Open-path near-IR dual-comb spectra collected at Mauna Loa Observatory in spring 2021, fit with different absorption models (eg HITRAN) and compared against NOAA GML's record.

The data in this dataset corresponds to the results in the paper entitled "Towards System Level Simulations of Public Safety Applications over 5G NR Sidelink" to appear in the proceeding of the 2024 IEEE World Forum on Public Safety Technology (WF-PST) conference.

The Health Misinformation track aims to (1) provide a venue for research on retrieval methods that promote better decision making with search engines, and (2) develop new online and offline evaluation methods to predict the decision making quality induced by search results. Consumer health information is used as the domain of interest in the track.

This data publication contains the raw, extracted, and derived (e.g., peak areas) mass spectrometry data for explosives, propellants, and post-blast debris. These samples were analyzed by wipe-based collection, thermal desorption, and in-line dielectric barrier discharge ionization coupled to a transportable time-of-flight mass spectrometer. Samples include RDX, HMX, TNT, Tetryl, PETN, and NG explosives, black powder and black powder substitutes, and post-blast debris from devices based on dynamite, black powder, and blasting emulsion explosive. 

Dataset for figures in the publication, "Using EM Side-Channels Near a Bluetooth Server Implementation to Monitor Bit-Level Leakages in BLE Communications Channels," by V.V Iyer and J.D. Rezac (GLSVLSI 2024). The abstract for this publication is as follows: Unintentional electromagnetic (EM) emanations from general purpose embedded systems have been comprehensively studied as data recovery and monitoring tools for hardware security.

iKAT is the successor to the TREC Conversational Assistance Track (CAsT). The fourth year of CAST aimed to add more conversational elements to the interaction streams, by introducing mixed initiatives (clarifications, and suggestions) to create multi-path, multi-turn conversations for each topic. TREC iKAT evolves CAsT into a new track to signal this new trajectory. iKAT aims to focus on supporting multi-path, multi-turn, multi-perspective conversations.

The product search track focuses on IR tasks in the world of product search and discovery. This track seeks to understand what methods work best for product search, improve evaluation methodology, and provide a reusable dataset which allows easy benchmarking in a public forum.

This template presents a structured methodology for describing and assessing automated vehicle (AV) features, with a focus on ensuring comprehensive standardization and reproducibility in testing across various scenarios. The document delineates a systematic approach to integrating operational design domains (ODD), levels of automation, and behaviors into AV feature descriptions.

The Tip-of-the-Tongue (ToT) Track focuses on the known-item identification task where the searcher has previously experienced or consumed the item (e.g., a movie) but cannot recall a reliable identifier (i.e., It's on the tip of my tongue...). Unlike traditional ad-hoc keyword-based search, these information requests tend to be natural-language, verbose, and complex containing a wide variety of search strategies such as multi-hop reasoning, and frequently express uncertainty and suffer from false memories.

This dataset contains data used in the investigation of Universally Unique Identifiers (UUIDs) that will enable a standards-based digital thread of product data in ISO 10303-242. Included are EXPRESS schema used for implementation and .stp files that were exported from native CAD (CATIA V5, Creo, and NX). UUIDs were assigned to CAD features during .stp export for each of the four design iterations.