Introduction: The aim of this study was to compare the reliability and the agreement of the Pederson and Pernambuco difficulty indexes in predicting the surgical extraction difficulty of the impacted mandibular third molars. Materials and methods: A prospective observational cohort study was conducted on 83 patients who had undergone surgical removal of impacted mandibular third molar. The difficulty of extraction was determined preoperatively according to the total scores obtained from the Pederson and Pernambuco difficulty indexes, the operative difficulty was determined by the surgical technique and the duration of extraction. The accuracy of prediction of the surgical difficulty and

Investments in shares represent an essential component of companies’ assets and a source of profit making resources. These investments are linked to the areas of trading and speculation, which is reflected on their market value, which makes accounting for and evaluating these investments require their own accounting standards, and thus several international standards were issued regarding this as well as a statement of their impact on growth Sustainable, as the research problem is to show the impact of measuring investments in shares according to international accounting and financial reporting standards on the sustainable growth of economic units, the research sample and its reflection on audit procedures. In accordance with i

Twenty five samples out of sixty wound swabs taken from burn patients were identified as P. aeruginosabacteria by conventional methods. Antibiotics susceptibility tests were performed against thirteen antibiotics. P. aeruginosa samples were treated with 0.5 mg/ml of Safranin O solution then irradiated with 532nm Q-switched Nd:YAG laser at four energy densities (0.324, 0.704, 1.380, and 1.831 J/cm2) for different times of 5, 8 and 11 minutes with 5Hz repetition rate. The viability, susceptibility to antibiotic and production of pyocyanin were determined before and after irradiation. The results showed that the number of CFU/ml of P. aeruginosa decreased with increasing the dose of irradiation. Complete killing of cells was observed at 1.8

Many academics have concentrated on applying machine learning to retrieve information from databases to enable researchers to perform better. A difficult issue in prediction models is the selection of practical strategies that yield satisfactory forecast accuracy. Traditional software testing techniques have been extended to testing machine learning systems; however, they are insufficient for the latter because of the diversity of problems that machine learning systems create. Hence, the proposed methodologies were used to predict flight prices. A variety of artificial intelligence algorithms are used to attain the required, such as Bayesian modeling techniques such as Stochastic Gradient Descent (SGD), Adaptive boosting (ADA), Decision Tre

The manual classification of oranges according to their ripeness or flavor takes a long time; furthermore, the classification of ripeness or sweetness by the intensity of the fruit’s color is not uniform between fruit varieties. Sweetness and color are important factors in evaluating the fruits, the fruit’s color may affect the perception of its sweetness. This article aims to study the possibility of predicting the sweetness of orange fruits based on artificial intelligence technology by studying the relationship between the RGB values of orange fruits and the sweetness of those fruits by using the Orange data mining tool. The experiment has applied machine learning algorithms to an orange fruit image dataset and performed a co

Many academics have concentrated on applying machine learning to retrieve information from databases to enable researchers to perform better. A difficult issue in prediction models is the selection of practical strategies that yield satisfactory forecast accuracy. Traditional software testing techniques have been extended to testing machine learning systems; however, they are insufficient for the latter because of the diversity of problems that machine learning systems create. Hence, the proposed methodologies were used to predict flight prices. A variety of artificial intelligence algorithms are used to attain the required, such as Bayesian modeling techniques such as Stochastic Gradient Descent (SGD), Adaptive boosting (ADA), Deci

This study aims to evaluate drinking water quality at the Al Wahda plant (WTP) in Baghdad city. A conventional water treatment plant with an average flow rate of 72.82 MLD. Water samples were taken from the influent and effluent of the treatment plant and analyzed for some physicochemical and biological parameters during the period from June to November 2020. The results of the evaluation indicate that treated water has almost the same characteristics as raw water; in other terms, the plant units do not remove pollutants as efficiently as intended. Based on this, the station appears to be nothing more than a series of water passage units. However, apart from Total dissolved solids, the mean values of all parameters in the study were