In this study, the effect of grafting with magnesium (Mg) ratios (0.1, 0.3, 0.5) on the structural and optical properties of cadmium oxide films (CdO) was studied, as these films were prepared on glass bases using the method of pulse laser deposition (PLD). The crystallization nature of the prepared membranes was examined by X-ray diffraction technique (XRD), which showed that the synthesis of the prepared membranes is polycrystalline, and (AFM) images also showed that the increased deformation with magnesium led to an increase in the grain size ratio and a decrease in surface roughness, as well as the absorption coefficient was calculated. And the optical energy gap for the prepared membranes, where it was found that the absorption coef

In this work, lead oxide nanoparticles were prepared by laser ablation of lead target immersed in deionized water by using pulsed Nd:YAG laser with laser energy 400 mJ/pulse and different laser pulses. The chemical bonding of lead oxide nps was investigated by Fourier Transform Infrared (FTIR); surface morphology and optical properties were investigated by Scanning Electron Microscope (SEM) and UV-Visible spectroscopy respectively, and the size effect of lead oxide nanoparticles was studied on its antibacterial action against two types of bacteria Gram-negitive (Escherichia coli) and Gram-positive (Staphylococcusaurus) by diffusion method. The antibacterial property results show that the antibacterial activity of the Lead oxide NPs was

Total dissolved solids are at the top of the parameters list of water quality that requires investigations for planning and management, especially for irrigation and drinking purposes. If the quality of water is sufficiently predictable, then appropriate management is possible. In the current study, Multiple Linear Regression (MLR) and Artificial Neural Network (ANN) models were used as indicators of water quality and for the prediction of Total Dissolved Solids (TDS) along the Tigris River, in Baghdad city. To build these models five water parameters were selected from the intakes of four water treatment plants on the Tigris River, for the period between 2013 and 2017. The selected water parameters were Total Dissolved Solids (TDS

The last decade of this 20th century provides a wide spread of applications of one of the computer techniques, which is called Fuzzy Logic. This technique depends mainly on the fuzzy set theory, which is considered as a general domain with respect to the conventional set theory. This paper presents in initiative the fuzzy sets theory and fuzzy logic as a complete mathematics system. Here it was explained the concept of fuzzy set and defined the operations of fuzzy logic. It contains eleven operations beside the other operations which related to fuzzy algebra. Such search is considered as an enhancement for supporting the others waiting search activities in this field.

In this work  Polyynes was synthesized by pulse laser ablation of graphite target in ethanol solution. UV-Visible Spectrophotometer, Fourier Transform Infrared Spectroscopy (FTIR) and Transmission electron microscopy (TEM) were used to study the optical absorption, chemical bonding, particle size and the morphology.  UV absorption peaks coincide with the electronic transitions corresponding to linear hydrogen – capped polyyne (C_n+1H₂), the absorption peaks intensity increased when the polyynes were produced at different laser energies and the formation rats of polyynes increased with the increasing of laser pulse number. The FTIR absorption peak at 2368.4 cm^-1, 1640.0 cm^-1 and 1276.

The use of real-time machine learning to optimize passport control procedures at airports can greatly improve both the efficiency and security of the processes. To automate and optimize these procedures, AI algorithms such as character recognition, facial recognition, predictive algorithms and automatic data processing can be implemented. The proposed method is to use the R-CNN object detection model to detect passport objects in real-time images collected by passport control cameras. This paper describes the step-by-step process of the proposed approach, which includes pre-processing, training and testing the R-CNN model, integrating it into the passport control system, and evaluating its accuracy and speed for efficient passenger flow

Multiple linear regressions are concerned with studying and analyzing the relationship between the dependent variable and a set of explanatory variables. From this relationship the values of variables are predicted. In this paper the multiple linear regression model and three covariates were studied in the presence of the problem of auto-correlation of errors when the random error distributed the distribution of exponential. Three methods were compared (general least squares, M robust, and Laplace robust method). We have employed the simulation studies and calculated the statistical standard mean squares error with sample sizes (15, 30, 60, 100). Further we applied the best method on the real experiment data representing the varieties of

This work was conducted to study the treatment of industrial waste water, and more particularly those in the General Company of Electrical Industries.This waste water, has zinc ion with maximum concentration in solution of 90 ppm.
The reuse of such effluent can be made possible via appropriate treatments, such as chemical coagulation, Na2S is used as coagulant.
The parameters that influenced the waste water treatment are: temperature, pH, dose of coagulant and settling time.
It was found that the best condition for zinc removal, within the range of operation used ,were a temperature of 20C a pH value of 13 , a coagulant dose of 15 g Na2S /400ml solution and a settling time of 7 days. Under these conditions the zinc concentrat

The area of character recognition has received a considerable attention by researchers all over the world during the last three decades. However, this research explores best sets of feature extraction techniques and studies the accuracy of well-known classifiers for Arabic numeral using the Statistical styles in two methods and making comparison study between them. First method Linear Discriminant function that is yield results with accuracy as high as 90% of original grouped cases correctly classified. In the second method, we proposed algorithm, The results show the efficiency of the proposed algorithms, where it is found to achieve recognition accuracy of 92.9% and 91.4%. This is providing efficiency more than the first method.