This study aims to evaluate the performance of the sewage treatment plant in Al- Diwaniya, one of cities in the southern part in Iraq. This evaluation could be used to facilitate effluent quality assessment or optimal process control of the plant. The influent reaching the plant is considered a medium to strong in strength with BOD5/COD ratio in the range 0.23 and 0.69 which can be considered an easily degradable sewage by the biological processes performed by the activated sludge unit. The quality of the effluent was found to be higher than the Iraqi standards for disposal to water bodies. The BOD5/COD ratios of the treated sewage varied over a wide range as low of 0.13 to 1.48 indicating operational problems in the plant. Regressio
... Show MoreThis study aims to evaluate the performance of the sewage treatment plant in Al-Diwaniya, one of cities in the southern part in Iraq. This evaluation could be used to facilitate effluent quality assessment or optimal process control of the plant. The influent reaching the plant is considered a medium to strong in strength with BOD5/COD ratio in the range 0.23 and 0.69 which can be considered an easily degradable sewage by the biological processes performed by the activated sludge unit. The quality of the effluent was found to be higher than the Iraqi standards for disposal to water bodies. The BOD5/COD ratios of the treated sewage varied over a wide range as low of 0.13 to 1.48 indicating operational problems in the plant. Regression ana
... Show MoreThe investigation of earth dams under significant earthquake loads, such as catastrophic earthquakes, is a critical subject in dynamic evaluation. Damage mitigation and structural performance during an earthquake are crucial considerations for an earthen dam. However, Iraq and its neighbors have experienced frequent earthquake activity, including the 2017 Halabja Earthquake, which may have damaged some existing earth dams, posing a higher risk of severe earthquake-induced damage than a cyclic shock. Therefore, assessing the dam’s safety is crucial for protecting downstream communities and determining the best strategies to prevent slope stability failure in the face of frequent s
During a period of two years, from January 1995 till December 1996, the first survey on fish parasites in Bahr Al-Najaf depression, mid Iraq, was achieved. A total of 6992 fishes, belonging to 11 species, were collected and inspected for external and internal parasites. These fishes were infected with three protozoans (Ichthyophthirius multifiliis, Trichodina domerguei and Myxobolus pfeifferi), two monogeneans (Dactylogyrus cornu and Gyrodactylus elegans), two digenetic trematodes (Clinostomum complanatum and Ascocotyle coleostoma), one nematode (Contracaecum sp.) and one acanthocephalan (Neoechinorhynchus iraqensis). Five fish species were recorded as new h
... Show MoreMotives for public exposure to specialized sports satellite channels and the gratifications achieved about it - Research presented by (Dr. Dr. Laila Ali Jumaa), Imam Al-Kadhim College (peace be upon him) - Department of Information-2021.
The research aims to know the extent of public exposure to specialized sports satellite channels, and what gratifications are achieved from them, and to reach scientific results that give an accurate description of exposure, motives and gratifications verified by that exposure, and the research objectives are summarized in the following:
- Revealing the habits and patterns of public exposure to specialized sports satelli
Densities ρ and viscosities η for several concentrations of amino acids (Serine, Cysteine and Threonine) at different temperatures (298.15, 303.15 and 308.15K) have been measured. On the basis of these data, the apparent molal volumes v , partial molal volumes at infinite dilution v , slope Sv , Gibbs free energy of activation for viscous flow of solution ∆G1,2 and Jones – Dole Bcoefficients were calculated the nature of solute-solvent and solute-solute interactions have been discussed in terms of the values of v , v , Sv and B-coefficents
Wildfire risk has globally increased during the past few years due to several factors. An efficient and fast response to wildfires is extremely important to reduce the damaging effect on humans and wildlife. This work introduces a methodology for designing an efficient machine learning system to detect wildfires using satellite imagery. A convolutional neural network (CNN) model is optimized to reduce the required computational resources. Due to the limitations of images containing fire and seasonal variations, an image augmentation process is used to develop adequate training samples for the change in the forest’s visual features and the seasonal wind direction at the study area during the fire season. The selected CNN model (Mob
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