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

تقدم هذه الدراسة وصفا للطريقة المستخدمة في تحضير الكربون المنشط  (AC)من بقايا الشاي. تم دراسة الخواص الفيزيائية والكيميائية وكفاءة الامتزاز للكربون المنشط المحضر. تم إنتاج الكربون المنشط (AC) على مرحلتين: الاولى التنشيط باستخدام حامض الفوسفوريك (H3PO4) والثانية الكربنة عند درجة حرارة 450 درجة مئوية. استخدم الكربون المنشط لغرض امتصاص العقار الدوائي السيبروفلوكساسين(CIP) . تمت  دراسة عدة عوامل تشغيلية  بدرجة حرار

تقدم هذه الدراسة وصفا للطريقة المستخدمة في تحضير الكربون المنشط  (AC)من بقايا الشاي. تم دراسة الخواص الفيزيائية والكيميائية وكفاءة الامتزاز للكربون المنشط المحضر. تم إنتاج الكربون المنشط (AC) على مرحلتين: الاولى التنشيط باستخدام حامض الفوسفوريك (H3PO4) والثانية الكربنة عند درجة حرارة 450 درجة مئوية. استخدم الكربون المنشط لغرض امتصاص العقار الدوائي السيبروفلوكساسين(CIP) . تمت  دراسة عدة عوامل تشغيلية  بدرجة حرار

This research describes a new model inspired by Mobilenetv2 that was trained on a very diverse dataset. The goal is to enable fire detection in open areas to replace physical sensor-based fire detectors and reduce false alarms of fires, to achieve the lowest losses in open areas via deep learning. A diverse fire dataset was created that combines images and videos from several sources. In addition, another self-made data set was taken from the farms of the holy shrine of Al-Hussainiya in the city of Karbala. After that, the model was trained with the collected dataset. The test accuracy of the fire dataset that was trained with the new model reached 98.87%.

The unstable and uncertain nature of natural rubber prices makes them highly volatile and prone to outliers, which can have a significant impact on both modeling and forecasting. To tackle this issue, the author recommends a hybrid model that combines the autoregressive (AR) and Generalized Autoregressive Conditional Heteroscedasticity (GARCH) models. The model utilizes the Huber weighting function to ensure the forecast value of rubber prices remains sustainable even in the presence of outliers. The study aims to develop a sustainable model and forecast daily prices for a 12-day period by analyzing 2683 daily price data from Standard Malaysian Rubber Grade 20 (SMR 20) in Malaysia. The analysis incorporates two dispersion measurements (I

      The Costing Accounting is one the analytic tools which plays important role by support the management in planning&  control and decisions-making ,as it became attendant necessity to establish any project whether industrial ,commercial ,service or agriculture ..etc.

     The consolidated accounting system has committed the companies to have their active costing system in which the management can obtain their own data, but we found most of the economic units face problems of applying the costing system because of reasons related to the system design itself or might be related to the requirements of the application success.