Semiempirical hyperspherical model for4HeN clusters

Semiempirical Model for Adsorption of Binary Mixtures

As it can clearly be observed in Figure 1a and 2a in the paper, the total coverage of the biggest species (in this case k = 6) has a maximum and later decreases to a limit value. This behavior is known as adsorption preference reversal (APR) and has also been observed in theoretical calculations and Monte Carlo simulations [1, 2]. The APR phenomenon usually is attributed to presence of repulsiv...

Semiempirical model for nanoscale device simulations

Semiempirical model of positron scattering and annihilation

A two-parameter semiempirical theory of positron scattering and annihilation is developed and used to investigate the behavior of positrons interacting with the rare gases and metal vapors. The two-parameter theory is able to do a reasonable job of reproducing existing cross section and annihilation data for the rare gases. A model-potential calculation that correctly predicts the behavior of t...

A hyperspherical transformation forecasting model for compositional data

Although Aitchison’s [Aitchison, J., 1986. The Statistical Analysis of Compositional Data, Chapman and Hall, London] method of logratio transformation of compositional data is widely used in various domains, it is limited by the assumption of a strict non-negativity of the components and the requirement of special treatments in practice of the zero components. We propose a dimension-reduction a...

Mixture of Watson Distributions: A Generative Model for Hyperspherical Embeddings

Machine learning applications often involve data that can be analyzed as unit vectors on a d-dimensional hypersphere, or equivalently are directional in nature. Spectral clustering techniques generate embeddings that constitute an example of directional data and can result in different shapes on a hypersphere (depending on the original structure). Other examples of directional data include text...