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The exponent and circumdiameter of primitive directed graphsDame, Lorraine Frances. 10 April 2008 (has links)
No description available.
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Kernels and quasi-kernels in digraphsHeard, Scott. 10 April 2008 (has links)
No description available.
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The reversing number of a digraph /Narayan, Darren Amal. January 2000 (has links)
Thesis (Ph. D.)--Lehigh University, 2000. / Includes vita. Includes bibliographical references (leaf 70).
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Graded traces and irreducible representations of Aut(A(Gamma)) acting on graded A(Gamma) and A(Gamma)!Duffy, Colleen M. January 2008 (has links)
Thesis (Ph. D.)--Rutgers University, 2008. / "Graduate Program in Mathematics." Includes bibliographical references (p. 82-83).
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Polytopal digraphs and non-polytopal facet graphs /Mihalisin, James Edward. January 2001 (has links)
Thesis (Ph. D.)--University of Washington, 2001. / Vita. Includes bibliographical references (p. 69-73).
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A causal model of linkages among strategy, structure, and performance using directed acyclic graphs: A manufacturing subset of Fortune 500 industrials 1990-1998Chong, Hogun 30 September 2004 (has links)
This research explored the causal relationships among strategies, corporate structure, and performance of the largest U.S. non-financial firms using Directed Acyclic Graphs (DAGs). Corporate strategies and structure have been analyzed as major variables to influence corporate performance in management and organizational studies. However, their causal relationships in terms of which variables are leaders and followers, as well as the choices of variables to configure them, are controversial. Finding of causal relationships among strategic variables, structural variables, and corporate performance is beneficial to researchers as well as corporate mangers. It provides guidance to researchers how to build a model in order to measure influences from one variable to the other, lowering the risk of drawing spurious conclusions. It also provides managers a prospect of how certain important variables would change by making a certain strategic decision. Literatures from agency theory, transactional cost economics, and traditional strategic management perspective are used to suggest variables essential to analyze corporate performance. This study includes size and multi-organizational ownership hierarchy as variables to configure corporate structure. The variables to configure corporate strategies are unrelated and related diversification, ownership by institutional investors, debt, investment in R&D, and investment in advertisement.
The study finds that most of the variables classified as corporate strategy and corporate structure variables are either direct or indirect causes of corporate accounting performance. Generally, results supports the relational model: corporate structure® corporate strategy® corporate performance. Ownership hierarchy structure, unrelated diversification, advertising expenses, and R&D intensity have direct causal influences on corporate accounting performance. Size and related diversification affected corporate accounting performance indirectly, both through ownership hierarchy structure. Theoretical causal relationships from agency theory are less supported than those from transaction cost economics and traditional strategic management perspective. Further my study suggests that, in general, good corporate performance in 1990s was mainly achieved by internal expansion through investment in R&D and advertisement, rather than external expansion of firms through unrelated diversification, related diversification, and expansion of ownership hierarchy.
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Energy of graphs and digraphsJahanbakht, Nafiseh, University of Lethbridge. Faculty of Arts and Science January 2010 (has links)
The energy of a graph is the sum of the absolute values of the eigenvalues
of its adjacency matrix. The concept is related to the energy of a class of
molecules in chemistry and was first brought to mathematics by Gutman
in 1978 ([8]). In this thesis, we do a comprehensive study on the energy
of graphs and digraphs.
In Chapter 3, we review some existing upper and lower bounds for
the energy of a graph. We come up with some new results in this chapter.
A graph with n vertices is hyper-energetic if its energy is greater than
2n−2. Some classes of graphs are proved to be hyper-energetic. We find
a new class of hyper-energetic graphs which is introduced and proved to
be hyper-energetic in Section 3.3.
The energy of a digraph is the sum of the absolute values of the real
part of the eigenvalues of its adjacency matrix. In Chapter 4, we study
the energy of digraphs in a way that Pe˜na and Rada in [19] have defined.
Some known upper and lower bounds for the energy of digraphs are reviewed.
In Section 4.5, we bring examples of some classes of digraphs
in which we find their energy.
Keywords. Energy of a graph, hyper-energetic graph, energy of a digraph. / vii, 80 leaves ; 29 cm
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C*-algebras associated to higher-rank graphsSims, Aidan. January 2003 (has links)
Thesis (Ph.D.) -- University of Newcastle, 2003. / School of Mathematical and Physical Sciences. Includes bibliographical references (p. 161-162). "Also available online".
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Monoid pictures and finite derivation type /Gains, David, January 1900 (has links)
Thesis (M.Sc.) - Carleton University, 2005. / Includes bibliographical references (p. 61-63). Also available in electronic format on the Internet.
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A layout algorithm for hierarchical graphs with constraints /Slade, Michael L. January 1994 (has links)
Thesis (M.S.)--Rochester Institute of Technology, 1994. / Typescript. Includes bibliographical references (leaves 77-80).
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