High Speed FPGA-based implementations of Delayed-LMS filters

A variation of the least means squares (LMS) algorithm, called the delayed LMS (DLMS) algorithm is an ideally suited to achieve highly pipelined, adaptive digital filter implementations. The paper presents an efficient method of determining the delays in the DLMS filter and then transferring these delays using retiming in order to achieve fully pipelined circuit architectures for FPGA implementation. The method has been used to derive a series of retimed delayed LMS (RDLMS) architectures, which considerable reduce the number of delays and convergence time and give superior performance in terms of throughput rate when compared to previous work. Three circuit architectures and three hardware shared versions are presented which have been implemented using the Virtex-II FPGA technology resulting in a throughout rate of 182 Msample/s.

Rasch Analysis of the Daily Living Tasks Dependent on Vision (DLTV)

PURPOSE. To examine internal consistency, refine the response scale, and obtain a linear scoring system for the visual function instrument, the Daily Living Tasks Dependent on Vision (DLTV). METHODS. Data were available from 186 participants with a clinical diagnosis of AMD who completed the 22-item DLTV (DLTV-22) according to four-point ordinal response scale. An independent group of 386 participants with AMD were administered a reduced version of the DLTV with 11 items (DLTV-11), according to a five-point response scale. Rasch analysis was performed on both datasets and used to generate item statistics for measure order, response odds ratios per item and per person, and infit and outfit mean square statistics. The Rasch output from the DLTV-22 was examined to identify redundant items and for factorial validity and person item measure separation reliabilities. RESULTS. The average rating for the DLTV-22 changed monotonically with the magnitude of the latent person trait. The expected versus observed average measures were extremely close, with step calibrations evenly separated for the four-point ordinal scale. In the case of the DLTV-11, step calibrations were not as evenly separated, suggesting that the five-point scale should be reduced to either a four- or three-point scale. Five items in the DLTV-22 were removed, and all 17 remaining items had good infit and outfit mean squares. PCA with residuals from Rasch analysis identified two domains containing 7 and 10 items each. The domains had high person separation reliabilities (0.86 and 0.77 for domains 1 and 2, respectively) and item measure reliabilities (0.99 and 0.98 for domains 1 and 2, respectively). CONCLUSIONS. With the improved internal consistency, establishment of the accuracy and precision of the rating scale for the DLTV and the establishment of a valid domain structure we believe that it constitutes a useful instrument for assessing visual function in older adults with age-related macular degeneration.

Difference equation sensor characterization algorithms for two-thermocouple probes

The characterization of thermocouple sensors for temperature measurement in variable flow environments is a challenging problem. In this paper, novel difference equation-based algorithms are presented that allow in situ characterization of temperature measurement probes consisting of two-thermocouple sensors with differing time constants. Linear and non-linear least squares formulations of the characterization problem are introduced and compared in terms of their computational complexity, robustness to noise and statistical properties. With the aid of this analysis, least squares optimization procedures that yield unbiased estimates are identified. The main contribution of the paper is the development of a linear two-parameter generalized total least squares formulation of the sensor characterization problem. Monte-Carlo simulation results are used to support the analysis.

SuperWASP-North extrasolar planet candidates: candidates from fields 17h

We have performed photometric observations of nearly seven million stars with 8 <V <15 with the SuperWASP-North instrument from La Palma between 2004 May to September. Fields in the right ascension range 17-18h, yielding over 185000 stars with sufficient quality data, have been searched for transits using a modified box least-squares (BLS) algorithm. We find a total of 58 initial transiting candidates which have high signal-to-noise ratio in the BLS, show multiple transit-like dips and have passed visual inspection. Analysis of the blending and the inferred planetary radii for these candidates leave, a total of seven transiting planet candidates which pass all the tests plus four which pass the majority. We discuss the derived parameters for these candidates and their properties and comment on the implications for future transit searches.

Fast model based feature matching technique applied to airport lighting

The use of image processing techniques to assess the performance of airport landing lighting using images of it collected from an aircraft-mounted camera is documented. In order to assess the performance of the lighting, it is necessary to uniquely identify each luminaire within an image and then track the luminaires through the entire sequence and store the relevant information for each luminaire, that is, the total number of pixels that each luminaire covers and the total grey level of these pixels. This pixel grey level can then be used for performance assessment. The authors propose a robust model-based (MB) featurematching technique by which the performance is assessed. The development of this matching technique is the key to the automated performance assessment of airport lighting. The MB matching technique utilises projective geometry in addition to accurate template of the 3D model of a landing-lighting system. The template is projected onto the image data and an optimum match found, using nonlinear least-squares optimisation. The MB matching software is compared with standard feature extraction and tracking techniques known within the community, these being the Kanade–Lucus–Tomasi (KLT) and scaleinvariant feature transform (SIFT) techniques. The new MB matching technique compares favourably with the SIFT and KLT feature-tracking alternatives. As such, it provides a solid foundation to achieve the central aim of this research which is to automatically assess the performance of airport lighting.

Robust fuzzy Gustafson-Kessel clustering for nonlinear system identification

This paper deals with Takagi-Sugeno (TS) fuzzy model identification of nonlinear systems using fuzzy clustering. In particular, an extended fuzzy Gustafson-Kessel (EGK) clustering algorithm, using robust competitive agglomeration (RCA), is developed for automatically constructing a TS fuzzy model from system input-output data. The EGK algorithm can automatically determine the 'optimal' number of clusters from the training data set. It is shown that the EGK approach is relatively insensitive to initialization and is less susceptible to local minima, a benefit derived from its agglomerate property. This issue is often overlooked in the current literature on nonlinear identification using conventional fuzzy clustering. Furthermore, the robust statistical concepts underlying the EGK algorithm help to alleviate the difficulty of cluster identification in the construction of a TS fuzzy model from noisy training data. A new hybrid identification strategy is then formulated, which combines the EGK algorithm with a locally weighted, least-squares method for the estimation of local sub-model parameters. The efficacy of this new approach is demonstrated through function approximation examples and also by application to the identification of an automatic voltage regulation (AVR) loop for a simulated 3 kVA laboratory micro-machine system.

The rotational broadening of V395 Carinae. Implications on the compact object's mass

Context: The masses previously obtained for the X-ray binary 2S 0921-630 inferred a compact object that was either a high-mass neutron star or low-mass black-hole, but used a previously published value for the rotational broadening (v sin i) with large uncertainties. Aims: We aim to determine an accurate mass for the compact object through an improved measurement of the secondary star's projected equatorial rotational velocity. Methods: We have used UVES echelle spectroscopy to determine the v sin i of the secondary star (V395 Car) in the low-mass X-ray binary 2S 0921-630 by comparison to an artificially broadened spectral-type template star. In addition, we have also measured v sin i from a single high signal-to-noise ratio absorption line profile calculated using the method of Least-Squares Deconvolution (LSD). Results: We determine v sin i to lie between 31.3±0.5 km s-1 to 34.7±0.5 km s-1 (assuming zero and continuum limb darkening, respectively) in disagreement with previous results based on intermediate resolution spectroscopy obtained with the 3.6 m NTT. Using our revised v sin i value in combination with the secondary star's radial velocity gives a binary mass ratio of 0.281±0.034. Furthermore, assuming a binary inclination angle of 75° gives a compact object mass of 1.37±0.13 M_?. Conclusions: We find that using relatively low-resolution spectroscopy can result in systemic uncertainties in the measured v sin i values obtained using standard methods. We suggest the use of LSD as a secondary, reliable check of the results as LSD allows one to directly discern the shape of the absorption line profile. In the light of the new v sin i measurement, we have revised down the compact object's mass, such that it is now compatible with a canonical neutron star mass.

Multivariate Statistical Analysis Applied to an IL6 Signal Transduction Model in Hepatocytes

This paper introduces the application of linear multivariate statistical techniques, including partial least squares (PLS), canonical correlation analysis (CCA) and reduced rank regression (RRR), into the area of Systems Biology. This new approach aims to extract the important proteins embedded in complex signal transduction pathway models.The analysis is performed on a model of intracellular signalling along the janus-associated kinases/signal transducers and transcription factors (JAK/STAT) and mitogen activated protein kinases (MAPK) signal transduction pathways in interleukin-6 (IL6) stimulated hepatocytes, which produce signal transducer and activator of transcription factor 3 (STAT3).A region of redundancy within the MAPK pathway that does not affect the STAT3 transcription was identified using CCA. This is the core finding of this analysis and cannot be obtained by inspecting the model by eye. In addition, RRR was found to isolate terms that do not significantly contribute to changes in protein concentrations, while the application of PLS does not provide such a detailed picture by virtue of its construction.This analysis has a similar objective to conventional model reduction techniques with the advantage of maintaining the meaning of the states prior to and after the reduction process. A significant model reduction is performed, with a marginal loss in accuracy, offering a more concise model while maintaining the main influencing factors on the STAT3 transcription.The findings offer a deeper understanding of the reaction terms involved, confirm the relevance of several proteins to the production of Acute Phase Proteins and complement existing findings regarding cross-talk between the two signalling pathways.

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.

A hierarchical multiclass support vector machine incorporated with holistic triple learning units

This paper proposes a new hierarchical learning structure, namely the holistic triple learning (HTL), for extending the binary support vector machine (SVM) to multi-classification problems. For an N-class problem, a HTL constructs a decision tree up to a depth of A leaf node of the decision tree is allowed to be placed with a holistic triple learning unit whose generalisation abilities are assessed and approved. Meanwhile, the remaining nodes in the decision tree each accommodate a standard binary SVM classifier. The holistic triple classifier is a regression model trained on three classes, whose training algorithm is originated from a recently proposed implementation technique, namely the least-squares support vector machine (LS-SVM). A major novelty with the holistic triple classifier is the reduced number of support vectors in the solution. For the resultant HTL-SVM, an upper bound of the generalisation error can be obtained. The time complexity of training the HTL-SVM is analysed, and is shown to be comparable to that of training the one-versus-one (1-vs.-1) SVM, particularly on small-scale datasets. Empirical studies show that the proposed HTL-SVM achieves competitive classification accuracy with a reduced number of support vectors compared to the popular 1-vs-1 alternative.

Translating evidence into practice: A shared priority in public health?

Translational and transdisciplinary research is needed to tackle complex public health problems. This article has three aims. Firstly, to determine how academics and non-academics (practitioners, policy makers and community workers) identified with the goals of the UKCRC Centre of Excellence for Public Health in Northern Ireland and how their attitudes varied in terms of knowledge brokerage and translation. Secondly, to map and analyse the network structure of the public health sector and the placement of the Centre within this. Thirdly, to aggregate responses from members of the network by work setting to construct the trans-sectoral network and devise the Root Mean Sum of Squares to determine the quality and potential value of connections across this network.The analysis was based on data collected from 98 individuals who attended the launch of the Centre in June 2008. Analysis of participant expectations and personal goals suggests that the academic members of the network were more likely to expect the work of the Centre to produce new knowledge than non-academics, but less likely to expect the Centre to generate health interventions and influence health policy. Academics were also less strongly oriented than non-academics to knowledge transfer as a personal goal, though more confident that research findings would be diffused beyond the immediate network. A central core of five nodes is crucial to the overall configuration of the regional public health network in Northern Ireland, with the Centre being well placed to exert influence within this. Though the overall network structure is fairly robust, the connections between some component parts of the network - such as academics and the third sector - are unidirectional.Identifying these differences and core network structure is key to translational and transdisciplinary research. Though exemplified in a regional study, these techniques are generalisable and applicable to many networks of interest: public health, interdisciplinary research or organisational involvement and stakeholder linkage.

Distribution of the common lizard (Zootoca vivipara) and landscape favourability for the species in Northern Ireland

The common lizard (Zootoca vivipara) is Ireland’s only native reptile, forming a key part of the island’s biodiversity. However, there is a general paucity of distributional and abundance data for the species. In this study, we collated incidental records for common lizard sightings to define the distribution of the species in Northern Ireland. Maximum entropy modelling was employed to describe species-habitat associations. The resulting predicted landscape favourability was used to evaluate the current status of the species based on the distribution of its maximum potential range in relation to the degree of fragmentation of remaining suitable habitat. In common with previous studies in the Republic of Ireland, sightings were highly clustered indicating under-recording, observer bias, and fragmentation of suitable habitat. A total of 98 records were collated from 1905 to 2009. The species was recorded in 63 (ca. 34%) of 186 × 10 km Northern Irish grid squares. Lizard occurrence was strongly and positively associated with landscapes dominated by heathland, bog and coastal habitats. The single best approximating model correctly classified the presence of lizards in 84.2% of cases. Upland heath, lowland raised bog and sand dune systems are all subject to Habitat Action Plans in Northern Ireland and are threatened by conversion to agriculture, afforestation, invasive species encroachment and infrastructural development. Consequently, remaining common lizard populations are likely to be small, isolated and highly fragmented. Establishment of an ecological network to preserve connectivity of remaining heath and bog will not only benefit remaining common lizard populations but biodiversity in general.

Developing a methodology for the National Frog Survey of Ireland: a pilot study in Co. Mayo.

A National Frog Survey of Ireland is planned for spring 2011. We conducted a pilot survey of 25 water bodies in ten 0.25 km2 survey squares in Co. Mayo during spring 2010. Drainage ditches were the most commonly available site for breeding and, generally, two 100 m stretches of ditch were surveyed in each square. The restricted period for peak spawning activity renders any methodology utilizing only one site visit inherently risky. Consequently, each site was visited three times from late March to early April. Occurrence of spawn declined significantly from 72 % to 44 % between the first and third visit whilst the overall occurrence of spawn at all sites was 76 %. As the breeding season advanced, spawn either hatched or was predated and, therefore, disappeared. In those water bodies where spawning was late, however, greater densities of spawn were deposited than in those sites where breeding was early. Consequently, spawn density and estimated frog density did not differ significantly between site visits. Future surveys should nevertheless include multiple site visits to avoid biased estimation of species occurrence and distribution. Ecological succession was identified as the main threat present at 44 % of sites.

Robust Estimation of HDR in fMRI using H∞ Filters

Estimation and detection of the hemodynamic response (HDR) are of great importance in functional MRI (fMRI) data analysis. In this paper, we propose the use of three H 8 adaptive filters (finite memory, exponentially weighted, and time-varying) for accurate estimation and detection of the HDR. The H 8 approach is used because it safeguards against the worst case disturbances and makes no assumptions on the (statistical) nature of the signals [B. Hassibi and T. Kailath, in Proc. ICASSP, 1995, vol. 2, pp. 949-952; T. Ratnarajah and S. Puthusserypady, in Proc. 8th IEEE Workshop DSP, 1998, pp. 1483-1487]. Performances of the proposed techniques are compared to the conventional t-test method as well as the well-known LMSs and recursive least squares algorithms. Extensive numerical simulations show that the proposed methods result in better HDR estimations and activation detections.

RCS CONTROL USING CASCADED CIRCULARLY POLARIZED FREQUENCY SELECTIVE SURFACES AND AN AMC STRUCTURE AS A SWITCHABLE TWIST POLARIZER

This article presents a cascaded arrangement comprising a double-layer frequency selective surface circularly polarizing (CPFSS) and a second screen that can be switched between artificial magnetic conduction (AMC) or perfect electric conducting. (PEC) states. The CPFSS consists of two stacked aluminium sheets patterned with periodic split ring structures While the AMC is a PCB sheet patterned with metallic squares interconnected by links By either open or short circuiting these links it is shown that the cascade of screens can be made to twist, or not to twist, an incident 45 degrees linearly polirized signal through 90 degrees upon reflection from the assembly The system was designed and optimized using CST software and predictions were validated experimentally and measured monostatic reflection loss results (C) 2010 Wiley Periodicals, Inc Microwave Opt Technol Lett 52 577-580, 2010. Published online in Wiley InterScience (www.interscience.wiley.com) DOI 10.1002/mop.24979