More Like this

1. Recruiting Teachers for VolsTeach for Appalachia

   Kim, N.; Hodge, L.; King, S. (July 2021, Southeastern Robert Noyce Conference)

   null (Ed.)

   This presentation poster summarizes the recruitment efforts, insights gained, and lessons learned through the VolsTeach for Appalachia project that focuses on recruiting and preparing community college students in becoming STEM teachers in East Tennessee. 

   more » « less
2. Prioritization Framework for Rockfall Countermeasures for Rock-Cut Slopes for Rural Roads

   https://doi.org/10.1061/(ASCE)CO.1943-7862.0002139  

   Yoon, Yoojung; GangaRao, Hota (October 2021, Journal of Construction Engineering and Management)

   null (Ed.)
3. AI for Security and Security for AI

   https://doi.org/10.1145/3422337.3450357  

   Bertino, Elisa; Kantarcioglu, Murat; Akcora, Cuneyt Gurcan; Samtani, Sagar; Mittal, Sudip; Gupta, Maanak (April 2021, ACM Conference on Datta and Application Security and Privacy (CODASPY) 2021)

   null (Ed.)
4. 2023 roadmap for materials for quantum technologies

   https://doi.org/10.1088/2633-4356/aca3f2  

   Becher, Christoph; Gao, Weibo; Kar, Swastik; Marciniak, Christian D; Monz, Thomas; Bartholomew, John G; Goldner, Philippe; Loh, Huanqian; Marcellina, Elizabeth; Goh, Kuan Eng; et al (January 2023, Materials for Quantum Technology)

   Abstract Quantum technologies are poised to move the foundational principles of quantum physics to the forefront of applications. This roadmap identifies some of the key challenges and provides insights on material innovations underlying a range of exciting quantum technology frontiers. Over the past decades, hardware platforms enabling different quantum technologies have reached varying levels of maturity. This has allowed for first proof-of-principle demonstrations of quantum supremacy, for example quantum computers surpassing their classical counterparts, quantum communication with reliable security guaranteed by laws of quantum mechanics, and quantum sensors uniting the advantages of high sensitivity, high spatial resolution, and small footprints. In all cases, however, advancing these technologies to the next level of applications in relevant environments requires further development and innovations in the underlying materials. From a wealth of hardware platforms, we select representative and promising material systems in currently investigated quantum technologies. These include both the inherent quantum bit systems and materials playing supportive or enabling roles, and cover trapped ions, neutral atom arrays, rare earth ion systems, donors in silicon, color centers and defects in wide-band gap materials, two-dimensional materials and superconducting materials for single-photon detectors. Advancing these materials frontiers will require innovations from a diverse community of scientific expertise, and hence this roadmap will be of interest to a broad spectrum of disciplines. 

   more » « less
5. Algorithms for Computing Closest Points for Segments

   https://doi.org/10.4230/LIPIcs.STACS.2024.58  

   Wang, Haitao (March 2024, Schloss Dagstuhl – Leibniz-Zentrum für Informatik)

   Beyersdorff, Olaf; Kanté, Mamadou Moustapha; Kupferman, Orna; Lokshtanov, Daniel (Ed.)

   Given a set P of n points and a set S of n segments in the plane, we consider the problem of computing for each segment of S its closest point in P. The previously best algorithm solves the problem in n^{4/3}2^{O(log^*n)} time [Bespamyatnikh, 2003] and a lower bound (under a somewhat restricted model) Ω(n^{4/3}) has also been proved. In this paper, we present an O(n^{4/3}) time algorithm and thus solve the problem optimally (under the restricted model). In addition, we also present data structures for solving the online version of the problem, i.e., given a query segment (or a line as a special case), find its closest point in P. Our new results improve the previous work. 

   more » « less