لطالما كان انتظار الملأ للخلاص والتي ترتبط بشكل اساسي بال "منتظر" او ال "مخلص" جزءا من الوعي الجمعي الذي تطور ليكون مرتبطا بالنمط البدائي والذي بدوره أصبح مرآةً تنعكس على اساسها فرص الانسان نحو النجاة. في مسرح القرن العشرين, لم تنفك فكرة الانتظار ان ترتبط بمسرحية صاموئيل بيكيت العبثية " في انتظار غودو" كونها مثالا رمزيا بالرغم من انه تجسيد شخصية "غودو" وقعت تحت وطأة الكثير من عمليات التحوير والتغيير في اطاره

This abstract focuses on the significance of wireless body area networks (WBANs) as a cutting-edge and self-governing technology, which has garnered substantial attention from researchers. The central challenge faced by WBANs revolves around upholding quality of service (QoS) within rapidly evolving sectors like healthcare. The intricate task of managing diverse traffic types with limited resources further compounds this challenge. Particularly in medical WBANs, the prioritization of vital data is crucial to ensure prompt delivery of critical information. Given the stringent requirements of these systems, any data loss or delays are untenable, necessitating the implementation of intelligent algorithms. These algorithms play a pivota

Various theories have been proposed since in last century to predict the first sighting of a new crescent moon. None of them uses the concept of machine and deep learning to process, interpret and simulate patterns hidden in databases. Many of these theories use interpolation and extrapolation techniques to identify sighting regions through such data. In this study, a pattern recognizer artificial neural network was trained to distinguish between visibility regions. Essential parameters of crescent moon sighting were collected from moon sight datasets and used to build an intelligent system of pattern recognition to predict the crescent sight conditions. The proposed ANN learned the datasets with an accuracy of more than 72% in comp