Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: In industrial hygiene, a worker’s exposure to chemical, physical, and biological agents is increasingly being modeled using deterministic physical models that study exposures near and farther away from a contaminant source. Hover, predicting exposure in the workplace is challenging and simply regressing on a physical model may prove ineffective due to biases and extraneous variability. A further complication is that data from the workplace are usually misaligned. This means that not all timepoints measure concentrations near and far from the source.  recognize these challenges and outline a flexible Bayesian hierarchical framework to synthesize the physical model with the field data.  reckon that the physical model, by itself, is inadequate for enhanced inferential and predictive performance and deploy (multivariate) Gaussian processes to capture uncertainties and associations.  propose rich covariance structures for multiple outcomes using latent stochastic processes. This article has supplementa...
['João V. D. Monteiro', 'Sudipto Banerjee', 'Gurumurthy Ramachandran']
I am writing a research paper on a idea Bayesian Modeling for Physical Processes in Industrial Hygiene Using Misaligned Workplace Data
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