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 ene

Social risks posed a great challenge to the development path in Iraq, which resulted in widening the development gaps, whether these gaps were between rural and embargoed areas, or between Iraqi governorates, and the gender gap. Besides, the nature of the reciprocal relationship between the social risks and the development process requires the adoption of development trends that are sensitive to the risks that take upon themselves the prompt and correct response to these risks, away from randomness and confusion that Iraq suffered from for decades. However, currently, the situation has differed a great deal. This is because the size and types of such gaps have widened and become more complicated than before; a matter which has led to hav

Linear motor offers several features in many applications that require linear motion. Nevertheless, the presence of cogging force can deteriorate the thrust of a permanent magnet linear motor. Using several methodologies, a design of synchronous single sided linear iron-core motor was proposed. According to exact formulas with surface-mounted magnets and concentrated winding specification, which are relying on geometrical parameters. Two-dimensional performance analysis of the designed model and its multi-objective optimization were accomplished as a method to reduce the motor cogging force using MAXWELL ANSYS. The optimum model design results showed that the maximum force ripple was approximatrly reduced by 81.24%compared to the origina

Introduction: Diabetic foot infections are one of the most severe complications of diabetes. This study was aimed to determine the common bacterial isolates of diabetic foot infections and the in vitro antibiotic susceptibility then treatment.
Methods: A swab was taken from the foot ulcer, and the aerobic bacteria were isolated and identified by cultural, microscopic and biochemical test, then by api-20E system. After that their antibiotic susceptibility pattern was determined. Then local and systemic treatment was used to treat the diabetic foot patients.
Results: Bacterial isolates belonging to twelve species were obtained from diabetic foot patients. Gram (-) bacteria were the predominant pathogens in the diabetic foot infection

Background: Bacteriocin is a peptidic toxin has many advantages to bacteria in their ecological niche and has strong antibacterial activity. Objective: The aim of this study was to evaluation of bacteriocin using Streptococcus sanguinis isolated from human dental caries.

Subjects and Methods: Thirty five streptococcus isolates were diagnosed and tested for their production of bacteriocin, and then the optimal conditions for production of bacteriocin were determined.  After that, the purification of bacteriocin was made partially by ammonium sulfate at 95% saturation levels, followed by and gel filtration chromatography

Various theories have been proposed since in last century to predict the first sighting of a new crescent moon. None of them uses the concept of machine and deep learning to process, interpret and simulate patterns hidden in databases. Many of these theories use interpolation and extrapolation techniques to identify sighting regions through such data. In this study, a pattern recognizer artificial neural network was trained to distinguish between visibility regions. Essential parameters of crescent moon sighting were collected from moon sight datasets and used to build an intelligent system of pattern recognition to predict the crescent sight conditions. The proposed ANN learned the datasets with an accuracy of more than 72% in comp