A method of lines approach for modelling saltwater intrusion in coastal aquifiers

The equations governing saltwater intrusion in coastal aquifers are complex. Backward Euler time stepping approaches are often used to advance the solution to these equations in time, which typically requires that small time steps be taken in order to ensure that an accurate solution is obtained. We show that a method of lines approach incorporating variable order backward differentiation formulas can greatly improve the efficiency of the time stepping process.

A fuzzy neural network approach for contractor pre-qualification

Nonlinearity, uncertainty and subjectivity are the three predominant characteristics of contractors prequalification which cause the process more of an art than a scientific evaluation. A fuzzy neural network (FNN) model, amalgamating both the fuzzy set and neural network theories, has been developed aiming to improve the objectiveness of contractor prequalification. Through the FNN theory, the fuzzy rules as used by the prequalifiers can be identified and the corresponding membership functions can be transformed. Eighty-five cases with detailed decision criteria and rules for prequalifying Hong Kong civil engineering contractors were collected. These cases were used for training (calibrating) and testing the FNN model. The performance of the FNN model was compared with the original results produced by the prequalifiers and those generated by the general feedforward neural network (GFNN, i.e. a crisp neural network) approach. Contractor’s ranking orders, the model efficiency (R2) and the mean absolute percentage error (MAPE) were examined during the testing phase. These results indicate the applicability of the neural network approach for contractor prequalification and the benefits of the FNN model over the GFNN model. The FNN is a practical approach for modelling contractor prequalification.

XCFS - a novel approach for clustering XML documents using both the structure and the content

XML document clustering is essential for many document handling applications such as information storage, retrieval, integration and transformation. An XML clustering algorithm should process both the structural and the content information of XML documents in order to improve the accuracy and meaning of the clustering solution. However, the inclusion of both kinds of information in the clustering process results in a huge overhead for the underlying clustering algorithm because of the high dimensionality of the data. This paper introduces a novel approach that first determines the structural similarity in the form of frequent subtrees and then uses these frequent subtrees to represent the constrained content of the XML documents in order to determine the content similarity. The proposed method reduces the high dimensionality of input data by using only the structure-constrained content. The empirical analysis reveals that the proposed method can effectively cluster even very large XML datasets and outperform other existing methods.

A sequencing approach for creating new train timetables

Train scheduling is a complex and time consuming task of vital importance. To schedule trains more accurately and efficiently than permitted by current techniques a novel hybrid job shop approach has been proposed and implemented. Unique characteristics of train scheduling are first incorporated into a disjunctive graph model of train operations. A constructive algorithm that utilises this model is then developed. The constructive algorithm is a general procedure that constructs a schedule using insertion, backtracking and dynamic route selection mechanisms. It provides a significant search capability and is valid for any objective criteria. Simulated Annealing and Local Search meta-heuristic improvement algorithms are also adapted and extended. An important feature of these approaches is a new compound perturbation operator that consists of many unitary moves that allows trains to be shifted feasibly and more easily within the solution. A numerical investigation and case study is provided and demonstrates that high quality solutions are obtainable on real sized applications.

Robot path planning in dynamic environments using a simulated annealing based approach

Mobile robots are widely used in many industrial fields. Research on path planning for mobile robots is one of the most important aspects in mobile robots research. Path planning for a mobile robot is to find a collision-free route, through the robot’s environment with obstacles, from a specified start location to a desired goal destination while satisfying certain optimization criteria. Most of the existing path planning methods, such as the visibility graph, the cell decomposition, and the potential field are designed with the focus on static environments, in which there are only stationary obstacles. However, in practical systems such as Marine Science Research, Robots in Mining Industry, and RoboCup games, robots usually face dynamic environments, in which both moving and stationary obstacles exist. Because of the complexity of the dynamic environments, research on path planning in the environments with dynamic obstacles is limited. Limited numbers of papers have been published in this area in comparison with hundreds of reports on path planning in stationary environments in the open literature. Recently, a genetic algorithm based approach has been introduced to plan the optimal path for a mobile robot in a dynamic environment with moving obstacles. However, with the increase of the number of the obstacles in the environment, and the changes of the moving speed and direction of the robot and obstacles, the size of the problem to be solved increases sharply. Consequently, the performance of the genetic algorithm based approach deteriorates significantly. This motivates the research of this work. This research develops and implements a simulated annealing algorithm based approach to find the optimal path for a mobile robot in a dynamic environment with moving obstacles. The simulated annealing algorithm is an optimization algorithm similar to the genetic algorithm in principle. However, our investigation and simulations have indicated that the simulated annealing algorithm based approach is simpler and easier to implement. Its performance is also shown to be superior to that of the genetic algorithm based approach in both online and offline processing times as well as in obtaining the optimal solution for path planning of the robot in the dynamic environment. The first step of many path planning methods is to search an initial feasible path for the robot. A commonly used method for searching the initial path is to randomly pick up some vertices of the obstacles in the search space. This is time consuming in both static and dynamic path planning, and has an important impact on the efficiency of the dynamic path planning. This research proposes a heuristic method to search the feasible initial path efficiently. Then, the heuristic method is incorporated into the proposed simulated annealing algorithm based approach for dynamic robot path planning. Simulation experiments have shown that with the incorporation of the heuristic method, the developed simulated annealing algorithm based approach requires much shorter processing time to get the optimal solutions in the dynamic path planning problem. Furthermore, the quality of the solution, as characterized by the length of the planned path, is also improved with the incorporated heuristic method in the simulated annealing based approach for both online and offline path planning.

Theoretical investigation of thermal tweezers for parallel manipulation of atoms and nanoparticles on surfaces

A major focus of research in nanotechnology is the development of novel, high throughput techniques for fabrication of arbitrarily shaped surface nanostructures of sub 100 nm to atomic scale. A related pursuit is the development of simple and efficient means for parallel manipulation and redistribution of adsorbed atoms, molecules and nanoparticles on surfaces – adparticle manipulation. These techniques will be used for the manufacture of nanoscale surface supported functional devices in nanotechnologies such as quantum computing, molecular electronics and lab-on-achip, as well as for modifying surfaces to obtain novel optical, electronic, chemical, or mechanical properties. A favourable approach to formation of surface nanostructures is self-assembly. In self-assembly, nanostructures are grown by aggregation of individual adparticles that diffuse by thermally activated processes on the surface. The passive nature of this process means it is generally not suited to formation of arbitrarily shaped structures. The self-assembly of nanostructures at arbitrary positions has been demonstrated, though these have typically required a pre-patterning treatment of the surface using sophisticated techniques such as electron beam lithography. On the other hand, a parallel adparticle manipulation technique would be suited for directing the selfassembly process to occur at arbitrary positions, without the need for pre-patterning the surface. There is at present a lack of techniques for parallel manipulation and redistribution of adparticles to arbitrary positions on the surface. This is an issue that needs to be addressed since these techniques can play an important role in nanotechnology. In this thesis, we propose such a technique – thermal tweezers. In thermal tweezers, adparticles are redistributed by localised heating of the surface. This locally enhances surface diffusion of adparticles so that they rapidly diffuse away from the heated regions. Using this technique, the redistribution of adparticles to form a desired pattern is achieved by heating the surface at specific regions. In this project, we have focussed on the holographic implementation of this approach, where the surface is heated by holographic patterns of interfering pulsed laser beams. This implementation is suitable for the formation of arbitrarily shaped structures; the only condition is that the shape can be produced by holographic means. In the simplest case, the laser pulses are linearly polarised and intersect to form an interference pattern that is a modulation of intensity along a single direction. Strong optical absorption at the intensity maxima of the interference pattern results in approximately a sinusoidal variation of the surface temperature along one direction. The main aim of this research project is to investigate the feasibility of the holographic implementation of thermal tweezers as an adparticle manipulation technique. Firstly, we investigate theoretically the surface diffusion of adparticles in the presence of sinusoidal modulation of the surface temperature. Very strong redistribution of adparticles is predicted when there is strong interaction between the adparticle and the surface, and the amplitude of the temperature modulation is ~100 K. We have proposed a thin metallic film deposited on a glass substrate heated by interfering laser beams (optical wavelengths) as a means of generating very large amplitude of surface temperature modulation. Indeed, we predict theoretically by numerical solution of the thermal conduction equation that amplitude of the temperature modulation on the metallic film can be much greater than 100 K when heated by nanosecond pulses with an energy ~1 mJ. The formation of surface nanostructures of less than 100 nm in width is predicted at optical wavelengths in this implementation of thermal tweezers. Furthermore, we propose a simple extension to this technique where spatial phase shift of the temperature modulation effectively doubles or triples the resolution. At the same time, increased resolution is predicted by reducing the wavelength of the laser pulses. In addition, we present two distinctly different, computationally efficient numerical approaches for theoretical investigation of surface diffusion of interacting adparticles – the Monte Carlo Interaction Method (MCIM) and the random potential well method (RPWM). Using each of these approaches we have investigated thermal tweezers for redistribution of both strongly and weakly interacting adparticles. We have predicted that strong interactions between adparticles can increase the effectiveness of thermal tweezers, by demonstrating practically complete adparticle redistribution into the low temperature regions of the surface. This is promising from the point of view of thermal tweezers applied to directed self-assembly of nanostructures. Finally, we present a new and more efficient numerical approach to theoretical investigation of thermal tweezers of non-interacting adparticles. In this approach, the local diffusion coefficient is determined from solution of the Fokker-Planck equation. The diffusion equation is then solved numerically using the finite volume method (FVM) to directly obtain the probability density of adparticle position. We compare predictions of this approach to those of the Ermak algorithm solution of the Langevin equation, and relatively good agreement is shown at intermediate and high friction. In the low friction regime, we predict and investigate the phenomenon of ‘optimal’ friction and describe its occurrence due to very long jumps of adparticles as they diffuse from the hot regions of the surface. Future research directions, both theoretical and experimental are also discussed.

Alternate structural system of incorporating flat bed rail wagons as low volume road bridge decks

The stimulus for this project rose from the need to find an alternative solution to aging superstructures of road-bridge in low volume roads (LVR). The solution investigated, designed and consequently plans to construct, involved replacing an aging super-structure of a 10m span bridge with Flat-Bed Rail Wagon (FBRW). The main focus of this paper is to present alternate structural system for the design of the FBRW as road bridge deck conforming to AS5100. The structural adequacy of the primary members of the FBRW was first validated using full scale experimental investigation to AS5100 serviceability and ultimate limit state loading. The bare FBRW was further developed to include a running surface. Two options were evaluated during the design phase, namely timber and reinforced concrete. First option, which is presented here, involved strengthening of the FBRW using numerous steel sections and overlaying the bridge deck with timber planks. The idea of this approach was to use all the primary and secondary members of the FBRW in load sharing and to provide additional members where weaknesses in the original members arose. The second option, which was the preferred option for construction, involved use of primary members only with an overlaying reinforced concrete slab deck. This option minimised the risk associated with any uncertainty of secondary members to its structural adequacy. The paper will report selected results of the experiment as well as the design phases of option one with conclusions highlighting the viability of option 1 and its limitations.

A risk-based approach to course quality assurance

A decade ago, Queensland University of Technology (QUT) developed an innovative annual Courses Performance Report, but through incremental change, this report became quite labour-intensive. A new risk-based approach to course quality assurance, that consolidates voluminous data in a simple dashboard, responds to the changing context of the higher education sector. This paper will briefly describe QUT’s context and outline the second phase of implementation of this new approach to course quality assurance. The main components are: Individual Course Reports (ICRs), the Consolidated Courses Performance Report (CCPR), Underperforming Courses Status Update and the Strategic Faculty Courses Update (SFCU). These components together form a parsimonious and strategic annual cycle of reporting and place QUT in a positive position to respond to future sector change

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.

Examining psychosocial influences on speeding in Australian and Chinese contexts : a social learning approach

Speeding remains a significant contributing factor to road trauma internationally, despite increasingly sophisticated speed management strategies being adopted around the world. Increases in travel speed are associated with increases in crash risk and crash severity. As speed choice is a voluntary behaviour, driver perceptions are important to our understanding of speeding and, importantly, to designing effective behavioural countermeasures. The four studies conducted in this program of research represent a comprehensive approach to examining psychosocial influences on driving speeds in two countries that are at very different levels of road safety development: Australia and China. Akers’ social learning theory (SLT) was selected as the theoretical framework underpinning this research and guided the development of key research hypotheses. This theory was chosen because of its ability to encompass psychological, sociological, and criminological perspectives in understanding behaviour, each of which has relevance to speeding. A mixed-method design was used to explore the personal, social, and legal influences on speeding among car drivers in Queensland (Australia) and Beijing (China). Study 1 was a qualitative exploration, via focus group interviews, of speeding among 67 car drivers recruited from south east Queensland. Participants were assigned to groups based on their age and gender, and additionally, according to whether they self-identified as speeding excessively or rarely. This study aimed to elicit information about how drivers conceptualise speeding as well as the social and legal influences on driving speeds. The findings revealed a wide variety of reasons and circumstances that appear to be used as personal justifications for exceeding speed limits. Driver perceptions of speeding as personally and socially acceptable, as well as safe and necessary were common. Perceptions of an absence of danger associated with faster driving speeds were evident, particularly with respect to driving alone. An important distinction between the speed-based groups related to the attention given to the driving task. Rare speeders expressed strong beliefs about the need to be mindful of safety (self and others) while excessive speeders referred to the driving task as automatic, an absent-minded endeavour, and to speeding as a necessity in order to remain alert and reduce boredom. For many drivers in this study, compliance with speed limits was expressed as discretionary rather than mandatory. Social factors, such as peer and parental influence were widely discussed in Study 1 and perceptions of widespread community acceptance of speeding were noted. In some instances, the perception that ‘everybody speeds’ appeared to act as one rationale for the need to raise speed limits. Self-presentation, or wanting to project a positive image of self was noted, particularly with respect to concealing speeding infringements from others to protect one’s image as a trustworthy and safe driver. The influence of legal factors was also evident. Legal sanctions do not appear to influence all drivers to the same extent. For instance, fear of apprehension appeared to play a role in reducing speeding for many, although previous experiences of detection and legal sanctions seemed to have had limited influence on reducing speeding among some drivers. Disregard for sanctions (e.g., driving while suspended), fraudulent demerit point use, and other strategies to avoid detection and punishment were widely and openly discussed. In Study 2, 833 drivers were recruited from roadside service stations in metropolitan and regional locations in Queensland. A quantitative research strategy assessed the relative contribution of personal, social, and legal factors to recent and future self-reported speeding (i.e., frequency of speeding and intentions to speed in the future). Multivariate analyses examining a range of factors drawn from SLT revealed that factors including self-identity (i.e., identifying as someone who speeds), favourable definitions (attitudes) towards speeding, personal experiences of avoiding detection and punishment for speeding, and perceptions of family and friends as accepting of speeding were all significantly associated with greater self-reported speeding. Study 3 was an exploratory, qualitative investigation of psychosocial factors associated with speeding among 35 Chinese drivers who were recruited from the membership of a motoring organisation and a university in Beijing. Six focus groups were conducted to explore similar issues to those examined in Study 1. The findings of Study 3 revealed many similarities with respect to the themes that arose in Australia. For example, there were similarities regarding personal justifications for speeding, such as the perception that posted limits are unreasonably low, the belief that individual drivers are able to determine safe travel speeds according to personal comfort with driving fast, and the belief that drivers possess adequate skills to control a vehicle at high speed. Strategies to avoid detection and punishment were also noted, though they appeared more widespread in China and also appeared, in some cases, to involve the use of a third party, a topic that was not reported by Australian drivers. Additionally, higher perceived enforcement tolerance thresholds were discussed by Chinese participants. Overall, the findings indicated perceptions of a high degree of community acceptance of speeding and a perceived lack of risk associated with speeds that were well above posted speed limits. Study 4 extended the exploratory research phase in China with a quantitative investigation involving 299 car drivers recruited from car washes in Beijing. Results revealed a relatively inexperienced sample with less than 5 years driving experience, on average. One third of participants perceived that the certainty of penalties when apprehended was low and a similar proportion of Chinese participants reported having previously avoided legal penalties when apprehended for speeding. Approximately half of the sample reported that legal penalties for speeding were ‘minimally to not at all’ severe. Multivariate analyses revealed that past experiences of avoiding detection and punishment for speeding, as well as favourable attitudes towards speeding, and perceptions of strong community acceptance of speeding were most strongly associated with greater self-reported speeding in the Chinese sample. Overall, the results of this research make several important theoretical contributions to the road safety literature. Akers’ social learning theory was found to be robust across cultural contexts with respect to speeding; similar amounts of variance were explained in self-reported speeding in the quantitative studies conducted in Australia and China. Historically, SLT was devised as a theory of deviance and posits that deviance and conformity are learned in the same way, with the balance of influence stemming from the ways in which behaviour is rewarded and punished (Akers, 1998). This perspective suggests that those who speed and those who do not are influenced by the same mechanisms. The inclusion of drivers from both ends of the ‘speeding spectrum’ in Study 1 provided an opportunity to examine the wider utility of SLT across the full range of the behaviour. One may question the use of a theory of deviance to investigate speeding, a behaviour that could, arguably, be described as socially acceptable and prevalent. However, SLT seemed particularly relevant to investigating speeding because of its inclusion of association, imitation, and reinforcement variables which reflect the breadth of factors already found to be potentially influential on driving speeds. In addition, driving is a learned behaviour requiring observation, guidance, and practice. Thus, the reinforcement and imitation concepts are particularly relevant to this behaviour. Finally, current speed management practices are largely enforcement-based and rely on the principles of behavioural reinforcement captured within the reinforcement component of SLT. Thus, the application of SLT to a behaviour such as speeding offers promise in advancing our understanding of the factors that influence speeding, as well as extending our knowledge of the application of SLT. Moreover, SLT could act as a valuable theoretical framework with which to examine other illegal driving behaviours that may not necessarily be seen as deviant by the community (e.g., mobile phone use while driving). This research also made unique contributions to advancing our understanding of the key components and the overall structure of Akers’ social learning theory. The broader SLT literature is lacking in terms of a thorough structural understanding of the component parts of the theory. For instance, debate exists regarding the relevance of, and necessity for including broader social influences in the model as captured by differential association. In the current research, two alternative SLT models were specified and tested in order to better understand the nature and extent of the influence of differential association on behaviour. Importantly, the results indicated that differential association was able to make a unique contribution to explaining self-reported speeding, thereby negating the call to exclude it from the model. The results also demonstrated that imitation was a discrete theoretical concept that should also be retained in the model. The results suggest a need to further explore and specify mechanisms of social influence in the SLT model. In addition, a novel approach was used to operationalise SLT variables by including concepts drawn from contemporary social psychological and deterrence-based research to enhance and extend the way that SLT variables have traditionally been examined. Differential reinforcement was conceptualised according to behavioural reinforcement principles (i.e., positive and negative reinforcement and punishment) and incorporated concepts of affective beliefs, anticipated regret, and deterrence-related concepts. Although implicit in descriptions of SLT, little research has, to date, made use of the broad range of reinforcement principles to understand the factors that encourage or inhibit behaviour. This approach has particular significance to road user behaviours in general because of the deterrence-based nature of many road safety countermeasures. The concept of self-identity was also included in the model and was found to be consistent with the definitions component of SLT. A final theoretical contribution was the specification and testing of a full measurement model prior to model testing using structural equation modelling. This process is recommended in order to reduce measurement error by providing an examination of the psychometric properties of the data prior to full model testing. Despite calls for such work for a number of decades, the current work appears to be the only example of a full measurement model of SLT. There were also a number of important practical implications that emerged from this program of research. Firstly, perceptions regarding speed enforcement tolerance thresholds were highlighted as a salient influence on driving speeds in both countries. The issue of enforcement tolerance levels generated considerable discussion among drivers in both countries, with Australian drivers reporting lower perceived tolerance levels than Chinese drivers. It was clear that many drivers used the concept of an enforcement tolerance in determining their driving speed, primarily with the desire to drive faster than the posted speed limit, yet remaining within a speed range that would preclude apprehension by police. The quantitative results from Studies 2 and 4 added support to these qualitative findings. Together, the findings supported previous research and suggested that a travel speed may not be seen as illegal until that speed reaches a level over the prescribed enforcement tolerance threshold. In other words, the enforcement tolerance appears to act as a ‘de facto’ speed limit, replacing the posted limit in the minds of some drivers. The findings from the two studies conducted in China (Studies 2 and 4) further highlighted the link between perceived enforcement tolerances and a ‘de facto’ speed limit. Drivers openly discussed driving at speeds that were well above posted speed limits and some participants noted their preference for driving at speeds close to ‘50% above’ the posted limit. This preference appeared to be shaped by the perception that the same penalty would be imposed if apprehended, irrespective of what speed they travelling (at least up to 50% above the limit). Further research is required to determine whether the perceptions of Chinese drivers are mainly influenced by the Law of the People’s Republic of China or by operational practices. Together, the findings from both studies in China indicate that there may be scope to refine enforcement tolerance levels, as has happened in other jurisdictions internationally over time, in order to reduce speeding. Any attempts to do so would likely be assisted by the provision of information about the legitimacy and purpose of speed limits as well as risk factors associated with speeding because these issues were raised by Chinese participants in the qualitative research phase. Another important practical implication of this research for speed management in China is the way in which penalties are determined. Chinese drivers described perceptions of unfairness and a lack of transparency in the enforcement system because they were unsure of the penalty that they would receive if apprehended. Steps to enhance the perceived certainty and consistency of the system to promote a more equitable approach to detection and punishment would appear to be welcomed by the general driving public and would be more consistent with the intended theoretical (deterrence) basis that underpins the current speed enforcement approach. The use of mandatory, fixed penalties may assist in this regard. In many countries, speeding attracts penalties that are dependent on the severity of the offence. In China, there may be safety benefits gained from the introduction of a similar graduated scale of speeding penalties and fixed penalties might also help to address the issue of uncertainty about penalties and related perceptions of unfairness. Such advancements would be in keeping with the principles of best practice for speed management as identified by the World Health Organisation. Another practical implication relating to legal penalties, and applicable to both cultural contexts, relates to the issues of detection and punishment avoidance. These two concepts appeared to strongly influence speeding in the current samples. In Australia, detection avoidance strategies reported by participants generally involved activities that are not illegal (e.g., site learning and remaining watchful for police vehicles). The results from China were similar, although a greater range of strategies were reported. The most common strategy reported in both countries for avoiding detection when speeding was site learning, or familiarisation with speed camera locations. However, a range of illegal practices were also described by Chinese drivers (e.g., tampering with or removing vehicle registration plates so as to render the vehicle unidentifiable on camera and use of in-vehicle radar detectors). With regard to avoiding punishment when apprehended, a range of strategies were reported by drivers from both countries, although a greater range of strategies were reported by Chinese drivers. As the results of the current research indicated that detection avoidance was strongly associated with greater self-reported speeding in both samples, efforts to reduce avoidance opportunities are strongly recommended. The practice of randomly scheduling speed camera locations, as is current practice in Queensland, offers one way to minimise site learning. The findings of this research indicated that this practice should continue. However, they also indicated that additional strategies are needed to reduce opportunities to evade detection. The use of point-to-point speed detection (also known as sectio

Development and validation of a novel approach to work sampling : a study of nurse practitioner work patterns

Objectives: This methodological paper reports on the development and validation of a work sampling instrument and data collection processes to conduct a national study of nurse practitioners’ work patterns. ---------- Design: Published work sampling instruments provided the basis for development and validation of a tool for use in a national study of nurse practitioner work activities across diverse contextual and clinical service models. Steps taken in the approach included design of a nurse practitioner-specific data collection tool and development of an innovative web-based program to train and establish inter rater reliability of a team of data collectors who were geographically dispersed across metropolitan, rural and remote health care settings. ---------- Setting: The study is part of a large funded study into nurse practitioner service. The Australian Nurse Practitioner Study is a national study phased over three years and was designed to provide essential information for Australian health service planners, regulators and consumer groups on the profile, process and outcome of nurse practitioner service. ---------- Results: The outcome if this phase of the study is empirically tested instruments, process and training materials for use in an international context by investigators interested in conducting a national study of nurse practitioner work practices. ---------- Conclusion: Development and preparation of a new approach to describing nurse practitioner practices using work sampling methods provides the groundwork for international collaboration in evaluation of nurse practitioner service.

The use of phase in complex spectrum subtraction for robust speech recognition

In this paper we propose a new method for utilising phase information by complementing it with traditional magnitude-only spectral subtraction speech enhancement through Complex Spectrum Subtraction (CSS). The proposed approach has the following advantages over traditional magnitude-only spectral subtraction: (a) it introduces complementary information to the enhancement algorithm; (b) it reduces the total number of algorithmic parameters, and; (c) is designed for improving clean speech magnitude spectra and is therefore suitable for both automatic speech recognition (ASR) and speech perception applications. Oracle-based ASR experiments verify this approach, showing an average of 20% relative word accuracy improvements when accurate estimates of the phase spectrum are available. Based on sinusoidal analysis and assuming stationarity between observations (which is shown to be better approximated as the frame rate is increased), this paper also proposes a novel method for acquiring the phase information called Phase Estimation via Delay Projection (PEDEP). Further oracle ASR experiments validate the potential for the proposed PEDEP technique in ideal conditions. Realistic implementation of CSS with PEDEP shows performance comparable to state of the art spectral subtraction techniques in a range of 15-20 dB signal-to-noise ratio environments. These results clearly demonstrate the potential for using phase spectra in spectral subtractive enhancement applications, and at the same time highlight the need for deriving more accurate phase estimates in a wider range of noise conditions.

A study of heuristic approach on station track allocation in mainline railways

Station track allocation is the critical component in the overall railway timetabling. Because of its intrinsic complexity and lack of modeling on station track layouts and train movement within station, analytical approach to attain optimal solution is not feasible. This study investigates the possibilities of applying a heuristic approach and identifies possible difficulties in practice. It is the first and important step to resolve one of the burning issues in the mainline railway operation in China.

SSE based parallel solution for power systems network equations

Streaming SIMD Extensions (SSE) is a unique feature embedded in the Pentium III class of microprocessors. By fully exploiting SSE, parallel algorithms can be implemented on a standard personal computer and a theoretical speedup of four can be achieved. In this paper, we demonstrate the implementation of a parallel LU matrix decomposition algorithm for solving power systems network equations with SSE and discuss advantages and disadvantages of this approach.

A parallel solution to linear systems

Streaming SIMD Extensions (SSE) is a unique feature embedded in the Pentium III and IV classes of microprocessors. By fully exploiting SSE, parallel algorithms can be implemented on a standard personal computer and a theoretical speedup of four can be achieved. In this paper, we demonstrate the implementation of a parallel LU matrix decomposition algorithm for solving linear systems with SSE and discuss advantages and disadvantages of this approach based on our experimental study.