Creating a functional musician: a performance workshop model

This paper examines the innovative re-alignment of one Australian tertiary music program in response to economic imperatives and a rapidly evolving marketplace. A 'functional musician' is technically sound, versatile, adaptive, collaborative, empathetic, creative, and capable of adapting to most professional situations. Conservatoire training models designed to produce classical musicians specialising in performance or education do not necessarily meet industry needs in twenty-first century Australia. Following changes to the secondary school music curriculum, undergraduate students are arriving at University with different musical skills. Responding to these changes, the University of Southern Queensland has adapted its tertiary classical music degree programs to create a new 'workshop model' for Music Practice courses to produce employable music graduates with adaptable skills suitable for the diverse Australian musical sector. The new model had its initial implementation in semester 1 (February-June) 2012. Data was collected from two student surveys and from student reflective journals; it is intended that these form the beginning of a longitudinal survey. Analysis of the initial data indicates the workshop model is successful in many of its aims, but shows some areas needing refinement

Towards Automated Performance Bug Identification in Python

Context: Software performance is a critical non-functional requirement, appearing in many fields such as mission critical applications, financial, and real time systems. In this work we focused on early detection of performance bugs; our software under study was a real time system used in the advertisement/marketing domain. Goal: Find a simple and easy to implement solution, predicting performance bugs. Method: We built several models using four machine learning methods, commonly used for defect prediction: C4.5 Decision Trees, Na\"{\i}ve Bayes, Bayesian Networks, and Logistic Regression. Results: Our empirical results show that a C4.5 model, using lines of code changed, file's age and size as explanatory variables, can be used to predict performance bugs (recall=0.73, accuracy=0.85, and precision=0.96). We show that reducing the number of changes delivered on a commit, can decrease the chance of performance bug injection. Conclusions: We believe that our approach can help practitioners to eliminate performance bugs early in the development cycle. Our results are also of interest to theoreticians, establishing a link between functional bugs and (non-functional) performance bugs, and explicitly showing that attributes used for prediction of functional bugs can be used for prediction of performance bugs

What does the vibration therapy add?: a quasi-experimental, pilot study on the short term effects of whole-body vibration as mode of exercise for nursing home residents aged 80+

Aims: To compare the responses of nursing home residents aged 80+ to an 8 weeks exercise program performed on a vibratory device and to the same exercise program preformed without vibration on lower limb performance, functional dependence and quality of life. Methods:Lower limb performance was evaluated using the 30 seconds Chair Sit to Stand test. Functional mobility was assessed using the timed up and go test. Postural stability was measured using a force platform. The Barthel Index was used to assess functional dependence and the EuroQol was used to evaluate Health-Related Quality of Life. 44 participants were allocated to the whole-body vibration group (n= 15), non-vibration group (n= 15) or to the control group (n= 14). Results:Significant differences were detected in favour of the whole-body vibration group in lower limb muscle performance (p= 0.001), mobility (p= 0.001), functional independence (p= 0.009) and quality of life (p <0.001) as compared to the control and non-vibration groups. Conclusions: Whole body vibration based interventions may add additional benefits to conventional exercise programs in terms of lower limb muscle performance, functional dependence and quality of life among nursing home residents over 80 years

An experimental study on performance portability of OpenCL kernels

Accelerator processors allow energy-efficient computation at high performance, especially for computationintensive applications. There exists a plethora of different accelerator architectures, such as GPUs and the Cell Broadband Engine. Each accelerator has its own programming language, but the recently introduced OpenCL language unifies accelerator programming languages. Hereby, OpenCL achieves functional protability, allowing to reduce the development time of kernels. Functional portability however has limited value without performance portability: the possibility to re-use optimized kernels with good performance. This paper investigates the specificity of code optimizations to accelerator architecture and the severity of lack of performance portability

A framework for FPGA functional units in high performance computing

FPGAs make it practical to speed up a program by defining hardware functional units that perform calculations faster than can be achieved in software. Specialised digital circuits avoid the overhead of executing sequences of instructions, and they make available the massive parallelism of the components. The FPGA operates as a coprocessor controlled by a conventional computer. An application that combines software with hardware in this way needs an interface between a communications port to the processor and the signals connected to the functional units. We present a framework that supports the design of such systems. The framework consists of a generic controller circuit defined in VHDL that can be configured by the user according to the needs of the functional units and the I/O channel. The controller contains a register file and a pipelined programmable register transfer machine, and it supports the design of both stateless and stateful functional units. Two examples are described: the implementation of a set of basic stateless arithmetic functional units, and the implementation of a stateful algorithm that exploits circuit parallelism

Melt compounding with graphene to develop functional, high-performance elastomers

Rather than using graphene oxide, which is limited by a high defect concentration and cost due to oxidation and reduction, we adopted cost-effective, 3.56 nm thick graphene platelets (GnPs) of high structural integrity to melt compound with an elastomer—ethylene–propylene–diene monomer rubber (EPDM)—using an industrial facility. An elastomer is an amorphous, chemically crosslinked polymer generally having rather low modulus and fracture strength but high fracture strain in comparison with other materials; and upon removal of loading, it is able to return to its original geometry, immediately and completely. It was found that most GnPs dispersed uniformly in the elastomer matrix, although some did form clusters. A percolation threshold of electrical conductivity at 18 vol% GnPs was observed and the elastomer thermal conductivity increased by 417% at 45 vol% GnPs. The modulus and tensile strength increased by 710% and 404% at 26.7 vol% GnPs, respectively. The modulus improvement agrees well with the Guth and Halpin-Tsai models. The reinforcing effect of GnPs was compared with silicate layers and carbon nanotube. Our simple fabrication would prolong the service life of elastomeric products used in dynamic loading, thus reducing thermosetting waste in the environment