104 research outputs found

    Optimization with partial differential equations in dieudonné-rashevsky form and conjugate problems

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    Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/46185/1/205_2004_Article_BF00247693.pd

    Information inequalities and Generalized Graph Entropies

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    In this article, we discuss the problem of establishing relations between information measures assessed for network structures. Two types of entropy based measures namely, the Shannon entropy and its generalization, the R\'{e}nyi entropy have been considered for this study. Our main results involve establishing formal relationship, in the form of implicit inequalities, between these two kinds of measures when defined for graphs. Further, we also state and prove inequalities connecting the classical partition-based graph entropies and the functional-based entropy measures. In addition, several explicit inequalities are derived for special classes of graphs.Comment: A preliminary version. To be submitted to a journa

    Project management between will and representation

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    This article challenges some deep-rooted assumptions of project management. Inspired by the work of the German philosopher, Arthur Schopenhauer, it calls for looking at projects through two complementary lenses: one that accounts for cognitive and representational aspects and one that accounts for material and volitional aspects. Understanding the many ways in which these aspects transpire and interact in projects sheds new light on project organizations, as imperfect and fragile representations that chase a shifting nexus of intractable human, social, technical, and material processes. This, in turn, can bring about a new grasp of notions such as value,\ud knowledge, complexity, and risk

    Connections between Classical and Parametric Network Entropies

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    This paper explores relationships between classical and parametric measures of graph (or network) complexity. Classical measures are based on vertex decompositions induced by equivalence relations. Parametric measures, on the other hand, are constructed by using information functions to assign probabilities to the vertices. The inequalities established in this paper relating classical and parametric measures lay a foundation for systematic classification of entropy-based measures of graph complexity

    Multidimensional Lagrange problems of optimization in a fixed domain and an application to a problem of magnetohydrodynamics

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    Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/46178/1/205_2004_Article_BF00281359.pd
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