The general problem we consider in this thesis is the following: we have to analyze a stream of data (records, packets, events ...) by successively applying to each piece of data a set of ``rules'. Rules are best viewed as lightweight parallel processes synchronizing on each arrival of a new piece of data. In many applications, such as signature-based intrusion detection, only a few rules are concerned with each new piece of data. But all other rules have to be executed anyway just to conclude that they can ignore it. Our goal is to make it possible to avoid this useless work completely. To do so, we perform a static analysis of the code of each rule and we build a decision tree that we apply to each piece of data before executing the rule. The decision tree tells us whether executing the rule or not will change anything to the global analysis results. The decision trees are built at compile time, but their evaluation at each cycle (i.e., for each piece of data) entails an overhead. Thus we organize the set of all computed decision trees in a way that makes their evaluation as fast as possible. The two main original contributions of this thesis are the following. Firstly, we propose a method to organize the set of decision trees and the set of active rules in such a way that deciding which rules to execute can be made optimally in O(r_u), where r_u is the number of useful rules. This time complexity is thus independent of the actual (total) number of active rules. This method is based on the use of a global decision tree that integrates all individual decision trees built from the code of the rules. Secondly, as such a global tree may quickly become much too large if usual data structures are used, we introduce a novel kind of data structure called sequential tree that allows us to keep global decision trees much smaller in many situations where the individual trees share few common conditions. (When many conditions are shared by individual trees the global tree remains small.) To assess our contribution, we first modify the implementation of ASAX, a generic system for data stream analysis based on the rule paradigm presented above. Then we compare the efficiency of the optimized system with respect to its original implementation, using the MIT Lincoln Laboratory Evaluation Dataset and a classical set of intrusion detection rules. Impressive speed-ups are obtained. Finally, our optimized implementation has been used by Nicolas Vanderavero, in his PhD thesis, for the design of stateful honeytanks (i.e., low-interaction honeypots). It makes it possible to simulate tens of thousands hosts on a single computer, with a high level of realism.

The high sensitivity of high latitudes to global climate changes is the stimulus for the study of ancient Arctic ecosystems under greenhouse conditions. With an increasing number of studies, including the most recent Intergovernmental Panel on Climate Change (IPCC) report highlighting Pliocene climate as key example for the study of Earth system sensitivity to higher levels of atmospheric CO₂, the need for accurate proxy records for this period is crucial. In order to investigate Pliocene climate, I used stable isotopic studies of fossil molluscs, moss and wood from two fossil forest deposits in the Canadian High Arctic. Temperatures were determined for an Early Pliocene (4-5 Ma) fossil forest site located on Ellesmere Island using 'clumped' and stable isotopic analysis of mollusc shells and stable isotope values of fossil wood. Mollusc inferred growing season (May-Sept) temperatures derived using two independent techniques were estimated to be 11-16° C warmer than present (1950-1990) Ellesmere Island temperatures. Tree ring inferred growing season (June-July) temperatures (JJ) were 10-16° C and mean annual temperatures (MAT) were 18-20° C warmer than present (1950-1990). Mean annual and growing season (JJ) temperatures were also determined using fossil wood from a younger (2.4-2.8 Ma) late Pliocene-early Pleistocene site on Bylot Island. This deposit represents the remains of a flora that grew during an interglacial warm period during the transition to large-scale Northern Hemisphere glaciation that occurred between 2.5 to 3 million years ago. Mean annual temperatures were ~12° C and growing season temperatures were ~13° C warmer than present (1923-2010). The interglacial setting of the Bylot Island site and the warm temperatures suggests that prior to using such sites as true analogues of future conditions we may need to consider how close the feedbacks operating then were to the feedbacks we might expect in the future. However, that temperatures so much warmer than present existed in the high Arctic during a period when levels of atmospheric CO₂ were at nearpresent levels indicates that we may be moving beyond our ability to use the Pliocene as an example of the future.

The assumption that each latewood ring in trees represents one year of growth was tested for Utah juniper (Juniperus osteosperma) and pinyon pine (Pinus edulis). Ring characteristics and growth rates were evaluated for 72 years of growth following scars of consistent date on all trees sampled. Errors in age and growth rate estimates based on ring counts were evaluated. Potential variation among observers was accounted for. Average error in ring counts was lowest when rings were counted on the fastest-growing portions of each cross-section. Errors for more than 40% of the junipers exceeded 10 percent with about half of the trees with more rings and half with less rings than actual years. Pinyons rarely had more rings than years and only 5% of the trees were missing more than 10% of the 72 annual rings. Percentage errors in growth rate estimates based on ring counts were similar to ring count errors for both species. Assigning junipers to age classes based on ring counts also can lead to error in assumed ages of trees. Assuming that ring count error for each tree for the 72 year period studied approximates potential error over the life of each tree, more than half of junipers older than 250 years would be assigned to the wrong age class when using 50 year age classes. Number of rings in junipers was highly correlated with growth rate. Competition from surrounding trees explained as much as 53% and 40% of the variation in growth rates of junipers and pinyons respectively. Relating growth rates and ring counts to ordinations of stand, site and soil characteristics indicated that trees with relatively fast growth rates or trees with the most rings tended to occur on gentle, north to northeast aspects with relatively better- developed soils. However, stand competition often had an overriding influence on growth. Presence of Koelaria pyramidata in the understory was generally an indicator of relatively favorable growing conditions for junipers. Results suggest the need for more caution in the use of ring counts for estimating ages or growth rates of Utah junipers and pinyons than has generally been used in the past, especially when drawing conclusions about specific individuals.

This item was digitized as part of the Million Books Project led by Carnegie Mellon University and supported by grants from the National Science Foundation (NSF). Cornell University coordinated the participation of land-grant and agricultural libraries in providing historical agricultural information for the digitization project; the University of Arizona Libraries, the College of Agriculture and Life Sciences, and the Office of Arid Lands Studies collaborated in the selection and provision of material for the digitization project.

A Final Report Submitted to the U.S. Forest Service, Safford Ranger District, P.O. Box 709, Safford, Arizona 85548

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