The factorial analysis method consider a advanced statistical way concern in different ways like physical education field and the purpose to analyze the results that we want to test it or measure or for knowing the dimensions of some correlations between common variables that formed the phenomenon in less number of factors that effect on explanation , so we must depend use the self consistent that achieved for reaching that basic request. The goal of this search that depending on techntion of self consistent degree guessing for choosing perfect way from different methods for (orthogonal & oblique) kinds in physical education factor studies and we select some of references for ( master & doctoral) and also the scientific magazine and conferences. After receiving results the researchers reaches some conclusions like the techntion of choosing the self consistent important indicator helps for choosing compents style matrix by using one way from five ways for explaining results.
This research dealt with desalting of East Baghdad crude oil using pellets of either anionic, PVC, quartz, PE, PP or
nonionic at different temperature ranging from 30 to 80 °C, pH from 6 to 8, time from 2 to 20 minutes, volume percent
washing water from 5 to 25% and fluid velocity from 0.5 to 0.8 m/s under voltage from 2 to 6 kV and / or using additives
such as alkyl benzene sulphonate or sodium stearate. The optimum conditions and materials were reported to remove
most of water from East Baghdad wet crude oil.
This paper introduces a Certain Subclass of Meromorphic Univalent Positives Coefficients Defined by the q-Difference Operator. Coefficient estimates are investigated and obtained, and the upped bound is calculated.
The present study illustrates observations, record accurate description and discussion about the behavior of twelve tested, simply supported, precast, prestressed, segmental, concrete beams with different segment numbers exposed to high fire temperatures of 300°C, 500°C, and 700°C. The test program included thermal tests by using a furnace manufactured for this purpose to expose to high burning temperature (fire flame) nine beams which were loaded with sustaining dead load throughout the burning process. The beams were divided into three groups depending on the precast segments number. All had an identical total length of 3150mm but each had different segment number (9, 7, and 5 segments), in other words, different segment length
... Show MoreTo assess the total hip replacement patients’ knowledge of home – care regarding pain management, medication therapy, wound care, mobility limitation and complications may occur in the post hip replacement surgery, and to assess relationship between some variables such as, age level of education, sex & marital status with home- care knowledge. A descriptive study was used to assess the hip-replacement patient home-knowledge, a purposive sampling of (60) hip-replaced –patients were selected from Gazy Alhariri Hospital (central of surgical profession ) and Alwasity Hospital ( plastic surgery) , the questionnaire obtains two parts , part one, which included socio-demographical characteristics of the samp
... Show MoreAdhrt all fungal biological control ability Tdhadah less than 2 repel Alaftran Almamradan showed leaky mushroom Biological control is thermally laboratories and different concentrations of 5, 10 and 20% inhibition in the growth of fungus colonies amounted to 3.8 cm and 3.1 and 2.4 respectively in comparison with control 9 cm
The main aim of this paper is studied the punching shear and behavior of reinforced concrete slabs exposed to fires, the possibility of punching shear failure occurred as a result of the fires and their inability to withstand the loads. Simulation by finite element analysis is made to predict the type of failure, distribution temperature through the thickness of the slabs, deformation and punching strength. Nonlinear finite element transient thermal-structural analysis at fire conditions are analyzed by ANSYS package. The validity of the modeling is performed for the mechanical and thermal properties of materials from earlier works from literature to decrea
... Show MoreZinc Oxide (ZnO) is considered as one of the best materials already used as a window layer in solar cells due to its antireflective capability. The ZnO/MgF2 bilayer thin film is more efficient as antireflective coating. In this work, ZnO and ZnO/MgF2 thin films were deposited on glass substrate using pulsed laser deposition and thermal evaporation deposition methods. The optical measurements indicated that ZnO thin layer has an energy gap of (3.02 eV) while ZnO/MgF2 bilayer gives rise to an increase in the energy gap. ZnO/MgF2 bilayer shows a high energy gap (3.77 eV) with low reflectance (1.1-10 %) and refractive index (1.9) leading to high transmittance, this bilayer could be a good candidate optical material to improve the performance
... Show MoreThis research explored the performance of steel fiber concrete-filled stainless-steel tube columns stiffened with embedded carbon steel T-sections with various steel fiber ratios under biaxial bending conditions. A numerical parametric analysis was adopted, using finite element modeling with Abaqus CAE/2021 to evaluate the effects of the fiber ratio (ranging from 0% to 1.5%) on the load-bearing capacity and deflection behavior of columns. In addition, the compressive strength of concrete ranged between 45 and 65 MPa. An increase in the fiber ratio led to a substantial improvement in the ultimate load-bearing capacity (up to 24%), a reduction in deflection (of approximately 49%), and an improvement in column ductility, which were obt
... Show MoreAutism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D
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