Abstract
The use of electronic valves is commonly available. yet, the most
common is the techniques of communications as prod casting transmitter that
are used by these valves in addition to their use in communication tools as far
distance telephone, electronic measuring techniques , and others.
In this study, an attempt is endeavored for improving the efficiency of the
vacuum micro- valves(GI-19b) through activating their internal surfaces by the
use of ionic pumping which is used for treating valves which are out of order
(because of sedimentation some materials and oxide on its poles). The
existence of these materials and oxide increase the sum of current leakage
moving in between. The use of ionic pumping method leads to direct high
voltage on the poles since the sum of the current can be largely decreased.
Besides, they are other methods for fixing valves up these valves.
The practical result of measuring current leakage of the prepared valves
proves there is improving of the measured valves; it is noticed that these
valves are far less than these before treatment. This gives a clue of the
positive effect of this method for fixing valves up.
The integration of arti cial intelligence (AI), whether through devices or software, has become a critical tool in analyzing and evaluating technical performance. AI signi cantly contributes to enhancing athletic performance by enabling accurate data analysis and supporting educators in developing effective training programs and interactive curricula. This study addresses a noticeable gap in the literature regarding the attitudes and inclinations of educators toward AI in physical education and sport sciences—a gap often attributed to limited awareness and lack of access to moderntechnologies.Theprimaryaimofthestudyistoexaminethetendenciesandperceptionsoffemaleinstructorsin physical education and sport sciences toward the use of AI
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The logistic regression model is one of the nonlinear models that aims at obtaining highly efficient capabilities, It also the researcher an idea of the effect of the explanatory variable on the binary response variable. &nb
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