Designing and Standardizing two tests for motor coordination timing for youth basketball players Research submitted by Prof. Faris sami & asst. prof. Wasan hanoon ali & asst. prof. Feras muttasher Baghdad University-College Of Physical Education and Sport Sciences Motor coordination in basketball is considered one of the most important factors for success in skill performance accuracy and speed due to the defensive and offensive situations of the game. The problem of the research lies in the lack of tests that can specify the growth of motor coordination through which the relative change for a number of players can be noticed due to practice and training. The subjects of the research were (30) young league players of National Center for gifted in sports 2015-2016 U16. They were selected deliberately because it came first in the national league. A data base was founded for 100 players to come up with the results that were treated statistically. The researchers concluded designing and standardizing two tests for motor coordination procedures for young players under 16, motor coordination tests were applied for the first time in Iraq for youth basketball players, and specifying reference norms for motor coordination tests.
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 paper, a fixed point theorem of nonexpansive mapping is established to study the existence and sufficient conditions for the controllability of nonlinear fractional control systems in reflexive Banach spaces. The result so obtained have been modified and developed in arbitrary space having Opial’s condition by using fixed point theorem deals with nonexpansive mapping defined on a set has normal structure. An application is provided to show the effectiveness of the obtained result.
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Lean Six Sigma methodologies and Ergonomics principles are the main pillars of this work given their importance in the implementation of continuous improvement in assembly workstations design. When looking at the introduction of the Ergonomics that has been affected by the integration of the Lean and Six Sigma for improvements, it is necessary to understand why these methodologies belong to each other and how they can be handled in the industrial field. The aim of the work seeks towards the impact of analyzing the integration of the basics tools of Lean and Six Sigma that enhanced Ergonomics highlighted the importance of using the priority matrix in the selection of the priority criteria. Two models of a system based on
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The most hazardous class of pharmaceuticals for soil and aquatic ecosystems are antibiotics, which include prescription medications and cancer treatments. Hospital effluents are usually produced by all parts of medical facilities, including hospitals. This study's specific goal was to provide a quick, affordable, and accurate analytical technique for determining the levels of amoxicillin, azithromycin, and penicillin in wastewater from Medical City, Al-Mahmudiya, and Al-Yarmouk hospitals (Iraq, Baghdad). An HPLC with a receptive ODS C18 column was used. It was equipped with UV and pulsed amperometric detectors with wavelengths of 230 nm and 210-240 nm, respectively. The correlation coefficients for each drug are greater than 0.9999,
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Feature selection (FS) constitutes a series of processes used to decide which relevant features/attributes to include and which irrelevant features to exclude for predictive modeling. It is a crucial task that aids machine learning classifiers in reducing error rates, computation time, overfitting, and improving classification accuracy. It has demonstrated its efficacy in myriads of domains, ranging from its use for text classification (TC), text mining, and image recognition. While there are many traditional FS methods, recent research efforts have been devoted to applying metaheuristic algorithms as FS techniques for the TC task. However, there are few literature reviews concerning TC. Therefore, a comprehensive overview was systematicall
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Microbial fuel cell is a device that uses the microorganism metabolism for the production of electricity under specific operating conditions. Double chamber microbial fuel cell was tested for the use of two cheap electrode materials copper and aluminum for the production of electricity under different operating conditions. The investigated conditions were concentration of microorganism (yeast) (0.5- 2 g/l), solutions temperature (33-45 oC) and concentration of glucose as a substrate (1.5- 6 g/l). The results demonstrated that copper electrode exhibit good performance while the performance of aluminum is poor. The electricity is generated with and without the addition of substrate. Addition of glucose substrate
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