Error exponent analysis of energy-based Bayesian decentralized spectrum sensing under fading

This paper considers decentralized spectrum sensing, i.e., detection of occupancy of the primary users' spectrum by a set of Cognitive Radio (CR) nodes, under a Bayesian set-up. The nodes use energy detection to make their individual decisions, which are combined at a Fusion Center (FC) using the K-out-of-N fusion rule. The channel from the primary transmitter to the CR nodes is assumed to undergo fading, while that from the nodes to the FC is assumed to be error-free. In this scenario, a novel concept termed as the Error Exponent with a Confidence Level (EECL) is introduced to evaluate and compare the performance of different detection schemes. Expressions for the EECL under general fading conditions are derived. As a special case, it is shown that the conventional error exponent both at individual sensors, and at the FC is zero. Further, closed-form lower bounds on the EECL are derived under Rayleigh fading and lognormal shadowing. As an example application, it answers the question of whether to use pilot-signal based narrowband sensing, where the signal undergoes Rayleigh fading, or to sense over the entire bandwidth of a wideband signal, where the signal undergoes lognormal shadowing. Theoretical results are validated using Monte Carlo simulations. (C) 2015 Elsevier B.V. All rights reserved.

An Energy-Based Method for Analyzing Instrumented Spherical Indentation Experiments

Using dimensional analysis and finite element calculation, we studied spherical indentation in elastic-plastic solids with work hardening. We report two previously unknown relationships between hardness, reduced modulus, indentation depth, indenter radius, and work of indentation. These relationships, together with the relationship between initial unloading stiffness and reduced modulus, provide an energy-based method for determining contact area, reduced modulus, and hardness of materials from instrumented spherical indentation measurements. This method also provides a means for calibrating the effective radius of imperfectly shaped spherical indenters. Finally, the method is applied to the analysis of instrumented spherical indentation experiments on copper, aluminum, tungsten, and fused silica.

Analytically-based approach to rotor-stator interaction noise in mean swirling flow

A method for modelling and predicting the noise generated by the interaction between the unsteady wake shed from the rotor and a downstream row of stators in a modern ultra-high bypass ducted turbofan engine is described. An analytically-based model is developed to account for three main features of the problem. First, the way in which a typical unsteady wake disturbance from the rotor interacts and is distorted by the mean swirling flow as it propagates downstream. The analysis allows for the inclusion of mean entropy gradients and entropy perturbations. Second, the effects of real stator-blade geometry and proper representation of the genuinely three-dimensional nature of the problem. Third, to model the propagation of the resulting noise back upstream in mean swirling flow. The analytical nature of the problem allows for the inclusion of all wake harmonics and enables the response at all blade passing frequencies to be determined. Example results are presented for an initial wake distribution corresponding to a genuine rotor configuration. Comparisons between numerical data and the asymptotic model for the wake evolution are made. Copyright © 2004 by the American Institute of Aeronautics and Astronautics, Inc. All rights reserved.

Component-based approach to the holonic control of a robot assembly cell

The aim of this paper is to describe the implementation of a new approach for the introduction of so called 'holonic manufacturing' principles into existing production control systems. Such an approach is intended to improve the reconfigurability of the control system to cope with the increasing requirements of production change. A conceptual architecture is described and implemented in a robot assembly cell to demonstrate that this approach can lead to a manufacturing control system which can adapt relatively simply to long-term change. A design methodology and migration strategy for achieving these solutions using conventional hardware is proposed to develop execution level of manufacturing control systems.

A probability-based approach to setting annual catch levels.

The requirement of setting annual catch limits to prevent overfishing has been added to the Magnuson-Stevens Fishery Conservation and Management Reauthorization Act of 2006 (MSRA). Because this requirement is new, a body of applied scientific practice for deriving annual catch limits and accompanying targets does not yet exist. This article demonstrates an approach to setting levels of catch that is intended to keep the probability of future overfishing at a preset low level. The proposed framework is based on stochastic projection with uncertainty in population dynamics. The framework extends common projection methodology by including uncertainty in the limit reference point and in management implementation, and by making explicit the risk of overfishing that managers consider acceptable. The approach is illustrated with application to gag (Mycteroperca microlepis), a grouper that inhabits the waters off the southeastern United States. Although devised to satisfy new legislation of the MSRA, the framework has potential application to any fishery where the management goal is to limit the risk of overfishing by controlling catch.