Precise forecasting of pore pressures is crucial for efficiently planning and drilling oil and gas wells. It reduces expenses and saves time while preventing drilling complications. Since direct measurement of pore pressure in wellbores is costly and time-intensive, the ability to estimate it using empirical or machine learning models is beneficial. The present study aims to predict pore pressure using artificial neural network. The building and testing of artificial neural network are based on the data from five oil fields and several formations. The artificial neural network model is built using a measured dataset consisting of 77 data points of Pore pressure obtained from the modular formation dynamics tester. The input variables

This study aims to clarify areas of using information technology in accounting and its impact on the profession of auditors by reviewing the concept, types, areas and the importance of information technology and its implications on the audit profession as well as to clarify the extent of contribution of information technology in  developing of procedures of the audit profession and what its requirement, also this study aims to enhance the theoretical side by identifying the views of a sample of auditors in  Arab countries selected (Iraq, Syria, Jordan), for the extent of using of information technology in their work and level of their perception for the importance of that

In this study, an analysis of re-using the JPEG lossy algorithm on the quality of satellite imagery is presented. The standard JPEG compression algorithm is adopted and applied using Irfan view program, the rang of JPEG quality that used is 50-100.Depending on the calculated satellite image quality variation, the maximum number of the re-use of the JPEG lossy algorithm adopted in this study is 50 times. The image quality degradation to the JPEG quality factor and the number of re-use of the JPEG algorithm to store the satellite image is analyzed.

This study aims to identify both the importance of using (LinkedIn) and its drawbacks for researchers and specialists in the field of information and knowledge technologies. The study relied mainly on the statistical method (analytical method) from the collection of data tools (questionnaire) that was distributed electronically (Google Forms) to the sample community of (55) instructors. The feedback received illustrates that (46) instructors among those who participated in the questionnaire subscribed to (LinkedIn) and the rest did not. Their data was analyzed statistically, and the general arithmetic mean and the hypothetical mean was extracted for them to achieve the objectives of the study and prove their hypotheses. The site positively