The design and development of music eScape: A new iPhone mood management music App

The physical, emotional, educational and social developmental challenges of adolescence can be associated with high levels of emotional vulnerability. Thus, the development of effective emotion-regulation strategies is crucial during this time period. Young people commonly use music to identify, express and regulate their emotions. Modern mobile technology provides an engaging, easily accessible means of assisting young people through music. A systematic contextual review identified 20 iPhone applications addressing emotions through music and two independent raters, using the Mobile App Rating Scale (MARS), evaluated the quality of the apps. Their characteristics, key features and overall quality will be presented. Three participatory design workshops (N=13, 6 males, 7 females; age 15-25) were conducted to explore young people’s use of music to enhance wellbeing. Young people were also asked to trial existing mood and music apps and to conceptualise their ultimate mood targeting music application. A thematic analysis of the participatory design workshops content identified the following music affect-regulation strategies: relationship building, modifying cognitions, modifying emotions, and immersing in emotions. The application of the key learnings from the mobile app review and participatory design workshops and the design and development of the music eScape app were presented and implications for future research was discussed.

Automatic inference of driving task demand from visual cues of emotion and attention

Sensing the mental, physical and emotional demand of a driving task is of primary importance in road safety research and for effectively designing in-vehicle information systems (IVIS). Particularly, the need of cars capable of sensing and reacting to the emotional state of the driver has been repeatedly advocated in the literature. Algorithms and sensors to identify patterns of human behavior, such as gestures, speech, eye gaze and facial expression, are becoming available by using low cost hardware: This paper presents a new system which uses surrogate measures such as facial expression (emotion) and head pose and movements (intention) to infer task difficulty in a driving situation. 11 drivers were recruited and observed in a simulated driving task that involved several pre-programmed events aimed at eliciting emotive reactions, such as being stuck behind slower vehicles, intersections and roundabouts, and potentially dangerous situations. The resulting system, combining face expressions and head pose classification, is capable of recognizing dangerous events (such as crashes and near misses) and stressful situations (e.g. intersections and way giving) that occur during the simulated drive.

A convolutional neural network for automatic analysis of aerial imagery

This paper introduces a new method to automate the detection of marine species in aerial imagery using a Machine Learning approach. Our proposed system has at its core, a convolutional neural network. We compare this trainable classifier to a handcrafted classifier based on color features, entropy and shape analysis. Experiments demonstrate that the convolutional neural network outperforms the handcrafted solution. We also introduce a negative training example-selection method for situations where the original training set consists of a collection of labeled images in which the objects of interest (positive examples) have been marked by a bounding box. We show that picking random rectangles from the background is not necessarily the best way to generate useful negative examples with respect to learning.

Young people's uses of music for well-being

The period between 15 and 25 years is characterised by much personal change and is the peak age of onset of mental health problems. This prompts an interest in everyday strategies that young people might use to support their well-being. Music use is the preferred leisure activity among young people yet little is known about how music is linked to well-being in this population. This study aimed to develop and test a model of the relationships between young people’s use of music and their well-being, drawing on theories from the music psychology and clinical psychology fields. A qualitative analysis of transcripts from focus groups with 11 participants aged 15–25 years revealed four ways in which music listening links with well-being: relationship building, modifying emotions, modifying cognitions and emotional immersion. These linking variables were operationalised using questionnaire scores and tested on a new sample of 107 young people. Results of a multiple mediation analysis revealed that music listening was significantly related to all four linking variables, but not directly related to well-being as measured by the Mental Health Continuum. Nevertheless, the four linking variables indirectly mediated the effect of music listening on social wellbeing. The findings are consistent with earlier research on the role of music in emotion regulation and social connection although there are clearly other factors involved in determining young peoples’ well-being. These findings will help inform music-based interventions for young people.

Automatic clustering of white matter fibers in brain diffusion mri with an application to genetics

To understand factors that affect brain connectivity and integrity, it is beneficial to automatically cluster white matter (WM) fibers into anatomically recognizable tracts. Whole brain tractography, based on diffusion-weighted MRI, generates vast sets of fibers throughout the brain; clustering them into consistent and recognizable bundles can be difficult as there are wide individual variations in the trajectory and shape of WM pathways. Here we introduce a novel automated tract clustering algorithm based on label fusion - a concept from traditional intensity-based segmentation. Streamline tractography generates many incorrect fibers, so our top-down approach extracts tracts consistent with known anatomy, by mapping multiple hand-labeled atlases into a new dataset. We fuse clustering results from different atlases, using a mean distance fusion scheme. We reliably extracted the major tracts from 105-gradient high angular resolution diffusion images (HARDI) of 198 young normal twins. To compute population statistics, we use a pointwise correspondence method to match, compare, and average WM tracts across subjects. We illustrate our method in a genetic study of white matter tract heritability in twins.

Will algorithmic playlist curation be the end of music stardom?

It is 2015 and there are no indications that the relentless digital transformation of the music economy is about to slow down. Rather, the music economy continues to rapidly reinvent itself and industry powers, positions and practices that were redefined only a few years ago are being questioned once again. This paper examines the most recent changes of the music economy as it moves from a product-based towards an access-based logic. The paper starts out by recognising the essential role of technology in the evolution of the music economy. It then moves on to a discussion about the rise of so-called access-based music business models and points out some of the controversies and debates that are associated with these models and online services. With this as a background the paper explores how access-based music services and the algorithmically curated playlists developed by these services transform the relationship between artists, music and fans and challenges the music industrial power relationships and established industry practices once again.

Impact of automatic region-of-interest coding on perceived quality in mobile video

At present, the most reliable method to obtain end-user perceived quality is through subjective tests. In this paper, the impact of automatic region-of-interest (ROI) coding on perceived quality of mobile video is investigated. The evidence, which is based on perceptual comparison analysis, shows that the coding strategy improves perceptual quality. This is particularly true in low bit rate situations. The ROI detection method used in this paper is based on two approaches: - (1) automatic ROI by analyzing the visual contents automatically, and; - (2) eye-tracking based ROI by aggregating eye-tracking data across many users, used to both evaluate the accuracy of automatic ROI detection and the subjective quality of automatic ROI encoded video. The perceptual comparison analysis is based on subjective assessments with 54 participants, across different content types, screen resolutions, and target bit rates while comparing the two ROI detection methods. The results from the user study demonstrate that ROI-based video encoding has higher perceived quality compared to normal video encoded at a similar bit rate, particularly in the lower bit rate range.

International Journal of Music Business Research. Special Issue on the Australasian Music Economy

The music business is one of the most international of all the cultural industries. Music, industry practices, and people travel easily across country borders and the major music companies are dominating national music markets across the globe. However, at the same time the music industries in different countries are very idiosyncratic. Music is an ingrained part of a country’s history, its culture and heritage. One aspect of this idiosyncrasy is related to how creatives, audiences and music organizations are affected by and is able to take advantage of the ongoing digitization of society.

Automatic detection of diabetic foot complications with infrared thermography by asymmetric analysis

Early identification of diabetic foot complications and their precursors is essential in preventing their devastating consequences, such as foot infection and amputation. Frequent, automatic risk assessment by an intelligent telemedicine system might be feasible and cost effective. Infrared thermography is a promising modality for such a system. The temperature differences between corresponding areas on contralateral feet are the clinically significant parameters. This asymmetric analysis is hindered by (1) foot segmentation errors, especially when the foot temperature and the ambient temperature are comparable, and by (2) different shapes and sizes between contralateral feet due to deformities or minor amputations. To circumvent the first problem, we used a color image and a thermal image acquired synchronously. Foot regions, detected in the color image, were rigidly registered to the thermal image. This resulted in 97.8% ± 1.1% sensitivity and 98.4% ± 0.5% specificity over 76 high-risk diabetic patients with manual annotation as a reference. Nonrigid landmark-based registration with Bsplines solved the second problem. Corresponding points in the two feet could be found regardless of the shapes and sizes of the feet. With that, the temperature difference of the left and right feet could be obtained.

A survey of tagging techniques for music, speech and environmental sound

Sound tagging has been studied for years. Among all sound types, music, speech, and environmental sound are three hottest research areas. This survey aims to provide an overview about the state-of-the-art development in these areas.We discuss about the meaning of tagging in different sound areas at the beginning of the journey. Some examples of sound tagging applications are introduced in order to illustrate the significance of this research. Typical tagging techniques include manual, automatic, and semi-automatic approaches.After reviewing work in music, speech and environmental sound tagging, we compare them and state the research progress to date. Research gaps are identified for each research area and the common features and discriminations between three areas are discovered as well. Published datasets, tools used by researchers, and evaluation measures frequently applied in the analysis are listed. In the end, we summarise the worldwide distribution of countries dedicated to sound tagging research for years.

Music is a Wordless Knowing of Others : Resilience in Virtual Ensembles

Music making affects relationships with self and others by generating a sense of belonging to a culture or ideology (Bamford, 2006; Barovick, 2001; Dillon & Stewart, 2006; Fiske, 2000; Hallam, 2001). Whilst studies from arts education research present compelling examples of these relationships, others argue that they do not present sufficiently validated evidence of a causal link between music making experiences and cognitive or social change (Winner & Cooper, 2000; Winner & Hetland, 2000a, 2000b, 2001). I have suggested elsewhere that this disconnection between compelling evidence and observations of the effects of music making are in part due to the lack of rigor in research and the incapacity of many methods to capture these experiences in meaningful ways (Dillon, 2006). Part of the answer to these questions about rigor and causality lay in the creative use of new media technologies that capture the results of relationships in music artefacts. Crucially, it is the effective management of these artefacts within computer systems that allows researchers and practitioners to collect, organize, analyse and then theorise such music making experiences.

The effectiveness of a short-term group music therapy intervention for parents who have a child with a disability

Background The relationship between positive parent-child interactions and optimal child development is well established. Families with a child with a disability may face additional challenges to establishing positive parent-child relationships. There are limited studies addressing the effectiveness of interventions which seek to address these issues with parents and young children with a disability. In particular, prior studies of music therapy with this group have been limited by small sample sizes and the use of measures of limited reliability and validity. Objective This study investigates the effectiveness of a short-term group music therapy intervention for parents who have a child with a disability and explores the factors associated with higher outcomes for participating families. Methods The participants were 201 mother-child dyads, where the child had a disability. Pre and post intervention parental questionnaires and clinician observation measures were taken on a range of parental wellbeing, parenting behaviours and child developmental factors. Descriptive data, t-tests for repeated measures and a predictive model tested via logistic regression are presented. Results Significant improvements pre to post were found for parent mental health, child communication and social skills, parenting sensitivity, parental engagement with child and acceptance of child, child responsiveness to parent, and child interest and participation in program activities. There was also evidence that parents were very satisfied with the program and that it brought social benefits to families. Reliable change on six or more indicators of parent or child functioning was predicted by attendance and parent education. Conclusions This study provides positive evidence for the effectiveness of group music therapy in promoting improved parental mental health, positive parenting and key child developmental areas. Whilst several limitations are discussed, the study does address some of the gaps in the music therapy evidence base in this area.