Abstract: Aluminum alloys grade 6061-T6 are characterized by their excellent properties and processing characteristics which make them ideal for varieties of industrial applications under cyclic loading, aluminum alloys show less fatigue life than steel alloys of similar strength. In the current study, a nanosecond fiber laser of maximum pulse energy up to 9.9 mJ was used to apply laser shock peening process (LSP) on aluminum thin sheets to introduce residual stresses in order to enhance fatigue life under cyclic loading Box-Behnken design (BBD) based on the design of experiments (DOE) was employed in this study for experimental design data analysis, model building and optimization The effect of working parameters spot size (ω), scannin

Thin a-:H films were grown successfully by fabrication of designated ingot followed by evaporation onto glass slides. A range of growth conditions, Ge contents, dopant concentration (Al and As), and substrate temperature, were employed. Stoichiometry of the thin films composition was confirmed using standard surface techniques. The structure of all films was amorphous. Film composition and deposition parameters were investigated for their bearing on film electrical and optical properties. More than one transport mechanism is indicated. It was observed that increasing substrate temperature, Ge contents, and dopant concentration lead to a decrease in the optical energy gap of those films. The role of the deposition conditions on value

Thin films of highly pure (99.999%) Tellurium was prepared by high vacuum technique (5*10-5torr), on glass substrates .Thin films have thickness 0.6m was evaporated by thermal evaporation technique. The film deposited was annealed for one hour in vacuum of (5*10-4torr) at 373 and 423 K. Structural and electrical properties of the films are studies. The x-ray diffraction of the film represents a poly-crystalline nature in room temperature and annealed film but all films having different grain sizes. The d.c. electrical properties have been studied at low and at relatively high temperatures and show that the conductivity decreases with increasing temperature at all range of temperature. Two types of conduction mechanisms were found to d

BaTiO3 thin films have been deposited on Si (111) and glass substrates by using pulsed laser deposition technique. The films were characterized by using X-ray diffraction, atomic force microscope and optical transmission spectra. The films growth on Si after annealing at 873K showed a polycrystalline nature, and exhibited tetragonal structure, while on glass substrate no growth was noticed at that temperature. UV-VIS transmittance measurements showed that the films are highly transparent in the visible wavelength region and near-infrared region for sample annealing on glass substrate. The optical gap of the film were calculated from the curve of absorption coefficient (αhν) 2 vs. hν and was found tobe 3.6 eV at substrate temperature 5

              In this work, pure and doped Vanadium Pentoxide (V₂O₅) thin films with different concentration of TiO₂ (0, 0.1, 0.3, 0.5) wt  were obtained using Pulse laser deposition technique on amorphous glass substrate with thickness of (250)nm. The morphological, UV-Visible and Fourier Transform Infrared Spectroscopy (FT-IR) were studied. TiO₂ doping into V₂O₅ matrix revealed an interesting morphological change from an array of high density pure V₂O₅ nanorods (~140 nm) to granular structure in TiO₂-doped V₂O₅ thin film .Transform Infrared Spectro

In recent years, the world witnessed a rapid growth in attacks on the internet which resulted in deficiencies in networks performances. The growth was in both quantity and versatility of the attacks. To cope with this, new detection techniques are required especially the ones that use Artificial Intelligence techniques such as machine learning based intrusion detection and prevention systems. Many machine learning models are used to deal with intrusion detection and each has its own pros and cons and this is where this paper falls in, performance analysis of different Machine Learning Models for Intrusion Detection Systems based on supervised machine learning algorithms. Using Python Scikit-Learn library KNN, Support Ve

Tuberculosis status as the second leading causes of significant morbidity and mortality from an infectious disease worldwide, after human immunodeficiency virus (HIV). Sample collection was conducted at the Institute of Chest and Respiratory Diseases/Baghdad Medical City in Baghdad. The collection interval was from August to October 2014, 629 suspected TB patients were examined during this period. The results revealed among total 629 specimens, 56 (8.9%) of the specimens were positive by direct examination and 573 (91.1%) negative specimens by smear microscopy. Fifty six DNA samples were extracted from positive ZN smears of sputum specimens and 40 samples from healthy persons (as control) were subjected to molecular diagnosis by real tim