Investigation of the Effect of Array Geometry on the Performance of Free-Space Optical Interconnects

The effect of transmitter and receiver array configurations on the stray-light and diffraction-caused crosstalk in free-space optical interconnects was investigated. The optical system simulation software (Code V) is used to simulate both the stray-light and diffraction-caused crosstalk. Experimentally measured, spectrally-resolved, near-field images of VCSEL higher order modes were used as extended sources in our simulation model. In addition, we have included the electrical and optical noise in our analysis to give more accurate overall performance of the FSOI system. Our results show that by changing the square lattice geometry to a hexagonal configuration, we obtain an overall signal-to-noise ratio improvement of 3 dB. Furthermore, system density is increased by up to 4 channels/mm2.

Monitoring Infants By Automatic Video Processing

This work has, as its objective, the development of non-invasive and low-cost systems for monitoring and automatic diagnosing specific neonatal diseases by means of the analysis of suitable video signals. We focus on monitoring infants potentially at risk of diseases characterized by the presence or absence of rhythmic movements of one or more body parts. Seizures and respiratory diseases are specifically considered, but the approach is general. Seizures are defined as sudden neurological and behavioural alterations. They are age-dependent phenomena and the most common sign of central nervous system dysfunction. Neonatal seizures have onset within the 28th day of life in newborns at term and within the 44th week of conceptional age in preterm infants. Their main causes are hypoxic-ischaemic encephalopathy, intracranial haemorrhage, and sepsis. Studies indicate an incidence rate of neonatal seizures of 0.2% live births, 1.1% for preterm neonates, and 1.3% for infants weighing less than 2500 g at birth. Neonatal seizures can be classified into four main categories: clonic, tonic, myoclonic, and subtle. Seizures in newborns have to be promptly and accurately recognized in order to establish timely treatments that could avoid an increase of the underlying brain damage. Respiratory diseases related to the occurrence of apnoea episodes may be caused by cerebrovascular events. Among the wide range of causes of apnoea, besides seizures, a relevant one is Congenital Central Hypoventilation Syndrome (CCHS) \cite{Healy}. With a reported prevalence of 1 in 200,000 live births, CCHS, formerly known as Ondine's curse, is a rare life-threatening disorder characterized by a failure of the automatic control of breathing, caused by mutations in a gene classified as PHOX2B. CCHS manifests itself, in the neonatal period, with episodes of cyanosis or apnoea, especially during quiet sleep. The reported mortality rates range from 8% to 38% of newborn with genetically confirmed CCHS. Nowadays, CCHS is considered a disorder of autonomic regulation, with related risk of sudden infant death syndrome (SIDS). Currently, the standard method of diagnosis, for both diseases, is based on polysomnography, a set of sensors such as ElectroEncephaloGram (EEG) sensors, ElectroMyoGraphy (EMG) sensors, ElectroCardioGraphy (ECG) sensors, elastic belt sensors, pulse-oximeter and nasal flow-meters. This monitoring system is very expensive, time-consuming, moderately invasive and requires particularly skilled medical personnel, not always available in a Neonatal Intensive Care Unit (NICU). Therefore, automatic, real-time and non-invasive monitoring equipments able to reliably recognize these diseases would be of significant value in the NICU. A very appealing monitoring tool to automatically detect neonatal seizures or breathing disorders may be based on acquiring, through a network of sensors, e.g., a set of video cameras, the movements of the newborn's body (e.g., limbs, chest) and properly processing the relevant signals. An automatic multi-sensor system could be used to permanently monitor every patient in the NICU or specific patients at home. Furthermore, a wire-free technique may be more user-friendly and highly desirable when used with infants, in particular with newborns. This work has focused on a reliable method to estimate the periodicity in pathological movements based on the use of the Maximum Likelihood (ML) criterion. In particular, average differential luminance signals from multiple Red, Green and Blue (RGB) cameras or depth-sensor devices are extracted and the presence or absence of a significant periodicity is analysed in order to detect possible pathological conditions. The efficacy of this monitoring system has been measured on the basis of video recordings provided by the Department of Neurosciences of the University of Parma. Concerning clonic seizures, a kinematic analysis was performed to establish a relationship between neonatal seizures and human inborn pattern of quadrupedal locomotion. Moreover, we have decided to realize simulators able to replicate the symptomatic movements characteristic of the diseases under consideration. The reasons is, essentially, the opportunity to have, at any time, a 'subject' on which to test the continuously evolving detection algorithms. Finally, we have developed a smartphone App, called 'Smartphone based contactless epilepsy detector' (SmartCED), able to detect neonatal clonic seizures and warn the user about the occurrence in real-time.

Interferometric sensor interrogation using an arrayed waveguide grating

We experimentally investigate the use of an arrayed waveguide grating (AWG) to interrogate interferometric sensors. A single broad-band light source is used to illuminate the system. Reflected spectral information is directed to an AWG with integral photodetectors providing 40 electrical outputs. We show that using the dual-wavelength technique we can measure the length of a Fabry-Perot cavity by determining the optical phase changes of the scanned interferometric pattern, which produced a maximum unambiguous range of 1440 mum with an active sensor and a maximum unambiguous range of 300 mum with the introduction of a second processing interferometer, which allows the sensor to be passive.

Automatic processing, quality assurance and serving of real-time weather data over lightweight protocols

Recent advances in technology have produced a significant increase in the availability of free sensor data over the Internet. With affordable weather monitoring stations now available to individual meteorology enthusiasts a reservoir of real time data such as temperature, rainfall and wind speed can now be obtained for most of the United States and Europe. Despite the abundance of available data, obtaining useable information about the weather in your local neighbourhood requires complex processing that poses several challenges. This paper discusses a collection of technologies and applications that harvest, refine and process this data, culminating in information that has been tailored toward the user. In this case we are particularly interested in allowing a user to make direct queries about the weather at any location, even when this is not directly instrumented, using interpolation methods. We also consider how the uncertainty that the interpolation introduces can then be communicated to the user of the system, using UncertML, a developing standard for uncertainty representation.

A projected process kriging algorithm for sensor networks with heterogeneous error characteristics

Large monitoring networks are becoming increasingly common and can generate large datasets from thousands to millions of observations in size, often with high temporal resolution. Processing large datasets using traditional geostatistical methods is prohibitively slow and in real world applications different types of sensor can be found across a monitoring network. Heterogeneities in the error characteristics of different sensors, both in terms of distribution and magnitude, presents problems for generating coherent maps. An assumption in traditional geostatistics is that observations are made directly of the underlying process being studied and that the observations are contaminated with Gaussian errors. Under this assumption, sub–optimal predictions will be obtained if the error characteristics of the sensor are effectively non–Gaussian. One method, model based geostatistics, assumes that a Gaussian process prior is imposed over the (latent) process being studied and that the sensor model forms part of the likelihood term. One problem with this type of approach is that the corresponding posterior distribution will be non–Gaussian and computationally demanding as Monte Carlo methods have to be used. An extension of a sequential, approximate Bayesian inference method enables observations with arbitrary likelihoods to be treated, in a projected process kriging framework which is less computationally intensive. The approach is illustrated using a simulated dataset with a range of sensor models and error characteristics.

Application of digital image processing techniques to the photometric testing of vehicle headlamps

The aim of this Interdisciplinary Higher Degrees project was the development of a high-speed method of photometrically testing vehicle headlamps, based on the use of image processing techniques, for Lucas Electrical Limited. Photometric testing involves measuring the illuminance produced by a lamp at certain points in its beam distribution. Headlamp performance is best represented by an iso-lux diagram, showing illuminance contours, produced from a two-dimensional array of data. Conventionally, the tens of thousands of measurements required are made using a single stationary photodetector and a two-dimensional mechanical scanning system which enables a lamp's horizontal and vertical orientation relative to the photodetector to be changed. Even using motorised scanning and computerised data-logging, the data acquisition time for a typical iso-lux test is about twenty minutes. A detailed study was made of the concept of using a video camera and a digital image processing system to scan and measure a lamp's beam without the need for the time-consuming mechanical movement. Although the concept was shown to be theoretically feasible, and a prototype system designed, it could not be implemented because of the technical limitations of commercially-available equipment. An alternative high-speed approach was developed, however, and a second prototype syqtem designed. The proposed arrangement again uses an image processing system, but in conjunction with a one-dimensional array of photodetectors and a one-dimensional mechanical scanning system in place of a video camera. This system can be implemented using commercially-available equipment and, although not entirely eliminating the need for mechanical movement, greatly reduces the amount required, resulting in a predicted data acquisiton time of about twenty seconds for a typical iso-lux test. As a consequence of the work undertaken, the company initiated an 80,000 programme to implement the system proposed by the author.

Changes in information processing in children and their implications for marketing strategy

This thesis examines children's consumer choice behaviour using an information processing perspective, with the fundamental goal of applying academic research to practical marketing and commercial problems. Proceeding a preface, which describes the academic and commercial terms of reference within which this interdisciplinary study is couched, the thesis comprises four discernible parts. Initially, the rationale inherent in adopting an information processing perspective is justified and the diverse array of topics which have bearing on children's consumer processing and behaviour are aggregated. The second part uses this perspective as a springboard to appraise the little explored role of memory, and especially memory structure, as a central cognitive component in children's consumer choice processing. The main research theme explores the ease with which 10 and 11 year olds retrieve contemporary consumer information from subjectively defined memory organisations. Adopting a sort-recall paradigm, hierarchical retrieval processing is stimulated and it is contended that when two items, known to be stored proximally in the memory organisation are not recalled adjacently, this discrepancy is indicative of retrieval processing ease. Results illustrate the marked influence of task conditions and orientation of memory structure on retrieval; these conclusions are accounted for in terms of input and integration failure. The third section develops the foregoing interpellations in the marketing context. A straightforward methodology for structuring marketing situations is postulated, a basis for segmenting children's markets using processing characteristics is adopted, and criteria for communicating brand support information to children are discussed. A taxonomy of market-induced processing conditions is developed. Finally, a case study with topical commercial significance is described. The development, launch and marketing of a new product in the confectionery market is outlined, the aetiology of its subsequent demise identified and expounded, and prescriptive guidelines are put forward to help avert future repetition of marketing misjudgements.

Force sensing for measuring human body movement

The research developed in this thesis explores the sensing and inference of human movement in a dynamic way, as opposed to conventional measurement systems, that are only concerned with discrete evaluations of stimuli in sequential time. Typically, conventional approaches are used to infer the dynamic movement of the body; such as vision and motion tracking devices, with either a human diagnosis or complex image processing algorithm to classify the movement. This research is therefore the first of its kind to attempt and provide a movement classifying algorithm through the use of minimal sensing points, with the application for this novel system, to classify human movement during a golf swing. There are two main categories of force sensing. Firstly, array-type systems consisting of many sensing elements, and are the most commonly researched and commercially available. Secondly, reduced force sensing element systems (RFSES) also known as distributive systems have only been recently exploited in the academic world. The fundamental difference between these systems is that array systems handle the data captured from each sensor as unique outputs and suffer the effects of resolution. The effect of resolution, is the error in the load position measurement between sensing elements, as the output is quantized in terms of position. This can be compared to a reduced sensor element system that maximises that data received through the coupling of data from a distribution of sensing points to describe the output in discrete time. Also this can be extended to a coupling of transients in the time domain to describe an activity or dynamic movement. It is the RFSES that is to be examined and exploited in the commercial sector due to its advantages over array-based approaches such as reduced design, computational complexity and cost.

The application of fibre Bragg grating networks as strain sensors and as phased array antenna true time delay elements

The fabrication of in-fibre Bragg gratings, and the application of arrays of such gratings as strain sensors and as true time delay elements for the control of phased array antennas is reported. Chirped period Bragg gratings were produced using the fibre deformation fabrication technique, with chirps of between 2.9nm and 17.3nm achieved. Arrays of 5mm and 2mm long uniform period Bragg gratings were fabricated using the inscription method, for use as true time delay elements,dissimilar wavefronts and their spectral characteristics recorded. The uniform period grating arrays were used to create minimum time delays of 9.09ps, 19.02ps and 31ps; making them suitable for controlling phased array antennas operating at RF frequencies of up to 3GHz, with 10° phase resolution. Four 4mm long chirped gratings were produced using the dissimilar wavefronts fabrication method, having chirps of 7nm, 12nm, 20nm and 30nm, and were used to create time delays of between 0.3ps and 59ps. Hence they are suitable for controlling phased array antennas at RF frequencies of up to 48GHz. The application of in fibre Bragg gratings as strain sensors within smart structure materials was investigated, with their sensitivity to applied strain and compression measured for both embedded and surface mounted uniform period and fibre Fabry-Perot filter gratings. A fibre Bragg grating sensor demultiplexing scheme based on a liquid crystal filled Fabry-Perot etalon tuneable transmission filter was proposed, successfully constructed and fully characterised. Three characteristics of the LCFP etalon were found to pose operational limitations to its application in a Bragg grating sensor system; most significantly, the resonance peak wavelength was highly (-2,77nm/°C) temperature dependent. Several methods for minimising this temperature sensitivity were investigated, but enjoyed only limited success. It was therefore concluded that this type (E7 filled) of LCFP etalon is unsuitable for use as a Bragg grating sensor demultiplexing element.

Automatic processing, quality assurance and serving of real-time weather data

Recent advances in technology have produced a significant increase in the availability of free sensor data over the Internet. With affordable weather monitoring stations now available to individual meteorology enthusiasts a reservoir of real time data such as temperature, rainfall and wind speed can now be obtained for most of the United States and Europe. Despite the abundance of available data, obtaining useable information about the weather in your local neighbourhood requires complex processing that poses several challenges. This paper discusses a collection of technologies and applications that harvest, refine and process this data, culminating in information that has been tailored toward the user. In this case we are particularly interested in allowing a user to make direct queries about the weather at any location, even when this is not directly instrumented, using interpolation methods. We also consider how the uncertainty that the interpolation introduces can then be communicated to the user of the system, using UncertML, a developing standard for uncertainty representation.

Aptamer-based surface plasmon sensor for thrombin detection

A series of surface plasmonic fibre devices were fabricated using multiple coatings deposited on a lapped section of a single mode fibre and post-fabrication UV laser irradiation processing with a phase mask, producing a surface relief grating structure. These devices showed high spectral sensitivity in the aqueous index regime ranging up to 4000 nm/RIU for wavelength and 800 dB/RIU for intensity. The devices were then coated with human thrombin binding aptamer. Several concentrations of thrombin in buffer solution were made, ranging from 1nM to 1µM. All the concentrations were detectable by the devices demonstrating that sub-nM concentrations may be monitored.

Polarization-independent high-resolution spectral interrogation of FBGs using a BFBG-CCD array for optical sensing applications

Optical fibre strain sensors using Fibre Bragg Gratings (FBGs) are poised to play a major role in structural health monitoring in a variety of application from aerospace to civil engineering. At the heart of technology is the optoelectronic instrumentation required to convert optical signals into measurands. Users are demanding compact, lightweight, rugged and low cost solutions. This paper describes development of a new device based on a blazed FBG and CCD array that can potentially meet the above demands. We have shown that this very low cost technique may be used to interrogate a WDM array of sensor gratings with highly accurate and highly repeatable results unaffected by the polarisation state of the radiation. In this paper, we present results showing that sensors may be interrogated with an RMS error of 1.7pm, drift below 0.12pm and dynamic range of up to 65nm.

Helicopter vibration sensor selection using data visualisation

The main objective of the project is to enhance the already effective health-monitoring system (HUMS) for helicopters by analysing structural vibrations to recognise different flight conditions directly from sensor information. The goal of this paper is to develop a new method to select those sensors and frequency bands that are best for detecting changes in flight conditions. We projected frequency information to a 2-dimensional space in order to visualise flight-condition transitions using the Generative Topographic Mapping (GTM) and a variant which supports simultaneous feature selection. We created an objective measure of the separation between different flight conditions in the visualisation space by calculating the Kullback-Leibler (KL) divergence between Gaussian mixture models (GMMs) fitted to each class: the higher the KL-divergence, the better the interclass separation. To find the optimal combination of sensors, they were considered in pairs, triples and groups of four sensors. The sensor triples provided the best result in terms of KL-divergence. We also found that the use of a variational training algorithm for the GMMs gave more reliable results.