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Transport authorities rely on pavement characteristics to determine a pavement condition rating index. However, manually computing ratings can be a tedious, subjective, time-consuming, and training-intensive process. This paper presents a deep-learning framework for automatically rating the condition of rural road pavements using digital images captured from a dashboard-mounted camera. The framework includes pavement segmentation, data cleaning, image cropping and resizing, and pavement condition rating classification. A dataset of images, captured from diverse roads in Ireland and rated by two expert raters using the pavement surface condition index (PSCI) scale, was created. Deep-learning models were developed to perform pavement segmentation and condition rating classification. The automated PSCI rating achieved an average Cohen Kappa score and F1-score of 0.9 and 0.85, respectively, across 1–10 rating classes on an independent test set. The incorporation of unique image augmentation during training enabled the models to exhibit increased robustness against variations in background and clutter. • A deep-learning framework for automatic pavement condition rating for roads is presented. • Our proposed framework consists of segmentation, cleaning, resizing and classification. • A large open dataset of real-world images captured from regional and local roads in Ireland. • Images are labelled by expert data analysts using PSCI rating scale used in Ireland. • The unique augmentation enabled the models to be more robust to changes in background. [ABSTRACT FROM AUTHOR]

This article presents findings from a study of African immigration to Ireland. Set against a background description of who these recent immigrants are and why they come, this research, based primarily in a Dublin maternity hospital, looks at the experiences of pregnant and post-partal African women to explore questions surrounding use of maternity services and their relationship to larger issues of integration into Irish society. This gendered segment of the population is of particular interest, as the phenomenon of Irish-born children to non-national parents has been a lightning rod issue in immigration debates in Ireland, leading to a June 2004 referendum limiting access to citizenship by birth in unprecedented ways. Ireland, long a country characterized by emigration, only recently transitioned to a nation of net immigration, and, as such, is grappling with the implications of its rapidly changing ethnic make-up in questions of race and racism, allocation of social welfare entitlements, and effective health and human services delivery. Through this exploration of the phenomenon of inscribing immigration debates on African women’s bodies, this article highlights racism, family reunification, the right to work, and the lengthy process of adjudicating immigration claims as significant obstacles to integration into Irish society. Through this analysis, this article also provides empirical data that feed into ongoing debates about the meaning of “African diaspora.” [ABSTRACT FROM AUTHOR]