Knowing the quantity and the quality of products and tailings generated by a beneficiation plant, even before ore processing, can make the mining operations more sustainable, more profitable, and ...
Robert Stammer, CFA, is the former director of investor engagement at CFA Institute and writes on thought leadership in the investment management industry. Charlene Rhinehart is a CPA , CFE, chair of ...
Abstract: In this paper, we analyze the impact of compression with complex random matrices on Fisher information and the Cramér-Rao Bound (CRB) for estimating unknown parameters in the mean value ...
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The Python Toolkit for Uncertainty Quantification (PyTUQ) is a Python-only collection of libraries and tools designed for quantifying uncertainty in computational models. PyTUQ offers a range of UQ ...
Vocabulary acquisition is crucial in second language (L2) learning and can be affected by multi-variables. The fact that all these variables have typically been investigated separately (or, at best, ...
Abstract: Polynomial chaos (PC) has been proven to be an efficient method for uncertainty quantification, but its applicability is limited by two strong assumptions: the mutual independence of random ...
Divisive normalization is a ubiquitous computation commonly thought to be an implementation of the efficient coding principle. Despite empirical evidence that it reduces statistical redundancy present ...
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