Electrophysiological responses to violations of expectation from eye gaze and arrow cues

Isolating processes within the brain that are specific to human behavior is a key goal for social neuroscience. The current research was an attempt to test whether recent findings of enhanced negative ERPs in response to unexpected human gaze are unique to eye gaze stimuli by comparing the effects of gaze cues with the effects of an arrow cue. ERPs were recorded while participants (N¼30) observed a virtual actor or an arrow that gazed (or pointed) either toward (object congruent) or away from (object incongruent) a flashing checkerboard. An enhanced negative ERP (N300) in response to object incongruent compared to object congruent trials was recorded for both eye gaze and arrow stimuli. The findings are interpreted as reflecting a domain general mechanism for detecting unexpected events.

The quik fix study : a randomised controlled trial of brief interventions for young people with alcohol-related injuries and illnesses accessing emergency department and crisis support care

Background: Alcohol is a major preventable cause of injury, disability and death in young people. Large numbers of young people with alcohol-related injuries and medical conditions present to hospital emergency departments (EDs). Access to brief, efficacious, accessible and cost effective treatment is an international health priority within this age group. While there is growing evidence for the efficacy of brief motivational interviewing (MI) for reducing alcohol use in young people, there is significant scope to increase its impact, and determine if it is the most efficacious and cost effective type of brief intervention available. The efficacy of personality-targeted interventions (PIs) for alcohol misuse delivered individually to young people is yet to be determined or compared to MI, despite growing evidence for school-based PIs. This study protocol describes a randomized controlled trial comparing the efficacy and cost-effectiveness of telephone-delivered MI, PI and an Assessment Feedback/Information (AF/I) only control for reducing alcohol use and related harm in young people. Methods/design: Participants will be 390 young people aged 16 to 25 years presenting to a crisis support service or ED with alcohol-related injuries and illnesses (including severe alcohol intoxication). This single blinded superiority trial randomized young people to (i) 2 sessions of MI; (ii) 2 sessions of a new PI or (iii) a 1 session AF/I only control. Participants are reassessed at 1, 3, 6 and 12 months on the primary outcomes of alcohol use and related problems and secondary outcomes of mental health symptoms, functioning, severity of problematic alcohol use, alcohol injuries, alcohol-related knowledge, coping self-efficacy to resist using alcohol, and cost effectiveness. Discussion: This study will identify the most efficacious and cost-effective telephone-delivered brief intervention for reducing alcohol misuse and related problems in young people presenting to crisis support services or EDs. We expect efficacy will be greatest for PI, followed by MI, and then AF/I at 1, 3, 6 and 12 months on the primary and secondary outcome variables. Telephone-delivered brief interventions could provide a youth-friendly, accessible, efficacious, cost-effective and easily disseminated treatment for addressing the significant public health issue of alcohol misuse and related harm in young people. Trial registration: This trial is registered with the Australian and New Zealand Clinical Trials Registry ACTRN12613000108718.

Teachers’ beliefs about the possibilities and limitations of digital games in classrooms

Teachers’ beliefs about what it is (or is not) possible to achieve with digital games in educational contexts will inevitably influence the decisions that they make about how, when, and for what specific purposes they will bring these games into their classrooms. They play a crucial role in both shaping and responding to the complex contextual factors which influence how games are understood and experienced in educational settings. Throughout this article the authors draw upon data collected for a large-scale, mixed-methods research project focusing on literacy, learning and teaching with digital games in Australian classrooms, to focus explicitly on the attitudes,understandings and expectations held about digital games by diverse teachers at the beginning of the project. They seek to identify the beliefs about games that motivated teachers’ participation in a digital games research project while focusing, as well, on concerns that teachers express about risks or limitations of such a project. The authors’ aim is to develop a detailed picture of the mindsets that teachers bring to games-based learning environments, and the relevance of these mindsets to broader debates about the relationship between games, learning and school.

Reply by authors to J.C. Wilcox

This is a reply to "Comment on 'Online Estimation of Allan Variance Parameters' " by James C.Wilcox published in JOURNAL OF GUIDANCE, CONTROL, AND DYNAMICS Vol. 24, No. 3, May–June 2001. OUR statement “Modern gyros provide angular rate measurements directly, and hence, angular quantization is meaningless” made in the original paper should first be read with the accompanying sentences in the paragraph. The meaning of the sentence would perhaps have been clearer if written". . .

Online estimation of Allan variance parameters

A new online method is presented for estimation of the angular randomwalk and rate randomwalk coefficients of inertial measurement unit gyros and accelerometers. In the online method, a state-space model is proposed, and recursive parameter estimators are proposed for quantities previously measured from offline data techniques such as the Allan variance method. The Allan variance method has large offline computational effort and data storage requirements. The technique proposed here requires no data storage and computational effort of approximately 100 calculations per data sample.

Adaptive estimation of HMM transition probabilities

This paper presents new schemes for recursive estimation of the state transition probabilities for hidden Markov models (HMM's) via extended least squares (ELS) and recursive state prediction error (RSPE) methods. Local convergence analysis for the proposed RSPE algorithm is shown using the ordinary differential equation (ODE) approach developed for the more familiar recursive output prediction error (RPE) methods. The presented scheme converges and is relatively well conditioned compared with the ...

On adaptive HMM state estimation

In this paper new online adaptive hidden Markov model (HMM) state estimation schemes are developed, based on extended least squares (ELS) concepts and recursive prediction error (RPE) methods. The best of the new schemes exploit the idempotent nature of Markov chains and work with a least squares prediction error index, using a posterior estimates, more suited to Markov models then traditionally used in identification of linear systems.

Adaptive estimation of hidden semi-Markov chains with parameterised transition probabilities and exponential decaying states

This paper develops maximum likelihood (ML) estimation schemes for finite-state semi-Markov chains in white Gaussian noise. We assume that the semi-Markov chain is characterised by transition probabilities of known parametric from with unknown parameters. We reformulate this hidden semi-Markov model (HSM) problem in the scalar case as a two-vector homogeneous hidden Markov model (HMM) problem in which the state consist of the signal augmented by the time to last transition. With this reformulation we apply the expectation Maximumisation (EM ) algorithm to obtain ML estimates of the transition probabilities parameters, Markov state levels and noise variance. To demonstrate our proposed schemes, motivated by neuro-biological applications, we use a damped sinusoidal parameterised function for the transition probabilities.

Optimal HMM processing of differentially phase modulated communication systems

This paper investigates demodulation of differentially phase modulated signals DPMS using optimal HMM filters. The optimal HMM filter presented in the paper is computationally of order N3 per time instant, where N is the number of message symbols. Previously, optimal HMM filters have been of computational order N4 per time instant. Also, suboptimal HMM filters have be proposed of computation order N2 per time instant. The approach presented in this paper uses two coupled HMM filters and exploits knowledge of ...

Reduced complexity on-line estimation of hidden Markov model parameters

In this paper we propose and study low complexity algorithms for on-line estimation of hidden Markov model (HMM) parameters. The estimates approach the true model parameters as the measurement noise approaches zero, but otherwise give improved estimates, albeit with bias. On a nite data set in the high noise case, the bias may not be signi cantly more severe than for a higher complexity asymptotically optimal scheme. Our algorithms require O(N3) calculations per time instant, where N is the number of states. Previous algorithms based on earlier hidden Markov model signal processing methods, including the expectation-maximumisation (EM) algorithm require O(N4) calculations per time instant.

Faster parameter estimation using risk-sensitive filters

In this paper, we propose a risk-sensitive approach to parameter estimation for hidden Markov models (HMMs). The parameter estimation approach considered exploits estimation of various functions of the state, based on model estimates. We propose certain practical suboptimal risk-sensitive filters to estimate the various functions of the state during transients, rather than optimal risk-neutral filters as in earlier studies. The estimates are asymptotically optimal, if asymptotically risk neutral, and can give significantly improved transient performance, which is a very desirable objective for certain engineering applications. To demonstrate the improvement in estimation simulation studies are presented that compare parameter estimation based on risk-sensitive filters with estimation based on risk-neutral filters.

On-line estimation of Allan variance parameters

A new online method is presented for estimation of the angular random walk and rate random walk coefficients of IMU (inertial measurement unit) gyros and accelerometers. The online method proposes a state space model and proposes parameter estimators for quantities previously measured from off-line data techniques such as the Allan variance graph. Allan variance graphs have large off-line computational effort and data storage requirements. The technique proposed here requires no data storage and computational effort of O(100) calculations per data sample.

Optimal HMM filtering and decision feedback equalisation for differential encoded transmission systems

In this paper conditional hidden Markov model (HMM) filters and conditional Kalman filters (KF) are coupled together to improve demodulation of differential encoded signals in noisy fading channels. We present an indicator matrix representation for differential encoded signals and the optimal HMM filter for demodulation. The filter requires O(N3) calculations per time iteration, where N is the number of message symbols. Decision feedback equalisation is investigated via coupling the optimal HMM filter for estimating the message, conditioned on estimates of the channel parameters, and a KF for estimating the channel states, conditioned on soft information message estimates. The particular differential encoding scheme examined in this paper is differential phase shift keying. However, the techniques developed can be extended to other forms of differential modulation. The channel model we use allows for multiplicative channel distortions and additive white Gaussian noise. Simulation studies are also presented.

Looming aircraft threats : shape-based passive ranging of aircraft from monocular vision

This paper proposes new techniques for aircraft shape estimation, passive ranging, and shape-adaptive hidden Markov model filtering which are suitable for a monocular vision-based non-cooperative collision avoidance system. Vision-based passive ranging is an important missing technology that could play a significant role in resolving the sense-and-avoid problem in un-manned aerial vehicles (UAVs); a barrier hindering the wider adoption of UAVs for civilian applications. The feasibility of the pro- posed shape estimation, passive ranging and shape-adaptive filtering techniques is evaluated on flight test data.

Foundations for the future : A long-term plan for Australian ecosystem science

Abstract: Australia’s ecosystems are the basis of our current and future prosperity, and our national well-being.A strong and sustainable Australian ecosystem science enterprise is vital for understanding and securing these ecosystems in the face of current and future challenges. This Plan defines the vision and key directions for a national ecosystem science capability that will enable Australia to understand and effectively manage its ecosystems for decades to come.The Plan’s underlying theme is that excellent science supports a range of activities, including public engagement, that enable us to understand and maintain healthy ecosystems.Those healthy ecosystems are the cornerstone of our social and economic well-being.The vision guiding the development of this Plan is that in 20 years’ time the status of Australian ecosystems and how they change will be widely reported and understood, and the prosperity and well-being they provide will be secure. To enable this, Australia’s national ecosystem science capability will be coordinated, collaborative and connected.The Plan is based on an extensive set of collaboratively generated proposals from national town hall meetings that also formthe basis for its implementation. Some directions within the Plan are for the Australian ecosystem science community itself to implement, others will involve the users of ecosystem science and the groups that fund ecosystem science.We identify six equal priority areas for action to achieve our vision: (i) delivering maximum impact for Australia: enhancing relationships between scientists and end-users; (ii) supporting long-termresearch; (iii) enabling ecosystem surveillance; (iv) making the most of data resources; (v) inspiring a generation: empowering the public with knowledge and opportunities; (vi) facilitating coordination, collaboration and leadership. This shared vision will enable us to consolidate our current successes, overcome remaining barriers and establish the foundations to ensure Australian ecosystem science delivers for the future needs of Australia..