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 the last 5 meters from the total approach distance of 30 meters, The ratio of the conversion coefficient of horizontal velocity to vertical velocity, The ratio of the conversion coefficient of horizontal velocity to vertical velocity, The height of the fist is over the full length of the pole's stick) and these are considered independent variables, while the dependent variable was the prediction of achievement (Final height achieved by the jumper) as an output. The neural network architecture was represented by three layers, the first layer is the input layer with the five variables, and one layer is hidden and contains one node, while the last layer is the output layer that represents the outcome of the sport achievement prediction of male weight jumping. The momentum term and learning rate were chosen by 0.95 and 0.4 respectively, and the transfer function in the hidden layer was the sigmoid function and in the last layer was the sigmoid function, the historical data used in this model represent the Olympic achievements of a number of world champions, the results of this study were that the artificial neural network has the ability to prediction of sport achievement for determine the height of the jump of the pole player with a degree of accuracy of 90.10%, correlation coefficient and 95.60%.
If the Industrial Revolution has enabled the replacement of humans with machines, the digital revolution is moving towards replacing our brains with artificial intelligence, so it is necessary to consider how this radical transformation affects the graphic design ecosystem. Hence, the research problem emerged (what are the effects of artificial intelligence on graphic design) and the research aimed to know the capabilities and effects of artificial intelligence applications in graphic design, and the study dealt in its theoretical framework with two main axes, the first is the concept of artificial intelligence, and the second is artificial intelligence applications in graphic design. The descriptive approach adopted a method of content
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In this paper, the human robotic leg which can be represented mathematically by single input-single output (SISO) nonlinear differential model with one degree of freedom, is analyzed and then a simple hybrid neural fuzzy controller is designed to improve the performance of this human robotic leg model. This controller consists from SISO fuzzy proportional derivative (FPD) controller with nine rules summing with single node neural integral derivative (NID) controller with nonlinear function. The Matlab simulation results for nonlinear robotic leg model with the suggested controller showed that the efficiency of this controller when compared with the results of the leg model that is controlled by PI+2D, PD+NID, and F
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This research tests the relationship linkage and effect between the Employees Empowerment Strategy and Organizational Innovation, The research problem is how to understand the Employees Empowerment Strategy role in the achievement Organizational Innovation in Diyala Public Company For Electrical Industrial. A questionnaire was used in data collection depending on the distribution of (32) forms to the research sample. Data were analyzed Using (SPSS)program. Using a number of statistical tools for tests the research hypothesis. The research found set of conclusions, one of the most important thinks was, that there is a linkage and impact relation between Employees Empowerment Strategy, its variables, and Organizational Innovation a
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Precise forecasting of pore pressures is crucial for efficiently planning and drilling oil and gas wells. It reduces expenses and saves time while preventing drilling complications. Since direct measurement of pore pressure in wellbores is costly and time-intensive, the ability to estimate it using empirical or machine learning models is beneficial. The present study aims to predict pore pressure using artificial neural network. The building and testing of artificial neural network are based on the data from five oil fields and several formations. The artificial neural network model is built using a measured dataset consisting of 77 data points of Pore pressure obtained from the modular formation dynamics tester. The input variables
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In this study, a traumatic spinal cord injury (TSCI) classification system is proposed using a convolutional neural network (CNN) technique with automatically learned features from electromyography (EMG) signals for a non-human primate (NHP) model. A comparison between the proposed classification system and a classical classification method (k-nearest neighbors, kNN) is also presented. Developing such an NHP model with a suitable assessment tool (i.e., classifier) is a crucial step in detecting the effect of TSCI using EMG, which is expected to be essential in the evaluation of the efficacy of new TSCI treatments. Intramuscular EMG data were collected from an agonist/antagonist tail muscle pair for the pre- and post-spinal cord lesi
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The construction industry plays a crucial role in the countries' economy, especially in the developed country. This point encourages the concerned institution to use new techniques and integrate many techniques and methods to maximize the benefits. The main objective of this research is to evaluate the use of risk management, value management, and building information modeling in the Iraqi construction industry. The evaluation process aims at two objectives. The direct objective was to evaluate the knowledge in risk management (RM), value management (VM), and building information modeling (BIM). The indirect objective was to support the participants with information related to the main items mentioned. The questionnaire
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Economic performance is one of the most important indicators of economic activity and with the performance of the economy progress varied sources of output and increase economic growth rates and per capita national income, and to recover the business environment and increase investment rates and rising effectiveness of the financial and monetary institutions and credit market. Which leads to increased employment rates and reducing unemployment rates and the elimination of many of the social problems and improve the average per capita income as well as improve the level of national income.
The input / output tables is a technique mathematical indicates economic performance
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The issue of measurement of operational efficiency and productivity plays a major role in determining the weakness of the company, especially in relation to the productive processes, and thus starting to address these points and improve their performance. Hence the problem of research on how to determine the constraints in the production process, to identify weaknesses in the company. The research aims to clarify the role of throughput accounting in measuring the operational efficiency of the company in addition to clarify some of the constraints and causes behind them. The study concluded a set of conclusions, the most important of which is the availability of throughput accounting indicators that help in measuring operational efficienc
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