Achieving Marketplace Agility Through Human Resource Scalability

[Excerpt] Increasingly, firms find themselves, either by circumstances or choice, operating in highly turbulent business environments. For them, competitiveness is a constantly moving target. Many, it appears, are satisfied to enjoin the struggle with patched up business models and warmed over bureaucracies. But some, convinced that this is a losing proposition, are aggressively exploring and even experimenting with alternative frameworks and approaches. The monikers are many -- kinetic (Fradette and Michaud, 1998), dynamic (Peterson and Mannix, 2003), resilient (Hamel and Valikangas, 2003) and our favorite, agile (Shafer, Dyer, Kilty, Ericksen and Amos, 2001) -- but the aim is the same: to create organizations where change is the natural state of affairs. Clearly, this quest poses a number of major challenges for our field (Dyer and Shafer, 1999, 2003), one of which, optimizing human resource scalability, is the subject of this essay

Reflections on the Optimal Currency Area (oca) Criteria in the Light of EMU

The objective of this paper is first to review the use that has been made of Optimal Currency Area (OCA) theory in the European Monetary Union (EMU) context. Second, to look at some of its predictions in that respect. And third, to appraise some of the new theories - or speculations - that have arisen, partly as a result of the confrontation of the theory with the data. This is an area in which politics are very important; they play an important role in the reception and interpretation of positive work. Tentative ideas and speculative hypotheses acquire the aura of accomplished fact, whilst a single empirical illustration can be given the status of a many-times confirmed demonstration. This paper tries to be more careful in these remarks. Whilst history offers some instructive lessons, as illustrated for example in the work of Bordo and Jonung (1999), the fact is that in most relevant respects EMU represents an unparalleled experiment, with corresponding difficulties for empirical work.

A Brane Teaser

In this note we study the puzzle posed by two M5-branes intersecting on a string (or equivalently, a single M5-brane wrapping a holomorphic four-cycle in C^4). It has been known for a while that this system is different from all other configurations built using self-intersecting M-branes; in particular the corresponding supergravity solution exhibits various curious features which have remained unexplained. We propose that the resolution to these puzzles lies in the existence of a non-zero two-form on the M5-brane world-volume.Comment: 21 pages. References adde

Can Thomas Kuhn's paradigms help us understand software engineering

Peer reviewe

Optimising Spatial and Tonal Data for PDE-based Inpainting

Some recent methods for lossy signal and image compression store only a few selected pixels and fill in the missing structures by inpainting with a partial differential equation (PDE). Suitable operators include the Laplacian, the biharmonic operator, and edge-enhancing anisotropic diffusion (EED). The quality of such approaches depends substantially on the selection of the data that is kept. Optimising this data in the domain and codomain gives rise to challenging mathematical problems that shall be addressed in our work. In the 1D case, we prove results that provide insights into the difficulty of this problem, and we give evidence that a splitting into spatial and tonal (i.e. function value) optimisation does hardly deteriorate the results. In the 2D setting, we present generic algorithms that achieve a high reconstruction quality even if the specified data is very sparse. To optimise the spatial data, we use a probabilistic sparsification, followed by a nonlocal pixel exchange that avoids getting trapped in bad local optima. After this spatial optimisation we perform a tonal optimisation that modifies the function values in order to reduce the global reconstruction error. For homogeneous diffusion inpainting, this comes down to a least squares problem for which we prove that it has a unique solution. We demonstrate that it can be found efficiently with a gradient descent approach that is accelerated with fast explicit diffusion (FED) cycles. Our framework allows to specify the desired density of the inpainting mask a priori. Moreover, is more generic than other data optimisation approaches for the sparse inpainting problem, since it can also be extended to nonlinear inpainting operators such as EED. This is exploited to achieve reconstructions with state-of-the-art quality. We also give an extensive literature survey on PDE-based image compression methods