Prediction of penetration rate (ROP) is important process in optimization of drilling due to its crucial role in lowering drilling operation costs. This process has complex nature due to too many interrelated factors that affected the rate of penetration, which make difficult predicting process. This paper shows a new technique of rate of penetration prediction by using artificial neural network technique. A three layers model composed of two hidden layers and output layer has built by using drilling parameters data extracted from mud logging and wire line log for Alhalfaya oil field. These drilling parameters includes mechanical (WOB, RPM), hydraulic (HIS), and travel transit time (DT). Five data set represented five formations gathered

Background: The repair of bone defects remains a major clinical orthopaedic challenge. Bone is a highly vascularised tissue reliant on the close spatial and temporal connection between blood vessels and bone cells to maintain skeletal integrity. This study aimed to study the efficacy of Panax ginseng as a osteoinducer in tibia of rat and as a stimulator for bone healing and to study the immunohistochemical expression of osteonectin as bone formation markers in experimental and control groups during bone healing. Material and method: : In this study thirty albino male rats , weighting (200-300) gram ,aged (2-3) months ,will be used under control conditions of temperature ,drinking and food consumption. The animals will subject for an