This paper is concerned with preliminary test double stage shrinkage estimators to estimate the variance (s²) of normal distribution when a prior estimate  of the actual value (s²) is a available when the mean is unknown  , using specifying shrinkage weight factors y(×) in addition to pre-test region (R).

      Expressions for the Bias, Mean squared error [MSE (×)], Relative Efficiency [R.EFF (×)], Expected sample size [E(n/s²)] and percentage of overall sample saved of proposed estimator were derived. Numerical results (using MathCAD program) and conclusions are drawn about selection of different constants including in the me

Flexible pavements are considered an essential element of transportation infrastructure. So, evaluations of flexible pavement performance are necessary for the proper management of transportation infrastructure. Pavement condition index (PCI) and international roughness index (IRI) are common indices applied to evaluate pavement surface conditions. However, the pavement condition surveys to calculate PCI are costly and time-consuming as compared to IRI. This article focuses on developing regression models that predict PCI from IRI. Eighty-three flexible pavement sections, with section length equal to 250 m, were selected in Al-Diwaniyah, Iraq, to develop PCI-IRI relationships. In terms of the quantity and severity of eac

In modern times face recognition is one of the vital sides for computer vision. This is due to many reasons involving availability and accessibility of technologies and commercial applications. Face recognition in a brief statement is robotically recognizing a person from an image or video frame. In this paper, an efficient face recognition algorithm is proposed based on the benefit of wavelet decomposition to extract the most important and distractive features for the face and Eigen face method to classify faces according to the minimum distance with feature vectors. Faces94 data base is used to test the method. An excellent recognition with minimum computation time is obtained with accuracy reaches to 100% and recognition time decrease

The issue of increasing the range covered by a wireless sensor network with restricted sensors is addressed utilizing improved CS employing the PSO algorithm and opposition-based learning (ICS-PSO-OBL). At first, the iteration is carried out by updating the old solution dimension by dimension to achieve independent updating across the dimensions in the high-dimensional optimization problem. The PSO operator is then incorporated to lessen the preference random walk stage's imbalance between exploration and exploitation ability. Exceptional individuals are selected from the population using OBL to boost the chance of finding the optimal solution based on the fitness value. The ICS-PSO-OBL is used to maximize coverage in WSN by converting r

In this research, some robust non-parametric methods were used to estimate the semi-parametric regression model, and then  these methods were compared using the MSE comparison criterion, different sample sizes, levels of variance, pollution rates, and three different models were used. These methods are S-LLS S-Estimation -local smoothing, (M-LLS)M- Estimation -local smoothing, (S-NW) S-Estimation-NadaryaWatson Smoothing, and (M-NW) M-Estimation-Nadarya-Watson Smoothing.

The results in the first model proved that the (S-LLS) method was the best in the case of large sample sizes, and small sample sizes showed that the

In this paper,the homtopy perturbation method (HPM) was applied to obtain the approximate solutions of the fractional order integro-differential equations . The fractional order derivatives and fractional order integral are described in the Caputo and Riemann-Liouville sense respectively. We can easily obtain the solution from convergent the infinite series of HPM . A theorem for convergence and error estimates of the HPM for solving fractional order integro-differential equations was given. Moreover, numerical results show that our theoretical analysis are accurate and the HPM can be considered as a powerful method for solving fractional order integro-diffrential equations.

The Cu2SiO3 composite has been prepared from the binary compounds (Cu2O, and SiO2) with high purity by solid state reaction. The Cu2SiO3 thin films were deposited at room temperature on glass and Si substrates with thickness 400 nm by pulsed laser deposition method. X-ray analysis showed that the powder of Cu2SiO3 has a polycrystalline structure with monoclinic phase and preferred orientation along (111) direction at 2θ around 38.670o which related to CuO phase. While as deposited and annealed Cu2SiO3 films have amorphous structure. The morphological study revealed that the grains have granular and elliptical shape, with average diameter of 163.63 nm. The electrical properties which represent Hall effect were investigated. Hall coeffici

This paper deals with the blow-up properties of positive solutions to a parabolic system of two heat equations, defined on a ball in  associated with coupled Neumann boundary conditions of exponential type. The upper bounds of blow-up rate estimates are derived. Moreover, it is proved that the blow-up in this problem can only occur on the boundary.