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The acknowledged importance of uncertainty in economic decision making has stimulated the search for neural signals that could influence learning and inform decision mechanisms. Current views distinguish two forms of uncertainty, namely risk and ambiguity, ...
Composite materials are increasingly used in high volume automotive applications, usually as a replacement for assemblies of multiple metallic parts such as stamped and spot-welded steel sheets. One of the motivations is to reduce tooling and assembly cost ...
The current status of the ITER magnetics diagnostic is summarised. The various risks are discussed on the basis of when they could be present during ITER operation and appropriate mitigation is reviewed. An implementation risk or common mode operation fail ...
Preterm premature rupture of the foetal membranes (fruber vorzeitiger Blasensprung) has remained a devastating complication of pregnancy with very high risk of pregnancy loss. Several methods of sealing spontaneously ruptured membranes to stop amniotic flu ...
Breast cancer strikes one out of eight women in Switzerland. The increase in breast cancer incidence over the past 70 years parallels an enormous increase of man-made, persistent chemicals in our environment; some of which have endocrine-disrupting propert ...
In the standard real options approach to investment under uncertainty, agents formulate optimal policies under the assumptions of risk neutrality or perfect capital markets. However, in most situations, corporate executives face incomplete markets either b ...
This thesis comprises three essays on the relationship between innovation and finance. Although previous research has acknowledged the multi-faceted nature of innovation, this thesis unpacks its constituent elements, compares alternative drivers of innovat ...
We investigate the problem of automatic tuning of a deconvolution algorithm for three-dimensional (3D) fluorescence microscopy; specifically, the selection of the regularization parameter lambda. For this, we consider a realistic noise model for data obtai ...
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We investigate the problem of automatic tuning of a deconvolution algorithm for three-dimensional (3D) fluorescence microscopy; specifically, the selection of the regularization parameter λ. For this, we consider a realistic noise model for data obtained ...
We formulate the service composition problem as a multi-objective stochastic program which simultaneously optimizes the following quality of service (QoS) parameters: workflow duration, service invocation costs, availability, and reliability. All of these ...