This paper deals with social responsibility visible to the media and the role they play in spreading the culture of environmental protection, and make research on a sample of the University of Baghdad consisting students from 150 students, male and female were distributed questionnaire form on the sample to obtain the required information has been questionnaire included axes distributed questions achieve the objectives of the search, and after the form data were analyzed using statistical program spss results show that the visual media and its role in spreading the culture of environmental protection form averages arithmetic high, indicating a rise in the influence of th

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        Artificial Neural networks (ANN) are powerful and effective tools in time-series applications. The first aim of this paper is to diagnose better and more efficient ANN models (Back Propagation, Radial Basis Function Neural networks (RBF), and Recurrent neural networks) in solving the linear and nonlinear time-series behavior. The second aim is dealing with finding accurate estimators as the convergence sometimes is stack in the local minima. It is one of the problems that can bias the test of the robustness of the ANN in time series forecasting. To determine the best or the optimal ANN models, forecast Skill (SS) employed to measure the efficiency of the performance of ANN models. The mean square error and

The Artificial Neural Network methodology is a very important & new subjects that build's the models for Analyzing, Data Evaluation, Forecasting & Controlling without depending on an old model or classic statistic method that describe the behavior of statistic phenomenon, the methodology works by simulating the data to reach a robust optimum model that represent the statistic phenomenon & we can use the model in any time & states, we used the Box-Jenkins (ARMAX) approach for comparing, in this paper depends on the received power to build a robust model for forecasting, analyzing & controlling in the sod power, the received power come from

Machine learning models have recently provided great promise in diagnosis of several ophthalmic disorders, including keratoconus (KCN). Keratoconus, a noninflammatory ectatic corneal disorder characterized by progressive cornea thinning, is challenging to detect as signs may be subtle. Several machine learning models have been proposed to detect KCN, however most of the models are supervised and thus require large well-annotated data. This paper proposes a new unsupervised model to detect KCN, based on adapted flower pollination algorithm (FPA) and the k-means algorithm. We will evaluate the proposed models using corneal data collected from 5430 eyes at different stages of KCN severity (1520 healthy, 331 KCN1, 1319 KCN2, 1699 KCN3 a

The current research aims to identify the level of mental alertness among students of the Department of Chemistry in the Faculty of Education for Pure Sciences – Ibn Al-Haytham during the academic year (2022-2023). To achieve this goal, a descriptive approach was followed. The research community was identified as all chemistry students across the four grades (first, second, third, and fourth). A sample from each grade was selected for the current research. A tool was prepared to measure mental alertness within the research sample. The researcher adopted the scale by Baer, Smith, Kristemoyer, & Tany (2006), which was developed by Al-Buhairi et al. (2014), ensuring its validity, reliability, and psychometric characteristics, making i

Background: Ruptured posterior communicating artery (PCoA) aneurysms are common; they usually present with subarachnoid haemorrhage (SAH) and oculomotor nerve palsy. The aneurysmal dome projection may influence the safety access and aneurysmal neck clipping. Here, we discuss additional intraoperative steps that may be required to widen the surgical field to ensure safe surgical clipping of a rupture pure posteriorly directed PCoA aneurysm. Case description: A previously healthy 38-year-old male reported sudden severe headache and disturbed level of consciousness with a Glasgow coma scale (GCS) of 13. His initial computed tomography (CT) scan of the head showed SAH in the basal cistern. 3D-constructed CT angiography (CTA) revealed a