Background:Open reduction and internal fixation (ORIF) of using miniplates and screws is the treatment of choice of mandibular fractures. It is important to know both: the region where the bone providesafirm anchorage, andthe topography of the dental apices and inferior alveolar nerve to avoiddamaging them when inserting the screw. The aim of this study is to determine the thickness of buccal cortical plate and that of buccal bone at the parasymphysis and mandibular body, thereby determining the area that provide afirm anchorage and the maximum length of mono-cortical screws that can be safely placed in these regions without injuring the tooth roots or mandibular nerve. Materials and Methods:The sample of the present study was 110 Iraqi sub

Sediment accumulated in sewers is a major concern source as it induces numerous operational and environmental problems. For instance, during wet weather flow, the re-suspension of this sediment accompanied by the combined sewer overflow may cause huge pollutant load to the receiving water body. The characteristics of the sewer sediment are important as it shapes its behaviour and determines the extent of the pollution load. In this paper, an investigation of sewer sediment and its characterization is done for a case study in Baghdad city. Sediment depth covers more than 50% of the sewer cross-sectional area; several operational causes are comprised to cause this huge depths of sediment depositions. The testing and analysis of the s

      Faces of the individual in his life many stressful events, which includes expertise undesirable, and events may involve a lot of sources of tension and the risk factors and threats in all areas of life, and this would make the stressful events play a role in the genesis of many diseases physical.            

The high blood pressure is one of the most Actual manifestations of mental stress in the present scale physical disorders which may frequently in men relative to women, which may be caused by spasms in the blood vessels.      

With the rapid development of smart devices, people's lives have become easier, especially for visually disabled or special-needs people. The new achievements in the fields of machine learning and deep learning let people identify and recognise the surrounding environment. In this study, the efficiency and high performance of deep learning architecture are used to build an image classification system in both indoor and outdoor environments. The proposed methodology starts with collecting two datasets (indoor and outdoor) from different separate datasets. In the second step, the collected dataset is split into training, validation, and test sets. The pre-trained GoogleNet and MobileNet-V2 models are trained using the indoor and outdoor se