Abstract

Objective(s): To evaluate blended learning in nursing education at the Middle Region in Iraq.

Methodology: A descriptive study, using evaluation approach, is conducted to evaluate blended learning in nursing education in Middle Region in Iraq from September 26^th, 2021 to March 22^nd, 2022. The study is carried out at two Colleges of Nursing at the University of Baghdad and University of Tikrit in Iraq. A convenient, non-probability, sample of (60) undergraduate nursing students is selected. The sample is comprised of (30) student from each college of nursing, Self-report questionnaire is constructed from the literature, for e

According to the measuring the relationship between organizational loyalty and job satisfaction among staff members at one college in the higher education ministry in Iraq by using exploratory factor analysis methods to extraction the components which have the major effects on the variables related to organizational loyalty and job satisfaction .

The research contains four basic topics، the first section related to methodology and regarding the conceptual framework it is discussed in the second section، and the third section concentrated at the presentation and the analysis Scientific results and practical results are section presented in the fourth.

The aim of this study is to highlight the relationship between competitive intelligence and Entrepreneurial Performance by centralizing the strategic vigilance of a sample of civil faculties in Baghdad. The sample of the study was targeted at 10 Iraqi civil colleges, which consisted of (133) members of the faculty council of the faculties, the search data was collected using the questionnaire form as the main research tool. The results showed that the correlation and influence of competitive intelligence and strategic vigilance in the Entrepreneurial Performance, as well as the role of strategic vigilance as an intermediate variable between competitive intelligence and Entrepreneurial Performance.

It is shown that pure and 3% boron doped a-Si0.1Ge0.9:H and a-Si0.1Ge0.9:N thin films
could be prepared by flash evaporation processes. The hydrogenation and nitrogenation
are very successful in situ after depositing the films. The FT-IR analysis gave all the
known absorbing bonds of hydrogen and nitrogen with Si and Ge.
Our data showed a considerable effect of annealing temperature on the structural and
optical properties of the prepared films. The optical energy gap (Eopt.) of a-Si0.1Ge0.9
samples showed to have significant increase with annealing temperature (Ta) also the
refractive index and the real part of dielectric constant increases with Ta, however the
extinction coefficient and imaginary part of dielect

Smart cities have recently undergone a fundamental evolution that has greatly increased their potentials. In reality, recent advances in the Internet of Things (IoT) have created new opportunities by solving a number of critical issues that are allowing innovations for smart cities as well as the creation and computerization of cutting-edge services and applications for the many city partners. In order to further the development of smart cities toward compelling sharing and connection, this study will explore the information innovation in smart cities in light of the Internet of Things (IoT) and cloud computing (CC). IoT data is first collected in the context of smart cities. The data that is gathered is uniform. The Internet of Things,

The aim of the research is to diagnose and analyze the gap between the actual reality and the application of the eighth requirement (operation) in the National Insurance Company in accordance with the international standard specification for the quality management system (ISO 9001:2015), which is related to the planning, implementation and control of operations, which would raise the level of performance of employees and be reflected in the provision of An appropriate service for the faithful, as the reality of the condition of the requirement was studied by identifying the strengths and weaknesses of the system to diagnose the gap and find ways to address it. A workshop was held with company officials, through which questions were raise

The present work involves studying the effect of electrolyte composition [@1= 0.5 wt.%  NH₄F / 5% H₂O / 5% Glycerol (GLY)/ 90%  Ethylene Glycol (EG)] and [ @2= 0.5 wt. % NH₄F / 5% H₂O / 95%  Ethylene Glycol (EG)]  on the structural and photoelectrochemical properties of titania nanotubes arrays (TNTAs). TNTAs substrates were successfully carried out via anodization technique and were carried out in 40 V for one hour in different electrolytes (@1, and @2). The properties of physicochemical of TNTAs were distinguished via an X-ray Diffractometer (XRD), Field Emission Scanning Electron Microscope (FESEM), an Energy Dispersive X-ray (EDX), and UV–visible diffuse reflectance. T

Skull image separation is one of the initial procedures used to detect brain abnormalities. In an MRI image of the brain, this process involves distinguishing the tissue that makes up the brain from the tissue that does not make up the brain. Even for experienced radiologists, separating the brain from the skull is a difficult task, and the accuracy of the results can vary quite a little from one individual to the next. Therefore, skull stripping in brain magnetic resonance volume has become increasingly popular due to the requirement for a dependable, accurate, and thorough method for processing brain datasets. Furthermore, skull stripping must be performed accurately for neuroimaging diagnostic systems since neither non-brain tissues nor

Skull image separation is one of the initial procedures used to detect brain abnormalities. In an MRI image of the brain, this process involves distinguishing the tissue that makes up the brain from the tissue that does not make up the brain. Even for experienced radiologists, separating the brain from the skull is a difficult task, and the accuracy of the results can vary quite a little from one individual to the next. Therefore, skull stripping in brain magnetic resonance volume has become increasingly popular due to the requirement for a dependable, accurate, and thorough method for processing brain datasets. Furthermore, skull stripping must be performed accurately for neuroimaging diagnostic systems since neither no