In this research paper, two techniques were used to treat the drill cuttings resulting from the oil-based drilling fluid. The drill cuttings were taken from the southern Rumaila fields which prepared for testing and fixed with 100 gm per sample and contaminated with two types of crude oil, one from Rumaila oilfields with Sp.gr of 0.882 and the other from the eastern Baghdad oilfield with Sp.gr of 0.924 besides contamination levels of 10% and 15% w/w in mass. Samples were treated first with microwave with a power applied of 540 & 180 watts as well as a time of 50 minutes. It was found that the results reached below 1% w/w in mass, except for two samples they reached below 1.5% w/w in mass. Then, the sample of 1.41% w/w in mass, which has the highest contamination level after microwave treatment, was treated on three groups of earthworms. After the appropriate conditions, samples were prepared for treating by earthworms and for an incubation period of 21 days, the results highlighted the effectiveness of the succession process by reaching concentrations below 0.92%, 0.65%, and 0.42% w/w in mass.
The degradation of Toluidine Blue dye in aqueous solution under UV irradiation is investigated by using photo-Fenton oxidation (UV/H2O2/Fe+). The effect of initial dye concentration, initial ferrous ion concentration, pH, initial hydrogen peroxide dosage, and irradiation time are studied. It is found put that the removal rate increases as the initial concentration of H2O2 and ferrous ion increase to optimum value ,where in we get more than 99% removal efficiency of dye at pH = 4 when the [H2O2] = 500mg / L, [Fe + 2 = 150mg / L]. Complete degradation was achieved in the relatively short time of 75 minutes. Faster decolonization is achieved at low pH, with the optimal value at pH 4 .The concentrations of degradation dye are detected by spectr
... Show MoreAlzheimer's disease (AD) increasingly affects the elderly and is a major killer of those 65 and over. Different deep-learning methods are used for automatic diagnosis, yet they have some limitations. Deep Learning is one of the modern methods that were used to detect and classify a medical image because of the ability of deep Learning to extract the features of images automatically. However, there are still limitations to using deep learning to accurately classify medical images because extracting the fine edges of medical images is sometimes considered difficult, and some distortion in the images. Therefore, this research aims to develop A Computer-Aided Brain Diagnosis (CABD) system that can tell if a brain scan exhibits indications of
... Show MoreThe pollution producing from textile industries effluents is growing since the years, due to at discharged lots of it in water without treatment. The resulting effluent is colourful, highly toxic, and poses a significant environmental hazard. This problem can be solved by using enzymic biological treatment, where the Congo red dye was used with concentrations (100,200,300,500) mg /L, pH values (3,4,5,6,7,8), and variable temperatures (25,35,45)°C, the best removal of Congo red (CR) dye under optimum conditions for degradation was at concentration of 100 mg/L, at (pH 6, 25 °C) with efficiency of 99.85 % using the peroxidase enzyme extracted from red radish plant, while the removal percentage decreased when increase dye concentration
... Show MoreDuring COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve
... Show MoreDeep learning has recently received a lot of attention as a feasible solution to a variety of artificial intelligence difficulties. Convolutional neural networks (CNNs) outperform other deep learning architectures in the application of object identification and recognition when compared to other machine learning methods. Speech recognition, pattern analysis, and image identification, all benefit from deep neural networks. When performing image operations on noisy images, such as fog removal or low light enhancement, image processing methods such as filtering or image enhancement are required. The study shows the effect of using Multi-scale deep learning Context Aggregation Network CAN on Bilateral Filtering Approximation (BFA) for d
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This Paper aims to know the modern approaches of determining the Qiblah and its ruling in Islamic Faqah, as well as to find out the required in the identity of the Qiblah or the eye, and the care of the advanced Jurists in this matter, and to present some of their sayings on the issue. we have followed the Descriptive analytical method of the aspects of the jurists ’difference in what is required when facing the qiblah either the eye or aspect, the approach of several demands branched out from each topic, which were answered in the theoretical framework of the research, and the research concluded with the most important results: The need to receive the eye of the qiblah for the worshiper who is close to it and it is no
... Show MoreBackground: The incidence of maternal mortality in
placenta previa accrete is 7%,and its preoperative
diagnosis is of a great value.
Objective: to evaluate the efficacy of transabdominal
color Doppler ultrasound in diagnosing placenta
previa accreta and inccreta. Color Doppler imaging
criteria used in: includes diffuse parenchymal
placental lacunar flow, focal intra parenchymal
placental lacunar flow and bladder uterine serosa
interphase hyper-vascularity.
Design: Prospective study on patients from
January2007 to January 2008.
Patients and method: 48patients with one caesarean
section or more and with persistent anterior placenta
previa diagnosed by transabdominal ultrasound were
examined by c
In this paper, Bayes estimators of Poisson distribution have been derived by using two loss functions: the squared error loss function and the proposed exponential loss function in this study, based on different priors classified as the two different informative prior distributions represented by erlang and inverse levy prior distributions and non-informative prior for the shape parameter of Poisson distribution. The maximum likelihood estimator (MLE) of the Poisson distribution has also been derived. A simulation study has been fulfilled to compare the accuracy of the Bayes estimates with the corresponding maximum likelihood estimate (MLE) of the Poisson distribution based on the root mean squared error (RMSE) for different cases of the
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