High performance self-consolidating concrete HP-SCC is one of the most complex types of concrete which have the capacity to consolidated under its own weight, have excellent homogeneity and high durability. This study aims to focus on the possibility of using industrial by-products like Silica fumes SF in the preparation of HP-SCC enhanced with discrete steel fibers (DSF) and monofilament polypropylene fibers (PPF). From experimental results, it was found that using DSF with volume fraction of 0.50 %; a highly improvements were gained in the mechanical properties of HP-SCC. The compressive strength, splitting tensile strength, flexural strength and elastic modulus improved about 65.7 %, 70.5 %, 41.7 % and 80.3 % at 28 days age, respectively with retaining the main properties of HP-SCC. Furthermore, using PPF with volume fraction up to 0.10 %; an enhancement in the compressive and elastic modulus of HP-SCC about 47.4 % and 31 % was obtained at age of 28 days, respectively. Moreover, using PPF with volume fraction of 0.15 %, the splitting tensile strength and flexural strength of HP-SCC improved about 44.5 % and 20.3 %, respectively.
Ultimate oil recovery and displacement efficiency at the pore-scale are controlled by the rock wettability thus there is a growing interest in the wetting behaviour of reservoir rocks as production from fractured oil-wet or mixed-wet limestone formations have remained a key challenge. Conventional waterflooding methods are inefficient in such formation due to poor spontaneous imbibition of water into the oil-wet rock capillaries. However, altering the wettability to water-wet could yield recovery of significant amounts of additional oil thus this study investigates the influence of nanoparticles on wettability alteration. The efficiency of various formulated zirconium-oxide (ZrO2) based nanofluids at different nanoparticle concentrations (0
... Show MoreEnergy efficiency is a significant aspect in designing robust routing protocols for wireless sensor networks (WSNs). A reliable routing protocol has to be energy efficient and adaptive to the network size. To achieve high energy conservation and data aggregation, there are two major techniques, clusters and chains. In clustering technique, sensor networks are often divided into non-overlapping subsets called clusters. In chain technique, sensor nodes will be connected with the closest two neighbors, starting with the farthest node from the base station till the closest node to the base station. Each technique has its own advantages and disadvantages which motivate some researchers to come up with a hybrid routing algorit
... Show MoreThe research aims to clarify the COBIT5 framework for IT governance and to develop of a criterion based on Balanced Scorecard that contributes in measuring the performance of IT governance. To achieve these goals, the researchers adopted the deductive approach in the design of balanced scorecard to measure the IT governance at the Bank of Baghdad that was chosen because it relied heavily on IT.
The research has reached a number of conclusions, the most important of which is that the performance of IT department in the Bank of Baghdad falls within the good level that requires constant monitoring, the most committed items of Balanced Scorecard by the Bank were customer, internal operation, growth and finally the financial item; IT
... Show MoreThe paper uses the Direct Synthesis (DS) method for tuning the Proportional Integral Derivative (PID) controller for controlling the DC servo motor. Two algorithms are presented for enhancing the performance of the suggested PID controller. These algorithms are Back-Propagation Neural Network and Particle Swarm Optimization (PSO). The performance and characteristics of DC servo motor are explained. The simulation results that obtained by using Matlab program show that the steady state error is eliminated with shorter adjusted time when using these algorithms with PID controller. A comparative between the two algorithms are described in this paper to show their effectiveness, which is found that the PSO algorithm gives be
... Show MoreThin films of (CdO)x (CuO)1-x (where x = 0.0, 0.2, 0.3, 0.4 and 0.5) were prepared by the pulsed laser deposition. The CuO addition caused an increase in diffraction peaks intensity at (111) and a decrease in diffraction peaks intensity at (200). As CuO content increases, the band gap increases to a maximum of 3.51 eV, maximum resistivity of 8.251x 104 Ω.cm with mobility of 199.5 cm2 / V.s, when x= 0.5. The results show that the conductivity is ntype when x value was changed in the range (0 to 0.4) but further addition of CuO converted the samples to p-type.
The inhibitive power of Polyvinyl Alcohol (PVA) was investigated toward the corrosion of carbon steel in 0.2N H2SO4 solution in the temperature range of 30-60˚C and PVA concentration range of 150-2000 ppm.
The corrosion rate was measured using both the weight loss and the electrochemical techniques. The weight loss results showed that PVA could serve as a corrosion inhibitor but its inhibition power was found to be low for the corrosion of carbon steel in the acidic media. Electrochemical analysis of the corrosion process of carbon steel in an electrochemical corrosion cell was investigated using 3-Electrode corrosion cell. Polarization technique was used for carbon steel corrosion in 0.2N H
Recurrent strokes can be devastating, often resulting in severe disability or death. However, nearly 90% of the causes of recurrent stroke are modifiable, which means recurrent strokes can be averted by controlling risk factors, which are mainly behavioral and metabolic in nature. Thus, it shows that from the previous works that recurrent stroke prediction model could help in minimizing the possibility of getting recurrent stroke. Previous works have shown promising results in predicting first-time stroke cases with machine learning approaches. However, there are limited works on recurrent stroke prediction using machine learning methods. Hence, this work is proposed to perform an empirical analysis and to investigate machine learning al
... Show More