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  1. ; ; ; ( , Geophysical Research Letters)
    Free, publicly-accessible full text available February 16, 2023
  2. ; ; ; ; ; ; ( , Proceedings of the AAAI Conference on Artificial Intelligence)
    Free, publicly-accessible full text available February 1, 2023
  3. ; ; ; ; ; ; ( , ACM Conference on Economics and Computation)
    Free, publicly-accessible full text available January 1, 2023
  4. ; ; ; ; ; ; ; ; ; ; et al ( , Monthly Notices of the Royal Astronomical Society)
    ABSTRACT We report on the discovery and localization of fast radio bursts (FRBs) from the MeerTRAP project, a commensal fast radio transient-detection programme at MeerKAT in South Africa. Our hybrid approach combines a coherent search with an average field-of-view (FoV) of 0.4 $\rm deg^{2}$ with an incoherent search utilizing a FoV of ∼1.27 $\rm deg^{2}$ (both at 1284 MHz). Here, we present results on the first three FRBs: FRB 20200413A (DM = 1990.05 pc cm−3), FRB 20200915A (DM = 740.65 pc cm−3), and FRB 20201123A (DM = 433.55 pc cm−3). FRB 20200413A was discovered only in the incoherent beam. FRB 20200915A (also discovered only in the incoherent beam) shows speckled emission in the dynamicmore »spectrum, which cannot be explained by interstellar scintillation in our Galaxy or plasma lensing, and might be intrinsic to the source. FRB 20201123A shows a faint post-cursor burst of about 200 ms after the main burst and warrants further follow-up to confirm whether it is a repeating FRB. FRB 20201123A also exhibits significant temporal broadening, consistent with scattering, by a turbulent medium. The broadening exceeds from what is predicted for the medium along the sightline through our Galaxy. We associate this scattering with the turbulent medium in the environment of the FRB in the host galaxy. Within the approximately 1 arcmin localization region of FRB 20201123A, we identify one luminous galaxy (r ≈ 15.67; J173438.35-504550.4) that dominates the posterior probability for a host association. The galaxy’s measured properties are consistent with other FRB hosts with secure associations.« less
    Free, publicly-accessible full text available June 16, 2023
  5. ; ; ; ( , Proceedings of the Second Workshop on ScProceedings of the Second Workshop on Scholarly Document Processing, 2021 Association for Computational Linguistics)
    Presentation slides describing the content of scientific and technical papers are an efficient and effective way to present that work. However, manually generating presentation slides is labor intensive. We propose a method to automatically generate slides for scientific papers based on a corpus of 5000 paper-slide pairs compiled from conference proceedings websites. The sentence labeling module of our method is based on SummaRuNNer, a neural sequence model for extractive summarization. Instead of ranking sentences based on semantic similarities in the whole document, our algorithm measures importance and novelty of sentences by combining semantic and lexical features within a sentence window.more »Our method outperforms several baseline methods including SummaRuNNer by a significant margin in terms of ROUGE score.« less
    Accepted Manuscript Full Text Available
  6. ; ; ; ; ; ( , Physics of Fluids)
    Full Text Available 
  7. ( , Journal of construction engineering and management)
    de la Garza, J.M. (Ed.)
    There has been an increasing demand in building information modeling (BIM) for structural analysis. However, model exchange between architectural software and structural analysis software, which is an essential task in a construction project, is not fully interoperable yet. Various studies showed missing information and information inconsistency problems during conversion of models between different software; the lack of foundational methods enabling a seamless BIM interoperability between architectural design and structural analysis is evident. To address this gap and facilitate more use of BIM for structural analysis, the authors develop invariant signatures for architecture, engineering, and construction (AEC) objects and propose amore »new data-driven method to use invariant signatures for solving practical problems in BIM applications. The invariant signatures and the data-driven method were tested in developing the interoperable BIM support tool for structural analysis through an experiment. Ten models were created/adopted and used in this experiment, including five models for training and five models for testing. An information validation and mapping algorithm was developed based on invariant signatures and training models, which was then evaluated in the testing models. Compared with a manually created gold standard, results showed that the desired structural analysis software inputs were successfully generated using the algorithm with high accuracy. The invariant signatures of AEC objects can therefore be expected to serve as the foundation of seamless BIM interoperability.« less
    Full Text Available 
  8. ; ; ; ; ; ( , The Web conference)
    Accepted Manuscript Full Text Available
  9. ( , Proceedings of the First Workshop on Scholarly Document Processing)
    Acknowledgements are ubiquitous in scholarly papers. Existing acknowledgement entity recognition methods assume all named entities are acknowledged. Here, we examine the nuances between acknowledged and named entities by analyzing sentence structure. We develop an acknowledgement extraction system, ACKEXTRACT based on open-source text mining software and evaluate our method using manually labeled data. ACKEXTRACT uses the PDF of a scholarly paper as input and outputs acknowledgement entities. Results show an overall performance of F1 = 0:92. We built a supplementary database by linking CORD-19 papers with acknowledgement entities extracted by ACKEXTRACT including persons and organizations and find that only up tomore »50–60% of named entities are actually acknowledged. We further analyze chronological trends of acknowledgement entities in CORD-19 papers. All codes and labeled data are publicly available at https://github.com/ lamps-lab/ackextract.« less
    Accepted Manuscript Full Text Available
  10. ; ; ; ; ; ; ( , 2020 IEEE International Conference on Big Data (Big Data))
    The vastness of the web imposes a prohibitive cost on building large-scale search engines with limited resources. Crawl frontiers thus need to be optimized to improve the coverage and freshness of crawled content. In this paper, we propose an approach for modeling the dynamics of change in the web using archived copies of webpages. To evaluate its utility, we conduct a preliminary study on the scholarly web using 19,977 seed URLs of authors’ homepages obtained from their Google Scholar profiles. We first obtain archived copies of these webpages from the Internet Archive (IA), and estimate when their actual updates occurred.more »Next, we apply maximum likelihood to estimate their mean update frequency ( ) values. Our evaluation shows that   values derived from a short history of archived data provide a good estimate for the true update frequency in the short-term, and that our method provides better estimations of updates at a fraction of resources compared to the baseline models. Based on this, we demonstrate the utility of archived data to optimize the crawling strategy of web crawlers, and uncover important challenges that inspire future research directions.« less
    Accepted Manuscript Full Text Available