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 (
The research has been talked on specific an important notions concerning with the dimensions of effectiveness of good governance and sustainable development inside all Arab states, So that the scientific article reflected the role of investments in various sections of institutional business by draw attention toward different projects about analyzing the whole political reality according to the standard indications of political and social stability on the regional level and international aspects. Therefore, the study resembled scientific contains and the dimensions of political reform and administrative overhauling within governmental system in order to achieve all raw objectives for sustainable development. All international and
... Show MoreThe aims of the research is to know the role of Organisational learning in building talent management strategies in the Ministry of Science and Technology , where we see the challenges facing organizations today dictate now and in the future activation of scientific expertise to meet these challenges and the dissemination of these concepts within the priorities and data organizational culture of these organizations despite having a lot of the importance of organizational knowledge and learning applications .Despite learning and adopting some of the organizations have to enhance their competitiveness, we find a lot of organizations, including (The ministry researched) still do not realize the importance of the role of organization
... Show MoreThis research deals with unusual approach for analyzing the Simple Linear Regression via Linear Programming by Two - phase method, which is known in Operations Research: “O.R.”. The estimation here is found by solving optimization problem when adding artificial variables: Ri. Another method to analyze the Simple Linear Regression is introduced in this research, where the conditional Median of (y) was taken under consideration by minimizing the Sum of Absolute Residuals instead of finding the conditional Mean of (y) which depends on minimizing the Sum of Squared Residuals, that is called: “Median Regression”. Also, an Iterative Reweighted Least Squared based on the Absolute Residuals as weights is performed here as another method to
... Show MoreThe research discusses the obstacles that faced the Iraqi strategic performance in achieving sustainable development after the election of the first Iraqi government in 2005 and the most important strategies to overcome these obstacles.
يواجه العراق تحديات مائية خطيرة نتيجة التغيرات المناخية، مثل انخفاض معدلات هطول الأمطار، ارتفاع درجات الحرارة، وزيادة معدلات الجفاف والتصحر، فهذه التحديات تتطلب إستراتيجيات فعالة لإدارة الموارد المائية بشكل مستدام، وهو ما يمكن تحقيقه من خلال تبني التطورات التكنولوجية الحديثة في مجال الحوكمة البيئية ، و يركز هذا البحث على دور التحول الرقمي والتقنيات الذكية في تعزيز كفاءة إدارة المياه، إذ يمكن لتطبيقا
... Show MoreThe main objective of this work was to adopt an environmentally friendly technology with enhanced results. The technology of magnetic water (MW) treatment system can be used in concrete mixture production instead of potable water (PW) to improve both workability and strength. Two types of concrete were adopted: normal concreter production with two grades 25 and 35 MPa and the self-compacted concrete (SCC) with 35 MPa grade. The concrete mixes containing MW instead of PW results showed that, for 25 MPa grade, an improvement in a compressive strength of 15.1, 14.8, and 10.2% was achieved for 7, 28, and 90 days, respectively. For 35 MPa grade, an improvement of 13.6, 11.5, and
The main objective of this work was to adopt an environmentally friendly technology with enhanced results. The technology of magnetic water (MW) treatment system can be used in concrete mixture production instead of potable water (PW) to improve both workability and strength. Two types of concrete were adopted: normal concreter production with two grades 25 and 35 MPa and the self-compacted concrete (SCC) with 35 MPa grade. The concrete mixes containing MW instead of PW results showed that, for 25 MPa grade, an improvement in a compressive strength of 15.1, 14.8, and 10.2% was achieved for 7, 28, and 90 days, respectively. For 35 MPa grade, an improvement of 13.6, 11.5, and
To achieve the goals, the researcher followed the design of equal and independent groups of partial control and post-test . The research has chosen the Institute of Fine Arts in the area Almansour area as deliberate sample where three sections of students have been chosen and the number of students is (69) students. The researcher conducted equivalence in the variables (age, and IQ , and the overall rate for grade III). in diagnostic phase, (21) concepts of alternative image out of (46) concepts have been identified in addition to the goals of formulation of acquisition concepts according to the three processes (definition, discrimination and application). Achievement test has been
... Show MoreThe deep learning algorithm has recently achieved a lot of success, especially in the field of computer vision. This research aims to describe the classification method applied to the dataset of multiple types of images (Synthetic Aperture Radar (SAR) images and non-SAR images). In such a classification, transfer learning was used followed by fine-tuning methods. Besides, pre-trained architectures were used on the known image database ImageNet. The model VGG16 was indeed used as a feature extractor and a new classifier was trained based on extracted features.The input data mainly focused on the dataset consist of five classes including the SAR images class (houses) and the non-SAR images classes (Cats, Dogs, Horses, and Humans). The Conv
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