A metal-assisted chemical etching process employing p-type silicon wafers with varied etching durations is used to produce silicon nanowires. Silver nanoparticles prepared by chemical deposition are utilized as a catalyst in the formation of silicon nanowires. Images from field emission scanning electron microscopy confirmed that the diameter of SiNWs grows when the etching duration is increased. The photoelectrochemical cell's characteristics were investigated using p-type silicon nanowires as working electrodes. Linear sweep voltammetry (J-V) measurements on p-SiNWs confirmed that photocurrent density rose from 0.20 mA cm^-2 to 0.92 mA cm^-2 as the etching duration of prepared SiNWs increased from 15 to 30 min. The

The Adaptive Optics technique has been developed to obtain the correction of atmospheric seeing. The purpose of this study is to use the MATLAB program to investigate the performance of an AO system with the most recent AO simulation tools, Objected-Oriented Matlab Adaptive Optics (OOMAO). This was achieved by studying the variables that impact image quality correction, such as observation wavelength bands, atmospheric parameters, telescope parameters, deformable mirror parameters, wavefront sensor parameters, and noise parameters. The results presented a detailed analysis of the factors that influence the image correction process as well as the impact of the AO components on that process

The study aims to build a water quality index that fits the Iraqi aquatic systems and reflects the environmental reality of Iraqi water. The developed Iraqi Water Quality Index (IQWQI) includes physical and chemical components. To build the IQWQI, Delphi method was used to communicate with local and global experts in water quality indices for their opinion regarding the best and most important parameter we can use in building the index and the established weight of each parameter. From the data obtained in this study, 70% were used for building the model and 30% for evaluating the model. Multiple scenarios were applied to the model inputs to study the effects of increasing parameters. The model was built 4 by 4 until it reached 17 parame

The objective of the current research was to develop the posaconazole (PCZ) loaded NS into the carbopol 934 polymeric gel for prolonged drug release and improved topical delivery; seven different nanosponge formulations of PCZ were formulated using the emulsion solvent diffusion method using various amounts of polymer (ethylcellulose, EC). The aqueous and dispersed phases were prepared using polyvinyl alcohol (PVA) and dichloromethane. The prepared nanosponges (NS) were studied for particle size, structural appearance, and in vitro drug release. Furthermore, the selected formula was formulated as hydrogel and was evaluated for physical characteristics, drug content, and in-vitro drug release. Morphological studies revealed irregular

     In this paper, the botnet detection problem is defined as a feature selection problem and the genetic algorithm (GA) is used to search for the best significant combination of features from the entire search space of set of features. Furthermore, the Decision Tree (DT) classifier is used as an objective function to direct the ability of the proposed GA to locate the combination of features that can correctly classify the activities into normal traffics and botnet attacks. Two datasets  namely the UNSW-NB15 and the Canadian Institute for Cybersecurity Intrusion Detection System 2017 (CICIDS2017), are used as evaluation datasets. The results reveal that the proposed DT-aware GA can effectively find the relevant features from

Artificial Neural Networks (ANN) is one of the important statistical methods that are widely used in a range of applications in various fields, which simulates the work of the human brain in terms of receiving a signal, processing data in a human cell and sending to the next cell. It is a system consisting of a number of modules (layers) linked together (input, hidden, output). A comparison was made between three types of neural networks (Feed Forward Neural Network (FFNN), Back propagation network (BPL), Recurrent Neural Network (RNN). he study found that the lowest false prediction rate was for the recurrentt network architecture and using the Data on graduate students at the College of Administration and Economics, Univer

Extracting, studying and interpreting the morphological database of a basin is a basic building block for building a correct geomorphological understanding of this basin. In this work, Arc GIS 10.8 software and SRTM DEM satellite images were used. The principle of data integration was adopted by extracting the quantitative values of the morphometric characteristics that are affected by the geomorphological condition of the studied basin, then eliciting an optimal conception of the geomorphological condition of the basin from the meanings and connotations of these combined transactions. Hypsometric integration was extracted for each region in the basin separately with the value of integration of the plot curve for the relative heights of

Nanostructural cupric oxide (CuO) films were prepared on Si and glass substrate by pulsed laser deposition technique (PLD) using laser Nd:YAG, using different laser pulses energies from 200 to 600 mJ. The X-ray diffraction pattern (XRD) of the films showed a polycrystalline structure with a monoclinic symmetry and preferred orientation toward (111) plane with nano structure. The crystallite size was increasing with increasing of laser pulse energy. Optical properties was characterized by using UV–vis spectrometer in the wave lengthrange (200-1100) nm at room temperature. The results showed that the transmission spectrum decreases with the laser pulses energy increase. Sensitivity of NO2 gas at different operating temperatures, (50°C,