The design of fault tolerant software for loosely coupled distributed systems

Requirements for systems to continue to operate satisfactorily in the presence of faults has led to the development of techniques for the construction of fault tolerant software. This thesis addresses the problem of error detection and recovery in distributed systems which consist of a set of communicating sequential processes. A method is presented for the `a priori' design of conversations for this class of distributed system. Petri nets are used to represent the state and to solve state reachability problems for concurrent systems. The dynamic behaviour of the system can be characterised by a state-change table derived from the state reachability tree. Systematic conversation generation is possible by defining a closed boundary on any branch of the state-change table. By relating the state-change table to process attributes it ensures all necessary processes are included in the conversation. The method also ensures properly nested conversations. An implementation of the conversation scheme using the concurrent language occam is proposed. The structure of the conversation is defined using the special features of occam. The proposed implementation gives a structure which is independent of the application and is independent of the number of processes involved. Finally, the integrity of inter-process communications is investigated. The basic communication primitives used in message passing systems are seen to have deficiencies when applied to systems with safety implications. Using a Petri net model a boundary for a time-out mechanism is proposed which will increase the integrity of a system which involves inter-process communications.

Rapid machine tool verification

This paper describes work carried out to develop methods of verifying that machine tools are capable of machining parts to within specification, immediately before carrying out critical material removal operations, and with negligible impact on process times. A review of machine tool calibration and verification technologies identified that current techniques were not suitable due to requirements for significant time and skilled human intervention. A 'solution toolkit' is presented consisting of a selection circular tests and artefact probing which are able to rapidly verify the kinematic errors and in some cases also dynamic errors for different types of machine tool, as well as supplementary methods for tool and spindle error detection. A novel artefact probing process is introduced which simplifies data processing so that the process can be readily automated using only the native machine tool controller. Laboratory testing and industrial case studies are described which demonstrate the effectiveness of this approach.

Bit-error probability for direct detection of optical RZ signal degraded by ASE noise and timing jitter

We analyze theoretically the interplay between optical return-to-zero signal degradation due to timing jitter and additive amplified-spontaneous-emission noise. The impact of these two factors on the performance of a square-law direct detection receiver is also investigated. We derive an analytical expression for the bit-error probability and quantitatively determine the conditions when the contributions of the effects of timing jitter and additive noise to the bit error rate can be treated separately. The analysis of patterning effects is also presented. © 2007 IEEE.

Pulse compression applied to the detection of F.S.K. and P.S.K. signals

The matched filter detector is well known as the optimum detector for use in communication, as well as in radar systems for signals corrupted by Additive White Gaussian Noise (A.W.G.N.). Non-coherent F.S.K. and differentially coherent P.S.K. (D.P.S.K.) detection schemes, which employ a new approach in realizing the matched filter processor, are investigated. The new approach utilizes pulse compression techniques, well known in radar systems, to facilitate the implementation of the matched filter in the form of the Pulse Compressor Matched Filter (P.C.M.F.). Both detection schemes feature a mixer- P.C.M.F. Compound as their predetector processor. The Compound is utilized to convert F.S.K. modulation into pulse position modulation, and P.S.K. modulation into pulse polarity modulation. The mechanisms of both detection schemes are studied through examining the properties of the Autocorrelation function (A.C.F.) at the output of the P.C.M.F.. The effects produced by time delay, and carrier interference on the output A.C.F. are determined. Work related to the F.S.K. detection scheme is mostly confined to verifying its validity, whereas the D.P.S.K. detection scheme has not been reported before. Consequently, an experimental system was constructed, which utilized combined hardware and software, and operated under the supervision of a microprocessor system. The experimental system was used to develop error-rate models for both detection schemes under investigation. Performances of both F. S. K. and D.P. S. K. detection schemes were established in the presence of A. W. G. N. , practical imperfections, time delay, and carrier interference. The results highlight the candidacy of both detection schemes for use in the field of digital data communication and, in particular, the D.P.S.K. detection scheme, which performed very close to optimum in a background of A.W.G.N.

Detection of signals corrupted by the combination of Gaussian and Non-Gaussian noise

The detection of signals in the presence of noise is one of the most basic and important problems encountered by communication engineers. Although the literature abounds with analyses of communications in Gaussian noise, relatively little work has appeared dealing with communications in non-Gaussian noise. In this thesis several digital communication systems disturbed by non-Gaussian noise are analysed. The thesis is divided into two main parts. In the first part, a filtered-Poisson impulse noise model is utilized to calulate error probability characteristics of a linear receiver operating in additive impulsive noise. Firstly the effect that non-Gaussian interference has on the performance of a receiver that has been optimized for Gaussian noise is determined. The factors affecting the choice of modulation scheme so as to minimize the deterimental effects of non-Gaussian noise are then discussed. In the second part, a new theoretical model of impulsive noise that fits well with the observed statistics of noise in radio channels below 100 MHz has been developed. This empirical noise model is applied to the detection of known signals in the presence of noise to determine the optimal receiver structure. The performance of such a detector has been assessed and is found to depend on the signal shape, the time-bandwidth product, as well as the signal-to-noise ratio. The optimal signal to minimize the probability of error of; the detector is determined. Attention is then turned to the problem of threshold detection. Detector structure, large sample performance and robustness against errors in the detector parameters are examined. Finally, estimators of such parameters as. the occurrence of an impulse and the parameters in an empirical noise model are developed for the case of an adaptive system with slowly varying conditions.

Improved detection in CDMA for biased sources

We consider the detection of biased information sources in the ubiquitous code-division multiple-access (CDMA) scheme. We propose a simple modification to both the popular single-user matched-filter detector and a recently introduced near-optimal message-passing-based multiuser detector. This modification allows for detecting modulated biased sources directly with no need for source coding. Analytical results and simulations with excellent agreement are provided, demonstrating substantial improvement in bit error rate in comparison with the unmodified detectors and the alternative of source compression. The robustness of error-performance improvement is shown under practical model settings, including bias estimation mismatch and finite-length spreading codes. © 2007 IOP Publishing Ltd.

Visual acuity measures do not reliably detect childhood refractive error - an epidemiological study

Purpose To investigate the utility of uncorrected visual acuity measures in screening for refractive error in white school children aged 6-7-years and 12-13-years. Methods The Northern Ireland Childhood Errors of Refraction (NICER) study used a stratified random cluster design to recruit children from schools in Northern Ireland. Detailed eye examinations included assessment of logMAR visual acuity and cycloplegic autorefraction. Spherical equivalent refractive data from the right eye were used to classify significant refractive error as myopia of at least 1DS, hyperopia as greater than +3.50DS and astigmatism as greater than 1.50DC, whether it occurred in isolation or in association with myopia or hyperopia. Results Results are presented from 661 white 12-13-year-old and 392 white 6-7-year-old school-children. Using a cut-off of uncorrected visual acuity poorer than 0.20 logMAR to detect significant refractive error gave a sensitivity of 50% and specificity of 92% in 6-7-year-olds and 73% and 93% respectively in 12-13-year-olds. In 12-13-year-old children a cut-off of poorer than 0.20 logMAR had a sensitivity of 92% and a specificity of 91% in detecting myopia and a sensitivity of 41% and a specificity of 84% in detecting hyperopia. Conclusions Vision screening using logMAR acuity can reliably detect myopia, but not hyperopia or astigmatism in school-age children. Providers of vision screening programs should be cognisant that where detection of uncorrected hyperopic and/or astigmatic refractive error is an aspiration, current UK protocols will not effectively deliver.

Bayesian error bars for regression

Regression problems are concerned with predicting the values of one or more continuous quantities, given the values of a number of input variables. For virtually every application of regression, however, it is also important to have an indication of the uncertainty in the predictions. Such uncertainties are expressed in terms of the error bars, which specify the standard deviation of the distribution of predictions about the mean. Accurate estimate of error bars is of practical importance especially when safety and reliability is an issue. The Bayesian view of regression leads naturally to two contributions to the error bars. The first arises from the intrinsic noise on the target data, while the second comes from the uncertainty in the values of the model parameters which manifests itself in the finite width of the posterior distribution over the space of these parameters. The Hessian matrix which involves the second derivatives of the error function with respect to the weights is needed for implementing the Bayesian formalism in general and estimating the error bars in particular. A study of different methods for evaluating this matrix is given with special emphasis on the outer product approximation method. The contribution of the uncertainty in model parameters to the error bars is a finite data size effect, which becomes negligible as the number of data points in the training set increases. A study of this contribution is given in relation to the distribution of data in input space. It is shown that the addition of data points to the training set can only reduce the local magnitude of the error bars or leave it unchanged. Using the asymptotic limit of an infinite data set, it is shown that the error bars have an approximate relation to the density of data in input space.

Composite materials impact damage detection using neural networks

This thesis considers two basic aspects of impact damage in composite materials, namely damage severity discrimination and impact damage location by using Acoustic Emissions (AE) and Artificial Neural Networks (ANNs). The experimental work embodies a study of such factors as the application of AE as Non-destructive Damage Testing (NDT), and the evaluation of ANNs modelling. ANNs, however, played an important role in modelling implementation. In the first aspect of the study, different impact energies were used to produce different level of damage in two composite materials (T300/914 and T800/5245). The impacts were detected by their acoustic emissions (AE). The AE waveform signals were analysed and modelled using a Back Propagation (BP) neural network model. The Mean Square Error (MSE) from the output was then used as a damage indicator in the damage severity discrimination study. To evaluate the ANN model, a comparison was made of the correlation coefficients of different parameters, such as MSE, AE energy, AE counts, etc. MSE produced an outstanding result based on the best performance of correlation. In the second aspect, a new artificial neural network model was developed to provide impact damage location on a quasi-isotropic composite panel. It was successfully trained to locate impact sites by correlating the relationship between arriving time differences of AE signals at transducers located on the panel and the impact site coordinates. The performance of the ANN model, which was evaluated by calculating the distance deviation between model output and real location coordinates, supports the application of ANN as an impact damage location identifier. In the study, the accuracy of location prediction decreased when approaching the central area of the panel. Further investigation indicated that this is due to the small arrival time differences, which defect the performance of ANN prediction. This research suggested increasing the number of processing neurons in the ANNs as a practical solution.

Hearing protectors: a dilemma involving acoustics and personal safety

This thesis is concerned with the optimising of hearing protector selection. A computer model was used to estimate the reduction in noise exposure and risk of occupational deafness provided by the wearing of hearing protectors in industrial noise spectra. The model was used to show that low attenuation hearing protectors con provide greater protection than high attenuation protectors if the high attenuation protectors ore not worn for the total duration of noise exposure; or not used by a small proportion of the population. The model was also used to show that high attenuation protectors will not necessarily provide significantly greater reduction in risk than low attenuation protectors if the population has been exposed to the noise for many years prior to the provision of hearing protectors. The effects of earplugs and earmuffs on the localisation of sounds were studied to determine whether high attenuation earmuffs are likely to have greater potential than the lower attenuation earplugs for affecting personal safety. Laboratory studies and experiments at a foundry with normal-hearing office employees and noise-exposed foundrymen who had some experience of wearing hearing protectors showed that although earplugs reduced the ability of the wearer to determine the direction of warning sounds, earmuffs produced more total angular error and more confusions between left and right. !t is concluded from the research findings that the key to the selection of hearing protectors is to be found in the provision of hearing protectors that can be worn for a very high percentage of the exposure time by a high percentage of the exposed population with the minimum effect on the personal safety of the wearers - the attenuation provided by the protection should be adequate but not a maximum value.

Medication error in mental health:implications for primary care

Medication errors are associated with significant morbidity and people with mental health problems may be particularly susceptible to medication errors due to various factors. Primary care has a key role in improving medication safety in this vulnerable population. The complexity of services, involving primary and secondary care and social services, and potential training issues may increase error rates, with physical medicines representing a particular risk. Service users may be cognitively impaired and fail to identify an error placing additional responsibilities on clinicians. The potential role of carers in error prevention and medication safety requires further elaboration. A potential lack of trust between service users and clinicians may impair honest communication about medication issues leading to errors. There is a need for detailed research within this field.

Near-ML detection for MDL-impaired few-mode fiber transmission

Few-mode fiber transmission systems are typically impaired by mode-dependent loss (MDL). In an MDL-impaired link, maximum-likelihood (ML) detection yields a significant advantage in system performance compared to linear equalizers, such as zero-forcing and minimum-mean square error equalizers. However, the computational effort of the ML detection increases exponentially with the number of modes and the cardinality of the constellation. We present two methods that allow for near-ML performance without being afflicted with the enormous computational complexity of ML detection: improved reduced-search ML detection and sphere decoding. Both algorithms are tested regarding their performance and computational complexity in simulations of three and six spatial modes with QPSK and 16QAM constellations.

Adaptive congestion control of DSRC vehicle networks for collaborative road safety applications

Congestion control is critical for the provisioning of quality of services (QoS) over dedicated short range communications (DSRC) vehicle networks for road safety applications. In this paper we propose a congestion control method for DSRC vehicle networks at road intersection, with the aims of providing high availability and low latency channels for high priority emergency safety applications while maximizing channel utilization for low priority routine safety applications. In this method a offline simulation based approach is used to find out the best possible configurations of message rate and MAC layer backoff exponent (BE) for a given number of vehicles equipped with DSRC radios. The identified best configurations are then used online by an roadside access point (AP) for system operation. Simulation results demonstrated that this adaptive method significantly outperforms the fixed control method under varying number of vehicles. The impact of estimation error on the number of vehicles in the network on system level performance is also investigated.

Time resolved bit error rate analysis of a fast switching tunable laser for use in optically switched networks

We investigate the use of different direct detection modulation formats in a wavelength switched optical network. We find the minimum time it takes a tunable sampled grating distributed Bragg reflector laser to recover after switching from one wavelength channel to another for different modulation formats. The recovery time is investigated utilizing a field programmable gate array which operates as a time resolved bit error rate detector. The detector offers 93 ps resolution operating at 10.7 Gb/s and allows for all the data received to contribute to the measurement, allowing low bit error rates to be measured at high speed. The recovery times for 10.7 Gb/s non-return-to-zero on–off keyed modulation, 10.7 Gb/s differentially phase shift keyed signal and 21.4 Gb/s differentially quadrature phase shift keyed formats can be as low as 4 ns, 7 ns and 40 ns, respectively. The time resolved phase noise associated with laser settling is simultaneously measured for 21.4 Gb/s differentially quadrature phase shift keyed data and it shows that the phase noise coupled with frequency error is the primary limitation on transmitting immediately after a laser switching event.

Experimental and theoretical investigations of intensity-modulation and direct-detection optical fast-OFDM over MMF-links

We demonstrate the first experimental implementation of a 3.9-Gb/s differential binary phase-shift keying (DBPSK)-based double sideband (DSB) optical fast orthogonal frequency-division-multiplexing (FOFDM) system with a reduced subcarrier spacing equal to half the symbol rate over 300m of multimode fiber (MMF) using intensity-modulation and direct-detection (IM/DD). The required received optical power at a bit-error rate (BER) of 10(-3) was measured to be similar to -14.2 dBm with a receiver sensitivity penalty of only similar to 0.2 dB when compared to the back-to-back case. Experimental results agree very well with the theoretical predictions.