Nanoparticles have gained considerable interest in recent times for oil recovery purposes owing to significant capabilities in wettability alteration of reservoir rocks. Wettability is a key factor controlling displacement efficiency and ultimate recovery of oil. The present study investigates the influence of zirconium (IV) oxide (ZrO2) and nickel (II) oxide (NiO) nanoparticles on the wetting preference of fractured (oil-wet) limestone formations. Wettability was assessed through SEM, AFM and contact angle. The potentials of the nanoparticles to alter oil-wet calcite substrates water wet, was experimentally tested at low nanoparticle concentrations (0.004–0.05 wt%). Quite similar behaviour was observed for both nanoparticles at the same particle concentration; while ZrO2 demonstrated a better efficiency by altering strongly oil-wet (water contact angle θ=152°) calcite substrates into a strongly water-wet (θ=44°) state, NiO changed wettability to an intermediate-wet condition (θ=86°) at 0.05 wt% nanoparticle concentration. We conclude that ZrO2 is very efficient in terms of inducing strong water-wettability; and ZrO2 based nanofluids have a high potential as EOR agents.
Calculating the Inverse Kinematic (IK) equations is a complex problem due to the nonlinearity of these equations. Choosing the end effector orientation affects the reach of the target location. The Forward Kinematics (FK) of Humanoid Robotic Legs (HRL) is determined by using DenavitHartenberg (DH) method. The HRL has two legs with five Degrees of Freedom (DoF) each. The paper proposes using a Particle Swarm Optimization (PSO) algorithm to optimize the best orientation angle of the end effector of HRL. The selected orientation angle is used to solve the IK equations to reach the target location with minimum error. The performance of the proposed method is measured by six scenarios with different simulated positions of the legs. The proposed
... Show MoreBackground: asthma has an influence on craniofacial development. Recently evidences show that there is an association between oral health problems and chronic lung disease. The present study was designed to estimate the changes in arch dimension measurements among asthmatic children aged 12 years old who were collected from AL- Zahra Center Advisory for Allergy and Asthma and compare them with the non-asthmatic children of the same age and gender. Material and Methods: Fifty children (25 asthmatic and 25 non- asthmatic children) were included for the odontometric measurement. For both upper and lower study models, photographs were taken using special photographic apparatus for each child, and the statistical analysis were done by using SPSS
... Show MoreThe aim of this study is to shed light on the importance of biofuels as an alternative to conventional energy, in addition to the importance of preserving agricultural crops, which are the main source of this fuel, to maintain food security, especially in developing countries. The increase in global oil prices, in addition to the fear of global warming, are among the main factors that draw the world’s attention to searching for alternative sources of traditional energy, which are sustainable on the one hand, and on the other hand reduce carbon emissions. Therefore, the volume of global investment in renewable energy in general, and in liquid biofuels and biomass in particular, has increased. Global fears emerged that the excessive
... Show MoreThis research aims at studying the relation between fair value and the Financial Reports Quality to achieve a number of aims such as :-
1- Throw light on the problems of the measurement that depends on the historic cost as it paves the way towards the method of the fair value in the accounting measurement.
2-Give a general definition for fair value in the accounting via analyzing the theoretical aspects that relates the subject and the scientific bases on which the relating accounting treatment depend.
3- Exhibit the characteristics that could be added by the fair value to the accounting Information .
The study problem is summarized in that the e
... Show MoreThere is various human biometrics used nowadays, one of the most important of these biometrics is the face. Many techniques have been suggested for face recognition, but they still face a variety of challenges for recognizing faces in images captured in the uncontrolled environment, and for real-life applications. Some of these challenges are pose variation, occlusion, facial expression, illumination, bad lighting, and image quality. New techniques are updating continuously. In this paper, the singular value decomposition is used to extract the features matrix for face recognition and classification. The input color image is converted into a grayscale image and then transformed into a local ternary pattern before splitting the image into
... Show Moreoday deep ocean life has not been discovered by humans including many secret world things to be explored. The researcher has focused on underwater optical wireless communications using various kinds of complex digital Signal processing most of them used in air and starting applied in underwater communication. The Internet of Things (IoT) uses underwater called Internet of Underwater Things (IoUT) applications to explore the underwater world with other devices. However, the difference in concentration between air and water surfaces is not easy making wireless communication more complicated. Visible light passes the water's surface with scattering and distortion inside the water and each color of light has different attenuation the blue laser
... Show MoreThis work implements an Electroencephalogram (EEG) signal classifier. The implemented method uses Orthogonal Polynomials (OP) to convert the EEG signal samples to moments. A Sparse Filter (SF) reduces the number of converted moments to increase the classification accuracy. A Support Vector Machine (SVM) is used to classify the reduced moments between two classes. The proposed method’s performance is tested and compared with two methods by using two datasets. The datasets are divided into 80% for training and 20% for testing, with 5 -fold used for cross-validation. The results show that this method overcomes the accuracy of other methods. The proposed method’s best accuracy is 95.6% and 99.5%, respectively. Finally, from the results, it
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