The development of fast bowling experts in Australian cricket

In this paper, we highlight key concepts from dynamical systems theory and complexity sciences to exemplify constraints on talent development in a sample of elite cricketers. Eleven international fast bowlers who cumulatively had taken more than 2,400 test wickets in over 600 international test matches were interviewed using an in-depth, open-ended, and semi-structured approach. Qualitative data were analysed to identify key components in fast bowling expertise development. Results revealed that, contrary to traditional perspectives, the athletes progressed through unique, nonlinear trajectories of development, which appears to be a commonality in the experts' developmental pathways. During development, individual experts encountered unique constraints on the acquisition of expertise in cricket fast bowling, resulting in unique performance adaptations. Specifically, data illustrated experts' ability to continually adapt behaviours under multifaceted ecological constraints.

Fast content-based file type identification

Digital forensic examiners often need to identify the type of a file or file fragment based only on the content of the file. Content-based file type identification schemes typically use a byte frequency distribution with statistical machine learning to classify file types. Most algorithms analyze the entire file content to obtain the byte frequency distribution, a technique that is inefficient and time consuming. This paper proposes two techniques for reducing the classification time. The first technique selects a subset of features based on the frequency of occurrence. The second speeds classification by sampling several blocks from the file. Experimental results demonstrate that up to a fifteen-fold reduction in file size analysis time can be achieved with limited impact on accuracy.

Children’s food and activity patterns following a six-month child weight management program

Objective To describe the impact of a parent-led, family focused child weight management program on the food intake and activity patterns of pre-pubertal children. Methods n assessor-blinded, randomized controlled trial involving 111 (64% female) overweight, pre-pubertal children 6 to 9 years of age randomly assigned to parenting-skills training plus intensive lifestyle education, parenting-skills training alone, or a 12-month wait-listed control. Study outcomes were assessed at baseline, 6 months, and 12 months. This paper presents data on food intake assessed via a validated 54-item parent completed dietary questionnaire and activity behaviours assessed via a parent-report 20-item activity questionnaire. Results Intake of energy-dense nutrient poor foods was lower in both intervention groups at 6 months (mean difference, P+DA -1.5 serves [CI -2.0;-1.0]; P -1.0 serves [-2.0;-0.5]) and 12 months (mean difference P+DA -1.0 serves [CI -2.0;-0.5]; P -1.0 serves [-1.5; 0.0]) compared to baseline. Intake of vegetables, fruit, breads and cereals, meat and alternatives and dairy foods remained unchanged. Regardless of study group there were significant reductions over time in the reported time spent engaged in small screen activities and an increase in the time reported spent in active play. Conclusion Child weight management intervention that promotes food intake in line with national dietary guidelines achieves a reduction in children’s intake of energy dense, nutrient poor foods. This was achieved without compromising intake of nutrient-rich food and changes in were maintained even once the intervention ceased.

Analysis of micro-structural changes and measurement of their parameters of a food material

Food microstructure represents the way their elements arrangement and their interaction. Researchers in this field benefit from identifying new methods of examination of the microstructure and analysing the images. Experiments were undertaken to study micro-structural changes of food material during drying. Micro-structural images were obtained for potato samples of cubical shape at different moisture contents during drying using scanning electron microscopy. Physical parameters such as cell wall perimeter, and area were calculated using an image identification algorithm, based on edge detection and morphological operators. The algorithm was developed using Matlab.

What the experts think : fast bowling expertise acquisition and talent development

For applied sport scientists charged with developing talented performers an essential requirement is to identify components contributing to the development and maintenance of expertise. Previous qualitative analysis has revealed several psychological (e.g., mental focus, goal-setting and selfevaluation), socio-cultural (e.g. community and family support, cultural influence), physical (e.g., strength, height) and environmental (e.g., access to facilities and climate) constraints on successful Olympian development (Abbott et al., 2005). Open-ended interviews with expert athletes and/or expert coaches have been used to reveal competencies of elite performers to derive factors associated with success (Durand-Bush et al., 2002). However, the influence of these factors is likely to be sport-specific due to different task constraints and the changing nature of the performer-environment relationship through practice, coaching and competing (Vaeyens et al., 2008). So far, only one study on expertise acquisition in cricket has been undertaken. Weissensteiner, et al. (2009) found that development of expertise in cricket batting in Australia may be facilitated by early unstructured play (i.e. ‘backyard cricket’), a wide range of sport experience during development, and early exposure to playing with seniors.

Quantifying variability within technique and performance in elite fast bowlers : is technical variability dysfunctional or functional?

In fast bowling, cricketers are expected to produce a range of delivery lines and lengths while maximising ball speed. From a coaching perspective, technique consistency has been typically associated with superior performance in these areas. However, although bowlers are required to bowl consistently, at the elite level they must also be able to vary line, length and speed to adapt to opposition batters’ strengths and weaknesses. The relationship between technique and performance variability (and consistency) has not been investigated in previous fast bowling research. Consequently, the aim of this study was to quantify both technique (bowling action and coordination) and performance variability in elite fast bowlers from Australian Junior and National Pace Squads. Technique variability was analysed to investigate whether it could be classified as functional or dysfunctional in relation to speed and accuracy.

Designing for engagement towards healthier lifestyles through food image sharing : the case of I8DAT

This paper introduces the underlying design concepts of I8DAT, a food image sharing application that has been developed as part of a three-year research project – Eat, Cook, Grow: Ubiquitous Technology for Sustainable Food Culture in the City (http://www.urbaninformatics .net/projects/food) – exploring urban food practices to engage people in healthier, more environmentally and socially sustainable eating, cooking, and growing food in their everyday lives. The key aim of the project is to produce actionable knowledge, which is then applied to create and test several accessible, user-centred interactive design solutions that motivate user-engagement through playful and social means rather than authoritative information distribution. Through the design and implementation processes we envisage to integrate these design interventions to create a sustainable food network that is both technical and socio-cultural in nature (technosocial). Our primary research locale is Brisbane, Australia, with additional work carried out in three reference cities with divergent geographic, socio-cultural, and technological backgrounds: Seoul, South Korea, for its global leadership in ubiquitous technology, broadband access, and high population density; Lincoln, UK, for the regional and peri-urban dimension it provides, and Portland, Oregon, US, for its international standing as a hub of the sustainable food movement.

Start playing with your food : fun food experiences with mobile social media

Healthy and sustainable food is gaining more attention from consumers, industry, and researchers. Yet many approaches to date are limited to information dissemination, advertisement or education. We have embarked on a three year collaborative research project (2011 – 2013) to explore urban food practices – eating, cooking, growing food – to support the well-being of people and the environment. Our overall goal is to employ a user-centred interaction design research approach to inform the development of entertaining, real-time, mobile and networked applications, engaging playful feedback to build motivation. Our aspiration for this study is to deliver usable and useful mobile and situated interaction prototypes that employ individual and group strategies to foster food cultures that provide new pathways to produce, share and enjoy food that is green, healthy, and fun.

Fast rates for estimation error and oracle inequalities for model section

We consider complexity penalization methods for model selection. These methods aim to choose a model to optimally trade off estimation and approximation errors by minimizing the sum of an empirical risk term and a complexity penalty. It is well known that if we use a bound on the maximal deviation between empirical and true risks as a complexity penalty, then the risk of our choice is no more than the approximation error plus twice the complexity penalty. There are many cases, however, where complexity penalties like this give loose upper bounds on the estimation error. In particular, if we choose a function from a suitably simple convex function class with a strictly convex loss function, then the estimation error (the difference between the risk of the empirical risk minimizer and the minimal risk in the class) approaches zero at a faster rate than the maximal deviation between empirical and true risks. In this paper, we address the question of whether it is possible to design a complexity penalized model selection method for these situations. We show that, provided the sequence of models is ordered by inclusion, in these cases we can use tight upper bounds on estimation error as a complexity penalty. Surprisingly, this is the case even in situations when the difference between the empirical risk and true risk (and indeed the error of any estimate of the approximation error) decreases much more slowly than the complexity penalty. We give an oracle inequality showing that the resulting model selection method chooses a function with risk no more than the approximation error plus a constant times the complexity penalty.