Background: Bone density is a major factor that affect mini implant primarily stability; no Iraqi studies have evaluated bone density related to mini-implant placement for orthodontic anchorage at age 13 -15 years. The present research aims to evaluate gender, side and site differences in the bone density at various orthodontic implant sites for the maxillary alveolar bone. Materials and methods: Twenty nine individuals (16 males and 13 females) had subjected to clinical examination, then 64-multislice computed tomography scan data were evaluated and bone density was measured in Hounsfield unit at 21 points (9 points for each side and 3 points between the right and left central incisors) . Results: The results obtained showed that there ar

Use Almtafr axis to study the response component that isolates gave a positive response to the use of standard Almtafr which leads to lower the temperature and the number of cells at a temperature suitable Rifampicin resistant less than that TJ and similarly reflected on the frequency of mutations induced

Use Almtafr Alcderan orange, one of the factors Hashr Alttafaria to study Alatjabh isolates elected on the basis of specifications so that was a positive response with mutagen record and system consisting of three isolates used Alcderan orange graded concentrations and under specific Trov similar conditions Alttafar Pal NTG compared

Laser-Induced Breakdown Spectroscopy (LIBS) has been documented as an Atomic Emission Spectroscopy (AES) technique, utilising laser-induced plasma, in order to analyse elements in materials (gases, liquids and solid). The Nd:YAG laser passively Q-switched at 1064nm and 9ns pulse duration focused by convex lens with focal length 100 mm to generates power density 5.5×1012 Mw/mm2 with optical spectrum in the range 320-740 nm. Four soil samples were brought from different northern region of Iraq, northern region (Beiji, Sherkat, Serjnar and Zerkary).
The soil of the Northern region of Beige, Sherkat, Serjnar and Zarkary has abundant ratios of the elements P [0.08, 0.09, 0.18, 0.18] and Ca [0.61, 0.15, 0.92, 0.92] while it lack of Si [0.0

This work is concerned with the vibration attenuation of a smart beam interacting with fluid using proportional-derivative PD control and adaptive approximation compensator AAC. The role of the AAC is to improve the PD performance by compensating for unmodelled dynamics using the concept of function approximation technique FAT. The key idea is to represent the unknown parameters using the weighting coefficient and basis function matrices/vectors. The weighting coefficient vector is updated using Lyapunov theory. This controller is applied to a flexible beam provided with surface bonded piezo-patches while the vibrating beam system is submerged in a fluid. Two main effects are considered: 1) axial stretching of the vibrating beam that leads

     In this paper, we study some cases of a common fixed point theorem for classes of firmly nonexpansive and generalized nonexpansive maps. In addition, we establish that the Picard-Mann iteration is faster than Noor iteration and we used Noor iteration to find the solution of delay differential equation.

As a result of the significance of image compression in reducing the volume of data, the requirement for this compression permanently necessary; therefore, will be transferred more quickly using the communication channels and kept in less space in memory. In this study, an efficient compression system is suggested; it depends on using transform coding (Discrete Cosine Transform or bi-orthogonal (tap-9/7) wavelet transform) and LZW compression technique. The suggested scheme was applied to color and gray models then the transform coding is applied to decompose each color and gray sub-band individually. The quantization process is performed followed by LZW coding to compress the images. The suggested system was applied on a set of seven stand

   A comparison of double informative and non- informative priors assumed for the parameter of Rayleigh distribution is considered. Three different sets of double priors are included, for a single unknown parameter of Rayleigh distribution. We have assumed three double priors: the square root inverted gamma (SRIG) - the natural conjugate family of priors distribution, the square root inverted gamma – the non-informative distribution, and the natural conjugate family of priors - the non-informative distribution as double priors .The data is generating form three cases from Rayleigh distribution for different samples sizes (small, medium, and large). And Bayes estimators for the parameter is derived under a squared erro

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class