As the reservoir conditions are in continuous changing during its life, well production rateand its performance will change and it needs to re-model according to the current situationsand to keep the production rate as high as possible.Well productivity is affected by changing in reservoir pressure, water cut, tubing size andwellhead pressure. For electrical submersible pump (ESP), it will also affected by numberof stages and operating frequency.In general, the production rate increases when reservoir pressure increases and/or water cutdecreases. Also the flow rate increase when tubing size increases and/or wellhead pressuredecreases. For ESP well, production rate increases when number of stages is increasedand/or pump frequency is

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%.

A common approach to the color image compression was started by transform
the red, green, and blue or (RGB) color model to a desire color model, then applying
compression techniques, and finally retransform the results into RGB model In this
paper, a new color image compression method based on multilevel block truncation
coding (MBTC) and vector quantization is presented. By exploiting human visual
system response for color, bit allocation process is implemented to distribute the bits
for encoding in more effective away.
To improve the performance efficiency of vector quantization (VQ),
modifications have been implemented. To combines the simple computational and
edge preservation properties of MBTC with high c

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

‎تم في هذه الدراسة ، تزيين ‏رقائق أكسيد الجرافين (‏GO‏) بجسيمات ‏كوبلتيت النيكل النانوية ‏NiCo2O4‎‏(‏NC‏) عن طريق الترسيب في ‏الموقع ، وتم استخدام المتراكب ‏المحضر (‏NC: GO‏) كسطح ماز لإزالة ‏صبغة الميثيل الخضراء ( ‏MG‏) من ‏المحاليل المائية. تم التحقق من ‏التغطية الناجحة لأوكسيد الجرافين ‏بجزيئات كوبلتيت النيكل النانوية ‏‏(‏NC‏) باستخدام دراسات ‏FT-IR‏ وحيود ‏الأشعة السينية (‏XRD‏). كانت أحجام  ‏الجسيم