The present study deals with the application of supervised machine learning regression algorithms known as Linear Regression (LR), Support Vector Machine (SVM), and Gaussian process (GPR) to frequency temperature-dependent dielectric parameters polymer/inorganic film composites. experimental data set (ε^' ε^'') Polypyrrole/Kufeki Stone (PPy/KS) has been utilized. ML models were compared based o...

the steger and warming flux vector splitting implicit scheme is used to numerically solve two dimensional reynolds averaged navier–stokes (rans) equations governing the vortex induced vibration of a flexible riser laterally supported by a spring and a damper. the k–ε model is used as turbulence model to simulate the turbulent flow in the wake of the riser. to update the new position of the rise...

∂ν = 0, x ∈ ∂ , where is the Laplace operator, is a smooth bounded domain in R(N ≥ 2), ν is the unit outward normal vector to ∂ , 2< p < 2N/(N−2) for N ≥ 3, 2< p <+∞ for N = 2, and ε > 0 is a constant. Problem (P)ε may be viewed as prototype of pattern formation in biology. Indeed, the steady-state problem for a chemotactic aggregation model with logarithmic sensitivity is reduced by Keller and...

I discuss the role of the ∆I = 1/2 selection rule in K → ππ decays for the theoretical calculations of ε/ε . Lacking reliable “first principle” calculations, phenomenological approaches may help in understanding correlations among different contributions and available experimental data. In particular, in the chiral quark model approach the same dynamics which underlies the ∆I = 1/2 selection ru...

During the last decade, the stringent pressures from environmental and social requirements have spurred an interest in designing a reverse logistics (RL) network. The success of a logistics system may depend on the decisions of the facilities locations and vehicle routings. The location-routing problem (LRP) simultaneously locates the facilities and designs the travel routes for vehicles among ...

7 We study the problem of constructing ε-kernel coresets for uncertain points. We consider uncertainty8under the existential model where each point’s location is fixed but only occurs with a certain probability,9and the locational model where each point has a probability distribution describing its location. An ε-10kernel coreset approximates the width of a point set...