An energy aware scheme for layered chain in underwater wireless sensor networks using genetic algorithm

Extending the network lifetime is a very challenging problem that needs to be taken into account during routing data in wireless sensor networks in general and particularly in underwater wireless sensor networks (UWSN). For this purpose, the present paper proposes a multilayer chain based on genetic algorithm routing (MCGA) for routing data from nodes to the sink. This algorithm consists to create a limited number of local chains constructed by using genetic algorithm in order to obtain the shortest path between nodes; furthermore, a leader node (LN) is elected in each chain followed by constructing a global chain containing LNs. The selection of the LN in the closest chain to the sink is as follows: Initially, the closest node to sink is elected LN in this latter because all nodes have initially the same energy value; then the future selection of the LN is based on the residual energy of the nodes. LNs in the other chains are selected based on the proximity to the previous LNs. Data transmission is performed in two steps: intra-chain transmission and inter-chain transmission. Furthermore, MCGA is simulated for different scenarios of mobility and density of nodes in the networks. The performance evaluation of the proposed technique shows a considerable reduction in terms of energy consumption and network lifespan

Detection of Drug Interactions via Android Smartphone: Design and Implementation

Despite the morbidity and cases of widespread drug poisoning, clinical guidelines are largely written by taking into account only one treatment at a time. The cumulative impact of multiple treatments is rarely considered. Drug treatment for people with several diseases produces a complex regimen called “polypharmacy” with a potential combination of harmful and even lethal drugs that can be prevented. This polypharmacy causes in many cases the death of some people due to drug interactions. The vast majority of these deaths can be prevented by detecting interactions before taking these medications. But the problem is that such information exists in a state that is difficult to access for the general public, much less for people with little knowledge in the field. Although the pharmacist is unmistakable and most viable source to avoid such a problem, he cannot know what the patient does not mention because he is not aware of what may affect his treatment. To remedy this, we aim in this paper to develop an ergonomic Android application that will inform the patient about the potential risks of such drug interactions. The application is optimized to handle various databases and operate automation of QR code

A Novel Algorithm to Estimate Closely Spaced Source DOA

In order to improve resolution and direction of arrival (DOA) estimation of two closely spaced sources, in context of array processing, a new algorithm is presented. However, the proposed algorithm combines both spatial sampling technic to widen the resolution and a high resolution method which is the Multiple Signal Classification (MUSIC) to estimate the DOA of two closely spaced sources impinging on the far-field of Uniform Linear Array (ULA). Simulations examples are discussed to demonstrate the performance and the effectiveness of the proposed approach (referred as Spatial sampling MUSIC SS-MUSIC) compared to the classical MUSIC method when it’s used alone in this context