This dissertation explores an immunological model of distributed detection, called negative detection, and studies its performance in the domain of intrusion detection on computer networks. The goal of the detection system is to distinguish between illegitimate behaviour (nonself ), and legitimate behaviour (self ). The detection system consists of sets of negative detectors that detect instances of nonself; these detectors are distributed across multiple locations. The negative detection model was developed previously; this research extends that previous work in several ways. Firstly, analyses are derived for the negative detection model. In particular, a framework for explicitly incorporating distribution is developed, and is used to demonstrate that negative detection is both scalable and robust. Furthermore, it is shown that any scalable distributed detection system that requires communication (memory sharing) is always less robust than a system that does not require communication...

We survey results from distributed computing that show tasks to be impossible, either outright or within given resource bounds, in various models. The parameters of the models considered include synchrony, fault-tolerance, different communication media, and randomization. The resource bounds refer to time, space and message complexity. These results are useful in understanding the inherent difficulty of individual problems and in studying the power of different models of distributed computing.

Some theories of visual word recognition postulate that there is a level of processing or representation at which morphemes are treated differently from whole words. Support for these theories has been derived from priming experiments in which the recognition of a target word is facilitated by the prior presentation of a morphologicallyrelatedprime (departure-DEPART). In English, such facilitation could be due to morphological relatedness, or to some combination of the orthographic and semantic relatedness characteristic of derivationally related words. We report two sets of visual priming experiments in which the morphological, semantic, and orthographic relationships between primes and targets are varied in three SOA conditions (43 ms, 72 ms, and 230 ms). Results showed that morphological structure plays a signi�cant role in the early visual recognition of English words that is independent of both semantic and orthographic relatedness. Findings are discussed in terms of current approaches to morphological processing. Requests for reprints should be addressed to Kathleen Rastle, Department of Experimental

There has been considerable discussion of the claim by Stapp [1] that quantum theory is incompatible with locality. In this note I analyze the meaning of some of the statements used in this discussion. 1

Biodiversity is often ill-defined and subjectively surveyed, resulting in inefficient and ambiguous estimates. Strengths and deficiencies of prevailing survey techniques are appraised through a review of selected literature. Analogies with forest inventory are used to suggest options for more efficient and rigorous biodiversity assessment. Techniques such as variable-probability and model-based sampling, especially when used in conjunction with generalized linear modelling, offer efficient alternatives to more traditional assessments based on quadrats and nested plots. Bayesian methods offer scope to combine expert and local knowledge with formal samples, and warrant further investigation. Suggestions for further research are given. 1.

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vii List of Figures xii Chapter 1.

This paper describes the application of data farming techniques (Brandstein and Horne 1998) to explore various aspects of coevolutionary dynamics (McKelvey 2002) in organization science. Data farming is an iterative process using high-performance computing to execute and vary agent-based models, collect and explore statistical results, and integrate these results for the purposes of growing more data by virtue of generative analysis. The tool of choice for creating these agent-based models is the University

Literature alert services, good evidence-based resources and real-time decision support can all help to reduce information overload f all disease was caused by the four humours; if our only treatments were blood-letting, purging or cold baths; and if all research was forbidden, medicine would be much easier. But medicine has changed, and is changing, more than most practitioners recognise. While no organisation keeps a precise count of the number of diseases, the expert system DiagnosisPro

Can people comprehend assertions without believing them? Descartes (1644/1984) suggested that people can and should, whereas Spinoza (1677/1982) suggested that people should but cannot. Three experiments support the hypothesis that comprehension includes an initial belief in the information comprehended. Ss were exposed to false information about a criminal defendant (Experiments 1 and 2) or a college student (Experiment 3). Some Ss were exposed to this information while under load (Experiments 1 and 2) or time pressure (Experiment 3). Ss made judgments about the target (sentencing decisions or liking judgments). Both load and time pressure caused Ss to believe the false information and to use it in making consequential decisions about the target. In Spinozan terms, both manipulations prevented Ss from "unbelieving " the false information they automatically believed during comprehension. This article was written while Daniel T. Gilbert was a Fellow at the Center for Advanced