The developments and transformations taking place in the era and the growth of knowledge economies and communication technology led this development to compel higher education institutions in Iraq to reconsider their objectives to keep pace with development. And one of the most important tools of development was the application of e-learning standards and its long-term impact on the performance of the educational institution. Performance auditing plays an important role in verifying the extent to which these institutions have implemented their activities and programs that auditing performance by adopting e-learning standards helps the institutions’ management by providing appropriate information on the extent to which they achieve their goals through efficient, effective and economical utilization of the available resources. E-learning standards. Based on the research problem represented in the absence of a program to audit the performance of structural capital in accordance with e-learning standards, which were circulated to all Iraqi universities as a result of the conditions imposed by the Corona pandemic, which obligated all Iraqi universities to apply, which was reflected in the performance of the college, the research sample. The research was built on the hypothesis that (the presence of a program to audit the performance of the structural capital in the college, the research sample, according to the standards of e-learning, is reflected in the performance in universities). Indicators included in e-learning standards.
Diabetes mellitus type II is a disorder of metabolism and complex diseases affected by genetic environmental factors and associated with inflammation. The symptoms of type II diabetes develop gradually, which are associated with increased blood concentration of marker of the endothelial inflammatory factors. The expression of adhesion molecules, including E-selectin, intracellular adhesion molecule-1(ICAM-1) and vascular cell adhesion molecule-1 (VCAM-1) on the surface of vascular endothelial cells to help leukocyte stick to other surrounding tissues. Many researchers have made attempts to determine the significance of particular ABO phenotype for the susceptibility to diseases. Many reports show a strong association with the ABO blood grou
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Die vorliegende Forschung handelt es um die Satzfelder, besonders das Mittelfeld des Satzes im deutschen und Arabischen. Diese Forschung wurde mit der Satzdefinition, Satzglieder begonnen, damit wir diese klar werden und dann werden die Felder des Satzes gut gekannt. Der erste Abschnitt schlieβt auch den Mittelfeld des Satzes und, wie man das Feld erkennen und bestimmen kann. Die Forschung untersucht auch. Ob es in der arabischen Sprache den selben Struktur wie im Deutschen gibt, z.B Bildung des Satzes sowie Satzfelder bezügllich das Mittelfeld.
Der zweite Abschnitt handelt sich um den arabischen Teil und behandelt die Wortarten im Arabischen sowie den Satz als auch Satzarten (Nominal- Verbal- Halbsatz).
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... Show MoreComputational Thinking (CT) is very useful in the process of solving everyday problems for undergraduates. In terms of content, computational thinking involves solving problems, studying data patterns, deconstructing problems using algorithms and procedures, doing simulations, computer modeling, and reasoning about abstract things. However, there is a lack of studies dealing with it and its skills that can be developed and utilized in the field of information and technology used in learning and teaching. The descriptive research method was used, and a test research tool was prepared to measure the level of (CT) consisting of (24) items of the type of multiple-choice to measure the level of "CT". The research study group consists of
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In this paper we investigate the automatic recognition of emotion in text. We propose a new method for emotion recognition based on the PPM (PPM is short for Prediction by Partial Matching) character-based text compression scheme in order to recognize Ekman’s six basic emotions (Anger, Disgust, Fear, Happiness, Sadness, Surprise). Experimental results with three datasets show that the new method is very effective when compared with traditional word-based text classification methods. We have also found that our method works best if the sizes of text in all classes used for training are similar, and that performance significantly improves with increased data.
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In this paper, we investigate the automatic recognition of emotion in text. We perform experiments with a new method of classification based on the PPM character-based text compression scheme. These experiments involve both coarse-grained classification (whether a text is emotional or not) and also fine-grained classification such as recognising Ekman’s six basic emotions (Anger, Disgust, Fear, Happiness, Sadness, Surprise). Experimental results with three datasets show that the new method significantly outperforms the traditional word-based text classification methods. The results show that the PPM compression based classification method is able to distinguish between emotional and nonemotional text with high accuracy, between texts invo
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Here, we found an estimation of best approximation of unbounded functions which satisfied weighted Lipschitz condition with respect to convex polynomial by means of weighted Totik-Ditzian modulus of continuity
The game of basketball (orange ball) is considered one of the fast and exciting games in the world. It is played by both sexes and different ages. It has Olympic and international championships and has various performance skills, including defensive ones. This game requires physical abilities that players must have for duties during matches, including special endurance that is compatible with... The peculiarity of the game is the changing rhythm and positions on the field. The importance of the research lies in the importance of special exercises to develop special endurance and its role in influencing the defensive skill performance of the players throughout the duration of the match.The problem of the research appeared in the decline in i
... Show MoreAbstract: Data mining is become very important at the present time, especially with the increase in the area of information it's became huge, so it was necessary to use data mining to contain them and using them, one of the data mining techniques are association rules here using the Pattern Growth method kind enhancer for the apriori. The pattern growth method depends on fp-tree structure, this paper presents modify of fp-tree algorithm called HFMFFP-Growth by divided dataset and for each part take most frequent item in fp-tree so final nodes for conditional tree less than the original fp-tree. And less memory space and time.
The paper proposes a methodology for predicting packet flow at the data plane in smart SDN based on the intelligent controller of spike neural networks(SNN). This methodology is applied to predict the subsequent step of the packet flow, consequently reducing the overcrowding that might happen. The centralized controller acts as a reactive controller for managing the clustering head process in the Software Defined Network data layer in the proposed model. The simulation results show the capability of Spike Neural Network controller in SDN control layer to improve the (QoS) in the whole network in terms of minimizing the packet loss ratio and increased the buffer utilization ratio.
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<span>Dust is a common cause of health risks and also a cause of climate change, one of the most threatening problems to humans. In the recent decade, climate change in Iraq, typified by increased droughts and deserts, has generated numerous environmental issues. This study forecasts dust in five central Iraqi districts using machine learning and five regression algorithm supervised learning system framework. It was assessed using an Iraqi meteorological organization and seismology (IMOS) dataset. Simulation results show that the gradient boosting regressor (GBR) has a mean square error of 8.345 and a total accuracy ratio of 91.65%. Moreover, the results show that the decision tree (DT), where the mean square error is 8.965, c
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