Joined Spectral Trees for Scalable SPIHT-Based Multispectral Image Compression

In this paper, the compression of multispectral images is addressed. Such 3-D data are characterized by a high correlation across the spectral components. The efficiency of the state-of-the-art wavelet-based coder 3-D SPIHT is considered. Although the 3-D SPIHT algorithm provides the obvious way to process a multispectral image as a volumetric block and, consequently, maintain the attractive properties exhibited in 2-D (excellent performance, low complexity, and embeddedness of the bit-stream), its 3-D trees structure is shown to be not adequately suited for 3-D wavelet transformed (DWT) multispectral images. The fact that each parent has eight children in the 3-D structure considerably increases the list of insignificant sets (LIS) and the list of insignificant pixels (LIP) since the partitioning of any set produces eight subsets which will be processed similarly during the sorting pass. Thus, a significant portion from the overall bit-budget is wastedly spent to sort insignificant information. Through an investigation based on results analysis, we demonstrate that a straightforward 2-D SPIHT technique, when suitably adjusted to maintain the rate scalability and carried out in the 3-D DWT domain, overcomes this weakness. In addition, a new SPIHT-based scalable multispectral image compression algorithm is used in the initial iterations to exploit the redundancies within each group of two consecutive spectral bands. Numerical experiments on a number of multispectral images have shown that the proposed scheme provides significant improvements over related works.

More-than-human histories and the failure of grand state schemes: sylviculture in the New Forest, England

As James Scott’s Seeing Like a State attests, forests played a central role in the rise of the modern state, specifically as test spaces for evolving methods of managing state resources at a distance, and as the location for grand state schemes. Together, such ambitions necessitated both the elimination of local understandings of forest management – to be replaced by centrally controlled scientific precision – and a narrowing of state vision. Forests thus began to be conflated with trees (and their timber) alone. All other aspects of the forest, both human and non-human, were ignored. Through the lens of the 18th and early 19th century New Forest in southern England, this paper examines the impact of government attempts to shift the focus of state forests from being remnant medieval hunting spaces to spaces of income generation through the creation of vast sylvicultural plantations. This state scheme not only reworked the relationship between the metropole and the provinces – something effected through systematic surveys and novel bureaucratic procedures – but also dramatically impacted upon the biophysical and cultural geographies of the forest. By equating forest space with trees alone, the British state failed to legislate for the actions of both local commoners and non-human others in resisting their schemes. Indeed, subsequent oppositions proved not only the tenacity of commoners in protecting their livelihoods but also the destructive power of non-human actants, specifically rabbits and mice. The paper concludes that grand state schemes necessarily fail due to their own internal illogic: the narrowing of state vision creates blind spots in which human and non-human lives assert their own visions.

Discrete Conditional Phase-type models utilising classification trees: Application to modelling health service capacities

Discrete Conditional Phase-type (DC-Ph) models consist of a process component (survival distribution) preceded by a set of related conditional discrete variables. This paper introduces a DC-Ph model where the conditional component is a classification tree. The approach is utilised for modelling health service capacities by better predicting service times, as captured by Coxian Phase-type distributions, interfaced with results from a classification tree algorithm. To illustrate the approach, a case-study within the healthcare delivery domain is given, namely that of maternity services. The classification analysis is shown to give good predictors for complications during childbirth. Based on the classification tree predictions, the duration of childbirth on the labour ward is then modelled as either a two or three-phase Coxian distribution. The resulting DC-Ph model is used to calculate the number of patients and associated bed occupancies, patient turnover, and to model the consequences of changes to risk status.

On the ability to metaphorize: Talking trees and singing tigers in the English classroom

This article reviews and discusses how metaphor as a trope has been regarded as an essential element in rhetorical approaches to reading and to writing. In addition it considers the extent to which, while metaphor-making is a fundamental cognitive capacity, a metaphorizing habit of mind may be especially pertinent to some aspects of aesthetic activity in English and it has salience also in a multimodal environment. There is exploration of how contemporary practice in the English classroom could accommodate and consolidate the ability to metaphorize.

Topological mappings between graphs, trees and generalized trees

We present novel topological mappings between graphs, trees and generalized trees that means between structured objects with different properties. The two major contributions of this paper are, first, to clarify the relation between graphs, trees and generalized trees, a graph class recently introduced. Second, these transformations provide a unique opportunity to transform structured objects into a representation that might be beneficial for a processing, e.g., by machine learning techniques for graph classification. (c) 2006 Elsevier Inc. All rights reserved.