The study aims to predict Total Dissolved Solids (TDS) as a water quality indicator parameter at spatial and temporal distribution of the Tigris River, Iraq by using Artificial Neural Network (ANN) model. This study was conducted on this river between Mosul and Amarah in Iraq on five positions stretching along the river for the period from 2001to 2011. In the ANNs model calibration, a computer program of multiple linear regressions is used to obtain a set of coefficient for a linear model. The input parameters of the ANNs model were the discharge of the Tigris River, the year, the month and the distance of the sampling stations from upstream of the river. The sensitivity analysis indicated that the distance and discharge have the most significant affect on the predicted TDS concentrations. The results showed that a network with (8) hidden neurons was highly accurate in predicting TDS concentration. The correlation coefficient (r), root mean square error (RMSE) and mean absolute percentage error (MAPE) between measured data and model outputs were calculated as 0.975, 113.9 and 11.51%, respectively for testing data sets. Comparisons between final results of ANNs and multiple linear regressions (MLR) showed that the ANNs model could be successfully applied and provides high accuracy to predict TDS concentrations as a water quality parameter.
This research represents a practical attempt applied to calibrate and verify a hydraulic model for the Blue Nile River. The calibration procedures are performed using the observed data for a previous period and comparing them with the calibration results while verification requirements are achieved with the application of the observed data for another future period and comparing them with the verification results. The study objective covered a relationship of the river terrain with the distance between the assumed points of the dam failures along the river length. The computed model values and the observed data should conform to the theoretical analysis and the overall verification performance of the model by comparing it with anothe
... Show MoreErosion and deposition are natural phenomena in many estuaries that can cause morphological changes, leading to navigation and offshore structure problems. Many previous studies have focused on investigating the morphological changes of estuaries depending on different parameters and their combined effects with erosion and deposition processes, such as maximum flow amplitude, waves, currents, tidal flow, storms, rising sea elevation, maximum turbidity, salinity, and bed roughness height as input parameters. These studies are based on field measurements and numerical simulations by using topographic surveys, soil samples, satellite images, geological data, and bathymetric maps with the aid of ArcGIS. Some of these studies examine the
... Show MoreJoint diseases, such as osteoarthritis, induce pain and loss of mobility to millions of people around the world. Current clinical methods for the diagnosis of osteoarthritis include X-ray, magnetic resonance imaging, and arthroscopy. These methods may be insensitive to the earliest signs of osteoarthritis. This study investigates a new procedure that was developed and validated numerically for use in the evaluation of cartilage quality. This finite element model of the human articular cartilage could be helpful in providing insight into mechanisms of injury, effects of treatment, and the role of mechanical factors in degenerative
conditions, this three-dimensional finite element model is a useful tool for understanding of the stress d
Predicting permeability is a cornerstone of petroleum reservoir engineering, playing a vital role in optimizing hydrocarbon recovery strategies. This paper explores the application of neural networks to predict permeability in oil reservoirs, underscoring their growing importance in addressing traditional prediction challenges. Conventional techniques often struggle with the complexities of subsurface conditions, making innovative approaches essential. Neural networks, with their ability to uncover complicated patterns within large datasets, emerge as a powerful alternative. The Quanti-Elan model was used in this study to combine several well logs for mineral volumes, porosity and water saturation estimation. This model goes be
... Show MoreContamination of the operating theatre is a major cause of nosocomial infection. This report aimed to show the types of microorganisms and their percentages cultivated from operating theatres of 16 health directorates of 14 Iraqi governorates (3 health directorates in Baghdad and 1 in each other 13 governorates) that was reported to the Pollution Control Section at Ministry of Health in Iraq from first of January to the end of June 2018. The data of all health directorates have included cultivation taken from governmental and private hospitals. Duhok, Erbil, Sulaymaniyah, and Nineveh were not involved in this report due to unavailability of their data during the above period. Escherichia coli, Pseudomonas aeruginosa and Staphylococcus aureu
... Show MoreOndansetron hydrochloride (ONH) is a very bitter, potent antiemetic drug used for the treatment and/or prophylaxis of chemotherapy or radiotherapy or postoperative induced emesis. The objective of this study is to formulate and evaluate of taste masked fast dissolving tablet (FDTs) of ONH to increase patient compliance.
ONH taste masked granules were prepared by solid dispersion technique using Eudragit E100 polymer as an inert carrier. Solvent evaporation and fusion melting methods were used for such preparation.
Completely taste masking with zero release of drug in phosphate buffer pH 6.8was obtained from granules prepared by solvent evaporation method using drug: polymer ratio of 1:2, from which four formulas pas
... Show MoreCoupling reaction of 4-amino antipyrene with 2,6-dimethyl phenol gave bidentate azo ligand. The prepared ligand was identified by Microelemental Analysis, 1HNMR, FT-IR and UV-Vis spectroscopic techniques. Treatment of the prepared ligand with the following metal ions (CoII, NiII, CuII, ZnII, CdII, and HgII) in aqueous ethanol with a 1:2 M:L ratio and at optimum pH, yielded a series of neutral complexes of the general formula [M(L)2Cl2]. The prepared complexes were characterized using flame atomic absorption, (C.H.N) Analysis, FT-IR and UVVis spectroscopic methods as well as magnetic susceptibility and conductivity measurements. Chloride ion content was also evaluated by (Mohr method). The nature of the complexes formed were studied followin
... Show MoreCoupling reaction of 2-amino benzoic acid with phenol gave the new bidentate azo ligand. The prepared ligand was identified by Microelemental Analysis, FT-IR and UV-Vis spectroscopic technique. Treatment of the prepared ligand with the following metal ions (CoII, NiII, CuII and ZnII) in aqueous ethanol with a 1:2 M:L ratio and at optimum pH, yielded a series of neutral complexes of the general formula [M(L)2]. The prepared complexes were characterized using flame atomic absorption, (C.H.N) Analysis, FT-IR and UV-Vis spectroscopic methods as well as magnetic susceptibility and conductivity measurements. The nature of the complexes formed were studied following the mole ratio and continuous variation methods, Beer's law obeyed over a concentr
... Show MorePosible interference of vamin with the activity of several antibiotics against E. coli was evaluated in vitro. In MBS- glucose medium, significant growth delay was induced by 8 ug/ml of terramycin (oxytetracycline- polymyxin B) and bactrim (trimethoprim-sulphamethoxazole), and by 16 ug/ml of refocin, lincomycin, and chloramphenicol. Rapid growth inhibition was induced by 32 ug/ml of all an- tibiotic tested separately. Significant inactivation of up to 64 ug/ml of licomycin and bactrim was in- duced by the addition of vamin at a concentration of 1:20 v/v of the medium. This effect was found to be due to the presence of specific amino acids in vamin. Among them is valine, leucine, isoleucine tyrosine, tryptophan, phenylalanine, cysteine, meth
... Show MoreArtificial Intelligence Algorithms have been used in recent years in many scientific fields. We suggest employing artificial TABU algorithm to find the best estimate of the semi-parametric regression function with measurement errors in the explanatory variables and the dependent variable, where measurement errors appear frequently in fields such as sport, chemistry, biological sciences, medicine, and epidemiological studies, rather than an exact measurement.