The use of visual analogue scales to assess motivation to eat in human subjects: a review of their reliability and validity with an evaluation of new hand-held computerized stsytems for temporal tracking of appetite ratings.

This present paper reviews the reliability and validity of visual analogue scales (VAS) in terms of (1) their ability to predict feeding behaviour, (2) their sensitivity to experimental manipulations, and (3) their reproducibility. VAS correlate with, but do not reliably predict, energy intake to the extent that they could be used as a proxy of energy intake. They do predict meal initiation in subjects eating their normal diets in their normal environment. Under laboratory conditions, subjectively rated motivation to eat using VAS is sensitive to experimental manipulations and has been found to be reproducible in relation to those experimental regimens. Other work has found them not to be reproducible in relation to repeated protocols. On balance, it would appear, in as much as it is possible to quantify, that VAS exhibit a good degree of within-subject reliability and validity in that they predict with reasonable certainty, meal initiation and amount eaten, and are sensitive to experimental manipulations. This reliability and validity appears more pronounced under the controlled (but more arti®cial) conditions of the laboratory where the signal : noise ratio in experiments appears to be elevated relative to real life. It appears that VAS are best used in within-subject, repeated-measures designs where the effect of different treatments can be compared under similar circumstances. They are best used in conjunction with other measures (e.g. feeding behaviour, changes in plasma metabolites) rather than as proxies for these variables. New hand-held electronic appetite rating systems (EARS) have been developed to increase reliability of data capture and decrease investigator workload. Recent studies have compared these with traditional pen and paper (P&P) VAS. The EARS have been found to be sensitive to experimental manipulations and reproducible relative to P&P. However, subjects appear to exhibit a signi®cantly more constrained use of the scale when using the EARS relative to the P&P. For this reason it is recommended that the two techniques are not used interchangeably

The ethics of regional water planning : planning and management of water resources in a growth region

Abstract Providing water infrastructure in times of accelerating climate change presents interesting new problems. Expanding demands must be met or managed in contexts of increasingly constrained sources of supply, raising ethical questions of equity and participation. Loss of agricultural land and natural habitats, the coastal impacts of desalination plants and concerns over re-use of waste water must be weighed with demand management issues of water rationing, pricing mechanisms and inducing behaviour change. This case study examines how these factors impact on infrastructure planning in South East Queensland, Australia: a region with one of the developed world’s most rapidly growing populations, which has recently experienced the most severe drought in its recorded history. Proposals to match forecast demands and potential supplies for water over a 20 year period are reviewed by applying ethical principles to evaluate practical plans to meet the water needs of the region’s activities and settlements.

Speech recognition using ad-hoc microphone arrays

While close talking microphones give the best signal quality and produce the highest accuracy from current Automatic Speech Recognition (ASR) systems, the speech signal enhanced by microphone array has been shown to be an effective alternative in a noisy environment. The use of microphone arrays in contrast to close talking microphones alleviates the feeling of discomfort and distraction to the user. For this reason, microphone arrays are popular and have been used in a wide range of applications such as teleconferencing, hearing aids, speaker tracking, and as the front-end to speech recognition systems. With advances in sensor and sensor network technology, there is considerable potential for applications that employ ad-hoc networks of microphone-equipped devices collaboratively as a virtual microphone array. By allowing such devices to be distributed throughout the users’ environment, the microphone positions are no longer constrained to traditional fixed geometrical arrangements. This flexibility in the means of data acquisition allows different audio scenes to be captured to give a complete picture of the working environment. In such ad-hoc deployment of microphone sensors, however, the lack of information about the location of devices and active speakers poses technical challenges for array signal processing algorithms which must be addressed to allow deployment in real-world applications. While not an ad-hoc sensor network, conditions approaching this have in effect been imposed in recent National Institute of Standards and Technology (NIST) ASR evaluations on distant microphone recordings of meetings. The NIST evaluation data comes from multiple sites, each with different and often loosely specified distant microphone configurations. This research investigates how microphone array methods can be applied for ad-hoc microphone arrays. A particular focus is on devising methods that are robust to unknown microphone placements in order to improve the overall speech quality and recognition performance provided by the beamforming algorithms. In ad-hoc situations, microphone positions and likely source locations are not known and beamforming must be achieved blindly. There are two general approaches that can be employed to blindly estimate the steering vector for beamforming. The first is direct estimation without regard to the microphone and source locations. An alternative approach is instead to first determine the unknown microphone positions through array calibration methods and then to use the traditional geometrical formulation for the steering vector. Following these two major approaches investigated in this thesis, a novel clustered approach which includes clustering the microphones and selecting the clusters based on their proximity to the speaker is proposed. Novel experiments are conducted to demonstrate that the proposed method to automatically select clusters of microphones (ie, a subarray), closely located both to each other and to the desired speech source, may in fact provide a more robust speech enhancement and recognition than the full array could.

A hidden Markov model and relative entropy rate approach to vision-based dim target detection for UAV sense-and-avoid

Uninhabited aerial vehicles (UAVs) are a cutting-edge technology that is at the forefront of aviation/aerospace research and development worldwide. Many consider their current military and defence applications as just a token of their enormous potential. Unlocking and fully exploiting this potential will see UAVs in a multitude of civilian applications and routinely operating alongside piloted aircraft. The key to realising the full potential of UAVs lies in addressing a host of regulatory, public relation, and technological challenges never encountered be- fore. Aircraft collision avoidance is considered to be one of the most important issues to be addressed, given its safety critical nature. The collision avoidance problem can be roughly organised into three areas: 1) Sense; 2) Detect; and 3) Avoid. Sensing is concerned with obtaining accurate and reliable information about other aircraft in the air; detection involves identifying potential collision threats based on available information; avoidance deals with the formulation and execution of appropriate manoeuvres to maintain safe separation. This thesis tackles the detection aspect of collision avoidance, via the development of a target detection algorithm that is capable of real-time operation onboard a UAV platform. One of the key challenges of the detection problem is the need to provide early warning. This translates to detecting potential threats whilst they are still far away, when their presence is likely to be obscured and hidden by noise. Another important consideration is the choice of sensors to capture target information, which has implications for the design and practical implementation of the detection algorithm. The main contributions of the thesis are: 1) the proposal of a dim target detection algorithm combining image morphology and hidden Markov model (HMM) filtering approaches; 2) the novel use of relative entropy rate (RER) concepts for HMM filter design; 3) the characterisation of algorithm detection performance based on simulated data as well as real in-flight target image data; and 4) the demonstration of the proposed algorithm's capacity for real-time target detection. We also consider the extension of HMM filtering techniques and the application of RER concepts for target heading angle estimation. In this thesis we propose a computer-vision based detection solution, due to the commercial-off-the-shelf (COTS) availability of camera hardware and the hardware's relatively low cost, power, and size requirements. The proposed target detection algorithm adopts a two-stage processing paradigm that begins with an image enhancement pre-processing stage followed by a track-before-detect (TBD) temporal processing stage that has been shown to be effective in dim target detection. We compare the performance of two candidate morphological filters for the image pre-processing stage, and propose a multiple hidden Markov model (MHMM) filter for the TBD temporal processing stage. The role of the morphological pre-processing stage is to exploit the spatial features of potential collision threats, while the MHMM filter serves to exploit the temporal characteristics or dynamics. The problem of optimising our proposed MHMM filter has been examined in detail. Our investigation has produced a novel design process for the MHMM filter that exploits information theory and entropy related concepts. The filter design process is posed as a mini-max optimisation problem based on a joint RER cost criterion. We provide proof that this joint RER cost criterion provides a bound on the conditional mean estimate (CME) performance of our MHMM filter, and this in turn establishes a strong theoretical basis connecting our filter design process to filter performance. Through this connection we can intelligently compare and optimise candidate filter models at the design stage, rather than having to resort to time consuming Monte Carlo simulations to gauge the relative performance of candidate designs. Moreover, the underlying entropy concepts are not constrained to any particular model type. This suggests that the RER concepts established here may be generalised to provide a useful design criterion for multiple model filtering approaches outside the class of HMM filters. In this thesis we also evaluate the performance of our proposed target detection algorithm under realistic operation conditions, and give consideration to the practical deployment of the detection algorithm onboard a UAV platform. Two fixed-wing UAVs were engaged to recreate various collision-course scenarios to capture highly realistic vision (from an onboard camera perspective) of the moments leading up to a collision. Based on this collected data, our proposed detection approach was able to detect targets out to distances ranging from about 400m to 900m. These distances, (with some assumptions about closing speeds and aircraft trajectories) translate to an advanced warning ahead of impact that approaches the 12.5 second response time recommended for human pilots. Furthermore, readily available graphic processing unit (GPU) based hardware is exploited for its parallel computing capabilities to demonstrate the practical feasibility of the proposed target detection algorithm. A prototype hardware-in- the-loop system has been found to be capable of achieving data processing rates sufficient for real-time operation. There is also scope for further improvement in performance through code optimisations. Overall, our proposed image-based target detection algorithm offers UAVs a cost-effective real-time target detection capability that is a step forward in ad- dressing the collision avoidance issue that is currently one of the most significant obstacles preventing widespread civilian applications of uninhabited aircraft. We also highlight that the algorithm development process has led to the discovery of a powerful multiple HMM filtering approach and a novel RER-based multiple filter design process. The utility of our multiple HMM filtering approach and RER concepts, however, extend beyond the target detection problem. This is demonstrated by our application of HMM filters and RER concepts to a heading angle estimation problem.

An initial technology roadmap for home automation : home and personal life management

Home Automation (HA) has emerged as a prominent ¯eld for researchers and in- vestors confronting the challenge of penetrating the average home user market with products and services emerging from technology based vision. In spite of many technology contri- butions, there is a latent demand for a®ordable and pragmatic assistive technologies for pro-active handling of complex lifestyle related problems faced by home users. This study has pioneered to develop an Initial Technology Roadmap for HA (ITRHA) that formulates a need based vision of 10-15 years, identifying market, product and technology investment opportunities, focusing on those aspects of HA contributing to e±cient management of home and personal life. The concept of Family Life Cycle is developed to understand the temporal needs of family. In order to formally describe a coherent set of family processes, their relationships, and interaction with external elements, a reference model named Fam- ily System is established that identi¯es External Entities, 7 major Family Processes, and 7 subsystems-Finance, Meals, Health, Education, Career, Housing, and Socialisation. Anal- ysis of these subsystems reveals Soft, Hard and Hybrid processes. Rectifying the lack of formal methods for eliciting future user requirements and reassessing evolving market needs, this study has developed a novel method called Requirement Elicitation of Future Users by Systems Scenario (REFUSS), integrating process modelling, and scenario technique within the framework of roadmapping. The REFUSS is used to systematically derive process au- tomation needs relating the process knowledge to future user characteristics identi¯ed from scenarios created to visualise di®erent futures with richly detailed information on lifestyle trends thus enabling learning about the future requirements. Revealing an addressable market size estimate of billions of dollars per annum this research has developed innovative ideas on software based products including Document Management Systems facilitating automated collection, easy retrieval of all documents, In- formation Management System automating information services and Ubiquitous Intelligent System empowering the highly mobile home users with ambient intelligence. Other product ideas include robotic devices of versatile Kitchen Hand and Cleaner Arm that can be time saving. Materialisation of these products require technology investment initiating further research in areas of data extraction, and information integration as well as manipulation and perception, sensor actuator system, tactile sensing, odour detection, and robotic controller. This study recommends new policies on electronic data delivery from service providers as well as new standards on XML based document structure and format.

Don’t judge a superannuation default investment option by its name

With the massive decline in savings arising from the Global Financial Crisis (GFC), it is timely to review superannuation fund investment and disclosure strategies in the lead-up to the crisis. Accordingly, this study examines differences among superannuation funds’ default investment options in terms of naming and framing over three years from 2005 to 2007, as presented in product disclosure statements (PDSs). The findings indicate that default options are becoming more alike regardless of their name, and consequently, members may face increasing difficulties in distinguishing between balanced and growth-named default options when comparing them across superannuation funds. Comparability is also likely to be constrained by variations in the framing of default options presented in investment option menus in PDSs. These findings highlight the need for standardisation of default option definitions and disclosures to ensure descriptive accuracy, transparency and comparability.

Automatic speaker recognition under adverse conditions

Speaker verification is the process of verifying the identity of a person by analysing their speech. There are several important applications for automatic speaker verification (ASV) technology including suspect identification, tracking terrorists and detecting a person’s presence at a remote location in the surveillance domain, as well as person authentication for phone banking and credit card transactions in the private sector. Telephones and telephony networks provide a natural medium for these applications. The aim of this work is to improve the usefulness of ASV technology for practical applications in the presence of adverse conditions. In a telephony environment, background noise, handset mismatch, channel distortions, room acoustics and restrictions on the available testing and training data are common sources of errors for ASV systems. Two research themes were pursued to overcome these adverse conditions: Modelling mismatch and modelling uncertainty. To directly address the performance degradation incurred through mismatched conditions it was proposed to directly model this mismatch. Feature mapping was evaluated for combating handset mismatch and was extended through the use of a blind clustering algorithm to remove the need for accurate handset labels for the training data. Mismatch modelling was then generalised by explicitly modelling the session conditions as a constrained offset of the speaker model means. This session variability modelling approach enabled the modelling of arbitrary sources of mismatch, including handset type, and halved the error rates in many cases. Methods to model the uncertainty in speaker model estimates and verification scores were developed to address the difficulties of limited training and testing data. The Bayes factor was introduced to account for the uncertainty of the speaker model estimates in testing by applying Bayesian theory to the verification criterion, with improved performance in matched conditions. Modelling the uncertainty in the verification score itself met with significant success. Estimating a confidence interval for the "true" verification score enabled an order of magnitude reduction in the average quantity of speech required to make a confident verification decision based on a threshold. The confidence measures developed in this work may also have significant applications for forensic speaker verification tasks.

Multi-robot control in highly dynamic, competitive environments

The control and coordination of multiple mobile robots is a challenging task; particularly in environments with multiple, rapidly moving obstacles and agents. This paper describes a robust approach to multi-robot control, where robustness is gained from competency at every layer of robot control. The layers are: (i) a central coordination system (MAPS), (ii) an action system (AES), (iii) a navigation module, and (iv) a low level dynamic motion control system. The multi-robot coordination system assigns each robot a role and a sub-goal. Each robots action execution system then assumes the assigned role and attempts to achieve the specified sub-goal. The robots navigation system directs the robot to specific goal locations while ensuring that the robot avoids any obstacles. The motion system maps the heading and speed information from the navigation system to force-constrained motion. This multi-robot system has been extensively tested and applied in the robot soccer domain using both centralized and distributed coordination.

Distributed control of gait for a humanoid robot

This paper describes a walking gait for a humanoid robot with a distributed control system. The motion for the robot is calculated in real time on a central controller, and sent over CAN bus to the distributed control system. The distributed control system loosely follows the motion patterns from the central controller, while also acting to maintain stability and balance. There is no global feedback control system; the system maintains its balance by the interaction between central gait and soft control of the actuators. The paper illustrates a straight line walking gait and shows the interaction between gait generation and the control system. The analysis of the data shows that successful walking can be achieved without maintaining strict local joint control, and without explicit global balance coordination.

Operation and control of a DVR in the presence of interharmonics

The paper discusses the operating principles and control characteristics of a dynamic voltage restorer (DVR). It is assumed that the source voltages contain interharmonic components in addition to fundamental components. The main aim of the DVR is to produce a set of clean balanced sinusoidal voltages across the load terminals irrespective of unbalance, distortion and voltage sag/swell in the supply voltage. An algorithm has been discussed for extracting fundamental phasor sequence components from the samples of three-phase voltages or current waveforms having integer harmonics and interharmonics. The DVR operation based on extracted components is demonstrated. The switching signal is generated using a deadbeat controller. It has been shown that the DVR is able to compensate these interharmonic components such that the load voltages are perfectly regulated. The DVR operation under deep voltage sag is also discussed. The proposed DVR operation is verified through the computer simulation studies using the MATLAB software package.

Load compensation for systems with non-stiff source using state feedback

Various load compensation schemes proposed in literature assume that voltage source at point of common coupling (PCC) is stiff. In practice, however, the load is remote from a distribution substation and is supplied by a feeder. In the presence of feeder impedance, the PWM inverter switchings distort both the PCC voltage and the source currents. In this paper load compensation with such a non-stiff source is considered. A switching control of the voltage source inverter (VSI) based on state feedback is used for load compensation with non-stiff source. The design of the state feedback controller requires careful considerations in choosing a gain matrix and in the generation of reference quantities. These aspects are considered in this paper. Detailed simulation and experimental results are given to support the control design.

Torsional Interaction Studies on a Power System Compensated by SSSC and Fixed Capacitor

In this paper, a static synchronous series compensator (SSSC), along with a fixed capacitor, is used to avoid torsional mode instability in a series compensated transmission system. A 48-step harmonic neutralized inverter is used for the realization of the SSSC. The system under consideration is the IEEE first benchmark model on SSR analysis. The system stability is studied both through eigenvalue analysis and EMTDC/PSCAD simulation studies. It is shown that the combination of the SSSC and the fixed capacitor improves the synchronizing power coefficient. The presence of the fixed capacitor ensures increased damping of small signal oscillations. At higher levels of fixed capacitor compensation, a damping controller is required to stabilize the torsional modes of SSR.

TCSC control design for transient stability improvement of a multi-machine power system using trajectory sensitivity

This paper discusses the effects of thyristor controlled series compensator (TCSC), a series FACTS controller, on the transient stability of a power system. Trajectory sensitivity analysis (TSA) has been used to measure the transient stability condition of the system. The TCSC is modeled by a variable capacitor, the value of which changes with the firing angle. It is shown that TSA can be used in the design of the controller. The optimal locations of the TCSC-controller for different fault conditions can also be identified with the help of TSA. The paper depicts the advantage of the use of TCSC with a suitable controller over fixed capacitor operation.