Machine Learning and the Future of Realism

The preceding three decades have seen the emergence, rise, and proliferation of machine learning (ML). From half-recognised beginnings in perceptrons, neural nets, and decision trees, algorithms that extract correlations (that is, patterns) from a set of data points have broken free from their origin in computational cognition to embrace all forms of problem solving, from voice recognition to medical diagnosis to automated scientific research and driverless cars, and it is now widely opined that the real industrial revolution lies less in mobile phone and similar than in the maturation and universal application of ML. Among the consequences just might be the triumph of anti-realism over realism

How can I encourage multi-stakeholder narrative and reflection on the use of ICT in Teacher Professional Development programmes in Rwanda?

This is an action research enquiry into how I can improve my practice to encourage multi-stakeholder narrative and reflection on the use of Information and Communication Technology (ICT) in Teacher Professional Development (TPD) programmes in Rwanda. I examine the complexity of the ICT-TPD landscape in the Africa Region. I describe two action research cycles in which I attempt to encourage reflection on ICT in professional development in Rwanda. In each cycle I explore the potential of an Activity Theory lens for probing the issues and examining the perspectives of the stakeholder community of teachers, teacher educators, curriculum developers and researchers affiliated to national ICT in TPD programmes and initiatives. I integrate a “Most Significant Change” narrative technique to engage participants in telling stories of significant change in their practice with technology integration. Through the rigour of the action research living theory approach I come to a number of conclusions about my own values and how I actually live my values in practice as I engage with partners in discourse and reflection for mutual learning on the issues of ICT integration in Teacher Professional Development

The Applicability of Nonlinear Systems Dynamics Chaos Measures to Cardiovascular Physiology Variables

Three measures of nonlinear chaos (fractal dimension, Approximate Entropy (ApEn), and Lyapunov exponents) were studied as potential measures of cardiovascular condition. It is suggested that these measures have potential in the assessment of cardiovascular condition in environments of normal cardiovascular stress (normal gravity on the Earth surface), cardiovascular deconditioning (microgravity of space), and increased cardiovascular stress (lower body negative pressure (LBNP) treatments)

Combining Functional Data Registration and Factor Analysis

We extend the definition of functional data registration to encompass a larger class of registered functions. In contrast to traditional registration models, we allow for registered functions that have more than one primary direction of variation. The proposed Bayesian hierarchical model simultaneously registers the observed functions and estimates the two primary factors that characterize variation in the registered functions. Each registered function is assumed to be predominantly composed of a linear combination of these two primary factors, and the function-specific weights for each observation are estimated within the registration model. We show how these estimated weights can easily be used to classify functions after registration using both simulated data and a juggling data set.Comment: The paper was updated with a better real data exampl