The sound of music : sharing song selections between collocated strangers in public urban places

This paper presents Capital Music, a mobile application enabling real-time sharing of song choices with collocated urban dwellers. Due to the real-time, location-based peer-to-peer approach of the application, a user experience study was performed utilising the Wizard of Oz method. The study provides insight into how sharing non-privacy sensitive but personal data in an anonymous way can influence the user experience of people in public urban places. We discuss the findings in relation to how Capital Music influences the process of “cocooning” in public urban places, the practice of designing anonymous interactions between collocated strangers, and how the sharing of song choices can create a sense of commonality between anonymous users in the urban space. The outcomes of this study are relevant for future location-based social networking applications that aim to create interactions between collocated strangers.

Automatic region-of-interest detection and prioritisation for visually optimised coding of low bit rate videos

The increasing popularity of video consumption from mobile devices requires an effective video coding strategy. To overcome diverse communication networks, video services often need to maintain sustainable quality when the available bandwidth is limited. One of the strategy for a visually-optimised video adaptation is by implementing a region-of-interest (ROI) based scalability, whereby important regions can be encoded at a higher quality while maintaining sufficient quality for the rest of the frame. The result is an improved perceived quality at the same bit rate as normal encoding, which is particularly obvious at the range of lower bit rate. However, because of the difficulties of predicting region-of-interest (ROI) accurately, there is a limited research and development of ROI-based video coding for general videos. In this paper, the phase spectrum quaternion of Fourier Transform (PQFT) method is adopted to determine the ROI. To improve the results of ROI detection, the saliency map from the PQFT is augmented with maps created from high level knowledge of factors that are known to attract human attention. Hence, maps that locate faces and emphasise the centre of the screen are used in combination with the saliency map to determine the ROI. The contribution of this paper lies on the automatic ROI detection technique for coding a low bit rate videos which include the ROI prioritisation technique to give different level of encoding qualities for multiple ROIs, and the evaluation of the proposed automatic ROI detection that is shown to have a close performance to human ROI, based on the eye fixation data.

Australian copyright regimes and political economy of music

In this chapter I review the history of copyright in Australia through a singular and exemplary ruling of the Australian High Court made in 2012 and then relate that to the declining fortunes of Australian recorded music professionals. The case in point is Phonographic Performance Company [PPCA] of Australia Limited v Commonwealth of Australia [2012] HCA 8 (hereafter, HCA 8 2012). The case encapsulates the history of copyright law in Australia, with the judicial decision drawing substantive parts of its rationale from the Statute of Anne (8 Anne, c. 19, 1710), as well as copyright acts that regulated the Australian markets prior to 1968. More importantly the High Court decision serves to delineate some important political economic aspects of the recorded music professional in Australia and demonstrates Attali’s (1985) assertion that copyright is the mechanism through which composers are, by statute, literally excluded from capitalistic engagement as ‘productive labour’.

Non-linear position control for hover and automatic landing of unmanned aerial vehicles

This study presents a disturbance attenuation controller for horizontal position stabilisation for hover and automatic landings of a rotary-wing unmanned aerial vehicle (RUAV) operating close to the landing deck in rough seas. Based on a helicopter model representing aerodynamics during the landing phase, a non-linear state feedback H∞ controller is designed to achieve rapid horizontal position tracking in a gusty environment. Practical constraints including flapping dynamics, servo dynamics and time lag effect are considered. A high-fidelity closed-loop simulation using parameters of the Vario XLC gas-turbine helicopter verifies performance of the proposed horizontal position controller. The proposed controller not only increases the disturbance attenuation capability of the RUAV, but also enables rapid position response when gusts occur. Comparative studies show that the H∞ controller exhibits performance improvement and can be applied to ship/RUAV landing systems.

Sound Musicianship : Understanding the Crafts of Music

Sound Musicianship is a book for music educators and musicians about musicianship—about musical skills, abilities, habits, sensibilities and understandings. Musicianship is explored as a form of craftsmanship. Like most crafts, music requires a balance of theoretical knowledge and practical skills that contribute to a highly tuned ability to appreciate and express music. In particular, the book explores general trends that influence musicianship in the twenty-first century, such as an increased reliance on digital media, greater awareness of the neurological basis for musical behaviour, a renewed interest in connections between bodily movements and musical expression, and increased cultural plurality resulting from more frequent travel, increased levels of migration and ubiquitous telecommunications. The book has a deliberate focus on the developmental aspects of musicianship, which will benefit those hoping to advance their own music learning or that of others. It includes a diverse range of views and perspectives on musicianship and is organised into five sections. The first four sections explore the implications of music understood as sound, experience, motion and culture, respectively. In these sections, leading researchers and thinkers outline important issues and debates that are relevant to developing the crafts of music making and they share insights into recent trends and understandings. The final section of the book looks at educational considerations and provides a series of case studies that document innovative approaches to developing musicianship. Readers will encounter some new, interesting and thought-provoking ideas within these pages. As we move further into the twenty-first century—with all the opportunities and challenges for music making it brings—the requirement to review our concepts of musicianship training will intensify, and the definition of a “sound basis” for a contemporary musicianship will evolve. This book is intended to help stimulate and inform that evolutionary process.

Monotonous trend estimation of deck displacement for automatic landing of rotorcraft UAVs

This paper presents a novel and practical procedure for estimating the mean deck height to assist in automatic landing operations of a Rotorcraft Unmanned Aerial Vehicle (RUAV) in harsh sea environments. A modified Prony Analysis (PA) procedure is outlined to deal with real-time observations of deck displacement, which involves developing an appropriate dynamic model to approach real deck motion with parameters identified through implementing the Forgetting Factor Recursive Least Square (FFRLS) method. The model order is specified using a proper order-selection criterion based on minimizing the summation of accumulated estimation errors. In addition, a feasible threshold criterion is proposed to separate the dominant components of deck displacement, which results in an accurate instantaneous estimation of the mean deck position. Simulation results demonstrate that the proposed recursive procedure exhibits satisfactory estimation performance when applied to real-time deck displacement measurements, making it well suited for integration into ship-RUAV approach and landing guidance systems.

Automatic segmentation of choroidal thickness in optical coherence tomography

The assessment of choroidal thickness from optical coherence tomography (OCT) images of the human choroid is an important clinical and research task, since it provides valuable information regarding the eye’s normal anatomy and physiology, and changes associated with various eye diseases and the development of refractive error. Due to the time consuming and subjective nature of manual image analysis, there is a need for the development of reliable objective automated methods of image segmentation to derive choroidal thickness measures. However, the detection of the two boundaries which delineate the choroid is a complicated and challenging task, in particular the detection of the outer choroidal boundary, due to a number of issues including: (i) the vascular ocular tissue is non-uniform and rich in non-homogeneous features, and (ii) the boundary can have a low contrast. In this paper, an automatic segmentation technique based on graph-search theory is presented to segment the inner choroidal boundary (ICB) and the outer choroidal boundary (OCB) to obtain the choroid thickness profile from OCT images. Before the segmentation, the B-scan is pre-processed to enhance the two boundaries of interest and to minimize the artifacts produced by surrounding features. The algorithm to detect the ICB is based on a simple edge filter and a directional weighted map penalty, while the algorithm to detect the OCB is based on OCT image enhancement and a dual brightness probability gradient. The method was tested on a large data set of images from a pediatric (1083 B-scans) and an adult (90 B-scans) population, which were previously manually segmented by an experienced observer. The results demonstrate the proposed method provides robust detection of the boundaries of interest and is a useful tool to extract clinical data.

Mawson the astrobiologist rover : towards automatic recognition of stromatolites

This work aims at developing a planetary rover capable of acting as an assistant astrobiologist: making a preliminary analysis of the collected visual images that will help to make better use of the scientists time by pointing out the most interesting pieces of data. This paper focuses on the problem of detecting and recognising particular types of stromatolites. Inspired by the processes actual astrobiologists go through in the field when identifying stromatolites, the processes we investigate focus on recognising characteristics associated with biogenicity. The extraction of these characteristics is based on the analysis of geometrical structure enhanced by passing the images of stromatolites into an edge-detection filter and its Fourier Transform, revealing typical spatial frequency patterns. The proposed analysis is performed on both simulated images of stromatolite structures and images of real stromatolites taken in the field by astrobiologists.

A typology of music distribution models

A typology of music distribution models is proposed consisting of the ownership model, the access model, and the context model. These models are not substitutes for each other and may co‐exist serving different market niches. The paper argues that increasingly the economic value created from recorded music is based on con‐text rather than on ownership. During this process, access‐based services temporarily generate economic value, but such services are destined to eventually become commoditised.

The enemy of music : modeling the behavior of a cultural industry in crisis

The purpose of this explorative study is to contribute to the understanding of current music industry dynamics. The situation is undeniably quite dramatic: Since the turn of the millennium, the global music industry has declined by $ US 6.2 billion in value—a fall of 16.3% in constant dollar terms. IFPI, the trade organization representing the international recording industry, identifies a number of exogenous factors as the main drivers of the downturn. This article suggests that other factors, in addition to those identified by IFPI, may have contributed to the current difficulties. A model is presented which indicates that business strategies which were designed to cope with the challenging business environment have reduced product diversity, damaged profitability, and contributed to the problem they were intended to solve.

Automatic classification of free-text radiology reports to identify limb fractures using machine learning and the SNOMED CT ontology

Objective To develop and evaluate machine learning techniques that identify limb fractures and other abnormalities (e.g. dislocations) from radiology reports. Materials and Methods 99 free-text reports of limb radiology examinations were acquired from an Australian public hospital. Two clinicians were employed to identify fractures and abnormalities from the reports; a third senior clinician resolved disagreements. These assessors found that, of the 99 reports, 48 referred to fractures or abnormalities of limb structures. Automated methods were then used to extract features from these reports that could be useful for their automatic classification. The Naive Bayes classification algorithm and two implementations of the support vector machine algorithm were formally evaluated using cross-fold validation over the 99 reports. Result Results show that the Naive Bayes classifier accurately identifies fractures and other abnormalities from the radiology reports. These results were achieved when extracting stemmed token bigram and negation features, as well as using these features in combination with SNOMED CT concepts related to abnormalities and disorders. The latter feature has not been used in previous works that attempted classifying free-text radiology reports. Discussion Automated classification methods have proven effective at identifying fractures and other abnormalities from radiology reports (F-Measure up to 92.31%). Key to the success of these techniques are features such as stemmed token bigrams, negations, and SNOMED CT concepts associated with morphologic abnormalities and disorders. Conclusion This investigation shows early promising results and future work will further validate and strengthen the proposed approaches.

Deleuze and music : a creative approach to the study of music

The work of Gilles Deleuze has influenced an increasing number of music scholars and practicing musicians, particularly those interested in experimental, electronic and popular music. This is despite the notoriously complex nature of his writings, and the specialised theoretical vocabulary that he employs. This thesis both demystifies some of the key terms and concepts of this vocabulary, before demonstrating how Deleuze’s ideas may be put to work in new and fruitful ways; this is achieved with specific reference to the relationships that music has with thought, time and machines. In Chapter 1, Deleuze’s understanding of the power of thought is examined, in particular his approach to communication, transcendence and immanence, and the “powers of thought.” Each of these concepts helps us to understand Deleuze’s work within broad problem of how to think about music immanently: that is, how to maintain that thought and music are both immanent aspects of life and experience. Chapter 2 examines time within a Deleuzian framework, linking his work on cinema with the concept of the “refrain”; both of these areas prove crucial to his understanding of music, as seen in Deleuze’s approach to the work of Varese, Messiaen, and Boulez. In addition, Deleuze’s understanding of time proves fruitful in examining various aspects of music production, as seen in contemporary electronic dance music. Finally, Chapter 3 looks at the concept of the machine, as developed by Deleuze and Guattari, with reference to the sorts of “machinic” connections that a Deleuzian approach encourages us to seek out in music. Once again, examples from contemporary electronic music are presented, in relation to the notions of becoming and subjectivity. Throughout these chapters, Deleuze’s broad understanding of philosophy as the “creation of concepts” is deployed. This means introducing new ideas and specific types of music that encourage creative and novel engagements with the study of music.

Automatic classification of human epithelial type 2 cell indirect immunofluorescence images using cell pyramid matching

This paper describes a novel system for automatic classification of images obtained from Anti-Nuclear Antibody (ANA) pathology tests on Human Epithelial type 2 (HEp-2) cells using the Indirect Immunofluorescence (IIF) protocol. The IIF protocol on HEp-2 cells has been the hallmark method to identify the presence of ANAs, due to its high sensitivity and the large range of antigens that can be detected. However, it suffers from numerous shortcomings, such as being subjective as well as time and labour intensive. Computer Aided Diagnostic (CAD) systems have been developed to address these problems, which automatically classify a HEp-2 cell image into one of its known patterns (eg. speckled, homogeneous). Most of the existing CAD systems use handpicked features to represent a HEp-2 cell image, which may only work in limited scenarios. We propose a novel automatic cell image classification method termed Cell Pyramid Matching (CPM), which is comprised of regional histograms of visual words coupled with the Multiple Kernel Learning framework. We present a study of several variations of generating histograms and show the efficacy of the system on two publicly available datasets: the ICPR HEp-2 cell classification contest dataset and the SNPHEp-2 dataset.