The problem of optimizing a biconvex function over a given (bi)convex or compact set frequently occurs in theory as well as in industrial applications, for example, in the field of multifacility location or medical image registration. Thereby, a function f : X × Y → R is called biconvex, if f (x, y) is convex in y for fixed x ∈ X, and f (x, y) is convex in… (More)
Point Based Registration Algorithms a definition of registration " Image registration is the process of overlaying images (two or more) of the same scene taken at different times, from different viewpoints, and/or from different sensors. Point Based Registration Algorithms principle structure ◮ find corresponding points (assignment) ◮ find a transformation… (More)
As a basis for meaningful simulation and optimization efforts with regard to traffic engineering or energy consumption in telecommunication networks, suitable models are indispensable. This concerns not only realistic network topologies but also models for the geographical distribution and the temporal dynamics of traffic, as well as the assumptions on… (More)
T cells orchestrate the adaptive immune response, making them targets for immunotherapy. Although immunosuppressive therapies prevent disease progression, they also leave patients susceptible to opportunistic infections. To identify novel drug targets, we established a logical model describing T-cell receptor (TCR) signaling. However, to have a model that… (More)
We assess the impact of traffic variations on energy consumption and devices lifetime in a core network. Specifically, we first define a model to control the spatial as well as the temporal variations of traffic. We generate different sets of traffic matrices by adopting our model, which are then used as input to an energy-aware algorithm, with the aim of… (More)
For a mixed integer programming formulation of the problem of registering two medical images we propose a geometric Branch & Bound algorithm, which applies a geometric branching strategy on the transformation variables. The results show that medium sized problem instances can be solved to global optimality in a reasonable amount of time.