Information Processing and Transmission in Cellular Automata

A cellular automaton is an iterative array of very simple identical information processing machines called cells. Each cell can communicate with neighboring cells. At discrete moments of time the cells can change from one state to another as a function of the states of the cell and its neighbors. Thus on a global basis, the collection of cells is characterized by some type of behavior. The goal of this investigation was to determine just how simple the individual cells could be while the global behavior achieved some specified criterion of complexity ??ually the ability to perform a computation or to reproduce some pattern. The chief result described in this thesis is that an array of identical square cells (in two dimensions), each cell of which communicates directly with only its four nearest edge neighbors and each of which can exist in only two states, can perform any computation. This computation proceeds in a straight forward way. A configuration is a specification of the states of all the cells in some area of the iterative array. Another result described in this thesis is the existence of a self-reproducing configuration in an array of four-state cells, a reduction of four states from the previously known eight-state case. The technique of information processing in cellular arrays involves the synthesis of some basic components. Then the desired behaviors are obtained by the interconnection of these components. A chapter on components describes some sets of basic components. Possible applications of the results of this investigation, descriptions of some interesting phenomena (for vanishingly small cells), and suggestions for further study are given later.

CEDI: A Neural Model of Colour Vision, with Applications to Image Processing and Classification

Air Force Office of Scientific Research (F49620-01-1-0423); National Geospatial-Intelligence Agency (NMA 201-01-1-2016); National Science Foundation (SBE-035437, DEG-0221680); Office of Naval Research (N00014-01-1-0624)

Digital signal processing and artificial intelligence for the automated classification of food allergy

As a by-product of the ‘information revolution’ which is currently unfolding, lifetimes of man (and indeed computer) hours are being allocated for the automated and intelligent interpretation of data. This is particularly true in medical and clinical settings, where research into machine-assisted diagnosis of physiological conditions gains momentum daily. Of the conditions which have been addressed, however, automated classification of allergy has not been investigated, even though the numbers of allergic persons are rising, and undiagnosed allergies are most likely to elicit fatal consequences. On the basis of the observations of allergists who conduct oral food challenges (OFCs), activity-based analyses of allergy tests were performed. Algorithms were investigated and validated by a pilot study which verified that accelerometer-based inquiry of human movements is particularly well-suited for objective appraisal of activity. However, when these analyses were applied to OFCs, accelerometer-based investigations were found to provide very poor separation between allergic and non-allergic persons, and it was concluded that the avenues explored in this thesis are inadequate for the classification of allergy. Heart rate variability (HRV) analysis is known to provide very significant diagnostic information for many conditions. Owing to this, electrocardiograms (ECGs) were recorded during OFCs for the purpose of assessing the effect that allergy induces on HRV features. It was found that with appropriate analysis, excellent separation between allergic and nonallergic subjects can be obtained. These results were, however, obtained with manual QRS annotations, and these are not a viable methodology for real-time diagnostic applications. Even so, this was the first work which has categorically correlated changes in HRV features to the onset of allergic events, and manual annotations yield undeniable affirmation of this. Fostered by the successful results which were obtained with manual classifications, automatic QRS detection algorithms were investigated to facilitate the fully automated classification of allergy. The results which were obtained by this process are very promising. Most importantly, the work that is presented in this thesis did not obtain any false positive classifications. This is a most desirable result for OFC classification, as it allows complete confidence to be attributed to classifications of allergy. Furthermore, these results could be particularly advantageous in clinical settings, as machine-based classification can detect the onset of allergy which can allow for early termination of OFCs. Consequently, machine-based monitoring of OFCs has in this work been shown to possess the capacity to significantly and safely advance the current state of clinical art of allergy diagnosis

Application of guar gum as a flocculant aid in food processing and potable water treatment

The paper deals with use of a food grade coagulant (guar gum) as a replacement for synthetic coagulants for potable water treatment.

Direct and indirect effects of species displacements; an invading freshwater amphipod can disrupt leaf litter processing and shredder efficiency

Invasive species may threaten the fundamental role played by native macroinvertebrate shredders in determining energy flow and the trophic dynamics of freshwater ecosystems. Functionally, amphipods have long been regarded as mainly shredders, but they are increasingly recognized as major predators of other macroinvertebrate taxa. Furthermore, intraguild predation (IGP) between native and invasive amphipods underlies many species displacements. We used laboratory mesocosms to investigate what might happen to shredders and leaf-litter processing in water bodies invaded by the highly predatory Ponto-Caspian amphipod Dikerogammarus villosus, which is spreading rapidly throughout Europe and may soon invade the North American Great Lakes. The leaf-shredding efficiency of D. villosus was significantly lower than that of 3 Gammarus species (2 native and 1 invasive) that D. villosus has either already displaced or may be currently displacing in The Netherlands. In addition, D. villosus was a major predator of all of these native and invasive amphipod shredders and of a common isopod shredder Asellus aquaticus. Leaf processing in Gammarus and Asellus mesocosms declined rapidly in the presence of D. villosus and ceased altogether within 4 d because by then, all potential shredders had been killed and consumed. Furthermore, the shredding efficiency of surviving amphipods and isopods declined significantly within 2 d of the release of D. villosus, a result indicating that predator-avoidance behavior may override leaf processing. We discuss the implications of these direct and indirect effects of D. villosus invasions and species displacements on community structure and litter processing in aquatic ecosystems. © 2011 The North American Benthological Society.


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