Collective dynamics and control of a 3-D small-world network with time delays

The paper presents a detailed analysis on the collective dynamics and delayed state feedback control of a three-dimensional delayed small-world network. The trivial equilibrium of the model is first investigated, showing that the uncontrolled model exhibits complicated unbounded behavior. Then three control strategies, namely a position feedback control, a velocity feedback control, and a hybrid control combined velocity with acceleration feedback, are then introduced to stabilize this unstable system. It is shown in these three control schemes that only the hybrid control can easily stabilize the 3-D network system. And with properly chosen delay and gain in the delayed feedback path, the hybrid controlled model may have stable equilibrium, or periodic solutions resulting from the Hopf bifurcation, or complex stranger attractor from the period-doubling bifurcation. Moreover, the direction of Hopf bifurcation and stability of the bifurcation periodic solutions are analyzed. The results are further extended to any "d" dimensional network. It shows that to stabilize a "d" dimensional delayed small-world network, at least a "d – 1" order completed differential feedback is needed. This work provides a constructive suggestion for the high dimensional delayed systems.

Understanding the abnormal brain activity in epilepsy as a potential predictor of the onset of an epileptic seizure

The Brain Research Institute (BRI) uses various types of indirect measurements, including EEG and fMRI, to understand and assess brain activity and function. As well as the recovery of generic information about brain function, research also focuses on the utilisation of such data and understanding to study the initiation, dynamics, spread and suppression of epileptic seizures. To assist with the future focussing of this aspect of their research, the BRI asked the MISG 2010 participants to examine how the available EEG and fMRI data and current knowledge about epilepsy should be analysed and interpreted to yield an enhanced understanding about brain activity occurring before, at commencement of, during, and after a seizure. Though the deliberations of the study group were wide ranging in terms of the related matters considered and discussed, considerable progress was made with the following three aspects. (1) The science behind brain activity investigations depends crucially on the quality of the analysis and interpretation of, as well as the recovery of information from, EEG and fMRI measurements. A number of specific methodologies were discussed and formalised, including independent component analysis, principal component analysis, profile monitoring and change point analysis (hidden Markov modelling, time series analysis, discontinuity identification). (2) Even though EEG measurements accurately and very sensitively record the onset of an epileptic event or seizure, they are, from the perspective of understanding the internal initiation and localisation, of limited utility. They only record neuronal activity in the cortical (surface layer) neurons of the brain, which is a direct reflection of the type of electrical activity they have been designed to record. Because fMRI records, through the monitoring of blood flow activity, the location of localised brain activity within the brain, the possibility of combining fMRI measurements with EEG, as a joint inversion activity, was discussed and examined in detail. (3) A major goal for the BRI is to improve understanding about ``when'' (at what time) an epileptic seizure actually commenced before it is identified on an eeg recording, ``where'' the source of this initiation is located in the brain, and ``what'' is the initiator. Because of the general agreement in the literature that, in one way or another, epileptic events and seizures represent abnormal synchronisations of localised and/or global brain activity the modelling of synchronisations was examined in some detail. References C. M. Michel, G. Thut, S. Morand, A. Khateb, A. J. Pegna, R. Grave de Peralta, S. Gonzalez, M. Seeck and T. Landis, Electric source imaging of human brain functions, Brain Res. 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Interpersonal coordination tendencies, decision-making and information governing dynamics in rugby union

In this chapter, ideas from ecological psychology and nonlinear dynamics are integrated to characterise decision-making as an emergent property of self-organisation processes in the interpersonal interactions that occur in sports teams. A conceptual model is proposed to capture constraints on dynamics of decisions and actions in dyadic systems, which has been empirically evaluated in simulations of interpersonal interactions in team sports. For this purpose, co-adaptive interpersonal dynamics in team sports such as rubgy union have been studied to reveal control parameter and collective variable relations in attacker-defender dyads. Although interpersonal dynamics of attackers and defenders in 1 vs 1 situations showed characteristics of chaotic attractors, the informational constraints of rugby union typically bounded dyadic systems into low dimensional attractors. Our work suggests that the dynamics of attacker-defender dyads can be characterised as an evolving sequence since players' positioning and movements are connected in diverse ways over time.

Interpersonal pattern dynamics and adaptive behavior in multiagent neurobiological systems : conceptual model and data

Ecological dynamics characterizes adaptive behavior as an emergent, self-organizing property of interpersonal interactions in complex social systems. The authors conceptualize and investigate constraints on dynamics of decisions and actions in the multiagent system of team sports. They studied coadaptive interpersonal dynamics in rugby union to model potential control parameter and collective variable relations in attacker–defender dyads. A videogrammetry analysis revealed how some agents generated fluctuations by adapting displacement velocity to create phase transitions and destabilize dyadic subsystems near the try line. Agent interpersonal dynamics exhibited characteristics of chaotic attractors and informational constraints of rugby union boxed dyadic systems into a low dimensional attractor. Data suggests that decisions and actions of agents in sports teams may be characterized as emergent, self-organizing properties, governed by laws of dynamical systems at the ecological scale. Further research needs to generalize this conceptual model of adaptive behavior in performance to other multiagent populations.

The impact of institutional, instrumental and interpersonal underpinnings on network dynamics and outcomes

Networks form a key part of the infrastructure of contemporary governance arrangements and, as such, are likely to continue for some time. Networks can take many forms and be formed for many reasons. Some networks have been explicitly designed to generate a collective response to an issue; some arise from a top down perspective through mandate or coercion; while others rely more heavily on interpersonal relations and doing the right thing. In this paper, these three different perspectives are referred to as the “3I”s: Instrumental, Institutional or Interpersonal. It is proposed that these underlying motivations will affect the process dynamics within the different types of networks in different ways and therefore influence the type of outcomes achieved. This proposition is tested through a number of case studies. An understanding of these differences will lead to more effective design, management and clearer expectations of what can be achieved through networks.

GPS fault detection with IMU and aircraft dynamics

Approaches with Vertical Guidance (APV) can provide greater safety and cost savings to general aviation through accurate GPS horizontal and vertical navigation. However, GPS needs augmentation to achieve APV fault detection requirements. Aircraft Based Augmentation Systems (ABAS) fuse GPS with additional sensors at the aircraft. Typical ABAS designs assume high-quality inertial sensors with Kalman filters but these are too expensive for general aviation. Instead of using high-quality (and expensive) sensors, the purpose of this paper is to investigate augmenting GPS with a low-quality MEMS IMU and Aircraft Dynamic Model (ADM). The IMU and ADM are fused together using a multiple model fusion strategy in a bank of Extended Kalman Filters (EKF) with the Normalized Solution Separation (NSS) fault detection scheme. A tightly-coupled configuration with GPS is used and frequent GPS updates are applied to the IMU and ADM to compensate for their errors. Based upon a simulated APV approach, the performance of this architecture in detecting a GPS ramp fault is investigated showing a performance improvement over a GPS-only “snapshot” implementation of the NSS method. The effect of fusing the IMU with the ADM is evaluated by comparing a GPS-IMU-ADM EKF with a GPS-IMU EKF where a small improvement in protection levels is shown.

Manipulating task constraints to improve tactical knowledge and collective decision-making in rugby union

In team sports such as rugby union, a myriad of decisions and actions occur within the boundaries that compose the performance perceptual- motor workspace. The way that these performance boundaries constrain decision making and action has recently interested researchers and has involved developing an understanding of the concept of constraints. Considering team sports as complex dynamical systems, signifies that they are composed of multiple, independent agents (i.e. individual players) whose interactions are highly integrated. This level of complexity is characterized by the multiple ways that players in a rugby field can interact. It affords the emergence of rich patterns of behaviour, such as rucks, mauls, and collective tactical actions that emerge due to players’ adjustments to dynamically varying competition environments. During performance, the decisions and actions of each player are constrained by multiple causes (e.g. technical and tactical skills, emotional states, plans, thoughts, etc.) that generate multiple effects (e.g. to run or pass, to move forward to tackle or maintain position and drive the opponent to the line), a prime feature in a complex systems approach to team games performance (Bar- Yam, 2004). To establish a bridge between the complexity sciences and learning design in team sports like rugby union, the aim of practice sessions is to prepare players to pick up and explore the information available in the multiple constraints (i.e. the causes) that influence performance. Therefore, learning design in training sessions should be soundly based on the interactions amongst players (i.e.teammates and opponents) that will occur in rugby matches. To improve individual and collective decision making in rugby union, Passos and colleagues proposed in previous work a performer- environment interaction- based approach rather than a traditional performer- based approach (Passos, Araújo, Davids & Shuttleworth, 2008).

Compensation of unmodeled aircraft dynamics in airborne inspection of linear infrastructure assets

Fixed-wing aircraft equipped with downward pointing cameras and/or LiDAR can be used for inspecting approximately piecewise linear assets such as oil-gas pipelines, roads and power-lines. Automatic control of such aircraft is important from a productivity and safety point of view (long periods of precision manual flight at low-altitude is not considered reasonable from a safety perspective). This paper investigates the effect of any unwanted coupling between guidance and autopilot loops (typically caused by unmodeled delays in the aircraft’s response), and the specific impact of any unwanted dynamics on the performance of aircraft undertaking inspection of piecewise linear corridor assets (such as powerlines). Simulation studies and experimental flight tests are used to demonstrate the benefits of a simple compensator in mitigating the unwanted lateral oscillatory behaviour (or coupling) that is caused by unmodeled time constants in the aircraft dynamics.

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.

Competing together : assessing the dynamics of team-team and player-team synchrony in professional association football

This study investigated movement synchronization of players within and between teams during competitive association football performance. Cluster phase analysis was introduced as a method to assess synchronies between whole teams and between individual players with their team as a function of time, ball possession and field direction. Measures of dispersion (SD) and regularity (sample entropy – SampEn – and cross sample entropy – Cross-SampEn) were used to quantify the magnitude and structure of synchrony. Large synergistic relations within each professional team sport collective were observed, particularly in the longitudinal direction of the field (0.89 ± 0.12) compared to the lateral direction (0.73 ± 0.16, p < .01). The coupling between the group measures of the two teams also revealed that changes in the synchrony of each team were intimately related (Cross-SampEn values of 0.02 ± 0.01). Interestingly, ball possession did not influence team synchronization levels. In player–team synchronization, individuals tended to be coordinated under near in-phase modes with team behavior (mean ranges between −7 and 5° of relative phase). The magnitudes of variations were low, but more irregular in time, for the longitudinal (SD: 18 ± 3°; SampEn: 0.07 ± 0.01), compared to the lateral direction (SD: 28 ± 5°; SampEn: 0.06 ± 0.01, p < .05) on-field. Increases in regularity were also observed between the first (SampEn: 0.07 ± 0.01) and second half (SampEn: 0.06 ± 0.01, p < .05) of the observed competitive game. Findings suggest that the method of analysis introduced in the current study may offer a suitable tool for examining team’s synchronization behaviors and the mutual influence of each team’s cohesiveness in competing social collectives.

Impact of passenger group dynamics on an airport evacuation process using an agent-based model

The safety of passengers is a major concern to airports. In the event of crises, having an effective and efficient evacuation process in place can significantly aid in enhancing passenger safety. Hence, it is necessary for airport operators to have an in-depth understanding of the evacuation process of their airport terminal. Although evacuation models have been used in studying pedestrian behaviour for decades, little research has been done in considering the evacuees’ group dynamics and the complexity of the environment. In this paper, an agent-based model is presented to simulate passenger evacuation process. Different exits were allocated to passengers based on their location and security level. The simulation results show that the evacuation time can be influenced by passenger group dynamics. This model also provides a convenient way to design airport evacuation strategy and examine its efficiency. The model was created using AnyLogic software and its parameters were initialised using recent research data published in the literature.

Interpreting scratch assays using pair density dynamics and approximate Bayesian computation

Quantifying the impact of biochemical compounds on collective cell spreading is an essential element of drug design, with various applications including developing treatments for chronic wounds and cancer. Scratch assays are a technically simple and inexpensive method used to study collective cell spreading; however, most previous interpretations of scratch assays are qualitative and do not provide estimates of the cell diffusivity, D, or the cell proliferation rate,l. Estimating D and l is important for investigating the efficacy of a potential treatment and provides insight into the mechanism through which the potential treatment acts. While a few methods for estimating D and l have been proposed, these previous methods lead to point estimates of D and l, and provide no insight into the uncertainty in these estimates. Here, we compare various types of information that can be extracted from images of a scratch assay, and quantify D and l using discrete computational simulations and approximate Bayesian computation. We show that it is possible to robustly recover estimates of D and l from synthetic data, as well as a new set of experimental data. For the first time, our approach also provides a method to estimate the uncertainty in our estimates of D and l. We anticipate that our approach can be generalized to deal with more realistic experimental scenarios in which we are interested in estimating D and l, as well as additional relevant parameters such as the strength of cell-to-cell adhesion or the strength of cell-to-substrate adhesion.

Multi-rotor with suspended load: System dynamics and control toolbox

There is an increasing demand for Unmanned Aerial Systems (UAS) to carry suspended loads as this can provide significant benefits to several applications in agriculture, law enforcement and construction. The load impact on the underlying system dynamics should not be neglected as significant feedback forces may be induced on the vehicle during certain flight manoeuvres. The constant variation in operating point induced by the slung load also causes conventional controllers to demand increased control effort. Much research has focused on standard multi-rotor position and attitude control with and without a slung load. However, predictive control schemes, such as Nonlinear Model Predictive Control (NMPC), have not yet been fully explored. To this end, we present a novel controller for safe and precise operation of multi-rotors with heavy slung load in three dimensions. The paper describes a System Dynamics and Control Simulation Toolbox for use with MATLAB/SIMULINK which includes a detailed simulation of the multi-rotor and slung load as well as a predictive controller to manage the nonlinear dynamics whilst accounting for system constraints. It is demonstrated that the controller simultaneously tracks specified waypoints and actively damps large slung load oscillations. A linear-quadratic regulator (LQR) is derived and control performance is compared. Results show the improved performance of the predictive controller for a larger flight envelope, including aggressive manoeuvres and large slung load displacements. The computational cost remains relatively small, amenable to practical implementations.

The dynamics of individual teacher autonomy: A case study of teachers' work in a Queensland secondary school

The emphasis on collegiality and collaboration in the literature on teachers' work and school reform has tended to underplay the significance of teacher autonomy. This thesis explores the dynamics of teachers' understandings and experiences of individual teacher autonomy (as contrasted with collective autonomy) in an independent school in Queensland which promoted itself as a 'teachers' school' with a strong commitment to individual teacher autonomy. The research was a case study which drew on methodological signposts from critical, feminist and traditional ethnography. Intensive fieldwork in the school over five months incorporated the ethnographic techniques of observation, interviews and document analysis. Teachers at Thornton College understood their experience of individual autonomy at three interrelated levels--in terms of their work in the classroom, their working life in the school, and their voice in the decision-making processes of the school. They felt that they experienced a great deal of individual autonomy at each of these three levels. These understandings and experiences of autonomy were encumbered or enabled by a range of internal and external stakeholder groups. There were also a number of structural influences (community perceptions, market forces, school size, time and bureaucracy) emerging from the economic, social and political structures in Australian society which influenced the experience of autonomy by teachers. The experience of individual teacher autonomy was constantly shifting, but there were some emergent patterns. Consensus on educational goals and vision, and strong expressions of trust and respect between teachers and stakeholders in the school, characterised the contexts in which teachers felt they experienced high levels of autonomy in their work. The demand for accountability and desire for relatedness motivated stakeholders and structural forces to influence teacher autonomy. Some significant gaps emerged between the rhetoric of a commitment to individual teacher autonomy and decision-making practices in the school, that gave ultimate power to the co-principals. Despite the rhetoric and promotion of non-hierarchical structures and collaborative decision-making processes, many teachers perceived that their experience of individual autonomy remained subject to the exercise of 'partial democracy' by school leaders.