A genetic algorithm model coupled with artificial neural network model was developed to find the optimal values of upstream, downstream cutoff lengths, length of floor and length of downstream protection required for a hydraulic structure. These were obtained for a given maximum difference head, depth of impervious layer and degree of anisotropy. The objective function to be minimized was the cost function with relative cost coefficients for the different dimensions obtained. Constraints used were those that satisfy a factor of safety of 2 against uplift pressure failure and 3 against piping failure.
Different cases reaching 1200 were modeled and analyzed using geo-studio modeling, with different values of input variables. The soil was considered homogeneous anisotropic. For each case, the length of protection (L) and the volume of the superstructure (V) required to satisfy the factors of safety mentioned above were calculated. These data were used to obtain an artificial neural network model for estimating (L) and (V) for a given length of upstream cutoff (S1), length of downstream cutoff (S2), head difference (H), length of floor (B), depth of impervious layer (D) and degree of anisotropy (kx/ky).
A MatLAB code was written to perform a genetic algorithm optimization modeling using the obtained ANN model .The obtained optimum solution for some selected cases were compared with the Geo-studio modeling to find the length of protection required in the downstream side and volume required for superstructure. Values estimated were found comparable to the obtained values from the Genetic Algorithm model.
Scheduling Timetables for courses in the big departments in the universities is a very hard problem and is often be solved by many previous works although results are partially optimal. This work implements the principle of an evolutionary algorithm by using genetic theories to solve the timetabling problem to get a random and full optimal timetable with the ability to generate a multi-solution timetable for each stage in the collage. The major idea is to generate course timetables automatically while discovering the area of constraints to get an optimal and flexible schedule with no redundancy through the change of a viable course timetable. The main contribution in this work is indicated by increasing the flexibility of generating opti
... Show MoreMultilateral wells require a sophisticated type of well model to be applied in reservoir simulators to represent them. The model must be able to determine the flow rate of each fluid and the pressure throughout the well. The production rate calculations are very important because they give an indication about some main issues associated with multi-lateral wells such as one branch may produce water or gas before others, no production rate from one branch, and selecting the best location of a new branch for development process easily.  
... Show MoreIn the present work, the magnetic dipole and electric quadrupole moments for some sodium isotopes have been calculated using the shell model, considering the effect of the two-body effective interactions and the single-particle potentials. These isotopes are; 21Na (3/2+), 23Na (3/2+), 25Na (5/2+), 26Na (3+), 27Na (5/2+), 28Na (1+) and, 29Na (3/2+). The one-body transition density matrix elements (OBDM) have been calculated using the (USDA, USDB, HBUMSD and W) two-body effective interactions carried out in the sd-shell model space. The sd shell model space consists of the active 2s1/2, 1d5/2,
... Show MoreBig data analysis is essential for modern applications in areas such as healthcare, assistive technology, intelligent transportation, environment and climate monitoring. Traditional algorithms in data mining and machine learning do not scale well with data size. Mining and learning from big data need time and memory efficient techniques, albeit the cost of possible loss in accuracy. We have developed a data aggregation structure to summarize data with large number of instances and data generated from multiple data sources. Data are aggregated at multiple resolutions and resolution provides a trade-off between efficiency and accuracy. The structure is built once, updated incrementally, and serves as a common data input for multiple mining an
... Show MoreThis study showed that liver of Passer domesticus bilobed the right lobe is cardiac shape while the left is elliptical and the liver colour is brown. It is occupying most of anterior and middle parts of abdominal cavity. The liver is surrounded by Glison capsule which is represented by a thin layer of connective tissue with septum extend peripherally in liver tissue. The liver tissue is formed from polyhedral hepatocyte arrange as irregular hepatic cord surrounded the central vein. Each cell contains one or two nucleus with one or more nucleolus. The blood sinusoid appeared between the liver cells .The hepatic cord arranged radially around the central vein. The portal area is clear and surrounded by connective tissue. Gallbladder is almost
... Show MoreThis study presents the findings of a 3D finite element modeling on the performance of a single pile under various slenderness ratios (25, 50, 75, 100). These percentages were assigned to cover the most commonly configuration used in such kind of piles. The effect of the soil condition (dry and saturated) on the pile response was also investigated. The pile was modeled as a linear elastic, the surrounded dry soil layers were simulated by adopting a modified Mohr-Coulomb model, and the saturated soil layers were simulated by the modified UBCSAND model. The soil-pile interaction was represented by interface elements with a reduction factor (R) of 0.6 in the loose sand layer and 0.7 in t
In the petroleum industry, multiphase flow dynamics within the tubing string have gained significant attention due to associated challenges. Accurately predicting pressure drops and wellbore pressures is crucial for the effective modeling of vertical lift performance (VLP). This study focuses on predicting the multiphase flow behavior in four wells located in the Faihaa oil field in southern Iraq, utilizing PIPESIM software. The process of selecting the most appropriate multiphase correlation was performed by utilizing production test data to construct a comprehensive survey data catalog. Subsequently, the results were compared with the correlations available within the PIPESIM software. The outcomes reveal that the Hagedorn and Brown (H
... Show MoreAbstract: The aim of this study was to evaluate the effect of bone density value in Hounsfield unit derived from cone beam computed tomography (CBCT), and implant dimensions in relation to implant stability parameters namely the resonance frequency analysis and the insertion torque (IT) value. It included 24 patients who received 42 dental implants (DI). The bone density of the planned implant site was preoperatively measured using cone beam computed tomography. The implant stability was measured using Osstell implant stability quotient (ISQ). The ISQ values were recorded immediately postoperatively and after 16 weeks. The IT value was categorized as 35 N/cm or > 35 N/cm. The mean (standard deviation) primary stability was 79.58 (5.27) ISQ,
... Show MoreThe paper present design of a control structure that enables integration of a Kinematic neural controller for trajectory tracking of a nonholonomic differential two wheeled mobile robot, then proposes a Kinematic neural controller to direct a National Instrument mobile robot (NI Mobile Robot). The controller is to make the actual velocity of the wheeled mobile robot close the required velocity by guarantees that the trajectory tracking mean squire error converges at minimum tracking error. The proposed tracking control system consists of two layers; The first layer is a multi-layer perceptron neural network system that controls the mobile robot to track the required path , The second layer is an optimization layer ,which is impleme
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