Internet of Things (IoT) technology could be an effective solution to accomplish real-time retrieval of historical electronic health records (EHRs) to present better service of healthcare. In a pilgrimage environment such as the Hajj, IoT can be applied by identifying the non-local patients as electronic tags, and the tag data can be read by wireless sensors. The data that is collected using Radio-Frequency Identification (RFID) can be acquired from a Wireless Sensor Network (WSN) in order to accomplish many decisions, such as sending an ambulance to a patient’s location, sending an emergency alert to his immediate family circle, and retrieving his EHR from a database. The main contribution of this research is to propose a conceptual IoT framework relevant to support the non-local patients through retrieval of EHR between countries via internet network. The conceptual framework based on four layers (connectivity, access, abstraction and service) is proposed to show how the IoT can be a solution for the case study. The validation results show that the proposed framework is useful to serve the health cases of Malaysian pilgrims.
Active worms have posed a major security threat to the Internet, and many research efforts have focused on them. This paper is interested in internet worm that spreads via TCP, which accounts for the majority of internet traffic. It presents an approach that use a hybrid solution between two detection algorithms: behavior base detection and signature base detection to have the features of each of them. The aim of this study is to have a good solution of detecting worm and stealthy worm with the feature of the speed. This proposal was designed in distributed collaborative scheme based on the small-world network model to effectively improve the system performance.
The occurrence of two species of the genus Myxobolus Bütschli, 1882 (Myxozoa: Myxosporea) for the first time in Iraq from freshwater fishes.
The monogenean Gyrodactylus bychowskianus Bogolepova, 1950 is recorded in the present study for the first time in Iraq from the gills of the cyprinid fish Arabibarbus grypus (Heckel, 1843); which was collected from the Tigris River at Al-Taji Beach north of Baghdad Province during the period from July until November 2018.
In this paper, we will illustrate a gamma regression model assuming that the dependent variable (Y) is a gamma distribution and that it's mean ( ) is related through a linear predictor with link function which is identity link function g(μ) = μ. It also contains the shape parameter which is not constant and depends on the linear predictor and with link function which is the log link and we will estimate the parameters of gamma regression by using two estimation methods which are The Maximum Likelihood and the Bayesian and a comparison between these methods by using the standard comparison of average squares of error (MSE), where the two methods were applied to real da
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