Physical and chemical adsorption analyses were carried out by nitrogen gas using ASTM apparatus at 77 K and hydrogen gas using volumetric apparatus at room temperature respectively. These analyses were used for determination the effect of coke deposition and poisoning metal on surface area, pore size distribution and metal surface area of fresh and spent hydrodesulphurization catalyst Co-MoAl2O3 .Samples of catalyst (fresh and spent) used in this study are taken from AL-Dura refinery. The results of physical adsorption shows that surface area of spent catalyst reduced to third compare with fresh catalyst and these catalysts exhibit behavior of type four according to BET classification ,so, the pores of these samples are cylindrical, and the

Drag has long been identified as the main reason for the loss of energy in fluid transmission like pipelines and other similar transportation channels. The main contributor to this drag is the viscosity as well as friction against the pipe walls, which will results in more pumping power consumption.

   The aim in this study was first to understand the role of additives in the viscosity reduction and secondly to evaluate the drag reduction efficiency when blending with different solvents.

   This research investigated flow increase (%FI) in heavy oil at different flow rates (2 to 10 m3/hr) in two pipes (0.0381 m & 0.0508 m) ID By using different additives (toluene and naphtha) with different concent

Many academics have concentrated on applying machine learning to retrieve information from databases to enable researchers to perform better. A difficult issue in prediction models is the selection of practical strategies that yield satisfactory forecast accuracy. Traditional software testing techniques have been extended to testing machine learning systems; however, they are insufficient for the latter because of the diversity of problems that machine learning systems create. Hence, the proposed methodologies were used to predict flight prices. A variety of artificial intelligence algorithms are used to attain the required, such as Bayesian modeling techniques such as Stochastic Gradient Descent (SGD), Adaptive boosting (ADA), Decision Tre

Many academics have concentrated on applying machine learning to retrieve information from databases to enable researchers to perform better. A difficult issue in prediction models is the selection of practical strategies that yield satisfactory forecast accuracy. Traditional software testing techniques have been extended to testing machine learning systems; however, they are insufficient for the latter because of the diversity of problems that machine learning systems create. Hence, the proposed methodologies were used to predict flight prices. A variety of artificial intelligence algorithms are used to attain the required, such as Bayesian modeling techniques such as Stochastic Gradient Descent (SGD), Adaptive boosting (ADA), Deci

In this study, phytoplankton density, chlorophyll-a, and selected physico- chemical parameters were investigated in Erbil wastewater channel. The surveys were carried out monthly from May 2003 to April 2004. Samplings were established on three sites from headwaters to the mouth. The results showed that pH was in alkaline side of neutrality, with significant differences (P<0.05) between sites 1 and 3. TSS concentration decreased from site 1 toward site 2 (mean value, 80.15 to 25.79 mg.l-1). A clear gradual increase in mineral content (TDS) observed from site one of the channel towards the mouthpart. Soluble reactive phosphate has a concentration maximum mean value reached 48.4 µg.l-1 which is recorded in site 2. A high positive relat

The present study addresses adopting the organic and nutritious materials in dairy wastewater as media for cultivation of microalgae, which represent an important source of renewable energy. This study was carried out through cultivation of three types of microalgae; Chlorella sp., Synechococcus, and Anabaena. The results shows the success the cultivation of the Synechococcus and  Chlorella Sp, while the Anabaena microalgae were in low-growth level. The highest growth was in the Synechococcus farm, followed by Chlorella and Anabaena. However, the growth of Synechococcus required 10 days to achieve this increase that re

The increasing demand for energy has encouraged the development of renewable resources and environmentally benign fuel such as biodiesel. In this study, ethyl fatty esters (EFEs), a major component of biodiesel fuel, were synthesized from soybean oil using sodium ethoxide as a catalyst. By-products were glycerol and difatty acyl urea (DFAU), which has biological characteristics, as antibiotics and antifungal medications. Both EFEs and DFAU have been characterized using Fourier transform infrared (FTIR) spectroscopy, and 1H nuclear magnetic resonance (NMR) technique. The optimum conditions were studied as a function of reaction time, reactant molar ratios, catalyst percentage and the effect of organic solvents. The conversion ratio of soybea

Estimation of mechanical and physical rock properties is an essential issue in applications related to reservoir geomechanics. Carbonate rocks have complex depositional environments and digenetic processes which alter the rock mechanical properties to varying degrees even at a small distance. This study has been conducted on seventeen core plug samples that have been taken from different formations of carbonate reservoirs in the Fauqi oil field (Jeribe, Khasib, and Mishrif formations). While the rock mechanical and petrophysical properties have been measured in the laboratory including the unconfined compressive strength, Young's modulus, bulk density, porosity, compressional and shear -waves, well logs have been used to do a compar

A substantial portion of today’s multimedia data exists in the form of unstructured text. However, the unstructured nature of text poses a significant task in meeting users’ information requirements. Text classification (TC) has been extensively employed in text mining to facilitate multimedia data processing. However, accurately categorizing texts becomes challenging due to the increasing presence of non-informative features within the corpus. Several reviews on TC, encompassing various feature selection (FS) approaches to eliminate non-informative features, have been previously published. However, these reviews do not adequately cover the recently explored approaches to TC problem-solving utilizing FS, such as optimization techniques.