Abstract-Node isolation is one of the fundamental metrics in the design consideration and evaluation of wireless ad hoc network. This paper is aimed to introduce a statistical framework for the computing of the isolation probability of a randomly chosen node in a wireless network. The statistical framework is proposed in the context of lognormal shadowing on Nakagami fading for multiple inputs multiple output schemes. In this work, the focus is on path loss component, network topology, node density and performance of a node. The performance of connectivity between nodes in a dense network are analysed by deriving analytical models. Analysis of experimental results indicate that they are useful in estimating connectivity issues and implementing more secure wireless ad hoc networks.

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Diabetic foot ulcer (DFU) is one of the major concern of diabetes and it is rapidly increasing, in worst case scenario this may lead to amputation. The DFU can be avoided by the early detection and proper diagnosis. Many of the studies carried out highlights that, thermography is the most useful technique to measure the changes in the temperature of plantar surface and alerts to indicate the risk associated with DFU. The distribution of temperature does not have a fixed pattern across the patients, hence it makes the difficulty in measuring the appropriate changes. This gap will provide a scope to improve the analysis technique so as to measure the plantar surface temperature effectively and identify any abnormal changes. In this paper, the segmentation algorithm namely adaptive C means (ACM) for the image segmentation is discussed. ACM is based on the spatial information and this method includes the two stage implementation. In the first stage, nonlocal spatial information is added and in the second stage, spatial shape information is used in order to refine the constraint of local spatial. Outcome of the proposed method shows that ACM is very much effective and it outperforms the other existing methods.

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