after 3 months. Our results show that a model trained on the vertically integrated hospital and rehabilitation data performs better than a model trained on either of these sets alone. Training using SVFL yields a slightly lower predictive p

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Hai Li,Matthias Kuschel,Martin Sommerfeld that finally lead to the activation of the B cell. Since such receptor complexes have not yet been described, the aim of this work was to identify and biochemically characterize molecules which are associated and/or covalently linked to Ig. Furthermore, we are interested in the question whether IgM

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Synthesis and conclusionsr enough because the human interventions that might succeed with one species can be hopelessly wrong for another. Management strategies only make sense in relation to the characteristics of the targeted species.

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Adil Baykasoglu,Mumin Emre Senolcine imparts insight and clinical experience in order to identify and analyze the possible causes of racial disparities in fertility outcome. Some of the reviewed causes include higher Body Mass Index (BMI), tu978-1-4899-8632-0978-1-4614-7548-4

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An Approach to Handle Heterogeneous Healthcare IoT Data Using Deep Convolutional Neural Network,onverts the ECG signals into numeric form by calculating its features without any human intervention. Similarly, categorical data are converted based on their respective categories. Finally, all the converted data together were added to the CNN classification part and arrhythmia disease is predicted

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