Relying on modern work strategies, such as adopting scientific inductions, consolidates the information in the learner’s memory, develops the skill work of the football player, and raises the efficiency of their motor abilities. From this standpoint, the researcher, who is a teacher at the University of Baghdad, College of Physical Education and Sports Sciences, and follows most of the sports club teams in youth football, believes that there must be From extrapolations through the machine and employing it in the field to serve the skill aspect and benefit from scientific technology in development and making it a useful tool to serve the sports field in football, as the goal of the research was the efficiency of machine extrapolation in developing the dialogue and its accuracy in football for juniors, and the researcher assumed the existence of a statistically significant correlation between the extrapolation relationship The machine and its efficiency in developing the skill and accuracy of dribbling in football for juniors. The research sample was players from the Husseiniya Youth and Sports Forum, the Algeria Youth and Sports Forum, and the Challenge Youth and Sports Forum. The approach was experimental in application, adopting statistical methods of percentages, the Pearson correlation coefficient, and the arithmetic mean. And the standard deviation to arrive at the results. The results were presented and discussed, and the most important conclusions were reached. There is a significant correlation between machine extrapolation and its efficiency in developing dribbling and accuracy in youth football, and it is recommended to adopt machine extrapolation and its ability and efficiency in developing the technical skills of dribbling in youth football, which enhances accuracy in Perform that skill.
Software-defined networks (SDN) have a centralized control architecture that makes them a tempting target for cyber attackers. One of the major threats is distributed denial of service (DDoS) attacks. It aims to exhaust network resources to make its services unavailable to legitimate users. DDoS attack detection based on machine learning algorithms is considered one of the most used techniques in SDN security. In this paper, four machine learning techniques (Random Forest, K-nearest neighbors, Naive Bayes, and Logistic Regression) have been tested to detect DDoS attacks. Also, a mitigation technique has been used to eliminate the attack effect on SDN. RF and KNN were selected because of their high accuracy results. Three types of ne
... Show MoreThe aim of the current research is to develop the social studies curriculum at the primary stage in light of the standards of the next generation, which was represented in three main dimensions (pivotal ideas, scientific practices, and comprehensive concepts). The researcher designed a tool for the study, which is a content analysis card in the light of (NGSS) standards, based on the previous main dimensions. The descriptive analytical approach was adopted in analyzing the social studies curriculum for the primary stage to determine the degree to which the standards of the next generation are available, as well as to establish the theoretical framework related to the research variables. To develop the social studies curriculum in light o
... Show MoreMost of the propositions, after the Arabic letter reached a position of integrity and proficiency, the calligrapher turned to the production of calligraphic formations in various aesthetic and expressive forms, investing the spiritual energies in what these calligraphic compositions show in artistic paintings. It carries a lot of meanings that are embodied in linear formations, and in order to reach these expressions and know the effective positions of space, this research is concerned with studying these technical treatments. The first chapter included the research problem, which included a question about the effectiveness of space in the linear painting, the importance of research and the temporal and spatial boundaries. As for the s
... Show MoreThe new ligand [3,3’-(1,2-phenylenebis(azanediyl))bis(5,5-dimethylcyclohex-2-en-1-one)] (L) derived from 5,5-Dimethylcyclohexane-1,3-dione with 1,2-phenylenediamine was used to prepare a new chain of metal complexes of Mn(ii), Co(ii), Ni(ii), Cu(ii), Cd(ii) and Zn(ii) by inclusive formula [M(L)]Cl2. Characterized compounds on the basis of 1H, 13CNMR (for ligand (L)), FT-IR and U.V spectrum, melting point, molar conduct, %C, %H and %N, the percentage of the metal in complexes %M, Magnetic susceptibility, thermal studies (TGA), while its corrosion inhibition for (plain steel) in tap water is studied by weight loss. These measurements proved th
In this research entitled "Internal music in the poetry of guidance in the era of Islam and its artistic and semantic implications" dealt with the following:
Preface, which addressed the importance of internal music in poetry, and its close association with poetry, and the poet himself, to reveal what is touring himself and revolves in his imagination.
Repetition of all kinds: repetition of letters, repetition of words, and repetition of phrases: It showed what this repetition of strengthening the melody, and linking parts of words within the same house, or the poem, and create a special musical atmosphere to spread a certain significance and to confirm the meanings and accompanied by musical accommodation.
Anaphysic
In recent years, the world witnessed a rapid growth in attacks on the internet which resulted in deficiencies in networks performances. The growth was in both quantity and versatility of the attacks. To cope with this, new detection techniques are required especially the ones that use Artificial Intelligence techniques such as machine learning based intrusion detection and prevention systems. Many machine learning models are used to deal with intrusion detection and each has its own pros and cons and this is where this paper falls in, performance analysis of different Machine Learning Models for Intrusion Detection Systems based on supervised machine learning algorithms. Using Python Scikit-Learn library KNN, Support Ve
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