Characterizing multi-agent team behavior from partial team tracings : evidence from the English Premier League

Real-world AI systems have been recently deployed which can automatically analyze the plan and tactics of tennis players. As the game-state is updated regularly at short intervals (i.e. point-level), a library of successful and unsuccessful plans of a player can be learnt over time. Given the relative strengths and weaknesses of a player’s plans, a set of proven plans or tactics from the library that characterize a player can be identified. For low-scoring, continuous team sports like soccer, such analysis for multi-agent teams does not exist as the game is not segmented into “discretized” plays (i.e. plans), making it difficult to obtain a library that characterizes a team’s behavior. Additionally, as player tracking data is costly and difficult to obtain, we only have partial team tracings in the form of ball actions which makes this problem even more difficult. In this paper, we propose a method to overcome these issues by representing team behavior via play-segments, which are spatio-temporal descriptions of ball movement over fixed windows of time. Using these representations we can characterize team behavior from entropy maps, which give a measure of predictability of team behaviors across the field. We show the efficacy and applicability of our method on the 2010-2011 English Premier League soccer data.

Efficient solution of two-sided nonlinear space-fractional diffusion equations using fast Poisson preconditioners

We develop a fast Poisson preconditioner for the efficient numerical solution of a class of two-sided nonlinear space fractional diffusion equations in one and two dimensions using the method of lines. Using the shifted Gr¨unwald finite difference formulas to approximate the two-sided(i.e. the left and right Riemann-Liouville) fractional derivatives, the resulting semi-discrete nonlinear systems have dense Jacobian matrices owing to the non-local property of fractional derivatives. We employ a modern initial value problem solver utilising backward differentiation formulas and Jacobian-free Newton-Krylov methods to solve these systems. For efficient performance of the Jacobianfree Newton-Krylov method it is essential to apply an effective preconditioner to accelerate the convergence of the linear iterative solver. The key contribution of our work is to generalise the fast Poisson preconditioner, widely used for integer-order diffusion equations, so that it applies to the two-sided space fractional diffusion equation. A number of numerical experiments are presented to demonstrate the effectiveness of the preconditioner and the overall solution strategy.

A banded preconditioner for the two-sided, nonlinear space-fractional diffusion equation

The method of lines is a standard method for advancing the solution of partial differential equations (PDEs) in time. In one sense, the method applies equally well to space-fractional PDEs as it does to integer-order PDEs. However, there is a significant challenge when solving space-fractional PDEs in this way, owing to the non-local nature of the fractional derivatives. Each equation in the resulting semi-discrete system involves contributions from every spatial node in the domain. This has important consequences for the efficiency of the numerical solver, especially when the system is large. First, the Jacobian matrix of the system is dense, and hence methods that avoid the need to form and factorise this matrix are preferred. Second, since the cost of evaluating the discrete equations is high, it is essential to minimise the number of evaluations required to advance the solution in time. In this paper, we show how an effective preconditioner is essential for improving the efficiency of the method of lines for solving a quite general two-sided, nonlinear space-fractional diffusion equation. A key contribution is to show, how to construct suitable banded approximations to the system Jacobian for preconditioning purposes that permit high orders and large stepsizes to be used in the temporal integration, without requiring dense matrices to be formed. The results of numerical experiments are presented that demonstrate the effectiveness of this approach.

Early adolescents’ helping behaviours when a friend is injured in a fight : the role of an extended Theory of Planned Behavior

This paper examines the role of first aid training in increasing adolescent helping behaviours when taught in a school-based injury prevention program, Skills for Preventing Injury in Youth (SPIY). The research involved the development and application of an extended Theory of Planned Behaviour (TPB), including “behavioural willingness in a fight situation,” “first aid knowledge” and “perceptions of injury seriousness”, to predict the relationship between participation in SPIY and helping behaviours when a friend is injured in a fight. From 35 Queensland high schools, 2500 Year 9 students (mean age = 13.5, 40% male) completed surveys measuring their attitudes, perceived behavioural control, subjective norms and behavioural intention, from the TPB, and added measures of behavioural willingness in a fight situation, perceptions of injury seriousness and first aid knowledge, to predict helping behaviours when a friend is injured in a fight. It is expected that the TPB will significantly contribute to understanding the relationship between participation in SPIY and helping behaviours when a friend is injured in a fight. Further analyses will determine whether the extension of the model significantly increases the variance explained in helping behaviours. The findings of this research will provide insight into the critical factors that may increase adolescent bystanders’ actions in injury situations.

Risky driving behavior among university students and staff in the Sultanate of Oman

Background: There is a well developed literature on research investigating the relationship between various driving behaviours and road crash involvement. However, this research has predominantly been conducted in developed economies dominated by western types of cultural environments. To date no research has been published that has empirically investigated this relationship within the context of the emerging economies such as Oman. Objective: The present study aims to investigate driving behaviour as indexed in the Driving Behaviour Questionnaire (DBQ) among a group of Omani university students and staff. Methods: A convenience non-probability self- selection sampling approach was utilized with Omani university students and staff. Results: A total of 1003 Omani students (n= 632) and staff (n=371) participated in the survey. Factor analysis of the BDQ revealed four main factors that were errors, speeding violation, lapses and aggressive violation. In the multivariate logistic backward regression analysis, the following factors were identified as significant predictors of being involved in causing at least one crash: driving experience, history of offences and two DBQ components i.e. errors and aggressive violation. Conclusion: This study indicates that errors and aggressive violation of the traffic regulations as well as history of having traffic offences are major risk factors for road traffic crashes among the sample. While previous international research has demonstrated that speeding is a primary cause of crashing, in the current context, the results indicate that an array of factors is associated with crashes. Further research using more rigorous methodology is warranted to inform the development of road safety countermeasures in Oman that improves overall traffic safety culture.

Integrating crowd-behavior modeling into military simulation using game technology

Crowds of noncombatants play a large and increasingly recognized role in modern military operations and often create substantial difficulties for the combatant forces involved. However, realistic models of crowds are essentially absent from current military simulations. To address this problem, the authors are developing a crowd simulation capable of generating crowds of noncombatant civilians that exhibit a variety of realistic individual and group behaviors at differing levels of fidelity. The crowd simulation is interoperable with existing military simulations using a standard, distributed simulation architecture. Commercial game technology is used in the crowd simulation to model both urban terrain and the physical behaviors of the human characters that make up the crowd. The objective of this article is to present the design and development process of a simulation that integrates commercially available game technology with current military simulations to generate realistic and believable crowd behavior.

Computer simulation of underground blast response of pile in saturated soil

This paper treats the blast response of a pile foundation in saturated sand using explicit nonlinear finite element analysis, considering complex material behavior of soil and soil–pile interaction. Blast wave propagation in the soil is studied and the horizontal deformation of pile and effective stresses in the pile are presented. Results indicate that the upper part of the pile to be vulnerable and the pile response decays with distance from the explosive. The findings of this research provide valuable information on the effects of underground explosions on pile foundation and will guide future development, validation and application of computer models.

Numerical approximation for a variable-order nonlinear reaction–subdiffusion equation

Fractional reaction–subdiffusion equations are widely used in recent years to simulate physical phenomena. In this paper, we consider a variable-order nonlinear reaction–subdiffusion equation. A numerical approximation method is proposed to solve the equation. Its convergence and stability are analyzed by Fourier analysis. By means of the technique for improving temporal accuracy, we also propose an improved numerical approximation. Finally, the effectiveness of the theoretical results is demonstrated by numerical examples.

Discrepancy between antennal and behavioral responses for enantiomers of a-Pinene : electrophysiology and behavior of helicoverpa armigera (Lepidoptera)

The ability of adult cotton bollworm, Helicoverpa armigera (Hübner), to distinguish and respond to enantiomers of α-pinene was investigated with electrophysiological and behavioral methods. Electroantennogram recordings using mixtures of the enantiomers at saturating dose levels, and single unit electrophysiology, indicated that the two forms were detected by the same receptor neurons. The relative size of the electroantennogram response was higher for the (−) compared to the (+) form, indicating greater affinity for the (−) form at the level of the dendrites. Behavioral assays investigated the ability of moths to discriminate between, and respond to the (+) and (−) forms of α-pinene. Moths with no odor conditioning showed an innate preference for (+)-α-pinene. This preference displayed by naïve moths was not significantly different from the preferences of moths conditioned on (+)-α-pinene. However, we found a significant difference in preference between moths conditioned on the (−) enantiomer compared to naïve moths and moths conditioned on (+)-α-pinene, showing that learning plays an important role in the behavioral response. Moths are less able to distinguish between enantiomers of α-pinene than different odors (e.g., phenylacetaldehyde versus (−)-α-pinene) in learning experiments. The relevance of receptor discrimination of enantiomers and learning ability of the moths in host plant choice is discussed.

The relationship between children's emotional and cognitive self-regulation at 2 to 3 years and prosocial behavior in the early years of school

This study used data from Growing Up in Australia: The Longitudinal Study of Australian Children (LSAC) to investigate how parent report of children’s emotional and cognitive regulation at age 2-3 years was associated with teacher ratings of children’s prosocial behaviors in the early years of school. A sample of 2,392 children was drawn from the LSAC Birth Cohort for the analyses. The analyses used structural equation modeling to estimate parameters of the relationships between key variables. Within the model, estimates of mother-reported emotional and cognitive regulation at age 2 to 3 years were significantly associated with teacher-reported prosocial behavior at 6 to 7 years. Emotional regulation was a slightly stronger indicator of prosocial behavior than cognitive regulation. Being female and from a family with a higher socioeconomic position were also associated with higher levels of prosocial behavior. Results are discussed in relation to the role of early childhood teachers in fostering children’s self-regulatory behaviors and in providing environments in which empathic and prosocial behaviors are modeled, guided, and scaffolded so that foundations are laid for caring behaviors to be understood and internalized by children.

Improving business process models using observed behavior

Process-aware information systems (PAISs) can be configured using a reference process model, which is typically obtained via expert interviews. Over time, however, contextual factors and system requirements may cause the operational process to start deviating from this reference model. While a reference model should ideally be updated to remain aligned with such changes, this is a costly and often neglected activity. We present a new process mining technique that automatically improves the reference model on the basis of the observed behavior as recorded in the event logs of a PAIS. We discuss how to balance the four basic quality dimensions for process mining (fitness, precision, simplicity and generalization) and a new dimension, namely the structural similarity between the reference model and the discovered model. We demonstrate the applicability of this technique using a real-life scenario from a Dutch municipality.

Examining young recreational sportswomen's intentions to engage in sun-protective behavior : the role of group and image norms

Researchers examined the sun-protective intentions and behavior of young, Caucasian, Australian sportswomen aged between 17 and 35 years (N = 100). The study adopted a 2 x 2 experimental design, comparing group norms (supportive vs. non-supportive) and image norms (tanned vs. pale) related to sun protection and taking into account group identification with friends and peers in the sport. While no significant findings emerged involving image norms, regression analyses revealed a significant two-way interaction for group norm x identification on recreational sportswomen's intentions to engage in sun protection in the next fortnight. Participants identifying strongly with their group had stronger intentions to engage in sun protection when exposed to a norm reflecting fellow recreational sportswomen engaging in sun-protective actions in comparison to those exposed to a non-supportive group. In addition, while prior intentions to engage in sun protection were not significantly related to sun-protection behavior, post-manipulation intentions after exposure to the sun-protective information that was provided were significantly related to follow-up behavior. Overall, the findings supported the importance of group-based social influences, rather than tanned media images, on sun-protective decisions among young recreational sportswomen and provided a targeted source for intervention strategies encouraging sun safety among this at-risk group for repeated sun exposure.

Social influences and the physical activity intentions of parents of young-children families: An extended Theory of Planned Behavior Approach

Evidence within Australia and internationally suggests parenthood as a risk factor for inactivity; however, research into understanding parental physical activity is scarce. Given that active parents can create active families and social factors are important for parents’ decision making, the authors investigated a range of social influences on parents’ intentions to be physically active. Parents (N = 580; 288 mothers and 292 fathers) of children younger than 5 years completed an extended Theory of Planned Behavior questionnaire either online or paper based. For both genders, attitude, control factors, group norms, friend general support, and an active parent identity predicted intentions, with social pressure and family support further predicting mothers’ intentions and active others further predicting fathers’ intentions. Attention to these factors and those specific to the genders may improve parents’ intentions to be physically active, thus maximizing the benefits to their own health and the healthy lifestyle practices for other family members.

Predicting the retention of first-time donors using an extended Theory of Planned Behavior

BACKGROUND: Donor retention is vital to blood collection agencies. Past research has highlighted the importance of early career behavior for long-term donor retention, yet research investigating the determinants of early donor behavior is scarce. Using an extended Theory of Planned Behavior (TPB), this study sought to identify the predictors of first-time blood donors' early career retention. STUDY DESIGN AND METHODS: First-time donors (n = 256) completed three surveys on blood donation. The standard TPB predictors and self-identity as a donor were assessed 3 weeks (Time 1) and at 4 months (Time 2) after an initial donation. Path analyses examined the utility of the extended TPB to predict redonation at 4 and 8 months after initial donation. RESULTS: The extended TPB provided a good fit to the data. Post-Time 1 and 2 behavior was consistently predicted by intention to redonate. Further, intention was predicted by attitudes, perceived control, and self-identity (Times 1 and 2). Donors' intentions to redonate at Time 1 were the strongest predictor of intention to donate at Time 2, while donors' behavior at Time 1 strengthened self-identity as a blood donor at Time 2. CONCLUSION: An extended TPB framework proved efficacious in revealing the determinants of first-time donor retention in an initial 8-month period. The results suggest that collection agencies should intervene to bolster donors' attitudes, perceived control, and identity as a donor during this crucial post–first donation period.

Nonlinear actuator fault detection for small-scale UAS

This paper presents a recursive strategy for online detection of actuator faults on a unmanned aerial system (UAS) subjected to accidental actuator faults. The proposed detection algorithm aims to provide a UAS with the capability of identifying and determining characteristics of actuator faults, offering necessary flight information for the design of fault-tolerant mechanism to compensate for the resultant side-effect when faults occur. The proposed fault detection strategy consists of a bank of unscented Kalman filters (UKFs) with each one detecting a specific type of actuator faults and estimating corresponding velocity and attitude information. Performance of the proposed method is evaluated using a typical nonlinear UAS model and it is demonstrated in simulations that our method is able to detect representative faults with a sufficient accuracy and acceptable time delay, and can be applied to the design of fault-tolerant flight control systems of UASs.