The effects of three different additives formulations namely Lubrizol 21001, HiTEC 8722B and HiTEC 340 on the efficiency of VII namely OCP of three base lubricating oils namely 40 stock and 60 stock and 150 stock at four temperatures 40, 60, 80 and 100oC were investigated. The efficiency of OCP is decreased when blended with 4 and 8 wt% of Lubrizol 21001 for all the three base oil types. But it is increased when adding 4 wt% and 8 wt% of H-8722B in 40 stock. While for 60 stock and 150 stock the OCP efficiency decreased by adding 4 and 8 wt% of H-8722B. In the other hand, it is decreased with a high percentage by adding 4 and 8 wt% of H-340 for 60 stock and 150 stock and for 40 stock it is increased by adding 4 wt% of H-340 and decreased

 In this work, plasma parameters such as (electron temperature (Te), electron density (ne), plasma frequency (fp) and Debye length (λD)) were studied using spectral analysis techniques. The spectrum of the plasma was recorded with different energy values, SnO2 and ZnO anesthetized at a different ratio (X = 0.2, 0.4 and 0.6) were recorded. Spectral study of this mixing in the air. The results showed electron density and electron temperature increase in zinc oxide: tin oxide alloy targets. It was located  that  The intensity of the lines increases in different laser peak powers when the laser peak power increases and then decreases when the force continues to increase.

3D models delivered from digital photogrammetric techniques have massively increased and developed to meet the requirements of many applications. The reliability of these models is basically dependent on the data processing cycle and the adopted tool solution in addition to data quality. Agisoft PhotoScan is a professional image-based 3D modelling software, which seeks to create orderly, precise n 3D content from fixed images. It works with arbitrary images those qualified in both controlled and uncontrolled conditions. Following the recommendations of many users all around the globe, Agisoft PhotoScan, has become an important source to generate precise 3D data for different applications. How reliable is this data for accurate 3D mo

The consumption of fossil fuels has caused many challenges, including environmental and climate damage, global warming, and rising energy costs, which has prompted seeking to substitute other alternative sources. The current study explored the microwave pyrolysis of Albizia branches to assess its potential to produce all forms of fuel (solid, liquid, gas), time savings, and effective thermal heat transfer. The impact of the critical parameters on the quantity and quality of the biofuel generation, including time, power levels, biomass weight, and particle size, were investigated. The results revealed that the best bio-oil production was 76% at a power level of 450 W and 20 g of biomass. Additionally, low power levels led to enhanced

     Deep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning mod