Crash risk estimation and assessment tool

Currently in Australia, there are no decision support tools for traffic and transport engineers to assess the crash risk potential of proposed road projects at design level. A selection of equivalent tools already exists for traffic performance assessment, e.g. aaSIDRA or VISSIM. The Urban Crash Risk Assessment Tool (UCRAT) was developed for VicRoads by ARRB Group to promote methodical identification of future crash risks arising from proposed road infrastructure, where safety cannot be evaluated based on past crash history. The tool will assist practitioners with key design decisions to arrive at the safest and the most cost -optimal design options. This paper details the development and application of UCRAT software. This professional tool may be used to calculate an expected mean number of casualty crashes for an intersection, a road link or defined road network consisting of a number of such elements. The mean number of crashes provides a measure of risk associated with the proposed functional design and allows evaluation of alternative options. The tool is based on historical data for existing road infrastructure in metropolitan Melbourne and takes into account the influence of key design features, traffic volumes, road function and the speed environment. Crash prediction modelling and risk assessment approaches were combined to develop its unique algorithms. The tool has application in such projects as road access proposals associated with land use developments, public transport integration projects and new road corridor upgrade proposals

Generalized breakup and coalescence models for population balance modelling of liquid-liquid flows

Population balance framework is a useful tool that can be used to describe size distribution of droplets in a liquid-liquid dispersion. Breakup and coalescence models provide closures for mathematical formulation of the population balance equation (PBE) and are crucial for accu- rate predictions of the mean droplet size in the ow. Number of closures for both breakup and coalescence can be identi ed in the literature and most of them need an estimation of model parameters that can di er even by several orders of magnitude on a case to case basis. In this paper we review the fundamental assumptions and derivation of breakup and coalescence ker- nels. Subsequently, we rigorously apply two-stage optimization over several independent sets of experiments in order to identify model parameters. Two-stage identi cation allows us to estab- lish new parametric dependencies valid for experiments that vary over large ranges of important non-dimensional groups. This be adopted for optimization of parameters in breakup and co- alescence models over multiple cases and we propose a correlation based on non-dimensional numbers that is applicable to number of di erent ows over wide range of Reynolds numbers

Red Guide Paper 42: Managing a Module Part 1: Delivering a Module

This revised guide covers various aspects of the process for developing a new module and provides an overview of the general principles of module development

The use of administrative health care databases to identify patients with Rheumatoid Arthritis

Objective: To validate and compare the decision rules to identify rheumatoid arthritis (RA) in administrative databases. Methods: A study was performed using administrative health care data from a population of 1 million people who had access to universal health care. Information was available on hospital discharge abstracts and physician billings. RA cases in health administrative databases were matched 1:4 by age and sex to randomly selected controls without inflammatory arthritis. Seven case definitions were applied to identify RA cases in the health administrative data, and their performance was compared with the diagnosis by a rheumatologist. The validation study was conducted on a sample of individuals with administrative data who received a rheumatologist consultation at the Arthritis Center of Nova Scotia. Results: We identified 535 RA cases and 2,140 non-RA, noninflammatory arthritis controls. Using the rheumatologist's diagnosis as the gold standard, the overall accuracy of the case definitions for RA cases varied between 68.9% and 82.9% with a kappa statistic between 0.26 and 0.53. The sensitivity and specificity varied from 20.7% to 94.8% and 62.5% to 98.5%, respectively. In a reference population of 1 million, the estimated annual number of incident cases of RA was between 176 and 1,610 and the annual number of prevalent cases was between 1,384 and 5,722. Conclusion: The accuracy of case definitions for the identification of RA cases from rheumatology clinics using administrative health care databases is variable when compared to a rheumatologist's assessment. This should be considered when comparing results across studies. This variability may also be used as an advantage in different study designs, depending on the relative importance of sensitivity and specificity for identifying the population of interest to the research question

Improving the performance of cascade correlation neural networks on multimodal functions

Intrinsic qualities of the cascade correlation algorithm make it a popular choice for many researchers wishing to utilize neural networks. Problems arise when the outputs required are highly multimodal over the input domain. The mean squared error of the approximation increases significantly as the number of modes increases. By applying ensembling and early stopping, we show that this error can be reduced by a factor of three. We also present a new technique based on subdivision that we call patchworking. When used in combination with early stopping and ensembling the mean improvement in error is over 10 in some cases

Targeting Creativity Skills for High School Students with Special Needs

Helping students organize their thoughts is an important component of teaching. Including thinking maps in instruction is beneficial and can be used to measure multiple aspects of student learning, such as understanding creativity. Creativity is a unique construct and often not evaluated in schools. This qualitative study examined creativity, which is the collection of the person, the field, and the domain (Ford, 1996), through a rubric, interviews, a sorting task, and teacher logs. A convenience sample including three high school students were selected to participate. The triangulation of the data sources revealed four themes: collaboration with peers and adults, brainstorming makes academic tasks more accessible, tolerating difficulty, and making connections

Mental Fatigue in Football

INTRODUCTION: Mental fatigue is a psychobiological state experienced following exposure to cognitively demanding tasks. Anecdotal evidence shows that mental fatigue can impair football (soccer) performance based on the cognitive demands of match play, fixture congestion, receiving high volumes of tactical information and internal and external pressures to succeed. In six original investigations, induced mental fatigue has negatively influenced football specific skill, physical, tactical and decision-making performance. However, these studies share consistent limitations, which include the use of cognitive tasks with low ecological validity to induce mental fatigue, as well as the recruitment of sub-elite or recreational players. Further research is required to address the limitations of the current research, investigate the relevance of current methods employed to induce mental fatigue, and to understand the true cognitive demands experienced by elite level football players. Therefore the aims of this thesis were as follows: i) to evaluate the applicability of the current mental fatigue research to elite football settings, ii) understand the relevance of the modified Stroop task in inducing mental fatigue, plus its impact on using implicit and explicit information, and iii) use a mixed methods approach to elucidate cognitive demands and influence on performance in elite male, female and academy football players. METHODS: i) A literature review was conducted to understand the collective impact of induced mental fatigue on football specific performance. ii) A current opinion article critically examined the methodology of the current mental fatigue in football research, with recommendations provided for future study designs. iii) The modified Stroop task was assessed for its impact on using implicit and explicit cues, plus boredom, a construct similar to the demands of mental fatigue. In addition, the impact of a brief rest period from cognitively demanding activity was measured. iv) English Football League and National League players completed an online survey which investigated the impact of football and lifestyle specific cognitive activities on perceived mental fatigue and impact on performance. v) An additional survey was completed by elite English academy football players (U14 – U23) which explored the effects of football and adolescent specific activities on perceived mental fatigue and impact on performance. vi) Focus group interviews explored the psychological demands of elite female football. RESULTS: i) Mental fatigue studies have used repetitive cognitive tasks with low contextual interference which do not resemble the real-life cognitive demands (i.e. high contextual interference in a dynamic environment) of elite football. ii) The modified Stroop elicits high subjective mental fatigue and boredom ratings which significantly reduce (but not to baseline levels) following a short break. iii) In elite English Football League/National League and academy football, any cognitive tasks completed are short and frequent (intake of tactical information, media commitments, travel) with a negligible influence on perceptions of mental fatigue and performance. A contrast was evident in elite female football, where travel, intake of excessive tactical information and internal pressure to succeed were commonly cited as psychological demands. DISCUSSION: Mental fatigue in football may be a transient sensation that subsides following a rest period. Due to predominantly extensive experience in football, elite football players may become accustomed to daily cognitive stressors, or the tasks completed may be too brief compared to the protocols that have been applied in studies to mental fatigue. Conversely mental fatigue may be more prevalent in environments where football is accompanied by additional commitments (full time work/education). The previous research inducing mental fatigue immediately prior to task performance may also be an irrelevant time period where mental fatigue is experienced in elite settings, likely due to high arousal induced by caffeine intake, listening to music and the players general intrinsic motivation to play. Future research is required to investigate the impact of other time periods (e.g. latter stages of a match, 24 hours post-match) and longitudinal durations (i.e. daily monitoring throughout a season) and subsequent risk of mental fatigue

A study of early stopping, ensembling, and patchworking for cascade correlation neural networks

The constructive topology of the cascade correlation algorithm makes it a popular choice for many researchers wishing to utilize neural networks. However, for multimodal problems, the mean squared error of the approximation increases significantly as the number of modes increases. The components of this error will comprise both bias and variance and we provide formulae for estimating these values from mean squared errors alone. We achieve a near threefold reduction in the overall error by using early stopping and ensembling. Also described is a new subdivision technique that we call patchworking. Patchworking, when used in combination with early stopping and ensembling, can achieve an order of magnitude improvement in the error. Also presented is an approach for validating the quality of a neural network’s training, without the explicit use of a testing dataset