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In this project, we investigate the possibility of using information from social media platforms to help predict critical information about Ebola from baseline data. For the first time, we have a unique dataset consisting of Ebola-related posts from Twitter, a social media platform with over 300M active users globally. We have developed a baseline model based on Twitter data to predict Ebola infections and deaths. This baseline model is used to predict Ebola cases in the…
This effort analyzed a dataset of approximately 1 billion smart meter readings collected over the past 2 years for the purpose of determining the effects of solar radiation on air quality within an urban setting. The atmospheric chemical composition at each station was analyzed to characterize the pollution-related air quality trends. Furthermore, the meteorological conditions surrounding each station were also analyzed to deternm…
The University of Wisconsin Probabilistic Downscaling (UWPD) is a statistically downscaled dataset based on the Coupled Model Intercomparison Project Phase 5 (CMIP5) climate models. UWPD consists of three variables, daily precipitation and maximum and minimum temperature. The spatial resolution is 0.1×0.1 degree resolution for the United States and southern Canada east of the Rocky Mountains.
The downscaling methodology is not deterministic. Instead, to properly capture unexplained variability and extreme events, the methodology predicts a spatially and temporally varying Probability Density Function (PDF) for each variable. Statistics such as the mean, mean PDF and annual maximum statistics can be calculated directly from the daily PDF and these statistics are included in the dataset. In addition, standard, raw data is created by randomly sampling from the PDFs to create a realization of the local scale given the large-scale from the climate model. There are 3 realizations for temperature and 14 realizations for precipitation. …
The specified fuel consumption and emission data has been determined according to the measurement procedures specified by law. As from 1st September 2017, some new vehicles are already being type-approved according to the Worldwide Harmonized Light Vehicles Test Procedure (WLTP), a more realistic test procedure for measuring fuel consumption and CO2 emissions. Since 1st September 2018, WLTP has also replaced the New European Driving Cycle (NEDC) for light commercial vehicles. In cases where the fuel consumption and emission values are specified as value ranges, these do not refer to a particular individual vehicle and do not constitute part of the sales offering. They are solely used for comparison purposes between the different vehicle types.
The specified fuel consumption and emission data has been determined according to the measurement procedures specified by law. As from 1st September 2017, some new vehicles are already being type-approved according to the Worldwide Harmonized Light Vehicles Test Procedure (WLTP), a more realistic test procedure for measuring fuel consumption and CO2 emissions. Since 1st September 2018, WLTP has also replaced the New European Driving Cycle (NEDC) for light commercial vehicles.
AgricultureVision/2020 Visions is to be an image dataset that is multi-spectral with two, three, and four bands, high-resolution, with multiple types of annotations. The original dataset affiliated with the 2020 CVPR paper includes 94,986 512x512images sampled from 3,432 farmland with nine types of annotations: double plant, drydown, endrow, nutrient deficiency, planter skip, storm damage, water, waterway and weed cluster. All of these patterns have substantial impacts on field conditions and the final yield. These images were captured between 201…
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