Keeping clear on costs: Geatches v Anglo Coal (Moranbah North Management Pty Ltd) [2014] QSC 106

In Geatches v Anglo Coal (Moranbah North Management Pty Ltd [2014] QSC 106, a dispute arose in the context of an assessment of costs as to the meaning to be attributed to particular terms of settlement and discharge signed by the parties. The court was required to consider the implications of those documents, and of a subsequent consent order intended to reflect the agreed settlement. Recovery of costs - terms of settlement and discharge exclude recovery of costs against one party and require other party to pay costs of claim against it - whether only subsequent consent order should be construed - implications where costs were common and mixed costs - whether costs should be apportioned

On the construction of costs: McDermott v Robinson Helicopter Company (No.2) [2014] QSC 213

The decision in McDermott v Robinson Helicopter Company (No 2) [2014] QSC 213 involves an extensive examination of authorities on the general principle relating to the awarding of costs to a successful party. The court concluded that there was a predilection in favour of distributing costs according to the outcome or 'event' of particular issues in the action.

Harnessing information from injury narrative in the 'big data' era: Understanding and applying machine learning for injury surveillance

Objective Vast amounts of injury narratives are collected daily and are available electronically in real time and have great potential for use in injury surveillance and evaluation. Machine learning algorithms have been developed to assist in identifying cases and classifying mechanisms leading to injury in a much timelier manner than is possible when relying on manual coding of narratives. The aim of this paper is to describe the background, growth, value, challenges and future directions of machine learning as applied to injury surveillance. Methods This paper reviews key aspects of machine learning using injury narratives, providing a case study to demonstrate an application to an established human-machine learning approach. Results The range of applications and utility of narrative text has increased greatly with advancements in computing techniques over time. Practical and feasible methods exist for semi-automatic classification of injury narratives which are accurate, efficient and meaningful. The human-machine learning approach described in the case study achieved high sensitivity and positive predictive value and reduced the need for human coding to less than one-third of cases in one large occupational injury database. Conclusion The last 20 years have seen a dramatic change in the potential for technological advancements in injury surveillance. Machine learning of ‘big injury narrative data’ opens up many possibilities for expanded sources of data which can provide more comprehensive, ongoing and timely surveillance to inform future injury prevention policy and practice.

Obvious error in approach to default costs assessment

The decision of Henry J in Ginn & Anor v Ginn; ex parte Absolute Law Lawyers & Attorneys [2015] QSC 49 provides clarification of the approach to be taken on a default costs assessment under r708 of the Uniform Civil Procedure Rules 1999

Design and Development of an In-Vehicle Human Machine Interface to Improve Fuel Efficiency & Safety

Road transport plays a significant role in various industries and mobility services around the globe and has a vital impact on our daily lives. However it also has serious impacts on both public health and the environment. In-vehicle feedback systems are a relatively new approach to encouraging driver behaviour change for improving fuel efficiency and safety in automotive environments. While many studies claim that the adoption of eco-driving practices, such as eco-driving training programs and in-vehicle feedback to drivers, has the potential to improve fuel efficiency, limited research has integrated safety and eco-driving. Therefore, this research seeks to use human factors related theories and practices to inform the design and evaluation of an in-vehicle Human Machine Interface (HMI) providing real-time driver feedback with the aim of improving both fuel efficiency and safety.

No win no fee - no lien and no costs

In Lupker v Shine Lawyers Pty Ltd [2015] QSC 278 Bond J considered the implications for a law practice in relation to its entitlement to recovery of its professional fees when the client terminates a no win no fee retainer.

Costs on review - what charges are appropriate?

In Picamore Pty Ltd v Challen [2015] QDC 067 McGill DCJ considered the nature of a review under r742 of the Uniform Civil Procedure Rules 1999 (Qld) (UCPR) in the context of a review of a costs assessment conducted under the Legal Profession Act 2007 (Qld). His Honour increased the amount that had been allowed by the costs assessor for a number of items. The judgment includes observations about what may appropriately be charged for particular items of legal work.

Change to costs and lengths of stay in the emergency department and the Brisbane protocol: An observational study

- Objective To compare health service cost and length of stay between a traditional and an accelerated diagnostic approach to assess acute coronary syndromes (ACS) among patients who presented to the emergency department (ED) of a large tertiary hospital in Australia. - Design, setting and participants This historically controlled study analysed data collected from two independent patient cohorts presenting to the ED with potential ACS. The first cohort of 938 patients was recruited in 2008–2010, and these patients were assessed using the traditional diagnostic approach detailed in the national guideline. The second cohort of 921 patients was recruited in 2011–2013 and was assessed with the accelerated diagnostic approach named the Brisbane protocol. The Brisbane protocol applied early serial troponin testing for patients at 0 and 2 h after presentation to ED, in comparison with 0 and 6 h testing in traditional assessment process. The Brisbane protocol also defined a low-risk group of patients in whom no objective testing was performed. A decision tree model was used to compare the expected cost and length of stay in hospital between two approaches. Probabilistic sensitivity analysis was used to account for model uncertainty. - Results Compared with the traditional diagnostic approach, the Brisbane protocol was associated with reduced expected cost of $1229 (95% CI −$1266 to $5122) and reduced expected length of stay of 26 h (95% CI −14 to 136 h). The Brisbane protocol allowed physicians to discharge a higher proportion of low-risk and intermediate-risk patients from ED within 4 h (72% vs 51%). Results from sensitivity analysis suggested the Brisbane protocol had a high chance of being cost-saving and time-saving. - Conclusions This study provides some evidence of cost savings from a decision to adopt the Brisbane protocol. Benefits would arise for the hospital and for patients and their families.

Tax compliance and psychic costs: Behavioral experimental evidence using a physiological marker

Although paying taxes is a key element of a well-functioning society, there is still limited understanding as to why people actually pay their taxes. Models emphasizing that taxpayers make strategic, financially motivated compliance decisions seemingly assume an overly restrictive view of human nature. Law abidance may be more accurately explained by social norms, a concept that has gained growing importance as research attempts to understand the tax compliance puzzle. This study analyzes the influence of psychic stress generated by the possibility of breaking social norms in the tax compliance context. We measure psychic stress using heart rate variability (HRV), which captures the psychobiological or neural equivalents of psychic stress that may arise from the contemplation of real or imagined actions, producing immediate physiologic discomfort. The results of our laboratory experiments provide empirical evidence of a positive correlation between psychic stress and tax compliance, thus underscoring the importance of moral sentiments for tax compliance. We also identify three distinct types of individuals who differ in their levels of psychic stress, tax morale, and tax compliance.

Malaria burden and costs of intensified control in Bhutan, 2006-2014: A situational analysis

- Introduction Malaria cases have dwindled in Bhutan with aim of malaria elimination by 2016. The aims of this study are to determine the trends and burden of malaria, the costs of intensified control activities, the main donors of the control activities and the costs of different preventive measures in the pre-elimination phase (2006-2014). - Methods A descriptive analysis of malaria surveillance data from 2006-2014 was carried out, using data from the Vector-borne Disease Control Programme (VDCP), Bhutan. Malaria morbidity and mortality among local Bhutanese and foreign nationals were analysed. The cost of different control and preventive measures, and estimation of the average numbers of long-lasting insecticidal nests (LLINs) per person were calculated. - Findings There were 5,491 confirmed malaria cases from 2006 to 2014. By 2013, there was an average of one LLIN for every 1·51 individuals. The Global Fund was the main international donor accounting for > 80% of the total funds. The cost of procuring LLINs accounted for > 90% of the total cost of prevention measures. - Interpretation The malaria burden reduced significantly over the study period with high coverage of LLINs in Bhutan. This foreseeable challenges that require national attention to maintain malaria-free status after elimination are importation of malaria, particularly from India; continued protection of the population in endemic districts through complete coverage with LLINs and IRS; and exploration of local funding modalities post elimination in the event there is a reduction in international funding.

Improved wound management at lower costs: A sensible goal for Australia

Chronic wounds cost the Australian health system at least US$2·85 billion per year. Wound care services in Australia involve a complex mix of treatment options, health care sectors and funding mechanisms. It is clear that implementation of evidence-based wound care coincides with large health improvements and cost savings, yet the majority of Australians with chronic wounds do not receive evidence-based treatment. High initial treatment costs, inadequate reimbursement, poor financial incentives to invest in optimal care and limitations in clinical skills are major barriers to the adoption of evidence-based wound care. Enhanced education and appropriate financial incentives in primary care will improve uptake of evidence-based practice. Secondary-level wound specialty clinics to fill referral gaps in the community, boosted by appropriate credentialing, will improve access to specialist care. In order to secure funding for better services in a competitive environment, evidence of cost-effectiveness is required. Future effort to generate evidence on the cost-effectiveness of wound management interventions should provide evidence that decision makers find easy to interpret. If this happens, and it will require a large effort of health services research, it could be used to inform future policy and decision-making activities, reduce health care costs and improve patient outcomes.

R1STM: One-class support tensor machine with randomised kernel

Identifying unusual or anomalous patterns in an underlying dataset is an important but challenging task in many applications. The focus of the unsupervised anomaly detection literature has mostly been on vectorised data. However, many applications are more naturally described using higher-order tensor representations. Approaches that vectorise tensorial data can destroy the structural information encoded in the high-dimensional space, and lead to the problem of the curse of dimensionality. In this paper we present the first unsupervised tensorial anomaly detection method, along with a randomised version of our method. Our anomaly detection method, the One-class Support Tensor Machine (1STM), is a generalisation of conventional one-class Support Vector Machines to higher-order spaces. 1STM preserves the multiway structure of tensor data, while achieving significant improvement in accuracy and efficiency over conventional vectorised methods. We then leverage the theory of nonlinear random projections to propose the Randomised 1STM (R1STM). Our empirical analysis on several real and synthetic datasets shows that our R1STM algorithm delivers comparable or better accuracy to a state-of-the-art deep learning method and traditional kernelised approaches for anomaly detection, while being approximately 100 times faster in training and testing.

Cost-efficient virtual machine management in data centers

Virtual Machine (VM) management is an obvious need in today's data centers for various management activities and is accomplished in two phases— finding an optimal VM placement plan and implementing that placement through live VM migrations. These phases result in two research problems— VM placement problem (VMPP) and VM migration scheduling problem (VMMSP). This research proposes and develops several evolutionary algorithms and heuristic algorithms to address the VMPP and VMMSP. Experimental results show the effectiveness and scalability of the proposed algorithms. Finally, a VM management framework has been proposed and developed to automate the VM management activity in cost-efficient way.

Mixed pixel analysis for flood mapping using extended support vector machine

This paper addresses the challenges of flood mapping using multispectral images. Quantitative flood mapping is critical for flood damage assessment and management. Remote sensing images obtained from various satellite or airborne sensors provide valuable data for this application, from which the information on the extent of flood can be extracted. However the great challenge involved in the data interpretation is to achieve more reliable flood extent mapping including both the fully inundated areas and the 'wet' areas where trees and houses are partly covered by water. This is a typical combined pure pixel and mixed pixel problem. In this paper, an extended Support Vector Machines method for spectral unmixing developed recently has been applied to generate an integrated map showing both pure pixels (fully inundated areas) and mixed pixels (trees and houses partly covered by water). The outputs were compared with the conventional mean based linear spectral mixture model, and better performance was demonstrated with a subset of Landsat ETM+ data recorded at the Daly River Basin, NT, Australia, on 3rd March, 2008, after a flood event.

Spectral unmixing with estimated adaptive endmember index using Extended Support Vector Machine

The most difficult operation in the flood inundation mapping using optical flood images is to separate fully inundated areas from the ‘wet’ areas where trees and houses are partly covered by water. This can be referred as a typical problem the presence of mixed pixels in the images. A number of automatic information extraction image classification algorithms have been developed over the years for flood mapping using optical remote sensing images. Most classification algorithms generally, help in selecting a pixel in a particular class label with the greatest likelihood. However, these hard classification methods often fail to generate a reliable flood inundation mapping because the presence of mixed pixels in the images. To solve the mixed pixel problem advanced image processing techniques are adopted and Linear Spectral unmixing method is one of the most popular soft classification technique used for mixed pixel analysis. The good performance of linear spectral unmixing depends on two important issues, those are, the method of selecting endmembers and the method to model the endmembers for unmixing. This paper presents an improvement in the adaptive selection of endmember subset for each pixel in spectral unmixing method for reliable flood mapping. Using a fixed set of endmembers for spectral unmixing all pixels in an entire image might cause over estimation of the endmember spectra residing in a mixed pixel and hence cause reducing the performance level of spectral unmixing. Compared to this, application of estimated adaptive subset of endmembers for each pixel can decrease the residual error in unmixing results and provide a reliable output. In this current paper, it has also been proved that this proposed method can improve the accuracy of conventional linear unmixing methods and also easy to apply. Three different linear spectral unmixing methods were applied to test the improvement in unmixing results. Experiments were conducted in three different sets of Landsat-5 TM images of three different flood events in Australia to examine the method on different flooding conditions and achieved satisfactory outcomes in flood mapping.