Theory and practice in sport psychology and motor behaviour needs to be constrained by integrative modelling of brain and behaviour

Because of advances in technology, the non-invasive study of the human brain has enhanced the knowledge base within the neurosciences, resulting in an increased impact on the psychological study of human behaviour. We argue that application of this knowledge base should be considered in theoretical modelling within sport psychology and motor behaviour alongside existing ideas. We propose that interventions founded on current theoretical and empirical understanding in both psychology and the neurosciences may ultimately lead to greater benefits for athletes during practice and performance. As vehicles for exploring the arguments of a greater integration of psychology and neurosciences research, imagery and perception–action within the sport psychology and motor behaviour domains will serve as exemplars. Current neuroscience evidence will be discussed in relation to theoretical developments; the implications for sport scientists will be considered.     

Confirmatory factor analysis of the Competitive State Anxiety Inventory-2

The aim of this study was to evaluate the factor structure ofthe Competitive State Anxiety Inventory-2 (CSAI-2) using confirmatory factor analysis. Volunteer participants (n= 1213) completed the CSAI-2 approximately 1 h before competition and the data were analysed in two samples. The hypothesized model showed poor fit indices in both samples independently (Robust Comparative Fit Index: sample A=0.82, sample B =0.84) and simultaneously (Comparative FitIndex = 0.83), suggesting that the factor structure proposed by Martens et al. is flawed. Our findings suggest that a limitation of the Cognitive Anxiety scale derives from phrasing items around the word ‘concerned’ rather than ‘worried’. We suggest that being concerned about an impending performance does not necessarily mean that an athlete is experiencing negative thoughts, but that the athlete is acknowledging the importance and difficulty of the challenge and is attempting to mobilize resources to cope. The present results question the use of the CSAI-2 as a valid measure of competitive state anxiety.     

Career performance trajectories of Olympic swimmers: Benchmarks for talent development

Abstract

The age-related progression of elite athletes to their career-best performances can provide benchmarks for talent development. The purpose of this study was to model career performance trajectories of Olympic swimmers to develop these benchmarks. We searched the Web for annual best times of swimmers who were top 16 in pool events at the 2008 or 2012 Olympics, from each swimmer's earliest available competitive performance through to 2012. There were 6959 times in the 13 events for each sex, for 683 swimmers, with 10 ± 3 performances per swimmer (mean ± s). Progression to peak performance was tracked with individual quadratic trajectories derived using a mixed linear model that included adjustments for better performance in Olympic years and for the use of full-body polyurethane swimsuits in 2009. Analysis of residuals revealed appropriate fit of quadratic trends to the data. The trajectories provided estimates of age of peak performance and the duration of the age window of trivial improvement and decline around the peak. Men achieved peak performance later than women (24.2 ± 2.1 vs. 22.5 ± 2.4 years), while peak performance occurred at later ages for the shorter distances for both sexes (～1.5–2.0 years between sprint and distance-event groups). Men and women had a similar duration in the peak-performance window (2.6 ± 1.5 years) and similar progressions to peak performance over four years (2.4 ± 1.2%) and eight years (9.5 ± 4.8%). These data provide performance targets for swimmers aiming to achieve elite-level performance.     

OpenGL的应用与探讨

本文介绍了系统仿真的概念和OGL在建立仿真模型的功能特点,及其在系统仿真中的应用,并根据课题开发的仿真系统,很好的说明了用OpenGL建立的仿真模型具有建模方便、易于控制等优点。     

Evaluating engagement with graduate outcomes across higher education institutions in Aotearoa/New Zealand

Our research addressed two aims: to develop a systematic way to evaluate institutional engagement with graduate outcomes and to explore such engagement in higher education institutions in Aotearoa/New Zealand. An online survey was completed by 14/29 institutions with nine follow-up interviews to gather information on institutional engagement with graduate outcomes. Using a Maturity Modelling approach with indicators of planning, systems, delivery, assessment, evaluation and professional development support for graduate outcomes, we assessed the level of engagement in each institution. Results revealed patchy engagement across the polytechnic and university sectors. There was strong engagement with the planning, systems and delivery of graduate outcomes, particularly in the polytechnic sector, but much lower engagement with their assessment and evaluation, and overall, weak engagement with professional development support for graduate outcomes. Some mechanisms for promoting engagement with graduate outcomes were external drivers, a teaching-focused culture, strong leadership from the top and enabling structures. Our findings can inform institutional policies and practices in order to support not only compliance, but more importantly engagement with the graduate outcome agenda to improve the student learning experience.     

Ontology-driven approach for KPI meta-modelling,selection and reasoning

A key challenge in current Business Analytics (BA) is the selection of suitable indicators for business objectives. This requires the exploration of business data through data-driven approaches, while modelling business strategies together with domain experts in order to represent domain knowledge. In particular, Key Performance Indicators (KPIs) allow human experts to properly model ambiguous enterprise goals by means of quantitative variables with numeric ranges and clear thresholds. Besides business-related domains, the usefulness of KPIs has been shown in multiple domains, such as: Education, Healthcare and Agriculture. However, finding accurate KPIs for a given strategic goal still remains a complex task, specially due to the discrepancy between domain assumptions and data facts. In this regard, the semantic web emerges as a powerful technology for knowledge representation and data modeling through explicit representation formats and standards such as RDF(S) and OWL. By using this technology, the semantic annotation of indicators of business objectives would enrich the strategic model obtained. With this motivation, an ontology-driven approach is proposed to formally conceptualize essential elements of indicators, covering: performance, results, measures, goals and relationships of a given business strategy. In this way, all the data involved in the selection and analysis of KPIs are then integrated and stored in common repositories, hence enabling sophisticated querying and reasoning for semantic validation. The proposed semantic model is evaluated on a real-world case study on water management. A series of data analysis and reasoning tasks are conducted to show how the ontological model is able to detect semantic conflicts in actual correlations of selected indicators.     

Leveraging Deep Learning and SNA approaches for Smart City Policing in the Developing World

Is it possible to identify crime suspects by their mobile phone call records? Can the spatial-temporal movements of individuals linked to convicted criminals help to identify those who facilitate crime? Might we leverage the usage of mobile phones, such as incoming and outgoing call numbers, coordinates, call duration and frequency of calls, in a specific time window on either side of a crime to provide a focus for the location and period under investigation? Might the call data records of convicted criminals' social networks serve to distinguish criminals from non-criminals? To address these questions, we used heterogeneous call data records dataset by tapping into the power of social network analysis and the advancements in graph convolutional networks. In collaboration with the Punjab Police and Punjab Information Technology Board, these techniques were useful in identifying convicted individuals. The approaches employed are useful in identifying crime suspects and facilitators to support smart policing in the fight against the country's increasing crime rates. Last but not least, the applied methods are highly desirable to complement high-cost video-based smart city surveillance platforms in developing countries.     

Smart city model based on systems theory

While there are several partial solutions to model some aspects of cities (e.g. transportation or energy), there is no framework allowing modelling of a complex system such as a city. This paper aims on providing a solution that can be used by practitioners to model impact of different scenarios and smart city projects encapsulating different subsystems, such as transportation, energetics or, for example, eGovernment. The term “smart cities” is classified into Systems Theory, particularly focusing on Cyber-Physical Systems. This classification is further elaborated to define a new term, so-called Smart City Agent (SCA). The SCA is considered as the main building block for modelling smart cities. The approach within this paper however stresses the interconnection of different systems within a city. Its’ strength is in better exchange of data and among heterogeneous agents. This information management approach is the missing key in the growing market of partial smart city solutions as it will allow simulation of solutions in complex systems such as a city. The suitability of usefulness of the proposed approach is demonstrated on a use case dealing with charging of electrical vehicles. The results show that the approach is suitable for modelling of dynamic behaviour.     

基于因特网的个性化信息服务研究

个性化信息服务 ,是针对不同用户采用不同服务策略和方式提供不同信息内容的服务。它具有以用户为中心、对用户需求进行挖掘、灵活多样和主动将信息推送给用户的特点。其类型有 :个性化内容定制服务 ;个性化信息检索定制服务 ;个性化界面定制服务。用户个性化需求可通过用户访问记录挖掘、Bookmark和Agent获取。个性化信息服务模型 ,可采用信息A gent自主学习法、信息过滤法、基于多Multi AgentSystem的合作法等方法构建。参考文献 14。     

Longitudinal changes in submaximal oxygen uptake in 11- to 13-year-olds

The aim of this study was to monitor longitudinal changes in young people's submaximal oxygen uptake (VO 2 ) responses during horizontal treadmill running at 8 km h -1 . The 236 participants (118 boys, 118 girls) were aged 11.2 +/- 0.4 years (mean +/- s) at the onset of the study. Submaximal VO 2 , peak VO 2 and anthropometry were recorded annually for three consecutive years. The data were analysed using multi-level regression modelling within a multiplicative, allometric framework. The initial model examined sex, age and maturity-related changes in submaximal VO 2 relative to body mass as the sole anthropometric covariate. Our results demonstrate that the conventional ratio standard ml kg -1 min -1 does not adequately describe the true relationship between body mass and submaximal VO 2 during this period of growth. The effects of maturity and age were non-significant, but girls consumed significantly less VO 2 than boys running at 8 km h -1 . In subsequent models, stature was shown to be a significant explanatory variable, but this effect became non-significant when the sum of two skinfolds was added. Thus, within this population, submaximal VO 2 responses were explained predominantly by changes in body mass and skinfold thicknesses, with no additional maturity-related increments. When differences in body mass and skinfolds were controlled for, there was still a difference between the sexes in submaximal VO 2 , with girls becoming increasingly more economical with age.