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Chalmers University of Technology

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601 Projects, page 1 of 121
  • Open Access mandate for Publications and Research data
    Funder: EC Project Code: 661482
    Overall Budget: 185,857 EURFunder Contribution: 185,857 EUR
    Partners: Chalmers University of Technology

    The past decades have brought fascinating technological improvements of medical imaging techniques. This rapid development is accompanied by a growing need for computer based algorithms to align and extract markers from medical images. The days of heuristically engineered computer algorithms are, however, over; competitive, state-of-the-art medical imaging software must be based on rigorous mathematics to ensure accuracy, efficiency, and stability. Our research project lies at the forefront of computational anatomy (CA), a truly interdisciplinary field within medical imaging, combining differential equations theory, numerical analysis, computer vision, statistical methods, and differential geometry. CA is an emerging field that harbours a wealth of challenging problems. In particular, to develop image registration algorithms capable of handling heavily nonlinear deformations. In this project we construct image registration algorithms beyond state-of-the-art, adept of tasks where today's methods are inadequate. This is achieved by combining the knowledge of Professor Stig Larsson (scientist in charge) with the knowledge of Dr Klas Modin (experienced researcher). Larsson is a world-leading expert on numerical methods for partial differential equations. He has a large network of international collaborators as well as close connections to the medical imaging industry in Sweden. Modin has extensive expertise on geometric integration (GI), infinite-dimensional geometry, and CA, acquired via two post-doctoral positions at top research groups in two third countries. He thus brings state-of-the-art knowledge to the European research area. In particular, Modin's mastery of large deformation diffeomorphic metric matching (LDDMM) and Euler--Arnold equations is essential; it provides the link between image registration and PDEs. This link is the basis of the new, exciting methodology in the project: to apply state-of-the-art numerical PDE techniques to image registration.

  • Open Access mandate for Publications and Research data
    Funder: EC Project Code: 101065422
    Funder Contribution: 222,728 EUR
    Partners: Chalmers University of Technology

    In parallel to the evolution of 5G communication systems, 6G concepts are being developed in the academic community. In 6G, several key technical enablers are envisioned: i) mmWave and THz frequencies electromagnetic with extremely large bandwidths, and extremely large antenna arrays; ii) reconfigurable intelligent surfaces that control the propagation environment; and iii) machine learning to solve problems for which mathematical models are not sufficient. As location-aware communication (i.e., to optimize network efficiency and communication capacity by exploiting location, map, and trajectory information) is already a part of 5G, we expect that the 6G key enablers will also lead to high-accuracy sensing and localization and, in turn, improve communication quality. The goal of this project is to develop integrated sensing, localization, and communication systems for 6G, and the project comprises the following 3 work packages (WPs). In WP1, joint parameter estimation methods for the 6G channel are studied, and low-complexity methods will be developed based on the inherent high resolution of the 6G channel. By exploiting the estimated channel parameters of 6G signals, novel methods for estimating user state as well as sensing the time-varying propagation environment will be developed in WP2. We will design methods to use sensing and localization information from WP2 for initial beam search, beamspace processing, beam alignment, and power allocation in WP3. In doing so, we address several of the fundamental challenges in 6G communications and high-accuracy sensing and localization.

  • Open Access mandate for Publications
    Funder: EC Project Code: 813236
    Overall Budget: 150,000 EURFunder Contribution: 150,000 EUR
    Partners: Chalmers University of Technology

    Free-space optical communication links provide higher capacity and smaller beam divergence than their radio-frequency counterpart, and are increasingly being used for relatively short links often established for temporary purposes (e.g. outdoor sporting and concert events). They are also explored for extremely long reaches (e.g. between satellites, to the moon and beyond). In both cases, the sensitivity is fundamentally limited by the effect of diffraction, which results in the divergence of a free-space beam as it travels from the transmitter to the receiver. As there are practical limits on the size of the aperture permitted at both the transmitter and receiver, the diffraction results in a signal loss that limits the capacity and reach of the link. Our approach, which is to implement a unique noiseless optical amplifier in the receiver, is expected to result in a 40% transmission reach extension, or for a given reach target, reduce the aperture size of the optics (significant cost reduction) and increase the capacity. Our technique will help enable the transition from radio-frequency links to lightwave based links as it add significant performance benefits to the latter approach. We wish to use our new knowledge and expertise from our recent ERC AdG project to demonstrate, verify, and explore the commercial prospects of FSO transmission using phase-sensitive amplifiers in the receiver to improve the sensitivity, thus maximizing the possible link power budget, beyond what is possible with today’s approaches. We will work on market evaluation, technology verification, and commercialization strategy with the support from the Chalmers innovation office on our campus which has expertize on commercialization in the early stage. A goal of this project is to reach an agreement with commercial and/or institutional entities to pursue a field test of the PSA-based FSO technology.

  • Funder: EC Project Code: 307544
    Partners: Chalmers University of Technology
  • Funder: EC Project Code: 625121
    Partners: Chalmers University of Technology