The performance of sewage pumps stations affected by many factors through its work time which produce undesired transportation efficiency. This paper is focus on the use of artificial neural network and multiple linear regression (MLR) models for prediction the major sewage pump station in Baghdad city. The data used in this work were obtained from Al-Habibia sewage pump station during specified records- three years in Al-Karkh district, Baghdad. Pumping capability of the stations was recognized by considering the influent input importance of discharge, total suspended solids (TSS) and biological oxygen demand (BOD). In addition, the chemical oxygen demands (COD), pH and chloride (Cl). The proposed model performance has compared with the correlation coefficient (r). The suitable structure design of neural network model is examined through many trials, error, preparations and evaluation steps. Two prediction models of organic and sediment loading are presented. Result found that the estimating of the organic and sediment loading by ANN model could be successful. Moreover, results showed that influent discharge rate have more effect on organic and sediment loading predicting to other parameters.
Abstract : Objectives: The aims of the study are to identify the condition causes respiratory failure in both sex and to find out the relationship between prognosis and mortality rate with condition causes respiratory failure. Methodology : Descriptive study was carried out in Al- Yarmook Hospital in Respiratory care Unit in Baghdad from the 1st of August 2003 to 1st of August 2004, the sample consist of 300 patients (150) males and (150) females, descriptive and inferential statistics procedures were applied to the data analysis Results : The results shows that 24.4% of patients effect by post-operative compl
The experiment was carried out in the green house of botanical garden belong to Department of Biology/College of Education for Pure Science Ibn AL-Haitham, University of Baghdad for growing season 2017-2018 to evaluate effect of lead stress with concentrations (0, 50, 100, 150) mg.L -1 and Selenium concentrations (0, 15, 30) mg.L-1 on growth of dill plant using pots. The experiment was designed according to completely randomized design (CRD) with three replications. Result indicated that dill plants subjected to lead stress with height concentrations caused decrease in plant parameters (plant height, no. of branches. plant-1, root length, shoot dry weight, the content of nitrogen, phosphorus and potassium, protein concentration, no. of umbe
... Show More؛ ١٨his study male and female albino mice werdministr^d doses of alkaloid and phenolic extracts of Allium cepa at doses of( 25 ,50,100, 200) mg / kg of( body weight). males and females were divided into four groups and each croup comprised mice were injected intra^ritonially daily for one week and orally ٢٠٢ one month . After which animals were killed and the serum was separated for biochemical analysis (total blood suger, total protein , otal cholesterol). Results showed significant decrease ( p< 0,05) in the total blood suger and total cholesterol on the serum of both males and females and significant increase( p< 0,05) in the total serum protein of both males and females of the two types of injection and oral administr
... Show MoreIntrusion detection systems (IDS) are useful tools that help security administrators in the developing task to secure the network and alert in any possible harmful event. IDS can be classified either as misuse or anomaly, depending on the detection methodology. Where Misuse IDS can recognize the known attack based on their signatures, the main disadvantage of these systems is that they cannot detect new attacks. At the same time, the anomaly IDS depends on normal behaviour, where the main advantage of this system is its ability to discover new attacks. On the other hand, the main drawback of anomaly IDS is high false alarm rate results. Therefore, a hybrid IDS is a combination of misuse and anomaly and acts as a solution to overcome the dis
... Show MoreIn this study, an efficient compression system is introduced, it is based on using wavelet transform and two types of 3Dimension (3D) surface representations (i.e., Cubic Bezier Interpolation (CBI)) and 1 st order polynomial approximation. Each one is applied on different scales of the image; CBI is applied on the wide area of the image in order to prune the image components that show large scale variation, while the 1 st order polynomial is applied on the small area of residue component (i.e., after subtracting the cubic Bezier from the image) in order to prune the local smoothing components and getting better compression gain. Then, the produced cubic Bezier surface is subtracted from the image signal to get the residue component. Then, t
... Show MoreIn this paper, a cognitive system based on a nonlinear neural controller and intelligent algorithm that will guide an autonomous mobile robot during continuous path-tracking and navigate over solid obstacles with avoidance was proposed. The goal of the proposed structure is to plan and track the reference path equation for the autonomous mobile robot in the mining environment to avoid the obstacles and reach to the target position by using intelligent optimization algorithms. Particle Swarm Optimization (PSO) and Artificial Bee Colony (ABC) Algorithms are used to finding the solutions of the mobile robot navigation problems in the mine by searching the optimal paths and finding the reference path equation of the optimal
... Show MoreIn recent decades, the identification of faces with and without masks from visual data, such as video and still images, has become a captivating research subject. This is primarily due to the global spread of the Corona pandemic, which has altered the appearance of the world and necessitated the use of masks as a vital measure for epidemic prevention. Intellectual development based on artificial intelligence and computers plays a decisive role in the issue of epidemic safety, as the topic of facial recognition and identifying individuals who wear masks or not was most prominent in the introduction and in-depth education. This research proposes the creation of an advanced system capable of accurately identifying faces, both with and
... Show MoreThe objective of this study is to apply Artificial Neural Network for heat transfer analysis of shell-and-tube heat exchangers widely used in power plants and refineries. Practical data was obtained by using industrial heat exchanger operating in power generation department of Dura refinery. The commonly used Back Propagation (BP) algorithm was used to train and test networks by divided the data to three samples (training, validation and testing data) to give more approach data with actual case. Inputs of the neural network include inlet water temperature, inlet air temperature and mass flow rate of air. Two outputs (exit water temperature to cooling tower and exit air temperature to second stage of air compressor) were taken in ANN.
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