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Failed Information Technology (IT) projects are common in organisations, as IT solutions often do not meet the expectations of business clients. Business experts often have a negative perception of the people working in the IT function. There seems to be a proverbial "chicken-and-egg situation": the relationship between business and IT suffers because IT projects fail to solve the real business need and, on the other hand, many IT projects fail because of existing interpersonal relationship problems between business- and IT employees. Research was done to identify categories of issues in the business-IT interface and rank them in order of significance. The term "fusion" is used in this paper, to refer to the process by which the elements of the IT function and the rest of the business work together to achieve a common goal. This paper reports on the categories of issues and draws a conclusion of what would constitute fusion in the business-IT interface. [ABSTRACT FROM AUTHOR]

This section provides an overview of several articles on deep computing or high-performance computing which are applied to problems that require significant computing resources in order to facilitate relatively complex decision-making in fields ranging from business to the sciences. The papers capture a few illustrations of deep computing that cut across traditional disciplines. Deep computing requires not only massive amounts of computing,but also the processing of vast amounts of data and the use of sophisticated means for the interpretation of results. New algorithmic approaches are being developed that take into account computer architecture in order to address problems of general interest and answer questions that have impact beyond just scientific inquiry. The paper by Crivelli and Head-Gordon discusses a load-balancing technique to exploit the use of parallel architectures for addressing protein structure problems. In their paper, Fann et al. investigate multiwavelet approaches and apply them to areas of computational chemistry, computational electromagnetics, and fluid dynamics. Newns et al. discuss new algorithmic techniques they have developed for improving magnetic recording simulation. The applicability of deep computing to astrophysics is illustrated by the paper by Lake et al. The authors apply new algorithms coupled with deep computing to advance our understanding of the N-body problem.