Resolving the conflicts of sustainable world heritage landscapes in cities : fully open or limited access for visitors?

World Heritage Landscapes (WHLs) are receiving increased attention from researchers, urban planners, managers, and policy makers and many heritage values and resources are becoming irreversibly lost. This phenomenon is especially prominent for WHLs located in cities, where greater development opportunities are involved. Decision making for sustainable urban landscape planning, conservation and management of WHLs often takes place from an economic perspective, especially in developing countries. This, together with the uncertain source of funding to cover WHL operating and maintenance costs, has resulted in many urban managers seeking private sector funding either in the form of visitor access fees or leasing part of the site for high-rental facilities such as five star hotels, clubs and expensive restaurants. For the former, this can result in low-income urban citizens being unable to afford the access fees and hence contradicting the principle of equal access for all; while, for the latter, the principle of open access for all is equally violated. To resolve this conflict, a game model is developed to determine how urban managers should allocate WHL spaces to maximize the combination of economic, social and ecological benefits and cultural values. A case study is provided of the Hangzhou's West Lake Scenic Area, a WHL located at the centre of Hangzhou city, in which several high-rental facilities have recently been closed down by the local authorities due to charges of elitism and misuse of public funds by government officials. The result shows that the best solution is to lease a small space with high rents and leave the remainder of the site to the public. This solution is likely to be applicable only in cities with a strong economy.

Book review - Richard Goldberg, Medicinal Product Liability and Regulation (Hart Publishing, Oxford, 2013) 214pp

In December 2013, settlement was reached between approximately 100 Australian and New Zealand Thalidomide victims and the company which had acted as the Australian distributor of the infamous drug, thus putting to rest the possibility of litigation. Around the same time, Thalidomide victims in the United Kingdom (UK) launched a similar bid for compensation against the manufacturer and distributor. It is clear that despite a lengthy amount of time having passed ever since the thalidomide disaster commenced in 1962, the controversy over compensation continues. Indeed, the author of Medicinal Product Liability and Regulation (published before the announcement of the British legal claim), Professor Goldberg, notes that claims for resulting birth defects continue to emerge right into the present day. His prescient insight into the contemporary relevance of compensation for pharmaceutical injuries thus makes Medicinal Product Liability and Regulation a very relevant addition to the small body of scholarship that is available on this rather specific and complex issue.

An open pit multistage mine production scheduling model for drilling, blasting and excavating operations

This paper proposes a new multi-resource multi-stage scheduling problem for optimising the open-pit drilling, blasting and excavating operations under equipment capacity constraints. The flow process is analysed based on the real-life data from an Australian iron ore mine site. The objective of the model is to maximise the throughput and minimise the total idle times of equipment at each stage. The following comprehensive mining attributes and constraints have been considered: types of equipment; operating capacities of equipment; ready times of equipment; speeds of equipment; block-sequence-dependent movement times of equipment; equipment-assignment-dependent operation times of blocks; distances between each pair of blocks; due windows of blocks; material properties of blocks; swell factors of blocks; and slope requirements of blocks. It is formulated by mixed integer programming and solved by ILOG-CPLEX optimiser. The proposed model is validated with extensive computational experiments to improve mine production efficiency at the operational level. The model also provides an intelligent decision support tool to account for the availability and usage of equipment units for drilling, blasting and excavating stages.

Long-term outcomes following Medtronic Open Pivot valved conduit

Aortic root replacement is a complex procedure, though subsequent modifications of the original Bentall procedure have made surgery more reproducible. The study aim was to examine the outcomes of a modified Bentall procedure, using the Medtronic Open PivotTM valved conduit. Whilst short-term data on the conduit and long-term data on the valve itself are available, little is known of the long-term results with the valved conduit. Patients undergoing aortic root replacement between February 1999 and February 2010, using the Medtronic Open Pivot valved conduit were identified from the prospectively collected Cardiothoracic Register at The Prince Charles Hospital, Brisbane, Australia. All patients were followed up echocardiographically and clinically. The primary end-point was death, and a Cox proportional model was used to identify factors associated.with survival. Secondary end-points were valve-related morbidity (as defined by STS guidelines) and postoperative morbidity. Predictors of morbidity were identified using logistic regression. A total of 246 patients (mean age 50 years) was included in the study. The overall mortality was 12%, with actuarial 10-year survival 79% and a 10-year estimate of valve-related death of 0.04 (95% CI: 0.004, 0.07). Preoperative myocardial infarction (p = 0.004, HR 4.74), urgency of operation (p = 0.038, HR 2.8) and 10% incremental decreases in ejection fraction (p = 0.046, HR 0.69) were predictive of mortality. Survival was also affected by the valve gradients, with a unit increase in peak gradient reducing mortality (p = 0.021, HR 0.93). Valve-related morbidity occurred in 11 patients. Urgent surgery (p <0.001, OR 4.12), aortic dissection (p = 0.015, OR 3.35), calcific aortic stenosis (p = 0.016, OR 2.35) and Marfan syndrome (p 0.009, OR 3.75) were predictive of postoperative morbidity. The reoperation rate was 1.2%. The Medtronic Open Pivot valved conduit is a safe and durable option for aortic root replacement, and is associated with low morbidity and 10-year survival of 79%. However, further studies are required to determine the effect of valve gradient on survival.

A Likelihood-Maximizing Framework for Enhanced In-Car Speech Recognition Based on Speech Dialog System Interaction

Speech recognition in car environments has been identified as a valuable means for reducing driver distraction when operating noncritical in-car systems. Under such conditions, however, speech recognition accuracy degrades significantly, and techniques such as speech enhancement are required to improve these accuracies. Likelihood-maximizing (LIMA) frameworks optimize speech enhancement algorithms based on recognized state sequences rather than traditional signal-level criteria such as maximizing signal-to-noise ratio. LIMA frameworks typically require calibration utterances to generate optimized enhancement parameters that are used for all subsequent utterances. Under such a scheme, suboptimal recognition performance occurs in noise conditions that are significantly different from that present during the calibration session – a serious problem in rapidly changing noise environments out on the open road. In this chapter, we propose a dialog-based design that allows regular optimization iterations in order to track the ever-changing noise conditions. Experiments using Mel-filterbank noise subtraction (MFNS) are performed to determine the optimization requirements for vehicular environments and show that minimal optimization is required to improve speech recognition, avoid over-optimization, and ultimately assist with semireal-time operation. It is also shown that the proposed design is able to provide improved recognition performance over frameworks incorporating a calibration session only.

The Scent of Ancestral Memory

Poetry expresses the physical and spiritual worlds that other kinds of writing cannot. Travelling open our minds and frees our spirit. Creative writings and meditations on life, spirit, grace and relationships, art and nature weave their way through these lyrical poems. Some poems are suitable for study in the Australian Curriculum.

Investigative relevance

Criminal profiling is one tool available to investigative agencies that may assist in narrowing suspect pools, linking crimes, providing relevant leads and new investigative strategies, and keeping the overall investigation on track (Turvey, 2008). However, like a flashlight in a darkened room, profiling may not always provide valuable assistance if it shines in the wrong direction or fails to shine at all. In a perfect world, profiles are intended to provide investigators with a set of refined characteristics of the offender for a crime or a crime series that will assist their efforts. In contrast, it could be argued that profiles are not intended to provide information that may be irrelevant, unclear, confusing, or distracting to these efforts. Any information provided within the profile that does not assist in narrowing suspect pools or providing new avenues of inquiry is left open to misinterpretation and is therefore potentially damaging (Turvey, 2008). The degree to which information provided in a profile can actually be utilized by investigators to meet their goals is known as investigative relevance...

The Business of Unfinished Business : Reflections on Co-construction of Meanings in Research Encounters

My concern in this commentary is the discrepancy between cultural psychologists' theoretical claims that meanings are co-constructed by, with and for individuals in ongoing social interaction, and their research practices where researcher's and research participant's meaning-making processes are separated in time into sequential turns. I argue for the need to live up to these theoretical assumptions, by making both the initial research encounter and the researcher's later interpretation process more co-constructive. I suggest making the initial research encounter more co-constructive by paying attention to these moments when the negotiated flow of interaction between researcher and research participant breaks down, for it allows the research participant's meaning-making to be traced and makes the researcher's efforts towards meaning more explicit. I propose to make the later interpretation process more co-constructive by adopting a more open-ended and dialogical way of writing that is specifically addressed to research participants and invites them to actively engage with researcher's meaning-making.

Toward the adaptive generation of bespoke game content

In this chapter, we explore methods for automatically generating game content—and games themselves—adapted to individual players in order to improve their playing experience or achieve a desired effect. This goes beyond notions of mere replayability and involves modeling player needs to maximize their enjoyment, involvement, and interest in the game being played. We identify three main aspects of this process: generation of new content and rule sets, measurement of this content and the player, and adaptation of the game to change player experience. This process forms a feedback loop of constant refinement, as games are continually improved while being played. Framed within this methodology, we present an overview of our recent and ongoing research in this area. This is illustrated by a number of case studies that demonstrate these ideas in action over a variety of game types, including 3D action games, arcade games, platformers, board games, puzzles, and open-world games. We draw together some of the lessons learned from these projects to comment on the difficulties, the benefits, and the potential for personalized gaming via adaptive game design.

Learning through modelling in the primary years

Many nations are highlighting the need for a renaissance in the mathematical sciences as essential to the well-being of all citizens (e.g., Australian Academy of Science, 2006; 2010; The National Academies, 2009). Indeed, the first recommendation of The National Academies’ Rising Above the Storm (2007) was to vastly improve K–12 science and mathematics education. The subsequent report, Rising Above the Gathering Storm Two Years Later (2009), highlighted again the need to target mathematics and science from the earliest years of schooling: “It takes years or decades to build the capability to have a society that depends on science and technology . . . You need to generate the scientists and engineers, starting in elementary and middle school” (p. 9). Such pleas reflect the rapidly changing nature of problem solving and reasoning needed in today’s world, beyond the classroom. As The National Academies (2009) reported, “Today the problems are more complex than they were in the 1950s, and more global. They’ll require a new educated workforce, one that is more open, collaborative, and cross-disciplinary” (p. 19). The implications for the problem solving experiences we implement in schools are far-reaching. In this chapter, I consider problem solving and modelling in the primary school, beginning with the need to rethink the experiences we provide in the early years. I argue for a greater awareness of the learning potential of young children and the need to provide stimulating learning environments. I then focus on data modelling as a powerful means of advancing children’s statistical reasoning abilities, which they increasingly need as they navigate their data-drenched world.

Open problem: Shifting experts on easy data

A number of online algorithms have been developed that have small additional loss (regret) compared to the best “shifting expert”. In this model, there is a set of experts and the comparator is the best partition of the trial sequence into a small number of segments, where the expert of smallest loss is chosen in each segment. The regret is typically defined for worst-case data / loss sequences. There has been a recent surge of interest in online algorithms that combine good worst-case guarantees with much improved performance on easy data. A practically relevant class of easy data is the case when the loss of each expert is iid and the best and second best experts have a gap between their mean loss. In the full information setting, the FlipFlop algorithm by De Rooij et al. (2014) combines the best of the iid optimal Follow-The-Leader (FL) and the worst-case-safe Hedge algorithms, whereas in the bandit information case SAO by Bubeck and Slivkins (2012) competes with the iid optimal UCB and the worst-case-safe EXP3. We ask the same question for the shifting expert problem. First, we ask what are the simple and efficient algorithms for the shifting experts problem when the loss sequence in each segment is iid with respect to a fixed but unknown distribution. Second, we ask how to efficiently unite the performance of such algorithms on easy data with worst-case robustness. A particular intriguing open problem is the case when the comparator shifts within a small subset of experts from a large set under the assumption that the losses in each segment are iid.

An architecture for trustworthy open data services

This paper addresses the development of trust in the use of Open Data through incorporation of appropriate authentication and integrity parameters for use by end user Open Data application developers in an architecture for trustworthy Open Data Services. The advantages of this architecture scheme is that it is far more scalable, not another certificate-based hierarchy that has problems with certificate revocation management. With the use of a Public File, if the key is compromised: it is a simple matter of the single responsible entity replacing the key pair with a new one and re-performing the data file signing process. Under this proposed architecture, the the Open Data environment does not interfere with the internal security schemes that might be employed by the entity. However, this architecture incorporates, when needed, parameters from the entity, e.g. person who authorized publishing as Open Data, at the time that datasets are created/added.