Among the many modern skill-enhancing work practices, machine learning is among the mostskill-enhancing practices in the workplace, as it helps students remember more of what they havelearned, hone the technical talents and skills of football players, and make better use of theirmotor skills. The use of machine learning and its practical applications in football could havesignificant benefits by improving talent development and making better use of scientifictechniques. The primary objective of this study was to determine the effectiveness of machinelearning in improving soccer dribbling and passing accuracy in children aged 10-12 years. Thestudy authors hypothesized that soccer players in the Al-Zohour Neighborhood Youth Forumwould greatly benefit from machine learning's ability to improve their dribbling and passingaccuracy. The study used an experimental approach and statistical methods includingpercentages, arithmetic mean, standard deviation, and Pearson's correlation coefficient to reach conclusions.
In present study 74 specimens of urine were collected from patients suffering from urinary tract infections.Fifty (67.56%) isolates were identified as Escherichia coli. 78% of isolates were identified as extendedspectrum beta lactamases (ESBL) producer. Antibiotic susceptibility t est was done and ceftazidime wasselected to complete this study by implying stress at sub-MIC on isolate harbor high number of resistancegenes (N11) and compared with sensitive isolate (S). Only four β-lactamase coding genes were detected;blaTEM, blaPER, blaVIM and blaCTX-M-2 and N11 had blaTEM, blaPER, and blaVIM. It was found that the resistantisolate did not form biofilm when compared with the sensitive one, which formed moderate biofilm. Inaddition, ceftazidi
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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
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The aim of this work was to develop and validate a rapid and low cost method for estimation of ibuprofen in pharmaceutical suspensions using Reverse-Phase High Performance Liquid Chromatography. The proposed method was conducted and validated according to International Conference on Harmonization (ICH) requirements. The chromatographic parameters were as follows: column of octyldecylsilyl C18 with dimensions (150 × 4.6) mm, mobile phase composed of acetonitrile with phosphoric acid with a ratio of 50 to 50 each using isocratic mode, flow rate of 1.5 mL/min and injection volume of 5 μL. The detection was carried out using UV detector at 220 nm. The method was validated and showed short retention time for ibuprofen peak at 7.651 min, wit
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MH Hamzah, AF Abbas, International Journal of Early Childhood Special Education, 2022
In this research the results of applying Artificial Neural Networks with modified activation function to
perform the online and offline identification of four Degrees of Freedom (4-DOF) Selective Compliance
Assembly Robot Arm (SCARA) manipulator robot will be described. The proposed model of
identification strategy consists of a feed-forward neural network with a modified activation function that
operates in parallel with the SCARA robot model. Feed-Forward Neural Networks (FFNN) which have
been trained online and offline have been used, without requiring any previous knowledge about the
system to be identified. The activation function that is used in the hidden layer in FFNN is a modified
version of the wavelet func
In this research the results of applying Artificial Neural Networks with modified activation function to perform the online and offline identification of four Degrees of Freedom (4-DOF) Selective Compliance Assembly Robot Arm (SCARA) manipulator robot will be described. The proposed model of identification strategy consists of a feed-forward neural network with a modified activation function that operates in parallel with the SCARA robot model. Feed-Forward Neural Networks (FFNN) which have been trained online and offline have been used, without requiring any previous knowledge about the system to be identified. The activation function that is used in the hidden layer in FFNN is a modified version of the wavelet function. This approach ha
... Show MoreTwo nanocomposite corrosion inhibitors were synthesized from Aloe vera extract: one incorporating sodium thiosulfate and the other silver nitrate. Both nanocomposites were subjected to structural characterization using atomic force microscopy (AFM), which revealed distinct morphological features. The sodium thiosulfate-based nanocomposite exhibited uniform and well-dispersed nanoparticles with an average size of 47.51 nm, suggesting a stable and homogeneous distribution. In contrast, the silver nitrate-based nanocomposite displayed slightly larger particles with an average diameter of 58.34 nm, indicating a tendency toward moderate aggregation. The corrosion inhibition performance of these nanocomposites for carbon steel (CS1137) was invest
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This research aims to introduce the general tax on sales in gordan and the most important concepts related to this type of taxes and identify the most on characteristics and stand on its role in supplying the general budget of the necessary fundig to cover the over head of the state and the factorsinfluencing it and whether such a tax has been able to chieve the desired goals.including in contribute to an important and growing role in puplic revenues or not to be able to achieve these goals through the use of descriptive and analytical technique based on the data and information relevant.wasreached some conclusion and recommendations was most important is that the general sales tax comes in
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Two nanocomposite corrosion inhibitors were synthesized from Aloe vera extract: one incorporating sodium thiosulfate and the other silver nitrate. Both nanocomposites were subjected to structural characterization using atomic force microscopy (AFM), which revealed distinct morphological features. The sodium thiosulfate-based nanocomposite exhibited uniform and well-dispersed nanoparticles with an average size of 47.51 nm, suggesting a stable and homogeneous distribution. In contrast, the silver nitrate-based nanocomposite displayed slightly larger particles with an average diameter of 58.34 nm, indicating a tendency toward moderate aggregation. The corrosion inhibition performance of these nanocomposites for carbon steel (CS1137) was invest
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