Working paper summarizing research into cataloging theory, history of science, mathematics, and information science. / The report summarizes a research program that has been investigating how catalogers, other Cultural Heritage information workers, World Wide Web/Semantic Web technologists, and the general public understand, explain, and manage resource description tasks by creating, counting, measuring, classifying, and otherwise arranging descriptions of Cultural Heritage resources within the Bibliographic Universe and beyond it.

This thesis is concerned with one important question in artificial neural networks, that is, how biologically inspired connectivity of a network affects its associative memory performance. In recent years, research on the mammalian cerebral cortex, which has the main responsibility for the associative memory function in the brains, suggests that the connectivity of this cortical network is far from fully connected, which is commonly assumed in traditional associative memory models. It is found to be a sparse network with interesting connectivity characteristics such as the “small world network” characteristics, represented by short Mean Path Length, high Clustering Coefficient, and high Global and Local Efficiency. Most of the networks in this thesis are therefore sparsely connected. There is, however, no conclusive evidence of how these different connectivity characteristics affect the associative memory performance of a network. This thesis addresses this question using networks with different types of connectivity, which are inspired from biological evidences. The findings of this programme are unexpected and important. Results show that the performance of a non-spiking associative memory model is found to be predicted by its linear correlation with the Clustering Coefficient of the network, regardless of the detailed connectivity patterns. This is particularly important because the Clustering Coefficient is a static measure of one aspect of connectivity, whilst the associative memory performance reflects the result of a complex dynamic process. On the other hand, this research reveals that improvements in the performance of a network do not necessarily directly rely on an increase in the network’s wiring cost. Therefore it is possible to construct networks with high associative memory performance but relatively low wiring cost. Particularly, Gaussian distributed connectivity in a network is found to achieve the best performance with the lowest wiring cost, in all examined connectivity models. Our results from this programme also suggest that a modular network with an appropriate configuration of Gaussian distributed connectivity, both internal to each module and across modules, can perform nearly as well as the Gaussian distributed non-modular network. Finally, a comparison between non-spiking and spiking associative memory models suggests that in terms of associative memory performance, the implication of connectivity seems to transcend the details of the actual neural models, that is, whether they are spiking or non-spiking neurons.

Random NP-Complete problems have come under study as an important tool used in the analysis of optimization algorithms and help in our understanding of how to properly address issues of computational intractability. In this thesis, the Number Partition Problem and the Hamiltonian Cycle Problem are taken as representative NP-Complete classes. Numerical evidence is presented for a phase transition in the probability of solution when a modified Lévy-Stable distribution is used in instance creation for each. Numerical evidence is presented that show hard random instances exist near the critical threshold for the Hamiltonian Cycle problem. A choice of order parameter for the Number Partition Problem’s phase transition is also given. Finding Hamiltonian Cycles in Erdös-Rényi random graphs is well known to have almost sure polynomial time algorithms, even near the critical threshold. To the author’s knowledge, the graph ensemble presented is the first candidate, without specific graph structure built in, to generate graphs whose Hamiltonicity is intrinsically hard to determine. Random graphs are chosen via their degree sequence generated from a discretized form of Lévy-Stable distributions. Graphs chosen from this distribution still show a phase transition and appear to have a pickup in search cost for the algorithms considered. Search cost is highly dependent on the particular algorithm used and the graph ensemble is presented only as a potential graph ensemble to generate intrinsically hard graphs that are difficult to test for Hamiltonicity. Number Partition Problem instances are created by choosing each element in the list from a modified Lévy-Stable distribution. The Number Partition Problem has no known good approximation algorithms and so only numerical evidence to show the phase transition is provided without considerable focus on pickup in search cost for the solvers used. The failure of current approximation algorithms and potential candidate approximation algorithms are discussed.

The chromatic polynomial of a graph, is a polynomial that when evaluated at a positive integer k, is the number of proper k colorings of the graph. We can then find the orbital chromatic polynomial of a graph and a group of automorphisms of the graph, which is a polynomial whose value at a positive integer k is the number of orbits of k-colorings of a graph when acted upon by the group. By considering the roots of the orbital chromatic and chromatic polynomials, the similarities and differences of these polynomials is studied. Specifically we work toward proving a conjecture concerning the gap between the real roots of the chromatic polynomial and the real roots of the orbital chromatic polynomial.

In this dissertation the results of Jerrum and Sinclair on the conductance of Markov chains are used to prove that almost all generalized Steinhaus graphs are rapidly mixing and an algorithm for the uniform generation of 2 - (4k + 1,4,1) cyclic Mendelsohn designs is developed.

We define a new graph operation called the inner power of a graph. The construction is similar to the direct power of graphs, except that factors are intertwined in such a way that certain structural properties of graphs are more clearly reflected in their inner powers. We investigate various properties of inner powers, such as connectivity, bipartiteness, and their interaction with the direct product. We explore possible connections between inner powers and the problem of cancellation over the direct product of graphs.

The independence number of a graph is the maximum number of vertices from the vertex set of the graph such that no two vertices are adjacent. We systematically examine a collection of upper bounds for the independence number to determine graphs for which each upper bound is better than any other upper bound considered. A similar investigation follows for lower bounds. In several instances a graph cannot be found. We also include graphs for which no bound equals $\alpha$ and bounds which do not apply to general graphs.

How many equivalence classes of geodesic rays does a graph contain? How many bounded automorphisms does a planar graph have? Neimayer and Watkins studied these two questions and answered them for a certain class of graphs. Using the concept of excess of a vertex, the class of graphs that Neimayer and Watkins studied are extended to include graphs with positive excess at each vertex. The results of this paper show that there are an uncountable number of geodesic fibers for graphs in this extended class and that for any graph in this extended class the only bounded automorphism is the identity automorphism.

We study the complexity of the λ−L(p, q)-labelling problem for fixed λ, p, and q. The task is to assign vertices of a graph labels from the set {0, . . . , λ} such that labels of adjacent vertices differ by at least p while vertices with a common neighbor have different labels. We use two different reductions, one from the NAE-3SAT and the second one from the edge precoloring extension problem. 1

Graph immersions are a natural counterpart to the widely studied concepts of graph minors and topological graph minors, and yet their theory is much less developed. In the present work we search for sufficient conditions for the existence of the immersions and the properties of the graphs avoiding an immersion of a fixed graph. We prove that large tree-with of 4-edge-connected graph implies the existence of immersion of any 4-regular graph on small number of vertices and that large maximum degree of 3-edge-connected graph implies existence of immersion of any 3-regular graph on small number of vertices.