An investigation was conducted for the improvement of viscosity index of light lubricating oil fraction (40 stock)
obtained from vacuum distillation unit of lube oil plant of Daura Refinery, using solvent extraction process.
In this study furfural solvent was used to extract the undesirable materials which reduce the viscosity index of raw
lubricating oil fraction.
The studied effecting variables of extraction were extraction temperature range from 70 to 110°C, and solvent to oil
ratio range from 1:1 to 4:1 (wt/wt).
The n-d-M method was used for calculation of carbon distribution and structural group analysis of the raffinate
produced from furfural extraction.
Also the three component phase diagram for a mixed-ba

In this work, chemical and thermal treatment were used to enhance silica extract on the purity of rice husk and to reduce the impurities associated with the extraction of silica. The thermal degradation of rice husk was studied. The characteristics and thermal degradation behavior of rice husk which investigated using thermogravimetric analyzer (TGA). Hydrochloric acid was used to soak the rice husk and the study of leaching influence is followed by XRF tests for samples before and after the combustion process. Acid treatment and combustion method seem to have a clear effect on silica purity. The pyrolysis processes were carried out at Laboratory temperature up to 650 oC in the presence of nitrogen gas flowing at 150 ml/min. The effect o

This study aimed to identify the effect of resistance training on the biomechanics and accuracy of serve receiving skills in volleyball. The research community was composed of 26 young volleyball players of Baghdad volleyball clubs. A total of 4 players were selected for the preliminary experiment, while 14 participants were recruited as the main sample for the study. In the present study, a set of resistance exercises were designed by the researchers for the volleyball players of the sample. Exercises were performed by the sample participants during the course of study. The biomechanical variables considered in the present study were: Preparation moment (shoulder joint angle, hip angle, knee joint angle), moment of pr

The recent advances in technology, the increased dependence on electrical energy and the emergence of the fourth industrial revolution (Industry 4.0) were all factors in the increased need for smart, efficient and reliable energy systems. This introduced the concept of the Smart Grid (SG). A SG is a potential replacement for older power grids, capable of adapting and distributing energy based on demand. SG systems are complex. They combine various components and have high requirements for real time reliable operation. This paper attempts to provide an overview of SG systems, by outlining SG architecture and various components. It also introduces communication technologies, integration and network management tools that are involved in SG sys

Ensuring reliable data transmission in Network on Chip (NoC) is one of the most challenging tasks, especially in noisy environments. As crosstalk, interference, and radiation were increased with manufacturers' increasing tendency to reduce the area, increase the frequencies, and reduce the voltages.  So many Error Control Codes (ECC) were proposed with different error detection and correction capacities and various degrees of complexity. Code with Crosstalk Avoidance and Error Correction (CCAEC) for network-on-chip interconnects uses simple parity check bits as the main technique to get high error correction capacity. Per this work, this coding scheme corrects up to 12 random errors, representing a high correction capac

Erythrocytes aggregation is an important physiological phenomenon in the circulation of blood, and is a basic characteristic of normal blood that plays a major role in cardiovascular system especially in the microcirculation. Blood samples have been taken from (30) volunteers (15 male, and 15 female), their ages (20-30) years. The Erythrocytes Sedimentation Rate (ESR) for those subjects was measured at different Packed Cells Volume (PCV) (10%-25%), and also it was measured at different temperature (10oC-25oC). The results show that there was a highly significant decrease (P<0.01) in ESR when the PCV increase and a highly significant increase (P<0.01) in ESR when the temperatures increase. The conclusion from these results is that the ESR va

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