Abstract: This work evaluates the performance of several polynomial interpolation techniques applied to the Shamir Secret Sharing (SSS) scheme, considering seven methods: Lagrange, Newton, Neville, ...

This C++ header library features tools for piecewise linear and cubic interpolation of rectangular grid data in N dimensions. For cubic piecewise interpolation, the library features three types: ...

Kolmogorov flow, a canonical configuration involving sinusoidal body forcing in a periodic domain, has long served as a simplified yet insightful model for studying hydrodynamic stability, non-linear ...

Minterpy is an open-source Python package designed for constructing and manipulating multivariate interpolating polynomials with the goal of addressing the curse of dimensionality from interpolation ...

Rare earth elements (REEs) are powerful proxies used in many (bio-)geochemical studies. Interpretation of REE data relies on normalised REE patterns and anomaly quantification, and requires complete ...

The origins of bilinear interpolation are rooted in the broader field of numerical analysis and approximation theory. While it's challenging to pinpoint a single inventor, bilinear interpolation as a ...

In the previous article, I presented a data extraction tool and the strategy I generally use on the data extraction for interpolation. Besides that, I discussed some linear interpolation methods ...

Nowadays, the deep learning methods are widely applied to analyze and predict the trend of various disaster events and offer the alternatives to make the appropriate decisions. These support the water ...

Abstract: Inspired by image-to-image translation, we applied deep learning (DL) to regularly missing data reconstruction, aimed at translating incomplete data into their corresponding complete data.

Underwater gliders have become widely used in the last decade. This has led to a proliferation of data and the concomitant development of tools to process the data. These tools are focused primarily ...