Performing legitimacy in neighbourhood planning:Conflicting identities and hybrid governance

Neighbourhood planning in the UK is a striking example of the international turn to localism and public participation, the statutory weight afforded to it setting it apart from many other initiatives. Its promoters portray it as a straightforward transfer of power from state to community. However, its legitimacy relies upon complex, hybrid forms of representative, participatory and epistemological authority. A growing literature is interrogating the relations between neighbourhood planning groups – the collectives utilising these new powers – and the neighbourhoods for which they speak. This paper brings empirical evidence forward to build on such work by exploring how the identities of neighbourhood planning groups are constituted. Three different and sometimes conflicting relational identities are characterised. Each identity is associated with particular material relations, types of knowledge and ways of representing the neighbourhood, and consequently produces different forms of legitimacy. Analysing identities in this way aids understanding of the practices through which legitimacy is achieved in experiments in democracy that rely on hybrid forms of authority. It may also open possibilities for intervention that speak to some of the concerns raised in the literature about these hybrid forms

Pre-Symmetry Sets of 3D shapes

The investigation of 3D euclidean symmetry sets (SS) and medial axis is an important area, due in particular to their various important applications. The pre-symmetry set of a surface M in 3-space (resp. smooth closed curve in 2D) is the set of pairs of points which contribute to the symmetry set, that is, the closure of the set of pairs of distinct points p and q in M, for which there exists a sphere (resp. a circle) tangent to M at p and at q. The aim of this paper is to address problems related to the smoothness and the singularities of the pre-symmetry sets of 3D shapes. We show that the pre-symmetry set of a smooth surface in 3-space has locally the structure of the graph of a function from R^2 to R^2, in many cases of interest.Comment: ACM-class: I.2; I.5; I.4; J.2. Latex, 3 grouped figures. The final version will appear in the proceedings of the First International Workshop on Deep Structure, Singularities and Computer Vision, Maastricht June 200

Deformable Registration through Learning of Context-Specific Metric Aggregation

We propose a novel weakly supervised discriminative algorithm for learning context specific registration metrics as a linear combination of conventional similarity measures. Conventional metrics have been extensively used over the past two decades and therefore both their strengths and limitations are known. The challenge is to find the optimal relative weighting (or parameters) of different metrics forming the similarity measure of the registration algorithm. Hand-tuning these parameters would result in sub optimal solutions and quickly become infeasible as the number of metrics increases. Furthermore, such hand-crafted combination can only happen at global scale (entire volume) and therefore will not be able to account for the different tissue properties. We propose a learning algorithm for estimating these parameters locally, conditioned to the data semantic classes. The objective function of our formulation is a special case of non-convex function, difference of convex function, which we optimize using the concave convex procedure. As a proof of concept, we show the impact of our approach on three challenging datasets for different anatomical structures and modalities.Comment: Accepted for publication in the 8th International Workshop on Machine Learning in Medical Imaging (MLMI 2017), in conjunction with MICCAI 201

Guidelines for Negotiating Scientific Collaboration

Whether it's sharing reagents with a laboratory on the other side of the world or working with the postdoc at the neighboring bench, some simple rules of collaboration might help

A regularized solution to edge detection

AbstractWe assume that edge detection is the task of measuring and localizing changes of light intensity in the image. As discussed by V. Torre and T. Poggio (1984), “On Edge Detection,” AI Memo 768, MIT AI Lab), edge detection, when defined in this way, is λ problem of numerical differentiation, which is ill posed. This paper shows that simple regularization methods lead to filtering the image prior to an appropriate differentiation operation. In particular, we prove (1) that the variational formulation of Tikhonov regularization leads to λ convolution filter, (2) that the form of this filter is similar to the Gaussian filter, and (3) that the regularizing parameter λ in the variational principle effectively controls the scale of the filter

VoGE: A Differentiable Volume Renderer using Gaussian Ellipsoids for Analysis-by-Synthesis

Differentiable rendering allows the application of computer graphics onvision tasks, e.g. object pose and shape fitting, via analysis-by-synthesis,where gradients at occluded regions are important when inverting the renderingprocess. To obtain those gradients, state-of-the-art (SoTA) differentiablerenderers use rasterization to collect a set of nearest components for eachpixel and aggregate them based on the viewing distance. In this paper, wepropose VoGE, which uses ray tracing to capture nearest components with theirvolume density distributions on the rays and aggregates via integral of thevolume densities based on Gaussian ellipsoids, which brings more efficient andstable gradients. To efficiently render via VoGE, we propose an approximateclose-form solution for the volume density aggregation and a coarse-to-finerendering strategy. Finally, we provide a CUDA implementation of VoGE, whichgives a competitive rendering speed in comparison to PyTorch3D. Quantitativeand qualitative experiment results show VoGE outperforms SoTA counterparts whenapplied to various vision tasks,e.g., object pose estimation, shape/texturefitting, and occlusion reasoning. The VoGE library and demos are available athttps://github.com/Angtian/VoGE.<br

Mapping the landscape of climate engineering.

In the absence of a governance framework for climate engineering technologies such as solar radiation management (SRM), the practices of scientific research and intellectual property acquisition can de facto shape the development of the field. It is therefore important to make visible emerging patterns of research and patenting, which we suggest can effectively be done using bibliometric methods. We explore the challenges in defining the boundary of climate engineering, and set out the research strategy taken in this study. A dataset of 825 scientific publications on climate engineering between 1971 and 2013 was identified, including 193 on SRM; these are analysed in terms of trends, institutions, authors and funders. For our patent dataset, we identified 143 first filings directly or indirectly related to climate engineering technologies-of which 28 were related to SRM technologies-linked to 910 family members. We analyse the main patterns discerned in patent trends, applicants and inventors. We compare our own findings with those of an earlier bibliometric study of climate engineering, and show how our method is consistent with the need for transparency and repeatability, and the need to adjust the method as the field develops. We conclude that bibliometric monitoring techniques can play an important role in the anticipatory governance of climate engineering

Replicated Bethe Free Energy: A Variational Principle behind Survey Propagation

A scheme to provide various mean-field-type approximation algorithms is presented by employing the Bethe free energy formalism to a family of replicated systems in conjunction with analytical continuation with respect to the number of replicas. In the scheme, survey propagation (SP), which is an efficient algorithm developed recently for analyzing the microscopic properties of glassy states for a fixed sample of disordered systems, can be reproduced by assuming the simplest replica symmetry on stationary points of the replicated Bethe free energy. Belief propagation and generalized SP can also be offered in the identical framework under assumptions of the highest and broken replica symmetries, respectively.Comment: appeared in Journal of the Physical Society of Japan 74, 2133-2136 (2005