Current studies interested on the biosynthesis of zinc oxide nanoparticles (ZnO-NPs) using hot plants extracts of Allium sativum and characterization of them using: Atomic Force Microscopy (AFM), X-ray diffractions (XRD), Fourier Transform Infrared Spectroscopy (FT- IR), UV–visible spectral and Hot stage. The results found that all NPs are had nano-size. ZnO NPs was produced by four procedures using hot extract of Allium sativum. The average diameters were: 101.59 nm, 110.33 nm, 75.69 nm, 88.67 nm for first, second, third and fourth procedures respectively compared with 47.57 nm for standard NPs. The Roughness averages (Ra) were: 10.8 nm, 6.83 nm, 13.8 nm, 0.541 nm for first, second, third and fourth respectively. The Root mean square (Sq

In the present work, pattern recognition is carried out by the contrast and relative variance of clouds. The K-mean clustering process is then applied to classify the cloud type; also, texture analysis being adopted to extract the textural features and using them in cloud classification process. The test image used in the classification process is the Meteosat-7 image for the D3 region.The K-mean method is adopted as an unsupervised classification. This method depends on the initial chosen seeds of cluster. Since, the initial seeds are chosen randomly, the user supply a set of means, or cluster centers in the n-dimensional space.The K-mean cluster has been applied on two bands (IR2 band) and (water vapour band).The textural analysis is used

Finite element modeling of transient temperature distribution is used to understand physical phenomena occurring during the dwell (penetration) phase and moving of welding tool in friction stir welding (FSW) of 5mm plate made of 7020-T53 aluminum alloy at 1400rpm and 40mm/min.
Thermocouples are used in locations near to the pin and under shoulder surface to study the welding tool penetration in the workpiece in advance and retreate sides along welding line in three positions (penetrate (start welding) , mid, pullout (end welding)).
Numerical results of ANSYS 12.0 package are compared to experimental data including axial load measurements at different tool rotational speeds (710rpm.900rpm.1120rpm and 1400rpm) Based on the experiment

This work deals with the nematode parasitesfrom the midgut of (16) specimens of Green
toad (Bufo viridis) Laurenti, 1768 collected from Baghdad area,central Iraq.
The parasites are:Cosmocercoides variabilis (Cosmocercidae) that considered as the first
report in Iraq on it and Oswaldocruzia filiformis (Molineidae).

This paper proposes a better solution for EEG-based brain language signals classification, it is using machine learning and optimization algorithms. This project aims to replace the brain signal classification for language processing tasks by achieving the higher accuracy and speed process. Features extraction is performed using a modified Discrete Wavelet Transform (DWT) in this study which increases the capability of capturing signal characteristics appropriately by decomposing EEG signals into significant frequency components. A Gray Wolf Optimization (GWO) algorithm method is applied to improve the results and select the optimal features which achieves more accurate results by selecting impactful features with maximum relevance

In this work, satellite images classification for Al Chabaish marshes and the area surrounding district in (Dhi Qar) province for years 1990,2000 and 2015 using two software programming (MATLAB 7.11 and ERDAS imagine 2014) is presented. Proposed supervised classification method (Modified Vector Quantization) using MATLAB software and supervised classification method (Maximum likelihood Classifier) using ERDAS imagine have been used, in order to get most accurate results and compare these methods. The changes that taken place in year 2000 comparing with 1990 and in year 2015 comparing with 2000 are calculated. The results from classification indicated that water and vegetation are decreased, while barren land, alluvial soil and shallow water