Background: Chronic periodontitis (CP) is greatly prevalent condition of inflammatory behavior. Salivary biomarker total antioxidants capacity (T-AOC) status, may be related to both periodontal condition and oral hygiene. Aims of the study: To assess the level of salivary T-AOC of patients with chronic periodontitis in comparison to healthy control and to correlate between the level of this marker with the clinical periodontal parameters (plaque index (PLI), gingival index (GI), bleeding on probing (BOP), probing pocket depth (PPD), and clinical attachment level (CAL)). Materials and Methods: Ninety subjects of males and females with an age ranged between (35-55) years were participated in this study. Participants were divided into two grou

Background: Spleen is a hemopoietic organ which is capable of supporting elements of different systems. It is affected by several groups of diseases; inflammatory, hematopoietic, reticuloendothelial proliferation, portal hypertension and storage diseases. Ultrasound (US) may detect mild splenomegaly before it is clinically palpable. Knowledge of the normal range of spleen size in the population being examined is a prerequisite. Racial differences in splenic length could result in incorrect interpretation of splenic measurements and such differences would make it difficult to standardize expected splenic length and to determine non- palpable splenic enlargement.Objectives: To measure the normal values of splenic lengthin Iraqi subjects an

     This research aims to study the performance of operations to provide nursing services, which included dimensions (quality, timeliness, leadership skills, behavioral manifestations, relationships with others, problem-solving and decision-making, job performance) and its effects in nursing performance. The research to prove the value of the performance of service delivery processes dimensions by nursing staffs working in Iraqi hospitals, nursing and measuring performance. To find out the nature of nursing services, and a comparison between hospitals to measure the extent of the application dimensional among themselves, and that by relying on the dimensions of a global study, which was measu

In this paper, we investigate the automatic recognition of emotion in text. We perform experiments with a new method of classification based on the PPM character-based text compression scheme. These experiments involve both coarse-grained classification (whether a text is emotional or not) and also fine-grained classification such as recognising Ekman’s six basic emotions (Anger, Disgust, Fear, Happiness, Sadness, Surprise). Experimental results with three datasets show that the new method significantly outperforms the traditional word-based text classification methods. The results show that the PPM compression based classification method is able to distinguish between emotional and nonemotional text with high accuracy, between texts invo

In all applications and specially in real time applications, image processing and compression plays in modern life a very important part in both storage and transmission over internet for example, but finding orthogonal matrices as a filter or transform in different sizes is very complex and importance to using in different applications like image processing and communications systems, at present, new method to find orthogonal matrices as transform filter then used for Mixed Transforms Generated by using a technique so-called Tensor Product based for Data Processing, these techniques are developed and utilized. Our aims at this paper are to evaluate and analyze this new mixed technique in Image Compression using the Discrete Wavelet Transfo

This research describes a new model inspired by Mobilenetv2 that was trained on a very diverse dataset. The goal is to enable fire detection in open areas to replace physical sensor-based fire detectors and reduce false alarms of fires, to achieve the lowest losses in open areas via deep learning. A diverse fire dataset was created that combines images and videos from several sources. In addition, another self-made data set was taken from the farms of the holy shrine of Al-Hussainiya in the city of Karbala. After that, the model was trained with the collected dataset. The test accuracy of the fire dataset that was trained with the new model reached 98.87%.

In this research, the one of the most important model and widely used in many and applications is linear mixed model, which widely used to analysis the longitudinal data that characterized by the repeated measures form .where estimating linear mixed model by using two methods (parametric and nonparametric) and used to estimate the conditional mean and marginal mean in linear mixed model ,A comparison between number of models is made to get the best model that will represent the mean wind speed in Iraq.The application is concerned with 8 meteorological stations in Iraq that we selected randomly and   then we take a monthly data about wind speed over ten years Then average it over each month in corresponding year, so we g