Impairment of simulated motorcycle riding performance under low dose alcohol

Crash statistics that include the blood alcohol concentration (BAC) of vehicle operators reveal that crash involved motorcyclists are over represented at low BACs (e.g., ≤0.05%). This riding simulator study compared riding performance and hazard response under three low dose alcohol conditions (sober, 0.02% BAC, 0.05% BAC). Forty participants (20 novice, 20 experienced) completed simulated rides in urban and rural scenarios while responding to a safety-critical peripheral detection task (PDT). Results showed a significant increase in the standard deviation of lateral position in the urban scenario and PDT reaction time in the rural scenario under 0.05% BAC compared with zero alcohol. Participants were most likely to collide with an unexpected pedestrian in the urban scenario at 0.02% BAC, with novice participants at a greater relative risk than experienced riders. Novices chose to ride faster than experienced participants in the rural scenario regardless of BAC. Not all results were significant, emphasising the complex situation of the effects of low dose BAC on riding performance, which needs further research. The results of this simulator study provide some support for a legal BAC for motorcyclists below 0.05%.

Brake system performance requirements of a lightweight electric/hybrid rear wheel drive vehicle

Investigates the braking performance requirements of the UltraCommuter, a lightweight series hybrid electric vehicle currently under development at the University of Queensland. With a predicted vehicle mass of 600 kg and two in-wheel motors each capable of 500 Nm of peak torque, decelerations up to 0.46 g are theoretically possible using purely regenerative braking. With 99% of braking demands less than 0.35 g, essentially all braking can be regenerative. The wheel motors have sufficient peak torque capability to lock the rear wheels in combination with front axle braking, eliminating the need for friction braking at the rear. Emergency braking levels approaching 1 g are achieved by supplementation with front disk brakes. This paper presents equations describing the peak front and rear axle braking forces which occur under straight line braking, including gradients. Conventionally, to guarantee stability, mechanical front/rear proportioning of braking effort ensures that the front axle locks first. In this application, all braking is initially regenerative at the rear, and an adaptive ''by-wire'' proportioning system presented ensures this stability requirement is still satisfied. Front wheel drive and all wheel drive systems are also discussed. Finally, peak and continuous performance measures, not commonly provided for friction brakes, are derived for the UltraCommuter's motor capability and range of operation.

On-road driving studies to understand why drivers behave as they do at regional rail level crossings

Improving safety at rail level crossings is an important part of both road and rail safety strategies. While low in number, crashes between vehicles and trains at level crossings are catastrophic events typically involving multiple fatalities and serious injuries. Advances in driving assessment methods, such as the provision of on-road instrumented test vehicles with eye and head tracking, provide researchers with the opportunity to further understand driver behaviour at such crossings in ways not previously possible. This paper describes a study conducted to further understand the factors that shape driver behaviour at rail level crossings using instrumented vehicles. Twenty-two participants drove an On-Road Test Vehicle (ORTeV) on a predefined route in regional Victoria with a mix of both active (flashing lights with/without boom barriers) and passively controlled (stop, give way) crossings. Data collected included driving performance data, head checks, and interview data to capture driver strategies. The data from an integrated suite of methods demonstrated clearly how behaviour differs at active and passive level crossings, particularly for inexperienced drivers. For example, the head check data clearly show the reliance and expectancies of inexperienced drivers for active warnings even when approaching passively controlled crossings. These studies provide very novel and unique insights into how level crossing design and warnings shape driver behaviour.

Metastability and emergent performance of dynamic interceptive actions

Objectives: Adaptive patterning of human movement is context specific and dependent on interacting constraints of the performer–environment relationship. Flexibility of skilled behaviour is predicated on the capacity of performers to move between different states of movement organisation to satisfy dynamic task constraints, previously demonstrated in studies of visual perception, bimanual coordination, and an interceptive combat task. Metastability is a movement system property that helps performers to remain in a state of relative coordination with their performance environments, poised between multiple co-existing states (stable and distinct movement patterns or responses). The aim of this study was to examine whether metastability could be exploited in externally paced interceptive actions in fast ball sports, such as cricket. Design: Here we report data on metastability in performance of multi-articular hitting actions by skilled junior cricket batters (n = 5). Methods: Participants’ batting actions (key movement timings and performance outcomes) were analysed in four distinct performance regions varied by ball pitching (bounce) location. Results: Results demonstrated that, at a pre-determined distance to the ball, participants were forced into a meta-stable region of performance where rich and varied patterns of functional movement behaviours emerged. Participants adapted the organisation of responses, resulting in higher levels of variability in movement timing in this performance region, without detrimental effects on the quality of interceptive performance outcomes. Conclusions: Findings provide evidence for the emergence of metastability in a dynamic interceptive action in cricket batting. Flexibility and diversity of movement responses were optimised using experiential knowledge and careful manipulation of key task constraints of the specific sport context.

Personalized ontology learning for enhancing text mining effectiveness

Over the last decade, the majority of existing search techniques is either keyword- based or category-based, resulting in unsatisfactory effectiveness. Meanwhile, studies have illustrated that more than 80% of users preferred personalized search results. As a result, many studies paid a great deal of efforts (referred to as col- laborative filtering) investigating on personalized notions for enhancing retrieval performance. One of the fundamental yet most challenging steps is to capture precise user information needs. Most Web users are inexperienced or lack the capability to express their needs properly, whereas the existent retrieval systems are highly sensitive to vocabulary. Researchers have increasingly proposed the utilization of ontology-based tech- niques to improve current mining approaches. The related techniques are not only able to refine search intentions among specific generic domains, but also to access new knowledge by tracking semantic relations. In recent years, some researchers have attempted to build ontological user profiles according to discovered user background knowledge. The knowledge is considered to be both global and lo- cal analyses, which aim to produce tailored ontologies by a group of concepts. However, a key problem here that has not been addressed is: how to accurately match diverse local information to universal global knowledge. This research conducts a theoretical study on the use of personalized ontolo- gies to enhance text mining performance. The objective is to understand user information needs by a \bag-of-concepts" rather than \words". The concepts are gathered from a general world knowledge base named the Library of Congress Subject Headings. To return desirable search results, a novel ontology-based mining approach is introduced to discover accurate search intentions and learn personalized ontologies as user profiles. The approach can not only pinpoint users' individual intentions in a rough hierarchical structure, but can also in- terpret their needs by a set of acknowledged concepts. Along with global and local analyses, another solid concept matching approach is carried out to address about the mismatch between local information and world knowledge. Relevance features produced by the Relevance Feature Discovery model, are determined as representatives of local information. These features have been proven as the best alternative for user queries to avoid ambiguity and consistently outperform the features extracted by other filtering models. The two attempt-to-proposed ap- proaches are both evaluated by a scientific evaluation with the standard Reuters Corpus Volume 1 testing set. A comprehensive comparison is made with a num- ber of the state-of-the art baseline models, including TF-IDF, Rocchio, Okapi BM25, the deploying Pattern Taxonomy Model, and an ontology-based model. The gathered results indicate that the top precision can be improved remarkably with the proposed ontology mining approach, where the matching approach is successful and achieves significant improvements in most information filtering measurements. This research contributes to the fields of ontological filtering, user profiling, and knowledge representation. The related outputs are critical when systems are expected to return proper mining results and provide personalized services. The scientific findings have the potential to facilitate the design of advanced preference mining models, where impact on people's daily lives.

Visualising experimental flow fields through a stormwater gross pollutant trap

Abstract An experimental dataset representing a typical flow field in a stormwater gross pollutant trap (GPT) was visualised. A technique was developed to apply the image-based flow visualisation (IBFV) algorithm to the raw dataset. Particle image velocimetry (PIV) software was previously used to capture the flow field data by tracking neutrally buoyant particles with a high speed camera. The dataset consisted of scattered 2D point velocity vectors and the IBFV visualisation facilitates flow feature characterisation within the GPT. The flow features played a pivotal role in understanding stormwater pollutant capture and retention behaviour within the GPT. It was found that the IBFV animations revealed otherwise unnoticed flow features and experimental artefacts. For example, a circular tracer marker in the IBFV program visually highlighted streamlines to investigate the possible flow paths of pollutants entering the GPT. The investigated flow paths were compared with the behaviour of pollutants monitored during experiments.

A fuzzy TOPSIS based multi criteria performance measurement model for lean supply chain

Increasing global competition, rapid technological changes, advances in manufacturing and information technology and discerning customers are forcing supply chains to adopt improvement practices that enable them to deliver high quality products at a lower cost and in a shorter period of time. A lean initiative is one of the most effective approaches toward achieving this goal. In the lean improvement process, it is critical to measure current and desired performance level in order to clearly evaluate the lean implementation efforts. Many attempts have tried to measure supply chain performance incorporating both quantitative and qualitative measures but failed to provide an effective method of measuring improvements in performances for dynamic lean supply chain situations. Therefore, the necessity of appropriate measurement of lean supply chain performance has become imperative. There are many lean tools available for supply chains; however, effectiveness of a lean tool depends on the type of the product and supply chain. One tool may be highly effective for a supply chain involved in high volume products but may not be effective for low volume products. There is currently no systematic methodology available for selecting appropriate lean strategies based on the type of supply chain and market strategy This thesis develops an effective method to measure the performance of supply chain consisting of both quantitative and qualitative metrics and investigates the effects of product types and lean tool selection on the supply chain performance Supply chain performance matrices and the effects of various lean tools over performance metrics mentioned in the SCOR framework have been investigated. A lean supply chain model based on the SCOR metric framework is then developed where non- lean and lean as well as quantitative and qualitative metrics are incorporated in appropriate metrics. The values of appropriate metrics are converted into triangular fuzzy numbers using similarity rules and heuristic methods. Data have been collected from an apparel manufacturing company for multiple supply chain products and then a fuzzy based method is applied to measure the performance improvements in supply chains. Using the fuzzy TOPSIS method, which chooses an optimum alternative to maximise similarities with positive ideal solutions and to minimise similarities with negative ideal solutions, the performances of lean and non- lean supply chain situations for three different apparel products have been evaluated. To address the research questions related to effective performance evaluation method and the effects of lean tools over different types of supply chains; a conceptual framework and two hypotheses are investigated. Empirical results show that implementation of lean tools have significant effects over performance improvements in terms of time, quality and flexibility. Fuzzy TOPSIS based method developed is able to integrate multiple supply chain matrices onto a single performance measure while lean supply chain model incorporates qualitative and quantitative metrics. It can therefore effectively measure the improvements for supply chain after implementing lean tools. It is demonstrated that product types involved in the supply chain and ability to select right lean tools have significant effect on lean supply chain performance. Future study can conduct multiple case studies in different contexts.

Drinking and riding: is subjective workload related to performance?

Introduction: Within the context of road safety it is important that workload (the portion of a driver’s resources expended to perform a task) remains at a manageable level, preventing overloading and consequently performance decrements. Motorcyclists are over represented in crash statistics where the vehicle operator has a positive, low blood alcohol concentration (BAC) (e.g., 0.05%). The NASA task load index (NASA-TLX) comprises sub-scales that purportedly assess different aspects of subjective workload. It was hypothesized that, compared to a zero BAC condition, low BACs would be associated with increases in workload ratings, and decrements in riding performance. Method: Forty participants (20 novice, 20 experienced) completed simulated motorcycle rides in urban and rural scenarios under low dose BAC conditions (0.00%, 0.02%, 0.05% BAC), while completing a safety relevant peripheral detection task (PDT). Six sub-scales of the NASA-TLX were completed after each ride. Riding performance was assessed using standard deviation of lateral position (SDLP). Hazard perception was assessed by response time to the PDT. Results: Riding performance and hazard perception were affected by alcohol. There was a significant increase in SDLP in the urban scenario and of PDT reaction time in the rural scenario under 0.05% BAC compared to 0.00% BAC. Overall NASA-TLX score increased at 0.02% and 0.05% BAC in the urban environment only, with a trend for novices to rate workload higher than experienced riders. There was a significant main effect of sub-scale on workload ratings in both the urban and rural scenarios. Discussion: 0.05% BAC was associated with decrements in riding performance in the urban environment, decrements in hazard perception in the rural environment, and increases in overall ratings of subjective workload in the urban environment. The workload sub-scales of the NASA-TLX appear to be measuring distinct aspects of motorcycle riding-related workload. Issues of workload and alcohol impaired riding performance are discussed.

Echo theatre : from experience to performance

This research project investigates the characteristics of Echo Theatre, its potential to foster performative and narrative competencies in students, and the role of the teacher in this performative and educational practice. Echo Theatre is a method devised during my storytelling practice and this research confirms that there is no identical research or teaching practice which involves students staging personal narratives in the classroom in this way. The study has been informed by crossdisciplinary theory studies from the fields of phenomenology, cognitive sciences, and theatre practice. To analyse and discuss Echo Theatre's potential contribution to the development of the child I have defined the concept of a performative competence as well as redefined the concept of a narrative competence. The situated, embodied and performative character of human cognition is emphasised as physical actions and thinking in movement is related to both gestural and conceptual understandings. Studies in philosophy and psychology confirm that narrative structure, related to identity construction and meaning-­‐making, can be attained through the performing body. We tell stories to know who we are. Telling stories then in the Echo Theatre model develops multiple competencies related to the performative aspects of theatre practice as well as the narrative aspects of storytelling. The practice-­‐led aspect of this research project includes two fieldwork projects involving a primary school class who created sixteen different Echo Theatre stories. Student participation reveals that Echo Theatre is most constructive when it moves through five phases; recalled experience, narrative, drama, performance, and evaluation. Ongoing reflection is a part of all five phases. The study also confirms that while there is potential for Echo Theatre to support the development of performative and narrative competencies in students, the effectiveness of this directly relates to the teacher's theatre knowledge and skills and his or her didactic attitude towards the students. This study confirms that the potential for learning through the moving and performing body of Echo Theatre is strengthened by working with personal narratives in the classroom and led by teachers displaying heightened skills and knowledge of the aesthetics and dynamics of theatrical form.

Star performers : task and contextual performance are components, but are they enough?

Identifying outstanding performers or ‘stars’ is a critical component of managing talent. However, organizational effectiveness in this area is limited by the current lack of guidance about the behaviour and characteristics of stars. We address this gap by combining a conceptual analysis with an empirical study involving 174 managers. Conceptually we examine the alignment of managers’ perceptions of outstanding performance with the well established task and contextual performance model and find this framework accounts for a core element in managers’ judgments about outstanding performers. However, a second, more qualitative approach finds that other dimensions including being self-directed, and a willingness to lead are also important. Our findings are consistent with a long-term trend toward identifying work effectiveness with highly discretionary, psychological and behavioural elements, and we consider the implications of this for the study and management of high level, individual effectiveness.

Filter and control performance bounds in the presence of model uncertainties with aerospace applications

This thesis establishes performance properties for approximate filters and controllers that are designed on the basis of approximate dynamic system representations. These performance properties provide a theoretical justification for the widespread application of approximate filters and controllers in the common situation where system models are not known with complete certainty. This research also provides useful tools for approximate filter designs, which are applied to hybrid filtering of uncertain nonlinear systems. As a contribution towards applications, this thesis also investigates air traffic separation control in the presence of measurement uncertainties.