Results 11 to 20 of about 27,651,836 (340)
Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, 1998 A new method for analysing nonlinear and non-stationary data has been developed. The key part of the method is the ‘empirical mode decomposition’ method with which any complicated data set can be decomposed into a finite and often small number of ...
Norden E. Huang +8 more
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Nine questions on energy decomposition analysis [PDF]
Journal of Computational Chemistry, 2019 The paper collects the answers of the authors to the following questions: Is the lack of precision in the definition of many chemical concepts one of the reasons for the coexistence of many partition schemes? Does the adoption of a given partition scheme
J. Andrés +29 more
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Gait Analysis by Causal Decomposition [PDF]
IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2021 Recent studies have investigated bilateral gaits based on the causality analysis of kinetic (or kinematic) signals recorded using both feet. However, these approaches have not considered the influence of their simultaneous causation, which might lead to inaccurate causality inference.
Xiaohang Peng +12 more
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WIREs Computational Molecular Science, 2018 The energy decomposition analysis (EDA) is a powerful method for a quantitative interpretation of chemical bonds in terms of three major components. The instantaneous interaction energy ΔEintbetween two fragments A and B in a molecule A–B is partitioned in three terms, namely (1) the quasiclassical electrostatic interaction ΔEelstatbetween the ...
Lili Zhao +3 more
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Shape Decomposition using Modal Analysis [PDF]
Computer Graphics Forum, 2009 AbstractWe introduce a novel algorithm that decomposes a deformable shape into meaningful parts requiring only a single input pose. Using modal analysis, we are able to identify parts of the shape that tend to move rigidly. We define a deformation energy on the shape, enabling modal analysis to find the typical deformations of the shape. We then find a
Huang, Qixing +3 more
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Smoothed analysis of tensor decompositions [PDF]
Proceedings of the forty-sixth annual ACM symposium on Theory of computing, 2014 Low rank tensor decompositions are a powerful tool for learning generative models, and uniqueness results give them a significant advantage over matrix decomposition methods. However, tensors pose significant algorithmic challenges and tensors analogs of much of the matrix algebra toolkit are unlikely to exist because of hardness results.
Bhaskara, Aditya +3 more
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International Journal of Public Health, 2023 Objectives: This study examines the inequality between people with and without disabilities regarding unmet healthcare needs and preventable hospitalization.Methods: We used the Korea Health Panel of 2016–2018; the final analytical observations were 43 ...
Sujin Kim, Boyoung Jeon
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Competitive Analysis via Benchmark Decomposition [PDF]
Proceedings of the Sixteenth ACM Conference on Economics and Computation, 2015 We propose a uniform approach for the design and analysis of prior-free competitive auctions and online auctions. Our philosophy is to view the benchmark function as a variable parameter of the model and study a broad class of functions instead of a individual target benchmark.
Chen, Ning, Gravin, Nick, Lu, Pinyan
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Revue des Énergies Renouvelables, 2023 The reduction of energy consumption is an important key not only to improving the performance of the Algerian economy but also to contributing to the effective mitigation of greenhouse gas emissions.
Sarra Robei +2 more
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Foreign shareholding: a decomposition analysis [PDF]
Applied Financial Economics, 2011 Stulz (2005) has emphasized that for home bias to decline, insiders have to reduce ownership so as to make purchase of shares by foreigners possible. We offer a decomposition in the ownership of shares by foreigners into three parts: the change in insider shareholding, the change in market capitalization and the change in the fraction of outside ...
Shah, Ajay, Patnaik, Ila
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