However, NGD faces several challenges associated with gamma-ray generation and attenuation complexities. Unlike GGD, which utilizes 0.662 MeV monoenergetic γ rays from a 137 Cs source, NGD employs ...
This study introduces two-dimensional (2D) Kernel Density Estimation (KDE) plots as a novel tool for visualising Training Intensity Distribution (TID) in biathlon. The goal was to assess how KDE plots ...
Network estimation is essential for understanding the structure and function of biological systems, but current statistical approaches fail to capture intersubject heterogeneity or cross-modality ...
(a) Dense matrices. Variables are often encoded as dense numerical arrays M i,j = M[i,j]. This representation is convenient and well-supported, but also puts a heavy load on the memories of our ...
System identification learns models of dynamical systems from input–output measurements. Estimated models should generalize by predicting system’s output responses to new, previously unseen inputs.
Single-molecule super-resolution microscopy (SMLM) techniques like dSTORM can reveal biological structures down to the nanometer scale. The achievable resolution is not only defined by the ...
Mean shift clustering is a centroid-based algorithm effective for unsupervised learning applications. The algorithm shifts data points towards the mean of surrounding points to form clusters. Mean ...
The allure of a molecular dynamics simulation is that, given a sufficiently accurate force field, it can provide an atomic-level view of many interesting phenomena in biology. However, the result of a ...
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