The hydrological process has a dynamic nature characterised by randomness and complex phenomena. The application of machine learning (ML) models in forecasting river flow has grown rapidly. This is owing to their capacity to simulate the complex phenomena associated with hydrological and environmental processes. Four different ML models were developed for river flow forecasting located in semiarid region, Iraq. The effectiveness of data division influence on the ML models process was investigated. Three data division modeling scenarios were inspected including 70%–30%, 80%–20, and 90%–10%. Several statistical indicators are computed to verify the performance of the models. The results revealed the potential of the hybridized support vector regression model with a genetic algorithm (SVR-GA) over the other ML forecasting models for monthly river flow forecasting using 90%–10% data division. In addition, it was found to improve the accuracy in forecasting high flow events. The unique architecture of developed SVR-GA due to the ability of the GA optimizer to tune the internal parameters of the SVR model provides a robust learning process. This has made it more efficient in forecasting stochastic river flow behaviour compared to the other developed hybrid models.
This study ,the samples were collected from "118 patients " suffering from burn wound contaminated with Pseudomonas aeruginosa and 100 health individuals (male and female ) as a control group ,the samples were wound swap and blood sample . Chromatography technique was employed to extract and purify cell wall containing lipopolysaccharide by using P. aeruginosa isolate ATCC 15692,the purification done by addition of ammonuium sulfate, sodium dodecyl sulfat (SDS) anddialysis, gel filtration chromatography by using sepharose-4B. Immunogenicity of LPS component was determined by mice injection under the skin ,then Ab concentration agai
... Show MoreTwo different approaches, univariate and multivariate (simplex method), have been used to obtain the optimum conditions for the quantitative Spectrophotometric determination of Eu3+ using Solochrome violet RS (3-Hydroxy-4-(2-hydroxy phenyl azo) naphthalene -1sulfonic acid) (SVRS) as a chromogenic reagent. The investigation shows that Eu3+ ion forms a wine-red complex with SVRS in alkaline buffer solution having a maximum absorbance at 464 nm against reagent blank. Calibration graphs obtained under univariate and simplex were found to be linear in the range of (0.30-8.0) µg/ml with detection limit 0.061µg/ml and molar absorptivity of 9877.66 L/mol.cm and (0.40-10.0)µg/ml with
... Show MoreIn this study, new heterocyclic compounds were synthesized through the cyclization reactions of o-phenylenediamine (1) with various organic reagents. Benzodiazepine derivatives (2-4) were obtained by reaction of (1) with ethylacetoacetate, malonic acid and acetyl acetone.Treatment of compound (1) with chloroacetamide, chloroacetic acid, p-bromophenacyl bromide and oxalic acid dihydrate afforded quinoxaline derivatives (5-8), respectively. Reaction of compound (1) with benzoic acid, piperonal, cyclohexanone and carbon disulfide resulted in the formation of compounds (9-12), respectively. Finally, reaction of compound (12) with chloroacetic acid in the presence of potassium hydroxide produced compound (13).
The magnetic properties of a pure Nickel metal and Nickel-Zinc-Manganese ferrites having the chemical formula Ni0.1(Zn0.4Mn0.6)0.9Fe2O4 were studied. The phase formation and crystal structure was studied by using x-ray diffraction which confirmed the formation of pure single spinel cubic phase with space group (Fd3m) in the ferrite. The samples microstructure was studied with scanning electron microstructure and EDX. The magnetic properties of the ferrite and nickel metal were characterized by using a laboratory setup with a magnetic field in the range from 0-500 G. The ferrite showed perfect soft spinel phase behavior while the nickel sample showed higher magnetic loss an
... Show MoreThirty six bacteria were isolated from various sourcesc (soil, starch, cooked rice and other foods) and subjected to a series of primary screening tests to obtain the optimal isolation to production of amylase. The volume of producing zone by logal indicator for (Seven) isolates of the secondary screening by measuring the enzymatic activity and specific enzymatic activity. The isolate A4 was found to be the most efficient for production of amylase. Then this isolate was diagnosed through microscopic, vitek 2 system technique. in addition by gentic diagnesis through gene 16s of the genes nitrogen bases by use the polymerase chain reaction (PCR) which reached 1256 bases. In comparison to the available information at the National Center for
... Show MoreMixed ligand complexes of Cu(II), Ni(II) and Co(II) with metformin(MTF) as primary ligand and cysteine(Cys) as secondary ligand have been prepared and characterized by elemental analysis, atomic absorption, molar conductivity, magnetic susceptibility measurements, FTIR,UV-Vis ,1H-NMR and 13C-NMR spectral studies. The elemental analysis, atomic absorption data reveal the formation of [1:1:1] [M:MTF:Cys] complexes.The electronic spectra and magnetic moment measurements reveal the presence of complexes in an octahedral geometry and the molar conductivity studies of the complexes indicate their non-electrolytic nature. The infrared and NMR spectral were showed that the chelation behaviour of the ligands towards selected transition metal ions
... Show MoreIn this paper, the conditions of persistence of a mathematical model, consists from
a predator interacting with stage structured prey are established. The occurrence of
local bifurcation and Hopf bifurcation are investigated. Finally, in order to confirm
our obtained analytical results, numerical simulations have been done for a
hypothetical set of parameter values .
Convolutional Neural Networks (CNN) have high performance in the fields of object recognition and classification. The strength of CNNs comes from the fact that they are able to extract information from raw-pixel content and learn features automatically. Feature extraction and classification algorithms can be either hand-crafted or Deep Learning (DL) based. DL detection approaches can be either two stages (region proposal approaches) detector or a single stage (non-region proposal approach) detector. Region proposal-based techniques include R-CNN, Fast RCNN, and Faster RCNN. Non-region proposal-based techniques include Single Shot Detector (SSD) and You Only Look Once (YOLO). We are going to compare the speed and accuracy of Faster RCNN,
... Show MoreThis study was aimed to assess the impact of vermicompost, glutathione, and their interaction on beetroot (Beta vulgaris L.) growth, yield, and antioxidant traits. The experiment carried out at vegetable field of the College of Agricultural Engineering Sciences - University of Baghdad during fall season 2019. The experiment was conducted using factorial arrangement within Randomized Complete Block Design with two factors and three replicates (3X3X3). Applying vermicompost before cultivation represented the first factor (0, 15, 30 ton.ha-1), which symbolized (V0, V1, V2). Glutathione (0, 75, 150 mg.L-1) which symbolized (G0, G1, G2) represented the second factor. Results showed the superiority of secondary interaction treatment V2G2
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