994 resultados para Zero relative radial acceleration


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We consider a robust filtering problem for uncertain discrete-time, homogeneous, first-order, finite-state hidden Markov models (HMMs). The class of uncertain HMMs considered is described by a conditional relative entropy constraint on measures perturbed from a nominal regular conditional probability distribution given the previous posterior state distribution and the latest measurement. Under this class of perturbations, a robust infinite horizon filtering problem is first formulated as a constrained optimization problem before being transformed via variational results into an unconstrained optimization problem; the latter can be elegantly solved using a risk-sensitive information-state based filtering.

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This paper discusses practical issues related to the use of the division model for lens distortion in multi-view geometry computation. A data normalisation strategy is presented, which has been absent from previous discussions on the topic. The convergence properties of the Rectangular Quadric Eigenvalue Problem solution for computing division model distortion are examined. It is shown that the existing method can require more than 1000 iterations when dealing with severe distortion. A method is presented for accelerating convergence to less than 10 iterations for any amount of distortion. The new method is shown to produce equivalent or better results than the existing method with up to two orders of magnitude reduction in iterations. Through detailed simulation it is found that the number of data points used to compute geometry and lens distortion has a strong influence on convergence speed and solution accuracy. It is recommended that more than the minimal number of data points be used when computing geometry using a robust estimator such as RANSAC. Adding two to four extra samples improves the convergence rate and accuracy sufficiently to compensate for the increased number of samples required by the RANSAC process.

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In this article, an enriched radial point interpolation method (e-RPIM) is developed for computational mechanics. The conventional radial basis function (RBF) interpolation is novelly augmented by the suitable basis functions to reflect the natural properties of deformation. The performance of the enriched meshless RBF shape functions is first investigated using the surface fitting. The surface fitting results have proven that, compared with the conventional RBF, the enriched RBF interpolation has a much better accuracy to fit a complex surface than the conventional RBF interpolation. It has proven that the enriched RBF shape function will not only possess all advantages of the conventional RBF interpolation, but also can accurately reflect the deformation properties of problems. The system of equations for two-dimensional solids is then derived based on the enriched RBF shape function and both of the meshless strong-form and weak-form. A numerical example of a bar is presented to study the effectiveness and efficiency of e-RPIM. As an important application, the newly developed e-RPIM, which is augmented by selected trigonometric basis functions, is applied to crack problems. It has been demonstrated that the present e-RPIM is very accurate and stable for fracture mechanics problems.

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Government promotion of active transport has renewed interest in cycling safety. Research has shown that bicyclists are up to 20 times more likely to be involved in serious injury crashes than drivers. On-road cycling injuries are under-reported in police data, and many non-serious injuries are not recorded in any official database. This study aims to explore the relationships between rider characteristics and environmental factors that influence per kilometre risk of bicycle-related crash and non-crash injuries.

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Radial Hele-Shaw flows are treated analytically using conformal mapping techniques. The geometry of interest has a doubly-connected annular region of viscous fluid surrounding an inviscid bubble that is either expanding or contracting due to a pressure difference caused by injection or suction of the inviscid fluid. The zero-surface-tension problem is ill-posed for both bubble expansion and contraction, as both scenarios involve viscous fluid displacing inviscid fluid. Exact solutions are derived by tracking the location of singularities and critical points in the analytic continuation of the mapping function. We show that by treating the critical points, it is easy to observe finite-time blow-up, and the evolution equations may be written in exact form using complex residues. We present solutions that start with cusps on one interface and end with cusps on the other, as well as solutions that have the bubble contracting to a point. For the latter solutions, the bubble approaches an ellipse in shape at extinction.

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The purpose of this study was to determine the effects of cryotherapy, in the form of cold water immersion, on knee joint position sense. Fourteen healthy volunteers, with no previous knee injury or pre-existing clinical condition, participated in this randomized cross-over trial. The intervention consisted of a 30-min immersion, to the level of the umbilicus, in either cold (14 ± 1°C) or tepid water(28 ± 1°C). Approximately one week later, in a randomized fashion, the volunteers completed the remaining immersion. Active ipsilateral limb repositioning sense of the right knee was measured, using weight-bearing and non-weight bearing assessments, employing video-recorded 3D motion analysis. These assessments were conducted immediately before and after a cold and tepid water immersion. No significant differences were found between treatments for the absolute (P = 0.29), relative (P = 0.21) or variable error (P = 0.86). The average effect size of the outcome measures was modest (range –0.49 to 0.9) and all the associated 95% confidence intervals for these effect sizes crossed zero. These results indicate that there is no evidence of an enhanced risk of injury, following a return to sporting activity, after cold water.

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This note examines the productive efficiency of 62 starting guards during the 2011/12 National Basketball Association (NBA) season. This period coincides with the phenomenal and largely unanticipated performance of New York Knicks’ starting point guard Jeremy Lin and the attendant public and media hype known as Linsanity. We employ a data envelopment analysis (DEA) approach that includes allowance for an undesirable output, here turnovers per game, with the desirable outputs of points, rebounds, assists, steals, and blocks per game and an input of minutes per game. The results indicate that depending upon the specification, between 29 and 42 percent of NBA guards are fully efficient, including Jeremy Lin, with a mean inefficiency of 3.7 and 19.2 percent. However, while Jeremy Lin is technically efficient, he seldom serves as a benchmark for inefficient players, at least when compared with established players such as Chris Paul and Dwayne Wade. This suggests the uniqueness of Jeremy Lin’s productive solution and may explain why his unique style of play, encompassing individual brilliance, unselfish play, and team leadership, is of such broad public appeal.

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The quick detection of abrupt (unknown) parameter changes in an observed hidden Markov model (HMM) is important in several applications. Motivated by the recent application of relative entropy concepts in the robust sequential change detection problem (and the related model selection problem), this paper proposes a sequential unknown change detection algorithm based on a relative entropy based HMM parameter estimator. Our proposed approach is able to overcome the lack of knowledge of post-change parameters, and is illustrated to have similar performance to the popular cumulative sum (CUSUM) algorithm (which requires knowledge of the post-change parameter values) when examined, on both simulated and real data, in a vision-based aircraft manoeuvre detection problem.

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Nitrate reduction with nanoscale zero-valent iron (NZVI) was reported as a potential technology to remove nitrate from nitrate-contaminated water. In this paper, nitrate reduction with NZVI prepared by hydrogen reduction of natural goethite (NZVI-N, -N represents natural goethite) and hydrothermal goethite (NZVI-H, -H represents hydrothermal goethite) was conducted. Besides, the effects of reaction time, nitrate concentration, iron-to-nitrate ratio on nitrate removal rate over NZVI-H and NZVI-N were investigated. To prove their excellent nitrate reduction capacities, NZVI-N and NZVI-H were compared with ordinary zero-valent iron (OZVI-N) through the static experiments. Based on all above investigations, the mechanism of nitrate reduction with NZVI-N was proposed. The result showed that reaction time, nitrate concentration, iron-to-nitrate ratio played an important role in nitrate reduction by NZVI-N and NZVI-H. Compared with OZVI, NZVI-N and NZVI-H showed little relationship with pH. And NZVI-N for nitrate composition offers a higher stability than NZVI-H because of the existence of Al-substitution. Furthermore, NZVI-N, prepared by hydrogen reduction of goethite, has higher activity for nitrate reduction and the products contain hydrogen, nitrogen, NH 4 +, a little nitrite, but no NOx, meanwhile NZVI-N was oxidized to Fe 2+. It is a relatively easy and cost-effective method for nitrate removal, so NZVI-N reducing nitrate has a great potential application in nitrate removal of groundwater. © 2012 Elsevier B.V.

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Hybrid system representations have been exploited in a number of challenging modelling situations, including situations where the original nonlinear dynamics are too complex (or too imprecisely known) to be directly filtered. Unfortunately, the question of how to best design suitable hybrid system models has not yet been fully addressed, particularly in the situations involving model uncertainty. This paper proposes a novel joint state-measurement relative entropy rate based approach for design of hybrid system filters in the presence of (parameterised) model uncertainty. We also present a design approach suitable for suboptimal hybrid system filters. The benefits of our proposed approaches are illustrated through design examples and simulation studies.

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Background Cancer survivors face an increased likelihood of being subsequently diagnosed with another cancer. The aim of this study was to quantify the relative risk of survivors developing a second primary cancer in Queensland, Australia. Methods Standardised incidence rates stratified by type of first primary cancer, type of second primary cancer, sex, age at first diagnosis, period of first diagnosis and follow-up interval were calculated for residents of Queensland, Australia, who were diagnosed with a first primary invasive cancer between 1982 and 2001 and survived for a minimum of 2 months. Results A total of 23,580 second invasive primary cancers were observed over 1,370,247 years of follow-up among 204,962 cancer patients. Both males (SIR = 1.22; 95% CI = 1.20-1.24) and females (SIR = 1.36; 95% CI = 1.33-1.39) within the study cohort were found to have a significant excess risk of developing a second cancer relative to the incidence of cancer in the general population. The observed number of second primary cancers was also higher than expected within each age group, across all time periods and during each follow-up interval. Conclusions The excess risk of developing a second malignancy among cancer survivors can likely be attributed to factors including similar aetiologies, genetics and the effects of treatment, underlining the need for ongoing monitoring of cancer patients to detect subsequent tumours at an early stage. Education campaigns developed specifically for survivors may be required to lessen the prevalence of known cancer risk factors.

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This study proceeds from a central interest in the importance of systematically evaluating operational large-scale integrated information systems (IS) in organisations. The study is conducted within the IS-Impact Research Track at Queensland University of Technology (QUT). The goal of the IS-Impact Track is, "to develop the most widely employed model for benchmarking information systems in organizations for the joint benefit of both research and practice" (Gable et al, 2009). The track espouses programmatic research having the principles of incrementalism, tenacity, holism and generalisability through replication and extension research strategies. Track efforts have yielded the bicameral IS-Impact measurement model; the ‘impact’ half includes Organisational-Impact and Individual-Impact dimensions; the ‘quality’ half includes System-Quality and Information-Quality dimensions. Akin to Gregor’s (2006) analytic theory, the ISImpact model is conceptualised as a formative, multidimensional index and is defined as "a measure at a point in time, of the stream of net benefits from the IS, to date and anticipated, as perceived by all key-user-groups" (Gable et al., 2008, p: 381). The study adopts the IS-Impact model (Gable, et al., 2008) as its core theory base. Prior work within the IS-Impact track has been consciously constrained to Financial IS for their homogeneity. This study adopts a context-extension strategy (Berthon et al., 2002) with the aim "to further validate and extend the IS-Impact measurement model in a new context - i.e. a different IS - Human Resources (HR)". The overarching research question is: "How can the impacts of large-scale integrated HR applications be effectively and efficiently benchmarked?" This managerial question (Cooper & Emory, 1995) decomposes into two more specific research questions – In the new HR context: (RQ1): "Is the IS-Impact model complete?" (RQ2): "Is the ISImpact model valid as a 1st-order formative, 2nd-order formative multidimensional construct?" The study adhered to the two-phase approach of Gable et al. (2008) to hypothesise and validate a measurement model. The initial ‘exploratory phase’ employed a zero base qualitative approach to re-instantiating the IS-Impact model in the HR context. The subsequent ‘confirmatory phase’ sought to validate the resultant hypothesised measurement model against newly gathered quantitative data. The unit of analysis for the study is the application, ‘ALESCO’, an integrated large-scale HR application implemented at Queensland University of Technology (QUT), a large Australian university (with approximately 40,000 students and 5000 staff). Target respondents of both study phases were ALESCO key-user-groups: strategic users, management users, operational users and technical users, who directly use ALESCO or its outputs. An open-ended, qualitative survey was employed in the exploratory phase, with the objective of exploring the completeness and applicability of the IS-Impact model’s dimensions and measures in the new context, and to conceptualise any resultant model changes to be operationalised in the confirmatory phase. Responses from 134 ALESCO users to the main survey question, "What do you consider have been the impacts of the ALESCO (HR) system in your division/department since its implementation?" were decomposed into 425 ‘impact citations.’ Citation mapping using a deductive (top-down) content analysis approach instantiated all dimensions and measures of the IS-Impact model, evidencing its content validity in the new context. Seeking to probe additional (perhaps negative) impacts; the survey included the additional open question "In your opinion, what can be done better to improve the ALESCO (HR) system?" Responses to this question decomposed into a further 107 citations which in the main did not map to IS-Impact, but rather coalesced around the concept of IS-Support. Deductively drawing from relevant literature, and working inductively from the unmapped citations, the new ‘IS-Support’ construct, including the four formative dimensions (i) training, (ii) documentation, (iii) assistance, and (iv) authorisation (each having reflective measures), was defined as: "a measure at a point in time, of the support, the [HR] information system key-user groups receive to increase their capabilities in utilising the system." Thus, a further goal of the study became validation of the IS-Support construct, suggesting the research question (RQ3): "Is IS-Support valid as a 1st-order reflective, 2nd-order formative multidimensional construct?" With the aim of validating IS-Impact within its nomological net (identification through structural relations), as in prior work, Satisfaction was hypothesised as its immediate consequence. The IS-Support construct having derived from a question intended to probe IS-Impacts, too was hypothesised as antecedent to Satisfaction, thereby suggesting the research question (RQ4): "What is the relative contribution of IS-Impact and IS-Support to Satisfaction?" With the goal of testing the above research questions, IS-Impact, IS-Support and Satisfaction were operationalised in a quantitative survey instrument. Partial least squares (PLS) structural equation modelling employing 221 valid responses largely evidenced the validity of the commencing IS-Impact model in the HR context. ISSupport too was validated as operationalised (including 11 reflective measures of its 4 formative dimensions). IS-Support alone explained 36% of Satisfaction; IS-Impact alone 70%; in combination both explaining 71% with virtually all influence of ISSupport subsumed by IS-Impact. Key study contributions to research include: (1) validation of IS-Impact in the HR context, (2) validation of a newly conceptualised IS-Support construct as important antecedent of Satisfaction, and (3) validation of the redundancy of IS-Support when gauging IS-Impact. The study also makes valuable contributions to practice, the research track and the sponsoring organisation.

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Objective: To evaluate the impact of a government triple zero community awareness campaign on the characteristics of patients attending an ED. Methods: A study using Emergency Department Information System data was conducted in an adult metropolitan tertiary-referral teaching hospital in Brisbane. The three outcomes measured in the 3 month post-campaign period were arrival mode, Australasian Triage Scale and departure status. These measures reflect ambulance usage, clinical urgency and illness severity, respectively. They were compared with those in the 3 month pre-campaign period. Multivariate logistic regression models were used to investigate the impacts of the campaign on each of the three outcome measures after controlling for age, sex, day and time of arrival, and daily minimum temperature. Results: There were 17 920 visits in the pre- and 17 793 visits in the post-campaign period. After the campaign, fewer patients arrived at the ED by road ambulance (odds ratio [OR] 0.90, 95% confidence interval [CI] 0.80–1.00), although the impact of the campaign on the arrival mode was only close to statistical significance (Wald χ2-test, P= 0.055); and patients were significantly less likely to have higher clinical urgency (OR 0.86, 95% CI 0.79–0.94), while more likely to be admitted (OR 1.68, 95% CI 1.38–2.05) or complete treatment in the ED (OR 1.46, 95% CI 1.23–1.73) instead of leaving without waiting to be seen. Conclusions: The campaign had no significant impact on the arrival mode of the patients. After the campaign, the illness acuity of the patients decreased, whereas the illness severity of the patients increased.