Multiple Luminaire Identification in Airborne Images of Airport’s Approach Lighting Using Mathematical Morphology With Variable Length Structuring Element

The increasing demand for fast air transportation around the clock
has increased the number of night flights in civil aviation over
the past few decades. In night aviation, to land an aircraft, a
pilot needs to be able to identify an airport. The approach
lighting system (ALS) at an airport is used to provide
identification and guidance to pilots from a distance. ALS
consists of more than $100$ luminaires which are installed in a
defined pattern following strict guidelines by the International
Civil Aviation Organization (ICAO). ICAO also has strict
regulations for maintaining the performance level of the
luminaires. However, once installed, to date there is no automated
technique by which to monitor the performance of the lighting. We
suggest using images of the lighting pattern captured using a camera
placed inside an aircraft. Based on the information contained
within these images, the performance of the luminaires has to be
evaluated which requires identification of over $100$ luminaires
within the pattern of ALS image. This research proposes analysis
of the pattern using morphology filters which use a variable
length structuring element (VLSE). The dimension of the VLSE changes
continuously within an image and varies for different images.
A novel
technique for automatic determination of the VLSE is proposed and
it allows successful identification of the luminaires from the
image data as verified through the use of simulated and real data.

2DRMP-G: Migrating a large-scale numerical mathematical application to a grid environment

We report on the migration of a traditional, single architecture application to a grid application using heterogeneous resources. We focus on the use of the UK e-Science Level 2 grid (UKL2G) which provides a heterogeneous collection of resources distributed within the UK. We discuss the solution architecture, the performance of our application, its future development as a grid-based application and comment on the lessons we have learned in using a grid infrastructure for large-scale numerical problems.

The prediction of intake potential and organic matter digestibility of grass silages by near infrared spectroscopy analysis of undried samples

A study was undertaken to examine a range of sample preparation and near infrared reflectance spectroscopy (NIPS) methodologies, using undried samples, for predicting organic matter digestibility (OMD g kg(-1)) and ad libitum intake (g kg(-1) W-0.75) of grass silages. A total of eight sample preparation/NIRS scanning methods were examined involving three extents of silage comminution, two liquid extracts and scanning via either external probe (1100-2200 nm) or internal cell (1100-2500 nm). The spectral data (log 1/R) for each of the eight methods were examined by three regression techniques each with a range of data transformations. The 136 silages used in the study were obtained from farms across Northern Ireland, over a two year period, and had in vivo OMD (sheep) and ad libitum intake (cattle) determined under uniform conditions. In the comparisons of the eight sample preparation/scanning methods, and the differing mathematical treatments of the spectral data, the sample population was divided into calibration (n = 91) and validation (n = 45) sets. The standard error of performance (SEP) on the validation set was used in comparisons of prediction accuracy. Across all 8 sample preparation/scanning methods, the modified partial least squares (MPLS) technique, generally minimized SEP's for both OMD and intake. The accuracy of prediction also increased with degree of comminution of the forage and with scanning by internal cell rather than external probe. The system providing the lowest SEP used the MPLS regression technique on spectra from the finely milled material scanned through the internal cell. This resulted in SEP and R-2 (variance accounted for in validation set) values of 24 (g/kg OM) and 0.88 (OMD) and 5.37 (g/kg W-0.75) and 0.77 (intake) respectively. These data indicate that with appropriate techniques NIRS scanning of undried samples of grass silage can produce predictions of intake and digestibility with accuracies similar to those achieved previously using NIRS with dried samples. (C) 1998 Elsevier Science B.V.

On the Mechanism of Lewis Acid Catalyzed Glucose Transformations in Ionic Liquids

A complementary computational and experimental study of the reactivity of Lewis acidic CrCl2, CuCl2 and FeCl2 catalysts towards glucose activation in dialkylimidazolium chloride ionic liquids is performed. The selective dehydration of glucose to 5-hydroxymethylfurfural (HMF) proceeds through the intermediate formation of fructose. Although chromium(II) and copper(II) chlorides are able to dehydrate fructose with high HMF selectivity, reasonable HMF yields from glucose are only obtained with CrCl2 as the catalyst. Glucose conversion by CuCl2 is not selective, while FeCl2 catalyst does not activate sugar molecules. These differences in reactivity are rationalized on the basis of in situ X-ray absorption spectroscopy measurements and the results of density functional theory calculations. The reactivity in glucose dehydration and HMF selectivity are determined by the behavior of the ionic liquid-mediated Lewis acid catalysts towards the initial activation of the sugar molecules. The formation of a coordination complex between the Lewis acidic Cr2+ center and glucose directs glucose transformation into fructose. For Cu2+ the direct coordination of sugar to the copper(II) chloride complex is unfavorable. Glucose deprotonation by a mobile Cl- ligand in the CuCl42- complex initiates the nonselective conversion. In the course of the reaction the Cu2+ ions are reduced to Cu+. Both paths are prohibited for the FeCl2 catalyst.

A longitudinal analysis of estimation, counting skills, and mathematical ability across the first school year

In response to claims that the quality (and in particular linearity) of children's mental representation of number acts as a constraint on number development, we carried out a longitudinal assessment of the relationships between number line estimation, counting, and mathematical abilities. Ninety-nine 5-year-olds were tested on 4 occasions at 3 monthly intervals. Correlations between the 3 types of ability were evident, but while the quality of children's estimations changed over time and performance on the mathematical tasks improved over the same period, changes in one were not associated with changes in the other. In contrast to the earlier claims that the linearity of number representation is potentially a unique contributor to children's mathematical development, the data suggest that this variable is not significantly privileged in its impact over and above simple procedural number skills. We propose that both early arithmetic success and estimating skill are bound closely to developments in counting ability.

Mathematical Modelling of a Reciprocating Piston Expander

Modern internal combustion (IC) engines reject around two thirds of the energy provided by the fuel as low-grade waste heat. Capturing a portion of this waste heat energy and transforming it into a more useful form of energy could result in a significant reduction in fuel consumption. By using the low-grade heat, an organic Rankine cycle (ORC) can produce mechanical work from a pressurised organic fluid with the use of an expander.
Ideal gas assumptions are shown to produce significant errors in expander performance predictions when using an organic fluid. This paper details the mathematical modelling technique used to accurately model the thermodynamic processes for both ideal and non-ideal fluids within the reciprocating expander. A comparison between the two methods illustrates the extent of the errors when modelling a reciprocating piston expander. Use of the ideal gas assumptions are shown to produce an error of 55% in the prediction of power produced by the expander when operating on refrigerant R134a.