D4.2 Intelligent D-Band wireless systems and networks initial designs

This deliverable gives the results of the ARIADNE project's Task 4.2: Machine Learning based network intelligence. It presents the work conducted on various aspects of network management to deliver system level, qualitative solutions that leverage diverse machine learning techniques. The different chapters present system level, simulation and algorithmic models based on multi-agent reinforcement learning, deep reinforcement learning, learning automata for complex event forecasting, system level model for proactive handovers and resource allocation, model-driven deep learning-based channel estimation and feedbacks as well as strategies for deployment of machine learning based solutions. In short, the D4.2 provides results on promising AI and ML based methods along with their limitations and potentials that have been investigated in the ARIADNE project

Design, Fabrication and Computational Characterization of a 3D Micro-Valve Built by Multi-Photon Polymerization

We report on the design, modeling and fabrication by multi-photon polymerization of a complex medical fluidic device. The physical dimensions of the built micro-valve prototype are compared to those of its computer-designed model. Important fabrication issues such as achieving high dimensional resolution and ability to control distortion due to shrinkage are presented and discussed. The operational performance of both multi-photon and CAD-created models under steady blood flow conditions was evaluated and compared through computational fluid dynamics analysis