Robust fault detection using consistency techniques for uncertainty handling

Often practical performance of analytical redundancy for fault detection and diagnosis is decreased by uncertainties prevailing not only in the system model, but also in the measurements. In this paper, the problem of fault detection is stated as a constraint satisfaction problem over continuous domains with a big number of variables and constraints. This problem can be solved using modal interval analysis and consistency techniques. Consistency techniques are then shown to be particularly efficient to check the consistency of the analytical redundancy relations (ARRs), dealing with uncertain measurements and parameters. Through the work presented in this paper, it can be observed that consistency techniques can be used to increase the performance of a robust fault detection tool, which is based on interval arithmetic. The proposed method is illustrated using a nonlinear dynamic model of a hydraulic system

Multi-scale label interaction to improve object detection and segmentation

The project aims at advancing the state of the art in the use of context information for classification of image and video data. The use of context in the classification of images has been showed of great importance to improve the performance of actual object recognition systems. In our project we proposed the concept of Multi-scale Feature Labels as a general and compact method to exploit the local and global context. The feature extraction from the discriminative probability or classification confidence label field is of great novelty. Moreover the use of a multi-scale representation of the feature labels lead to a compact and efficient description of the context. The goal of the project has been also to provide a general-purpose method and prove its suitability in different image/video analysis problem. The two-year project generated 5 journal publications (plus 2 under submission), 10 conference publications (plus 2 under submission) and one patent (plus 1 pending). Of these publications, a relevant number make use of the main result of this project to improve the results in detection and/or segmentation of objects.

Reliable detection of directional couplings using rank statistics

To detect directional couplings from time series various measures based on distances in reconstructed state spaces were introduced. These measures can, however, be biased by asymmetries in the dynamics' structure, noise color, or noise level, which are ubiquitous in experimental signals. Using theoretical reasoning and results from model systems we identify the various sources of bias and show that most of them can be eliminated by an appropriate normalization. We furthermore diminish the remaining biases by introducing a measure based on ranks of distances. This rank-based measure outperforms existing distance-based measures concerning both sensitivity and specificity for directional couplings. Therefore, our findings are relevant for a reliable detection of directional couplings from experimental signals.

Predictability of music descriptor time series and its application to cover song detection

Intuitively, music has both predictable and unpredictable components. In this work we assess this qualitative statement in a quantitative way using common time series models fitted to state-of-the-art music descriptors. These descriptors cover different musical facets and are extracted from a large collection of real audio recordings comprising a variety of musical genres. Our findings show that music descriptor time series exhibit a certain predictability not only for short time intervals, but also for mid-term and relatively long intervals. This fact is observed independently of the descriptor, musical facet and time series model we consider. Moreover, we show that our findings are not only of theoretical relevance but can also have practical impact. To this end we demonstrate that music predictability at relatively long time intervals can be exploited in a real-world application, namely the automatic identification of cover songs (i.e. different renditions or versions of the same musical piece). Importantly, this prediction strategy yields a parameter-free approach for cover song identification that is substantially faster, allows for reduced computational storage and still maintains highly competitive accuracies when compared to state-of-the-art systems.

Development of In-Situ Detection Methods for Materials-Related Distress (MRD) in Concrete Pavements, July 2003

The purpose of this research was to summarize existing nondestructive test methods that have the potential to be used to detect materials-related distress (MRD) in concrete pavements. The various nondestructive test methods were then subjected to selection criteria that helped to reduce the size of the list so that specific techniques could be investigated in more detail. The main test methods that were determined to be applicable to this study included two stress-wave propagation techniques (impact-echo and spectral analysis of surface waves techniques), infrared thermography, ground penetrating radar (GPR), and visual inspection. The GPR technique was selected for a preliminary round of “proof of concept” trials. GPR surveys were carried out over a variety of portland cement concrete pavements for this study using two different systems. One of the systems was a state-of-the-art GPR system that allowed data to be collected at highway speeds. The other system was a less sophisticated system that was commercially available. Surveys conducted with both sets of equipment have produced test results capable of identifying subsurface distress in two of the three sites that exhibited internal cracking due to MRD. Both systems failed to detect distress in a single pavement that exhibited extensive cracking. Both systems correctly indicated that the control pavement exhibited negligible evidence of distress. The initial positive results presented here indicate that a more thorough study (incorporating refinements to the system, data collection, and analysis) is needed. Improvements in the results will be dependent upon defining the optimum number and arrangement of GPR antennas to detect the most common problems in Iowa pavements. In addition, refining highfrequency antenna response characteristics will be a crucial step toward providing an optimum GPR system for detecting materialsrelated distress.

A systolic array for linear MIMO detection based on an all-swap lattice reduction algorithm

A systolic array to implement lattice-reduction-aided lineardetection is proposed for a MIMO receiver. The lattice reductionalgorithm and the ensuing linear detections are operated in the same array, which can be hardware-efficient. All-swap lattice reduction algorithm (ASLR) is considered for the systolic design.ASLR is a variant of the LLL algorithm, which processes all lattice basis vectors within one iteration. Lattice-reduction-aided linear detection based on ASLR and LLL algorithms have very similarbit-error-rate performance, while ASLR is more time efficient inthe systolic array, especially for systems with a large number ofantennas.

Nd-, O-, and H-isotopic evidence for complex, closed-system fluid evolution of the peralkaline Ilimaussaq intrusion, South Greenland

Relatively homogeneous oxygen isotope compositions of amphibole, clinopyroxene, and olivine separates (+5.2 to +5.7parts per thousand relative to VSMOW) and neodymium isotope compositions (epsilon(Nd(T)) = -0.9 to -1.8 for primary magmatic minerals and epsilon(Nd(T)) = -0.1 and -0.5 for mineral separates from late-stage pegmatites and hydrothermal veins) from the alkaline to agpaitic llimaussaq intrusion, South Greenland, indicate a closed system evolution of this igneous complex and support a mantle derivation of the magma. In contrast to the homogeneous oxygen and neodymium isotopic data, deltaD values for hand-picked amphibole separates vary between -92 and -232parts per thousand and are among the most deuterium-depleted values known from igneous amphiboles. The calculated fluid phase coexisting with these amphiboles has a homogeneous oxygen isotopic composition within the normal range of magmatic waters, but extremely heterogeneous and low D/H ratios, implying a decoupling of the oxygen- and hydrogen isotope systems. Of the several possibilities that can account for such unusually low deltaD values in amphiboles (e.g., late-stage hydrothermal exchange with meteoric water, extensive magmatic degassing, contamination with organic matter, and/or effects of Fe-content and pressure on amphibole-water fractionation) the most likely explanation for the range in deltaD values is that the amphiboles have been influenced by secondary interaction and reequilibration with D-depleted fluids obtained through late-magmatic oxidation of internally generated CH(4) and/or H(2). This interpretation is consistent with the known occurrence of abundant magmatic CH(4) in the Ilimaussaq rocks and with previous studies on the isotopic compositions of the rocks and fluids. Copyright (C) 2004 Elsevier Ltd.

Molecular basis of odor detection in insects.

Olfactory systems are evolutionarily ancient, underlying the common requirement for all animals to sense and respond to diverse volatile chemical signals in their environment. Odor detection is mediated by odorant receptors (ORs) that, in most olfactory systems, comprise large families of divergent G protein-coupled receptors. Here, I discuss our and others' recent investigations of ORs in the fruit fly, Drosophila melanogaster, which have revealed insights into the distinct evolutionary origin and molecular function of insect ORs. I also describe a bioinformatics strategy that we developed to identify molecules that function with these insect-specific receptors in odor detection.

Evolving olfactory systems on the fly.

The detection of odour stimuli in the environment is universally important for primal behaviours such as feeding, mating, kin interactions and escape responses. Given the ubiquity of many airborne chemical signals and the similar organisation of animal olfactory circuits, a fundamental question in our understanding of the sense of smell is how species-specific behavioural responses to odorants can evolve. Recent comparative genomic, developmental and physiological studies are shedding light on this problem by providing insights into the genetic mechanisms that underlie anatomical and functional evolution of the olfactory system. Here we synthesise these data, with a particular focus on insect olfaction, to address how new olfactory receptors and circuits might arise and diverge, offering glimpses into how odour-evoked behaviours could adapt to an ever-changing chemosensory world.

Integrating detection probabilities in species distribution models of amphibians breeding in Mediterranean temporary ponds

Aim  The imperfect detection of species may lead to erroneous conclusions about species-environment relationships. Accuracy in species detection usually requires temporal replication at sampling sites, a time-consuming and costly monitoring scheme. Here, we applied a lower-cost alternative based on a double-sampling approach to incorporate the reliability of species detection into regression-based species distribution modelling.Location  Doñana National Park (south-western Spain).Methods  Using species-specific monthly detection probabilities, we estimated the detection reliability as the probability of having detected the species given the species-specific survey time. Such reliability estimates were used to account explicitly for data uncertainty by weighting each absence. We illustrated how this novel framework can be used to evaluate four competing hypotheses as to what constitutes primary environmental control of amphibian distribution: breeding habitat, aestivating habitat, spatial distribution of surrounding habitats and/or major ecosystems zonation. The study was conducted on six pond-breeding amphibian species during a 4-year period.Results  Non-detections should not be considered equivalent to real absences, as their reliability varied considerably. The occurrence of Hyla meridionalis and Triturus pygmaeus was related to a particular major ecosystem of the study area, where suitable habitat for these species seemed to be widely available. Characteristics of the breeding habitat (area and hydroperiod) were of high importance for the occurrence of Pelobates cultripes and Pleurodeles waltl. Terrestrial characteristics were the most important predictors of the occurrence of Discoglossus galganoi and Lissotriton boscai, along with spatial distribution of breeding habitats for the last species.Main conclusions  We did not find a single best supported hypothesis valid for all species, which stresses the importance of multiscale and multifactor approaches. More importantly, this study shows that estimating the reliability of non-detection records, an exercise that had been previously seen as a naïve goal in species distribution modelling, is feasible and could be promoted in future studies, at least in comparable systems.

Small scale underwater change detection

In this paper, we present a method to deal with the constraints of the underwater medium for finding changes between sequences of underwater images. One of the main problems of underwater medium for automatically detecting changes is the low altitude of the camera when taking pictures. This emphasise the parallax effect between the images as they are not taken exactly at the same position. In order to solve this problem, we are geometrically registering the images together taking into account the relief of the scene

Nonlinear relaxation time and the detection of weak signals

Laser systems can be used to detect very weak optical signals. The physical mechanism is the dynamical process of the relaxation of a laser from an unstable state to a steady stable state. We present an analysis of this process based on the study of the nonlinear relaxation time. Our analytical results are compared with numerical integration of the stochastic differential equations that model this process.

Optimization of laser interferometers for the detection of gravitational waves from coalescing binaries

Coalescing compact binary systems are important sources of gravitational waves. Here we investigate the detectability of this gravitational radiation by the recently proposed laser interferometers. The spectral density of noise for various practicable configurations of the detector is also reviewed. This includes laser interferometers with delay lines and Fabry-Prot cavities in the arms, both in standard and dual recycling arrangements. The sensitivity of the detector in all those configurations is presented graphically and the signal-to-noise ratio is calculated numerically. For all configurations we find values of the detector's parameters which maximize the detectability of coalescing binaries, the discussion comprising Newtonian- as well as post-Newtonian-order effects. Contour plots of the signal-to-noise ratio are also presented in certain parameter domains which illustrate the interferometer's response to coalescing binary signals.

Effect of the output of the system in signal detection

We analyze the consequences that the choice of the output of the system has in the efficiency of signal detection. It is shown that the output signal and the signal-to-noise ratio (SNR), used to characterize the phenomenon of stochastic resonance, strongly depend on the form of the output. In particular, the SNR may be enhanced for an adequate output.

Development and Demonstration of a Freezing Drizzle Algorithm for Roadway Environmental Sensing Systems, Final Report, October 2012

The primary goal of this project is to demonstrate the accuracy and utility of a freezing drizzle algorithm that can be implemented on roadway environmental sensing systems (ESSs). The types of problems related to the occurrence of freezing precipitation range from simple traffic delays to major accidents that involve fatalities. Freezing drizzle can also lead to economic impacts in communities with lost work hours, vehicular damage, and downed power lines. There are means for transportation agencies to perform preventive and reactive treatments to roadways, but freezing drizzle can be difficult to forecast accurately or even detect as weather radar and surface observation networks poorly observe these conditions. The detection of freezing precipitation is problematic and requires special instrumentation and analysis. The Federal Aviation Administration (FAA) development of aircraft anti-icing and deicing technologies has led to the development of a freezing drizzle algorithm that utilizes air temperature data and a specialized sensor capable of detecting ice accretion. However, at present, roadway ESSs are not capable of reporting freezing drizzle. This study investigates the use of the methods developed for the FAA and the National Weather Service (NWS) within a roadway environment to detect the occurrence of freezing drizzle using a combination of icing detection equipment and available ESS sensors. The work performed in this study incorporated the algorithm developed initially and further modified for work with the FAA for aircraft icing. The freezing drizzle algorithm developed for the FAA was applied using data from standard roadway ESSs. The work performed in this study lays the foundation for addressing the central question of interest to winter maintenance professionals as to whether it is possible to use roadside freezing precipitation detection (e.g., icing detection) sensors to determine the occurrence of pavement icing during freezing precipitation events and the rates at which this occurs.