Abstract

The study aimed: To assess the level of trainers' knowledge about the application of strategies and to find out the relationship between Trainer's knowledge and their socio-demographic characteristics.

Methodology: Using the pre-experimental design of the current study, for one group of 47 trainers working at the private Autism Centers in Baghdad, data was collected from 8/January / 2022 to 13 /February /2022. Using non-probability samples (convenient samples), self-management technology in which trainers fill out the questionnaire form themselves was used in the data collection process; it was analyzed through descriptive and inference statistics.

The 2D resistivity imaging technique was applied in an engineering study for the investigation of subsurface weakness zones within University of Anbar, western Iraq. The survey was carried out using Dipole-dipole array with an n-factor of 6 and a-spacing values of 2 m and 5 m. The inverse models of the 2D electrical imaging clearly show the resistivity contrast between the anomalous parts of the weakness zones and the background resistivity distribution. The thickness and shape of the subsurface weakness zones were well defined from the 2D imaging using Dipole-dipole array of 2 m a-spacing. The thickness of the weakness zone ranges between 9.5 m to 11.5 m. Whereas the Dipole-dipole array with a-spacing of 5 m and n-factor of 6 allocated

Diagnostic X-ray is one of the ionizing radiation that plays an important role in medical examination. Despite its great benefit, it is considered the largest source of artificial radiation exposure to public. The aim of the study is to measure the entrance surface dose (ESD) of patients undergoing chest, lumber spine and knee X-ray examination using TLD-100. The mean Entrance surface dose of chest (PA), lumber spine (AP, LAT) and knee (AP, LAT) are 1.3mGy, 8.57mGy, 21.5mGy and 0.49mGy, 0.48mGy respectively. The ESDs measured were found to be higher than the published work.

I

In this study, optical fibers were designed and implemented as a chemical sensor based on surface plasmon resonance (SPR) to estimate the age of the oil used in electrical transformers. The study depends on the refractive indices of the oil. The sensor was created by embedding the center portion of the optical fiber in a resin block, followed by polishing, and tapering to create the optical fiber sensor. The tapering time was 50 min. The multi-mode optical fiber was coated with 60 nm thickness gold metal. The deposition length was 4 cm. The sensor's resonance wavelength was 415 nm. The primary sensor parameters were calculated, including sensitivity (6.25), signal-to-noise ratio (2.38), figure of merit (4.88), and accuracy (3.2)

There is currently a pressing need to create an electro-analytical approach capable of detecting and monitoring genosensors in a highly sensitive, specific, and selective way. In this work, Functionalized Multiwall Carbon Nanotubes, Graphene, Polypyrrole, and gold nanoparticles nanocomposite (f-MWCNTs-GR-PPy-AuNP) were effectively deposited on the surface of the ITO electrode using a drop-casting process to modify it. The structural, morphological, and optical analysis of the modified ITO electrodes was carried out at room temperature using X-ray diffraction (XRD), field emission scanning electron microscopy (FE-SEM) images, atomic force microscopy (AFM) and Fourier transform infrared (FTIR) spectra. Cyclic voltammetry (CV) and electrochemi

 The optimum process conditions of the electrochemical deposition of carbon nanotubes (CNT) have been established by using developed, cheap and simple system. It has been found that temperature affects on the rate, purity and the yield of CNT obtained in this process. The electrochemical behavior of CNT deposition, kinetic and thermodynamic parameters were also discussed.

     In this paper, the propose is to use the xtreme value distribution as the rate of occurrence of the non-homogenous Poisson process, in order to improve the rate of occurrence of the non-homogenous process, which has been called the Extreme value Process. To estimate the parameters of this process, it is proposed to use the Maximum Likelihood method, Method of Moment and a smart method represented by the Artificial Bee Colony:(ABC) algorithm to reach an estimator for this process which represents the best data representation. The results of the three methods are compared through a simulation of the model, and it is concluded that the estimator of (ABC) is better than the estimator of the maximum likelihood method and method of mo