The Performing Arts in (North of) England

This mapping, commissioned specially for IETM Plenary Meeting in Hull, UK, offers an in-depth overview of the performing arts scene in the North of England, where possible focusing on inclusive practices. The publication explores the Northern culture and examines some of the geographical, historical and economic forces that helped shape Northern England. It also takes you on a journey through the venues, the festivals and the companies that live, work and play in the region, and looks at key organisations, artists and themes

Imitating Driver Behavior with Generative Adversarial Networks

The ability to accurately predict and simulate human driving behavior is critical for the development of intelligent transportation systems. Traditional modeling methods have employed simple parametric models and behavioral cloning. This paper adopts a method for overcoming the problem of cascading errors inherent in prior approaches, resulting in realistic behavior that is robust to trajectory perturbations. We extend Generative Adversarial Imitation Learning to the training of recurrent policies, and we demonstrate that our model outperforms rule-based controllers and maximum likelihood models in realistic highway simulations. Our model both reproduces emergent behavior of human drivers, such as lane change rate, while maintaining realistic control over long time horizons.Comment: 8 pages, 6 figure

Determinants of a digital divide in Sub-Saharan Africa : a spatial econometric analysis of cell phone coverage

Most discussions of the digital divide treat it as a"North-South"issue, but the conventional dichotomy doesn't applyto cell phones in Sub-Saharan Africa. Although almost all Sub-Saharan countries are poor by international standards, they exhibit great disparities in coverage by cell telephone systems. Buys, Dasgupta, Thomas and Wheeler investigate the determinants of these disparities with a spatially-disaggregated model that employs locational information for cell-phone towers across over 990,000 4.6-km grid squares in Sub-Saharan Africa. Using probit techniques, a probability model with adjustments for spatial autocorrelation has been estimated that relates the likelihood of cell-tower location within a grid square to potential market size (proximate population); installation and maintenance cost factors related to accessibility (elevation, slope, distance from a main road, distance from the nearest large city); and national competition policy. Probit estimates indicate strong, significant results for the supply-demand variables, and very strong results for the competition policy index. Simulations based on the econometric results suggest that a generalized improvement in competition policy to a level that currently characterizes the best-performing states in Sub-Saharan Africa could lead to huge improvements in cell-phone area coverage for many states currently with poor policy performance, and an overall coverage increase of nearly 100 percent.E-Business,ICT Policy and Strategies,Population Policies,Technology Industry,Geographical Information Systems

Advances in the stochastic modelling of satellite-derived rainfall estimates using a sparse calibration dataset

As satellite technology develops, satellite rainfall estimates are likely to become ever more important in the world of food security. It is therefore vital to be able to identify the uncertainty of such estimates and for end users to be able to use this information in a meaningful way. This paper presents new developments in the methodology of simulating satellite rainfall ensembles from thermal infrared satellite data. Although the basic sequential simulation methodology has been developed in previous studies, it was not suitable for use in regions with more complex terrain and limited calibration data. Developments in this work include the creation of a multithreshold, multizone calibration procedure, plus investigations into the causes of an overestimation of low rainfall amounts and the best way to take into account clustered calibration data. A case study of the Ethiopian highlands has been used as an illustration

Real-time wave assimilation using low-cost sensor arrays (Extended Abstract)

In this paper we present the underlying theory and principal results from a new real-time data-assimilation system in which we integrate a dense network of Spotters. The sensor network was deployed as part of the ONR Innershelf DRI experiment during the period from September 2017 till November 2017. The array consists of 18 Spotters, deployed seaward of Point Sal (California) along the 20-, 50- and 100-meter depth contours (Fig. 1). Each of these buoys provides estimates of the complete frequency-directional spectrum every hour. The wave spectra and directional moments are assimilated in real-time using an efficient backward raytracing algorithm to reconstruct the details of the offshore boundary conditions, which is subsequently used to drive a regional wave model to produce a fully dataconstrained nowcast of the regional wave conditions. We will discuss the data-assimilation framework developed in this study and compare assimilated results with conventional model predictions forced with predictions from the global NOAA WAVEWATCH III mode

Real-time wave assimilation using low-cost sensor arrays (Extended Abstract)

In this paper we present the underlying theory and principal results from a new real-time data-assimilation system in which we integrate a dense network of Spotters. The sensor network was deployed as part of the ONR Innershelf DRI experiment during the period from September 2017 till November 2017. The array consists of 18 Spotters, deployed seaward of Point Sal (California) along the 20-, 50- and 100-meter depth contours (Fig. 1). Each of these buoys provides estimates of the complete frequency-directional spectrum every hour. The wave spectra and directional moments are assimilated in real-time using an efficient backward raytracing algorithm to reconstruct the details of the offshore boundary conditions, which is subsequently used to drive a regional wave model to produce a fully dataconstrained nowcast of the regional wave conditions. We will discuss the data-assimilation framework developed in this study and compare assimilated results with conventional model predictions forced with predictions from the global NOAA WAVEWATCH III mode