The research included five sections containing the first section on the introduction o research and its importance and was addressed to the importance of the game of gymnastic and skilled parallel bars effectiveness and the importance of biochemical variables, either the research problem that there is a difference in learning this skill and difficulty in learning may be one of the most important reasons are falling and injury Has a negative impact on the performance and lack of sense of movement of is one of the obstacles in the completion of the skill and the goal of research to design a device that helps in the development of biochemical changes to skill of rear vault dismount with one-half twist on parallel bars in gymnastics . And the n

The physical sports sector in Iraq suffers from the problem of achieving sports achievements in individual and team games in various Asian and international competitions, for many reasons, including the lack of exploitation of modern, accurate and flexible technologies and means, especially in the field of information technology, especially the technology of artificial neural networks. The main goal of this study is to build an intelligent mathematical model to predict sport achievement in pole vaulting for men, the methodology of the research included the use of five variables as inputs to the neural network, which are Avarage of Speed (m/sec in Before distance 05 meters latest and Distance 05 meters latest, The maximum speed achieved in t

Wireless Body Area Sensor Networks (WBASNs) have garnered significant attention due to the implementation of self-automaton and modern technologies. Within the healthcare WBASN, certain sensed data hold greater significance than others in light of their critical aspect. Such vital data must be given within a specified time frame. Data loss and delay could not be tolerated in such types of systems. Intelligent algorithms are distinguished by their superior ability to interact with various data systems. Machine learning methods can analyze the gathered data and uncover previously unknown patterns and information. These approaches can also diagnose and notify critical conditions in patients under monitoring. This study implements two s

The method of predicting the electricity load of a home using deep learning techniques is called intelligent home load prediction based on deep convolutional neural networks. This method uses convolutional neural networks to analyze data from various sources such as weather, time of day, and other factors to accurately predict the electricity load of a home. The purpose of this method is to help optimize energy usage and reduce energy costs. The article proposes a deep learning-based approach for nonpermanent residential electrical ener-gy load forecasting that employs temporal convolutional networks (TCN) to model historic load collection with timeseries traits and to study notably dynamic patterns of variants amongst attribute par

To ensure fault tolerance and distributed management, distributed protocols are employed as one of the major architectural concepts underlying the Internet. However, inefficiency, instability and fragility could be potentially overcome with the help of the novel networking architecture called software-defined networking (SDN). The main property of this architecture is the separation of the control and data planes. To reduce congestion and thus improve latency and throughput, there must be homogeneous distribution of the traffic load over the different network paths. This paper presents a smart flow steering agent (SFSA) for data flow routing based on current network conditions. To enhance throughput and minimize latency, the SFSA distrib

Finding communities of connected individuals in complex networks is challenging, yet crucial for understanding different real-world societies and their interactions. Recently attention has turned to discover the dynamics of such communities. However, detecting accurate community structures that evolve over time adds additional challenges. Almost all the state-of-the-art algorithms are designed based on seemingly the same principle while treating the problem as a coupled optimization model to simultaneously identify community structures and their evolution over time. Unlike all these studies, the current work aims to individually consider this three measures, i.e. intra-community score, inter-community score, and evolution of community over

Nominal ellipsis is a linguistic phenomenon found in English and Arabic .It is
based on leaving out a part of a nominal construction or more for the sake of good
style , compactness and connectedness .This phenomenon is found in the language of
the Glorious Qur’an .The study in hand is concerned with how translators handle
translating Qur’anic verses which contain ellipted nouns , i ,e. , to what extent the
translated Qur’anic verses are close to the original ones , and to what extent their
translations serve understanding the meanings of the glorious verses while at the
same time maintaining their beauty in style. The study aims at shedding light on
nominal ellipsis in English and Arabic .The study undertak

The present paper is devoted to studying the imitation of some Quran phrases and words in the tale of "The Leprous Girl". The paper aims at identifying the common ground between the tale and some great stories related in the verses of the holy Quran, and comparing the original work with the present translation. First, we translated the tale from Russian into Arabic so as to be tackled in study, and then an identification of the commonalities between this tale and the Quran wording is made. It was found that texting is clear in the original text of the tale, hence the need for this paper. By studying the texts and phrases employed by the writer, we observe that the text is influenced by the Quranic stories whose effects have been reflecte