Amphibian

Amphibian is an 10’00’’ musical work which explores new musical interfaces and approaches to hybridising performance practices from the popular music, electronic dance music and computer music traditions. The work is designed to be presented in a range of contexts associated with the electro-acoustic, popular and classical music traditions. The work is for two performers using two synchronised laptops, an electric guitar and a custom designed gestural interface for vocal performers - the e-Mic (Extended Mic-stand Interface Controller). This interface was developed by one of the co-authors, Donna Hewitt. The e-Mic allows a vocal performer to manipulate the voice in real time through the capture of physical gestures via an array of sensors - pressure, distance, tilt - along with ribbon controllers and an X-Y joystick microphone mount. Performance data are then sent to a computer, running audio-processing software, which is used to transform the audio signal from the microphone. In this work, data is also exchanged between performers via a local wireless network, allowing performers to work with shared data streams. The duo employs the gestural conventions of guitarist and singer (i.e. 'a band' in a popular music context), but transform these sounds and gestures into new digital music. The gestural language of popular music is deliberately subverted and taken into a new context. The piece thus explores the nexus between the sonic and performative practices of electro acoustic music and intelligent electronic dance music (‘idm’). This work was situated in the research fields of new musical interfacing, interaction design, experimental music composition and performance. The contexts in which the research was conducted were live musical performance and studio music production. The work investigated new methods for musical interfacing, performance data mapping, hybrid performance and compositional practices in electronic music. The research methodology was practice-led. New insights were gained from the iterative experimental workshopping of gestural inputs, musical data mapping, inter-performer data exchange, software patch design, data and audio processing chains. In respect of interfacing, there were innovations in the design and implementation of a novel sensor-based gestural interface for singers, the e-Mic, one of the only existing gestural controllers for singers. This work explored the compositional potential of sharing real time performance data between performers and deployed novel methods for inter-performer data exchange and mapping. As regards stylistic and performance innovation, the work explored and demonstrated an approach to the hybridisation of the gestural and sonic language of popular music with recent ‘post-digital’ approaches to laptop based experimental music The development of the work was supported by an Australia Council Grant. Research findings have been disseminated via a range of international conference publications, recordings, radio interviews (ABC Classic FM), broadcasts, and performances at international events and festivals. The work was curated into the major Australian international festival, Liquid Architecture, and was selected by an international music jury (through blind peer review) for presentation at the International Computer Music Conference in Belfast, N. Ireland.

Nodule

Nodule is 19'54" musical work for two electronic music performers, two laptop computers and a custom built, sensor-based microphone controller - the e-Mic (Extended Mic-stand Interface Controller). This interface was developed by one of the co-authors, Donna Hewitt. The e-Mic allows a vocal performer to manipulate their voice in real time by capturing physical gestures via an array of sensors - pressure, distance, tilt – in addition to ribbon controllers and an X-Y joystick microphone mount. Performance data are then sent to a computer, running audio-processing software, which is used to transform the audio signal from the microphone in real time. The work seeks to explore the liminal space between the electro-acoustic music tradition and more recent developments in the electronic dance music tradition. It does so on both a performative (gestural) and compositional (sonic) level. Visually, the performance consists of a singer and a laptop performer, hybridising the gestural context of these traditions. On a sonic level, the work explores hybridity at deeper levels of the musical structure than simple bricolage or collage approaches. Hybridity is explored at the level of the sonic gesture (source material), in production (audio processing gestures), in performance gesture, and in approaches to the use of the frequency spectrum, pulse and meter. The work was designed to be performed in a range of contexts from concert halls, to clubs, to rock festivals, across a range of staging and production platforms. As a consequence, the work has been tested in a range of audience contexts, and has allowed the transportation of compositional and performance practices across traditional audience demographic boundaries.

A forward and backward secure key management in wireless sensor networks for PCS/SCADA

Process Control Systems (PCSs) or Supervisory Control and Data Acquisition (SCADA) systems have recently been added to the already wide collection of wireless sensor networks applications. The PCS/SCADA environment is somewhat more amenable to the use of heavy cryptographic mechanisms such as public key cryptography than other sensor application environments. The sensor nodes in the environment, however, are still open to devastating attacks such as node capture, which makes designing a secure key management challenging. In this paper, a key management scheme is proposed to defeat node capture attack by offering both forward and backward secrecies. Our scheme overcomes the pitfalls which Nilsson et al.'s scheme suffers from, and is not more expensive than their scheme.

Fusion of in-vehicle sensor data to develop Intelligent Driver Training System (IDTS)

The over represented number of novice drivers involved in crashes is alarming. Driver training is one of the interventions aimed at mitigating the number of crashes that involve young drivers. To our knowledge, Advanced Driver Assistance Systems (ADAS) have never been comprehensively used in designing an intelligent driver training system. Currently, there is a need to develop and evaluate ADAS that could assess driving competencies. The aim is to develop an unsupervised system called Intelligent Driver Training System (IDTS) that analyzes crash risks in a given driving situation. In order to design a comprehensive IDTS, data is collected from the Driver, Vehicle and Environment (DVE), synchronized and analyzed. The first implementation phase of this intelligent driver training system deals with synchronizing multiple variables acquired from DVE. RTMaps is used to collect and synchronize data like GPS, vehicle dynamics and driver head movement. After the data synchronization, maneuvers are segmented out as right turn, left turn and overtake. Each maneuver is composed of several individual tasks that are necessary to be performed in a sequential manner. This paper focuses on turn maneuvers. Some of the tasks required in the analysis of ‘turn’ maneuver are: detect the start and end of the turn, detect the indicator status change, check if the indicator was turned on within a safe distance and check the lane keeping during the turn maneuver. This paper proposes a fusion and analysis of heterogeneous data, mainly involved in driving, to determine the risk factor of particular maneuvers within the drive. It also explains the segmentation and risk analysis of the turn maneuver in a drive.

Towards continuous surveillance of fruit flies using sensor networks and machine vision

In Australia, the Queensland fruit fly (B. tryoni), is the most destructive insect pest of horticulture, attacking nearly all fruit and vegetable crops. This project has researched and prototyped a system for monitoring fruit flies so that authorities can be alerted when a fly enters a crop in a more efficient manner than is currently used. This paper presents the idea of our sensor platform design as well as the fruit fly detection and recognition algorithm by using machine vision techniques. Our experiments showed that the designed trap and sensor platform is capable to capture quality fly images, the invasive flies can be successfully detected and the average precision of the Queensland fruit fly recognition is 80% from our experiment.

External pressure in the hardening of phosphate in tribofilm on iron surfaces

Purpose: In the present work we consider our (in progress) spectroscopy study of zinc and iron phosphates under the influence external high pressure to determine zinc ion change coordination from tetrahedral to octahedral (or hexahedral) structure.----- Design/methodology/approach: The standard equipment is the optical high pressure cell with diamond (DAC). The DAC is assembled and then vibrational or electronic spectra are collected by mounting the cell in an infrared, Raman, EXAFS or UV-visible spectrometer.----- Findings: Mechanism by which zinc and iron methaphosphate material is transformed to glassy meta-phosphate is enhancing mechanical properties of tribofilm. The two decades of intensive study demonstrates that Zn (II) and Fe (III) ions participate to cross-link network under friction, hardening the phosphate.----- Research limitations/implications: Transition metal atoms with d orbital have flexible coordination numbers, for example zinc acts as a cross-linking agent increasing hardness, by changing coordination from tetrahedral to octahedral. Perhaps the external pressure effect on the [Zn–(O-P-)4 ] complex causes a transformation to an [Zn –(O-P-)6] grouping.----- Originality/value: This paper analyses high-pressure spectroscopy which has been applied for the investigation of 3D transition metal ions in solids. When studying pressure effects on coordination compounds structure, we can expect changes in ground electronic state (spin-crossovers), electronic spectra due to structural distortions (piezochromism), and changes in the ligand field causing shifts in the electronic transitions.

Integrated Diagnosis and Prognosis Model for High Pressure LNG Pump

In condition-based maintenance (CBM), effective diagnostics and prognostics are essential tools for maintenance engineers to identify imminent fault and to predict the remaining useful life before the components finally fail. This enables remedial actions to be taken in advance and reschedules production if necessary. This paper presents a technique for accurate assessment of the remnant life of machines based on historical failure knowledge embedded in the closed loop diagnostic and prognostic system. The technique uses the Support Vector Machine (SVM) classifier for both fault diagnosis and evaluation of health stages of machine degradation. To validate the feasibility of the proposed model, the five different level data of typical four faults from High Pressure Liquefied Natural Gas (HP-LNG) pumps were used for multi-class fault diagnosis. In addition, two sets of impeller-rub data were analysed and employed to predict the remnant life of pump based on estimation of health state. The results obtained were very encouraging and showed that the proposed prognosis system has the potential to be used as an estimation tool for machine remnant life prediction in real life industrial applications.