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

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

. 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

A finite element is a study that is capable of predicting crack initiation and simulating crack propagation of human bone. The material model is implemented in MATLAB finite element package, which allows extension to any geometry and any load configuration. The fracture mechanics parameters for transverse and longitudinal crack propagation in human bone are analyzed. A fracture toughness as well as stress and strain contour are generated and thoroughly evaluated. Discussion is given on how this knowledge needs to be extended to allow prediction of whole bone fracture from external loading to aid the design of protective systems.

Background: Optimal root canal retreatment was required safe and efficient removal of filling material from root canal. The aim of this in vitro study was to compare the efficacy of reciprocating and continuous motion of four retreatment systems in removal of root canal filling material. Materials and Methods: Forty distal roots of the mandibular first molars teeth were used in this study, these roots were embedded in cold clear acrylic,roots were instrumented using crown down technique and rotary ProTaper systemize Sx to size F2 ,instrumentation were done with copiousirrigation of 2.5% sodium hypochlorite and 17% buffered solution of EDTA was used as final irrigant followed by distilledwater, roots were obturated with AH26 sealer and Prota

In this study, the genus Xylocopa Latreille, 1802 (Hymenoptera: Apidae) was revised. There were 4 species registered in our investigations: X. hottentotta Smith, 1854; X. olivieri Lepeletier, 1841; X. pubescens Spinola, 1838 and X. valga Gerstäcker, 1872, the first species was described as being found for the first time for the insect fauna of Iraq, which were obtained from Solanum melogena L. flowers. Key to the species was constructed and supported by figures of the main diagnostic characters and some morphological features, illustrated and compared with other species, which are recorded in the current survey.

The present study aims to investigate the seroprevalence rate of Toxoplasma gondii infection and its relation to some demographic factors among males in Duhok province/Iraq. A total of 424 random blood samples were collected from the male population of different ages (18-60) years and different social-economic classes. Out of 424 samples examined, 108 (25.47%) were seropositive to the anti- T. gondii antibodies; 88 (20.75%) were found seropositive for IgG, while 20 (4.72%) samples were seropositive for IgM. Regarding occupation, the highest percentage for chronic toxoplasmosis was reported in workers followed by policemen and pensioners at rates of 23.96%, 23.6%, and 23.07%, respectively. The age group 18-30 y