A study carried out to prepare Hg1-xCdxTe compound and to see the effect on increasing the percentage of x on the compound structure by using x-ray diffraction and atomic absorption for 0

The problem of Multicollinearity is one of the most common problems, which deal to a large extent with the internal correlation between explanatory variables. This problem is especially Appear in economics and applied research, The problem of Multicollinearity has a negative effect on the regression model, such as oversized variance degree and estimation of parameters that are unstable when we use the Least Square Method ( OLS), Therefore, other methods were used to estimate the parameters of the negative binomial model, including the estimated Ridge Regression Method and the Liu type estimator, The negative binomial regression model is a nonline

In order to take measures in controlling soil erosion it is required to estimate soil loss over area of interest. Soil loss due to soil erosion can be estimated using predictive models such as Universal Soil Loss Equation (USLE). The accuracy of these models depends on parameters that are used in equations. One of the most important parameters in equations used in both of models is (C) factor that represents effects of vegetation and other land covers. Estimating land cover by interpretation of remote sensing imagery involves Normalized Difference Vegetation Index (NDVI), an indicator that shows vegetation cover. The aim of this study is estimate (C) factor values for Part of Baghdad city using NDVI derived from satellite Image of Landsat-7

In this work, silicon nitride (Si₃N₄) thin films were deposited on metallic substrates (aluminium and titanium sheets) by the DC reactive sputtering technique using two different silicon targets (n-type and p-type Si wafers) as well as two Ar:N₂ gas mixing ratios (50:50 and 70:30). The electrical conductivity of the metallic (aluminium and titanium) substrates was measured before and after the deposition of silicon nitride thin films on both surfaces of the substrates. The results obtained from this work showed that the deposited films, in general, reduced the electrical conductivity of the substrates, and the thin films prepared from n-type silicon targets using a 50:50 mixing ratio and deposited on both

Undoped and Iodine (I)–doped chrome oxide (Cr2O3)thin films have been prepared by chemical spray pyrolysis technique at substrate temperatures(773K) on glass substrate. Absorbance and transmittance spectra have been recorded as a function of wavelength in the range (340-800 nm) in order to study the optical properties such as reflectance, Energy gap of allowed direct transition, extinction coefficient refractive index, and dielectric constant in real and imagery parts all as a function of wavelength. It was found that all the investigated parameters affect by the doping ratios.

Positron annihilation lifetime (PAL) technique has been employed to
study the microstructural changes of polyurethane (PU), EUXIT 101
and epoxy risen (EP), EUXIT 60 by Gamma-ray irradiation with the
dose range (95.76 - 957.6) kGy. The size of the free volume hole and
their fraction in PU and EP were determined from ortho-positronium
lifetime component and its intensity in the measured lifetime spectra.
The results show that the irradiation causes significant changes in the
free volume hole size (V_h) and the fractional free volume (F_h), and
thereby the microstructure of PU and EP. The results indicate that
the γ-dose increases the crystallinity in the amorphous regions of PU
and increas

In most manufacturing processes, and in spite of statistical control, several process capability indices refer to non conformance of the true mean (µc ) from the target mean ( µT ), and the variation is also high. In this paper, data have been analyzed and studied for a blow molded plastic product (Zahi Bottle) (ZB). WinQSB software was used to facilitate the statistical process control, and process capability analysis and some of capability indices. The relationship between different process capability indices and the true mean of the process were represented, and then with the standard deviation (σ ), of achievement of process capability value that can reduce the standard deviation value and improve production out of theoretical con

Deep learning has recently received a lot of attention as a feasible solution to a variety of artificial intelligence difficulties. Convolutional neural networks (CNNs) outperform other deep learning architectures in the application of object identification and recognition when compared to other machine learning methods. Speech recognition, pattern analysis, and image identification, all benefit from deep neural networks. When performing image operations on noisy images, such as fog removal or low light enhancement, image processing methods such as filtering or image enhancement are required. The study shows the effect of using Multi-scale deep learning Context Aggregation Network CAN on Bilateral Filtering Approximation (BFA) for d