The deterioration of buried sewers during their lifetime can be affected by several factors leading to bad performance and can damage the infrastructure similar to other engineering structures. The Hydraulic deterioration of the buried sewers caused by sewer blockages while the structural deterioration caused by sewer collapses due to sewer specifications and the surrounding soil characteristics and the groundwater level. The main objective of this research is to develop deterioration models, which are used to predict changes in sewer condition that can provide assessment tools for determining the serviceability of sewer networks in Baghdad city. Two deterioration models were developed and tested using statistical software SPSS, the multiple discriminant model (MDM) and neural network model (NNM). Zublin trunk sewer in Baghdad city was selected as a case study. The deterioration model based on the NNDM provide the highest overall prediction efficiency which could be attributed to its inherent ability to model complex processes. The MDDM provided relatively low overall prediction efficiency, this may be due to the restrictive assumptions by this model. For the NNDM the confusion matrix gave overall prediction efficiency about 87.3% for model training and 70% for model validation, and the overall conclusion from these models may predict that Zublin trunk sewer is of a poor condition.
For cleaner air and unpolluted continue assessment study air pollution the city of
Baghdad by measuring the concentrations of air pollutants, which included TSP, Pb, where
the adoption of three stations (Andalus Square, Jadiriya, Allawi) are distributed in the city of
Baghdad in order to compare the concentrations of these pollutants with previous studies.
Study pointed out that the city's air contaminant, especially in minutes outstanding after
deducting the amount of atmospheric dust thick mechanism city this year where the highest
concentration of minutes outstanding (9895) micrograms / m 3 at the station Alawi and lower
concentration of 157 micrograms / m 3 at the station Alawi and this was higher than the
det
Knowledge of permeability, which is the ability of rocks to transmit the fluid, is important for understanding the flow mechanisms in oil and gas reservoirs.
Permeability is best measured in the laboratory on cored rock taken from the reservoir. Coring is expensive and time-consuming in comparison to the electronic survey techniques most commonly used to gain information about permeability.
Yamama formation was chosen, to predict the permeability by using FZI method. Yamama Formation is the main lower cretaceous carbonate reservoir in southern of Iraq. This formation is made up mainly of limestone. Yamama formation was deposited on a gradually rising basin floor. The digenesis of Yamama sediments is very important due to its direct
With the escalation of cybercriminal activities, the demand for forensic investigations into these crimeshas grown significantly. However, the concept of systematic pre-preparation for potential forensicexaminations during the software design phase, known as forensic readiness, has only recently gainedattention. Against the backdrop of surging urban crime rates, this study aims to conduct a rigorous andprecise analysis and forecast of crime rates in Los Angeles, employing advanced Artificial Intelligence(AI) technologies. This research amalgamates diverse datasets encompassing crime history, varioussocio-economic indicators, and geographical locations to attain a comprehensive understanding of howcrimes manifest within the city. Lev
... Show MoreAerial Robot Arms (ARAs) enable aerial drones to interact and influence objects in various environments. Traditional ARA controllers need the availability of a high-precision model to avoid high control chattering. Furthermore, in practical applications of aerial object manipulation, the payloads that ARAs can handle vary, depending on the nature of the task. The high uncertainties due to modeling errors and an unknown payload are inversely proportional to the stability of ARAs. To address the issue of stability, a new adaptive robust controller, based on the Radial Basis Function (RBF) neural network, is proposed. A three-tier approach is also followed. Firstly, a detailed new model for the ARA is derived using the Lagrange–d’A
... Show MoreIt is an established fact that substantial amounts of oil usually remain in a reservoir after primary and secondary processes. Therefore; there is an ongoing effort to sweep that remaining oil. Field optimization includes many techniques. Horizontal wells are one of the most motivating factors for field optimization. The selection of new horizontal wells must be accompanied with the right selection of the well locations. However, modeling horizontal well locations by a trial and error method is a time consuming method. Therefore; a method of Artificial Neural Network (ANN) has been employed which helps to predict the optimum performance via proposed new wells locations by incorporatin
The turning process has various factors, which affecting machinability and should be investigated. These are surface roughness, tool life, power consumption, cutting temperature, machining force components, tool wear, and chip thickness ratio. These factors made the process nonlinear and complicated. This work aims to build neural network models to correlate the cutting parameters, namely cutting speed, depth of cut and feed rate, to the machining force and chip thickness ratio. The turning process was performed on high strength aluminum alloy 7075-T6. Three radial basis neural networks are constructed for cutting force, passive force, and feed force. In addition, a radial basis network is constructed to model the chip thickness ratio. T
... Show MoreThe objective of this study was to investigate the prophylactic roles of human enteric derived Lactobacillus plantarum L1 (Ll) and Lactobacillus paracasei L2 (L2), on EHEC O157:H7 infection in rodent models (In vivo). The Lactobacillus suspensions (L1 and L2) were individually and orally administered to experimental rats at a daily two consecutives of 100 μl (108 CFU/ ml/rat) for up to two weeks. Thereafter, on the 8th day of experiment rats were orally challenged with one dose infection of EHEC (105 CFU/ml/rat). Animals mortality and illness symptoms have been monitored. There was no fatal EHEC infection in rats that had been pre‑colonized with the Lactobacillus strains, while most of EHEC infected rats were died (90%). The
... Show MoreBaghdad Lake Touristic is suffering from a lake of tourism and entertainment services
efficiency provided to their visitors , knowing that this type of services as they are the basics
to achieve economic and socialist development because of their indicators where their goal is
to serve human in city as they represent lungs which population breathe within .
The Parks are resorted as human usually in search of quiet and funny places , away from
the noise of the city and its complex , as well as they give the city a beauty manifestations ,
that give happiness.
The study reached that there is deficiencies in service present, inability to provide
services and inadequate for the population and bad distribution. So the s
Diabetes is one of the increasing chronic diseases, affecting millions of people around the earth. Diabetes diagnosis, its prediction, proper cure, and management are compulsory. Machine learning-based prediction techniques for diabetes data analysis can help in the early detection and prediction of the disease and its consequences such as hypo/hyperglycemia. In this paper, we explored the diabetes dataset collected from the medical records of one thousand Iraqi patients. We applied three classifiers, the multilayer perceptron, the KNN and the Random Forest. We involved two experiments: the first experiment used all 12 features of the dataset. The Random Forest outperforms others with 98.8% accuracy. The second experiment used only five att
... Show More