The dispersed nature and vibrant topology of wireless sensor network have some basic requirements that include reduced energy utilization and extended network's lifetime. In this paper, we have focused on hierarchical protocols. In such protocol the nodes are arranged in clusters. To synchronize action and route data, cluster head are selected one per cluster. We have introduced a new approach in wireless sensor network for selecting the cluster-head by making use of artificial neural network in order to increase network's lifetime. We have used residual energy as a factor to make cluster-head. Radial basis function network model is used for cluster-head selection problem. The simulation results provide network's performance on the basis of some factors including number of dead nodes, total energy consumption, cluster head formation, number of nodes dying and the number of packets transferred to base station and cluster head. The performance of the proposed algorithm is compared with LEACH and LEACH-C based on energy efficiency and improved network lifetime.
The scattered nature and active topology of wireless sensor networks (WSN) have some particular requirements -reduced energy consumption and extended network's lifetime. The paper provides a brief introduction about the wireless sensor network including the widely adopted architecture of wireless sensor network and wireless sensor node. The paper also focuses in critical issues of wsn that includes energy per packet, lower energy consumption, average packet delay, energy spent per round, packet size, distance, time until first node dies. The paper focuses on hierarchical routing protocols which are based on network structure scheme and explains how neural networks are helpful in providing energy efficiency to wireless sensor networks.
Migraines, a chronic disease, can be debilitating in university students, affecting their academic performance, attendance, and social interactions. The purpose of this study was to identify the impact of COVID-19 on the role functioning and perceived stress levels of students suffering from migraine-like headaches. Methods: Two identical cross-sectional surveys were sent to students in Fall 2019 and Spring 2021 at a mid-sized university in the U.S. The students were queried on the headache impact scale (HIT-6) and perceived stress scale (PSS-10). Associations between the migraine-like headaches, severity of the headaches, stress levels, and headache impacts on the individuals’ role functioning were analyzed. Results: The average age of the respondents (n = 721) was 20.81 ± 4.32 years in 2019 and (n = 520) 20.95 ± 3.19 years in 2021. A difference (p = 0.044) was found in the HIT-6 score <49 category. The other categories of the HIT-6 and the PSS-10 were not significant. Conclusions: During COVID-19, more students answered that their migraine-like headaches had lower impacts on their role functioning, thus suggesting that the students were having less severe migraines. A trend was seen for student’s stress levels, indicating a decrease from 2019 to 2021. Furthermore, our results showed that the impact of headaches and stress levels slightly declined throughout the pandemic.
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