Prediction and proactivity in real-time interactive music systems

We advocate for the use of predictive techniques in interactive computer music systems. We suggest that the inclusion of prediction can assist in the design of proactive rather than reactive computational performance partners. We summarize the significant role prediction plays in human musical decisions, and the only modest use of prediction in interactive music systems to date. After describing how we are working toward employing predictive processes in our own metacreation software we reflect on future extensions to these approaches.

Predicting invasion in grassland ecosystems: is exotic dominance the real embarrassment of richness?

Invasions have increased the size of regional species pools, but are typically assumed to reduce native diversity. However, global-scale tests of this assumption have been elusive because of the focus on exotic species richness, rather than relative abundance. This is problematic because low invader richness can indicate invasion resistance by the native community or, alternatively, dominance by a single exotic species. Here, we used a globally replicated study to quantify relationships between exotic richness and abundance in grass-dominated ecosystems in 13 countries on six continents, ranging from salt marshes to alpine tundra. We tested effects of human land use, native community diversity, herbivore pressure, and nutrient limitation on exotic plant dominance. Despite its widespread use, exotic richness was a poor proxy for exotic dominance at low exotic richness, because sites that contained few exotic species ranged from relatively pristine (low exotic richness and cover) to almost completely exotic-dominated ones (low exotic richness but high exotic cover). Both exotic cover and richness were predicted by native plant diversity (native grass richness) and land use (distance to cultivation). Although climate was important for predicting both exotic cover and richness, climatic factors predicting cover (precipitation variability) differed from those predicting richness (maximum temperature and mean temperature in the wettest quarter). Herbivory and nutrient limitation did not predict exotic richness or cover. Exotic dominance was greatest in areas with low native grass richness at the site- or regional-scale. Although this could reflect native grass displacement, a lack of biotic resistance is a more likely explanation, given that grasses comprise the most aggressive invaders. These findings underscore the need to move beyond richness as a surrogate for the extent of invasion, because this metric confounds monodominance with invasion resistance. Monitoring species' relative abundance will more rapidly advance our understanding of invasions.

The Law of Real Property Mortgages [2nd. Ed.]

This book examines the principles and practice of real estate mortgages in an easily accessible text referenced to all the Australian States. It specifically deals with the major theoretical and practical aspects of the land mortgage, including vitiating factors in formation, mortgagees’ powers and duties and mortgagors’ rights – both statutory and other – as well as assignment, insurance and discharge. It focuses exclusively on real estate mortgages and provides a thorough account of the law through analysis of the plethora of court decisions and statutory provisions in this area. Duncan and Dixon analyse the substance of the mortgage transaction from creation through to rights of enforcement. In its detailed consideration of the rights and obligations of mortgagors and mortgagees, it covers topics such as priorities and tacking, insurance, variation and assignment, rights of discharge, entry into possession, foreclosure and power of sale. In addition, the book contains a separate chapter on factors that may affect the validity and enforcement of a mortgage, together with separate consideration of a mortgagee’s right to enforce a guarantee provided on behalf of a mortgagor, and the rights and liabilities associated with a receivership regime initiated by

Real-time video event detection in crowded scenes using MPEG derived features : a multiple instance learning approach

This paper presents an investigation into event detection in crowded scenes, where the event of interest co-occurs with other activities and only binary labels at the clip level are available. The proposed approach incorporates a fast feature descriptor from the MPEG domain, and a novel multiple instance learning (MIL) algorithm using sparse approximation and random sensing. MPEG motion vectors are used to build particle trajectories that represent the motion of objects in uniform video clips, and the MPEG DCT coefficients are used to compute a foreground map to remove background particles. Trajectories are transformed into the Fourier domain, and the Fourier representations are quantized into visual words using the K-Means algorithm. The proposed MIL algorithm models the scene as a linear combination of independent events, where each event is a distribution of visual words. Experimental results show that the proposed approaches achieve promising results for event detection compared to the state-of-the-art.

Pulse-coupled neural network performance for real-time identification of vegetation during forced landing

Safety concerns in the operation of autonomous aerial systems require safe-landing protocols be followed during situations where the a mission should be aborted due to mechanical or other failure. On-board cameras provide information that can be used in the determination of potential landing sites, which are continually updated and ranked to prevent injury and minimize damage. Pulse Coupled Neural Networks have been used for the detection of features in images that assist in the classification of vegetation and can be used to minimize damage to the aerial vehicle. However, a significant drawback in the use of PCNNs is that they are computationally expensive and have been more suited to off-line applications on conventional computing architectures. As heterogeneous computing architectures are becoming more common, an OpenCL implementation of a PCNN feature generator is presented and its performance is compared across OpenCL kernels designed for CPU, GPU and FPGA platforms. This comparison examines the compute times required for network convergence under a variety of images obtained during unmanned aerial vehicle trials to determine the plausibility for real-time feature detection.

Residential real estate education and globalisation in Australian real estate markets and practices

The purpose of this scoping paper is to offer an overview of the literature to determine the development to date in the area of residential real estate agency academic and career education in respect to Foreign Direct Investment (FDI) transactions and implications in Australia. This paper will review studies on the issue of foreign real estate ownership and FDI in Australian real estate markets to develop an understanding of the current state of knowledge on residential real estate agency practice, career education and real estate licensing requirements in Australia. The distinction between the real estate profession education, compared to other professions such as accounting, legal and finance is based on the intensity of the professional career training prior or post formal academic training. Real estate education could be carried out with relatively higher standards in terms of licensing requirement, career and academic education. As FDI in the Australian real estate market is a complex globalisation and economic phenomenon, a simple content of residential real estate training and education may not promote proper management or capacity in dealing with relevant foreign residential property market transaction. The preliminary summarising from the literature of residential real estate agency education, with its current relevant or emerging licensing requirement are focused on its role and effectiveness and impact in residential real estate market. Particular focus will be directed to the FDI relevant residential real estate agency transactions and practices, which have been strongly influenced by the current residential real estate market and agency practices. Taken together, there are many opportunities for future research to extend our understanding and improving the residential real estate agency education and training of Foreign Direct Investment in the Australian residential real estate sector.

Real estate agents : why is education important?

Real Estate Agency education in Australia has undergone many changes during the last 40 years. This is primarily due to the changing nature of consumer protection provided by government and the expectation of increased fields of knowledge relating to real estate transactions. Each state and territory within Australia has a range of regulatory bodies to oversee consumer protection and the distinct licenses and educational requirements that comprise their regimes. Since the 1970’s minimum educational requirements in New South Wales are prescribed for real estate agency work. However, very little research exists in the Australian literature, where an analysis has been undertaken to evaluate these changes, which includes course content, hours allocated for each subject, assessment criteria for each subject,the educational qualification attained, and the requirement for industry experience as a pre-requisite for licensing approval. It is argued that the change to educational requirements, has impacted negatively for the consumer, with an increase in consumer complaints, particularly during the last 10 years.

Study of the effect of M&A on real estate industry firms' performance

This paper proposes to adopt data envelopment analysis (DEA) based Malmquist total factor productivity (TFP) indices methods to evaluate the effect of mergers and acquisitions (M&As) on acquirers in short-term and long-term window. Based on analyzing 32 M&A deals conducted by Chinese real estate firms from 2000-2011, the study result demonstrate that the effect of M&A on developers’ performance is positive. Through M&A, the developers’ Malmquist TFP experienced a steady growth; their technology has got noticeable progress immediately after acquisition; and their technical efficiency has suffered a slight decrease in short-term after acquisition, but then achieved marked increase in the long-term when realization of integration and synergy. However, there is no evidence that the real estate firms have achieved scale efficiency improvement after M&A in either short-term or long-term.

A novel real time pricing scheme for demand response in residential distribution systems

Price based technique is one way to handle increase in peak demand and deal with voltage violations in residential distribution systems. This paper proposes an improved real time pricing scheme for residential customers with demand response option. Smart meters and in-home display units are used to broadcast the price and appropriate load adjustment signals. Customers are given an opportunity to respond to the signals and adjust the loads. This scheme helps distribution companies to deal with overloading problems and voltage issues in a more efficient way. Also, variations in wholesale electricity prices are passed on to electricity customers to take collective measure to reduce network peak demand. It is ensured that both customers and utility are benefitted by this scheme.

Intercontinental haptic teleoperation of a flying vehicle : a step towards real-time applications

This paper describes the theory and practice for a stable haptic teleoperation of a flying vehicle. It extends passivity-based control framework for haptic teleoperation of aerial vehicles in the longest intercontinental setting that presents great challenges. The practicality of the control architecture has been shown in maneuvering and obstacle-avoidance tasks over the internet with the presence of significant time-varying delays and packet losses. Experimental results are presented for teleoperation of a slave quadrotor in Australia from a master station in the Netherlands. The results show that the remote operator is able to safely maneuver the flying vehicle through a structure using haptic feedback of the state of the slave and the perceived obstacles.

Real-time mobile 3D temperature mapping

The ability to measure surface temperature and represent it on a metrically accurate 3D model has proven applications in many areas such as medical imaging, building energy auditing, and search and rescue. A system is proposed that enables this task to be performed with a handheld sensor, and for the first time with results able to be visualized and analyzed in real-time. A device comprising a thermal-infrared camera and range sensor is calibrated geometrically and used for data capture. The device is localized using a combination of ICP and video-based pose estimation from the thermal-infrared video footage which is shown to reduce the occurrence of failure modes. Furthermore, the problem of misregistration which can introduce severe distortions in assigned surface temperatures is avoided through the use of a risk-averse neighborhood weighting mechanism. Results demonstrate that the system is more stable and accurate than previous approaches, and can be used to accurately model complex objects and environments for practical tasks.

Developing a dashboard for real-time data stream composition and visualization

Technological advances have led to an influx of affordable hardware that supports sensing, computation and communication. This hardware is increasingly deployed in public and private spaces, tracking and aggregating a wealth of real-time environmental data. Although these technologies are the focus of several research areas, there is a lack of research dealing with the problem of making these capabilities accessible to everyday users. This thesis represents a first step towards developing systems that will allow users to leverage the available infrastructure and create custom tailored solutions. It explores how this notion can be utilized in the context of energy monitoring to improve conventional approaches. The project adopted a user-centered design process to inform the development of a flexible system for real-time data stream composition and visualization. This system features an extensible architecture and defines a unified API for heterogeneous data streams. Rather than displaying the data in a predetermined fashion, it makes this information available as building blocks that can be combined and shared. It is based on the insight that individual users have diverse information needs and presentation preferences. Therefore, it allows users to compose rich information displays, incorporating personally relevant data from an extensive information ecosystem. The prototype was evaluated in an exploratory study to observe its natural use in a real-world setting, gathering empirical usage statistics and conducting semi-structured interviews. The results show that a high degree of customization does not warrant sustained usage. Other factors were identified, yielding recommendations for increasing the impact on energy consumption.

A reference station-based GNSS computing mode to support unified precise point positioning and real-time kinematic services

Currently, the GNSS computing modes are of two classes: network-based data processing and user receiver-based processing. A GNSS reference receiver station essentially contributes raw measurement data in either the RINEX file format or as real-time data streams in the RTCM format. Very little computation is carried out by the reference station. The existing network-based processing modes, regardless of whether they are executed in real-time or post-processed modes, are centralised or sequential. This paper describes a distributed GNSS computing framework that incorporates three GNSS modes: reference station-based, user receiver-based and network-based data processing. Raw data streams from each GNSS reference receiver station are processed in a distributed manner, i.e., either at the station itself or at a hosting data server/processor, to generate station-based solutions, or reference receiver-specific parameters. These may include precise receiver clock, zenith tropospheric delay, differential code biases, ambiguity parameters, ionospheric delays, as well as line-of-sight information such as azimuth and elevation angles. Covariance information for estimated parameters may also be optionally provided. In such a mode the nearby precise point positioning (PPP) or real-time kinematic (RTK) users can directly use the corrections from all or some of the stations for real-time precise positioning via a data server. At the user receiver, PPP and RTK techniques are unified under the same observation models, and the distinction is how the user receiver software deals with corrections from the reference station solutions and the ambiguity estimation in the observation equations. Numerical tests demonstrate good convergence behaviour for differential code bias and ambiguity estimates derived individually with single reference stations. With station-based solutions from three reference stations within distances of 22–103 km the user receiver positioning results, with various schemes, show an accuracy improvement of the proposed station-augmented PPP and ambiguity-fixed PPP solutions with respect to the standard float PPP solutions without station augmentation and ambiguity resolutions. Overall, the proposed reference station-based GNSS computing mode can support PPP and RTK positioning services as a simpler alternative to the existing network-based RTK or regionally augmented PPP systems.