Maryland Shared Open Access Repository

MD-SOAR is a shared digital repository platform for eleven colleges and universities in Maryland. It is currently funded by the University System of Maryland and Affiliated Institutions (USMAI) Library Consortium (usmai.org) and other participating partner institutions. MD-SOAR is jointly governed by all participating libraries, who have agreed to share policies and practices that are necessary and appropriate for the shared platform. Within this broad framework, each library provides customized repository services and collections that meet local institutional needs. Please follow the links below to learn more about each library's repository services and collections.

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Recently Added

  • Hotels Check in to Historic Buildings: Quantitative and Qualitative Success Factors For Adaptive Reuse of Historic Buildings to Hotels 

    Maruya, Harvey (2019-06-18)
    Economics drive projects that rehabilitate historic buildings, but environmental and social factors are just as important in the balancing act of benefits that a successful project can provide. The premise of this study ...
  • Modeling Atmosphere-Ocean Radiative Transfer: A PACE Mission Perspective 

    Chowdhary, Jacek; Zhai, Peng-Wang; Boss, Emmanuel; Dierssen, Heidi M.; Frouin, Robert; Ibrahim, Amir; Lee, Zhongping; Remer, Lorraine Ann; Twardowski, Michael; Xu, Feng; Zhang, Xiaodong; Ottaviani, Matteo; Espinosa, William Reed; Ramon, Didier (Frontiers Media S.A, 2019-06-18)
    The research frontiers of radiative transfer (RT) in coupled atmosphere-ocean systems are explored to enable new science and specifically to support the upcoming Plankton, Aerosol, Cloud ocean Ecosystem (PACE) satellite ...
  • 4 pillars of college success in science 

    Hrabowski, Freeman (TED Conferences, LLC, 2013-02)
    At age 12, Freeman Hrabowski marched with Martin Luther King. Now he's president of the University of Maryland, Baltimore County (UMBC), where he works to create an environment that helps under-represented students -- ...
  • Minimizing Classification Energy of Binarized Neural Network Inference for Wearable Devices 

    Hosseini, Morteza; Paneliya, Hirenkumar; Kallakuri, Uttej; Khatwani, Mohit; Mohsenin, Tinoosh (2019-03-25)
    In this paper, we propose a low-power hardware for efficient deployment of binarized neural networks (BNNs) that have been trained for physiological datasets. BNNs constrain weights and feature-map to 1 bit, can pack in ...
  • A method for quantifying near range point source induced O₃ titration events using Co-located Lidar and Pandora measurements 

    Gronoff, Guillaume; Robinson, Joseph; Berkoff, Timothy; Swap, Robert; Farris, Betsy; Schroeder, Jeremy; Halliday, Hannah S.; Knepp, Travis; Spinei, Elena; Carrion, William; Adcock, Edward E.; Johns, Zachary; Allen, Danette; Pippin, Margaret (Elsevier Ltd., 2019-02-19)
    A ground-based tropospheric O3 lidar with unique vertical near-range capabilities was deployed in support of the larger OWLETS 2017 campaign on the Chesapeake Bay Bridge Tunnel, at the mouth of the Chesapeake Bay. It was ...

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