Background: Fixed orthodontic appliances impede the maintenance of oral hygiene and result in plaque accumulation leads to enamel demineralization caused by acids produced by bacteria. Studies on plaque control strategies in orthodontic populations are limited. This might be caused by difficulties in the quantitative evaluation of dental plaque because the teeth have various levels of bracket coverage, and different tooth sizes and malocclusions, making the traditional categorical indices complex. The present study aims to evaluate the effect of different hygiene protocols on plaque quantity on bands with different attachments. Materials and method: Twenty patients had four bands within the orthodontic appliance. Then randomly divided into

A seemingly uncorrelated regression (SUR) model is a special case of multivariate models, in which the error terms in these equations are contemporaneously related. The method estimator (GLS) is efficient because it takes into account the covariance structure of errors, but it is also very sensitive to outliers. The robust SUR estimator can dealing outliers. We propose two robust methods for calculating the estimator, which are (S-Estimations, and FastSUR). We find that it significantly improved the quality of SUR model estimates. In addition, the results gave the FastSUR method superiority over the S method in dealing with outliers contained in the data set, as it has lower (MSE and RMSE) and higher (R-Squared and R-Square Adjus

The organizational integration forms a necessity according to McKinsey model, especially for service organizations. In the context of various service sector developments, importance adoption of compact mechanisms by these organizations to upgrade their services has increased and senior management must be more aware of environmental, competitive and developmental requirements. It gets more important when it shows in an organization seeking at excellence of making services within its policies and strategies. Subject organizational integration dimensions (strategy, structure, systems, style, staff, shared values, and skills) are effective components in directing behaviors of employees and organization. This motivated both researcher

The educational service industry is one of the most negatively affected industries by the spread of the COVID-19 pandemic. Government agencies have taken many measures to slow its spread, and then restrict movement and gatherings and stop recreational activities. Furthermore, the repercussions of the curfew had a significant impact due to the interruption in actual attendance for students and employees, and the severity of the Covid-19 crisis and its (economic, social, security, humanitarian and behavioral) effects on all societies and work sectors is no secret to anyone. Iraq, like other countries, was also affected by the negative impact of Covid-19 pandemic in all fields of institutional work, especially public fields, and specifically t

Abstract. In this paper, a high order extended state observer (HOESO) based a sliding mode control (SMC) is proposed for a flexible joint robot (FJR) system in the presence of time varying external disturbance. A composite controller is integrated the merits of both HOESO and SMC to enhance the tracking performance of FJR system under the time varying and fast lumped disturbance. First, the HOESO estimator is constructed based on only one measured state to precisely estimate unknown system states and lumped disturbance with its high order derivatives in the FJR system. Second, the SMC scheme is designed based on such accurate estimations to govern the nominal FJR system by well compensating the estimation errors in the states and the lumped

Gypseous soil, which covers vast area in west, middle, east and south west regions of Iraq exhibit acceptable strength properties when dry, but it is weak and collapsible when it comes in touch with moisture from rain or other sources. When such weak soil is adopted for earth reinforced embankment construction, it may exhibit hazardous situation. Gypseous soil was investigated for the optimum liquid asphalt requirements of both cutback and emulsion using the one-dimensional unconfined compression strength test. The optimum fluid content was 13% (7% of cutback with 6% water content), and 17% (9% of emulsion with 8% water content). A laboratory model box of 50x50x25 cm was used as a representative of embankment; soil or asphalt stabilize

In this paper, compared eight methods for generating the initial value and the impact of these methods to estimate the parameter of a autoregressive model, as was the use of three of the most popular methods to estimate the model and the most commonly used by researchers MLL method, Barg method  and the least squares method and that using the method of simulation model  first order autoregressive through the design of a number of simulation experiments and the different sizes of the samples.

In this article we  study a single stochastic process model for the evaluate the assets pricing and stock.,On of the models le'vy . depending on the so –called Brownian subordinate as it has been depending on the so-called Normal Inverse Gaussian (NIG). this article aims as the estimate that the parameters of his model using my way (MME,MLE) and then employ those  estimate of the parameters is the study of stock returns and evaluate asset pricing for both the united Bank and Bank of North which their data were taken from the Iraq stock Exchange.

which showed the results to a preference MLE on MME based on the standard of comparison the average square e

One of the most important features of the Amazon Web Services (AWS) cloud is that the program can be run and accessed from any location. You can access and monitor the result of the program from any location, saving many images and allowing for faster computation. This work proposes a face detection classification model based on AWS cloud aiming to classify the faces into two classes: a non-permission class, and a permission class, by training the real data set collected from our cameras. The proposed Convolutional Neural Network (CNN) cloud-based system was used to share computational resources for Artificial Neural Networks (ANN) to reduce redundant computation. The test system uses Internet of Things (IoT) services th