Spelling 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

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 a

Objective (s): To determine factors associated with the pregnancy complications (Maternal age, education,
obstetrical history, gravidity, birth space interval, and smoking).
Methodology: A cross-sectional study conducted at Al- washash & Bab-almoadham primary health care
centers. The sample was (non probability convenient sample) which included (550) pregnant women. The
study started from 1st April 2014 to 1
st of April 2015. The data was collected by direct interview using
special questionnaire to obtain socio-demographic information.
Results: the result shows that mean age of the subjects was 26.5± 4.39 years, 57.8% were housewives, the
sample included 103 premature uterine contractions, 98 pregnancy induce

Pseudomonas aeruginosa is an opportunistic pathogen responsible for serious infections. At least three different exopolysaccharides, alginate, polysaccharide synthesis locus (Psl), and pellicle exopolysaccharide (Pel) make up the biofilm matrix in P. aeruginosa . The effect of temperature on the biofilm formation and gene expression was examined by microtiter plate and real-time quantitative polymerase chain reaction (qRT-PCR). To be able to determine the effect of temperature on biofilm formation and gene expression of P. aeruginosa, 303 clinical and environmental samples were collected. Pseudomonas aeruginosa was isolated from 61 (20.1%) and 48 (15.8%) of the clinical and e

The study was preformed for investigating of Salmonella from meat, and compared Vidas UP Salmonella (SPT) with the traditional methods of isolation for Salmonella , were examined 42 meat samples (Beef and Chicken) from the Local and Imported From local markets in the city of Baghdad from period December 2013 -February 2014 the samples were cultured on enrichment and differential media and examined samples Vidas, and confirmed of isolates by cultivation chromgenic agar, biochemical tests ,Api20 E systeme , In addition serological tests , and the serotypes determinate in the Central Public Health Laboratory / National Institute of Salmonella The results showed the contamination in imported meat was more than in the local meat 11.9% and 2

In this study, a theoretical scenario has been used to calculate the electronic current in sensitizer N3 molecule contact to TiO2 semiconductor for electrons in functional solar cells. It is known to play an important role on the compute the eficiency of solar cell. Some parameters of electronic current such as the transition energy, driving force energy, barrier height coupling overlapping values are determined. Transition energy is a necessary parameter to calculate the electronic current in solar cell with using wide polarity solvents Acetic acid, 2-Methoxyethanol, 1-Butanol, Methyl alcohol, chloroform, N,N-Dimethylacetamide and Ethyl alcohol via the quantum donor-acceptor system. Here, we show the results of transition energy can be var

This research aims to provide insight into the Spatial Autoregressive Quantile Regression model (SARQR), which is more general than the Spatial Autoregressive model (SAR) and Quantile Regression model (QR) by integrating aspects of both. Since Bayesian approaches may produce reliable estimates of parameter and overcome the problems that standard estimating techniques, hence, in this model (SARQR), they were used to estimate the parameters. Bayesian inference was carried out using Markov Chain Monte Carlo (MCMC) techniques. Several criteria were used in comparison, such as root mean squared error (RMSE), mean absolute percentage error (MAPE), and coefficient of determination (R^2). The application was devoted on dataset of poverty rates acro