Wireless Body Area Sensor Networks (WBASNs) have garnered significant attention due to the implementation of self-automaton and modern technologies. Within the healthcare WBASN, certain sensed data hold greater significance than others in light of their critical aspect. Such vital data must be given within a specified time frame. Data loss and delay could not be tolerated in such types of systems. Intelligent algorithms are distinguished by their superior ability to interact with various data systems. Machine learning methods can analyze the gathered data and uncover previously unknown patterns and information. These approaches can also diagnose and notify critical conditions in patients under monitoring. This study implements two supervised machine learning classification techniques, Learning Vector Quantization (LVQ) and Support Vector Machine (SVM) classifiers, to achieve better search performance and high classification accuracy in a heterogeneous WBASN. These classification techniques are responsible for categorizing each incoming packet into normal, critical, or very critical, depending on the patient's condition, so that any problem affecting him can be addressed promptly. Comparative analyses reveal that LVQ outperforms SVM in terms of accuracy at 91.45% and 80%, respectively.
Permeability determination in Carbonate reservoir is a complex problem, due to their capability to be tight and heterogeneous, also core samples are usually only available for few wells therefore predicting permeability with low cost and reliable accuracy is an important issue, for this reason permeability predictive models become very desirable.
This paper will try to develop the permeability predictive model for one of Iraqi carbonate reservoir from core and well log data using the principle of Hydraulic Flow Units (HFUs). HFU is a function of Flow Zone Indicator (FZI) which is a good parameter to determine (HFUs).
Histogram analysis, probability analysis and Log-Log plot of Reservoir Qua
... Show MoreThe pilgrimage takes place in several countries around the world. The pilgrimage includes the simultaneous movement of a huge crowd of pilgrims which leads to many challenges for the pilgrimage authorities to track, monitor, and manage the crowd to minimize the chance of overcrowding’s accidents. Therefore, there is a need for an efficient monitoring and tracking system for pilgrims. This paper proposes powerful pilgrims tracking and monitoring system based on three Internet of Things (IoT) technologies; namely: Radio Frequency Identification (RFID), ZigBee, and Internet Protocol version 6 (IPv6). In addition, it requires low-cost, low-power-consumption implementation. The proposed
Skull image separation is one of the initial procedures used to detect brain abnormalities. In an MRI image of the brain, this process involves distinguishing the tissue that makes up the brain from the tissue that does not make up the brain. Even for experienced radiologists, separating the brain from the skull is a difficult task, and the accuracy of the results can vary quite a little from one individual to the next. Therefore, skull stripping in brain magnetic resonance volume has become increasingly popular due to the requirement for a dependable, accurate, and thorough method for processing brain datasets. Furthermore, skull stripping must be performed accurately for neuroimaging diagnostic systems since neither non-brain tissues nor
... Show MoreSecure information transmission over the internet is becoming an important requirement in data communication. These days, authenticity, secrecy, and confidentiality are the most important concerns in securing data communication. For that reason, information hiding methods are used, such as Cryptography, Steganography and Watermarking methods, to secure data transmission, where cryptography method is used to encrypt the information in an unreadable form. At the same time, steganography covers the information within images, audio or video. Finally, watermarking is used to protect information from intruders. This paper proposed a new cryptography method by using thre
... Show MoreIn cyber security, the most crucial subject in information security is user authentication. Robust text-based password methods may offer a certain level of protection. Strong passwords are hard to remember, though, so people who use them frequently write them on paper or store them in file for computer .Numerous of computer systems, networks, and Internet-based environments have experimented with using graphical authentication techniques for user authentication in recent years. The two main characteristics of all graphical passwords are their security and usability. Regretfully, none of these methods could adequately address both of these factors concurrently. The ISO usability standards and associated characteristics for graphical
... Show MoreFor businesses that provide delivery services, the efficiency of the delivery process in terms of punctuality is very important. In addition to increasing customer trust, efficient route management, and selection are required to reduce vehicle fuel costs and expedite delivery. Some small and medium businesses still use conventional methods to manage delivery routes. Decisions to manage delivery schedules and routes do not use any specific methods to expedite the delivery settlement process. This process is inefficient, takes a long time, increases costs and is prone to errors. Therefore, the Dijkstra algorithm has been used to improve the delivery management process. A delivery management system was developed to help managers and drivers
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