Abstract: Mixture models are in high demand for machine-learning analysis due to their computational tractability, and because they serve as a good approximation for continuous densities. Predominantly, entropy applications have been developed in the context of a mixture of normal densities. In this paper, we consider a novel class of skew-normal mixture models, whose components capture skewnes...

In this paper, a newsboy model is developed under uniformly distributed lead-time and demand that is an appropriate assumption in obtaining optimal relief inventory of humanitarian disasters. It is noteworthy that limited historical data are in hand on relief operations. Hence, analytical and approximate solutions for optimal relief order quan­tity were derived. The effect of lead-time uncertai...

Information leaks are a significant problem in modern software systems. In recent years, information theoretic concepts, such as Shannon entropy, have been applied to quantifying programs. One approach is use symbolic execution together with model counting constraints solvers order quantify leakage. There at least two reasons for unsoundness leakage using this approach: 1) Symbolic may not be a...

Shell-model calculations play a key role in elucidating various properties of nuclei. In general, those studies require huge number to be repeated for parameter calibration and quantifying uncertainties. To reduce the computational burden, we propose new workflow shell-model using method called eigenvector continuation (EC). It enables us efficiently approximate eigenpairs under given Hamiltoni...