Generative systems as relational bridges

Generative media systems present an opportunity for users to leverage computational systems to make sense of complex media forms through interactive and collaborative experiences. Generative music and art are a relatively new phenomenon that use procedural invention as a creative technique to produce music and visual media. These kinds of systems present a range of affordances that can facilitate new kinds of relationships with music and media performance and production. Early systems have demonstrated the potential to provide access to collaborative ensemble experiences to users with little formal musical or artistic expertise. This paper examines the relational affordances of these systems evidenced by selected field data drawn from the Network Jamming Project. These generative performance systems enable access to unique ensemble with very little musical knowledge or skill and they further offer the possibility of unique interactive relationships with artists and musical knowledge through collaborative performance. In this presentation I will focus on demonstrating how these simulated experiences might lead to understandings that may be of educational and social benefit. Conference participants will be invited to jam in real time using virtual interfaces and to view video artifacts that demonstrate an interactive relationship with artists.

Multi-objective mission flight planning in civil unmanned aerial systems

Unmanned Aerial Vehicles (UAVs) are emerging as an ideal platform for a wide range of civil applications such as disaster monitoring, atmospheric observation and outback delivery. However, the operation of UAVs is currently restricted to specially segregated regions of airspace outside of the National Airspace System (NAS). Mission Flight Planning (MFP) is an integral part of UAV operation that addresses some of the requirements (such as safety and the rules of the air) of integrating UAVs in the NAS. Automated MFP is a key enabler for a number of UAV operating scenarios as it aids in increasing the level of onboard autonomy. For example, onboard MFP is required to ensure continued conformance with the NAS integration requirements when there is an outage in the communications link. MFP is a motion planning task concerned with finding a path between a designated start waypoint and goal waypoint. This path is described with a sequence of 4 Dimensional (4D) waypoints (three spatial and one time dimension) or equivalently with a sequence of trajectory segments (or tracks). It is necessary to consider the time dimension as the UAV operates in a dynamic environment. Existing methods for generic motion planning, UAV motion planning and general vehicle motion planning cannot adequately address the requirements of MFP. The flight plan needs to optimise for multiple decision objectives including mission safety objectives, the rules of the air and mission efficiency objectives. Online (in-flight) replanning capability is needed as the UAV operates in a large, dynamic and uncertain outdoor environment. This thesis derives a multi-objective 4D search algorithm entitled Multi- Step A* (MSA*) based on the seminal A* search algorithm. MSA* is proven to find the optimal (least cost) path given a variable successor operator (which enables arbitrary track angle and track velocity resolution). Furthermore, it is shown to be of comparable complexity to multi-objective, vector neighbourhood based A* (Vector A*, an extension of A*). A variable successor operator enables the imposition of a multi-resolution lattice structure on the search space (which results in fewer search nodes). Unlike cell decomposition based methods, soundness is guaranteed with multi-resolution MSA*. MSA* is demonstrated through Monte Carlo simulations to be computationally efficient. It is shown that multi-resolution, lattice based MSA* finds paths of equivalent cost (less than 0.5% difference) to Vector A* (the benchmark) in a third of the computation time (on average). This is the first contribution of the research. The second contribution is the discovery of the additive consistency property for planning with multiple decision objectives. Additive consistency ensures that the planner is not biased (which results in a suboptimal path) by ensuring that the cost of traversing a track using one step equals that of traversing the same track using multiple steps. MSA* mitigates uncertainty through online replanning, Multi-Criteria Decision Making (MCDM) and tolerance. Each trajectory segment is modeled with a cell sequence that completely encloses the trajectory segment. The tolerance, measured as the minimum distance between the track and cell boundaries, is the third major contribution. Even though MSA* is demonstrated for UAV MFP, it is extensible to other 4D vehicle motion planning applications. Finally, the research proposes a self-scheduling replanning architecture for MFP. This architecture replicates the decision strategies of human experts to meet the time constraints of online replanning. Based on a feedback loop, the proposed architecture switches between fast, near-optimal planning and optimal planning to minimise the need for hold manoeuvres. The derived MFP framework is original and shown, through extensive verification and validation, to satisfy the requirements of UAV MFP. As MFP is an enabling factor for operation of UAVs in the NAS, the presented work is both original and significant.

Multi-objective four-dimensional vehicle motion planning in large dynamic environments

This paper presents Multi-Step A* (MSA*), a search algorithm based on A* for multi-objective 4D vehicle motion planning (three spatial and one time dimension). The research is principally motivated by the need for offline and online motion planning for autonomous Unmanned Aerial Vehicles (UAVs). For UAVs operating in large, dynamic and uncertain 4D environments, the motion plan consists of a sequence of connected linear tracks (or trajectory segments). The track angle and velocity are important parameters that are often restricted by assumptions and grid geometry in conventional motion planners. Many existing planners also fail to incorporate multiple decision criteria and constraints such as wind, fuel, dynamic obstacles and the rules of the air. It is shown that MSA* finds a cost optimal solution using variable length, angle and velocity trajectory segments. These segments are approximated with a grid based cell sequence that provides an inherent tolerance to uncertainty. Computational efficiency is achieved by using variable successor operators to create a multi-resolution, memory efficient lattice sampling structure. Simulation studies on the UAV flight planning problem show that MSA* meets the time constraints of online replanning and finds paths of equivalent cost but in a quarter of the time (on average) of vector neighbourhood based A*.

Beef carcasses with larger eye muscle areas, lower ossification scores and improved nutrition have a lower incidence of dark cutting

This study evaluated the effect of eye muscle area (EMA), ossification, carcass weight, marbling and rib fat depth on the incidence of dark cutting (pH u > 5.7) using routinely collected Meat Standards Australia (MSA) data. Data was obtained from 204,072 carcasses at a Western Australian processor between 2002 and 2008. Binomial data of pH u compliance was analysed using a logit model in a Bayesian framework. Increasing eye muscle area from 40 to 80 cm 2, increased pH u compliance by around 14% (P < 0.001) in carcasses less than 350 kg. As carcass weight increased from 150 kg to 220 kg, compliance increased by 13% (P < 0.001) and younger cattle with lower ossification were also 7% more compliant (P < 0.001). As rib fat depth increased from 0 to 20 mm, pH u compliance increased by around 10% (P < 0.001) yet marbling had no effect on dark cutting. Increasing musculature and growth combined with good nutrition will minimise dark cutting beef in Australia.

Methanesulfonic acid-catalyzed conversion of glucose and xylose mixtures to levulinic acid and furfural

Methanesulfonic acid (MSA) was compared with sulfuric acid for the conversion of glucose and xylose mixtures to produce levulinic acid and furfural. The interactions of glucose and xylose, the predominant sugars found in biomass, were found to influence product yields with furfural degradation reactions enhanced under higher reactant loadings. Fast heating rates allowed maximal yields (>60 mol%) of levulinic acid and furfural to be achieved under short reaction times. Under the range of conditions examined, sulfuric acid produced a slight increase in levulinic acid yield by 6% (P = 0.02), although there was no significant difference (P = 0.11) between MSA and sulfuric acid in levulinic acid formed from glucose alone. The amount and type of the solid residue is similar between MSA and sulfuric acid. As such, MSA is a suitable alternative because its use minimizes corrosion and disposal issues associated with mineral acid catalysts. The heating value of the residue was 22 MJ/kg implying that it is a suitable source of fuel. On the basis of these results, a two-stage processing strategy is proposed to target high levulinic acid and furfural yields, and other chemical products (e.g., lactic acid, xylitol, acetic acid and formic acid). This will result in full utilization of bagasse components.

Too cool for school

This article investigates MySchoolAct (MSA),an online music competition created exclusively for Australian high school students. MSA as a social networking platform, creates opportunities for young musicians to showcase their original music and expand their fanbase. From an education perspective, MSA hands ownership of the site to the user, and in this sense empowers young people to engage in meaningful knowledge exchange.

Estimates of lost material stock of buildings and roads due to the great east Japan earthquake and tsunami

This article describes research conducted for the Japanese government in the wake of the magnitude 9.0 earthquake and tsunami that struck eastern Japan on March 11, 2011. In this study, material stock analysis (MSA) is used to examine the losses of building and infrastructure materials after this disaster. Estimates of the magnitude of material stock that has lost its social function as a result of a disaster can indicate the quantities required for reconstruction, help garner a better understanding of the volumes of waste flows generated by that disaster, and also help in the course of policy deliberations in the recovery of disaster-stricken areas. Calculations of the lost building and road materials in the five prefectures most affected were undertaken. Analysis in this study is based on the use of geographical information systems (GIS) databases and statistics; it aims to (1) describe in spatial terms what construction materials were lost, (2) estimate the amount of infrastructure material needed to rehabilitate disaster areas, and (3) indicate the amount of lost material stock that should be taken into consideration during government policy deliberations. Our analysis concludes that the material stock losses of buildings and road infrastructure are 31.8 and 2.1 million tonnes, respectively. This research approach and the use of spatial MSA can be useful for urban planners and may also convey more appropriate information about disposal based on the work of municipalities in disaster-afflicted areas.