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Jonathan Hearn

    Competitive medical image segmentation
    Salvage ethnography in the financial sector
    The Domestication of Competition
    • The Domestication of Competition

      Social Evolution and Liberal Society

      • 330 Seiten
      • 12 Lesestunden
      4,0(1)Abgeben

      The book explores the nature and origins of modern liberal society, focusing on the pervasive role of competition within it. Aimed at academics in the social sciences and humanities, as well as an educated audience, it offers critical conceptual tools to understand the dynamics of competition and its implications for societal structure.

      The Domestication of Competition
    • Salvage ethnography in the financial sector

      The path to economic crisis in Scotland

      • 160 Seiten
      • 6 Lesestunden

      The book explores the historical ethnography of banking practices during the merger of Halifax and Bank of Scotland, shedding light on the 2008 economic crisis. It examines the influence of national identities, contrasting business styles, and the tensions that arose during the merger. Additionally, it delves into the unrest experienced and discusses the implications for future organizational development, offering a comprehensive understanding of the factors that shaped this significant event in banking history.

      Salvage ethnography in the financial sector
    • Continuous advancements in medical data acquisition and 3D display technologies have made them increasingly significant tools in modern medical treatment. However, these technologies are only effective with the use of innovative data processing methods that produce accurate 3D models of biological data, bridging the gap between acquisition and presentation. The most successful existing methods to accomplish this make use of significant data dependent input and user manipulations. This work introduces an innovative approach to solving this image segmentation problem through the integration of the popular Fast Marching method into a competitive framework. The technique''s design is centered around minimizing user interaction and maximizing generality, making it appropriate for use on various bodies of data without substantial modification. Analysis of the algorithm''s performance makes clear its strengths and weaknesses and demonstrates a promising future in surgical simulation and endoscopic studies.

      Competitive medical image segmentation