Discrepancy is a well-known measure for the irregularity of the distribution of a point set. Point sets with small discrepancy are called low discrepancy and are known to efficiently fill the space in a uniform manner. Low-discrepancy points play a central role in many problems in science and engineering, including numerical integration, computer vision, machine perception, computer graphics, machine learning, and simulation.
View Article and Find Full Text PDFAn accurate understanding of uncertainty is needed to properly interpret methane emission estimates from upstream oil and gas sources in a variety of contexts, from component-level measurements to yearly jurisdiction-wide inventories. To characterize measurement uncertainty, we examine controlled release (CR) data from five different technology providers including quantitative gas imaging (QOGI), tunable diode laser-absorption spectroscopy (TDLAS); and airborne near-infrared hyperspectral (NIR HS) imaging. We introduce a novel empirical method to develop probability distributions of measurements given a true emission rate using the CR data.
View Article and Find Full Text PDFBackground: The clinical benefit of systemic anticancer therapies can be unclear despite positive trials, and outcomes may not translate to real-world practice. This study evaluated the benefit of soft tissue sarcoma (STS) treatments using the European Society of Medical Oncology Magnitude of Clinical Benefit Scale (MCBS) v1.1 and measured the robustness of STS trial results using Fragility Index (FI).
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