As cities across the world grow and the mobility of populations increases, there has also been a corresponding increase in the number of vehicles on roads. The result of this has been a proliferation of challenges for authorities with regard to road traffic management. A consequence of this has been congestion of traffic, more accidents, and pollution. Accidents are a still major cause of death, despite the development of sophisticated systems for traffic management and other technologies linked with vehicles. Hence, it is necessary that a common system for accident management is developed. For instance, traffic congestion in most urban areas can be alleviated by the real-time planning of routes. However, the designing of an efficie

تسعى تركيا ضمن سياساتها المائية ومنذ زمن بعيد وبأصرار على تنفيذ المزيد من بناء السدود والمشاريع التخزينية المائية على حوضي دجلة والفرات، الامر الذي يؤدي بالضرورة الى تناقص معدل الواردات المائية لنهري دجلة والفرات الداخلة للاراضي العراقية .وبالتالي التأثير على مقومات التنمية الزراعية العربية بشكل عام والتنمية الزراعية بالعراق بشكل خاص ومن ثم تهديد الامن الغذائي الوطني.

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A nonlinear filter for smoothing color and gray images
corrupted by Gaussian noise is presented in this paper. The proposed
filter designed to reduce the noise in the R,G, and B bands of the
color images and preserving the edges. This filter applied in order to
prepare images for further processing such as edge detection and
image segmentation.
The results of computer simulations show that the proposed
filter gave satisfactory results when compared with the results of
conventional filters such as Gaussian low pass filter and median filter
by using Cross Correlation Coefficient (ccc) criteria.

       In the current worldwide health crisis produced by coronavirus disease (COVID-19), researchers and medical specialists began looking for new ways to tackle the epidemic. According to recent studies, Machine Learning (ML) has been effectively deployed in the health sector. Medical imaging sources (radiography and computed tomography) have aided in the development of artificial intelligence(AI) strategies to tackle the coronavirus outbreak. As a result, a classical machine learning approach for coronavirus detection from      Computerized Tomography (CT) images was developed. In this study, the convolutional neural network (CNN) model for feature extraction and support vector machine (SVM) for the classification of axial

High smoke emissions, nitrogen oxide and particulate matter typically produced by diesel engines. Diminishing the exhausted emissions without doing any significant changes in their mechanical configuration is a challenging subject. Thus, adding hydrogen to the traditional fuel would be the best practical choice to ameliorate diesel engines performance and reduce emissions. The air hydrogen mixer is an essential part of converting the diesel engine to work under dual fuel mode (hydrogen-diesel) without any engine modification. In this study, the Air-hydrogen mixer is developed to get a homogenous mixture for hydrogen with air and a stoichiometric air-fuel ratio according to the speed of the engine. The mixer depends on the balance between th

In this study, a mathematical model is presented to study the chemisorption of two interacting atoms on solid surface in the presence of laser field. Our mathematical model is based on the occupation numbers formula that depends on the laser field which we derived according to Anderson model for single atom adsorbed on solid surface. Occupation numbers formula and chemisorption energy formula are derived for two interacting atoms (as a diatomic molecule) as they approach to the surface taking into account the correlation effects on each atom and between atoms. This model is characterized by obvious dependence of all relations on the system variables and the laser field characteristics which gives precise description for the molecule –

Monetary policy is an important part of the economic policy to influence the monetary aspect of stabilization, for this reason the research will seek to clarify the extent of the impact of monetary policy in achieving monetary stability in Iraq during the chosen research period, because the Iraqi economy suffers from monetary instability due to political and security turmoil, Therefore, an effective and effective monetary policy is required in terms of reducing inflationary pressures to reach the required monetary stability, in order to create the appropriate monetary environment for the work of the economic and productive sectors. Thus, the research adopted a basic hypothesis that monetary policy in Iraq has a clear impact on achieving mon

Density functional theory calculations are employed to investigate the impact of edifenphos molecule on the reactivity and electronic sensitivity of pure calcium oxide (CaO) nanocluster. The strong adsorption of edifenphos molecule on CaO nanocluster occurs by the sulfur head of the adsorbate, and the amount of the energy of this adsorption is around − 84.40 kcal/mol. The adsorption of edifenphos molecules results in a decrease in the values of Eg of CaO from 4.67 to 3.56 eV, as well as an increase in the electrical conductance. Moreover, the work function of CaO nanocluster is significantly affected, which changes the current of the field emission electron. Eventually, the recovery time is calculated around 99 ms at ambient temperature f