The method of predicting the electricity load of a home using deep learning techniques is called intelligent home load prediction based on deep convolutional neural networks. This method uses convolutional neural networks to analyze data from various sources such as weather, time of day, and other factors to accurately predict the electricity load of a home. The purpose of this method is to help optimize energy usage and reduce energy costs. The article proposes a deep learning-based approach for nonpermanent residential electrical ener-gy load forecasting that employs temporal convolutional networks (TCN) to model historic load collection with timeseries traits and to study notably dynamic patterns of variants amongst attribute par

This work evaluates the influence of combining twisted fins in a triple-tube heat exchanger utilised for latent heat thermal energy storage (LHTES) in three-dimensional numerical simulation and comparing the outcome with the cases of the straight fins and no fins. The phase change material (PCM) is in the annulus between the inner and the outer tube, these tubes include a cold fluid that flows in the counter current path, to solidify the PCM and release the heat storage energy. The performance of the unit was assessed based on the liquid fraction and temperature profiles as well as solidification and the energy storage rate. This study aims to find suitable and efficient fins number and the optimum values of the Re and the inlet tem

يهدف البحث إلى تقييم الكفاءة الوظيفية لمؤسسات التعليم الأهلي في أداء وظيفتها بمستوى عالٍ لتشبع حاجة سكان المدينة الذين فضّلوا التعليم الأهلي على التعليم داخل المؤسسات الحكومية مما أدى إلى انتشارها، وصولا إلى أهم الآثار المترتبة على ذلك الانتشار إذ نافست فيه مؤسسات التعليم الحكومي، بل وتنافست المؤسسات الأهلية فيما بينها لتقديم أفضل خدمة تعليمية للصراع من أجل البقاء، وتهدف أيضا إلى  إظهار الوجه السلبي ا