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Body sensor networks (BSNs) have provided the opportunity to monitor energy expenditure (EE) in daily life and with that information help reduce sedentary behavior and ultimately improve human health. Current approaches for EE estimation using BSNs require tedious annotation of activity types and multiple body sensor nodes during data collection and high accuracy activity classifiers during post processing...
The fidelity of many inertial Body Sensor Network (BSN) applications depends on accurate spatio-temporal information retrieved from body-worn devices. However, there are many challenges caused by inherent sensor errors in inertial BSNs and the uncertainty of dynamic human motion in various situations, such as integration drift and mounting error. Spatial information is especially difficult to extract...
Reputation-based trust management is an effective method to improve network security in P2P networks. In this paper, we present a trust evaluation model based on parameter-estimation algorithms to enhance the accuracy of trust evaluation in unstructured P2P networks. Trust evaluation includes direct and second-hand trust information. It estimates and updates the trust value and uncertainty of each...
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