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.
Estimation of elements: Pb, Zn, Mn, Cd, and Cu, which were conducted seasonally from October-2021 till March-2022 in residential areas of Baghdad City using Geoaccumulation index (Igeo), enrichment factor ratios (EF), the factor of contamination (CF), contamination degree (Cd), index of pollution load (PLI) and index of potential ecological risk (Eif). The overall contamination factor in the research area is limited from low contamination with Cu, Mn, and Zn, moderately contaminated to very high contamination with Pb and Cd, while the assessment according to the I-geo index shows categories that vary from a slightly polluted to unpolluted by those examined heavy metals. The pollution load index indicates that the soils in some resi
... Show MoreIn this study the rate of infection in acute and chronic Toxoplasma gondii parasite that causes toxoplasmosis was determined. This study was Included 120 blood samples that collected from pregnant women revisions to some clinics and laboratories in Baghdad civil as well as 10 blood samples from non-infected women as a control group. All blood samples were collected in the first three months of the pregnancy period for detection toxoplasmosis by using serological tests of test kit ( Toxo , IgG.,Toxo , IgM ). To detect antibodies specialized type of IgG &IgM in acute and the chronic infection by Electro Clia manner using a Roche Cobas e411. The results showed that the total infection rate was (55.83)%, the rate of infection in acu
... Show MoreProjects suspensions are between the most insistent tasks confronted by the construction field accredited to the sector’s difficulty and its essential delay risk foundations’ interdependence. Machine learning provides a perfect group of techniques, which can attack those complex systems. The study aimed to recognize and progress a wellorganized predictive data tool to examine and learn from delay sources depend on preceding data of construction projects by using decision trees and naïve Bayesian classification algorithms. An intensive review of available data has been conducted to explore the real reasons and causes of construction project delays. The results show that the postpo
A total number of 68 water samples was revealed 20 isolates being Staphylococcus aureus. Irrigation water isolates represented 25% of isolates while wastewater 75%. all isolates were identified by morphological, microscopial, biochemical tests and VITEK®2 Compact. Bacterial isolates were subjected to 16 antibiotics, all irrigation water and wastewater isolates were resistant to penicillin while they were fully sensitive to Ciprofloxcin. Irrigation water isolates showed relatively greater multi-drug resistance than wastewater, wherein irrigation water isolates showed 100% multi-drug resistance while wastewater isolates showed 73.3% multi-drug resistance, indicating the ability of S. aureus MDR to move from one site to another, which means t
... Show MoreSmoking is the inhalation of smoke tobacco burning that cover with narghile and cigarettes. There are a many problems result smoking such as, deterioration of health in general, undesirable social phenomenon, waste of money and time and stress.This study design to identify the effects of smoking narghile and cigarettes on levels of MPO, HCY and lipidprofil via determination of those parameters in cohort younger of Baghdad city. So to found the correlation coefficient of MPO and those parameters in groups that smoking cigarette and narghiledaily.As well as, to consider the MPO as biomarker to predictor coronary heart diseases. Increased levels of MPO, HCY total cholesterol (TC), triglyceride (TG), very low-density lipoprotein (VLDL) and low-
... Show MoreEmissions of particulate matter from nanopapers as well as inks and organic solvents during the printing operationand copying machines constitute a threat to human health, especially with long time exposure in closed working environments. The present study was conducted in some printing houses and copying centers of Baghdad city during February and April .The studyproved the occurrence of an air pollution problem concerning lead and zinc contents in all the study sites. The levels of Pb, Zn and Cu were collected by low volume sampler from the air of the study sites then filter papers digested and determined the heavy metals by flame atomic spectrophotometer. Particulate matter was measured by Aerocet, Microtector meter device was use
... Show MoreBreast cancer is a heterogeneous disease characterized by molecular complexity. This research utilized three genetic expression profiles—gene expression, deoxyribonucleic acid (DNA) methylation, and micro ribonucleic acid (miRNA) expression—to deepen the understanding of breast cancer biology and contribute to the development of a reliable survival rate prediction model. During the preprocessing phase, principal component analysis (PCA) was applied to reduce the dimensionality of each dataset before computing consensus features across the three omics datasets. By integrating these datasets with the consensus features, the model's ability to uncover deep connections within the data was significantly improved. The proposed multimodal deep
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