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6 results for “UPC++”
Global Ionosphere Maps of vertical electron content combined in real-time from the RT-GIMs of CAS, CNES, UPC-IonSAT, and WHU International GNSS Service (IGS) centers (from Dec 1, 2020, to March 1, 2021)
<p>The datasets consists on 91 daily files, in IONEX format (<a href="http://ftp.aiub.unibe.ch/ionex/draft/ionex11.pdf">http://ftp.aiub.unibe.ch/ionex/draft/ionex11.pdf</a>) , corresponding to three months of global ionospheric maps (GIM) of vertical total electron content (VTEC) computed in real-time from the assessed and combined real-time GIMs generated by four analysis centers. Indeed, the Real-Time Working Group (RTWG) of International GNSS Service (IGS) is dedicated to providing high-quality data, high-accuracy products for Global Navigation Satellite System (GNSS) navigation, positioning, timing, and Earth observations. As one of the important part of real-time products, the IGS combined Real-Time Global Ionosphere Map (RT-GIM) have been generated by real-time weighting technique with the help of RT-GIMs from IGS real-time ionosphere centers including the Chinese Academy of Sciences (CAS), Centre National d’Etudes Spatiales (CNES), Universitat Politècnica de Catalunya (UPC), and Wuhan University (WHU). Compared with IGS rapid Global Ionosphere Maps (GIMs) (corg, ehrg, emrg, esrg, igrg, jprg, uhrg, uprg, uqrg, whrg) and IGS final combined GIM (igsg), the IGS combined RT-GIM (irtg) is equivalent to the post-processed GIMs and even better than some rapid GIMs. The IGS RT-GIMs are reliable sources of real-time global VTEC information and has great potential for real-time applications including range error correction for transionospheric radio signals (such as GNSS positioning, search and rescue, air traffic, radar altimetry, and radioastronomy), the monitoring of space weather (such as geomagnetic and ionospheric storms, ionospheric disturbance) and detection of natural hazards on a global scale (such as hurricanes/typhoons, ionospheric anomalies associated with earthquakes)</p>
Fastprk2 - Data (pilot Barcelona - UPC)
<p>Raw data from the project pilot in Barcelona (UPC premises) in 2018. </p> <p>12 FP-2 sensors have been tested.</p> <p><strong>Venue: </strong> </p> <p>UPC</p> <p><em>Calle Jordi Girona, 31</em></p> <p><em>08034 Barcelona, Spain</em></p> <p><em>GPS coordinates: 41.3889784344569,2.1138623938485956</em></p>
End of Year Biomass for the 1st UPC Inundation Experiment in Upper Phillips Creek marsh 1999-2014
The objective of this study was to determine the individual and compound effects of inundation and wrack deposition on high marsh community structure. Inundation pattern and wrack presence were manipulated individually and in combination, in two neighboring communities (a Juncus roemerianus-dominated and an adjacent Spartina patens and Distichlis spicata-dominated) in 1994 and 1995. Aboveground biomass was used to assess marsh response to the stressors of increased inundation and wrack presence (Tolley and Christian 1999) and continues to be collected from these experimental plots on an annual basis. Details of initial manipulation may be found in: Tolley, P.M. and R.R. Christian. 1999. Effects of increased inundation and wrack deposition on a high salt marsh plant community. Estuaries 22:944-954.
End of Year Biomass for the 2nd UPC Inundation Experiment in Upper Phillips Creek marsh 1999-2010
The objective of this study is to determine the effect of increasing inundation on healthy (in-tack turf) and unhealthy (hollow and hummock topography) high marsh habitat. Brinson et al. (1995) developed a model representing the change that occurs in ecosystem state (or habitat type) along the shorezone, from the forest -> high marsh -> low marsh -> mud flat, in response to the increased inundation caused by rising sea-level. They suggested that a seaward shift in ecosystem state is largely dependent on local slope and sediment supply. The states are associated with the dominant vegetation found within each. The most seaward (lowest in elevation) state is the mud flat. It is frequently inundated by tide and typically supports algal species. The next landward state is the mineral low marsh; it is dominated by Spartina alterniflora and is typically flooded at high tide. Sediments here may be largely mineral in origin. The next landward state is the high marsh; it may be dominated by S. patens, Distichlis spicata, and Juncus roemerianus. It is occasionally inundated by high tides and the soil is usually organic. The transition zone between the high marsh and the forest is typically dominated by Iva frutescens, Baccharis hamifolia, and Juniperus virginiana. It is only inundated during severe storm surges. The forest may be dominated by either pines or hardwoods and is again flooded with sea water only by storm surges. Goals: The goal of this long-term project is to evaluate how sea-level rise affects marsh evolution and ecosystem state change. Seventeen sites along Virginia's eastern shore have been selected to study marsh evolution on both the mainland and the barrier islands. These sites will be available for long-term seasonal to annual observations. Some sites will also be available for experimentation and short-term studies. The initial project is to establish initial site characteristics.
Dataset: Universe Pharmaceuticals INC (UPC) Stock Performance
This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.
UPC Benchmark structure.
<p>This dataset was collected during the experimental evaluation of the anomaly-aware monitoring method and has been published to support the related publication titled On Anomaly-Aware Structural Health Monitoring at the Extreme Edge authored by David Arnaiz<br> (corresponding author david.arnaiz@upc.edu), Eduard Alarcón, Francesc Moll, and Xavier Vilajosana.</p> <p>The benchmark structure is a steel frame reduced-scale model structure, built and maintained by the Department of Civil and Environmental Engineering at the Polytechnic University of Catalonia (UPC). The dataset was obtained using two sensor nodes placed on the structure, and contains 275 different monitoring events. The dataset contains the 3-D acceleration data measured by the nodes, the feature vector computed by the nodes, and (for the test cases) the inference results from their anomaly detection models.</p> <p>More information about the dataset can be seen in the README file and the corresponding publication.</p> <p>This work has been made possible thanks to the funding of the Agència de Gestió d’Ajuts Universitaris de Recerca (AGAUR), grand number 2019 DI 075.</p>
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