A Functional-Based Distribution Diagnostic for a Linear Model with Correlated Outcomes: Technical Report

Despite the widespread popularity of linear models for correlated outcomes (e.g. linear mixed modesl and time series models), distribution diagnostic methodology remains relatively underdeveloped in this context. In this paper we present an easy-to-implement approach that lends itself to graphical displays of model fit. Our approach involves multiplying the estimated marginal residual vector by the Cholesky decomposition of the inverse of the estimated marginal variance matrix. Linear functions or the resulting "rotated" residuals are used to construct an empirical cumulative distribution function (ECDF), whose stochastic limit is characterized. We describe a resampling technique that serves as a computationally efficient parametric bootstrap for generating representatives of the stochastic limit of the ECDF. Through functionals, such representatives are used to construct global tests for the hypothesis of normal margional errors. In addition, we demonstrate that the ECDF of the predicted random effects, as described by Lange and Ryan (1989), can be formulated as a special case of our approach. Thus, our method supports both omnibus and directed tests. Our method works well in a variety of circumstances, including models having independent units of sampling (clustered data) and models for which all observations are correlated (e.g., a single time series).

Cholesky Residuals for Assessing Normal Errors in a Linear Model with Correlated Outcomes: Technical Report

Despite the widespread popularity of linear models for correlated outcomes (e.g. linear mixed models and time series models), distribution diagnostic methodology remains relatively underdeveloped in this context. In this paper we present an easy-to-implement approach that lends itself to graphical displays of model fit. Our approach involves multiplying the estimated margional residual vector by the Cholesky decomposition of the inverse of the estimated margional variance matrix. The resulting "rotated" residuals are used to construct an empirical cumulative distribution function and pointwise standard errors. The theoretical framework, including conditions and asymptotic properties, involves technical details that are motivated by Lange and Ryan (1989), Pierce (1982), and Randles (1982). Our method appears to work well in a variety of circumstances, including models having independent units of sampling (clustered data) and models for which all observations are correlated (e.g., a single time series). Our methods can produce satisfactory results even for models that do not satisfy all of the technical conditions stated in our theory.

Implementation of a machine tool performance measurement and diagnostic system and its impact on parts verification

Five axis machine tools are increasing and becoming more popular as customers demand more complex machined parts. In high value manufacturing, the importance of machine tools in producing high accuracy products is essential. High accuracy manufacturing requires producing parts in a repeatable manner and precision in compliance to the defined design specifications. The performance of the machine tools is often affected by geometrical errors due to a variety of causes including incorrect tool offsets, errors in the centres of rotation and thermal growth. As a consequence, it can be difficult to produce highly accurate parts consistently. It is, therefore, essential to ensure that machine tools are verified in terms of their geometric and positioning accuracy. When machine tools are verified in terms of their accuracy, the resulting numerical values of positional accuracy and process capability can be used to define design for verification rules and algorithms so that machined parts can be easily produced without scrap and little or no after process measurement. In this paper the benefits of machine tool verification are listed and a case study is used to demonstrate the implementation of robust machine tool performance measurement and diagnostics using a ballbar system.

Development of diagnostic and prognostic algorithms for SF6 puffer circuit breakers from transient waveforms : a validation proposal

- This paper presents a validation proposal for development of diagnostic and prognostic algorithms for SF6 puffer circuit-breakers reproduced from actual site waveforms. The re-ignition/restriking rates are duplicated in given circuits and the cumulative energy dissipated in interrupters by the restriking currents. The targeted objective is to provide a simulated database for diagnosis of re-ignition/restrikes relating to the phase to earth voltage and the number of re-ignition/restrikes as well as estimating the remaining life of SF6 circuit-breakers. The model-based diagnosis of a tool will be useful in monitoring re-ignition/restrikes as well as predicting a nozzle’s lifetime. This will help ATP users with practical study cases and component data compilation for shunt reactor switching and capacitor switching. This method can be easily applied with different data for the different dielectric curves of circuit breakers and networks. This paper presents modelling details and some of the available cases, required project support, the validation proposal, the specific plan for implementation and the propsed main contributions.

Final report : a software diagnostic tool for evaluating distress mechanisms in bridges exposed to aggressive environments

Durability issues of reinforced concrete construction cost millions of dollars in repair or demolition. Identification of the causes of degradation and a prediction of service life based on experience, judgement and local knowledge has limitations in addressing all the associated issues. The objective of this CRC CI research project is to develop a tool that will assist in the interpretation of the symptoms of degradation of concrete structures, estimate residual capacity and recommend cost effective solutions. This report is a documentation of the research undertaken in connection with this project. The primary focus of this research is centred on the case studies provided by Queensland Department of Main Roads (QDMR) and Brisbane City Council (BCC). These organisations are endowed with the responsibility of managing a huge volume of bridge infrastructure in the state of Queensland, Australia. The main issue to be addressed in managing these structures is the deterioration of bridge stock leading to a reduction in service life. Other issues such as political backlash, public inconvenience, approach land acquisitions are crucial but are not within the scope of this project. It is to be noted that deterioration is accentuated by aggressive environments such as salt water, acidic or sodic soils. Carse, 2005, has noted that the road authorities need to invest their first dollars in understanding their local concretes and optimising the durability performance of structures and then look at potential remedial strategies.

Sequential decision fusion for controlled detection errors

Information fusion in biometrics has received considerable attention. The architecture proposed here is based on the sequential integration of multi-instance and multi-sample fusion schemes. This method is analytically shown to improve the performance and allow a controlled trade-off between false alarms and false rejects when the classifier decisions are statistically independent. Equations developed for detection error rates are experimentally evaluated by considering the proposed architecture for text dependent speaker verification using HMM based digit dependent speaker models. The tuning of parameters, n classifiers and m attempts/samples, is investigated and the resultant detection error trade-off performance is evaluated on individual digits. Results show that performance improvement can be achieved even for weaker classifiers (FRR-19.6%, FAR-16.7%). The architectures investigated apply to speaker verification from spoken digit strings such as credit card numbers in telephone or VOIP or internet based applications.

To err (on the road) is human? An on-road study of driver errors

Human error, its causes and consequences, and the ways in which it can be prevented, remain of great interest to road safety practitioners. This paper presents the findings derived from an on-road study of driver errors in which 25 participants drove a pre-determined route using MUARC's On-Road Test Vehicle (ORTeV). In-vehicle observers recorded the different errors made, and a range of other data was collected, including driver verbal protocols, forward, cockpit and driver video, and vehicle data (speed, braking, steering wheel angle, lane tracking etc). Participants also completed a post trial cognitive task analysis interview. The drivers tested made a range of different errors, with speeding violations, both intentional and unintentional, being the most common. Further more detailed analysis of a sub-set of specific error types indicates that driver errors have various causes, including failures in the wider road 'system' such as poor roadway design, infrastructure failures and unclear road rules. In closing, a range of potential error prevention strategies, including intelligent speed adaptation and road infrastructure design, are discussed.

The development of a serological-based diagnostic test for Dasheen mosaic potyvirus (DsMV)

Dasheen mosaic potyvirus (DsMV) is an important virus affecting taro. The virus has been found wherever taro is grown and infects both the edible and ornamental aroids, causing yield losses of up to 60%. The presence of DsMV, and other viruses,prevents the international movement of taro germplasm between countries. This has a significant negative impact on taro production in many countries due to the inability to access improved taro lines produced in breeding programs. To overcome this problem, sensitive and reliable virus diagnostic tests need to be developed to enable the indexing of taro germplasm. The aim of this study was to generate an antiserum against a recombinant DsMV coat protein (CP) and to develop a serological-based diagnostic test that would detect Pacific Island isolates of the virus. The CP-coding region of 16 DsMV isolates from Papua New Guinea, Samoa, Solomon Islands, French Polynesia, New Caledonia and Vietnam were amplified,cloned and sequenced. The size of the CP-coding region ranged from 939 to 1038 nucleotides and encoded putative proteins ranged from 313 to 346 amino acids, with the molecular mass ranging from 34 to 38 kDa. Analysis ofthe amino acid sequences revealed the presence of several amino acid motifs typically found in potyviruses,including DAG, WCIE/DN, RQ and AFDF. When the amino acid sequences were compared with each other and the DsMV sequences on the database, the maximum variability was21.9%. When the core region ofthe CP was analysed, the maximum variability dropped to 6% indicating most variability was present in the N terminus. Within seven PNG isolates ofDsMV, the maximum variability was 16.9% and 3.9% over the entire CP-coding region and core region, respectively. The sequence ofPNG isolate P1 was most similar to all other sequences. Phylogenetic analysis indicated that almost all isolates grouped according to their provenance. Further, the seven PNG isolates were grouped according to the region within PNG from which they were obtained. Due to the extensive variability over the entire CP-coding region, the core region ofthe CP ofPNG isolate Pl was cloned into a protein expression vector and expressed as a recombinant protein. The protein was purified by chromatography and SDS-PAGE and used as an antigen to generate antiserum in a rabbit. In western blots, the antiserum reacted with bands of approximately 45-47 kDa in extracts from purified DsMV and from known DsMV -infected plants from PNG; no bands were observed using healthy plant extracts. The antiserum was subsequently incorporated into an indirect ELISA. This procedure was found to be very sensitive and detected DsMV in sap diluted at least 1:1,000. Using both western blot and ELISA formats,the antiserum was able to detect a wide range ofDsMV isolates including those from Australia, New Zealand, Fiji, French Polynesia, New Caledonia, Papua New Guinea, Samoa, Solomon Islands and Vanuatu. These plants were verified to be infected with DsMV by RT-PCR. In specificity tests, the antiserum was also found to react with sap from plants infected with SCMV, PRSV-P, PRSV-W, but not with PVY or CMV -infected plants.

Swept frequency biompedance analysis for the determination of body water compartments

Bioelectrical impedance analysis, (BIA), is a method of body composition analysis first investigated in 1962 which has recently received much attention by a number of research groups. The reasons for this recent interest are its advantages, (viz: inexpensive, non-invasive and portable) and also the increasing interest in the diagnostic value of body composition analysis. The concept utilised by BIA to predict body water volumes is the proportional relationship for a simple cylindrical conductor, (volume oc length2/resistance), which allows the volume to be predicted from the measured resistance and length. Most of the research to date has measured the body's resistance to the passage of a 50· kHz AC current to predict total body water, (TBW). Several research groups have investigated the application of AC currents at lower frequencies, (eg 5 kHz), to predict extracellular water, (ECW). However all research to date using BIA to predict body water volumes has used the impedance measured at a discrete frequency or frequencies. This thesis investigates the variation of impedance and phase of biological systems over a range of frequencies and describes the development of a swept frequency bioimpedance meter which measures impedance and phase at 496 frequencies ranging from 4 kHz to 1 MHz. The impedance of any biological system varies with the frequency of the applied current. The graph of reactance vs resistance yields a circular arc with the resistance decreasing with increasing frequency and reactance increasing from zero to a maximum then decreasing to zero. Computer programs were written to analyse the measured impedance spectrum and determine the impedance, Zc, at the characteristic frequency, (the frequency at which the reactance is a maximum). The fitted locus of the measured data was extrapolated to determine the resistance, Ro, at zero frequency; a value that cannot be measured directly using surface electrodes. The explanation of the theoretical basis for selecting these impedance values (Zc and Ro), to predict TBW and ECW is presented. Studies were conducted on a group of normal healthy animals, (n=42), in which TBW and ECW were determined by the gold standard of isotope dilution. The prediction quotients L2/Zc and L2/Ro, (L=length), yielded standard errors of 4.2% and 3.2% respectively, and were found to be significantly better than previously reported, empirically determined prediction quotients derived from measurements at a single frequency. The prediction equations established in this group of normal healthy animals were applied to a group of animals with abnormally low fluid levels, (n=20), and also to a group with an abnormal balance of extra-cellular to intracellular fluids, (n=20). In both cases the equations using L2/Zc and L2/Ro accurately and precisely predicted TBW and ECW. This demonstrated that the technique developed using multiple frequency bioelectrical impedance analysis, (MFBIA), can accurately predict both TBW and ECW in both normal and abnormal animals, (with standard errors of the estimate of 6% and 3% for TBW and ECW respectively). Isotope dilution techniques were used to determine TBW and ECW in a group of 60 healthy human subjects, (male. and female, aged between 18 and 45). Whole body impedance measurements were recorded on each subject using the MFBIA technique and the correlations between body water volumes, (TBW and ECW), and heighe/impedance, (for all measured frequencies), were compared. The prediction quotients H2/Zc and H2/Ro, (H=height), again yielded the highest correlation with TBW and ECW respectively with corresponding standard errors of 5.2% and 10%. The values of the correlation coefficients obtained in this study were very similar to those recently reported by others. It was also observed that in healthy human subjects the impedance measured at virtually any frequency yielded correlations not significantly different from those obtained from the MFBIA quotients. This phenomenon has been reported by other research groups and emphasises the need to validate the technique by investigating its application in one or more groups with abnormalities in fluid levels. The clinical application of MFBIA was trialled and its capability of detecting lymphoedema, (an excess of extracellular fluid), was investigated. The MFBIA technique was demonstrated to be significantly more sensitive, (P<.05), in detecting lymphoedema than the current technique of circumferential measurements. MFBIA was also shown to provide valuable information describing the changes in the quantity of muscle mass of the patient during the course of the treatment. The determination of body composition, (viz TBW and ECW), by MFBIA has been shown to be a significant improvement on previous bioelectrical impedance techniques. The merit of the MFBIA technique is evidenced in its accurate, precise and valid application in animal groups with a wide variation in body fluid volumes and balances. The multiple frequency bioelectrical impedance analysis technique developed in this study provides accurate and precise estimates of body composition, (viz TBW and ECW), regardless of the individual's state of health.

Diagnostic and treatment pathways for men with prostate cancer in Queensland : investigating spatial and demographic inequalities

Background: Patterns of diagnosis and management for men diagnosed with prostate cancer in Queensland, Australia, have not yet been systematically documented and so assumptions of equity are untested. This longitudinal study investigates the association between prostate cancer diagnostic and treatment outcomes and key area-level characteristics and individual-level demographic, clinical and psychosocial factors.---------- Methods/Design: A total of 1064 men diagnosed with prostate cancer between February 2005 and July 2007 were recruited through hospital-based urology outpatient clinics and private practices in the centres of Brisbane, Townsville and Mackay (82% of those referred). Additional clinical and diagnostic information for all 6609 men diagnosed with prostate cancer in Queensland during the study period was obtained via the population-based Queensland Cancer Registry. Respondent data are collected using telephone and self-administered questionnaires at pre-treatment and at 2 months, 6 months, 12 months, 24 months, 36 months, 48 months and 60 months post-treatment. Assessments include demographics, medical history, patterns of care, disease and treatment characteristics together with outcomes associated with prostate cancer, as well as information about quality of life and psychological adjustment. Complementary detailed treatment information is abstracted from participants’ medical records held in hospitals and private treatment facilities and collated with health service utilisation data obtained from Medicare Australia. Information about the characteristics of geographical areas is being obtained from data custodians such as the Australian Bureau of Statistics. Geo-coding and spatial technology will be used to calculate road travel distances from patients’ residences to treatment centres. Analyses will be conducted using standard statistical methods along with multilevel regression models including individual and area-level components.---------- Conclusions: Information about the diagnostic and treatment patterns of men diagnosed with prostate cancer is crucial for rational planning and development of health delivery and supportive care services to ensure equitable access to health services, regardless of geographical location and individual characteristics. This study is a secondary outcome of the randomised controlled trial registered with the Australian New Zealand Clinical Trials Registry (ACTRN12607000233426)