Strategies for embedding agile decision making in aviation infrastructure

As highlighted by previous work in Normal Accident Theory1 and High Reliability Organisations, 2 the ability of a system to be flexible is of critical importance to its capability to prepare for, respond to, and recover from disturbance and disasters. This paper proposes that the research into ‘edge organisations’3 and ‘agility’4 is a potential means to operationalise components that embed high reliable traits in the management and oversight of critical infrastructure systems. Much prior work has focused on these concepts in a military frame whereas the study reported on here examines the application of these concepts to aviation infrastructure, specifically, a commercial international airport. As a commercial entity functions in a distinct manner from a military organisation this study aims to better understand the complementary and contradictory components of the application of agility work to a commercial context. Findings highlight the challenges of making commercial operators of infrastructure systems agile as well as embedding traits of High Reliability in such complex infrastructure settings.

Crisis response planning in tunnel and road networks

Critical road infrastructure (such as tunnels and overpasses) is of major significance to society and constitutes major components of interdependent, ‘systems and networks’. Failure in critical components of these wide area infrastructure systems can often result in cascading disturbances with secondary and tertiary impacts - some of which may become initiating sources of failure in their own right, triggering further systems failures across wider networks. Perrow1) considered the impact of our increasing use of technology in high-risk fields, analysing the implications on everyday life and argued that designers of these types of infrastructure systems cannot predict every possible failure scenario nor create perfect contingency plans for operators. Challenges exist for transport system operators in the conceptualisation and implementation of response and subsequent recovery planning for significant events. Disturbances can vary from reduced traffic flow causing traffic congestion throughout the local road network(s) and subsequent possible loss of income to businesses and industry to a major incident causing loss of life or complete loss of an asset. Many organisations and institutions, despite increasing recognition of the effects of crisis events, are not adequately prepared to manage crises2). It is argued that operators of land transport infrastructure are in a similar category of readiness given the recent instances of failures in road tunnels. These unexpected infrastructure failures, and their ultimately identified causes, suggest there is significant room for improvement. As a result, risk profiles for road transport systems are often complex due to the human behaviours and the inter-mix of technical and organisational components and the managerial coverage needed for the socio-technical components and the physical infrastructure. In this sense, the span of managerial oversight may require new approaches to asset management that combines the notion of risk and continuity management. This paper examines challenges in the planning of response and recovery practices of owner/operators of transport systems (above and below ground) in Australia covering: • Ageing or established infrastructure; and • New-build infrastructure. With reference to relevant international contexts this paper seeks to suggest options for enhancing the planning and practice for crisis response in these transport networks and as a result support the resilience of Critical Infrastructure.

Raman and infrared spectroscopic study of the mineral goyazite SrAl3(PO4)2(OH)5·H2O

We have studied the mineral goyazite using Raman and infrared spectroscopy. Goyazite is a member of the crandallite subgroup of the alunite supergroup. The crystal structure is of the alunite-type and consists of sheets of corner-sharing AlO6 octahedra parallel to (0001). The octahedrally coordinated Sr2+ cations occupy cavities between pairs of octahedral sheets and are surrounded by six oxygen atoms from the (Al3+)O6 octahedra. The very intense sharp band at 983 cm-1 is assigned to the ν1 PO43- symmetric stretching mode. The observation of a single band supports the concept that all the phosphate units are equivalent in the structure of goyazite. Raman bands observed at 1029 cm-1 and 1037 cm-1 are assigned to the to the ν3 PO43- antisymmetric stretching vibrations. Two Raman bands at 895 and 927 cm-1 are attributed to the stretching vibrations of H2PO4; thus indicating some hydrogen phosphate units in the structure of goyazite. Raman bands at 556, 581, 596 and 612 cm-1 are assigned to the ν4 PO43- bending modes, suggesting a reduction of symmetry of phosphate units. Two sharp Raman bands at 3609 and 3631 cm-1 are attributed to OH stretching vibrations from the goyazite hydroxyl units. Broad Raman bands at 2924, 3043, 3210, 3429 and 3511 cm-1 are assigned to water stretching vibrations. Vibrational spectroscopy enables subtle details of the molecular structure of goyazite to be determined.

Dynamic robot path planning using an enhanced simulated annealing approach

Evolutionary computation is an effective tool for solving optimization problems. However, its significant computational demand has limited its real-time and on-line applications, especially in embedded systems with limited computing resources, e.g., mobile robots. Heuristic methods such as the genetic algorithm (GA) based approaches have been investigated for robot path planning in dynamic environments. However, research on the simulated annealing (SA) algorithm, another popular evolutionary computation algorithm, for dynamic path planning is still limited mainly due to its high computational demand. An enhanced SA approach, which integrates two additional mathematical operators and initial path selection heuristics into the standard SA, is developed in this work for robot path planning in dynamic environments with both static and dynamic obstacles. It improves the computing performance of the standard SA significantly while giving an optimal or near-optimal robot path solution, making its real-time and on-line applications possible. Using the classic and deterministic Dijkstra algorithm as a benchmark, comprehensive case studies are carried out to demonstrate the performance of the enhanced SA and other SA algorithms in various dynamic path planning scenarios.

Something’s coming, something good: Identifying TPACK competence in pre-service teachers’ analyses of learning objects

There is a song at the beginning of the musical, West Side Story, where the character Tony sings that “something’s coming, something good.” The song is an anthem of optimism, brimming with promise. This paper is about the long-held promise of information and communication technology (ICT) to transform teaching and learning, to modernise the learning environment of the classroom, and to create a new digital pedagogy. But much of our experience to date in the schooling sector tells more of resistance and reaction than revolution, of more of the same but with a computer in the corner and of ICT activities as unwelcome time-fillers/time-wasters. Recently, a group of pre-service teachers in a postgraduate primary education degree in an Australian university were introduced to learning objects in an ICT immersion program. Their analyses and related responses, as recorded in online journals, have here been interpreted in terms of TPACK (Technological Pedagogical and Content Knowledge). Against contemporary observation, these students generally displayed high levels of competence and highly positive dispositions of students to the integration of ICT in their future classrooms. In short, they displayed the same optimism and confidence as the fictional “Tony” in believing that something good was coming.

Empirical evaluation of public transport travel time variability

Although transit travel time variability is essential for understanding the deterioration of reliability, optimising transit schedule and route choice; it has not attracted enough attention from the literature. This paper proposes public transport-oriented definitions of travel time variability and explores the distributions of public transport travel time using the Transit Signal Priority data. First, definitions of public transport travel time variability are established by extending the common definitions of variability in the literature and by using route and services data of public transport vehicles. Second, the paper explores the distribution of public transport travel time. A new approach for analysing the distributions involving all transit vehicles as well as vehicles from a specific route is proposed. The Lognormal distribution is revealed as the descriptors for public transport travel time from the same route and service. The methods described in this study could be of interest for both traffic managers and transit operators for planning and managing the transit systems.

Composite SaaS resource management in cloud computing using evolutionary computation

Cloud computing is an emerging computing paradigm in which IT resources are provided over the Internet as a service to users. One such service offered through the Cloud is Software as a Service or SaaS. SaaS can be delivered in a composite form, consisting of a set of application and data components that work together to deliver higher-level functional software. SaaS is receiving substantial attention today from both software providers and users. It is also predicted to has positive future markets by analyst firms. This raises new challenges for SaaS providers managing SaaS, especially in large-scale data centres like Cloud. One of the challenges is providing management of Cloud resources for SaaS which guarantees maintaining SaaS performance while optimising resources use. Extensive research on the resource optimisation of Cloud service has not yet addressed the challenges of managing resources for composite SaaS. This research addresses this gap by focusing on three new problems of composite SaaS: placement, clustering and scalability. The overall aim is to develop efficient and scalable mechanisms that facilitate the delivery of high performance composite SaaS for users while optimising the resources used. All three problems are characterised as highly constrained, large-scaled and complex combinatorial optimisation problems. Therefore, evolutionary algorithms are adopted as the main technique in solving these problems. The first research problem refers to how a composite SaaS is placed onto Cloud servers to optimise its performance while satisfying the SaaS resource and response time constraints. Existing research on this problem often ignores the dependencies between components and considers placement of a homogenous type of component only. A precise problem formulation of composite SaaS placement problem is presented. A classical genetic algorithm and two versions of cooperative co-evolutionary algorithms are designed to now manage the placement of heterogeneous types of SaaS components together with their dependencies, requirements and constraints. Experimental results demonstrate the efficiency and scalability of these new algorithms. In the second problem, SaaS components are assumed to be already running on Cloud virtual machines (VMs). However, due to the environment of a Cloud, the current placement may need to be modified. Existing techniques focused mostly at the infrastructure level instead of the application level. This research addressed the problem at the application level by clustering suitable components to VMs to optimise the resource used and to maintain the SaaS performance. Two versions of grouping genetic algorithms (GGAs) are designed to cater for the structural group of a composite SaaS. The first GGA used a repair-based method while the second used a penalty-based method to handle the problem constraints. The experimental results confirmed that the GGAs always produced a better reconfiguration placement plan compared with a common heuristic for clustering problems. The third research problem deals with the replication or deletion of SaaS instances in coping with the SaaS workload. To determine a scaling plan that can minimise the resource used and maintain the SaaS performance is a critical task. Additionally, the problem consists of constraints and interdependency between components, making solutions even more difficult to find. A hybrid genetic algorithm (HGA) was developed to solve this problem by exploring the problem search space through its genetic operators and fitness function to determine the SaaS scaling plan. The HGA also uses the problem's domain knowledge to ensure that the solutions meet the problem's constraints and achieve its objectives. The experimental results demonstrated that the HGA constantly outperform a heuristic algorithm by achieving a low-cost scaling and placement plan. This research has identified three significant new problems for composite SaaS in Cloud. Various types of evolutionary algorithms have also been developed in addressing the problems where these contribute to the evolutionary computation field. The algorithms provide solutions for efficient resource management of composite SaaS in Cloud that resulted to a low total cost of ownership for users while guaranteeing the SaaS performance.

Making the train : an examination of five perspectives of rail access and how they resonate with existing and potential passengers

Rail operators recognize a need to increase ridership in order to improve the economic viability of rail service, and to magnify the role that rail travel plays in making cities feel liveable. This study extends previous research that used cluster analysis with a small sample of rail passengers to identify five salient perspectives of rail access (Zuniga et al, 2013). In this project stage, we used correlation techniques to determine how those perspectives would resonate with two larger study populations, including a relatively homogeneous sample of university students in Brisbane, Australia and a diverse sample of rail passengers in Melbourne, Australia. Findings from Zuniga et al. (2013) described a complex typology of current passengers that was based on respondents’ subjective attitudes and perceptions rather than socio-demographic or travel behaviour characteristics commonly used for segmentation analysis. The typology included five qualitative perspectives of rail travel. Based on the transport accessibility literature, we expected to find that perspectives from that study emphasizing physical access to rail stations would be shared by current and potential rail passengers who live further from rail stations. Other perspectives might be shared among respondents who live nearby, since the relevance of distance would be diminished. The population living nearby would thus represent an important target group for increasing ridership, since making rail travel accessible to them does not require expansion of costly infrastructure such as new lines or stations. By measuring the prevalence of each perspective in a larger respondent pool, results from this study provide insight into the typical socio-demographic and travel behaviour characteristics that correspond to each perspective of intra-urban rail travel. In several instances, our quantitative findings reinforced Zuniga et al.’s (2013) qualitative descriptions of passenger types, further validating the original research. This work may directly inform rail operators’ approach to increasing ridership through marketing and improvements to service quality and station experience. Operators in other parts of Australia and internationally may also choose to replicate the study locally, to fine-tune understanding of diverse customer bases. Developing regional and international collaboration would provide additional opportunities to evaluate and benchmark service and station amenities as they address the various access dimensions.

Impairment of simulated motorcycle riding performance under low dose alcohol

Crash statistics that include the blood alcohol concentration (BAC) of vehicle operators reveal that crash involved motorcyclists are over represented at low BACs (e.g., ≤0.05%). This riding simulator study compared riding performance and hazard response under three low dose alcohol conditions (sober, 0.02% BAC, 0.05% BAC). Forty participants (20 novice, 20 experienced) completed simulated rides in urban and rural scenarios while responding to a safety-critical peripheral detection task (PDT). Results showed a significant increase in the standard deviation of lateral position in the urban scenario and PDT reaction time in the rural scenario under 0.05% BAC compared with zero alcohol. Participants were most likely to collide with an unexpected pedestrian in the urban scenario at 0.02% BAC, with novice participants at a greater relative risk than experienced riders. Novices chose to ride faster than experienced participants in the rural scenario regardless of BAC. Not all results were significant, emphasising the complex situation of the effects of low dose BAC on riding performance, which needs further research. The results of this simulator study provide some support for a legal BAC for motorcyclists below 0.05%.

Continuous monitoring of reservoir water quality: The Wivenhoe Project

The Lake Wivenhoe Integrated Wireless Sensor Network is conceptually similar to traditional SCADA monitoring and control approaches. However, it is applied in an open system using wireless devices to monitor processes that affect water quality at both a high spatial and temporal frequency. This monitoring assists scientists to better understand drivers of key processes that influence water quality and provide the operators with an early warning system if below standard water enters the reservoir. Both of these aspects improve the safety and efficient delivery of drinking water to the end users.

A Sustainable Community for Older People : Case Studies of Green Retirement Villages in Australia

In Australia, the proportion of the population aged 65 years and over reached 13.5% in 2010 and is expected to increase steadily to around 20% by the year 2056 [Australia Bureau of Statistics (ABS), 2010], creating what has been regarded as a looming crisis in how to house and care for older people. As a viable accommodation option, the retirement village is widely accepted as a means of promoting and enhancing independence, choice and quality of life for older people. Recent research by Barker (2010) indicates that the current and potential residents of retirement villages are generally very conscious of resource consumption and would like their residences and community to be more sustainable. The aim of this study was to understand the perception of older people toward sustainability ideas and identify the sustainable practices involved in retirement villages to improve the wellbeing of residents. Multiple research methods, including content analysis, questionnaire survey, interviews and case studies were conducted for the research purpose. The results indicate that most retirement village residents understand and recognize the importance of sustainability in their lifestyle. However, their sustainability requirements need to be supported and enhanced by the provision of affordable sustainability features. Additionally, many retirement village developers and operators realize the importance of providing a sustainable retirement community for their residents, and that a sustainable retirement village (that is environmental-friendly, affordable, and improves social engagement) can be achieved through the consideration of project planning, design, construction, and operations throughout the project life cycle. The clear shift from healthcare to lifestyle-focused services in the recent development of retirement villages together with the increasing number of aged people moving into retirement villages (Simpson and Cheney, 2007) has raised awareness of the need for the retirement village industry to provide a sustainable community for older people to improve their life quality after retirement. This is the first critical study of sustainable development in the retirement village industry and its potential in addressing the housing needs of older people, providing a contribution towards improving the life quality of older people and with direct and immediate significance to the community as a whole.

Continuous remote emissions monitoring – the lynchpin for air quality management

Diesel particulate matter (DPM), in particular, has been likened in a somewhat inflammatory manner to be the ‘next asbestos’. From the business change perspective, there are three areas holding the industry back from fully engaging with the issue: 1. There is no real feedback loop in any operational sense to assess the impact of investment or application of controls to manage diesel emissions. 2. DPM are getting ever smaller and more numerous, but there is no practical way of measuring them to regulate them in the field. Mass, the current basis of regulation, is becoming less and less relevant. 3. Diesel emissions management is generally wholly viewed as a cost, yet there are significant areas of benefit available from good management. This paper discusses a feedback approach to address these three areas to move the industry forward. The six main areas of benefit from providing a feedback loop by continuously monitoring diesel emissions have been identified: 1. Condition-based maintenance. Emissions change instantaneously if engine condition changes. 2. Operator performance. An operator can use a lot more fuel for little incremental work output through poor technique or discipline. 3. Vehicle utilisation. Operating hours achieved and ratios of idling to under power affect the proportion of emissions produced with no economic value. 4. Fuel efficiency. This allows visibility into other contributing configuration and environmental factors for the vehicle. 5. Emission rates. This allows scope to directly address the required ratio of ventilation to diesel emissions. 6. Total carbon emissions - for NGER-type reporting requirements, calculating the emissions individually from each vehicle rather than just reporting on fuel delivered to a site.

Assessing the suitability of market approach valuation methods for mine and quarry valuations

An area of property valuation that has attracted less attention than other property markets over the past 20 years has been the mining and extractive industries. These operations can range from small operators on leased or private land to multinational companies. Although there are a number of national mining standards that indicate the type of valuation methods that can be adopted for this asset class, these standards do not specify how or when these methods are best suited to particular mine operations. The RICS guidance notes and the draft IVSC guidance notes also advise the various valuations methods that can be used to value mining properties; but, again they do not specify what methods should be applied where and when. One of the methods supported by these standards and guidelines is the market approach. This paper will carry out an analysis of all mine, extractive industry and waste disposal sites sale transactions in Queensland Australia, a major world mining centre, to determine if a market valuation approach such as direct comparison is actually suitable for the valuation of a mine or extractive industry. The analysis will cover the period 1984 to 2011 and covers sale transactions for minerals, petroleum and gas, waste disposal sites, clay, sand and stone. Based on this analysis, the suitability of direct comparison for valuation purposes in this property sector will be tested.

The Smartphone App Economy and App Ecosystems

This chapter gives an overview of the smartphone app economy and its various constituent ecosystems. It examines the role of the app store model and the proliferation of mobile apps in the shift from value chains controlled by network operators and handset manufacturers, to value networks – or ecosystems – focused around operating systems and apps. It outlines some of the benefits and disadvantages for developers of the app store model for remuneration and distribution. The chapter concludes with a discussion of recent research on the size and employment effects of the app economy.

Frontier Techniques for Measuring and Estimating Airport Efficiency : An Empirical Review with Practical Guidelines for Analysis and Future Research

Airport efficiency is important because it has a direct impact on customer safety and satisfaction and therefore the financial performance and sustainability of airports, airlines, and affiliated service providers. This is especially so in a world characterized by an increasing volume of both domestic and international air travel, price and other forms of competition between rival airports, airport hubs and airlines, and rapid and sometimes unexpected changes in airline routes and carriers. It also reflects expansion in the number of airports handling regional, national, and international traffic and the growth of complementary airport facilities including industrial, commercial, and retail premises. This has fostered a steadily increasing volume of research aimed at modeling and providing best-practice measures and estimates of airport efficiency using mathematical and econometric frontiers. The purpose of this chapter is to review these various methods as they apply to airports throughout the world. Apart from discussing the strengths and weaknesses of the different approaches and their key findings, the paper also examines the steps faced by researchers as they move through the modeling process in defining airport inputs and outputs and the purported efficiency drivers. Accordingly, the chapter provides guidance to those conducting empirical research on airport efficiency and serves as an aid for aviation regulators and airport operators among others interpreting airport efficiency research outcomes.