Accurate and efficient face recognition from video

As a problem of high practical appeal but outstanding challenges, computer-based face recognition remains a topic of extensive research attention. In this paper we are specifically interested in the task of identifying a person from multiple training and query images. Thus, a novel method is proposed which advances the state-of-the-art in set based face recognition. Our method is based on a previously described invariant in the form of generic shape-illumination effects. The contributions include: (i) an analysis of computational demands of the original method and a demonstration of its practical limitations, (ii) a novel representation of personal appearance in the form of linked mixture models in image and pose-signature spaces, and (iii) an efficient (in terms of storage needs and matching time) manifold re-illumination algorithm based on the aforementioned representation. An evaluation and comparison of the proposed method with the original generic shape-illumination algorithm shows that comparably high recognition rates are achieved on a large data set (1.5% error on 700 face sets containing 100 individuals and extreme illumination variation) with a dramatic improvement in matching speed (over 700 times for sets containing 1600 faces) and storage requirements (independent of the number of training images).

What explains dissent on the High Court of Australia? An empirical assessment using a cointegration and error correction approach

This article examines the factors influencing the annual dissent rate on the High Court of Australia from its first full year of operation in 1904 up to 2001 within a cointegration and error correction framework. We hypothesize that institutional factors, socioeconomic complexity, and leadership style explain variations in the dissent rate on the High Court of Australia over time. The institutional factors that we consider are the Court's caseload, whether it had discretion to select the cases it hears, and whether it was a final court of appeal. To measure socioeconomic complexity we use the divorce rate, urbanization rate, and real GDP per capita. Our main finding is that in the long run and short run, caseload and real income are the main factors influencing dissent. We find that a 1 percent increase in caseload and real income reduce the dissent rate on the High Court of Australia by 0.3 percent and 0.6 percent, respectively, holding other factors constant.

Medical error and decision making : learning from the past and present in intensive care

Background : Human error occurs in every occupation. Medical errors may result in a near miss or an actual injury to a patient that has nothing to do with the underlying medical condition. Intensive care has one of the highest incidences of medical error and patient injury in any specialty medical area; thought to be related to the rapidly changing patient status and complex diagnoses and treatments.

Purpose : The aims of this paper are to: (1) outline the definition, classifications and aetiology of medical error; (2) summarise key findings from the literature with a specific focus on errors arising from intensive care areas; and (3) conclude with an outline of approaches for analysing clinical information to determine adverse events and inform practice change in intensive care.

Data source : Database searches of articles and textbooks using keywords: medical error, patient safety, decision making and intensive care. Sociology and psychology literature cited therein.

Findings : Critically ill patients require numerous medications, multiple infusions and procedures. Although medical errors are often detected by clinicians at the bedside, organisational processes and systems may contribute to the problem. A systems approach is thought to provide greater insight into the contributory factors and potential solutions to avoid preventable adverse events.

Conclusion : It is recommended that a variety of clinical information and research techniques are used as a priority to prevent hospital acquired injuries and address patient safety concerns in intensive care.

Accurately measuring recombination between closely related HIV-1 genomes

Retroviral recombination is thought to play an important role in the generation of immune escape and multiple drug resistance by shuffling pre-existing mutations in the viral population. Current estimates of HIV-1 recombination rates are derived from measurements within reporter gene sequences or genetically divergent HIV sequences. These measurements do not mimic the recombination occurring in vivo, between closely related genomes. Additionally, the methods used to measure recombination make a variety of assumptions about the underlying process, and often fail to account adequately for issues such as co-infection of cells or the possibility of multiple template switches between recombination sites. We have developed a HIV-1 marker system by making a small number of codon modifications in gag which allow recombination to be measured over various lengths between closely related viral genomes. We have developed statistical tools to measure recombination rates that can compensate for the possibility of multiple template switches. Our results show that when multiple template switches are ignored the error is substantial, particularly when recombination rates are high, or the genomic distance is large. We demonstrate that this system is applicable to other studies to accurately measure the recombination rate and show that recombination does not occur randomly within the HIV genome.

Measurement error causes scale-dependent threshold erosion of biological signals in animal movement data

Recent advances in telemetry technology have created a wealth of tracking data available for many animal species moving over spatial scales from tens of meters to tens of thousands of kilometers. Increasingly, such data sets are being used for quantitative movement analyses aimed at extracting fundamental biological signals such as optimal searching behavior and scale-dependent foraging decisions. We show here that the location error inherent in various tracking technologies reduces the ability to detect patterns of behavior within movements. Our analyses endeavored to set out a series of initial ground rules for ecologists to help ensure that sampling noise is not misinterpreted as a real biological signal. We simulated animal movement tracks using specialized random walks known as Lévy flights at three spatial scales of investigation: 100-km, 10-km, and 1-km maximum daily step lengths. The locations generated in the simulations were then blurred using known error distributions associated with commonly applied tracking methods: the Global Positioning System (GPS), Argos polar-orbiting satellites, and light-level geolocation. Deviations from the idealized Lévy flight pattern were assessed for each track after incrementing levels of location error were applied at each spatial scale, with additional assessments of the effect of error on scale-dependent movement patterns measured using fractal mean dimension and first-passage time (FPT) analyses. The accuracy of parameter estimation (Lévy μ, fractal mean D, and variance in FPT) declined precipitously at threshold errors relative to each spatial scale. At 100-km maximum daily step lengths, error standard deviations of ≥10 km seriously eroded the biological patterns evident in the simulated tracks, with analogous thresholds at the 10-km and 1-km scales (error SD ≥ 1.3 km and 0.07 km, respectively). Temporal subsampling of the simulated tracks maintained some elements of the biological signals depending on error level and spatial scale. Failure to account for large errors relative to the scale of movement can produce substantial biases in the interpretation of movement patterns. This study provides researchers with a framework for understanding the limitations of their data and identifies how temporal subsampling can help to reduce the influence of spatial error on their conclusions.

Prevalence of visual impairment and uncorrected refractive error - report from a Canadian urban population-based study

The prevalence of visual impairment due to uncorrected refractive error has not been previously studied in Canada. A population-based study was conducted in Brantford, Ontario. The target population included all people 40 years of age and older. Study participants were selected using a randomized sampling strategy based on postal codes. Presenting distance and near visual acuities were measured with habitual spectacle correction, if any, in place. Best corrected visual acuities were determined for all participants who had a presenting distance visual acuity of less than 20/25. Population weighted prevalence of distance visual impairment (visual acuity <20/40 in the better eye) was 2.7% (n = 768, 95% confidence interval (CI) 1.8–4.0%) with 71.8% correctable by refraction. Population weighted prevalence of near visual impairment (visual acuity <20/40 with both eyes) was 2.2% (95% CI 1.4–3.6) with 69.1% correctable by refraction. Multivariable adjusted analysis showed that the odds of having distance visual impairment was independently associated with increased age (odds ratio, OR, 3.56, 95% CI 1.22–10.35; ≥65 years compared to those 39–64 years), and time since last eye examination (OR 4.93, 95% CI 1.19–20.32; ≥5 years compared to ≤2 years). The same factors appear to be associated with increased prevalence of near visual impairment but were not statistically significant. The majority of visual impairment found in Brantford was due to uncorrected refractive error. Factors that increased the prevalence of visual impairment were the same for distance and near visual acuity measurements.

Implementation of an audit with feedback knowledge translation intervention to promote medication error reporting in health care: a protocol.

BACKGROUND: Health professionals strive to deliver high-quality care in an inherently complex and error-prone environment. Underreporting of medical errors challenges attempts to understand causative factors and impedes efforts to implement preventive strategies. Audit with feedback is a knowledge translation strategy that has potential to modify health professionals' medical error reporting behaviour. However, evidence regarding which aspects of this complex, multi-dimensional intervention work best is lacking. The aims of the Safe Medication Audit Reporting Translation (SMART) study are to: 1. Implement and refine a reporting mechanism to feed audit data on medication errors back to nurses 2. Test the feedback reporting mechanism to determine its utility and effect 3. Identify characteristics of organisational context associated with error reporting in response to feedback METHODS/DESIGN: A quasi-experimental design, incorporating two pairs of matched wards at an acute care hospital, is used. Randomisation occurs at the ward level; one ward from each pair is randomised to receive the intervention. A key stakeholder reference group informs the design and delivery of the feedback intervention. Nurses on the intervention wards receive the feedback intervention (feedback of analysed audit data) on a quarterly basis for 12 months. Data for the feedback intervention come from medication documentation point-prevalence audits and weekly reports on routinely collected medication error data. Weekly reports on these data are obtained for the control wards. A controlled interrupted time series analysis is used to evaluate the effect of the feedback intervention. Self-report data are also collected from nurses on all four wards at baseline and at completion of the intervention to elicit their perceptions of the work context. Additionally, following each feedback cycle, nurses on the intervention wards are invited to complete a survey to evaluate the feedback and to establish their intentions to change their reporting behaviour. To assess sustainability of the intervention, at 6 months following completion of the intervention a point-prevalence chart audit is undertaken and a report of routinely collected medication errors for the previous 6 months is obtained. This intervention will have wider application for delivery of feedback to promote behaviour change for other areas of preventable error and adverse events.

Impact of automated dispensing cabinets on medication selection and preparation error rates in an emergency department: a prospective and direct observational before-and-after study

RATIONALE, AIMS AND OBJECTIVES: The implementation of automated dispensing cabinets (ADCs) in healthcare facilities appears to be increasing, in particular within Australian hospital emergency departments (EDs). While the investment in ADCs is on the increase, no studies have specifically investigated the impacts of ADCs on medication selection and preparation error rates in EDs. Our aim was to assess the impact of ADCs on medication selection and preparation error rates in an ED of a tertiary teaching hospital. METHODS: Pre intervention and post intervention study involving direct observations of nurses completing medication selection and preparation activities before and after the implementation of ADCs in the original and new emergency departments within a 377-bed tertiary teaching hospital in Australia. Medication selection and preparation error rates were calculated and compared between these two periods. Secondary end points included the impact on medication error type and severity. RESULTS: A total of 2087 medication selection and preparations were observed among 808 patients pre and post intervention. Implementation of ADCs in the new ED resulted in a 64.7% (1.96% versus 0.69%, respectively, P = 0.017) reduction in medication selection and preparation errors. All medication error types were reduced in the post intervention study period. There was an insignificant impact on medication error severity as all errors detected were categorised as minor. CONCLUSION: The implementation of ADCs could reduce medication selection and preparation errors and improve medication safety in an ED setting.