Life before ‘The New Biography’: Modernist biographical methods in the Hogarth Press ‘Books on Tolstoi’ 1920-24

In the early 1920s, before Virginia Woolf wrote her now well-known essays “The New Biography” and “The Art of Biography,” the Hogarth Press published four biographies of Tolstoy. Each of these English translations of Russian works takes a different approach to biographical composition, and as a group they offer multiple and contradictory perspectives on Tolstoy’s character and on the genre of biography in the early twentieth century. These works show that Leonard and Virginia Woolf’s Hogarth Press took a multi-perspectival, modernist approach to publishing literary lives.

A fuzzy multi-criteria decision approach for enhanced auto-tracking of seismic events

The main activity carried out by the geophysicist when interpreting seismic data, in terms of both importance and time spent is tracking (or picking) seismic events. in practice, this activity turns out to be rather challenging, particularly when the targeted event is interrupted by discontinuities such as geological faults or exhibits lateral changes in seismic character. In recent years, several automated schemes, known as auto-trackers, have been developed to assist the interpreter in this tedious and time-consuming task. The automatic tracking tool available in modem interpretation software packages often employs artificial neural networks (ANN's) to identify seismic picks belonging to target events through a pattern recognition process. The ability of ANNs to track horizons across discontinuities largely depends on how reliably data patterns characterise these horizons. While seismic attributes are commonly used to characterise amplitude peaks forming a seismic horizon, some researchers in the field claim that inherent seismic information is lost in the attribute extraction process and advocate instead the use of raw data (amplitude samples). This paper investigates the performance of ANNs using either characterisation methods, and demonstrates how the complementarity of both seismic attributes and raw data can be exploited in conjunction with other geological information in a fuzzy inference system (FIS) to achieve an enhanced auto-tracking performance.

Application of auto regressive models of wavelet sub-bands for classifying Terahertz pulse measurements

This paper presents an approach for automatic classification of pulsed Terahertz (THz), or T-ray, signals highlighting their potential in biomedical, pharmaceutical and security applications. T-ray classification systems supply a wealth of information about test samples and make possible the discrimination of heterogeneous layers within an object. In this paper, a novel technique involving the use of Auto Regressive (AR) and Auto Regressive Moving Average (ARMA) models on the wavelet transforms of measured T-ray pulse data is presented. Two example applications are examined - the classi. cation of normal human bone (NHB) osteoblasts against human osteosarcoma (HOS) cells and the identification of six different powder samples. A variety of model types and orders are used to generate descriptive features for subsequent classification. Wavelet-based de-noising with soft threshold shrinkage is applied to the measured T-ray signals prior to modeling. For classi. cation, a simple Mahalanobis distance classi. er is used. After feature extraction, classi. cation accuracy for cancerous and normal cell types is 93%, whereas for powders, it is 98%.

Auto-weighted minimum-variance self-tuning controller

A self-tuning controller which automatically assigns weightings to control and set-point following is introduced. This discrete-time single-input single-output controller is based on a generalized minimum-variance control strategy. The automatic on-line selection of weightings is very convenient, especially when the system parameters are unknown or slowly varying with respect to time, which is generally considered to be the type of systems for which self-tuning control is useful. This feature also enables the controller to overcome difficulties with non-minimum phase systems.

Auto-associative memory using n-tuple techniques

The use of n-tuple or weightless neural networks as pattern recognition devices has been well documented. They have a significant advantages over more common networks paradigms, such as the multilayer perceptron in that they can be easily implemented in digital hardware using standard random access memories. To date, n-tuple networks have predominantly been used as fast pattern classification devices. The paper describes how n-tuple techniques can be used in the hardware implementation of a general auto-associative network.

Catch-up strategies in the Indian auto components industry: domestic firms’ responses to market liberalization

Market liberalization in emerging-market economies and the entry of multinational firms spur significant changes to the industry/institutional environment faced by domestic firms. Prior studies have described how such changes tend to be disruptive to the relatively backward domestic firms, and negatively affect their performance and survival prospects. In this paper, we study how domestic supplier firms may adapt and continue to perform, as market liberalization progresses, through catch-up strategies aimed at integrating with the industry's global value chain. Drawing on internalization theory and the literatures on upgrading and catch-up processes, learning and relational networks, we hypothesize that, for continued performance, domestic supplier firms need to adapt their strategies from catching up initially through technology licensing/collaborations and joint ventures with multinational enterprises (MNEs) to also developing strong customer relationships with downstream firms (especially MNEs). Further, we propose that successful catch-up through these two strategies lays the foundation for a strategy of knowledge creation during the integration of domestic industry with the global value chain. Our analysis of data from the auto components industry in India during the period 1992–2002, that is, the decade since liberalization began in 1991, offers support for our hypotheses.

Temporality, cultural biography and seasonality: rethinking time in wetland archaeology

Wetland archaeology is uniquely well placed to investigate questions of chronology, temporality, life-cycles and seasonality. Beyond the usual archaeological approaches to time (eg seriation, typology and stratigraphy), most wetland archaeological investigations have access to a ready supply of samples (ie wood, peat and organic deposits) for absolute scientific dating, particularly radiocarbon and dendrochronology. Indeed, the success of dendrochronology in revealing dynamic sequences of site and regional occupation, use and abandonment are well known. Investigating wetland archaeological sites, environmental archaeologists have used the evidence of insects' plant remains, seeds and even testate amoeba to establish the season, or months, of a site's occupation. Soil micromorphologists have carried out innovative studies of settlement deposits to reconstruct the chronological sequences of processes and events leading to their formation. In brief, wetland archaeology has become adept at calibrating past times.

North Sea archaeologies: a maritime biography, 10,000 BC - AD 1500

North Sea Archaeologies traces the way people engaged with the North Sea from the end of the last ice age, around 10,000 BC, to the close of the Middle Ages, about AD 1500, drawing upon archaeological research from many countries, including the UK, Netherlands, Germany, Denmark, Sweden, Norway, Belgium, and France. It addresses topics which include the first interactions of people with the emerging North Sea, the origin and development of fishing, the creation of coastal landscapes, the importance of islands and archipelagos, the development of seafaring ships and their use by early seafarers and pirates, and the treatment of boats and ships at the end of their useful lives. The study offers a ‘maritime turn’ in Archaeology through the investigation of aspects of human behaviour that have been, to various extents, disregarded, overlooked, or ignored in archaeological studies of the land. The study concludes that the relationship between humans and the sea challenges the frequently invoked dichotomy between pre-modernity and modernity, since many ancient beliefs, superstitions, and practices linked to seafaring and engagement with the sea are still widespread in the modern era.