The spaces of the Wednesday Play (BBC TV 1964–1970): production, technology and style

The BBC television drama anthology The Wednesday Play, broadcast from 1964-70 on the BBC1 channel, was high-profile and often controversial in its time and has since been central to accounts of British television’s ‘golden age’. This article demonstrates that production technologies and methods were more diverse at that time than is now acknowledged, and that The Wednesday Play dramas drew both approving but also very critical responses from contemporary viewers and professional reviewers. This article analyses the ways that the physical spaces of production for different dramas in the series, and the different technologies of shooting and recording that were adopted in these production spaces, are associated with but do not determine aesthetic style. The adoption of single-camera location filming rather than the established production method of multi-camera studio videotaping in some of the dramas in the series has been important to The Wednesday Play’s significance, but each production method was used in different ways. The dramas drew their dramatic forms and aesthetic emphases from both theatre and cinema, as well as connecting with debates about the nature of drama for television. Institutional and regulatory frameworks such as control over staff working away from base, budgetary considerations and union agreements also impacted on decisions about how programmes were made. The article makes use of records from the BBC Written Archives Centre, as well as published scholarship. By placing The Wednesday Play in a range of overlapping historical contexts, its identity can be understood as transitional, differentiated and contested.

National interest to global reform: patterns of reasoning in British foreign policy discourse

Discussion of the national interest often focuses on how Britain's influence can be maximized, rather than on the goals that influence serves. Yet what gives content to claims about the national interest is the means-ends reasoning which links interests to deeper goals. In ideal-typical terms, this can take two forms. The first, and more common, approach is conservative: it infers national interests and the goals they advance from existing policies and commitments. The second is reformist: it starts by specifying national goals and then asks how they are best advanced under particular conditions. New Labour's foreign policy discourse is notable for its explicit use of a reformist approach. Indeed, Gordon Brown's vision of a 'new global society' not only identifies global reform as a key means of fulfilling national goals, but also thereby extends the concept of the national interest well beyond a narrow concern with national security.

Application of complex extreme learning machine to multiclass classification problems with high dimensionality: a THz spectra classification problem

We extend extreme learning machine (ELM) classifiers to complex Reproducing Kernel Hilbert Spaces (RKHS) where the input/output variables as well as the optimization variables are complex-valued. A new family of classifiers, called complex-valued ELM (CELM) suitable for complex-valued multiple-input–multiple-output processing is introduced. In the proposed method, the associated Lagrangian is computed using induced RKHS kernels, adopting a Wirtinger calculus approach formulated as a constrained optimization problem similarly to the conventional ELM classifier formulation. When training the CELM, the Karush–Khun–Tuker (KKT) theorem is used to solve the dual optimization problem that consists of satisfying simultaneously smallest training error as well as smallest norm of output weights criteria. The proposed formulation also addresses aspects of quaternary classification within a Clifford algebra context. For 2D complex-valued inputs, user-defined complex-coupled hyper-planes divide the classifier input space into four partitions. For 3D complex-valued inputs, the formulation generates three pairs of complex-coupled hyper-planes through orthogonal projections. The six hyper-planes then divide the 3D space into eight partitions. It is shown that the CELM problem formulation is equivalent to solving six real-valued ELM tasks, which are induced by projecting the chosen complex kernel across the different user-defined coordinate planes. A classification example of powdered samples on the basis of their terahertz spectral signatures is used to demonstrate the advantages of the CELM classifiers compared to their SVM counterparts. The proposed classifiers retain the advantages of their ELM counterparts, in that they can perform multiclass classification with lower computational complexity than SVM classifiers. Furthermore, because of their ability to perform classification tasks fast, the proposed formulations are of interest to real-time applications.

An evaluation of the pedestrian classification in a multi-domain multi-modality setup

The objective of this article is to study the problem of pedestrian classification across different light spectrum domains (visible and far-infrared (FIR)) and modalities (intensity, depth and motion). In recent years, there has been a number of approaches for classifying and detecting pedestrians in both FIR and visible images, but the methods are difficult to compare, because either the datasets are not publicly available or they do not offer a comparison between the two domains. Our two primary contributions are the following: (1) we propose a public dataset, named RIFIR , containing both FIR and visible images collected in an urban environment from a moving vehicle during daytime; and (2) we compare the state-of-the-art features in a multi-modality setup: intensity, depth and flow, in far-infrared over visible domains. The experiments show that features families, intensity self-similarity (ISS), local binary patterns (LBP), local gradient patterns (LGP) and histogram of oriented gradients (HOG), computed from FIR and visible domains are highly complementary, but their relative performance varies across different modalities. In our experiments, the FIR domain has proven superior to the visible one for the task of pedestrian classification, but the overall best results are obtained by a multi-domain multi-modality multi-feature fusion.

Non-cinema: the location of politics in film

Philosophy has repeatedly denied cinema in order to grant it artistic status. Adorno, for example, defined an ‘uncinematic’ element in the negation of movement in modern cinema, ‘which constitutes its artistic character’. Similarly, Lyotard defended an ‘acinema’, which rather than selecting and excluding movements through editing, accepts what is ‘fortuitous, dirty, confused, unclear, poorly framed, overexposed’. In his Handbook of Inaesthetics, Badiou embraces a similar idea, by describing cinema as an ‘impure circulation’ that incorporates the other arts. Resonating with Bazin and his defence of ‘impure cinema’, that is, of cinema’s interbreeding with other arts, Badiou seems to agree with him also in identifying the uncinematic as the location of the Real. This article will investigate the particular impurities of cinema that drive it beyond the specificities of the medium and into the realm of the other arts and the reality of life itself. Privileged examples will be drawn from various moments in film history and geography, starting with the analysis of two films by Jafar Panahi: This Is Not a Film (In film nist, 2011), whose anti-cinema stance in announced in its own title; and The Mirror (Aineh, 1997), another relentless exercise in self-negation. It goes on to examine Kenji Mizoguchi’s deconstruction of cinematic acting in his exploration of the geidomono genre (films about theatre actors) in The Story of the Last Chrysanthemums (Zangigku monogatari, 1939), and culminates in the conjuring of the physical experience of death through the systematic demolition of film genres in The Act of Killing (Joshua Oppenheimer et al., 2012).

A Genetic Algorithm for the selection of structural MRI features for classification of Mild Cognitive Impairment and Alzheimer's Disease

This work investigates the problem of feature selection in neuroimaging features from structural MRI brain images for the classification of subjects as healthy controls, suffering from Mild Cognitive Impairment or Alzheimer’s Disease. A Genetic Algorithm wrapper method for feature selection is adopted in conjunction with a Support Vector Machine classifier. In very large feature sets, feature selection is found to be redundant as the accuracy is often worsened when compared to an Support Vector Machine with no feature selection. However, when just the hippocampal subfields are used, feature selection shows a significant improvement of the classification accuracy. Three-class Support Vector Machines and two-class Support Vector Machines combined with weighted voting are also compared with the former and found more useful. The highest accuracy achieved at classifying the test data was 65.5% using a genetic algorithm for feature selection with a three-class Support Vector Machine classifier.