Using data mining to predict road crash count with a focus on skid resistance values

Road crashes cost world and Australian society a significant proportion of GDP, affecting productivity and causing significant suffering for communities and individuals. This paper presents a case study that generates data mining models that contribute to understanding of road crashes by allowing examination of the role of skid resistance (F60) and other road attributes in road crashes. Predictive data mining algorithms, primarily regression trees, were used to produce road segment crash count models from the road and traffic attributes of crash scenarios. The rules derived from the regression trees provide evidence of the significance of road attributes in contributing to crash, with a focus on the evaluation of skid resistance.

When the right to be counted doesn’t count : the politics and challenges of researching the health of asylum seekers

A fundamental prerequisite of population health research is the ability to establish an accurate denominator. This in turn requires that every individual in the study population is counted. However, this seemingly simple principle has become a point of conflict between researchers whose aim is to produce evidence of disparities in population health outcomes and governments whose policies promote(intentionally or not) inequalities that are the underlying causes of health disparities. Research into the health of asylum seekers is a case in point. There is a growing body of evidence documenting the adverse affects of recent changes in asylum-seeking legislation, including mandatory detention. However, much of this evidence has been dismissed by some governments as being unsound, biased and unscientific because, it is argued, evidence is derived from small samples or from case studies. Yet, it is the policies of governments that are the key barrier to the conduct of rigorous population health research on asylum seekers. In this paper, the authors discuss the challenges of counting asylum seekers and the limitations of data reported in some industrialized countries. They argue that the lack of accurate statistical data on asylum seekers has been an effective neo-conservative strategy for erasing the health inequalities in this vulnerable population, indeed a strategy that renders invisible this population. They describe some alternative strategies that may be used by researchers to obtain denominator data on hard-to-reach populations such as asylum seekers.

Does 'habitus' count in Chinese Australians' mathematics achievement?

Large-scale international comparative studies and cross-ethnic studies have revealed that Chinese students, whether living in China or overseas, consistently outperform their counterparts in mathematics achievement. These studies tended to explain this result from psychological, educational, or cultural perspectives. However, there is scant sociological investigation addressing Chinese students’ better mathematics achievement. Drawing on Bourdieu’s sociological theory, this study conceptualises Chinese Australians’ “Chineseness” by the notion of ‘habitus’ and considers this “Chineseness” generating but not determinating mechanism that underpins Chinese Australians’ mathematics learning. Two hundred and thirty complete responses from Chinese Australian participants were collected by an online questionnaire. Simple regression model statistically significantly well predicted mathematics achievement by “Chineseness” (F = 141.90, R = .62, t = 11.91, p < .001). Taking account of “Chineseness” as a sociological mechanism for Chinese Australians’ mathematics learning, this study complements psychological and educational impacts on better mathematics achievement of Chinese students revealed by previous studies. This study also challenges the cultural superiority discourse that attributes better mathematics achievement of Chinese students to cultural factors.

Body temperature and its effect on leukocyte mobilization, cytokines and markers of neutrophil activation during and after exercise

We investigated the influence of rectal temperature on the immune system during and after exercise. Ten well-trained male cyclists completed exercise trials (90 min cycling at 60% VO(2max) + 16.1 - km time trial) on three separate occasions: once in 18 degrees C and twice in 32 degrees C. Twenty minutes after the trials in 32 degrees C, the cyclists sat for approximately 20 min in cold water (14 degrees C) on one occasion, whereas on another occasion they sat at room temperature. Rectal temperature increased significantly during cycling in both conditions, and was significantly higher after cycling in 32 degrees C than in 18 degrees C (P < 0.05). Leukocyte counts increased significantly during cycling but did not differ between the conditions. The concentrations of serum interleukin (IL)-6, IL-8 and IL-10, plasma catecholamines, granulocyte-colony stimulating factor, myeloperoxidase and calprotectin increased significantly following cycling in both conditions. The concentrations of serum IL-8 (25%), IL-10 (120%), IL-1 receptor antagonist (70%), tumour necrosis factor-alpha (17%), plasma myeloperoxidase (26%) and norepinephrine (130%) were significantly higher after cycling in 32 degrees C than in 18 degrees C. During recovery from exercise in 32 degrees C, rectal temperature was significantly lower in response to sitting in cold water than at room temperature. However, immune changes during 90 min of recovery did not differ significantly between sitting in cold water and at room temperature. The greater rise in rectal temperature during exercise in 32 degrees C increased the concentrations of serum IL-8, IL-10, IL-1ra, TNF-alpha and plasma myeloperoxidase, whereas the greater decline in rectal temperature during cold water immersion after exercise did not affect immune responses.

Exercise-recruited NK cells display exercise-associated eHSP-70

It is hypothesized that increased plasma or serum concentrations of extracellular heat shock proteins (eHSP) serve as a danger signal to the innate immune system. Cellular binding of eHSP leads to activation of NK cells and monocytes, as measured by their increased cytokine production, mitotic division and killing capacity. We examined whether eHSP binds to NK lymphocytes in vivo in athletes performing endurance exercise in the heat. Eighteen trained male runners ran at 70% VO2max at 35 degrees C and 40% relative humidity. Venous blood collected before, after and 1.5 h after exercise was analysed for leukocyte distribution, phenotype and eHSP70. NK cell-enriched samples were examined for co-localization of CD94 and eHSP70 expression. Plasma eHSP-70 concentration was measured by ELISA. Subjects ran for approximately 50 min, which elicited a reversible leukocytosis. NK cell count increased 83% (p < 0.01) immediately after exercise, then decreased to 66% of the resting level 1.5 h after exercise (p < 0.05). Plasma eHSP concentration increased 167% after exercise and remained elevated (by up to 71%) 1.5 h after exercise (p < 0.01). eHSP was expressed on both NK cells and monocytes at all times; the count of NK cells positive for eHSP doubled from 0.04 +/- 0.02 10(9)/L (mean +/- SD) to 0.08 +/- 0.06 10(9)/L after exercise. In summary, exercise in the heat increased free plasma eHSP concentration, and the eHSP co-localized with CD94 on NK cells. These data confirm the link between exercise and activation of the innate immune system.

Exact and approximate Bayesian inference for low count time series models with intractable likelihoods

In this paper we present a new simulation methodology in order to obtain exact or approximate Bayesian inference for models for low-valued count time series data that have computationally demanding likelihood functions. The algorithm fits within the framework of particle Markov chain Monte Carlo (PMCMC) methods. The particle filter requires only model simulations and, in this regard, our approach has connections with approximate Bayesian computation (ABC). However, an advantage of using the PMCMC approach in this setting is that simulated data can be matched with data observed one-at-a-time, rather than attempting to match on the full dataset simultaneously or on a low-dimensional non-sufficient summary statistic, which is common practice in ABC. For low-valued count time series data we find that it is often computationally feasible to match simulated data with observed data exactly. Our particle filter maintains $N$ particles by repeating the simulation until $N+1$ exact matches are obtained. Our algorithm creates an unbiased estimate of the likelihood, resulting in exact posterior inferences when included in an MCMC algorithm. In cases where exact matching is computationally prohibitive, a tolerance is introduced as per ABC. A novel aspect of our approach is that we introduce auxiliary variables into our particle filter so that partially observed and/or non-Markovian models can be accommodated. We demonstrate that Bayesian model choice problems can be easily handled in this framework.

Count-min sketches for estimating password frequency within Hamming distance two

The count-min sketch is a useful data structure for recording and estimating the frequency of string occurrences, such as passwords, in sub-linear space with high accuracy. However, it cannot be used to draw conclusions on groups of strings that are similar, for example close in Hamming distance. This paper introduces a variant of the count-min sketch which allows for estimating counts within a specified Hamming distance of the queried string. This variant can be used to prevent users from choosing popular passwords, like the original sketch, but it also allows for a more efficient method of analysing password statistics.

Mining universities : can we count on the integrity of research coming out of today's mining-funded tertiary sector?

Australia's economic growth and national identity have been widely celebrated as being founded on the nation's natural resources. With the golden era of pastoralism fading into the distance, a renewed love affair with primary industries has been much lauded, particularly by purveyors of neoliberal ideology. The considerable wealth generated by resource extraction has, despite its environmental and social record, proved seductive to the university sector. The mining industry is one of a number of industries and sectors (alongside pharmaceutical, chemical and biotechnological) that is increasingly courting Australian universities. These new public-private alliances are often viewed as the much-needed cash cow to bridge the public funding shortfall in the tertiary sector. However, this trend also raises profound questions about the capacity of public good institutions, as universities were once assumed to be, to maintain institutional independence and academic freedoms.

Does counting still count? Revisiting the security of counting based user authentication protocols against statistical attacks

At NDSS 2012, Yan et al. analyzed the security of several challenge-response type user authentication protocols against passive observers, and proposed a generic counting based statistical attack to recover the secret of some counting based protocols given a number of observed authentication sessions. Roughly speaking, the attack is based on the fact that secret (pass) objects appear in challenges with a different probability from non-secret (decoy) objects when the responses are taken into account. Although they mentioned that a protocol susceptible to this attack should minimize this difference, they did not give details as to how this can be achieved barring a few suggestions. In this paper, we attempt to fill this gap by generalizing the attack with a much more comprehensive theoretical analysis. Our treatment is more quantitative which enables us to describe a method to theoretically estimate a lower bound on the number of sessions a protocol can be safely used against the attack. Our results include 1) two proposed fixes to make counting protocols practically safe against the attack at the cost of usability, 2) the observation that the attack can be used on non-counting based protocols too as long as challenge generation is contrived, 3) and two main design principles for user authentication protocols which can be considered as extensions of the principles from Yan et al. This detailed theoretical treatment can be used as a guideline during the design of counting based protocols to determine their susceptibility to this attack. The Foxtail protocol, one of the protocols analyzed by Yan et al., is used as a representative to illustrate our theoretical and experimental results.

Semiparametric estimation of count regression models

This paper develops a semiparametric estimation approach for mixed count regression models based on series expansion for the unknown density of the unobserved heterogeneity. We use the generalized Laguerre series expansion around a gamma baseline density to model unobserved heterogeneity in a Poisson mixture model. We establish the consistency of the estimator and present a computational strategy to implement the proposed estimation techniques in the standard count model as well as in truncated, censored, and zero-inflated count regression models. Monte Carlo evidence shows that the finite sample behavior of the estimator is quite good. The paper applies the method to a model of individual shopping behavior. © 1999 Elsevier Science S.A. All rights reserved.

A high cell count cascade full bridge converter for wide bandwidth ultrasonic transducer excitation

A nine level modular multilevel cascade converter (MMCC) based on four full bridge cells is shown driving a piezoelectric ultrasonic transducer at 71 and 39 kHz, in simulation and experimentally. The modular cells are small stackable PCBs, each with two fully integrated surface mount 22 V, 40 A MOSFET half-bridge converters, and include all control signal and power isolation. In this work, the bridges operate at 12 V and 384 kHz, to deliver a 96 Vpp 9 level waveform with an effective switching frequency of 3 MHz. A 9 pH air cored inductor forms a low pass filter in conjunction with the 3000 pF capacitance of the transducer load. Eight equally phase-displaced naturally sampled pulse width modulation (PWM) drive signals, along with the modulating sinusoid, are generated using phase accumulation techniques in a dedicated FPGA. Experimental time domain and FFT plots of the multilevel and transducer output waveforms are presented and discussed.