Range of validity of weakly non-linear theory in Rayleigh-Bénard convection

In this paper we examine the equilibrium states of periodic finite amplitude flow in a horizontal channel with differential heating between the two rigid boundaries. The solutions to the Navier-Stokes equations are obtained by means of a perturbation method for evaluating the Landau coefficients and through a Newton-Raphson iterative method that results from the Fourier expansion of the solutions that bifurcate above the linear stability threshold of infini- tesimal disturbances. The results obtained from these two different methods of evaluating the convective flow are compared in the neighbourhood of the critical Rayleigh number. We find that for small Prandtl numbers the discrepancy of the two methods is noticeable.

Automatic processing, quality assurance and serving of real-time weather data

Recent advances in technology have produced a significant increase in the availability of free sensor data over the Internet. With affordable weather monitoring stations now available to individual meteorology enthusiasts a reservoir of real time data such as temperature, rainfall and wind speed can now be obtained for most of the United States and Europe. Despite the abundance of available data, obtaining useable information about the weather in your local neighbourhood requires complex processing that poses several challenges. This paper discusses a collection of technologies and applications that harvest, refine and process this data, culminating in information that has been tailored toward the user. In this case we are particularly interested in allowing a user to make direct queries about the weather at any location, even when this is not directly instrumented, using interpolation methods. We also consider how the uncertainty that the interpolation introduces can then be communicated to the user of the system, using UncertML, a developing standard for uncertainty representation.

Retail competition and consumer choice:contextualising the “food deserts” debate

The “food deserts” debate can be enriched by setting the particular circumstances of food deserts – areas of very limited consumer choice – within a wider context of changing retail provision in other areas. This paper’s combined focus on retail competition and consumer choice shifts the emphasis from changing patterns of retail provision towards a more qualitative understanding of how “choice” is actually experienced by consumers at the local level “on the ground”. This argument has critical implications for current policy debates where the emphasis on monopolies and mergers at the national level needs to be brought together with the planning and regulation of retail provision at the local, neighbourhood level.

The influence of newer member states in the European Union:the case of Poland and the Eastern partnership

This article seeks to examine and assess the role of Poland in the early stages of the making of the Eastern Partnership of the European Union. First, it briefly reviews Poland's aims and ambitions with regard to the European Union's policy towards its eastern neighbours, both before and since it joined the European Union in 2004. Second, it describes and analyses the Eastern Partnership, including its added value for the European Neighbourhood Policy. Third, it draws on a range of interviews carried out by the authors in Brussels and Warsaw on Poland's role in the initial formation of the Eastern Partnership, as seen by its partners in the other member states and European institutions. In addition, it seeks to unpack some of the early stage lessons learnt by the Polish government about how best to achieve its ambitions in the European Union, and notes the remaining weaknesses of the Polish administration, particularly in the area of administrative capacity. © 2013 University of Glasgow.

Socio-economic vision graph generation and handover in distributed smart camera networks

In this article we present an approach to object tracking handover in a network of smart cameras, based on self-interested autonomous agents, which exchange responsibility for tracking objects in a market mechanism, in order to maximise their own utility. A novel ant-colony inspired mechanism is used to learn the vision graph, that is, the camera neighbourhood relations, during runtime, which may then be used to optimise communication between cameras. The key benefits of our completely decentralised approach are on the one hand generating the vision graph online, enabling efficient deployment in unknown scenarios and camera network topologies, and on the other hand relying only on local information, increasing the robustness of the system. Since our market-based approach does not rely on a priori topology information, the need for any multicamera calibration can be avoided. We have evaluated our approach both in a simulation study and in network of real distributed smart cameras.

An examination of the determinants of entrepreneurship at the regional level:the case of East Midlands region

Despite the importance of new firms to the economy, determinants of start-ups have mainly been examined at a country level and discussion of regional entrepreneurial activity has received less attention. Since there are significant variations in entrepreneurship rates across and within countries, such an investigation at a regional level would help in gaining an in depth understanding of the impact of the individual level resource endowments and neighbourhood characteristics on an individual’s decision to engage in entrepreneurial activity. The main aim of the thesis is to explore various theories of entrepreneurship and develop integrated frameworks for examining the determinants of entrepreneurial activity at a neighbourhood level in the East Midlands region in England. The specific objectives of the thesis are to examine how the individual level resources and the neighbourhood characteristics: (i) combine to influence an individual to engage in the different stages of the entrepreneurial process, (ii) influence natives and migrants to engage in start up activity and (iii) influence women and men to become self-employed and ambitious entrepreneurs. In terms of the methodology, the empirical analysis is based on two databases combined: 2006 to 2009 GEM East Midlands region and the English Index of Multiple Deprivation dataset. Based on the critical review of the literature on entrepreneurship the thesis develop theoretical frameworks which led to formulate hypotheses related to the differentiated impact of both individual and neighbourhood level factors on the propensity of an individual to be involved in entrepreneurial activity. The findings indicate that the determinants of entrepreneurial activity vary with human, financial and the local environment factors affecting the entrepreneurial process. Finally, the thesis calls for caution when developing and applying generic and specific policy measures aimed at promoting entry into entrepreneurship.

Experiences of families living in Kingshurst, North Solihull

This report sets out findings of a rapid-ethnographic research project commissioned by The Children’s Society and conducted by a research team from Aston University into the experiences of families living in Kingshurst – a neighbourhood within the metropolitan borough of Solihull in the West Midlands.

Plant closures and taskforce responses:an analysis of the impact of and policy response to MG Rover in Birmingham

This paper explores the socio-economic impacts and associated policy responses to the collapse of MG Rover at Longbridge in Birmingham. Critically, it attempts to move beyond a ‘standard’ taskforce narrative that emphasizes the role of the regional response. While recognizing that significant policy ‘successes’ were indeed evident at the regional level in anticipating and responding to the crisis, a wider perspective is required that situates this taskforce response in (1) a fuller understanding of labour market precariousness (that in turn mitigates some of its policy ‘successes’), and (2) more local perspectives that highlight the local impacts of closure, the role of the neighbourhood level officials and the third sector in mediating these. Taking this broader perspective suggests that longer-term, workers face a precarious situation and the need for policies to create and sustain ‘good quality’ jobs remains paramount. Adding in more local perspectives, a key lesson from the Longbridge experience for dealing with closures more generally is that the public policy responses must be: multidimensional in that they transcend narrow sector-based concerns and addresses broader spatial impacts; inclusive in that they build on a broad coalition of economic and social stakeholders; and long-term in that they acknowledge that adaptation takes many years. If anything, the Birmingham Longbridge experience demonstrates the difficulty of achieving such responses in the context of crisis where action is imperative and deliberation a luxury.

"Belonging” in the gentrified Golden Horn/Halic neighbourhoods of Istanbul

Mainstream gentrification research predominantly examines experiences and motivations of the middle-class gentrifier groups, while overlooking experiences of non-gentrifying groups including the impact of in situ local processes on gentrification itself. In this paper, I discuss gentrification, neighbourhood belonging and spatial distribution of class in Istanbul by examining patterns of belonging both of gentrifiers and non-gentrifying groups in historic neighbourhoods of the Golden Horn/Halic. I use multiple correspondence analysis (MCA), a methodology rarely used in gentrification research, to explore social and symbolic borders between these two groups. I show how gentrification leads to spatial clustering by creating exclusionary practices and eroding social cohesion, and illuminate divisions that are inscribed into the physical space of the neighbourhood.

Probabilistic topographic information visualisation

The focus of this thesis is the extension of topographic visualisation mappings to allow for the incorporation of uncertainty. Few visualisation algorithms in the literature are capable of mapping uncertain data with fewer able to represent observation uncertainties in visualisations. As such, modifications are made to NeuroScale, Locally Linear Embedding, Isomap and Laplacian Eigenmaps to incorporate uncertainty in the observation and visualisation spaces. The proposed mappings are then called Normally-distributed NeuroScale (N-NS), T-distributed NeuroScale (T-NS), Probabilistic LLE (PLLE), Probabilistic Isomap (PIso) and Probabilistic Weighted Neighbourhood Mapping (PWNM). These algorithms generate a probabilistic visualisation space with each latent visualised point transformed to a multivariate Gaussian or T-distribution, using a feed-forward RBF network. Two types of uncertainty are then characterised dependent on the data and mapping procedure. Data dependent uncertainty is the inherent observation uncertainty. Whereas, mapping uncertainty is defined by the Fisher Information of a visualised distribution. This indicates how well the data has been interpolated, offering a level of ‘surprise’ for each observation. These new probabilistic mappings are tested on three datasets of vectorial observations and three datasets of real world time series observations for anomaly detection. In order to visualise the time series data, a method for analysing observed signals and noise distributions, Residual Modelling, is introduced. The performance of the new algorithms on the tested datasets is compared qualitatively with the latent space generated by the Gaussian Process Latent Variable Model (GPLVM). A quantitative comparison using existing evaluation measures from the literature allows performance of each mapping function to be compared. Finally, the mapping uncertainty measure is combined with NeuroScale to build a deep learning classifier, the Cascading RBF. This new structure is tested on the MNist dataset achieving world record performance whilst avoiding the flaws seen in other Deep Learning Machines.

Can mean shift trackers perform better?

Many tracking algorithms have difficulties dealing with occlusions and background clutters, and consequently don't converge to an appropriate solution. Tracking based on the mean shift algorithm has shown robust performance in many circumstances but still fails e.g. when encountering dramatic intensity or colour changes in a pre-defined neighbourhood. In this paper, we present a robust tracking algorithm that integrates the advantages of mean shift tracking with those of tracking local invariant features. These features are integrated into the mean shift formulation so that tracking is performed based both on mean shift and feature probability distributions, coupled with an expectation maximisation scheme. Experimental results show robust tracking performance on a series of complicated real image sequences. © 2010 IEEE.