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 (
Shadow removal is crucial for robot and machine vision as the accuracy of object detection is greatly influenced by the uncertainty and ambiguity of the visual scene. In this paper, we introduce a new algorithm for shadow detection and removal based on different shapes, orientations, and spatial extents of Gaussian equations. Here, the contrast information of the visual scene is utilized for shadow detection and removal through five consecutive processing stages. In the first stage, contrast filtering is performed to obtain the contrast information of the image. The second stage involves a normalization process that suppresses noise and generates a balanced intensity at a specific position compared to the neighboring intensit
... Show MoreSorting and grading agricultural crops using manual sorting is a cumbersome and arduous process, in addition to the high costs and increased labor, as well as the low quality of sorting and grading compared to automatic sorting. the importance of deep learning, which includes the artificial neural network in prediction, also shows the importance of automated sorting in terms of efficiency, quality, and accuracy of sorting and grading. artificial neural network in predicting values and choosing what is good and suitable for agricultural crops, especially local lemons.
In this paper, we investigate two stress-strength models (Bounded and Series) in systems reliability based on Generalized Inverse Rayleigh distribution. To obtain some estimates of shrinkage estimators, Bayesian methods under informative and non-informative assumptions are used. For comparison of the presented methods, Monte Carlo simulations based on the Mean squared Error criteria are applied.
This research includes the study of dual data models with mixed random parameters, which contain two types of parameters, the first is random and the other is fixed. For the random parameter, it is obtained as a result of differences in the marginal tendencies of the cross sections, and for the fixed parameter, it is obtained as a result of differences in fixed limits, and random errors for each section. Accidental bearing the characteristic of heterogeneity of variance in addition to the presence of serial correlation of the first degree, and the main objective in this research is the use of efficient methods commensurate with the paired data in the case of small samples, and to achieve this goal, the feasible general least squa
... Show MoreThere is no doubt that teachers are the leaders of positive changing in community where they directed the students and build their brains. In our current generation that characterized by accelerated technological development that communication changes, economic and politics, needs from the teacher an active leadership skills that match with the soul of our generation and contribute in confrontation the current challenges and the future challenges in the form that lead to create a conscious generation where they will be a basic brick for the future community where the listeners looking forward the education where they support the continuity communication of develop process, economy, scientifically and in all life fields. In our study we take
... Show MoreAbstract- Asymptomatic or clinically silent kidney stones are possibly serious because, in their expected passage, they may cause infection, obstruction and renal impairment. The purpose of this study was to determine the prevalence of silent kidney stones in a sample of Baghdad population and consider how this value could affect the justification for a screening system. To our best knowledge, this is the first study of its kind conducted in Iraq. We investigated 714 consecutive patients who sustained an abdominal ultrasound at our hospital with further kidney screening. All these patients did not have clinical signs and symptoms of nephrolithiasis. Age, sex, the indication for ultrasound, the size, side, and the number of the disco
... Show MoreThe Red Palm Weevil (RPW), Rhynchophorus ferrugineus (Olivier, 1790) is a devastating invasive pest of palm trees, invading the Iraqi date palm tree in 2015 for the first time in Safwan county, Basrah province. The Red Palm weevil has been categorized as a quarantine pest of date palm trees worldwide. In this study, a five years monitoring program has been achieved by scouting the invasive pest RPW population in Safwan county by using visual sampling and Pheromone baited traps.
The results indicated that the number of infested palms, increased from 12 trees in 2015 to 111 in 16 orchards in 2016. The number of the infested palms was minimized to 3 trees in the county in 2019 due to the management protocol of the Ministry of Agriculture
It is the regression analysis is the foundation stone of knowledge of statistics , which mostly depends on the ordinary least square method , but as is well known that the way the above mentioned her several conditions to operate accurately and the results can be unreliable , add to that the lack of certain conditions make it impossible to complete the work and analysis method and among those conditions are the multi-co linearity problem , and we are in the process of detected that problem between the independent variables using farrar –glauber test , in addition to the requirement linearity data and the lack of the condition last has been resorting to the
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