PLS modelling and fault detection on the Tennessee Eastman benchmark

This paper describes the application of multivariate regression techniques to the Tennessee Eastman benchmark process for modelling and fault detection. Two methods are applied : linear partial least squares, and a nonlinear variant of this procedure using a radial basis function inner relation. The performance of the RBF networks is enhanced through the use of a recently developed training algorithm which uses quasi-Newton optimization to ensure an efficient and parsimonious network; details of this algorithm can be found in this paper. The PLS and PLS/RBF methods are then used to create on-line inferential models of delayed process measurements. As these measurements relate to the final product composition, these models suggest that on-line statistical quality control analysis should be possible for this plant. The generation of `soft sensors' for these measurements has the further effect of introducing a redundant element into the system, redundancy which can then be used to generate a fault detection and isolation scheme for these sensors. This is achieved by arranging the sensors and models in a manner comparable to the dedicated estimator scheme of Clarke et al. 1975, IEEE Trans. Pero. Elect. Sys., AES-14R, 465-473. The effectiveness of this scheme is demonstrated on a series of simulated sensor and process faults, with full detection and isolation shown to be possible for sensor malfunctions, and detection feasible in the case of process faults. Suggestions for enhancing the diagnostic capacity in the latter case are covered towards the end of the paper.

Performance Analysis of Novel Randomly Shifted Certification Authority Authentication Protocol for MANETs

The provision of security in mobile ad hoc networks is of paramount importance due to their wireless nature. However, when conducting research into security protocols for ad hoc networks it is necessary to consider these in the context of the overall system. For example, communicational delay associated with the underlying MAC layer needs to be taken into account. Nodes in mobile ad hoc networks must strictly obey the rules of the underlying MAC when transmitting security-related messages while still maintaining a certain quality of service. In this paper a novel authentication protocol, RASCAAL, is described and its performance is analysed by investigating both the communicational-related effects of the underlying IEEE 802.11 MAC and the computational-related effects of the cryptographic algorithms employed. To the best of the authors' knowledge, RASCAAL is the first authentication protocol which proposes the concept of dynamically formed short-lived random clusters with no prior knowledge of the cluster head. The performance analysis demonstrates that the communication losses outweigh the computation losses with respect to energy and delay. MAC-related communicational effects account for 99% of the total delay and total energy consumption incurred by the RASCAAL protocol. The results also show that a saving in communicational energy of up to 12.5% can be achieved by changing the status of the wireless nodes during the course of operation. Copyright (C) 2009 G. A. Safdar and M. P. O'Neill (nee McLoone).

Rift Valley Fever Epidemiology, Surveillance, and Control: What Have Models Contributed?

Background: Rift Valley fever (RVF) is an emerging vector-borne zoonotic disease that represents a threat to human health, animal health, and livestock production, particularly in Africa. The epidemiology of RVF is not well understood, so that forecasting RVF outbreaks and carrying out efficient and timely control measures remains a challenge. Various epidemiological modeling tools have been used to increase knowledge on RVF epidemiology and to inform disease management policies.