Wastewater projects are one of the most important infrastructure projects, which require developing strategic plans to manage these projects. Most of the wastewater projects in Iraq don’t have a maintenance plan. This research aims to prepare the maintenance management plan (MMP) for wastewater projects. The objective of the research is to predict the cost and time of maintenance projects by building a model using ANN. The research sample included (15) completed projects in Wasit Governorate, where the researcher was able to obtain the data of these projects through the historical information of the Wasit Sewage Directorate. In this research artificial neural networks (ANN) technique was used to build two models (cost

The current research deals with practical studies that explain to the Iraqi consumer multiple instances about the phenomenon of water hammer which occur in the water pipeline operating with pressure. It concern a practical study of the characteristics of this phenomenon and economically harmful to the consumer the same time. Multiple pipe fittings are used aimed to reduce this phenomenon and its work as alternatives to the manufactured arresters that used to avoid water hammer in the sanitary installations, while the consumer did not have any knowledge as to the non-traded for many reasons, including the water pressure decreases in the networks and the use of consumer pumps to draw water directly from the network. Study found a number of

Based on a finite element analysis using Matlab coding, eigenvalue problem has been formulated and solved for the buckling analysis of non-prismatic columns. Different numbers of elements per column length have been used to assess the rate of convergence for the model. Then the proposed model has been used to determine the critical buckling load factor () for the idealized supported columns based on the comparison of their buckling loads with the corresponding hinge supported columns . Finally in this study the critical buckling factor () under end force (P) increases by about 3.71% with the tapered ratio increment of 10% for different end supported columns and the relationship between normalized critical load and slenderness ratio was g

The research focuses on determination of best location of high elevated tank using the required head of pump as a measure for this purpose. Five types of network were used to find the effect of the variation in the discharge and the node elevation on the best location. The most weakness point was determined for each network. Preliminary tank locations were chosen for test along the primary pipe with same interval distance. For each location, the water elevation in tank and pump head was calculated at each hour depending on the pump head that required to achieve the minimum pressure at the most weakness point. Then, the sum of pump heads through the day was determined. The results proved that there is a most economical lo

The convolutional neural networks (CNN) are among the most utilized neural networks in various applications, including deep learning. In recent years, the continuing extension of CNN into increasingly complicated domains has made its training process more difficult. Thus, researchers adopted optimized hybrid algorithms to address this problem. In this work, a novel chaotic black hole algorithm-based approach was created for the training of CNN to optimize its performance via avoidance of entrapment in the local minima. The logistic chaotic map was used to initialize the population instead of using the uniform distribution. The proposed training algorithm was developed based on a specific benchmark problem for optical character recog

The green synthesis of nickel oxide nanoparticles (NiO-NP) was investigated using Ni(NO3)2 as a precursor, olive tree leaves as a reducing agent, and D-sorbitol as a capping agent. The structural, optical, and morphology of the synthesized NiO-NP have been characterized using ultraviolet–visible spectroscopy (UV-Vis), X-ray crystallography (XRD) pattern, Fourier transform infrared spectroscopy (FT-IR) and scanning electron microscope (SEM) analysis. The SEM analysis showed that the nanoparticles have a spherical shape and highly crystalline as well as highly agglomerated and appear as cluster of nanoparticles with a size range of (30 to 65 nm). The Scherrer relation has been used to estimate the crystallite size of NiO-NP which ha

A UV-Vis spectrophotometry method was developed for the determination of metoclopramide hydrochloride in pure and several pharmaceutical preparations, such as Permosan tablets, Meclodin syrups, and Plasil ampoules. The method is based on the diazotization reaction of metoclopramide hydrochloride with sodium nitrate and hydrochloric acid to yield the diazonium salt, which is then reacted with 3,5-dimethyl phenol in the presence of sodium hydroxide to form a yellow azo dye. Calibration curves were linear in the range from 0.3 to 6.5 µg/mL, with a correlation coefficient of 0.9993. The limits of detection and quantification were determined and found to be 0.18 and 0.61 µg/mL, respectively. Accuracy and precision were also determined b

A simple, environmental friendly and selective sample preparation technique employing porous membrane protected micro-solid phase extraction (μ-SPE) loaded with molecularly imprinted polymer (MIP) for the determination of ochratoxin A (OTA) is described. After the extraction, the analyte was desorbed using ultrasonication and was analyzed using high performance liquid chromatography. Under the optimized conditions, the detection limits of OTA for coffee, grape juice and urine were 0.06 ng g−1, 0.02 and 0.02 ng mL−1, respectively while the quantification limits were 0.19 ng g−1, 0.06 and 0.08 ng mL−1, respectively. The recoveries of OTA from coffee spiked at 1, 25 and 50 ng g−1, grape juice and urine samples at 1, 25 and 50 ng mL