The study aims to build a proposed training program for school leaders in the Sultanate of Oman on the planning practices of the Kaufman model in light of the needs and challenges of reality. It also aims to identify the challenges facing school leaders in practicing the stages of strategic planning. To achieve these objectives, the study adopted the descriptive approach due to its suitability to the nature of the study. A questionnaire was used to collect the needed data. The study sample included (225) individuals from school principals, their assistants and senior teachers in post-basic education in the Sultanate of Oman. After processing the data statistically, the study concluded that the reality of planning practices for school lea

Virtual reality, VR, offers many benefits to technical education, including the delivery of information through multiple active channels, the addressing of different learning styles, and experiential-based learning. This paper presents work performed by the authors to apply VR to engineering education, in three broad project areas: virtual robotic learning, virtual mechatronics laboratory, and a virtual manufacturing platform. The first area provides guided exploration of domains otherwise inaccessible, such as the robotic cell components, robotic kinematics and work envelope.  The second promotes mechatronics learning and guidance for new mechatronics engineers when dealing with robots in a safe and interactive manner. And the thir

Background Bloodstream infection (BSI) is a life-threatening condition caused by the presence of microorganisms, generally caused by a range of bacteria in the blood. Objectives The aim of this study was to evaluate the possible role of procalcitonin (PCT) and C-reactive protein (CRP) as biomarkers of pediatric BSI. Methodology The study was conducted on 150 blood samples collected from the patient who admitted to Children Welfare Teaching Hospital, Medical City, Baghdad. During the period from November 2020 to March 2021, ninety blood samples from them were positive culture and 60 blood samples were negative culture (control group). The isolates were identified depending on the morphological, microscopic examination, and biochemical tests.

The present research had dealt with preparing  bars  with the length of about  (13 cm) and  adiametar  of  (1.5 cm) of composite materials with metal  matrix  represented by (Al-Cu-Mg) alloy cast enforced by (ZrO₂) particles with chosen weight  percentages (1.5, 2.5 ,3.5, 5.5 %). The base  cast and the composite  materials were prepared by casting method by uses vortex  Technique inorder to  fix up (ZrO₂) particles in homogeneous way on  the  base cast. In addition to  that, two main groups of composite materials were prepared depending on the particles size of (ZrO₂) , respectively.       &n

In this paper, we derive and prove the stability bounds of the momentum coefficient µ and the learning rate ? of the back propagation updating rule in Artificial Neural Networks .The theoretical upper bound of learning rate ? is derived and its practical approximation is obtained

Artificial Intelligence Algorithms have been used in recent years in many scientific fields. We suggest employing flower pollination algorithm in the environmental field to find the best estimate of the semi-parametric regression function with measurement errors in the explanatory variables and the dependent variable, where measurement errors appear frequently in fields such as chemistry, biological sciences, medicine, and epidemiological studies, rather than an exact measurement. We estimate the regression function of the semi-parametric model by estimating the parametric model and estimating the non-parametric model, the parametric model is estimated by using an instrumental variables method (Wald method, Bartlett’s method, and Durbin

The Electric Discharge (EDM) method is a novel thermoelectric manufacturing technique in which materials are removed by a controlled spark erosion process between two electrodes immersed in a dielectric medium. Because of the difficulties of EDM, determining the optimum cutting parameters to improve cutting performance is extremely tough. As a result, optimizing operating parameters is a critical processing step, particularly for non-traditional machining process like EDM. Adequate selection of processing parameters for the EDM process does not provide ideal conditions, due to the unpredictable processing time required for a given function. Models of Multiple Regression and Genetic Algorithm are considered as effective methods for determ