Automated control of a dragline using machine vision

The research described in this paper is directed toward increasing productivity of draglines through automation. In particular, it focuses on the swing-to-dump, dump, and return-to-dig phases of the dragline operational cycle by developing a swing automation system. In typical operation the dragline boom can be in motion for up to 80% of the total cycle time. This provides considerable scope for improving cycle time through automated or partially automated boom motion control. This paper describes machine vision based sensor technology and control algorithms under development to solve the problem of continuous real time bucket location and control. Incorporation of this capability into existing dragline control systems will then enable true automation of dragline swing and dump operations.

Development of a Systematic Approach to Assessing Quality within Australian Residential Aged Care Facilities: The Clinical Care Indicators Tool

Recent years have seen the introduction of formalised accreditation processes in both community and residential aged care, but these only partially address quality assessment within this sector. Residential aged care in Australia does not yet have a standardised system of resident assessment related to clinical, rather than administrative, outcomes. This paper describes the development of a quality assessment tool aimed at addressing this gap. Utilising previous research and the results of nominal groups with experts in the field, the 21-item Clinical Care Indicators (CCI) Tool for residential aged care was developed and trialled nationally. The CCI Tool was found to be simple to use and an effective means of collecting data on the state of resident health and care, with potential benefits for resident care planning and continuous quality improvement within facilities and organisations. The CCI Tool was further refined through a small intervention study to assess its utility as a quality improvement instrument and to investigate its relationship with resident quality of life. The current version covers 23 clinical indicators, takes about 30 minutes to complete and is viewed favourably by nursing staff who use it. Current work focuses on psychometric analysis and benchmarking, which should enable the CCI Tool to make a positive contribution to the measurement of quality in aged care in Australia.

The Machine Vision Toolbox : A MATLAB Toolbox for vision and vision-based control

The article described an open-source toolbox for machine vision called Machine Vision Toolbox (MVT). MVT includes more than 60 functions including image file reading and writing, acquisition, display, filtering, blob, point and line feature extraction, mathematical morphology, homographies, visual Jacobians, camera calibration, and color space conversion. MVT can be used for research into machine vision but is also versatile enough to be usable for real-time work and even control. MVT, combined with MATLAB and a model workstation computer, is a useful and convenient environment for the investigation of machine vision algorithms. The article illustrated the use of a subset of toolbox functions for some typical problems and described MVT operations including the simulation of a complete image-based visual servo system.

Validity of the Waterlow screening tool and risks for pressure injury in acute care

Objectives: To assess the validity of the Waterlow screening tool in a cohort of internal medicine patients and to identify factors contributing to pressure injury. Design: Longitudinal cohort study Setting: A tertiary hospital in Brisbane, Australia Participants: 274 patients admitted through the Emergency Department or outpatient clinics and expected to remain in hospital for at least three days were included in the study. The mean age was 65.3 years. Interventions: Patients were screened on admission using the Waterlow screening tool. Every second day, their pressure ulcer status was monitored and recorded. Main outcome measures: Pressure ulcer incidence Results: Fifteen participants (5.5%) had an existing pressure ulcer and a further 12 (4.4%) developed a pressure ulcer during their hospital stay. Sensitivity of the Waterlow scale was 0.67, (95% CI: 0.35 to 0.88); specificity 0.79, (95% CI: 0.73 to 0.85); PPV 0.13, (95% CI: 0.07 to 0.24); NPV 0.98, (95% CI: 0.94 to 0.99). Conclusion: This study provides further evidence of the poor predictive validity of the Waterlow scale. A suitably powered randomised controlled trial is urgently needed to provide definitive evidence about the usefulness of the Waterlow scale compared with other screening tools and with clinical judgement.

The risky behaviour of young drivers : developing a measurement tool

The contribution of risky behaviour to the increased crash and fatality rates of young novice drivers is recognised in the road safety literature around the world. Exploring such risky driver behaviour has led to the development of tools like the Driver Behaviour Questionnaire (DBQ) to examine driving violations, errors, and lapses [1]. Whilst the DBQ has been utilised in young novice driver research, some items within this tool seem specifically designed for the older, more experienced driver, whilst others appear to asses both behaviour and related motives. The current study was prompted by the need for a risky behaviour measurement tool that can be utilised with young drivers with a provisional driving licence. Sixty-three items exploring young driver risky behaviour developed from the road safety literature were incorporated into an online survey. These items assessed driver, passenger, journey, car and crash-related issues. A sample of 476 drivers aged 17-25 years (M = 19, SD = 1.59 years) with a provisional driving licence and matched for age, gender, and education were drawn from a state-wide sample of 761 young drivers who completed the survey. Factor analysis based upon a principal components extraction of factors was followed by an oblique rotation to investigate the underlying dimensions to young novice driver risky behaviour. A five factor solution comprising 44 items was identified, accounting for 55% of the variance in young driver risky behaviour. Factor 1 accounted for 32.5% of the variance and appeared to measure driving violations that were transient in nature - risky behaviours that followed risky decisions that occurred during the journey (e.g., speeding). Factor 2 accounted for 10.0% of variance and appeared to measure driving violations that were fixed in nature; the risky decisions being undertaken before the journey (e.g., drink driving). Factor 3 accounted for 5.4% of variance and appeared to measure misjudgment (e.g., misjudged speed of oncoming vehicle). Factor 4 accounted for 4.3% of variance and appeared to measure risky driving exposure (e.g., driving at night with friends as passengers). Factor 5 accounted for 2.8% of variance and appeared to measure driver emotions or mood (e.g., anger). Given that the aim of the study was to create a research tool, the factors informed the development of five subscales and one composite scale. The composite scale had a very high internal consistency measure (Cronbach’s alpha) of .947. Self-reported data relating to police-detected driving offences, their crash involvement, and their intentions to break road rules within the next year were also collected. While the composite scale was only weakly correlated with self-reported crashes (r = .16, p < .001), it was moderately correlated with offences (r = .26, p < .001), and highly correlated with their intentions to break the road rules (r = .57, p < .001). Further application of the developed scale is needed to confirm the factor structure within other samples of young drivers both in Australia and in other countries. In addition, future research could explore the applicability of the scale for investigating the behaviour of other types of drivers.

Modelling and solving train scheduling problems under capacity constraints

Many large coal mining operations in Australia rely heavily on the rail network to transport coal from mines to coal terminals at ports for shipment. Over the last few years, due to the fast growing demand, the coal rail network is becoming one of the worst industrial bottlenecks in Australia. As a result, this provides great incentives for pursuing better optimisation and control strategies for the operation of the whole rail transportation system under network and terminal capacity constraints. This PhD research aims to achieve a significant efficiency improvement in a coal rail network on the basis of the development of standard modelling approaches and generic solution techniques. Generally, the train scheduling problem can be modelled as a Blocking Parallel- Machine Job-Shop Scheduling (BPMJSS) problem. In a BPMJSS model for train scheduling, trains and sections respectively are synonymous with jobs and machines and an operation is regarded as the movement/traversal of a train across a section. To begin, an improved shifting bottleneck procedure algorithm combined with metaheuristics has been developed to efficiently solve the Parallel-Machine Job- Shop Scheduling (PMJSS) problems without the blocking conditions. Due to the lack of buffer space, the real-life train scheduling should consider blocking or hold-while-wait constraints, which means that a track section cannot release and must hold a train until the next section on the routing becomes available. As a consequence, the problem has been considered as BPMJSS with the blocking conditions. To develop efficient solution techniques for BPMJSS, extensive studies on the nonclassical scheduling problems regarding the various buffer conditions (i.e. blocking, no-wait, limited-buffer, unlimited-buffer and combined-buffer) have been done. In this procedure, an alternative graph as an extension of the classical disjunctive graph is developed and specially designed for the non-classical scheduling problems such as the blocking flow-shop scheduling (BFSS), no-wait flow-shop scheduling (NWFSS), and blocking job-shop scheduling (BJSS) problems. By exploring the blocking characteristics based on the alternative graph, a new algorithm called the topological-sequence algorithm is developed for solving the non-classical scheduling problems. To indicate the preeminence of the proposed algorithm, we compare it with two known algorithms (i.e. Recursive Procedure and Directed Graph) in the literature. Moreover, we define a new type of non-classical scheduling problem, called combined-buffer flow-shop scheduling (CBFSS), which covers four extreme cases: the classical FSS (FSS) with infinite buffer, the blocking FSS (BFSS) with no buffer, the no-wait FSS (NWFSS) and the limited-buffer FSS (LBFSS). After exploring the structural properties of CBFSS, we propose an innovative constructive algorithm named the LK algorithm to construct the feasible CBFSS schedule. Detailed numerical illustrations for the various cases are presented and analysed. By adjusting only the attributes in the data input, the proposed LK algorithm is generic and enables the construction of the feasible schedules for many types of non-classical scheduling problems with different buffer constraints. Inspired by the shifting bottleneck procedure algorithm for PMJSS and characteristic analysis based on the alternative graph for non-classical scheduling problems, a new constructive algorithm called the Feasibility Satisfaction Procedure (FSP) is proposed to obtain the feasible BPMJSS solution. A real-world train scheduling case is used for illustrating and comparing the PMJSS and BPMJSS models. Some real-life applications including considering the train length, upgrading the track sections, accelerating a tardy train and changing the bottleneck sections are discussed. Furthermore, the BPMJSS model is generalised to be a No-Wait Blocking Parallel- Machine Job-Shop Scheduling (NWBPMJSS) problem for scheduling the trains with priorities, in which prioritised trains such as express passenger trains are considered simultaneously with non-prioritised trains such as freight trains. In this case, no-wait conditions, which are more restrictive constraints than blocking constraints, arise when considering the prioritised trains that should traverse continuously without any interruption or any unplanned pauses because of the high cost of waiting during travel. In comparison, non-prioritised trains are allowed to enter the next section immediately if possible or to remain in a section until the next section on the routing becomes available. Based on the FSP algorithm, a more generic algorithm called the SE algorithm is developed to solve a class of train scheduling problems in terms of different conditions in train scheduling environments. To construct the feasible train schedule, the proposed SE algorithm consists of many individual modules including the feasibility-satisfaction procedure, time-determination procedure, tune-up procedure and conflict-resolve procedure algorithms. To find a good train schedule, a two-stage hybrid heuristic algorithm called the SE-BIH algorithm is developed by combining the constructive heuristic (i.e. the SE algorithm) and the local-search heuristic (i.e. the Best-Insertion- Heuristic algorithm). To optimise the train schedule, a three-stage algorithm called the SE-BIH-TS algorithm is developed by combining the tabu search (TS) metaheuristic with the SE-BIH algorithm. Finally, a case study is performed for a complex real-world coal rail network under network and terminal capacity constraints. The computational results validate that the proposed methodology would be very promising because it can be applied as a fundamental tool for modelling and solving many real-world scheduling problems.

Some applications of logic to feasibility in higher types

While it is commonly accepted that computability on a Turing machine in polynomial time represents a correct formalization of the notion of a feasibly computable function, there is no similar agreement on how to extend this notion on functionals, that is, what functionals should be considered feasible. One possible paradigm was introduced by Mehlhorn, who extended Cobham's definition of feasible functions to type 2 functionals. Subsequently, this class of functionals (with inessential changes of the definition) was studied by Townsend who calls this class POLY, and by Kapron and Cook who call the same class basic feasible functionals. Kapron and Cook gave an oracle Turing machine model characterisation of this class. In this article, we demonstrate that the class of basic feasible functionals has recursion theoretic properties which naturally generalise the corresponding properties of the class of feasible functions, thus giving further evidence that the notion of feasibility of functionals mentioned above is correctly chosen. We also improve the Kapron and Cook result on machine representation.Our proofs are based on essential applications of logic. We introduce a weak fragment of second order arithmetic with second order variables ranging over functions from NN which suitably characterises basic feasible functionals, and show that it is a useful tool for investigating the properties of basic feasible functionals. In particular, we provide an example how one can extract feasible programs from mathematical proofs that use nonfeasible functions.