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Data for: Ok Google, What Am I Doing? Acoustic Activity Recognition Bounded by Conversational Assistant Interactions
No full textAn annotated dataset of audio interactions with a conversational assistant with background sounds of 19 activities.
Abstract: Conversational assistants in the form of stand-alone devices such as Amazon Echo and Google Home have become popular and embraced by millions of people. By serving as a natural interface to services ranging from home automation to media players, conversational assistants help people perform many tasks with ease, such as setting timers, playing music and managing to-do lists. While these systems offer useful capabilities, they are largely passive and unaware of the human behavioral context in which they are used. In this work, we explore how off-the-shelf conversational assistants can be enhanced with acoustic-based human activity recognition by leveraging the short interval after a voice command is given to the device. Since always-on audio recording can pose privacy concerns, our method is unique in that it does not require capturing and analyzing any audio other than the speech-based interactions between people and their conversational assistants. In particular, we leverage background environmental sounds present in these short duration voice-based interactions to recognize activities of daily living. We conducted a study with 14 participants in 3 different locations in their own homes. We showed that our method can recognize 19 different activities of daily living with average precision of 84.85% and average recall of 85.67% in a leave-one-participant-out performance evaluation with 30-second audio clips bound by the voice interactions.
IRB approved under ID: 2016020035-MODCR0
Video - "Gene Drive: would it be a good or bad idea for managing agricultural pests?"
No full textThis video provides information about gene drive, a new genetic-based technology in the early stages of research. Among other potential applications, gene drive is being considered for managing agricultural pests. Why might gene drive be used for this? What are some of the downsides? This video was included in a survey of stakeholder organizations associated with agriculture and pest management in Texas and in a public opinion survey that was representative of both the U.S. national population and the population of Texas
Total water storage extremes index from GRACE and GRACE-FO missions
No full textTotal water storage extremes index from GRACE and GRACE-FO missions
• TWS: total water storage is the sum of (Soil moisture+ surface water+snow water equivalent+glaciers+groundwater)
• Data based on GRACE and GRACE-FO missions estimates of TWS
GRACE/GRACE-FO - Gravity Recovery and Climate Experiment (utexas.edu)
Contents of Netcdf
• “lon”: longitudes
• “lat”: latitudes
• “time” Days since 2002_01_01
• “TWS_Extremes_unit_mm” is the extreme change in the total storage relative to the normal climatology between 2002/04 and 2021/08. with unit mm
• “TWS_Extremes_index” Index of the extremes (unitless);
Positive values: above normal storage changes (Floods)
Negative values: below normal storage changes (Droughts)
• Data range: 04/2002 – 08/202
Actual Use of Robots for COVID-19 response
No full textThis dataset contains 338 instances of robots used explicitly in response to COVID-19 from 24 Jan, 2020, to 23 Jan, 2021, in 48 countries
Data Archive for: Goudge et al. (2021), The importance of lake breach floods for valley incision on early Mars.
No full textDataset archive for Goudge et al. (2021), The importance of lake breach floods for valley incision on early Mars, Nature, doi: 10.1038/s41586-021-03860-1. Dataset contains four compressed .TAR.GZ files, each with a distinct component of the archived dataset, fully explained in the included README file
Hammer Model - BWSN-II Subsection
No full textFiles with Bentley Hammer model for the transient simulation of a subsection of the BWSN-II water distribution network
Delaware Basin Deterministic Fault Slip Potential ArcMap Shape Files
No full textData set includes ArcMap shape files and associated ReadMe file containing the basement-rooted and shallow normal faults and the deterministic fault slip potential for the paper: Hennings, P. H., Dvory, N., Horne, E. A., LI, P., Savvaidis, A., Zoback, M., (2021) Stability of the Fault Systems that Host Induced Earthquakes in the Delaware Basin of West Texas and Southeast New Mexico, The Seismic Record
Replication Data for: Madrid-Morales, D., & Wasserman, H. (2022). Research Methods in Comparative Disinformation Studies. In H. Wasserman & D. Madrid-Morales (Eds.), Disinformation in the Global South. Wiley.
No full textDataset including information from 3,864 academic articles published in high-impact indexed journals from 2000 to 2020 that includes the words "disinformation", "misinformation" and/or "fake news". Information was retrieved from JSTOR and EbscoHost databases, as well as scraped from the websites of Taylor and Francis and SAGE. This collection also includes the R language script using to analyse the data, included in the chapter "Research Methods in Comparative Disinformation Studies.
The data (in a csv format) includes the following fields:
Journal Title (journal_title)
Article Title (article_title)
Publication Year (article_year)
Article Abstract (article_abstract)
Article URL (article_url)
Article DOI (article_doi)
Source Database (source_db)
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