Electronic remote identification (ER-ID) is a new radio frequency (RF) technology that is initiated by the Federal Aviation Authorities (FAA). For security reasons, traffic control, and so on, ER-ID has been applied for drones by the FAA to enable them to transmit their unique identification and location so that unauthorized drones can be identified. The current limitation of the existing ER-ID algorithms is that the application is limited to the Wi-Fi and Bluetooth wireless controllers, which results in a maximum range of 10–20 m for Bluetooth and 50–100 m for Wi-Fi. In this study, a mathematical computing technique based on finite state automaton (FSA) is introduced to expand the range of the ER-ID RF system and reduce the energy required by the drone to use the technology. A finite number of states have been designed to include a larger range of wireless network techniques, enabling the drones to be recognized while they are further away and in remote areas. This is achieved by including other means of RF channels, such as 4G/5G, Automatic Dependent Surveillance-Broadcast (ADS-B), long range Internet of things (IoT), and satellite communications, in the suggested ER-ID algorithm of this study. The introduced algorithm is tested via a case study. The results showed the ability to detect drones using all types of available radio frequency communication systems (RF-CS) while also minimizing the consumed energy. Hence, the authorities can control the licensed drones by using available RF-CS devices, such as Bluetooth and Wi-Fi, which are already widely used for mobile phones, as an example.
When industrial and constructional renaissance started in the world, the great interest was going on towards the equipment’s, which was the first mean for production. After industry was settled the interest was going on towards the men ship which manpower on which the production depends. It was approved that it represents the basic part in all of the processes and the protection of those individuals against dangers of these equipment’s, industry and its accidents was the basic things which was studied in many researches until it crystallized in general principles for all industries and other take care in each industry.
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... Show MoreBackground: Osteoid osteoma(OO) is a relatively common benign skeletal neoplasm of unknown etiology that is composed of osteoid and woven bone, usually seen in adolescent and young males Although, the clinical, radiological and scintigraphic features of OO have been well described, these features may be misleading or altered in the cases of lesser trochanter of the femur which is relatively uncommon location for OO with a few number of cases reported up to date.Case Presentation: We report a case of a 20-year-old man who presented with painful limpThe pain had begun six months earlier and was made worse by walking and by exercise., with normal initial X-rays .The diagnosis was made after six months when typical Computed tomography, magne
... Show MoreThe oyster ??????? (planned) (Pallas) of lesions that have entered Iraq recently became spyware severe damage in more than a station from power plants in Iraq, including the power plant in Mussayab Vamahar accumulates in pipes cooling and disrupts their work Vtafrtf heat systems cooling and thereby determiningefficiency and lead to added cost many cleaning or replacement of damaged parts
This article investigates Iraq wars presentation in literature and media. The first section investigates the case of the returnees from the war and their experience, their trauma and final presentation of that experience. The article also investigates how trauma and fear is depicted to create an optimized image and state of fear that could in turn show Iraqi society as a traumatized society. Critics such as Suzie Grogan believes that the concept of trauma could expand to influence societies rather than one individual after exposure to trauma of being involved in wars and different major conflicts. This is reflected in Iraq as a country that was subjected to six comprehensive conflicts in its recent history, i.e. less than half a century; th
... Show MoreIn this paper two ranking functions are employed to treat the fuzzy multiple objective (FMO) programming model, then using two kinds of membership function, the first one is trapezoidal fuzzy (TF) ordinary membership function, the second one is trapezoidal fuzzy weighted membership function. When the objective function is fuzzy, then should transform and shrinkage the fuzzy model to traditional model, finally solving these models to know which one is better
The image caption is the process of adding an explicit, coherent description to the contents of the image. This is done by using the latest deep learning techniques, which include computer vision and natural language processing, to understand the contents of the image and give it an appropriate caption. Multiple datasets suitable for many applications have been proposed. The biggest challenge for researchers with natural language processing is that the datasets are incompatible with all languages. The researchers worked on translating the most famous English data sets with Google Translate to understand the content of the images in their mother tongue. In this paper, the proposed review aims to enhance the understanding o
... Show MoreThe state did not witness the emergence of independent bodies because of the nature of the ruling regimes that were characterized by political tyranny represented by the king at the time, as is the case with Greece and the Greeks and Persia and the Romans and others. As for the Islamic state, which emerged later, it saw the emergence of what looks like independent bodies that we see today, There was the so-called Diwan Al-Hesba and the Ombudsman's Office as an independent body from the Islamic State, which operated independently to support the oppressed and the equitable distribution of financial resources, even though it was headed by well-known governors of justice and honesty. A state in the modern era, many countries, especially in E
... Show MoreThe paper proposes a methodology for predicting packet flow at the data plane in smart SDN based on the intelligent controller of spike neural networks(SNN). This methodology is applied to predict the subsequent step of the packet flow, consequently reducing the overcrowding that might happen. The centralized controller acts as a reactive controller for managing the clustering head process in the Software Defined Network data layer in the proposed model. The simulation results show the capability of Spike Neural Network controller in SDN control layer to improve the (QoS) in the whole network in terms of minimizing the packet loss ratio and increased the buffer utilization ratio.