One of the diseases on a global scale that causes the main reasons of death is lung cancer. It is considered one of the most lethal diseases in life. Early detection and diagnosis are essential for lung cancer and will provide effective therapy and achieve better outcomes for patients; in recent years, algorithms of Deep Learning have demonstrated crucial promise for their use in medical imaging analysis, especially in lung cancer identification. This paper includes a comparison between a number of different Deep Learning techniques-based models using Computed Tomograph image datasets with traditional Convolution Neural Networks and SequeezeNet models using X-ray data for the automated diagnosis of lung cancer. Although the simple details p

Biometrics represent the most practical method for swiftly and reliably verifying and identifying individuals based on their unique biological traits. This study addresses the increasing demand for dependable biometric identification systems by introducing an efficient approach to automatically recognize ear patterns using Convolutional Neural Networks (CNNs). Despite the widespread adoption of facial recognition technologies, the distinct features and consistency inherent in ear patterns provide a compelling alternative for biometric applications. Employing CNNs in our research automates the identification process, enhancing accuracy and adaptability across various ear shapes and orientations. The ear, being visible and easily captured in

Semiconductor laser is used in processing many issues related to the scientific, military, medical, industrial and agricultural fields due to its unique properties such as coherence and high strength where GaN-based components are the most efficient in this field. Current technological developments mention to the strong connection of GaN with sustainable electronic and optoelectronic devices which have high-efficiency. The threshold current density of Al0.1Ga0.9N/GaN triple quantum well laser structure was investigated to determine best values of the parameters affecting the threshold current density that are well width, average thickness of active region, cavity length, reflectivity of cavity mirrors and optical confinement factor. The opt

Sage (Salvia officinalis), belong to Labiatae family is indigenous to Iraq and other Mediterranean areas but now cultivated world- wide, principally for its use as culinary herb. In the present study preliminary screening for the important phytochemical natural product groups indicated the presence of flavonoid, saponin, hyrolysable and condensed tannin groups. The antibacterial  activity of two concentrations 10 mg/ml and 100 mg/ml of chloroform and hydroalcoholic extracts from  Salvia officinalis leaves was evaluated against four strains of gram negative bacteria (Escherichia coli,  Pseudomonas arigenossa,  Klebsiella pneumonia, and  Proteus spp) and two str

Copper with different concentrations doped with zinc oxide nanoparticles were prepared from a mixture of zinc acetate and copper acetate with sodium hydroxide in aqueous solution. The structure of the prepared samples was done by X-ray diffraction, atomic force microscopy (AFM) and UV-VIS absorption spectrophotometer. Debye-Scherer formula was used to calculate the size of the prepared samples. The band gap of the nanoparticle ZnO was determined by using UV-VIS optical spectroscopy.

Risks are confronting the foundations of buildings and structures when exposed to earthquakes which leads to high displacements that may cause the failure of the structures. This research elaborates numerically the effect of the earthquake on the vertical and lateral displacement of footing resting on the soil. The thickness of the footing and depth of soil layer below the footing was taken as (0.5, 1.0, and 2.0 m) and (10, 20 and 40m), respectively. The stiffness ratio of soil to footing was also elaborated at 0.68, 0.8, 1.0, and 1.7. The results showed an increase in the verticle displacement of footing as the duration of the earthquake increases. The increase of soil layer thickness below the footing leads to a reduction in the vertical

Different additives are used in drilling fluids when the demanded properties cannot be gotten with clays. Drilling muds needs several additives and materials to give good characteristics. There are local alternatives more suitable for enhancing the rheology and filtration of drilling fluids. An experimental work had been conducted to assess the suitability of using potato starch to enhance rheological properties and filtration in drilling mud. This study investigated the potato starch as a viscosifier and fluid losses agent in drilling fluid. Results from this study proved that rheological properties of potato starch mud increased when pH of drilling fluid is increased.  Potato starch could be used to enhance gel strength at low pH

The operating characteristics of optoelectronic devices depend critically on the properties physical of the constituent materials, interesting compound has been focused on this research formed from group III and V of the periodic table. Thin film n-InSb heterjuntion were successfully fabricated on p-Si substrates by thermal evaporation technique at different annealing temperature (as prepared, 400,500,600) °C. The effect of annealing temperature on the structural, surface morphology, optical and optoelectronic properties of InSb films were investigated and studied. The crystal structure of the film was characterized by X-ray diffraction and techniques. AFM techniques inspect the surface morphology of InSb films, the study presented the val

The type of groundwater in the studied area is slightly brackish. In general, the dominant water type is calcium-sulfate. The reasons behind these different chemical groundwater types can be referred to the active ion exchange between the groundwater of the Dammam aquifer and Rus Formation. The groundwater of the Dammam unconfined aquifer is not suitable for human drinking in all the parameters properties. The groundwater class is fair in the Qasir Al-Ukhaider area, while the Shebcha area and Al-Salman area are poor class except the eastern part of Al-Salman area is very poor.