Mobile Ad hoc Networks (MANETs) is a wireless technology that plays an important role in several modern applications which include military, civil, health and real-time applications. Providing Quality of Service (QoS) for this application with network characterized by node mobility, infrastructure-less, limitation resource is a critical issue and takes greater attention. However, transport protocols effected influential on the performance of MANET application. This study provides an analysis and evaluation of the performance for TFRC, UDP and TCP transport protocols in MANET environment. In order to achieve high accuracy results, the three transport protocols are implemented and simulated with four different network topology which are 5, 10, 30 and 50 nodes, respectively using well known Network Simulator (NS-2.35). Moreover, Constant Bit Rate (CBR) considered as a traffic source and On-demand Distance Vector (AODV) as the routing protocol. For evaluation performance, QoS metrics such as end-to-end delay, packet delivery ratio, throughput and jitter are measured. The results show that delay and jitter of TFRC are slightly less than UDP and TCP whereas UDP has the significantly better performance wise throughput.
Nowadays, there is increased interest in the biosynthesis of microbial melanin related to their numerous biological functions and applications in many fields, especially in medical fields, including immune-modulating, antimicrobial antibiotic, antiviral antivenin, anticancer, antitumor activity, and anti-biofilm activity. Pyomelanin is a hydrophobic macromolecule that is typically dark brown or black in color, formed by the oxidative polymerization of phenolic or indolic compounds. Pyomelanin is reported to be safe for consumption, thus providing a crucial strategy for biocontrol of biofilm. Furthermore, natural pyomelanin is known as a potent antioxidant, photoprotective, and free radical scavenging. Objective: This study focuses on the
... Show MoreMobile Wireless sensor networks have acquired a great interest recently due to their capability to provide good solutions and low-priced in multiple fields. Internet of Things (IoT) connects different technologies such as sensing, communication, networking, and cloud computing. It can be used in monitoring, health care and smart cities. The most suitable infrastructure for IoT application is wireless sensor networks. One of the main defiance of WSNs is the power limitation of the sensor node. Clustering model is an actual way to eliminate the inspired power during the transmission of the sensed data to a central point called a Base Station (BS). In this paper, efficient clustering protocols are offered to prolong network lifetime. A kern
... Show MoreTo observe the effect of media of the internal pressure on the equivalent stress distribution in the tube, an experimental study is done by constructing a testing rig to apply the hydraulic pressure and three dies are manufactured with different bulging configurations (square, cosine, and conical). In the other part, ANSYS APDL is generated to analyze the bulging process with hydraulic and rubber (natural and industrial) media. It was found that when the media is a rubber, the stress is decreased about 9.068% in case of cosine die and 5.4439% in case of conical die and 2.8544% in case of square die. So, it can be concluded that the internal pressure in the rubber media is much better than in hydraulic media. Also, the force needed for fo
... Show MoreThe software-defined network (SDN) is a new technology that separates the control plane from data plane for the network devices. One of the most significant issues in the video surveillance system is the link failure. When the path failure occurs, the monitoring center cannot receive the video from the cameras. In this paper, two methods are proposed to solve this problem. The first method uses the Dijkstra algorithm to re-find the path at the source node switch. The second method uses the Dijkstra algorithm to re-find the path at the ingress node switch (or failed link).
... Show MoreEarly detection of brain tumors is critical for enhancing treatment options and extending patient survival. Magnetic resonance imaging (MRI) scanning gives more detailed information, such as greater contrast and clarity than any other scanning method. Manually dividing brain tumors from many MRI images collected in clinical practice for cancer diagnosis is a tough and time-consuming task. Tumors and MRI scans of the brain can be discovered using algorithms and machine learning technologies, making the process easier for doctors because MRI images can appear healthy when the person may have a tumor or be malignant. Recently, deep learning techniques based on deep convolutional neural networks have been used to analyze med
... Show MoreA new and hybrid deep learning-based approach for diagnosing faults in electric vehicle (EV) drive motors is proposed in this article. This article presents a new and hybrid deep learning-based method of diagnosing faults in the drive motors of electric vehicles (EV). In contrast to standard CNNLSTM approaches that depend on SoftMax classification, the introduced framework combines a Random Forest (RF) classifier to enhance the generalization, interpretability, and robustness of fault prediction. Furthermore meant for use on edge computing equipment with IoT integration, the design allows for real-time monitoring in resource-limited settings. The introduced algorithm utilizes a Random Forest (RF) classifier for accurate fault classification
... Show MoreAbstract Background: The novel coronavirus 2 (SARS?CoV?2) pandemic is a pulmonary disease, which leads to cardiac, hematologic, and renal complications. Anticoagulants are used for COVID-19 infected patients because the infection increases the risk of thrombosis. The world health organization (WHO), recommend prophylaxis dose of anticoagulants: (Enoxaparin or unfractionated Heparin for hospitalized patients with COVID-19 disease. This has created an urgent need to identify effective medications for COVID-19 prevention and treatment. The value of COVID-19 treatments is affected by cost-effectiveness analysis (CEA) to inform relative value and how to best maximize social welfare through evidence-based pricing decisions. O
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The great expansion of teaching skills requires finding ways and methods to help teachers acquire experiences of all kinds. The researcher found in the subject of the teaching skills for teachers in public and private schools a fertile field for conducting a study that enables the measurement of these skills. Thus, the study aims to identify the skills of teaching lessons for teachers, the difference in teaching lesson skills for teachers according to the years of service, the differences in teaching lesson skills for teachers according to the specialized teachers and non-specialized teachers, the differences in teaching lesson skills for teachers according to the public and private school. The
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