Recent growth in transport and wireless communication technologies has aided the evolution of Intelligent Transportation Systems (ITS). The ITS is based on different types of transportation modes like road, rail, ocean and aviation. Vehicular ad hoc network (VANET) is a technology that considers moving vehicles as nodes in a network to create a wireless communication network. VANET has emerged as a resourceful approach to enhance the road safety. Road safety has become a critical issue in recent years. Emergency incidents such as accidents, heavy traffic and road damages are the main causes of the inefficiency of the traffic flow. These occurrences do not only create the congestion on the road but also increase the fuel consumption and pollute the environment. Emergency messages notify the drivers about road accidents and congestions, and how to avoid the dangerous zones. This paper classifies the emergency messages schemes into three categories based on relay node, clustering and infrastructure. The capabilities and limitations of the emergency messages schemes are investigated in terms of dissemination process, message forward techniques, road awareness and performance metrics. Moreover, it highlights VANET-based challenges and open research problems to provide the solutions for a safer, more efficient and sustainable future ITS.
The current research aims to identify: 1) the challenges facing blended education from the point of view of teachers of students with disabilities. 2) The challenges facing blended education from the point of view of teachers of students with disabilities according to the gender variable (males-females). 3) The challenges facing blended education from the point of view of teachers of students with disabilities, according to the academic qualifications of graduates
(institute-bachelors-masters). 4) The challenges facing blended education from the point of view of male and female teachers, according to the functional service period with students with disabilities (less than 8 years - from 9 to 15 years - 16 years and above). 5) the
... Show MoreTraining has an effect on employees’ performances. Accordingly, the person who is responsible for employees’ development must figure out the most effective way to train and develop employees. Central Michigan University (CMU) has recognized the importance of providing appropriate training for employees who have a duty in advising students. The reason is that these employees have a significant impact on students’ educational performances. Thus, special attention to this category of employees is needed to improve advising quality. This research attempted to explore the impact of training on academic advising at CMU. Face-to-face interviews and online surveys were used as data collection tools for this study. The study scope c
... Show MoreBackground: Understanding the challenges facing nurses toward providing care to patients with cerebrovascular accidents is the initial step in developing strategies to address these challenges, thereby ensuring high-quality care. Aim: The study aimed to assess the challenges experienced by nurses in delivering care to patients with CVAs in neurological wards. Results: Of the 80 questionnaire participants in the qualitative part, (MS = 0.66) reported a "moderate" rating as an overall assessment. These challenges are divided into workload (MS = 0.53) at a moderate rate, the psychological burden (MS = 0.85) at a high rate, the supporting materials (MS = 0.85) at a high rate, the sense of responsibility (MS = 0.77) at a high rate, and the role
... Show MoreThis study aims to design unified electronic information system to manage students attendance in Lebanese French university/Erbil, as a system that simplifies the process of entering and counting the students absence, and generate absence reports to expel students who passed the acceptable limit of being absent, and by that we can replace the traditional way of using papers to count absence, with a complete electronically system for managing students attendance, in a way that makes the results accurate and unchangeable by the students.
In order to achieve the study's objectives, we designed an information syst
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Many water supplies are now contaminated by anthropogenic sources such as domestic and agricultural waste, as well as manufacturing activities, the public's concern about the environmental effects of wastewater contamination has grown. Several traditional wastewater treatment methods, such as chemical coagulation, adsorption, and activated sludge, have been used to eliminate pollution; however, there are several drawbacks, most notably high operating costs, because of its low operating and repair costs, the usage of aerobic waste water treatment as a reductive medium is gaining popularity. Furthermore, it is simple to produce and has a high efficacy and potential to degrade pollu
... Show MoreThe rapid sprawl in urban areas caused by excessive production and consumption of goods (as driven by local poor social choices) has inevitably resulted in a major burden due to environmental degradation worldwide. Unfortunately, these traditional models of urban planning fail to properly account for the intricacies that permeate a modern city and are deficient in terms of their approach as they shape themselves within an environment largely divorced from natural systems, resulting in vast mismanagement of resources, guiding cities down trajectories where growth destroys both physical and cultural landscapes. As cities suffer from increasing scarcity, we advocate for regeneration and resilience to be embedded in advanced urban design approa
... Show MoreThis 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%.