This study aimed to develop a more accurate model for predicting the widths of unerupted canines and premolars in Emirati children, using deep learning and machine learning techniques. Dental models of 380 Emirati individuals aged 15–30 years were collected. The mesiodistal widths of permanent teeth were measured with a standardized orthodontic digital caliper. Regression models were developed using linear regression, Support Vector Regression (SVR; machine learning), and Artificial Neural Networks (ANN; deep learning). The widths of mandibular lateral incisors, central incisors, and the summed width of mandibular incisors were used as predictors. A two-tailed paired t-test was used to assess differences between measured and predicted values. Model performance was evaluated using pass rate (defined as predictions within ± 1 mm of measured values), mean absolute error (MAE), root mean square error (RMSE), and coefficient of determination (R
2
). The dataset was randomly divided into training (70%), validation (20%), and test (10%) sets. A statistically significant difference (
Disasters, crises and wars are a serious and unforeseen threat. The capacity of the early warning system to monitor such crises is therefore crucial. The ability to make quick decisions in a short time is necessary to prevent crises from occurring. Here, the role and effectiveness of the early warning system emerges through its ability to monitor, record and analyze signals. It can also be evidenced by its ability to immediately convey these indicators to the concerned authorities to take measures that ensure these conflicts and disasters do not worsen. The system’s ability to detect disasters and crises, identify the crisis and its type, and use the scientific method and common sense to deal with it is something that contributes to findi
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Characterized by the Ordinary Least Squares (OLS) on Maximum Likelihood for the greatest possible way that the exact moments are known , which means that it can be found, while the other method they are unknown, but approximations to their biases correct to 0(n-1) can be obtained by standard methods. In our research expressions for approximations to the biases of the ML estimators (the regression coefficients and scale parameter) for linear (type 1) Extreme Value Regression Model for Largest Values are presented by using the advanced approach depends on finding the first derivative, second and third.
In this research, Artificial Neural Networks (ANNs) technique was applied in an attempt to predict the water levels and some of the water quality parameters at Tigris River in Wasit Government for five different sites. These predictions are useful in the planning, management, evaluation of the water resources in the area. Spatial data along a river system or area at different locations in a catchment area usually have missing measurements, hence an accurate prediction. model to fill these missing values is essential.
The selected sites for water quality data prediction were Sewera, Numania , Kut u/s, Kut d/s, Garaf observation sites. In these five sites models were built for prediction of the water level and water quality parameters.
This research deals with the role of Qur’anic intents in facilitating and facilitating the understanding of the reader and the seeker of knowledge of the verses of the Holy Qur’an, particularly in the doctrinal investigations (prophecies), and the feature that distinguishes reference to the books of the intentions or the intentional interpretations is that it sings from referring to the books of speakers and delving into their differences in contractual issues and facilitating access To the meanings, purposes and wisdom that the wise street wanted directly from the rulings and orders contained in the verses of the wise Qur’an.
Accurate pore and fracture pressure detection is a major step in successful drilling operations design. The overestimation of these parameters absolutely leads to serious problems throughout and after well drilling. This study is concerned with the characterization and analysis of the most significant diagenetic processes that degrade or improve the reservoir characteristics of the Mauddud Formation in the Badra oil field. The primary goal of this research is to estimate the pore pressure and fracture pressure using well logging data by Techlog 2015 software in order to assess the impact on the estimation of the mud weight window (MWW). The estimated values of formation pressures are then analyzed according to different diagenetic p
... Show MoreThe present study stresses two of the most significant aspects of linguistic approach: Pragmatics” and the “Speech Act Theory”, revealing its importance and the stages and levels of development through Hebrew language’s speech acts analysis including (political speech, the Holy Bible, Hebrew stories).
Chronologically, Pragmatics has always been the center of linguists’ interests due to its importance in linguistic decryptions, particularly, through “Speech Act Theory” that has been initiated and developed by the most prominent philosophers and linguistics.
The prese
... Show MoreIndustries copper a craft that requires precision and patience great in the processes of industrialization and execution of product launches brass designs and a variety of forms , and the goal of research into the possibility of the use of modern technologies in the development of industries copper local , and identifies research study models of industries copper local to the city of Baghdad , and are available in the markets for the period from (200 - 2011) , Chapter II Multi industries copper local and technical in the copper industry , and after analysis models the sample was the most important conclusions : can work forms a multi- product copper formations deep or window using the technique work motifs and patterns. - formations deco
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