High performance liquid chromatography determined alkamide levels in Australian-grown Echinacea spp.

Extracts of Echinacea spp. are widely used as therapeutic immunostimulants with such activity being attributed in part to the alkamide fractions of these plants. Using high performance liquid chromatography, the levels of 8 alkamides, including 2 tetraene alkamides (dodeca-2E, 4E, 8Z, 10E/Z-tetraenoic acid isobutylamide), were quantitatively determined in 2 Australian-grown Echinacea spp. Overall, the levels of alkamides in Australian-grown E. angustifolia were found to be comparable with levels obtained in this study and other studies for USA and European Echinacea spp. However, results obtained for one sample of E. angustifolia suggested that it may have been mislabelled and that it was most likely a sample of E. pallida. Levels of tetraene alkamides in Australian-grown E. purpurea were also similar to, if not higher, than levels which have been reported for the same species grown in Germany and the USA. Preliminary studies on the stability of alkamide compounds in E. angustifolia indicated that they are susceptible to degradation, with a 13% loss of alkamide level over 2 months. Overall, results indicate that there is considerable potential to develop Echinacea as a viable crop in Australia.

Composite SaaS resource management in cloud computing using evolutionary computation

Cloud computing is an emerging computing paradigm in which IT resources are provided over the Internet as a service to users. One such service offered through the Cloud is Software as a Service or SaaS. SaaS can be delivered in a composite form, consisting of a set of application and data components that work together to deliver higher-level functional software. SaaS is receiving substantial attention today from both software providers and users. It is also predicted to has positive future markets by analyst firms. This raises new challenges for SaaS providers managing SaaS, especially in large-scale data centres like Cloud. One of the challenges is providing management of Cloud resources for SaaS which guarantees maintaining SaaS performance while optimising resources use. Extensive research on the resource optimisation of Cloud service has not yet addressed the challenges of managing resources for composite SaaS. This research addresses this gap by focusing on three new problems of composite SaaS: placement, clustering and scalability. The overall aim is to develop efficient and scalable mechanisms that facilitate the delivery of high performance composite SaaS for users while optimising the resources used. All three problems are characterised as highly constrained, large-scaled and complex combinatorial optimisation problems. Therefore, evolutionary algorithms are adopted as the main technique in solving these problems. The first research problem refers to how a composite SaaS is placed onto Cloud servers to optimise its performance while satisfying the SaaS resource and response time constraints. Existing research on this problem often ignores the dependencies between components and considers placement of a homogenous type of component only. A precise problem formulation of composite SaaS placement problem is presented. A classical genetic algorithm and two versions of cooperative co-evolutionary algorithms are designed to now manage the placement of heterogeneous types of SaaS components together with their dependencies, requirements and constraints. Experimental results demonstrate the efficiency and scalability of these new algorithms. In the second problem, SaaS components are assumed to be already running on Cloud virtual machines (VMs). However, due to the environment of a Cloud, the current placement may need to be modified. Existing techniques focused mostly at the infrastructure level instead of the application level. This research addressed the problem at the application level by clustering suitable components to VMs to optimise the resource used and to maintain the SaaS performance. Two versions of grouping genetic algorithms (GGAs) are designed to cater for the structural group of a composite SaaS. The first GGA used a repair-based method while the second used a penalty-based method to handle the problem constraints. The experimental results confirmed that the GGAs always produced a better reconfiguration placement plan compared with a common heuristic for clustering problems. The third research problem deals with the replication or deletion of SaaS instances in coping with the SaaS workload. To determine a scaling plan that can minimise the resource used and maintain the SaaS performance is a critical task. Additionally, the problem consists of constraints and interdependency between components, making solutions even more difficult to find. A hybrid genetic algorithm (HGA) was developed to solve this problem by exploring the problem search space through its genetic operators and fitness function to determine the SaaS scaling plan. The HGA also uses the problem's domain knowledge to ensure that the solutions meet the problem's constraints and achieve its objectives. The experimental results demonstrated that the HGA constantly outperform a heuristic algorithm by achieving a low-cost scaling and placement plan. This research has identified three significant new problems for composite SaaS in Cloud. Various types of evolutionary algorithms have also been developed in addressing the problems where these contribute to the evolutionary computation field. The algorithms provide solutions for efficient resource management of composite SaaS in Cloud that resulted to a low total cost of ownership for users while guaranteeing the SaaS performance.

Distributed low-power image processing in wireless sensor networks for intelligent video surveillance applications

Distributed Wireless Smart Camera (DWSC) network is a special type of Wireless Sensor Network (WSN) that processes captured images in a distributed manner. While image processing on DWSCs sees a great potential for growth, with its applications possessing a vast practical application domain such as security surveillance and health care, it suffers from tremendous constraints. In addition to the limitations of conventional WSNs, image processing on DWSCs requires more computational power, bandwidth and energy that presents significant challenges for large scale deployments. This dissertation has developed a number of algorithms that are highly scalable, portable, energy efficient and performance efficient, with considerations of practical constraints imposed by the hardware and the nature of WSN. More specifically, these algorithms tackle the problems of multi-object tracking and localisation in distributed wireless smart camera net- works and optimal camera configuration determination. Addressing the first problem of multi-object tracking and localisation requires solving a large array of sub-problems. The sub-problems that are discussed in this dissertation are calibration of internal parameters, multi-camera calibration for localisation and object handover for tracking. These topics have been covered extensively in computer vision literatures, however new algorithms must be invented to accommodate the various constraints introduced and required by the DWSC platform. A technique has been developed for the automatic calibration of low-cost cameras which are assumed to be restricted in their freedom of movement to either pan or tilt movements. Camera internal parameters, including focal length, principal point, lens distortion parameter and the angle and axis of rotation, can be recovered from a minimum set of two images of the camera, provided that the axis of rotation between the two images goes through the camera's optical centre and is parallel to either the vertical (panning) or horizontal (tilting) axis of the image. For object localisation, a novel approach has been developed for the calibration of a network of non-overlapping DWSCs in terms of their ground plane homographies, which can then be used for localising objects. In the proposed approach, a robot travels through the camera network while updating its position in a global coordinate frame, which it broadcasts to the cameras. The cameras use this, along with the image plane location of the robot, to compute a mapping from their image planes to the global coordinate frame. This is combined with an occupancy map generated by the robot during the mapping process to localised objects moving within the network. In addition, to deal with the problem of object handover between DWSCs of non-overlapping fields of view, a highly-scalable, distributed protocol has been designed. Cameras that follow the proposed protocol transmit object descriptions to a selected set of neighbours that are determined using a predictive forwarding strategy. The received descriptions are then matched at the subsequent camera on the object's path using a probability maximisation process with locally generated descriptions. The second problem of camera placement emerges naturally when these pervasive devices are put into real use. The locations, orientations, lens types etc. of the cameras must be chosen in a way that the utility of the network is maximised (e.g. maximum coverage) while user requirements are met. To deal with this, a statistical formulation of the problem of determining optimal camera configurations has been introduced and a Trans-Dimensional Simulated Annealing (TDSA) algorithm has been proposed to effectively solve the problem.

ACE research vignette 026 : Do Entrepreneurs’ Personal Networks Influence Small Firm Performance?

This series of research vignettes is aimed at sharing current and interesting research findings from our team of international Entrepreneurship researchers. This vignette, written by Dr. Rene Bakker, examines the evidence on the effects of a entrepreneurs’ personal networks on small firm performance, and the factors that moderate this relationship.

Relationship between CEO salaries and performance of banks in Australia and Germany

Purpose: The purpose of this paper was to examine the relationship between CEO salaries and firm performance in the banking sector. Design/methodology/approach: The data relating to a six year period (2007 - 2012) was gathered from databases and the websites of the major banks in Australia and Germany. The data was subjected to Regression and Pearson Correlation Analysis to test if there was a positive correlation between total salary including incentive bonuses against the variables indicating the performance of the firm. Findings: The tests indicate a weak relationship between the CEO salary package and the key indicators of a firm's performance in Australian banks but a strong relationship in the German banks. Research limitations/implications: This study was limited in that it only covers the major banks in Australia and Germany and may therefore not be relevant to different countries with different economic climates. Practical implications: This study provides additional evidence to support the continued debate regarding the need to have greater accountability for CEO salary packages linked to actual performance measures of firms. Originality/value: This paper adds to the literature in so far as it compares two different Countries of the banking sector in a global market

Performance of a cognitive, but not visual, secondary task interacts with alcohol-induced balance impairment in novice and experienced motorcycle riders

The appropriateness of applying drink driving legislation to motorcycle riding has been questioned as there may be fundamental differences in the effects of alcohol on driving and motorcycling. It has been suggested that alcohol may redirect riders’ focus from higher-order cognitive skills such as cornering, judgement and hazard perception, to more physical skills such as maintaining balance. To test this hypothesis, the effects of low doses of alcohol on balance ability were investigated in a laboratory setting. The static balance of twenty experienced and twenty novice riders was measured while they performed either no secondary task, a visual (search) task, or a cognitive (arithmetic) task following the administration of alcohol (0%, 0.02%, and 0.05% BAC). Subjective ratings of intoxication and balance impairment increased in a dose-dependent manner in both novice and experienced motorcycle riders, while a BAC of 0.05%, but not 0.02%, was associated with impairments in static balance ability. This balance impairment was exacerbated when riders performed a cognitive, but not a visual, secondary task. Likewise, 0.05% BAC was associated with impairments in novice and experienced riders’ performance of a cognitive, but not a visual, secondary task, suggesting that interactive processes underlie balance and cognitive task performance. There were no observed differences between novice vs. experienced riders on static balance and secondary task performance, either alone or in combination. Implications for road safety and future ‘drink riding’ policy considerations are discussed.

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.

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.

An ecological dynamics approach to skill acquisition : implications for development of talent in sport.

This paper proposes how ecological dynamics, a theory focusing on the performer-environment relationship, provides a basis for understanding skill acquisition in sport. From this perspective, learners are conceptualized as complex, neurobiological systems in which inherent self-organisation tendencies support the emergence of adaptive behaviours under a range of interacting task and environmental constraints. Intentions, perceptions and actions are viewed as intertwined processes which underpin functional movement solutions assembled by each learner during skill acquisition. These ideas suggest that skill acquisition programmes need to sample information from the performance environment to guide behaviour in practice tasks. Skill acquisition task protocols should allow performers to use movement variability to explore and create opportunities for action, rather than constraining them to passively receiving information. This conceptualisation also needs to characterize the design of talent evaluation tests, which need to faithfully represent the perception-action relationships in the performance environment. Since the dynamic nature of changing task constraints in sports cannot be predicted over longer timescales, an implication is that talent programmes should focus on developing performance expertise in each individual, rather than over-relying on identification of expert performers at specific points in time.

The engagement of small to medium enterprises for managing waste in building retrofit projects

The market of building retrofits is increasingly more intensified as existing buildings are aging. The building retrofit projects involve existing buildings which impose constraints on stakeholders throughout the project process. They are also risky, complex, less predictable and difficult to be well planned with on-site waste becoming one of the critical issues. Small and Medium Enterprises (SMEs) carry out most of the work in retrofit projects as subcontractors, but they often do not have adequate resources to deal with the specific technical challenges and project risks related to waste. This paper first discusses the requirements of waste management in building retrofit projects considering specific project characteristics and work natures, and highlights the importance of involving SMEs in waste planning and management through an appropriate way. By utilizing semi-structured interviews, this research develops a process model for SMEs to be applied in waste management. A collaboration scenario is also developed for collaborative waste planning and management by SMEs as subcontractors and large companies as main contractors. Findings from the paper will promote coordination of project delivery and waste management in building retrofit projects, and improve the involvement and performance of SMEs in dealing with waste problems.

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.

An examination of learning design in elite springboard diving

The overarching aim of this programme of work was to evaluate the effectiveness of the existing learning environment within the Australian Institute of Sport (AIS) elite springboard diving programme. Unique to the current research programme, is the application of ideas from an established theory of motor learning, specifically ecological dynamics, to an applied high performance training environment. In this research programme springboard diving is examined as a complex system, where individual, task, and environmental constraints are continually interacting to shape performance. As a consequence, this thesis presents some necessary and unique insights into representative learning design and movement adaptations in a sample of elite athletes. The questions examined in this programme of work relate to how best to structure practice, which is central to developing an effective learning environment in a high performance setting. Specifically, the series of studies reported in the chapters of this doctoral thesis: (i) provide evidence for the importance of designing representative practice tasks in training; (ii) establish that completed and baulked (prematurely terminated) take-offs are not different enough to justify the abortion of a planned dive; and (iii), confirm that elite athletes performing complex skills are able to adapt their movement patterns to achieve consistent performance outcomes from variable dive take-off conditions. Chapters One and Two of the thesis provide an overview of the theoretical ideas framing the programme of work, and include a review of literature pertinent to the research aims and subsequent empirical chapters. Chapter Three examined the representativeness of take-off tasks completed in the two AIS diving training facilities routinely used in springboard diving. Results highlighted differences in the preparatory phase of reverse dive take-offs completed by elite divers during normal training tasks in the dry-land and aquatic training environments. The most noticeable differences in dive take-off between environments began during the hurdle (step, jump, height and flight) where the diver generates the necessary momentum to complete the dive. Consequently, greater step lengths, jump heights and flight times, resulted in greater board depression prior to take-off in the aquatic environment where the dives required greater amounts of rotation. The differences observed between the preparatory phases of reverse dive take-offs completed in the dry-land and aquatic training environments are arguably a consequence of the constraints of the training environment. Specifically, differences in the environmental information available to the athletes, and the need to alter the landing (feet first vs. wrist first landing) from the take-off, resulted in a decoupling of important perception and action information and a decomposition of the dive take-off task. In attempting to only practise high quality dives, many athletes have followed a traditional motor learning approach (Schmidt, 1975) and tried to eliminate take-off variations during training. Chapter Four examined whether observable differences existed between the movement kinematics of elite divers in the preparation phases of baulked (prematurely terminated) and completed take-offs that might justify this approach to training. Qualitative and quantitative analyses of variability within conditions revealed greater consistency and less variability when dives were completed, and greater variability amongst baulked take-offs for all participants. Based on these findings, it is probable that athletes choose to abort a planned take-off when they detect small variations from the movement patterns (e.g., step lengths, jump height, springboard depression) of highly practiced comfortable dives. However, with no major differences in coordination patterns (topology of the angle-angle plots), and the potential for negative performance outcomes in competition, there appears to be no training advantage in baulking on unsatisfactory take-offs during training, except when a threat of injury is perceived by the athlete. Instead, it was considered that enhancing the athletes' movement adaptability would be a more functional motor learning strategy. In Chapter Five, a twelve-week training programme was conducted to determine whether a sample of elite divers were able to adapt their movement patterns and complete dives successfully, regardless of the perceived quality of their preparatory movements on the springboard. The data indeed suggested that elite divers were able to adapt their movements during the preparatory phase of the take-off and complete good quality dives under more varied take-off conditions; displaying greater consistency and stability in the key performance outcome (dive entry). These findings are in line with previous research findings from other sports (e.g., shooting, triple jump and basketball) and demonstrate how functional or compensatory movement variability can afford greater flexibility in task execution. By previously only practising dives with good quality take-offs, it can be argued that divers only developed strong couplings between information and movement under very specific performance circumstances. As a result, this sample was sometimes characterised by poor performance in competition when the athletes experienced a suboptimal take-off. Throughout this training programme, where divers were encouraged to minimise baulking and attempt to complete every dive, they demonstrated that it was possible to strengthen the information and movement coupling in a variety of performance circumstances, widening of the basin of performance solutions and providing alternative couplings to solve a performance problem even when the take-off was not ideal. The results of this programme of research provide theoretical and experimental implications for understanding representative learning design and movement pattern variability in applied sports science research. Theoretically, this PhD programme contributes empirical evidence to demonstrate the importance of representative design in the training environments of high performance sports programmes. Specifically, this thesis advocates for the design of learning environments that effectively capture and enhance functional and flexible movement responses representative of performance contexts. Further, data from this thesis showed that elite athletes performing complex tasks were able to adapt their movements in the preparatory phase and complete good quality dives under more varied take-off conditions. This finding signals some significant practical implications for athletes, coaches and sports scientists. As such, it is recommended that care should be taken by coaches when designing practice tasks since the clear implication is that athletes need to practice adapting movement patterns during ongoing regulation of multi-articular coordination tasks. For example, volleyball servers can adapt to small variations in the ball toss phase, long jumpers can visually regulate gait as they prepare for the take-off, and springboard divers need to continue to practice adapting their take-off from the hurdle step. In summary, the studies of this programme of work have confirmed that the task constraints of training environments in elite sport performance programmes need to provide a faithful simulation of a competitive performance environment in order that performance outcomes may be stabilised with practice. Further, it is apparent that training environments can be enhanced by ensuring the representative design of task constraints, which have high action fidelity with the performance context. Ultimately, this study recommends that the traditional coaching adage 'perfect practice makes perfect", be reconsidered; instead advocating that practice should be, as Bernstein (1967) suggested, "repetition without repetition".