Rapid prototyping framework for visual control of autonomous micro aerial vehicles

Rapid prototyping environments can speed up the research of visual control algorithms. We have designed and implemented a software framework for fast prototyping of visual control algorithms for Micro Aerial Vehicles (MAV). We have applied a combination of a proxy-based network communication architecture and a custom Application Programming Interface. This allows multiple experimental configurations, like drone swarms or distributed processing of a drone's video stream. Currently, the framework supports a low-cost MAV: the Parrot AR.Drone. Real tests have been performed on this platform and the results show comparatively low figures of the extra communication delay introduced by the framework, while adding new functionalities and flexibility to the selected drone. This implementation is open-source and can be downloaded from www.vision4uav.com/?q=VC4MAV-FW

Adoption of low-cost rail level crossing warning devices : an Australian case study

The objective of this chapter is to provide rail practitioners with a practical approach for determining safety requirements of low-cost level crossing warning devices (LCLCWDs) on an Australian railway by way of a case study. LCLCWDs, in theory, allow railway operators to improve the safety of passively controlled crossing by upgrading a larger number of level crossings with the same budget that would otherwise be used to upgrade these using the conventional active level crossing control technologies, e.g. track circuit initiated flashing light systems. The chapter discusses the experience and obstacles of adopting LCLCWDs in Australia, and demonstrates how the risk-based approach may be used to make the case for LCLCWDs.

Bayesian hierarchical models in statistical quality control methods to improve healthcare in hospitals

Quality oriented management systems and methods have become the dominant business and governance paradigm. From this perspective, satisfying customers’ expectations by supplying reliable, good quality products and services is the key factor for an organization and even government. During recent decades, Statistical Quality Control (SQC) methods have been developed as the technical core of quality management and continuous improvement philosophy and now are being applied widely to improve the quality of products and services in industrial and business sectors. Recently SQC tools, in particular quality control charts, have been used in healthcare surveillance. In some cases, these tools have been modified and developed to better suit the health sector characteristics and needs. It seems that some of the work in the healthcare area has evolved independently of the development of industrial statistical process control methods. Therefore analysing and comparing paradigms and the characteristics of quality control charts and techniques across the different sectors presents some opportunities for transferring knowledge and future development in each sectors. Meanwhile considering capabilities of Bayesian approach particularly Bayesian hierarchical models and computational techniques in which all uncertainty are expressed as a structure of probability, facilitates decision making and cost-effectiveness analyses. Therefore, this research investigates the use of quality improvement cycle in a health vii setting using clinical data from a hospital. The need of clinical data for monitoring purposes is investigated in two aspects. A framework and appropriate tools from the industrial context are proposed and applied to evaluate and improve data quality in available datasets and data flow; then a data capturing algorithm using Bayesian decision making methods is developed to determine economical sample size for statistical analyses within the quality improvement cycle. Following ensuring clinical data quality, some characteristics of control charts in the health context including the necessity of monitoring attribute data and correlated quality characteristics are considered. To this end, multivariate control charts from an industrial context are adapted to monitor radiation delivered to patients undergoing diagnostic coronary angiogram and various risk-adjusted control charts are constructed and investigated in monitoring binary outcomes of clinical interventions as well as postintervention survival time. Meanwhile, adoption of a Bayesian approach is proposed as a new framework in estimation of change point following control chart’s signal. This estimate aims to facilitate root causes efforts in quality improvement cycle since it cuts the search for the potential causes of detected changes to a tighter time-frame prior to the signal. This approach enables us to obtain highly informative estimates for change point parameters since probability distribution based results are obtained. Using Bayesian hierarchical models and Markov chain Monte Carlo computational methods, Bayesian estimators of the time and the magnitude of various change scenarios including step change, linear trend and multiple change in a Poisson process are developed and investigated. The benefits of change point investigation is revisited and promoted in monitoring hospital outcomes where the developed Bayesian estimator reports the true time of the shifts, compared to priori known causes, detected by control charts in monitoring rate of excess usage of blood products and major adverse events during and after cardiac surgery in a local hospital. The development of the Bayesian change point estimators are then followed in a healthcare surveillances for processes in which pre-intervention characteristics of patients are viii affecting the outcomes. In this setting, at first, the Bayesian estimator is extended to capture the patient mix, covariates, through risk models underlying risk-adjusted control charts. Variations of the estimator are developed to estimate the true time of step changes and linear trends in odds ratio of intensive care unit outcomes in a local hospital. Secondly, the Bayesian estimator is extended to identify the time of a shift in mean survival time after a clinical intervention which is being monitored by riskadjusted survival time control charts. In this context, the survival time after a clinical intervention is also affected by patient mix and the survival function is constructed using survival prediction model. The simulation study undertaken in each research component and obtained results highly recommend the developed Bayesian estimators as a strong alternative in change point estimation within quality improvement cycle in healthcare surveillances as well as industrial and business contexts. The superiority of the proposed Bayesian framework and estimators are enhanced when probability quantification, flexibility and generalizability of the developed model are also considered. The empirical results and simulations indicate that the Bayesian estimators are a strong alternative in change point estimation within quality improvement cycle in healthcare surveillances. The superiority of the proposed Bayesian framework and estimators are enhanced when probability quantification, flexibility and generalizability of the developed model are also considered. The advantages of the Bayesian approach seen in general context of quality control may also be extended in the industrial and business domains where quality monitoring was initially developed.

Reducing actuator switchings for motion control of autonomous underwater vehicles

A priority when designing control strategies for autonomous underwater vehicles is to emphasize their cost of implementation on a real vehicle and at the same time to minimize a prescribed criterion such as time, energy, payload or combination of those. Indeed, the major issue is that due to the vehicles' design and the actuation modes usually under consideration for underwater platforms the number of actuator switchings must be kept to a small value to ensure feasibility and precision. This constraint is typically not verified by optimal trajectories which might not even be piecewise constants. Our goal is to provide a feasible trajectory that minimizes the number of switchings while maintaining some qualities of the desired trajectory, such as optimality with respect to a given criterion. The one-sided Lipschitz constant is used to derive theoretical estimates. The theory is illustrated on two examples, one is a fully actuated underwater vehicle capable of motion in six degrees-of-freedom and one is minimally actuated with control motions constrained to the vertical plane.

Evaluation of the cost-effectiveness of strategies claiming to reduce the risk of surgical site infections following primary total hip arthroplasty

Background Total hip arthroplasty (THA) is a commonly performed procedure and numbers are increasing with ageing populations. One of the most serious complications in THA are surgical site infections (SSIs), caused by pathogens entering the wound during the procedure. SSIs are associated with a substantial burden for health services, increased mortality and reduced functional outcomes in patients. Numerous approaches to preventing these infections exist but there is no gold standard in practice and the cost-effectiveness of alternate strategies is largely unknown. Objectives The aim of this project was to evaluate the cost-effectiveness of strategies claiming to reduce deep surgical site infections following total hip arthroplasty in Australia. The objectives were: 1. Identification of competing strategies or combinations of strategies that are clinically relevant to the control of SSI related to hip arthroplasty 2. Evidence synthesis and pooling of results to assess the volume and quality of evidence claiming to reduce the risk of SSI following total hip arthroplasty 3. Construction of an economic decision model incorporating cost and health outcomes for each of the identified strategies 4. Quantification of the effect of uncertainty in the model 5. Assessment of the value of perfect information among model parameters to inform future data collection Methods The literature relating to SSI in THA was reviewed, in particular to establish definitions of these concepts, understand mechanisms of aetiology and microbiology, risk factors, diagnosis and consequences as well as to give an overview of existing infection prevention measures. Published economic evaluations on this topic were also reviewed and limitations for Australian decision-makers identified. A Markov state-transition model was developed for the Australian context and subsequently validated by clinicians. The model was designed to capture key events related to deep SSI occurring within the first 12 months following primary THA. Relevant infection prevention measures were selected by reviewing clinical guideline recommendations combined with expert elicitation. Strategies selected for evaluation were the routine use of pre-operative antibiotic prophylaxis (AP) versus no use of antibiotic prophylaxis (No AP) or in combination with antibiotic-impregnated cement (AP & ABC) or laminar air operating rooms (AP & LOR). The best available evidence for clinical effect size and utility parameters was harvested from the medical literature using reproducible methods. Queensland hospital data were extracted to inform patients’ transitions between model health states and related costs captured in assigned treatment codes. Costs related to infection prevention were derived from reliable hospital records and expert opinion. Uncertainty of model input parameters was explored in probabilistic sensitivity analyses and scenario analyses and the value of perfect information was estimated. Results The cost-effectiveness analysis was performed from a health services perspective using a hypothetical cohort of 30,000 THA patients aged 65 years. The baseline rate of deep SSI was 0.96% within one year of a primary THA. The routine use of antibiotic prophylaxis (AP) was highly cost-effective and resulted in cost savings of over $1.6m whilst generating an extra 163 QALYs (without consideration of uncertainty). Deterministic and probabilistic analysis (considering uncertainty) identified antibiotic prophylaxis combined with antibiotic-impregnated cement (AP & ABC) to be the most cost-effective strategy. Using AP & ABC generated the highest net monetary benefit (NMB) and an incremental $3.1m NMB compared to only using antibiotic prophylaxis. There was a very low error probability that this strategy might not have the largest NMB (<5%). Not using antibiotic prophylaxis (No AP) or using both antibiotic prophylaxis combined with laminar air operating rooms (AP & LOR) resulted in worse health outcomes and higher costs. Sensitivity analyses showed that the model was sensitive to the initial cohort starting age and the additional costs of ABC but the best strategy did not change, even for extreme values. The cost-effectiveness improved for a higher proportion of cemented primary THAs and higher baseline rates of deep SSI. The value of perfect information indicated that no additional research is required to support the model conclusions. Conclusions Preventing deep SSI with antibiotic prophylaxis and antibiotic-impregnated cement has shown to improve health outcomes among hospitalised patients, save lives and enhance resource allocation. By implementing a more beneficial infection control strategy, scarce health care resources can be used more efficiently to the benefit of all members of society. The results of this project provide Australian policy makers with key information about how to efficiently manage risks of infection in THA.

Why do policy decision-makers opt for command and control environmental regulation? An economic analysis with special reference to Sri Lanka

This chapter examines why policy decision-makers opt for command and control environmental regulation despite the availability of a plethora of market-based instruments which are more efficient and cost-effective. Interestingly, Sri Lanka has adopted a wholly command and control system, during both the pre and post liberalisation economic policies. This chapter first examines the merits and demerits of command and control and market-based approaches and then looks at Sri Lanka’s extensive environmental regulatory framework. The chapter then examines the likely reasons as to why the country has gone down the path of inflexible regulatory measures and has become entrenched in them. The various hypotheses are discussed and empirical evidence is provided. The chapter also discusses the consequences of an environmentally slack economy and policy implications stemming from adopting a wholly regulatory approach. The chapter concludes with a discussion of the main results.

Budget-aware role based access control

The suitability of Role Based Access Control (RBAC) is being challenged in dynamic environments like healthcare. In an RBAC system, a user's legitimate access may be denied if their need has not been anticipated by the security administrator at the time of policy specification. Alternatively, even when the policy is correctly specified an authorised user may accidentally or intentionally misuse the granted permission. The heart of the challenge is the intrinsic unpredictability of users' operational needs as well as their incentives to misuse permissions. In this paper we propose a novel Budget-aware Role Based Access Control (B-RBAC) model that extends RBAC with the explicit notion of budget and cost, where users are assigned a limited budget through which they pay for the cost of permissions they need. We propose a model where the value of resources are explicitly defined and an RBAC policy is used as a reference point to discriminate the price of access permissions, as opposed to representing hard and fast rules for making access decisions. This approach has several desirable properties. It enables users to acquire unassigned permissions if they deem them necessary. However, users misuse capability is always bounded by their allocated budget and is further adjustable through the discrimination of permission prices. Finally, it provides a uniform mechanism for the detection and prevention of misuses.

Cost-effectiveness analysis of a kidney and cardiovascular disease treatment program in an Australian Aboriginal population

The objective of the study was to assess, from a health service perspective, whether a systematic program to modify kidney and cardiovascular disease reduced the costs of treating end-stage kidney failure. The participants in the study were 1,800 aboriginal adults with hypertension, diabetes with microalbuminuria or overt albuminuria, and overt albuminuria, living on two islands in the Northern Territory of Australia during 1995 to 2000. Perindopril was the primary treatment agent, and other medications were also used to control blood pressure. Control of glucose and lipid levels were attempted, and health education was offered. Evaluation of program resource use and costs for follow-up periods was done at 3 and 4.7 years. On an intention-to-treat basis, the number of dialysis starts and dialysis-years avoided were estimated by comparing the fate of the treatment group with that of historical control subjects, matched for disease severity, who were followed in the before the treatment program began. For the first three years, an estimated 11.6 person-years of dialysis were avoided, and over 4.7 years, 27.7 person-years of dialysis were avoided. The net cost of the program was 1,210 dollars more per person per year than status quo care, and dialyses avoided gave net savings of 1.0 million dollars at 3 years and 3.4 million dollars at 4.6 years. The treatment program provided significant health benefit and impressive cost savings in dialysis avoided.

Key priorities for Australian infection control : summary of findings from the launch of the Centre for Research Excellence in Reducing Healthcare Associated Infections

The launch of the Centre of Research Excellence in Reducing Healthcare Associated Infection (CRE-RHAI) took place in Sydney on Friday 12 October 2012. The mission of the CRE-RHAI is to generate new knowledge about strategies to reduce healthcare associated infections and to provide data on the cost-effectiveness of infection control programs. As well as launching the CRE-RHAI, an important part of this event was a stakeholder Consultation Workshop, which brought together several experts in the Australian infection control community. The aims of this workshop were to establish the research and clinical priorities in Australian infection control, assess the importance of various multi-resistant organisms, and to gather information about decision making in infection control. We present here a summary and discussion of the responses we received.

Vertical infrastructure inspection using a quadcopter and shared autonomy control

This paper presents a shared autonomy control scheme for a quadcopter that is suited for inspection of vertical infrastructure — tall man-made structures such as streetlights, electricity poles or the exterior surfaces of buildings. Current approaches to inspection of such structures is slow, expensive, and potentially hazardous. Low-cost aerial platforms with an ability to hover now have sufficient payload and endurance for this kind of task, but require significant human skill to fly. We develop a control architecture that enables synergy between the ground-based operator and the aerial inspection robot. An unskilled operator is assisted by onboard sensing and partial autonomy to safely fly the robot in close proximity to the structure. The operator uses their domain knowledge and problem solving skills to guide the robot in difficult to reach locations to inspect and assess the condition of the infrastructure. The operator commands the robot in a local task coordinate frame with limited degrees of freedom (DOF). For instance: up/down, left/right, toward/away with respect to the infrastructure. We therefore avoid problems of global mapping and navigation while providing an intuitive interface to the operator. We describe algorithms for pole detection, robot velocity estimation with respect to the pole, and position estimation in 3D space as well as the control algorithms and overall system architecture. We present initial results of shared autonomy of a quadrotor with respect to a vertical pole and robot performance is evaluated by comparing with motion capture data.

Approaches to access control under uncertainty

The ultimate goal of an access control system is to allocate each user the precise level of access they need to complete their job - no more and no less. This proves to be challenging in an organisational setting. On one hand employees need enough access to the organisation’s resources in order to perform their jobs and on the other hand more access will bring about an increasing risk of misuse - either intentionally, where an employee uses the access for personal benefit, or unintentionally, through carelessness or being socially engineered to give access to an adversary. This thesis investigates issues of existing approaches to access control in allocating optimal level of access to users and proposes solutions in the form of new access control models. These issues are most evident when uncertainty surrounding users’ access needs, incentive to misuse and accountability are considered, hence the title of the thesis. We first analyse access control in environments where the administrator is unable to identify the users who may need access to resources. To resolve this uncertainty an administrative model with delegation support is proposed. Further, a detailed technical enforcement mechanism is introduced to ensure delegated resources cannot be misused. Then we explicitly consider that users are self-interested and capable of misusing resources if they choose to. We propose a novel game theoretic access control model to reason about and influence the factors that may affect users’ incentive to misuse. Next we study access control in environments where neither users’ access needs can be predicted nor they can be held accountable for misuse. It is shown that by allocating budget to users, a virtual currency through which they can pay for the resources they deem necessary, the need for a precise pre-allocation of permissions can be relaxed. The budget also imposes an upper-bound on users’ ability to misuse. A generalised budget allocation function is proposed and it is shown that given the context information the optimal level of budget for users can always be numerically determined. Finally, Role Based Access Control (RBAC) model is analysed under the explicit assumption of administrators’ uncertainty about self-interested users’ access needs and their incentives to misuse. A novel Budget-oriented Role Based Access Control (B-RBAC) model is proposed. The new model introduces the notion of users’ behaviour into RBAC and provides means to influence users’ incentives. It is shown how RBAC policy can be used to individualise the cost of access to resources and also to determine users’ budget. The implementation overheads of B-RBAC is examined and several low-cost sub-models are proposed.

Surgical site infection prevention following total hip arthroplasty in Australia : a cost-effectiveness analysis

Background: Surgical site infection (SSI) is associated with substantial costs for health services, reduced quality of life, and functional outcomes. The aim of this study was to evaluate the cost-effectiveness of strategies claiming to reduce the risk of SSI in hip arthroplasty in Australia. Methods: Baseline use of antibiotic prophylaxis (AP) was compared with no antibiotic prophylaxis (no AP), antibiotic-impregnated cement (AP þ ABC), and laminar air operating rooms (AP þ LOR). A Markov model was used to simulate long-term health and cost outcomes of a hypothetical cohort of 30,000 total hip arthroplasty patients from a health services perspective. Model parameters were informed by the best available evidence. Uncertainty was explored in probabilistic sensitivity and scenario analyses. Results: Stopping the routine use of AP resulted in over Australian dollars (AUD) $1.5 million extra costs and a loss of 163 quality-adjusted life years (QALYs). Using antibiotic cement in addition to AP (AP þ ABC)generated an extra 32 QALYs while saving over AUD $123,000. The use of laminar air operating rooms combined with routine AP (AP þ LOR) resulted in an AUD $4.59 million cost increase and 127 QALYs lost compared with the baseline comparator. Conclusion: Preventing deep SSI with antibiotic prophylaxis and antibiotic-impregnated cement has shown to improve health outcomes among hospitalized patients, save lives, and enhance resource allocation. Based on this evidence, the use of laminar air operating rooms is not recommended.

Reply - Malnutrition and its impact on cost of hospitalization, length of stay, readmission and 3-year mortality

Dear Editor We thank Dr Klek for his interest in our article and giving us the opportunity to clarify our study and share our thoughts. Our study looks at the prevalence of malnutrition in an acute tertiary hospital and tracked the outcomes prospectively.1 There are a number of reasons why we chose Subjective Global Assessment (SGA) to determine the nutritional status of patients. Firstly, we took the view that nutrition assessment tools should be used to determine nutrition status and diagnose presence and severity of malnutrition; whereas the purpose of nutrition screening tools are to identify individuals who are at risk of malnutrition. Nutritional assessment rather than screening should be used as the basis for planning and evaluating nutrition interventions for those diagnosed with malnutrition. Secondly, Subjective Global Assessment (SGA) has been well accepted and validated as an assessment tool to diagnose the presence and severity of malnutrition in clinical practice.2, 3 It has been used in many studies as a valid prognostic indicator of a range of nutritional and clinical outcomes.4, 5, 6 On the other hand, Malnutrition Universal Screening Tool (MUST)7 and Nutrition Risk Screening 2002 (NRS 2002)8 have been established as screening rather than assessment tools.

Coordinated probabilistic optimal decision-making model for multi-area ATC with risk control

In the decision-making of multi-area ATC (Available Transfer Capacity) in electricity market environment, the existing resources of transmission network should be optimally dispatched and coordinately employed on the premise that the secure system operation is maintained and risk associated is controllable. The non-sequential Monte Carlo simulation is used to determine the ATC probability density distribution of specified areas under the influence of several uncertainty factors, based on which, a coordinated probabilistic optimal decision-making model with the maximal risk benefit as its objective is developed for multi-area ATC. The NSGA-II is applied to calculate the ATC of each area, which considers the risk cost caused by relevant uncertainty factors and the synchronous coordination among areas. The essential characteristics of the developed model and the employed algorithm are illustrated by the example of IEEE 118-bus test system. Simulative result shows that, the risk of multi-area ATC decision-making is influenced by the uncertainties in power system operation and the relative importance degrees of different areas.

Humans, ‘things’ and space : costing hospital infection control interventions

Background: Previous attempts at costing infection control programmes have tended to focus on accounting costs rather than economic costs. For studies using economic costs, estimates tend to be quite crude and probably underestimate the true cost. One of the largest costs of any intervention is staff time, but this cost is difficult to quantify and has been largely ignored in previous attempts. Aim: To design and evaluate the costs of hospital-based infection control interventions or programmes. This article also discusses several issues to consider when costing interventions, and suggests strategies for overcoming these issues. Methods: Previous literature and techniques in both health economics and psychology are reviewed and synthesized. Findings: This article provides a set of generic, transferable costing guidelines. Key principles such as definition of study scope and focus on large costs, as well as pitfalls (e.g. overconfidence and uncertainty), are discussed. Conclusion: These new guidelines can be used by hospital staff and other researchers to cost their infection control programmes and interventions more accurately.