Thin films whose compositions can be expressed by (GeS₂)_100-xGa_x (x=0, 6,12,18) formula were obtained by thermal evaporation technique  of bulk material at a base pressure of ~10^-5 torr. Optical transmission spectra of the films were taken in the range of 300-1100 nm then the optical band gap, tail width of localized states,  refractive index, extinction coefficient were calculated. The optical constants were found to increase at low concentration of Ga (0 to12%) while they decreases with further addition of Ga. The optical band gap was found to change in opposite manner to that of optical constants. The variation in the optical parameters are explained in terms of average bond energy

The main objective of the research is to identify the role of strategic training and its effect on enhancing the self-growth of the individual. Stratigic training represents a contemporary tendency. that is adopted by business organizations in carrying out their activities and tasks.

It is worth to mention, that self-growth of the individual is one of the indictors used to determine the ability of organization to a achieve its goals. 

The problem of the research has pointed out to the minimum awareness of the important role played by training strategy in enhancing the self-growth of the individual. The researcher has adopted an analytical approach, in collecting and analyses

In this work the analysis of laser beam profile system ,using a two dimensional CCD (Charge Coupled Device) arrays, is established. The system is capable of producing video graphics that give a two dimensional image of laser beam. The video graphics system creates color distribution that represent the intensity distribution of the laser beam or the energy profile of the beam. The software used is capable of analyzing and displaying the profile in four different methods that is , color code intensity contouring , intensity shareholding, intensity cross section along two dimension x-y, and three dimensional plot of the beam intensity given in the same display.

Smart systems are the trend for modern organizations and should meet the quality of services that expect to produce. Internet of Everything (IoE) helped smart systems to adopt microcontrollers for improving the performance. Analyzing and controlling data in such a system are critical issues. In this study, a survey of IoE systems conducted to show how to apply a suitable model that meets such system requirements. The analysis of some microcontroller boards is explored based on known features. Factors for applying IoE devices have been defined such as connectivity, power consumption, compatibility, and cost. Different methods have been explained as an overview of applying IoE systems. Further, different approaches for applying IoE technology

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.

<span lang="EN-US">Diabetes is one of the deadliest diseases in the world that can lead to stroke, blindness, organ failure, and amputation of lower limbs. Researches state that diabetes can be controlled if it is detected at an early stage. Scientists are becoming more interested in classification algorithms in diagnosing diseases. In this study, we have analyzed the performance of five classification algorithms namely naïve Bayes, support vector machine, multi layer perceptron artificial neural network, decision tree, and random forest using diabetes dataset that contains the information of 2000 female patients. Various metrics were applied in evaluating the performance of the classifiers such as precision, area under the c

Obtaining the computational models for the functioning of the brain gives us a chance to understand the brain functionality thoroughly. This would help the development of better treatments for neurological illnesses and disorders. We created a cortical model using Python language using the Brian simulator. The Brian simulator is specialized in simulating the neuronal connections and synaptic interconnections. The dynamic connection model has multiple parameters in order to ensure an accurate simulation (Bowman, 2016). We concentrated on the connection weights and studied their effect on the interactivity and connectivity of the cortical neurons in the same cortical layer and across multiple layers. As synchronization helps us to mea