18,680 research outputs found
The On-Site Analysis of the Cherenkov Telescope Array
The Cherenkov Telescope Array (CTA) observatory will be one of the largest
ground-based very high-energy gamma-ray observatories. The On-Site Analysis
will be the first CTA scientific analysis of data acquired from the array of
telescopes, in both northern and southern sites. The On-Site Analysis will have
two pipelines: the Level-A pipeline (also known as Real-Time Analysis, RTA) and
the level-B one. The RTA performs data quality monitoring and must be able to
issue automated alerts on variable and transient astrophysical sources within
30 seconds from the last acquired Cherenkov event that contributes to the
alert, with a sensitivity not worse than the one achieved by the final pipeline
by more than a factor of 3. The Level-B Analysis has a better sensitivity (not
be worse than the final one by a factor of 2) and the results should be
available within 10 hours from the acquisition of the data: for this reason
this analysis could be performed at the end of an observation or next morning.
The latency (in particular for the RTA) and the sensitivity requirements are
challenging because of the large data rate, a few GByte/s. The remote
connection to the CTA candidate site with a rather limited network bandwidth
makes the issue of the exported data size extremely critical and prevents any
kind of processing in real-time of the data outside the site of the telescopes.
For these reasons the analysis will be performed on-site with infrastructures
co-located with the telescopes, with limited electrical power availability and
with a reduced possibility of human intervention. This means, for example, that
the on-site hardware infrastructure should have low-power consumption. A
substantial effort towards the optimization of high-throughput computing
service is envisioned to provide hardware and software solutions with
high-throughput, low-power consumption at a low-cost.Comment: In Proceedings of the 34th International Cosmic Ray Conference
(ICRC2015), The Hague, The Netherlands. All CTA contributions at
arXiv:1508.0589
Engineering technology for networks
Space Network (SN) modeling and evaluation are presented. The following tasks are included: Network Modeling (developing measures and metrics for SN, modeling of the Network Control Center (NCC), using knowledge acquired from the NCC to model the SNC, and modeling the SN); and Space Network Resource scheduling
Volcanic Hot-Spot Detection Using SENTINEL-2: A Comparison with MODISâMIROVA Thermal Data Series
In the satellite thermal remote sensing, the new generation of sensors with high-spatial resolution SWIR data open the door to an improved constraining of thermal phenomena related to volcanic processes, with strong implications for monitoring applications. In this paper, we describe a new hot-spot detection algorithm developed for SENTINEL-2/MSI data that combines spectral indices on the SWIR bands 8a-11-12 (with a 20-meter resolution) with a spatial and statistical analysis on clusters of alerted pixels. The algorithm is able to detect hot-spot-contaminated pixels (S2Pix) in a wide range of environments and for several types of volcanic activities, showing high accuracy performances of about 1% and 94% in averaged omission and commission rates, respectively, underlining a strong reliability on a global scale. The S2-derived thermal trends, retrieved at eight key-case volcanoes, are then compared with the Volcanic Radiative Power (VRP) derived from MODIS (Moderate Resolution Imaging Spectroradiometer) and processed by the MIROVA (Middle InfraRed Observation of Volcanic Activity) system during an almost four-year-long period, January 2016 to October 2019. The presented data indicate an overall excellent correlation between the two thermal signals, enhancing the higher sensitivity of SENTINEL-2 to detect subtle, low-temperature thermal signals. Moreover, for each case we explore the specific relationship between S2Pix and VRP showing how different volcanic processes (i.e., lava flows, domes, lakes and open-vent activity) produce a distinct pattern in terms of size and intensity of the thermal anomaly. These promising results indicate how the algorithm here presented could be applicable for volcanic monitoring purposes and integrated into operational systems. Moreover, the combination of high-resolution (S2/MSI) and moderate-resolution (MODIS) thermal timeseries constitutes a breakthrough for future multi-sensor hot-spot detection systems, with increased monitoring capabilities that are useful for communities which interact with active volcanoes
Automation of surface observations program
At present, surface weather observing methods are still largely manual and labor intensive. Through the nationwide implementation of Automated Surface Observing Systems (ASOS), this situation can be improved. Two ASOS capability levels are planned. The first is a basic-level system which will automatically observe the weather parameters essential for aviation operations and will operate either with or without supplemental contributions by an observer. The second is a more fully automated, stand-alone system which will observe and report the full range of weather parameters and will operate primarily in the unattended mode. Approximately 250 systems are planned by the end of the decade. When deployed, these systems will generate the standard hourly and special long-line transmitted weather observations, as well as provide continuous weather information direct to airport users. Specific ASOS configurations will vary depending upon whether the operation is unattended, minimally attended, or fully attended. The major functions of ASOS are data collection, data processing, product distribution, and system control. The program phases of development, demonstration, production system acquisition, and operational implementation are described
Modeling an ontology on accessible evacuation routes for emergencies
Providing alert communication in emergency situations is vital to reduce the number of victims. However, this is a challenging goal for researchers and professionals due to the diverse pool of prospective users, e.g. people with disabilities as well as other vulnerable groups. Moreover, in the event of an emergency situation, many people could become vulnerable because of exceptional circumstances such as stress, an unknown environment or even visual impairment (e.g. fire causing smoke). Within this scope, a crucial activity is to notify affected people about safe places and available evacuation routes. In order to address this need, we propose to extend an ontology, called SEMA4A (Simple EMergency Alert 4 [for] All), developed in a previous work for managing knowledge about accessibility guidelines, emergency situations and communication technologies. In this paper, we introduce a semi-automatic technique for knowledge acquisition and modeling on accessible evacuation routes. We introduce a use case to show applications of the ontology and conclude with an evaluation involving several experts in evacuation procedures. © 2014 Elsevier Ltd. All rights reserved
The IceCube Neutrino Observatory: Instrumentation and Online Systems
The IceCube Neutrino Observatory is a cubic-kilometer-scale high-energy
neutrino detector built into the ice at the South Pole. Construction of
IceCube, the largest neutrino detector built to date, was completed in 2011 and
enabled the discovery of high-energy astrophysical neutrinos. We describe here
the design, production, and calibration of the IceCube digital optical module
(DOM), the cable systems, computing hardware, and our methodology for drilling
and deployment. We also describe the online triggering and data filtering
systems that select candidate neutrino and cosmic ray events for analysis. Due
to a rigorous pre-deployment protocol, 98.4% of the DOMs in the deep ice are
operating and collecting data. IceCube routinely achieves a detector uptime of
99% by emphasizing software stability and monitoring. Detector operations have
been stable since construction was completed, and the detector is expected to
operate at least until the end of the next decade.Comment: 83 pages, 50 figures; updated with minor changes from journal review
and proofin
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