In this paper, chip and powder copper are used as reinforcing phase in polyester matrix to form composites. Mechanical properties such as flexural strength and impact test of polymer reinforcement copper (powder and chip) were done, the maximum flexural strength for the polymer reinforcement with copper (powder and chip) are (85.13 Mpa) and (50.08 Mpa) respectively was obtained, while the maximum observation energy of the impact test for the polymer reinforcement with copper (powder and chip) are (0.85 J) and (0.4 J) respectively  

Well dispersed Cu2FeSnSe4 (CFTSe) nanofilms were synthesized by hot-injection method. The structural and morphological measurements were characterized using XRD (X-ray diffraction), Raman spectroscopy, SEM (scanning electron microscopy), and TEM (transmission electron microscopy). Chemical composition and optical properties of as-synthesized CFTSe nanoparticles were characterized using EDS (energy dispersive spectroscopy) and UV-Vis spectrophotometry. The average particle size of the nanoparticles was about 7-10 nm. The UV-Vis absorption spectra showed that the synthesized CFTS nanofilms have a band gap (Eg) of about 1.16 eV. Photo-electrochemical characteristics of CFTSe nanoparticles were studied and indicated their potential application

diasotiation compondnds sulphate upon with melting elemental aryl been used in his mouth for a while of studied

The MTX was converted to MTX nanoparticles by the modified method based on changing the pH gradually with exposure to ultrasound and shaking , changing the pH with exposure to ultrasound plays an significant role in the formation of nanoparticles, and this is shown in some previous studies. As the change in pH affects the nature of bonding between molecules, as well as the strength of bonding that depends on the change of electrical charges The exposure to ultrasound waves will greatly affect the breakdown of large particles into small particles that reach the level of nanoparticles. The MTX NPs formation was characterized by UV-Vis spectra analysis , Atomic force microscopy (AFM) analysis, Scanning electron microscope (SEM) and Fou

A new tridentate ligand has been synthesized derived from phenyl(pyridin-3-yl)methanone. Three coordinated metal complexes were prepared by complexation of the new ligand with Cu(II), Ni(II) and Zn(II) metal salts. The new Schiff base “benzyl -2-[phenyl(pyridin-3-yl)methylidene]hydrazinecarbodithioate” and the new metal complexes were characterized using various physico-chemical and spectroscopic techniques. From the analysis results, the expected structure to the metal complexes are octahedral in geometry for Cu(II) complex, square planner for Ni(II) and tetrahedral for Zn(II) complex. The new compounds are expected to show strong bioactivity against bacteria and cancer cells.

Data of multispectral satellite image (Landsat- 5 and Landsat-7) was used to monitoring the case of study area in the agricultural (extension and plant density), using ArcGIS program by the method of analysis (Soil adjusted vegetative Index). The data covers the selected area at west of Baghdad Government with a part of the Anbar and Karbala Government. Satellite image taken during the years 1990, 2001 and 2007. The scene of Satellite Image is consists of seven of spectral band for each satellite, Landsat-5(TM) thematic mapper for the year 1990, as well as satellite Landsat-7 (ETM+) Enhancement thematic mapper for the year 2001 and 2007. The results showed that in the period from 1990 to 2001 decreased land area exposed (bare) and increased

During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve

In this work Laser wireless video communication system using intensity modualtion direct
detection IM/DD over a 1 km range between transmitter and receiver is experimentally investigated and
demonstrated. Beam expander and beam collimeter were implemented to collimete laser beam at the
transmitter and focus this beam at the receiver respectively. The results show that IM/DD communication
sysatem using laser diode is quite attractive for transmitting video signal. In this work signal to noise
ratio (S/N) higher than 20 dB is achieved in this work.

During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve