Self-driving automobiles are prominent in science and technology, which affect social and economic development. Deep learning (DL) is the most common area of study in artificial intelligence (AI). In recent years, deep learning-based solutions have been presented in the field of self-driving cars and have achieved outstanding results. Different studies investigated a variety of significant technologies for autonomous vehicles, including car navigation systems, path planning, environmental perception, as well as car control. End-to-end learning control directly converts sensory data into control commands in autonomous driving. This research aims to identify the most accurate pre-trained Deep Neural Network (DNN) for predicting the steerin

The establishment of a high quality service in oral health care achieved by a member of dental professional is an important feature of any system of peer review in dentistry. This protocol attempts to discuss two crucial elements (I) suitability and feasibility of treatment modality and (II) quality of treatment performed to Iraqi patients. The Iraq endodontic society is designing a standardized protocol for endodontic treatment following the quality guidelines of European society of Endodontology (2006) to meet the highest standard of care generally given by competent practitioners. The Iraqi endodontic society has the expertise and professional responsibility clinically relevant to empower the dental profession through creating significan

The dose rate for bremsstrahlung radiation from beta particles with energy (1.710) MeV and (2.28) MeV which comes from (32P and 90Y) beta source respectively have been calculated through six materials (polyethylene, wood, aluminum, iron, tungsten and lead) for first shielding material with thickness (x=1) mm which are putting between beta sources and second shield (polyethylene, aluminum and lead) with thickness (1, 2 &4) mm have been calculated. The distance between beta source and second shield is constant (D=1) cm. This dose rate was found by program called Rad Pro Calculator (version 3.26). The results of dose rate of beta particles were plotted as a function to the atomic number (Z) for first shield materials for each

The dose rate for bremsstrahlung radiation from beta particles with energy (1.710) MeV and (2.28) MeV which comes from (32P and 90Y) beta source respectively have been calculated through six materials (polyethylene, wood, aluminum, iron, tungsten and lead) for first shielding material with thickness (x=1) mm which are putting between beta sources and second shield (polyethylene, aluminum and lead) with thickness (1, 2 &4) mm have been calculated. The distance between beta source and second shield is constant (D=1) cm. This dose rate was found by program called Rad Pro Calculator (version 3.26). The results of dose rate of beta particles were plotted as a function to the atomic number (Z) for first shield materials for each

Background: Lung cancer is a common disease for patients over the age of 50 years, especially males due to smoking habits. This study aimed to compare the modulation complexity score (MCS) for the advanced treatment planning techniques which the intensity modulated radiation therapy (IMRT) and volumetric modulated arc therapy (VMAT). Materials and Methods: Thirty patients who had non-small lung cancerous tumors on their left side participated in this study. The range ages were 68 to 98 years, the heights were between 151 and 182cm and they having weights from 46 to 79 kg. For Each patient will create two plans dial using two different techniques, which will be Intensity Modulated Radiation Therapy (IMRT) and Volumetric Modulated Arc Therapy

 A mixture model is used to model data that come from more than one component. In recent years, it became an effective tool in drawing inferences about the complex data that we might come across in real life. Moreover, it can represent a tremendous confirmatory tool in classification observations based on similarities amongst them. In this paper, several mixture regression-based methods were conducted under the assumption that the data come from a finite number of components. A comparison of these methods has been made according to their results in estimating component parameters. Also, observation membership has been inferred and assessed for these methods. The results showed that the flexible mixture model outperformed the

 A mixture model is used to model data that come from more than one component. In recent years, it became an effective tool in drawing inferences about the complex data that we might come across in real life. Moreover, it can represent a tremendous confirmatory tool in classification observations based on similarities amongst them. In this paper, several mixture regression-based methods were conducted under the assumption that the data come from a finite number of components. A comparison of these methods has been made according to their results in estimating component parameters. Also, observation membership has been inferred and assessed for these methods. The results showed that the flexible mixture model outperformed the others

Maximizing the net present value (NPV) of oil field development is heavily dependent on optimizing well placement. The traditional approach entails the use of expert intuition to design well configurations and locations, followed by economic analysis and reservoir simulation to determine the most effective plan. However, this approach often proves inadequate due to the complexity and nonlinearity of reservoirs. In recent years, computational techniques have been developed to optimize well placement by defining decision variables (such as well coordinates), objective functions (such as NPV or cumulative oil production), and constraints. This paper presents a study on the use of genetic algorithms for well placement optimization, a ty

         It is clear that correct application of antibiotic prophylaxis can reduce the incidence of infection  resulting from the bacterial  inoculation in a variety of clinical situations; it cannot   prevent  all  infections  any  more  than it  can   eliminate  all  established infections. Optimum  antibiotic   prophylaxis  depends on:  rational  selection  of the drug(s),  adequate  concentrations  of the  drug  in  the  tissues that  are at risk, and attention to  timing  of  administration.  Moreover,  the  risk  of

         It is clear that correct application of antibiotic prophylaxis can reduce the incidence of infection  resulting from the bacterial  inoculation in a variety of clinical situations; it cannot   prevent  all  infections  any  more  than it  can   eliminate  all  established infections. Optimum  antibiotic   prophylaxis  depends on:  rational  selection  of the drug(s),  adequate  concentrations  of the  drug  in  the  tissues that  are at risk, and attention to  timing  of  administration.  Moreover,  the  risk  of  infection  in  some situations  does not outweigh  the risks which  attend the administration of even the safest antibiotic drug. The aim of this study was to comp