A model using the artificial neural networks and genetic algorithm technique is developed for obtaining optimum dimensions of the foundation length and protections of small hydraulic structures. The procedure involves optimizing an objective function comprising a weighted summation of the state variables. The decision variables considered in the optimization are the upstream and downstream cutoffs lengths and their angles of inclination, the foundation length, and the length of the downstream soil protection. These were obtained for a given maximum difference in head, depth of impervious layer and degree of anisotropy. The optimization carried out is subjected to constraints that ensure a safe structure aga

The Study aims at evaluating the efficiency of the regional transportation net in Al-mahmoodiya Qadaa center. The bus station of the Qadaa center is suffering from heavy traffic jam, which is due to the ongoing movement of the adjacent provinces, particularly the small cities. They vary in the degree of their link by the regional transportation net that links the province with the centers of big cities. That affects the traffic flow of the civilians of these cities and their daily activities in hierarchical way To achieve the purpose of the study, a questionnaire has been constructed to collect data through selecting a random sample including the passengers who are coming to the bus station in Al-Mahmoodiya center to know the flo

Sewer network is one of the important utilities in modern cities which discharge the sewage from all facilities. The increase of population numbers consequently leads to the increase in water consumption; hence waste water generation. Sewer networks work is very expensive and need to be designed accurately. Thus construction effective sewer network system with minimum cost is very necessary to handle waste water generation.

 In this study trunk mains networks design was applied which connect the pump stations together by underground pipes for too long distances. They usually have large diameters with varying depths which consequently need excavations and gathering from pump stations and transport the sewage

Alzheimer's disease (AD) increasingly affects the elderly and is a major killer of those 65 and over. Different deep-learning methods are used for automatic diagnosis, yet they have some limitations. Deep Learning is one of the modern methods that were used to detect and classify a medical image because of the ability of deep Learning to extract the features of images automatically. However, there are still limitations to using deep learning to accurately classify medical images because extracting the fine edges of medical images is sometimes considered difficult, and some distortion in the images. Therefore, this research aims to develop A Computer-Aided Brain Diagnosis (CABD) system that can tell if a brain scan exhibits indications of

Objectives: This study aims to assess and compare the micro-shear bond strength (μSBS) of a novel resin-modified glass-ionomer luting cement functionalized with a methacrylate co-monomer containing a phosphoric acid group, 30 wt% 2-(methacryloxy) ethyl phosphate (2-MEP), with different substrates (dentin, enamel, zirconia, and base metal alloy). This assessment is conducted in comparison with conventional resin-modified glass ionomer cement and self-adhesive resin cement. Materials and methods: In this in vitro study, ninety-six specimens were prepared and categorized into four groups: enamel (A), dentin (B), zirconia (C), and base metal alloys (D). Enamel (E) and dentin (D) specimens were obtained from 30 human maxillary first premolars e

The study presents the modification of the Broyden-Flecher-Goldfarb-Shanno (BFGS) update (H-Version) based on the determinant property of inverse of Hessian matrix (second derivative of the objective function), via updating of the vector s ( the difference between the next solution and the current solution), such that the determinant of the next inverse of Hessian matrix is equal to the determinant of the current inverse of Hessian matrix at every iteration. Moreover, the sequence of inverse of Hessian matrix generated by the method would never  approach a near-singular matrix, such that the program would never break before the minimum value of the objective function is obtained. Moreover, the new modification of BFGS update (H-vers

The dual nature of asphalt binder necessitates improvements to mitigate rutting and fatigue since it performs as an elastic material under the regime of rapid loading or cold temperatures and as a viscous fluid at elevated temperatures. The present investigation assesses the effectiveness of Nano Alumina (NA), Nano Silica (NS), and Nano Titanium Dioxide (NT) at weight percentages of 0, 2, 4, 6, and 8% in asphalt cement to enhance both asphalt binder and mixture performance. Binder evaluations include tests for consistency, thermal susceptibility, aging, and workability, while mixture assessments focus on Marshall properties, moisture susceptibility, resilient modulus, permanent deformation, and fatigue characteristics. NS notably im

The efforts embedded in this paper have been devoted to designing, preparing, and testing warm mix asphalt (WMA) mixtures and comparing their behavior against traditional hot mix asphalt mixtures. For WMA preparation, the Sasobit wax additive has been added to a 40/50 asphalt binder with a concentration of 3%. An experimental evaluation has been performed by conducting the Marshall together with volumetric properties, indirect tensile strength, and wheel tracking tests to acquire the tensile strength ratio (TSR), retained stability index (RSI), and rut depth. It was found that the gained benefit of reduction in mixing and compaction temperatures was reversely associated with a noticeable decline in Marshall properties and moisture s