Fusion of finite set distributions: Pointwise consistency and global cardinality

A recent trend in distributed multi-sensor fusion is to use random finite set filters at the sensor nodes and fuse the filtered distributions algorithmically using their exponential mixture densities (EMDs). Fusion algorithms which extend the celebrated covariance intersection and consensus based approaches are such examples. In this article, we analyse the variational principle underlying EMDs and show that the EMDs of finite set distributions do not necessarily lead to consistent fusion of cardinality distributions. Indeed, we demonstrate that these inconsistencies may occur with overwhelming probability in practice, through examples with Bernoulli, Poisson and independent identically distributed (IID) cluster processes. We prove that pointwise consistency of EMDs does not imply consistency in global cardinality and vice versa. Then, we redefine the variational problems underlying fusion and provide iterative solutions thereby establishing a framework that guarantees cardinality consistent fusion.Comment: accepted for publication in the IEEE Transactions on Aerospace and Electronics System

Assimilating Seizure Dynamics

Observability of a dynamical system requires an understanding of its state—the collective values of its variables. However, existing techniques are too limited to measure all but a small fraction of the physical variables and parameters of neuronal networks. We constructed models of the biophysical properties of neuronal membrane, synaptic, and microenvironment dynamics, and incorporated them into a model-based predictor-controller framework from modern control theory. We demonstrate that it is now possible to meaningfully estimate the dynamics of small neuronal networks using as few as a single measured variable. Specifically, we assimilate noisy membrane potential measurements from individual hippocampal neurons to reconstruct the dynamics of networks of these cells, their extracellular microenvironment, and the activities of different neuronal types during seizures. We use reconstruction to account for unmeasured parts of the neuronal system, relating micro-domain metabolic processes to cellular excitability, and validate the reconstruction of cellular dynamical interactions against actual measurements. Data assimilation, the fusing of measurement with computational models, has significant potential to improve the way we observe and understand brain dynamics

Enhancing Participatory Strategies With Designerly Ways for Sociolegal Impact: Lessons From Research Aimed at Making Hate Crime Visible

This paper draws the attention of impact-curious sociolegal researchers to the potential of participatory research strategies; and proposes that the effectiveness of those strategies can be enhanced by the introduction of ‘designerly ways’. It explores and evidences this proposition through the multi-country Facing All the Facts project which aimed to support and accelerate the process of making hate crime conceptually and empirically visible in Europe. The paper concludes that by pursuing the designerly strategy of making experiences, perceptions and expectations around hate crime reporting and recording visible and tangible in artefacts (formal graphics and collaborative prototypes), the project activities generated structured-yet-free spaces in which publics/stakeholders could more effectively participate in practical, critical and imaginative discussion about how things are, and how they might be; and that this has improved the relevance and rigour of the research, and its ability to generate meaningful change (‘impact’)