Compact double-side liquid-impingement-cooled integrated power electronic module

This paper presents a compact integrated power electronic module (IPEM) which seeks to overcome the volumetric power density limitations of conventional packaging technologies. A key innovation has been the development of a substrate sandwich structure which permits double side cooling of the embedded dies whilst controlling the mechanical stresses both within the module and at the heat exchanger interface. A 3-phase inverter module has been developed, integrating the sandwich structures with high efficiency impingement coolers, delink capacitance and gate drive units. Full details of the IPEM construction and electrical evaluation are given in the paper. © 2007 IEEE.

Demonstration of a compact InGaAsP active crosspoint switch operating at 1.5 μm using novel reflective y-coupler components

An extremely compact active optoelectronic crosspoint switch, having overall dimensions of 400 μm×200 μm, is reported. The device provides unity facet-to-facet gain for both bar and cross state operation for TE or TM input signals.

Optimal control predicts human performance on objects with internal degrees of freedom.

On a daily basis, humans interact with a vast range of objects and tools. A class of tasks, which can pose a serious challenge to our motor skills, are those that involve manipulating objects with internal degrees of freedom, such as when folding laundry or using a lasso. Here, we use the framework of optimal feedback control to make predictions of how humans should interact with such objects. We confirm the predictions experimentally in a two-dimensional object manipulation task, in which subjects learned to control six different objects with complex dynamics. We show that the non-intuitive behavior observed when controlling objects with internal degrees of freedom can be accounted for by a simple cost function representing a trade-off between effort and accuracy. In addition to using a simple linear, point-mass optimal control model, we also used an optimal control model, which considers the non-linear dynamics of the human arm. We find that the more realistic optimal control model captures aspects of the data that cannot be accounted for by the linear model or other previous theories of motor control. The results suggest that our everyday interactions with objects can be understood by optimality principles and advocate the use of more realistic optimal control models for the study of human motor neuroscience.