Most Internet of Vehicles (IoV) applications are delay-sensitive and require resources for data storage and tasks processing, which is very difficult to afford by vehicles. Such tasks are often offloaded to more powerful entities, like cloud and fog servers. Fog computing is decentralized infrastructure located between data source and cloud, supplies several benefits that make it a non-frivolous extension of the cloud. The high volume data which is generated by vehicles’ sensors and also the limited computation capabilities of vehicles have imposed several challenges on VANETs systems. Therefore, VANETs is integrated with fog computing to form a paradigm namely Vehicular Fog Computing (VFC) which provide low-latency services to mobile vehicles. Several studies have tackled the task offloading problem in the VFC field. However, recent studies have not carefully addressed the transmission path to the destination node and did not consider the energy consumption of vehicles. This paper aims to optimize the task offloading process in the VFC system in terms of latency and energy objectives under deadline constraint by adopting a Multi-Objective Evolutionary Algorithm (MOEA). Road Side Units (RSUs) x-Vehicles Mutli-Objective Computation offloading method (RxV-MOC) is proposed, where an elite of vehicles are utilized as fog nodes for tasks execution and all vehicles in the system are utilized for tasks transmission. The well-known Dijkstra's algorithm is adopted to find the minimum path between each two nodes. The simulation results show that the RxV-MOC has reduced significantly the energy consumption and latency for the VFC system in comparison with First-Fit algorithm, Best-Fit algorithm, and the MOC method.
Renewable energy resources have become a promissory alternative to overcome the problems related to atmospheric pollution and limited sources of fossil fuel energy. The technologies in the field of renewable energy are used also to improve the ventilation and cooling in buildings by using the solar chimney and heat exchanger. This study addresses the design, construction and testing of a cooling system by using the above two techniques. The aim was to study the effects of weather conditions on the efficiency of this system which was installed in Baghdad for April and May 2020. The common weather in these months is hot in Baghdad. The test room of the design which has a size of 1 m3 was situated to face the geographical south. The te
... Show MoreThe present study aimed at examining the factors that affect the choice of A major among a sample of BA fe(male) students at the levels 3-8 in King Abdulaziz University (KAU), in Jeddah, Saudi Arabia. To meet this objective, a descriptive survey method was used together with a questionnaire that consisted of 4 axes to answer the central question: What are the factors affecting the choice of a major at the university? Results have shown that the item that measured the students’ ability to choose the major ranked (First); it was concerned with the effect on the students' choice of his/her major in the university. On the last position and with respect to this effect came the professional tendencies and desires. Results have also shown tha
... Show MoreObesity is an escalating health problem in developing countries. One to ten children worldwide are overweight in a report showed by the International Obesity Task Force. Ghrelin, orexigenic peptide, has 28 amino acids, it is considered the greatest remarkable promotion in the last two decades for understanding the physiological changes of action regulating food intake and hunger. Obestatin is a 23-amino acid peptide nearly connected to ghrelin that secures from substitutio
... Show MoreAutism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D
... Show MoreOxidative stress plays a crucial role in the pathogenesis of peripheral artery disease (PAD). This study aimed to investigate the effect of clopidogrel on oxidative stress in PAD patients. Seventy subjects were divided into three groups: PAD patients before treatment (B-PAD), PAD patients after treatment with clopidogrel (A-PAD), and healthy controls. Serum levels of superoxide dismutase (SOD), copper (Cu), zinc (Zn), manganese (Mn), and oxidized protein were measured. SOD activities were also determined. The results showed that SOD activities, and SOD specific activities were significantly decreased in PAD patients compared to healthy individuals. After treatment with clopidogrel, SOD activities, and SOD specific activities were continuous
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