Set dietary program for some of dietary supplements and training for badminton young players, and identifying effect of taking some of the dietary supplementary for badminton young players. The research population :( badminton young players group (Arminian club). For age group (16-18) years the sample is divided in to two experimental groups within each group (6) players, and two for the exploratory experiment which was within the research sample, they were divided in to two groups, the first group take some of the dietary supplements (multivitamin creating) .the set exercises by the researchers in the main part of the training unit and the second group (amino acids, vitamins) and the set exercises by the researcher. The scientific approach

Shatt Al-Hilla branches from the left of Euphrates River, U/S Hindiyah Barrage, Iraq, and extends about 100 km. It branches at the end into Shatt Al-Diwaniya 112 km and Shatt Al-Daghara 64 km. The study aims to evaluate and develop (Hilla-Daghara) rivers system, which is included Shatt Al-Hilla and Shatt Al-Daghara. Fieldwork began from (26 October until December) 2020. M9, S5 devices, and the installed staff gauges were used to measure discharges and water levels, respectively. A one-dimensional model was developed for the study area by HEC-RAS, after calibration and verification by field measurements; the Manning's n of Shatt Al-Daghara is found to be 0.022. Five Scenarios were simulated to study the reach under the cu

In this work, the superconducting CuBa2LaCa2Cu4O11+δ compound was prepared by citrate precursor method and the electrical and structural properties were studied. The electrical resistivity has been measured using four probe test to find the critical temperature Tc(offset) and Tc(onset). It was found that Tc (offset) at zero resistivity has 101 K and Tc (onset) has 116 K. The X-ray diffraction (XRD) analysis exhibited that a prepared compound has a tetragonal structure. The crystal size and microscopic strain due to lattice deformation of CuBa2LaCa2Cu4O11+δ were estimated by four methods, namely Scherer(S), Halder-Wagner(H-W), size-strain plot (SSP) and Williamson-Hall, (W-H) methods. Results of crystal sizes obtained by these meth

A simulated ion/electron optical transport and focusing system has been put forward to
be mounted on high voltage transmission electron microscope for in situ investigations.
The suggested system consists of three axially symmetric electrostatic lenses namely an
einzel lens, an accelerating immersion lens, and a decelerating immersion lens, in addition
to an electrostatic quadrupole doublet lens placed on the image side. The electrodes
profile of these lenses is determined from the proposed axial field distributions. The
optical properties of the whole system have been computed together with the trajectory of
the accelerated charged-particles beam along the optical axis of the system. The computed
dimensions of th

In this work, the design and implementation of a smart energy metering system has been developed. This system consists of two parts: billing center and a set of distributed smart energy meters. The function of smart energy meter is measuring and calculating the cost of consumed energy according to a multi-tariff scheme. This can be effectively solving the problem of stressing the electrical grid and rising consumer awareness. Moreover, smart energy meter decreases technical losses by improving power factor. The function of the billing center is to issue a consumer bill and contributes in locating the irregularities on the electrical grid (non-technical losses). Moreover, it sends the switch off command in case of the consumer bill is not

<span lang="EN-GB">Transmitting the highest capacity throughput over the longest possible distance without any regeneration stage is an important goal of any long-haul optical network system. Accordingly, Polarization-Multiplexed Quadrature Phase-Shift-Keying (PM-QPSK) was introduced lately to achieve high bit-rate with relatively high spectral efficiency. Unfortunately, the required broad bandwidth of PM-QPSK increases the linear and nonlinear impairments in the physical layer of the optical fiber network. Increased attention has been spent to compensate for these impairments in the last years. In this paper, Single Mode Fiber (SMF), single channel, PM-QPSK transceiver was simulated, with a mix of optical and electrical (Digi

      TV medium derives its formal shape from the technological development taking place in all scientific fields, which are creatively fused in the image of the television, which consists mainly of various visual levels and formations. But by the new decade of the second millennium, the television medium and mainly (drama) became looking for that paradigm shift in the aesthetic formal innovative fields and the advanced expressive performative fields that enable it to develop in treating what was impossible to visualize previously. In the meantime, presenting what is new and innovative in the field of unprecedented and even the familiar objective and intellectual treatments. Thus the TV medium has sought for work

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class