DATA ASSIMILATION AS A LEARNING TOOL TO INFER ORDINARY DIFFERENTIAL EQUATION REPRESENTATIONS OF DYNAMICAL MODELS

Data assimilation as a learning tool to infer ordinary differential equation representations of dynamical models

Recent progress in machine learning has shown how to forecast and, to some extent, learn the dynamics of a model from its output, resorting in particular to neural networks and deep learning techniques.We will show how the same goal can be directly achieved using data assimilation techniques without leveraging on machine learning software libraries

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Association of Glycemic Index Using HbA1c and Sensorineural Hearing Loss in Diabetes Mellitus Type 2 Patients: A Systematic Review and Meta-Analysis

ABSTRACT Objective: To systematically review the available evidence on the association of HBA1c levels and development of sensorineural hearing loss and to quantitatively analyze the available data on HBA1c levels in patients with type 2 diabetes mellitus and sensorineural hearing loss to determine an HbA1c level that may be associated with the ris

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Student satisfaction with the heutagogical approach in education

The heutagogical approach places a strong emphasis on learner autonomy and the enhancement of their potential for a self-directed learning, technology utilization also can make it easier to integrate heutagogy in the classroom, improving learning results and increasing learner engagement.Thus, the student satisfaction is an essential element of hig

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Computationally efficient direction-of-arrival estimation of non-circular signal based on subspace rotation technique

In order to solve the problem Dining Table that the high computational burden of the multiple signal classification algorithm of non-circular signal (NC-MUSIC) in direction-of-arrival (DOA) estimation,a novel computationally efficient DOA estimation algorithm based on subspace rotation technique was proposed.Firstly,the partitioning of noise subspa

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