A review of hough transform and line segment detection approaches

In a wide range of image processing and computer vision problems, line segment detection is one of the most critical challenges. For more than three decades researchers have contributed to build more robust and accurate algorithms with faster performance. In this paper we review the main approaches and in particular the Hough transform and its extensions, which are among the most well-known techniques for the detection of straight lines in a digital image. This paper is based on extensive practical research and is organised into two main parts. In the first part, the HT and its major research directions and limitations are discussed. In the second part of the paper, state-of-the-art line segmentation techniques are reviewed and categorized into three main groups with fundamentally distinctive characteristics. Their relative advantages and disadvantages are compared and summarised in a table

Alley Greening: A Tool for Enhancing Community Resilience?

In many cities across the world alleys are transitioning from residual spaces to hybrid places providing the foundation for new functions, uses, and identities to take root and coincide through a process of “alley greening”. Such manifestations are transforming the relationship between people (local residents) and place (alleyway–local area), most notably during the COVID-19 pandemic when a new urgency for the provision, or repurposing, of safe, social spaces emerged. Yet, the potential of alley greening to affect people-place relationships and engender community resilience has been relatively unexplored. Adopting a mixed-methods approach, including questionnaires, interviews, and case study analyses, this paper critically investigates the experience and perspectives of green alleys from various place-based actors in Belfast, Northern Ireland. The findings reveal that, even in the absence of institutional and policy support, green alley projects have the potential to stimulate positive people-place relationships in various ways and enhance wider community resilience to shocks and stresses. However, barriers prevail, curtailing the reach and purpose of such projects both in Belfast and elsewhere. The paper considers how governance arrangements might best overcome such hurdles and strengthen pro-environmental and pro-social behaviours that are fundamental to community resilience. Key policy highlights Despite their integral form and function in the city, alleyways, nor their potential, are rarely recognised in the policy. The COVID-19 pandemic exposed a policy-implementation gap in the provision of locally accessible greenspace. Policy inertia exacerbated this gap preventing the fulfilment of changing community needs. Alley greening emerged as a tactical urban response. A lack of place-based approaches within policy has polarised institutions from communities. People-place relationships, essential to resilience-building and green alley longevity, are subsequently inadequately engaged with and fostered. An opportunity exists for alley greening to be a place-based policy instrument to stimulate pro-social and pro-environmental behaviours for building community resilience.</p

Stepped wedge cluster randomised trials: a review of the statistical methodology used and available

Background: Previous reviews have focussed on the rationale for employing the stepped wedge design (SWD), the areas of research to which the design has been applied and the general characteristics of the design. However these did not focus on the statistical methods nor addressed the appropriateness of sample size methods used.This was a review of the literature of the statistical methodology used in stepped wedge cluster randomised trials. Methods: Literature Review. The Medline, Embase, PsycINFO, CINAHL and Cochrane databases were searched for methodological guides and RCTs which employed the stepped wedge design. Results: This review identified 102 trials which employed the stepped wedge design compared to 37 from the most recent review by Beard et al. 2015. Forty six trials were cohort designs and 45 % (n = 46) had fewer than 10 clusters. Of the 42 articles discussing the design methodology 10 covered analysis and seven covered sample size. For cohort stepped wedge designs there was only one paper considering analysis and one considering sample size methods. Most trials employed either a GEE or mixed model approach to analysis (n = 77) but only 22 trials (22 %) estimated sample size in a way which accounted for the stepped wedge design that was subsequently used. Conclusions: Many studies which employ the stepped wedge design have few clusters but use methods of analysis which may require more clusters for unbiased and efficient intervention effect estimates. There is the need for research on the minimum number of clusters required for both types of stepped wedge design. Researchers should distinguish in the sample size calculation between cohort and cross sectional stepped wedge desi

The Octagon Values Model: community resilience and coastal regeneration

This paper considers efforts to build community resilience through bottom-up responses to socioeconomic and environmental change in coastal communities on the island of Ireland. The discussion adds to a growing body of research which suggests that regeneration initiatives which do not consider a community’s resilience to change will fail to catalyse the changes needed to put that place on a more sustainable trajectory. The Octagon Values Model is presented as a heuristic device for exploring this potentially complimentary and co-influencing relationship between regeneration and resilience building. When applied to two case studies of coastal Transition Towns, the Model illustrates how, in practical terms, resilience may be used to tap into personal concerns to mobilise civil engagement in specific local regeneration initiatives. The discussion highlights some of the perennial practical obstacles confronting voluntary-based, community-level activities which raise questions for the generation of proactive community resilience responses and modes of governance. In capturing environmental, economic, social and governance value domains, the Octagon Values Model illustrates that reconciling values and resource use is critical to both regeneration and resilience ambitions

Models for discrete epidemiological and clinical data

Discrete data, often known as frequency or count data, comprises of observations which can only take certain separate values, resulting in a more restricted numerical measurement than those provided by continuous data and are common in the clinical sciences and epidemiology. The Poisson distribution is the simplest and most common probability model for discrete data with observations assumed to have a constant rate of occurrence amongst individual units with the property of equal mean and variance. However, in many applications the variance is greater than the mean and overdispersion is said to be present. The application of the Poisson distribution to data exhibiting overdispersion can lead to incorrect inferences and/or inefficient analyses. The most commonly used extension of the Poisson distribution is the negative binomial distribution which allows for unequal mean and variance, but may still be inadequate to model datasets with long tails and/or value-inflation. Further extensions such as Delaporte, Sichel, Gegenbauer and Hermite distributions, give greater flexibility than the negative binomial distribution. These models have received less interest than the Poisson and negative binomial distributions within the statistical literature and many have not been implemented in current statistical software. Also, diagnostics and goodness-of-fit statistics are seldom considered when analysing such datasets. The aim of this thesis is to develop software for analysing discrete data which do not follow the Poisson or negative binomial distributions including component-mix and parameter-mix distributions, value-inflated models, as well as modifications for truncated distributions. The project’s main goals are to create three libraries within the framework of the R project for statistical computing. They are: 1. altmann: to fit and compare a wide range of univariate discrete models 2. discrete.diag: to provide goodness-of-fit and outlier detection diagnostics for these models 3. discrete.reg: to fit regression models to discrete response variables within the gamlss framework These libraries will be freely available to the clinical and scientific community to facilitate discrete data interpretation

Brexit: surname diversity and voting patterns

An interesting by‐product of the UK's referendum on membership of the EU (page 4) has been the wide variety of excellent data analyses and visualisations to explain and add context to the results (see bit.ly/29W7Glx, for example). However, one of the few aspects that has not been analysed is how surname diversity in districts relates to referendum voting patterns. Surname distributions are increasingly used in geography, for example, to characterise cultural regions. There are, however, few studies analysing the associations between surname distributions and voting patterns. This is what we set out to do here, using data on surnames and locations from the 2001 UK electoral register and the results of the EU referendum (bit.ly/29W8tCR)