Thin films of Mn2O3 doped with Cu have been fabricated using the simplest and cheapest chemical spray pyrolysis technique onto a glass substrate heated up to 250 oC. Transmittance and absorptance spectra were studied in the wavelength range (300 -1100) nm. The average transmittance at low energy was about 60% and decrease with Cu doping, Optical constants like refractive index, extinction coefficient and dielectric constants (εr), (εi) are calculated and correlated with doping process.

Using photo electrochemical etching technique (PEC), porous silicon (PS) layers were produced on n-type silicon (Si) wafers to generate porous silicon for n-type with an orientation of (111) The results of etching time were investigated at: (5,10,15 min). X-ray diffraction experiments revealed differences between the surface of the sample sheet and the synthesized porous silicon. The largest crystal size is (30 nm) and the lowest crystal size is (28.6 nm) The analysis of Atomic Force Microscopy (AFM) and Field Emission Scanning Electron Microscope (FESEM) were used to research the morphology of porous silicon layer. As etching time increased, AFM findings showed that root mean square (RMS) of roughness and po

This research deals with a shrinking method concernes with the principal components similar to that one which used in the multiple regression “Least Absolute Shrinkage and Selection: LASS”. The goal here is to make an uncorrelated linear combinations from only a subset of explanatory variables that may have a multicollinearity problem instead taking the whole number say, (K) of them. This shrinkage will force some coefficients to equal zero, after making some restriction on them by some "tuning parameter" say, (t) which balances the bias and variance amount from side, and doesn't exceed the acceptable percent explained variance of these components. This had been shown by MSE criterion in the regression case and the percent explained v

This research describes a new model inspired by Mobilenetv2 that was trained on a very diverse dataset. The goal is to enable fire detection in open areas to replace physical sensor-based fire detectors and reduce false alarms of fires, to achieve the lowest losses in open areas via deep learning. A diverse fire dataset was created that combines images and videos from several sources. In addition, another self-made data set was taken from the farms of the holy shrine of Al-Hussainiya in the city of Karbala. After that, the model was trained with the collected dataset. The test accuracy of the fire dataset that was trained with the new model reached 98.87%.

The unstable and uncertain nature of natural rubber prices makes them highly volatile and prone to outliers, which can have a significant impact on both modeling and forecasting. To tackle this issue, the author recommends a hybrid model that combines the autoregressive (AR) and Generalized Autoregressive Conditional Heteroscedasticity (GARCH) models. The model utilizes the Huber weighting function to ensure the forecast value of rubber prices remains sustainable even in the presence of outliers. The study aims to develop a sustainable model and forecast daily prices for a 12-day period by analyzing 2683 daily price data from Standard Malaysian Rubber Grade 20 (SMR 20) in Malaysia. The analysis incorporates two dispersion measurements (I

A common approach to the color image compression was started by transform
the red, green, and blue or (RGB) color model to a desire color model, then applying
compression techniques, and finally retransform the results into RGB model In this
paper, a new color image compression method based on multilevel block truncation
coding (MBTC) and vector quantization is presented. By exploiting human visual
system response for color, bit allocation process is implemented to distribute the bits
for encoding in more effective away.
To improve the performance efficiency of vector quantization (VQ),
modifications have been implemented. To combines the simple computational and
edge preservation properties of MBTC with high c

This research depends on the relationship between the reflected spectrum, the nature of each target, area and the percentage of its presence with other targets in the unity of the target area. The changes occur in Land cover have been detected for different years using satellite images based on the Modified Spectral Angle Mapper (MSAM) processing, where Landsat satellite images are utilized using two software programming (MATLAB 7.11 and ERDAS imagine 2014). The proposed supervised classification method (MSAM) using a MATLAB program with supervised classification method (Maximum likelihood Classifier) by ERDAS imagine have been used to get farthest precise results and detect environmental changes for periods. Despite using two classificatio

In this study, Al2O3 thin films were prepared by dc reactive sputtering technique using different gas mixtures of argon and oxygen gases (90:10, 70:30, 50:50, 30:70, and 10:90). These films were characterized to introduce their surface morphology and elemental composition as functions of the oxygen content in the gas mixture. The gas mixing ratio plays a crucial role in controlling the nanoscale morphology of the prepared thin films. The [Al]/[O] ratio varies non-linearly with the Ar:O2​ mixing ratio. Increasing the oxygen content leads to a progressive decrease in surface roughness, resulting in smoother and more uniform films with finer granular features. These results presented herein are useful to optimize the sputtering process to ac