Communications
Here we introduce so-far the largest subject-rated database of its kind, namely, "Effect of Millet vegetation on path-loss between CC2538 SoC 32-bit Arm Cortex-M3 based sensor nodes operating at 2.4 GHz Radio Frequency (RF)". This database contains received signal strength measurements collected through campaigns in the IEEE 802.15.4 standard precision agricultural monitoring infrastructure developed for millet crop monitoring from period 03/06/2020 to 04/10/2020.
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Cartesian multipole moments in HFSS
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This dataset is a set of eighteen directed networks that represents message exchanges among Twitter accounts during eighteen crisis events. The dataset comprises 645,339 anonymized unique user IDs and 1,396,709 edges that are labeled with respect to Plutchik's basic emotions (anger, fear, sadness, disgust, joy, trust, anticipation, and surprise) or "neutral" (if a tweet conveys no emotion).
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Appendix for the submitted paper
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Abstract
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This dataset contains requests execution times for comparison of direct requests and requests via API gateway to test API.
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Radio-frequency noise mapping data collected from Downtown, Back Bay and North End neighborhoods within Boston, MA, USA in 2018 and 2019.
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Wide area control (WAC) in smart grid requires low-latency communications across the grid to transfer various control commands and Phasor Measurement Unit (PMU) measurements. Smart grid communications are generally implemented between multiple control centers, transformer substations and control centers, and power plants and control centers.
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The diversity of video delivery pipeline poses a grand challenge to the evaluation of adaptive bitrate (ABR) streaming algorithms and objective quality-of-experience (QoE) models.
Here we introduce so-far the largest subject-rated database of its kind, namely WaterlooSQoE-IV, consisting of 1350 adaptive streaming videos created from diverse source contents, video encoders, network traces, ABR algorithms, and viewing devices.
We collect human opinions for each video with a series of carefully designed subjective experiments.
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This Dataset includes the lsit of articles indexed by Google Scholar from 2003-2019, realted to: Edge Computing, Fog Computing, Multi-Access Edge Computing, Mobile Cloud Computing.
The data has been cleaned by removing duplicates, non-english articles, un-realted articles (i.e. computing edges in a picture is not about Edge Computing) and articles that weren't directly or easily accessable.
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