Representative learning design in dynamic interceptive actions

The overarching aim of this thesis was to investigate how processes of perception and action emerge under changing informational constraints during performance of multi-articular interceptive actions. Interceptive actions provide unique opportunities to study processes of perception and action in dynamic performance environments. The movement model used to exemplify the functionally coupled relationship between perception and action, from an ecological dynamics perspective, was cricket batting. Ecological dynamics conceptualises the human body as a complex system composed of many interacting sub-systems, and perceptual and motor system degrees of freedom, which leads to the emergence of patterns of behaviour under changing task constraints during performance. The series of studies reported in the Chapters of this doctoral thesis contributed to understanding of human behaviour by providing evidence of key properties of complex systems in human movement systems including self-organisation under constraints and meta-stability. Specifically, the studies: i) demonstrated how movement organisation (action) and visual strategies (perception) of dynamic human behaviour are constrained by changing ecological (especially informational) task constraints; (ii) provided evidence for the importance of representative design in experiments on perception and action; and iii), provided a principled theoretical framework to guide learning design in acquisition of skill in interceptive actions like cricket batting.

Two-stage power network reconfiguration strategy considering node importance and restored generation capacity

Network reconfiguration after complete blackout of a power system is an essential step for power system restoration. A new node importance evaluation method is presented based on the concept of regret, and maximisation of the average importance of a path is employed as the objective of finding the optimal restoration path. Then, a two-stage method is presented to optimise the network reconfiguration strategy. Specifically, the restoration sequence of generating units is first optimised so as to maximise the restored generation capacity, then the optimal restoration path is selected to restore the generating nodes concerned and the issues of selecting a serial or parallel restoration mode and the reconnecting failure of a transmission line are next considered. Both the restoration path selection and skeleton-network determination are implemented together in the proposed method, which overcomes the shortcoming of separate decision-making in the existing methods. Finally, the New England 10-unit 39-bus power system and the Guangzhou power system in South China are employed to demonstrate the basic features of the proposed method.

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".

A Hybrid Queue-based Bayesian Network Framework for passenger facilitation modelling

This paper presents a novel framework for the modelling of passenger facilitation in a complex environment. The research is motivated by the challenges in the airport complex system, where there are multiple stakeholders, differing operational objectives and complex interactions and interdependencies between different parts of the airport system. Traditional methods for airport terminal modelling do not explicitly address the need for understanding causal relationships in a dynamic environment. Additionally, existing Bayesian Network (BN) models, which provide a means for capturing causal relationships, only present a static snapshot of a system. A method to integrate a BN complex systems model with stochastic queuing theory is developed based on the properties of the Poisson and Exponential distributions. The resultant Hybrid Queue-based Bayesian Network (HQBN) framework enables the simulation of arbitrary factors, their relationships, and their effects on passenger flow and vice versa. A case study implementation of the framework is demonstrated on the inbound passenger facilitation process at Brisbane International Airport. The predicted outputs of the model, in terms of cumulative passenger flow at intermediary and end points in the inbound process, are found to have an $R^2$ goodness of fit of 0.9994 and 0.9982 respectively over a 10 hour test period. The utility of the framework is demonstrated on a number of usage scenarios including real time monitoring and `what-if' analysis. This framework provides the ability to analyse and simulate a dynamic complex system, and can be applied to other socio-technical systems such as hospitals.

Litigating law of the sea disputes using the UNCLOS Dispute Settlement System

The interpretation and application of the United Nations Convention on the Law of the Sea (UNCLOS) may be the source of many disputes. UNCLOS introduced an à la carte menu for dispute settlement with a number of options for international dispute resolution, including a compulsory procedure entailing binding decisions. While drafting this ambitious and complex system of dispute settlement, the drafters had to negotiate many delicate compromises to secure a system for the uniform interpretation of the Convention. The aim of this paper r is to explore why litigation using the UNCLOS dispute settlement system is, or is not, a preferred mode of settlement for law of the sea disputes.

Self-organization processes in field-invasion team sports

In nature, the interactions between agents in a complex system (fish schools; colonies of ants) are governed by information that is locally created. Each agent self-organizes (adjusts) its behaviour, not through a central command centre, but based on variables that emerge from the interactions with other system agents in the neighbourhood. Self-organization has been proposed as a mechanism to explain the tendencies for individual performers to interact with each other in field-invasion sports teams, displaying functional co-adaptive behaviours, without the need for central control. The relevance of self-organization as a mechanism that explains pattern-forming dynamics within attacker-defender interactions in field-invasion sports has been sustained in the literature. Nonetheless, other levels of interpersonal coordination, such as intra-team interactions, still raise important questions, particularly with reference to the role of leadership or match strategies that have been prescribed in advance by a coach. The existence of key properties of complex systems, such as system degeneracy, nonlinearity or contextual dependency, suggests that self-organization is a functional mechanism to explain the emergence of interpersonal coordination tendencies within intra-team interactions. In this opinion article we propose how leadership may act as a key constraint on the emergent, self-organizational tendencies of performers in field-invasion sports.

Science of winning soccer : emergent pattern-forming dynamics in association football

Quantitative analysis is increasingly being used in team sports to better understand performance in these stylized, delineated, complex social systems. Here we provide a first step toward understanding the pattern-forming dynamics that emerge from collective offensive and defensive behavior in team sports. We propose a novel method of analysis that captures how teams occupy sub-areas of the field as the ball changes location. We used the method to analyze a game of association football (soccer) based upon a hypothesis that local player numerical dominance is key to defensive stability and offensive opportunity. We found that the teams consistently allocated more players than their opponents in sub-areas of play closer to their own goal. This is consistent with a predominantly defensive strategy intended to prevent yielding even a single goal. We also find differences between the two teams' strategies: while both adopted the same distribution of defensive, midfield, and attacking players (a 4:3:3 system of play), one team was significantly more effective both in maintaining defensive and offensive numerical dominance for defensive stability and offensive opportunity. That team indeed won the match with an advantage of one goal (2 to 1) but the analysis shows the advantage in play was more pervasive than the single goal victory would indicate. Our focus on the local dynamics of team collective behavior is distinct from the traditional focus on individual player capability. It supports a broader view in which specific player abilities contribute within the context of the dynamics of multiplayer team coordination and coaching strategy. By applying this complex system analysis to association football, we can understand how players' and teams' strategies result in successful and unsuccessful relationships between teammates and opponents in the area of play.

Mathematical relationships for metal build-up on urban road surfaces based on traffic and land use characteristics

The study investigated the influence of traffic and land use parameters on metal build-up on urban road surfaces. Mathematical relationships were developed to predict metals originating from fuel combustion and vehicle wear. The analysis undertaken found that nickel and chromium originate from exhaust emissions, lead, copper and zinc from vehicle wear, cadmium from both exhaust and wear and manganese from geogenic sources. Land use does not demonstrate a clear pattern in relation to the metal build-up process, though its inherent characteristics such as traffic activities exert influence. The equation derived for fuel related metal load has high cross-validated coefficient of determination (Q2) and low Standard Error of Cross-Validation (SECV) values indicates that the model is reliable, while the equation derived for wear-related metal load has low Q2 and high SECV values suggesting its use only in preliminary investigations. Relative Prediction Error values for both equations are considered to be well within the error limits for a complex system such as an urban road surface. These equations will be beneficial for developing reliable stormwater treatment strategies in urban areas which specifically focus on mitigation of metal pollution.

Health Information Exchange in the wake of ‘big data’ paradigm – the theme is from ‘quality of information to quality of life’

Health Information Exchange (HIE) is an interesting phenomenon. It is a patient centric health and/or medical information management scenario enhanced by integration of Information and Communication Technologies (ICT). While health information systems are repositioning complex system directives, in the wake of the ‘big data’ paradigm, extracting quality information is challenging. It is anticipated that in this talk, ICT enabled healthcare scenarios with big data analytics will be shared. In addition, research and development regarding big data analytics, such as current trends of using these technologies for health care services and critical research challenges when extracting quality of information to improve quality of life will be discussed.

A Hybrid Queue-based Bayesian Network framework for passenger facilitation modelling

This paper presents a novel framework for the modelling of passenger facilitation in a complex environment. The research is motivated by the challenges in the airport complex system, where there are multiple stakeholders, differing operational objectives and complex interactions and interdependencies between different parts of the airport system. Traditional methods for airport terminal modelling do not explicitly address the need for understanding causal relationships in a dynamic environment. Additionally, existing Bayesian Network (BN) models, which provide a means for capturing causal relationships, only present a static snapshot of a system. A method to integrate a BN complex systems model with stochastic queuing theory is developed based on the properties of the Poisson and exponential distributions. The resultant Hybrid Queue-based Bayesian Network (HQBN) framework enables the simulation of arbitrary factors, their relationships, and their effects on passenger flow and vice versa. A case study implementation of the framework is demonstrated on the inbound passenger facilitation process at Brisbane International Airport. The predicted outputs of the model, in terms of cumulative passenger flow at intermediary and end points in the inbound process, are found to have an R2 goodness of fit of 0.9994 and 0.9982 respectively over a 10 h test period. The utility of the framework is demonstrated on a number of usage scenarios including causal analysis and ‘what-if’ analysis. This framework provides the ability to analyse and simulate a dynamic complex system, and can be applied to other socio-technical systems such as hospitals.

Innovate triple constraints model for better construction projects results

The continuous changing impacts appeared in all solution understanding approaches in the projects management field (especially in the construction field of work) by adopting dynamic solution paths. The paper will define what argue to be a better relational model for project management constraints (time, cost, and scope). This new model will increase the success factors of any complex program / project. This is a qualitative research adopting a new avenue of investigation by following different approach of attributing project activities with social phenomena, and supporting phenomenon with field of observations rather than mathematical method by emerging solution from human, and ants' colonies successful practices. The results will show the correct approach of relation between the triple constraints considering the relation as multi agents system having specified communication channels based on agents locations. Information will be transferred between agents, and action would be taken based on constraint agents locations in the project structure allowing immediate changes abilities in order to overcome issues of over budget, behind schedule, and additional scope impact. This is complex adaptive system having self organizes technique, and cybernetic control. Resulted model can be used for improving existing project management methodologies.

Dynamic agent composition for large-scale agent-based models

PURPOSE: This paper describes dynamic agent composition, used to support the development of flexible and extensible large-scale agent-based models (ABMs). This approach was motivated by a need to extend and modify, with ease, an ABM with an underlying networked structure as more information becomes available. Flexibility was also sought after so that simulations are set up with ease, without the need to program. METHODS: The dynamic agent composition approach consists in having agents, whose implementation has been broken into atomic units, come together at runtime to form the complex system representation on which simulations are run. These components capture information at a fine level of detail and provide a vast range of combinations and options for a modeller to create ABMs. RESULTS: A description of the dynamic agent composition is given in this paper, as well as details about its implementation within MODAM (MODular Agent-based Model), a software framework which is applied to the planning of the electricity distribution network. Illustrations of the implementation of the dynamic agent composition are consequently given for that domain throughout the paper. It is however expected that this approach will be beneficial to other problem domains, especially those with a networked structure, such as water or gas networks. CONCLUSIONS: Dynamic agent composition has many advantages over the way agent-based models are traditionally built for the users, the developers, as well as for agent-based modelling as a scientific approach. Developers can extend the model without the need to access or modify previously written code; they can develop groups of entities independently and add them to those already defined to extend the model. Users can mix-and-match already implemented components to form large-scales ABMs, allowing them to quickly setup simulations and easily compare scenarios without the need to program. The dynamic agent composition provides a natural simulation space over which ABMs of networked structures are represented, facilitating their implementation; and verification and validation of models is facilitated by quickly setting up alternative simulations.

An agent-based approach to immune modelling

This study focuses on trying to understand why the range of experience with respect to HIV infection is so diverse, especially as regards to the latency period. The challenge is to determine what assumptions can be made about the nature of the experience of antigenic invasion and diversity that can be modelled, tested and argued plausibly. To investigate this, an agent-based approach is used to extract high-level behaviour which cannot be described analytically from the set of interaction rules at the cellular level. A prototype model encompasses local variation in baseline properties contributing to the individual disease experience and is included in a network which mimics the chain of lymphatic nodes. Dealing with massively multi-agent systems requires major computational efforts. However, parallelisation methods are a natural consequence and advantage of the multi-agent approach. These are implemented using the MPI library.

Systems modelling of the socio-technical aspects of residential electricity use and network peak demand

Provision of network infrastructure to meet rising network peak demand is increasing the cost of electricity. Addressing this demand is a major imperative for Australian electricity agencies. The network peak demand model reported in this paper provides a quantified decision support tool and a means of understanding the key influences and impacts on network peak demand. An investigation of the system factors impacting residential consumers’ peak demand for electricity was undertaken in Queensland, Australia. Technical factors, such as the customers’ location, housing construction and appliances, were combined with social factors, such as household demographics, culture, trust and knowledge, and Change Management Options (CMOs) such as tariffs, price,managed supply, etc., in a conceptual ‘map’ of the system. A Bayesian network was used to quantify the model and provide insights into the major influential factors and their interactions. The model was also used to examine the reduction in network peak demand with different market-based and government interventions in various customer locations of interest and investigate the relative importance of instituting programs that build trust and knowledge through well designed customer-industry engagement activities. The Bayesian network was implemented via a spreadsheet with a tick box interface. The model combined available data from industry-specific and public sources with relevant expert opinion. The results revealed that the most effective intervention strategies involve combining particular CMOs with associated education and engagement activities. The model demonstrated the importance of designing interventions that take into account the interactions of the various elements of the socio-technical system. The options that provided the greatest impact on peak demand were Off-Peak Tariffs and Managed Supply and increases in the price of electricity. The impact in peak demand reduction differed for each of the locations and highlighted that household numbers, demographics as well as the different climates were significant factors. It presented possible network peak demand reductions which would delay any upgrade of networks, resulting in savings for Queensland utilities and ultimately for households. The use of this systems approach using Bayesian networks to assist the management of peak demand in different modelled locations in Queensland provided insights about the most important elements in the system and the intervention strategies that could be tailored to the targeted customer segments.

A near Optimal Cane Rail Scheduler under Limited and Unlimited Capacity Constraints

Australia is the world’s third largest exporter of raw sugar after Brazil and Thailand, with around $2.0 billion in export earnings. Transport systems play a vital role in the raw sugar production process by transporting the sugarcane crop between farms and mills. In 2013, 87 per cent of sugarcane was transported to mills by cane railway. The total cost of sugarcane transport operations is very high. Over 35% of the total cost of sugarcane production in Australia is incurred in cane transport. A cane railway network mainly involves single track sections and multiple track sections used as passing loops or sidings. The cane railway system performs two main tasks: delivering empty bins from the mill to the sidings for filling by harvesters; and collecting the full bins of cane from the sidings and transporting them to the mill. A typical locomotive run involves an empty train (locomotive and empty bins) departing from the mill, traversing some track sections and delivering bins at specified sidings. The locomotive then, returns to the mill, traversing the same track sections in reverse order, collecting full bins along the way. In practice, a single track section can be occupied by only one train at a time, while more than one train can use a passing loop (parallel sections) at a time. The sugarcane transport system is a complex system that includes a large number of variables and elements. These elements work together to achieve the main system objectives of satisfying both mill and harvester requirements and improving the efficiency of the system in terms of low overall costs. These costs include delay, congestion, operating and maintenance costs. An effective cane rail scheduler will assist the traffic officers at the mill to keep a continuous supply of empty bins to harvesters and full bins to the mill with a minimum cost. This paper addresses the cane rail scheduling problem under rail siding capacity constraints where limited and unlimited siding capacities were investigated with different numbers of trains and different train speeds. The total operating time as a function of the number of trains, train shifts and a limited number of cane bins have been calculated for the different siding capacity constraints. A mathematical programming approach has been used to develop a new scheduler for the cane rail transport system under limited and unlimited constraints. The new scheduler aims to reduce the total costs associated with the cane rail transport system that are a function of the number of bins and total operating costs. The proposed metaheuristic techniques have been used to find near optimal solutions of the cane rail scheduling problem and provide different possible solutions to avoid being stuck in local optima. A numerical investigation and sensitivity analysis study is presented to demonstrate that high quality solutions for large scale cane rail scheduling problems are obtainable in a reasonable time. Keywords: Cane railway, mathematical programming, capacity, metaheuristics