Recent technological advances in wireless communications and wireless sensor networks have enabled the design of low-cost, intelligent, tiny, and lightweight medical sensor nodes that can be strategically placed on human body, create a wireless body area network (WBAN) to monitor various physiological vital signs for a long period of time and providing real-time feedback to the user and medical staff. WBANs promise to revolutionize health monitoring. In this paper, medical sensors were used to collect physiological data from patients and transmit it to Intelligent Personal digital Assistant (IPDA) using ZigBee/IEEE802.15.4 standard and to medical server using 3G communications. We introduced priority scheduling and data compression into the system to increase transmission rate of physiological critical signals which improve the bandwidth utilization. It also extends the life time of hand-held personal server by reducing power consumption during transmission.

One of the major constraints of wireless sensor networks is limited energy available to sensor nodes because of the small size of the batteries they use as source of power. Clustering is one of the routing techniques that have been using to minimize sensor nodes' energy consumption during operation. In this paper, A Novel Clustering Algorithm for Energy Efficiency in Wireless Sensor Networks (ANCAEE) has been proposed. The algorithm achieves good performance in terms of minimizing energy consumption during data transmission and energy consumptions are distributed uniformly among all nodes. ANCAEE uses a new method of clusters formation and election of cluster heads. The algorithm ensures that a node transmits its data to the cluster head with a single hop transmission and cluster heads forward their data to the base station with multi-hop transmissions. Simulation results show that our approach consumes less energy and effectively extends network utilization.

No abstract

Computational complexity is a characteristic of almost all Lesk-based algorithms for word sense disambiguation (WSD). In this paper, we address this issue by developing a simple and optimized variant of the algorithm using topic composition in documents based on the theory underlying topic models. The knowledge resource adopted is the English WordNet enriched with linguistic knowledge from Wikipedia and Semcor corpus. Besides the algorithm’s eficiency, we also evaluate its efectiveness using two datasets; a general domain dataset and domain-specific dataset. The algorithm achieves a superior performance on the general domain dataset and superior performance for knowledge-based techniques on the domain-specific dataset.

The sensitivity of health-care information and its accessibility via the Internet and mobile technology systems is a cause for concern in these modern times. The privacy, integrity and confidentiality of a patient's data are key factors to be considered in the transmission of medical information for use by authorised health-care personnel. Mobile communication has enabled medical consultancy, treatment, drug administration and the provision of laboratory results to take place outside the hospital. With the implementation of electronic patient records and the Internet and Intranets, medical information sharing amongst relevant health-care providers was made possible. But the vital issue in this method of information sharing is security: the patient's privacy, as well as the confidentiality and integrity of the health-care information system, should not be compromised. We examine various ways of ensuring the security and privacy of a patient's electronic medical information in order to ensure the integrity and confidentiality of the information.