The theoretical underpinnings of Chicago sociology in the 1920s and 30s

This paper looks at the work of the Chicago School in the 1920s and 1930s from the standpoint of the debate between positivism and its critics within the discipline of sociology. It is argued that, despite appearances to the contrary, Chicago sociology at this time is based on a rejection of the principles of positivism. It is an attempt to apply the principles of interpretative understanding to the practical problems of empirical research.     

Teacher training and multiculturalism in a transitional society: the case of the Slovak Republic

The authors explore a number of issues surrounding multicultural education in “societies in transition”, emerging from their experiences during a TEMPUS project that took place in the Slovak Republic. The TEMPUS project entailed the development of a multicultural education curriculum for teacher trainers, as a response to the conditions for entry into the European Union. The paper provides background information on the position of ethnic minorities in Slovakia, in particular the Hungarian and Roma population and the development of policies, especially in education, for combating racism. In examining the challenges to educators in developing a more open system than the command education of the recent past, issues such as the predominance of traditional pedagogies, multiculturalism and antiracism, the problems of “other isms” and of giving voice to minorities are considered.     

Will oil markets tighten again? A survey of policies to manage possible oil supply disruptions

The effects of an oil supply disruption on the U.S. economy are analyzed along with the various policy options. Part of the analysis is based on a computerized model of the U.S. economy and the world oil market. Micro as well as macroeconomic issues are considered. The paper argues against the use of price controls and allocations and also against a disruption tariff used as a stand-alone measure. It advocates the use of some stabilizing macroeconomic measures and a temporary producer tax similar to the windfall profits tax.     

Small-sample results for maximum-likelihood estimation in branching processes

In this article, small sample properties of the maximum-likelihood estimator (m.l.e.) for the offspring distribution (pk) and its mean m are considered in the context of the simple branching process. A representation theorem is given for the m.l.e. of (Pk) from which the m.l.e. of m is obtained. The case where p0 + p1 + p2 = 1 is studied in detail: numerical results are given for the exact bias of these estimators as a function of the age of the process; a curve fitting analysis expresses the bias of m? as a function of the mean and the variance of the offspring distribution and finally an “approximate m.l.e.” for (pk) is given.     

Scale-space theory: a basic tool for analyzing structures at different scales

An inherent property of objects in the world is that they only exist as meaningful entities over certain ranges of scale. If one aims to describe the structure of unknown real-world signals, then a multi-scale representation of data is of crucial importance. This paper gives a tutorial review of a special type of multi-scale representation—linear scale-space representation—which has been developed by the computer vision community to handle image structures at different scales in a consistent manner. The basic idea is to embed the original signal into a one-parameter family of gradually smoothed signals in which the fine-scale details are successively suppressed. Under rather general conditions on the type of computations that are to be performed at the first stages of visual processing, in what can be termed ‘the visual front-end’, it can be shown that the Gaussian kernel and its derivatives are singled out as the only possible smoothing kernels. The conditions that specify the Gaussian kernel are, basically, linearity and shift invariance, combined with different ways of formalizing the notion that structures at coarse scales should correspond to simplifications of corresponding structures at fine scales-they should not be accidental phenomena created by the smoothing method. Notably, several different ways of choosing scale-space axioms give rise to the same conclusion. The output from the scale-space representation can be used for a variety of early visual tasks; operations such as feature detection, feature classification and shape computation can be expressed directly in terms of (possibly non-linear) combinations of Gaussian derivatives at multiple scales. In this sense the scale-space representation canserve as a basis for early vision. During the last few decades, a number of other approaches to multiscale representations have been developed, which are more or less related to scale-space theory, notably the theories of pyramids, wavelets and multi grid methods.Despite their qualitative differences, the increasing propularity of each of these approaches indicates that the crucial notion of scale is increasingly appreciated by the computer.vision community and by researchers in other related fields. An interesting similarity to biological vision is that the scale-space operators closely resemble receptive field profiles registered in neurophysiological studies of the mam- malian retina and visual cortex.