The contamination of soil with the wastes of oil industry products that are complex mixtures of hydrocarbons increased recently due to the large development of oil industries in Iraq. This study deals with the remediation of low permeability contaminated clayey soil by using the enhanced electrokinetic technique (EK). The contaminated soil samples obtained from Thi-Qar oil refinery plant in Al-Nassyriah city, where the byproducts of refinery plant are disposed into that site. The byproduct contaminant treated as total petroleum hydrocarbons (TPH) to avoid dealing and complexity of treating the individual minerals and compounds consisting the contaminant. The initial concentrations of TPH were (702.7, 1168, 1235) ppm in the contaminated soil samples NA10, NA11, and NA12 respectively. The remediation technique includes a bench-scale experimental study by applying the enhanced electrokinetic test on the soil sample NA12 that contains the higher concentration of TPH in compared with other soil samples. A constant DC voltage gradient of 1.0 VDC/cm was applied for a period of 10 days. This echnology was enhanced by using flushing solution of ethanol and deionized water, which was mixed in ratios of 30% and 70% respectively. The results of this study showed that the removal of TPH at the anode was about 15% and the concentration of TPH decreased at anode, which reflect the migration of TPH towards the cathode.
. In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction a
... Show MoreHe mentioned in this article the main types of corruption, which are political, moral, financial and administrative. Others may add other types of corruption, such as religious, scientific, media, informational and statistical corruption. At the global level, the focus is largely on financial corruption, although other types of corruption are no less bad than it. Financial corruption can be defined as all financial deviations in violation of general laws or the provisions of regulations, legislation, and procedures regulating the work of the state, private institutions and individuals and applied in state institutions and the private sector in general and inconsistent with the controls and instructions of financial control.
In th
... Show MoreBackground:Oriental sore occurs mostly in the
mediteranian region , North Africa ,and the Middle East .
Rodents are the main reservoir for the parasite . The wet
type caused by L. major is rural and the dry type caused by
L. tropica is urban and humans are presumably the only
reservoir. Sand fly vectors are involved in all forms.
Objectives: This study aimed to show the most
important bacterial infections concomitant with cutaneous
leishmaniasis .
Methods; The study was performed on 75 patients (ages
1-50 years ) from both sexes were attending Skin Diseases
Department of Ramadi General Hospital during the period
extended from January to June 2000. These patients were
clinically diagnosed as patients
Transactions on Engineering and Sciences
In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction acc
... Show MoreBackground: Neudesin is a peptide secreted in brain and adipose tissues that has neural and metabolic functions. Its role as regulator of energy expenditure leads to assumption that its level may be regulated depending on thyroid gland pathology. Objective: This study aimed to investigate serum neudesin levels in patients with thyroidism and to evaluate1 any possible relationship between plasma neudesin levels and thyroid hormone levels. Methods: The study included 100 women with newly diagnosed thyroidisim were subdivided into two groups: hyperthyroidism group (50 female patients with age ranged from 18 to 60 years) and hypothyroidism group (50 female patients with age ranged from 18 to 75 years). A control group (30 healthy females with a
... Show MoreIn this paper we reported the microfabrication of three-dimensional structures using two-photon polymerization (2PP) in a mixture of MEH-PPV and an acrylic resin. Femtosecond laser operating at 800nm was employed for the two-photon polymerization processes. As a first step in this project we obtained the better composition in order to fabricate microstructers of MEH-PPV in the resin via two-photon polymerzation. Acknowledgement:This research is support by Mazur Group, Harvrad Universirt.
In Automatic Speech Recognition (ASR) the non-linear data projection provided by a one hidden layer Multilayer Perceptron (MLP), trained to recognize phonemes, and has previous experiments to provide feature enhancement substantially increased ASR performance, especially in noise. Previous attempts to apply an analogous approach to speaker identification have not succeeded in improving performance, except by combining MLP processed features with other features. We present test results for the TIMIT database which show that the advantage of MLP preprocessing for open set speaker identification increases with the number of speakers used to train the MLP and that improved identification is obtained as this number increases beyond sixty.
... Show MoreSpelling correction is considered a challenging task for resource-scarce languages. The Arabic language is one of these resource-scarce languages, which suffers from the absence of a large spelling correction dataset, thus datasets injected with artificial errors are used to overcome this problem. In this paper, we trained the Text-to-Text Transfer Transformer (T5) model using artificial errors to correct Arabic soft spelling mistakes. Our T5 model can correct 97.8% of the artificial errors that were injected into the test set. Additionally, our T5 model achieves a character error rate (CER) of 0.77% on a set that contains real soft spelling mistakes. We achieved these results using a 4-layer T5 model trained with a 90% error inject
... Show MoreThis study had succeeded in producing a new graphical representation of James abacus called nested chain abacus. Nested chain abacus provides a unique mathematical expression to encode each tile (image) using a partition theory where each form or shape of tile will be associated with exactly one partition.Furthermore, an algorithm of nested chain abacus movement will be constructed, which can be applied in tiling theory.