Publications

The computation and storage requirements of Deep Neural Networks (DNNs) make them challenging to deploy on edge devices, which often have limited resources.

While Lisp workstations provide a wonderfully productive development environment, they are expensive, often forcing the choice of another target machine for deployment.

Most UNIX(TM) system software can be easily moved from one machine to another, re-compiled, and run without difficulty.

Smartphone based indoor localization caught massive interest of the localization community during recent years.

Classical logics and Datalog-related logics have both been proposed as underlying formalisms for the Semantic Web.

We show that it is, in principle, possible to perform local realism violating experiments of the Hardy type in which only position and momentum measurements are made on two particles emanating from

High-accuracy positioning enables emerging of new vertical markets for the forthcoming fifth generation (5G) mobile networks.

Among the key differentiators of 6G compared to 5G will be the increased emphasis on radio based positioning and sensing.

We study positioning of high-speed trains in 5G new radio (NR) networks by utilizing specific NR synchronization signals.

We report on the relaxation of positive muons (mu(+)) stopped in a single crystal of sodium fluoride at 15 +-0.2K.