This study has dealt with, the issue of classification of rural road network , in addition to prepare a suggested for the classification for this network in Iraq , this classification account , the specifications and characteristics of rural roads, population, and the range taking of settlements , then this classification was applied on the rural road network in the Najaf province there are four categories of classification ,the first is major arterial rural roads divided into two major arterial and minor arterial roads , while the second category collected roads which was divided into minor arterial roads and main collected roads. The third category was represented by Local Roads , it has been divided into paved roads and unpaved, the fourth category was represented by special roads that lead certain service.
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
... Show MoreSewer systems are used to convey sewage and/or storm water to sewage treatment plants for disposal by a network of buried sewer pipes, gutters, manholes and pits. Unfortunately, the sewer pipe deteriorates with time leading to the collapsing of the pipe with traffic disruption or clogging of the pipe causing flooding and environmental pollution. Thus, the management and maintenance of the buried pipes are important tasks that require information about the changes of the current and future sewer pipes conditions. In this research, the study was carried on in Baghdad, Iraq and two deteriorations model's multinomial logistic regression and neural network deterioration model NNDM are used to predict sewers future conditions. The results of the
... Show MoreThe duration of sunshine is one of the important indicators and one of the variables for measuring the amount of solar radiation collected in a particular area. Duration of solar brightness has been used to study atmospheric energy balance, sustainable development, ecosystem evolution and climate change. Predicting the average values of sunshine duration (SD) for Duhok city, Iraq on a daily basis using the approach of artificial neural network (ANN) is the focus of this paper. Many different ANN models with different input variables were used in the prediction processes. The daily average of the month, average temperature, maximum temperature, minimum temperature, relative humidity, wind direction, cloud level and atmosp
... Show MoreInfertilityis oneuof the most problemsathatufacingaadvancedunations. In the general, about halfof allacasesaof the infertility are causedby factors thaturelated toathe male partner. Propos educausesvofumalev infertility include evgeneticuand environmental factors. Blood samples from 64 infertileumen allawere living in urban its al-Fallujah city (30 azospermeiauand 34 oligospermeia) and 32 fertile men (asuthe control group) were collected. Heavy metal concentrations inusera of infertile and fertile groupswereumeasured by using Atomic Absorption Spectrophotometer. Y- chromosomemicrodeletions were detected by using PCR techniques. Significantdifferences (P?0.05)uin the concentration ofucopper (0.0267±0.0147 and 0.0278±0.0273, for infertileua
... Show MoreInfertilityis oneuof the most problemsathatufacingaadvancedunations. In the general, about halfof allacasesaof the infertility are causedby factors thaturelated toathe male partner. Propos educausesvofumalev infertility include evgeneticuand environmental factors. Blood samples from 64 infertileumen allawere living in urban its al-Fallujah city (30 azospermeiauand 34 oligospermeia) and 32 fertile men (asuthe control group) were collected. Heavy metal concentrations inusera of infertile and fertile groupswereumeasured by using Atomic Absorption Spectrophotometer. Y- chromosomemicrodeletions were detected by using PCR techniques. Significantdifferences (P?0.05)uin the concentration ofucopper (0.0267±0.0147 and 0.0278±0.0273, for inf
... Show MoreTigris River is the lifeline that supplies a great part of Iraq with water from north to south. Throughout its entire length, the river is battered by various types of pollutants such as wastewater effluents from municipal, industrial, agricultural activities, and others. Hence, the water quality assessment of the Tigris River is crucial in ensuring that appropriate and adequate measures are taken to save the river from as much pollution as possible. In this study, six water treatment plants (WTPs) situated on the two-banks of the Tigris within Baghdad City were Al Karkh; Sharq Dijla; Al Wathba; Al Karama; Al Doura, and Al Wahda from northern Baghdad to its south, that selected to determine the removal efficiency of turbidity and
... Show MoreModeling forward kinematics with neural networks allows for efficient handling of nonlinear relationships and realistic error correction in time-critical applications by relying on accurate training data. This paper presents a Multi-Layer Feed-Forward Neural Network (MLFFNN) to solve the forward kinematics of a 3-DOF robot. The proposed MLFFNN consists of 50 hidden neurons and was trained using 628319 samples to find only the position (x, y, z) of the end-effector. Data were generated by MATLAB, assuming an incremental motion of joints. The joint variables ( , , and ) are the inputs of the NN, which outputs the positions of the end effector (x, y, z) calculated using the Denavit-Hartenberg (DH) method. The results demonstrate that t
... Show MoreThe majority of the environmental outputs from gas refineries are oily wastewater. This research reveals a novel combination of response surface methodology and artificial neural network to optimize and model oil content concentration in the oily wastewater. Response surface methodology based on central composite design shows a highly significant linear model with P value <0.0001 and determination coefficient R2 equal to 0.747, R adjusted was 0.706, and R predicted 0.643. In addition from analysis of variance flow highly effective parameters from other and optimization results verification revealed minimum oily content with 8.5 ± 0.7 ppm when initial oil content 991 ppm, tempe