Single photon detectors sensitive to near-infrared (NIR) wavelength light are used in an increasing number of applications, such as quantum key distribution, laser detection and ranging, and integrated circuit analysis. There are many types of NIR single photon detectors, e.g. photomultiplier tube, superconducting single photon detector and single photon avalanche diode (SPAD). However, the SPA...

In this paper, we solve two problems for some nonlinear SPDE driven by FiskStratonovich stoachastic integral. The main assumption is the commuting property of the drift and diffusion vector fields with respect of the Lie bracket. In the first problem (P1) we construct a classical solution for some nonlinear SPDE of parabolic type by assuming the compatibilty condition concerning the mentioned v...

The Pareto Differential Evolution (PDE) algorithm was introduced last year and showed competitive results. The behavior of PDE, as in many other evolutionary multiobjective optimization (EMO) methods, varies according to the crossover and mutation rates. In this paper, we present a new version of PDE with self-adaptive crossover and mutation. We call the new version Self–adaptive Pareto Differe...

The existence of random attractors for a large class of stochastic partial differential equations (SPDE) driven by general additive noise is established. The main results are applied to various types of SPDE, as e.g. stochastic reaction-diffusion equations, the stochastic p-Laplace equation and stochastic porous media equations. Besides classical Brownian motion, we also include space-time frac...

We deal with parametric estimation for a parabolic linear second-order stochastic partial differential equation (SPDE) small dispersion parameter based on high-frequency data which are observed in time and space. Using the thinned respect to space obtained from data, minimum contrast estimators of two coefficient parameters SPDE proposed. With these we construct an approximation coordinate proc...

In many applications it is important to be able to sample paths of SDEs conditional on observations of various kinds. This paper studies SPDEs which solve such sampling problems. The SPDE may be viewed as an infinite dimensional analogue of the Langevin SDE used in finite dimensional sampling. Here the theory is developed for conditioned Gaussian processes for which the resulting SPDE is linear...

In many applications it is important to be able to sample paths of SDEs conditional on observations of various kinds. This paper studies SPDEs which solve such sampling problems. The SPDE may be viewed as an infinite dimensional analogue of the Langevin SDE used in finite dimensional sampling. Here the theory is developed for conditioned Gaussian processes for which the resulting SPDE is linear...

The present study describes a method based on headspace-solid-phase dynamic extraction (HS-SPDE) followed by GC/MS for the qualitative and quantitative analysis of benzene, toluene, ethylbenzene, o-, m- and p-xylene (BTEX), and n-aldehydes (C(6)-C(10)) in water. To enhance the extraction capability of the HS-SPDE a new cooling device was tested that controls the temperature of the SPDE needle d...

Stochastic partial differential equations (SPDEs) are the basic tool for modeling systems where noise is important. SPDEs are used for models of turbulence, pattern formation, and the structural development of the universe itself. It is reasonably well known that certain SPDEs can be manipulated to be equivalent to (nonquantum) field theories that nevertheless exhibit deep and important relatio...

Accidents on the road have always been a major concern in modern society. According to World Health Organization, globally traffic collisions are one of leading and fastest growing causes disability death. The present research work is conducted ten years accident data an urban environment explore analyze spatial temporal variation accidents related injuries. proposed spatiotemporal model can ma...