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.

Target Detection and Tracking With Heterogeneous Sensors

We present a multimodal detection and tracking algorithm for sensors composed of a camera mounted between two microphones. Target localization is performed on color-based change detection in the video modality and on time difference of arrival (TDOA) estimation between the two microphones in the audio modality. The TDOA is computed by multiband generalized cross correlation (GCC) analysis. The estimated directions of arrival are then postprocessed using a Riccati Kalman filter. The visual and audio estimates are finally integrated, at the likelihood level, into a particle filter (PF) that uses a zero-order motion model, and a weighted probabilistic data association (WPDA) scheme. We demonstrate that the Kalman filtering (KF) improves the accuracy of the audio source localization and that the WPDA helps to enhance the tracking performance of sensor fusion in reverberant scenarios. The combination of multiband GCC, KF, and WPDA within the particle filtering framework improves the performance of the algorithm in noisy scenarios. We also show how the proposed audiovisual tracker summarizes the observed scene by generating metadata that can be transmitted to other network nodes instead of transmitting the raw images and can be used for very low bit rate communication. Moreover, the generated metadata can also be used to detect and monitor events of interest.

A statistical framework for the design of microarray experiments and effective detection of differential gene expression

Motivation: Microarray experiments generate a high data volume. However, often due to financial or experimental considerations, e.g. lack of sample, there is little or no replication of the experiments or hybridizations. These factors combined with the intrinsic variability associated with the measurement of gene expression can result in an unsatisfactory detection rate of differential gene expression (DGE). Our motivation was to provide an easy to use measure of the success rate of DGE detection that could find routine use in the design of microarray experiments or in post-experiment assessment.

Cooperative transmission protocol with full diversity and iterative detection

The authors propose a three-node full diversity cooperative protocol, which allows the retransmission of all symbols. By allowing multiple nodes to transmit simultaneously, relaying transmission only consumes limited bandwidth resource. To facilitate the performance analysis of the proposed cooperative protocol, the lower and upper bounds of the outage probability are first developed, and then the high signal-to-noise ratio behaviour is studied. Our analytical results show that the proposed strategy can achieve full diversity. To achieve the performance gain promised by the cooperative diversity, at the relays decode-and-forward strategy is adopted and an iterative soft-interference-cancellation minimum mean-squared error equaliser is developed. The simulation results compare the bit-error-rate performance of the proposed protocol with the non-cooperative scheme and the scheme presented by Azarian et al. ( 2005).

Interaction of water, hydrogen and their mixtures with SnO2 based materials: the role of surface hydroxyl groups in detection mechanisms

DRIFTS, TGA and resistance measurements have been used to study the mechanism of water and hydrogen interaction accompanied by a resistance change (sensor signal) of blank and Pd doped SnO2. It was found that a highly hydroxylated surface of blank SnO2 reacts with gases through bridging hydroxyl groups, whereas the Pd doped materials interact with hydrogen and water through bridging oxygen. In the case of blank SnO2 the sensor signal maximum towards H-2 in dry air (R-0/R-g) is observed at similar to 345 degrees C, and towards water, at similar to 180 degrees C, which results in high selectivity to hydrogen in the presence of water vapors (minor humidity effect). In contrast, on doping with Pd the response to hydrogen in dry air and to water occurred in the same temperature region (ca. 140 degrees C) leading to low selectivity with a high effect of humidity. An increase in water concentration in the gas phase changes the hydrogen interaction mechanism of Pd doped materials, while that of blank SnO2 is unchanged. The interaction of hydrogen with the catalyst doped SnO2 occurs predominantly through hydroxyl groups when the volumetric concentration of water in the gas phase is higher than that of H-2 by a factor of 1000.

Detection of aberrant behaviour in home environments from video sequence

We introduce an application for the detection of aberrant behaviour within home based environments, with a focus on repetitive actions, which may be present in instance of persons suffering from dementia. Video based analysis has been used to detect the motion of a person within a given scene in addition to tracking them over the time. Detection of repetitive actions has been based on the analysis of a person's trajectory using the principles of signal correlation. Along with the ability to detect repetitive motion the developed approach also has the ability to measure the amount of activity/inactivity within the scene during a given period of time. Our results showed that the developed approach had the ability to detect all patterns in the data set examined with an average accuracy of 96.67%. This work has therefore validated the proposed concept of video based analysis for the detection of repetitive activities.

A Pipeline Interleaved Heterogeneous SIMD Soft Processor Array Architecture for MIMO-OFDM Detection

The most promising way to maintain reliable data transfer across the rapidly fluctuating channels used by next generation multiple-input multiple-output communications schemes is to exploit run-time variable modulation and antenna configurations. This demands that the baseband signal processing architectures employed in the communications terminals must provide low cost and high performance with runtime reconfigurability. We present a softcore-processor based solution to this issue, and show for the first time, that such programmable architectures can enable real-time data operation for cutting-edge standards
such as 802.11n; furthermore, by exploiting deep processing pipelines and interleaved task execution, the cost and performance of these architectures is shown to be on a par with traditional dedicated circuit based solutions. We believe this to be the first such programmable architecture to achieve this, and the combination of implementation efficiency and programmability makes this implementation style the most promising approach for hosting such dynamic architectures.

Pterin detection using surface-enhanced Raman spectroscopy incorporating a straightforward silver colloid-based synthesis technique

Optical techniques toward the realization of sensitive and selective biosensing platforms have received considerable attention in recent times. Techniques based on interferometry, surface plasmon resonance, and waveguides have all proved popular, while spectroscopy in particular offers much potential. Raman spectroscopy is an information-rich technique in which the vibrational frequencies reveal much about the structure of a compound, but it is a weak process and offers poor sensitivity. In response to this problem, surface-enhanced Raman scattering (SERS) has received much attention, due to significant increases in sensitivity instigated by bringing the sample into contact with an enhancing substrate. Here we discuss a facile and rapid technique for the detection of pterins using SERS-active colloidal silver suspensions. Pterins are a family of biological compounds that are employed in nature in color pigmentation and as facilitators in metabolic pathways. In this work, small volumes of xanthopterin, isoxanthopterin, and 7,8-dihydrobiopterin have been examined while adsorbed to silver colloids. Limits of detection have been examined for both xanthopterin and isoxanthopterin using a 10-s exposure to a 12 mW 532 nm laser, which, while showing a trade-off between scan time and signal intensity, still provides the opportunity for the investigation of simultaneous detection of both pterins in solution. (C) 2011 Society of Photo-Optical Instrumentation Engineers (SPIE). [DOI: 10.1117/1.3600658]