Academic literature on the topic 'Atlas data'

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Journal articles on the topic "Atlas data"

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Jones, RWL, DM South, and KS Cranmer. "ATLAS Data Preservation." Journal of Physics: Conference Series 664, no. 3 (December 23, 2015): 032017. http://dx.doi.org/10.1088/1742-6596/664/3/032017.

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Barisits, Martin, Mikhail Borodin, Alessandro Di Girolamo, Johannes Elmsheuser, Dmitry Golubkov, Alexei Klimentov, Mario Lassnig, Tadashi Maeno, Rodney Walker, and Xin Zhao. "ATLAS Data Carousel." EPJ Web of Conferences 245 (2020): 04035. http://dx.doi.org/10.1051/epjconf/202024504035.

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The ATLAS experiment at CERN’s LHC stores detector and simulation data in raw and derived data formats across more than 150 Grid sites world-wide, currently in total about 200PB on disk and 250PB on tape. Data have different access characteristics due to various computational workflows, and can be accessed from different media, such as remote I/O, disk cache on hard disk drives or SSDs. Also, larger data centers provide the majority of offline storage capability via tape systems. For the HighLuminosity LHC (HL-LHC), the estimated data storage requirements are several factors bigger than the present forecast of available resources, based on a flat budget assumption. On the computing side, ATLAS Distributed Computing was very successful in the last years with high performance and high throughput computing integration and in using opportunistic computing resources for the Monte Carlo simulation. On the other hand, equivalent opportunistic storage does not exist. ATLAS started the Data Carousel project to increase the usage of less expensive storage, i.e. tapes or even commercial storage, so it is not limited to tape technologies exclusively. Data Carousel orchestrates data processing between workload management, data management, and storage services with the bulk data resident on offline storage. The processing is executed by staging and promptly processing a sliding window of inputs onto faster buffer storage, such that only a small percentage of input data are available at any one time. With this project, we aim to demonstrate that this is the natural way to dramatically reduce our storage cost. The first phase of the project was started in the fall of 2018 and was related to I/O tests of the sites archiving systems. Phase II now requires a tight integration of the workload and data management systems. Additionally, the Data Carousel studies the feasibility to run multiple computing workflows from tape. The project is progressing very well and the results presented in this document will be used before the LHC Run 3.
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Vaniachine, A. "Data Challenges in ATLAS computing." Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment 502, no. 2-3 (April 2003): 446–49. http://dx.doi.org/10.1016/s0168-9002(03)00465-0.

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Cuenca Almenar, C., A. Corso-Radu, H. Hadavand, Y. Ilchenko, S. Kolos, K. Slagle, and A. Taffard. "ATLAS Online Data Quality Monitoring." Nuclear Physics B - Proceedings Supplements 215, no. 1 (June 2011): 304–6. http://dx.doi.org/10.1016/j.nuclphysbps.2011.04.038.

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Adelman, J., M. Baak, N. Boelaert, M. D'Onofrio, J. A. Frost, C. Guyot, M. Hauschild, et al. "ATLAS offline data quality monitoring." Journal of Physics: Conference Series 219, no. 4 (April 1, 2010): 042018. http://dx.doi.org/10.1088/1742-6596/219/4/042018.

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Ould-Saada, Farid. "ATLAS Open Data – Development of a simple-but-real HEP data analysis framework." EPJ Web of Conferences 245 (2020): 08023. http://dx.doi.org/10.1051/epjconf/202024508023.

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The ATLAS Collaboration at the Large Hadron Collider is releasing a new set of recorded and simulated data samples at a centre-of-mass energy of 13 TeV collected in pp collisions at the LHC. This new dataset was designed after an in-depth review of the usage of the previous release of samples at 8 TeV. That review showed that capacity-building is one of the most important and abundant uses of public ATLAS samples. To fulfil the requirements of the community and at the same time attract new users and use cases, we developed real analysis software based on ROOT in two of the most popular programming languages: C++ and Python. These so-called analysis frameworks are complex enough to reproduce with reasonable accuracy the results -figures and final yields- of published ATLAS Collaboration physics papers, but still light enough to be run on commodity hardware. With the computers that university students and regular classrooms typically have, students can explore LHC data with similar techniques to those used by current ATLAS analysers. We present the development path and the final result of these analysis frameworks, their products and how they are distributed to final users inside and outside the ATLAS community.
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ŞENKUL, Çetin. "DATA LOGGER VERİLERİNE GÖRE GÖKNAR ORMANLARININ SICAKLIK VE NEMLİLİK İSTEKLERİ." ATLAS JOURNAL 4, no. 12 (January 1, 2018): 944–52. http://dx.doi.org/10.31568/atlas.157.

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Maelfait, Hannelore, and Kathy Belpaeme. "The Belgian Coastal Atlas: moving from the classic static atlas to an interactive data-driven atlas." Journal of Coastal Conservation 14, no. 1 (October 27, 2009): 13–19. http://dx.doi.org/10.1007/s11852-009-0076-5.

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Borodin, Mikhail, Alessandro Di Girolamo, Edward Karavakis, Alexei Klimentov, Tatiana Korchuganova, Mario Lassnig, Tadashi Maeno, Siarhei Padolski, and Xin Zhao. "The ATLAS Data Carousel Project Status." EPJ Web of Conferences 251 (2021): 02006. http://dx.doi.org/10.1051/epjconf/202125102006.

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The High Luminosity upgrade to the LHC, which aims for a tenfold increase in the luminosity of proton-proton collisions at an energy of 14 TeV, is expected to start operation in 2028/29 and will deliver an unprecedented volume of scientific data at the multi-exabyte scale. This amount of data has to be stored, and the corresponding storage system must ensure fast and reliable data delivery for processing by scientific groups distributed all over the world. The present LHC computing and data management model will not be able to provide the required infrastructure growth, even taking into account the expected hardware technology evolution. To address this challenge, the Data Carousel R&D project was launched by the ATLAS experiment in the fall of 2018. State-of-the-art data and workflow management technologies are under active development, and their current status is presented here.
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Carroll, C., R. F. Noss, and Bruce A. Stein. "US conservation atlas needs biodiversity data." Science 376, no. 6589 (April 8, 2022): 144–45. http://dx.doi.org/10.1126/science.abo0526.

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Dissertations / Theses on the topic "Atlas data"

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Parker, Vincent. "Statistical analysis of bird atlas data from Swaziland." Master's thesis, University of Cape Town, 1995. http://hdl.handle.net/11427/20195.

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The question of what determines the observed geographical distributions of animal species is one of great interest to natural scientists. In general terms, these distributions are known to be related to a number of environmental factors, but the nature of the relationships and the relative importance of the different factors remain poorly understood. This investigation sets out to obtain more insight into these questions by using statistical methods to explore the relationships between the observed geographical distributions of bird species in Swaziland and a number of environmental variables. In 1985 I set out to compile a bird atlas of Swaziland. Data were accumulated between 1985 and 1991 and the bird atlas submitted to a publisher in May 1993. The text of the bird atlas is included here as Appendix 2 because it provides the essential background to this dissertation. The introductory section of the atlas includes a description of the data gathering process. The analysis included in the bird atlas was aimed at a popular readership and was not intended to form part of an academic dissertation Chapter 1 describes the use of logistic regression to investigate the relationships between the bird distribution patterns and a set of environmental variables and to predict the distributions. Chapter 2 describes the results of applying the methods described in Chapter 1 for all of the bird species for which data were available. Because this paper was aimed at a different readership, some repetition of material contained in Chapter 1 was unavoidable. In Chapter 3, biplot techniques were used to obtain a graphical representation of the bird atlas data.
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Öhman, Henrik. "Analysis of early data from the ATLAS experiment towards H+ searches." Thesis, Uppsala universitet, Högenergifysik, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-159414.

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In the ATLAS experiment software plays a central role in data taking, reconstruction, and analysis. This thesis presents a set of analysis algorithms written for the ATLAS software framework Athena, towards H+ searches in the τ+jets channel. Data recorded by the ATLAS experiment for 900 GeV proton-proton collisions from 2009 and 7 TeV proton-proton collisions from 2010 are analyzed with these algorithms and compared to Monte Carlo. A search for top quarks is performed on 36 pb-1 of data, and the results are found to agree well with Monte Carlo.
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Price, Darren David. "Studies of quarkonium production and polarisation with early data at Atlas." Thesis, Lancaster University, 2008. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.527159.

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Zhang, Jia Ph D. Massachusetts Institute of Technology. "The constant atlas : mapping public data for individuals and their cities." Thesis, Massachusetts Institute of Technology, 2018. http://hdl.handle.net/1721.1/119075.

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Thesis: Ph. D., Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2018.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 131-136).
Over the past ten years the ability of institutions and businesses to capture, aggregate, and process an individual's data has grown significantly as digital technology has increasingly integrated into our daily lives. In the urban informatics context and in computational social science, projects use data collected about our behavior in the urban environment to solve problems including traffic congestion and public safety, the creation of targeted advertising, and the development of entire neighborhoods. Some projects using aggregate data may ultimately benefit individuals by making improvements to their environment at large. Although individuals are the source of aggregate information, an individual citizen often does not directly engage with the data collected about them. The research contained in this dissertation explores a series of visualization experiments concerning direct engagement between citizens and public datasets such as the U.S.Census. In order for such visualizations to be effective, they not only have to efficiently communicate data, but must also be intuitive, evocative, and utilize narratives presented from the user's perspective. In this dissertation I address the question: How can we design visualizations which inform daily interaction between individuals and public data about their environment? To answer this question, the dissertation introduces 4 sets of maps: (1) the Powers Map and Scopes Map contextualizes Census data(American Community Survey) by invoking changes in scale, (2) the Sightline Map and Cross Section Map use a person's physical experiences to orient Census data, (3) the Filtered Satellite Maps give qualitative comparisons of conditions described by Census tables, and (4) the Personal History Map leverages an individual's geospatial history to filter Census data. These 4 map groups share the goal of allowing us, as individuals, to use public data to design our own experiences within our environments and to make use of public data directly on our own behalf.
by Jia Zhang.
Ph. D.
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Agius, Nicola Kristina. "Dust in Early-Type Galaxies using Herschel-ATLAS and GAMA data." Thesis, University of Central Lancashire, 2014. http://clok.uclan.ac.uk/10715/.

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This work investigates the properties of Early-Type Galaxies (ETGs; elliptical and lenticulars) containing thermal dust emission, with aims of linking the formation and evolution of these galaxies with their current dust properties. Three different proxies for morphology are considered for selecting ETGs, and these are tested against three sets of visually classified galaxies. We find that classifying ETGs as those galaxies in the optical Red Sequence results in samples with ≳35% contamination by late-types, and ≲82% completeness. Concentration and Sérsic index proxies result in slightly improved contamination levels of ≳30% and ~60-70% completeness. These results lead to the conclusion that morphological proxies cannot be used to create fully robust samples of ETGs. Therefore, we choose to use visual inspection to identify ETGs at low redshifts.
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Beermann, Thomas [Verfasser]. "A popularity prediction and dynamic data replication study for the ATLAS distributed data management / Thomas Beermann." Wuppertal : Universitätsbibliothek Wuppertal, 2017. http://d-nb.info/1136872981/34.

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Klemetti, Miika. "Search for Higgs bosons beyond the standard model in early ATLAS data." Thesis, McGill University, 2011. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=104496.

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Higgs bosons are present in many extensions of the Standard Model, yet we are still waiting for the experimental confirmation of their existence. This thesis discusses Minimal and Next-to Minimal Supersymmetric Models, and presents searches for leptonic Higgs boson decays in channels that may provide the first unambiguous evidence of Higgs physics beyond the Standard Model. The channels considered are1 : gg→a1, gg→h1→2a1, H+→τν, and H+→a1W+, where a1→µµ and τ→ℓνν . A full data analysis is presented for gg→a1→µµ channel, while sensitivity prospects are discussed for the other channels. For the data analysis, we consider a data set with an integrated luminosity of 39 pb−1 collected by the ATLAS Detector at the Large Hadron Collider in 2010, operating at the centre of mass energy of √s = 7 TeV. As we observe no evidence for a signal in the gg→a1 channel, we set a model independent 95% confidence level upper limit on Higgs production cross section and branching ratio: σgg→a1×B(a1→µµ). This result represents the first measurement of σgg→a1×B(a1→µµ) in the world, and improves on the current experimental constraints on the Higgs sector beyond the Standard Model.
Les bosons de Higgs sont présents dans de nombreuses extensions du Modèle Standard, mais nous sommes toujours en attente de la confirmation exprimentale de leur existence. Cette thèse traite des modèles communs supersymetriques, et presente les recherches de désintégrations leptoniques du boson de Higgs dans les processus qui peuvent fournir la premiere preuve, sans equivoque, du Higgs au-dela du Modèle Standard. Les processus considérés sont: gg→a1, gg→h1→2a1, H+→τν,et H+→a1W+, avec a1→µµ et τ→ℓνν. La sensibilité des perspectives sont discutées pour les trois derniers, alors qu'une analyse de données complète est présentée pour le premier processus. Nous considérons un ensemble de données avec une luminosité integrée de 39 pb−1 collectées par le detecteur ATLAS au Large Hadron Collider en 2010, operant au centre de masse de √s = 7 TeV. Comme on n'observe pas de signal, nous avons mis une limite superieure sur la section efficace de production de Higgs et du rapport de branchement: σgg→a1×B(a1→µµ). Ce résultat représente une toute première mesure de σgg→a1×B(a1→µµ) dans le monde, et s'améliore sur les contraintes expérimentales courantes sur le secteur de Higgs au delà du Modèle Standard.
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Flowerdew, M. I. chael James. "Standard model Z/gamma to ee production in early data at Atlas." Thesis, University of Liverpool, 2009. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.526791.

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Argyropoulos, Spyridon. "Measurement of the ttbb production cross-section with 8 TeV ATLAS data." Doctoral thesis, Humboldt-Universität zu Berlin, Mathematisch-Naturwissenschaftliche Fakultät, 2016. http://dx.doi.org/10.18452/17476.

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Diese Dissertation beschreibt die Messung des Wirkungquerschnitts für die Produktion von ttbb in Protonkollisionen mit einer Schwerpunktsenergie von √s = 8 TeV. Der verwendete Datensatz entspricht einer integrierten Luminosität von 20.3/fb. Der Wirkungsquerschnitt wurde aus der Anzahl der Signalereignisse bestimmt, die durch harte Schnitte insbesondere auf genau 4 identifizierten b-jets, selektiert wurden, was zu einer hohen Reinheit des Signals führt. Bei der Messung wurden die präzisesten Kalibrierungen von der Jet-Energieskala und der b-jet Effizienz benutzt. Die Messung wurde in einem Referenzphasenraum durchgeführt, der daraufhin optimiert wurde, die Abhängigkeit von der Modellierung zu minimisieren. Der gemessene Wirkungsquerschnitt beträgt 18.9 ± 3.5 (stat)+5.6 (sys) ± 0.6 (Lumi) fb oder, nachdem der Beitrag von ttH(bb) und ttZ(bb) abgezogen wurde: 17.8 ± 3.5 (stat)+5.9 (sys) ± 0.6 (Lumi) fb. Das Ergebnis wurde mit einer Vielzahl von theoretischen Vorhersagen verglichen, einschließlich NLO-Berechnungen mit Partonschauern und einer Reihe von Modellen die sich in der Beschreibung der Gluon Spaltung unterscheiden. Es wurde gezeigt, dass das exstremste Model den Wirkungsquerschnitt überschätzt und dass die Messung die Vorhersagen bevorzugt, die mit einer niedrigen Renormierungs- und Faktorisierungsskala, berechnet wurden.
This thesis presents the measurement of the ttbb production cross-section, using a dataset of 20.3/fb of pp collisions collected with the ATLAS detector at 8 TeV. The measurement is based on a cut-and-count method, using a sample of events with exactly four b-tagged jets, which is shown to have a high purity in signal events. The measurement exploits the most precise jet energy scale and b-tagging calibrations and is performed in a fiducial phase space that is designed to minimize the model dependence of the measurement. The fiducial cross-section is measured to be 18.9 ± 3.5 (stat)+5.6 (sys) ± 0.6 (Lumi) fb or subtracting the contribution from ttH(bb) and ttZ(bb) final states, 17.8 ± 3.5 (stat)+5.9 (sys) ± 0.6 (Lumi) fb. The result is compared with a multitude of theoretical predictions, including different NLO calculations matched to a parton shower, which constitute the most precise predictions available to date, as well as with a series of models that differ in the description of the gluon splitting to b-quarks. It is shown that the most extreme gluon splitting model overestimates the observed rate of ttbb production and that the measurement favors calculations performed with renormalization/factorization scales which are softer than the scales usually employed in similar calculations.
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Muschter, Steffen Lothar. "Readout link and control board for the ATLAS Tile Calorimeter upgrade." Doctoral thesis, Stockholms universitet, Fysikum, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-116258.

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The Large Hadron Collider (LHC) at the CERN laboratory was designed to study the elementary particles and forces and search for new physics.  Detectors at LHC were designed to observe proton-proton collisions with center of mass energies up to 14 TeV, seven times higher than previously possible. One of the largest of these is the general purpose detector ATLAS. After almost 20 years of planning and construction, LHC and its detectors were finished in 2008. Since then ATLAS has produced valuable data, which contributed to the discovery of the 1964 postulated Higgs-particle and thus to the Nobel prize in physics in 2013. To expand the searches, LHC and its detectors will undergo several upgrades to the increase luminosity at least by a factor of 5 and to exploit the full potential of the machine. In order to adapt the detector to the resulting increasing event rates and radiation levels, new electronics have to be developed. This thesis describes the development process of a new upgraded digital readout system for one of the sub-detectors in ATLAS, the scintillating Tile Calorimeter (TileCal), and more specifically one of its key components, the high-speed data link DaughterBoard. Starting from the idea of transferring all recorded information of the detector using high speed serial optical links and the concept of using re-programmable logic for the readout electronics, completely new on-detector electronics were designed to be used as a core component for communication, control and monitoring. The electronics was tested, electrical characterized and proven to work in a setup similar to the upgraded readout electronics. The DaughterBoard is the Stockholm University contribution to the ATLAS upgrade in 2023.
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Books on the topic "Atlas data"

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United States. Ocean Assessments Division. Strategic Assessment Branch. National estuarine inventory data atlas. [Rockville, Md.]: The Service, 1985.

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Guest, Peter S. MIZEX 87 meteorology atlas. Monterey, Calif: Naval Postgraduate School, 1988.

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United States. National Environmental Satellite, Data, and Information Service. Atlas of surface marine data 1994. Washington, D.C: U.S. Dept. of Commerce, National Oceanic and Atmospheric Administration, National Environmental Satellite, Data, and Information Service, 1994.

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Lilley, William. State data atlas: The almanac of state legislatures. Washington, D.C: Congressional Quarterly, 1994.

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Cliff, A. D. Atlas of disease distributions: Analytic approaches to epidemiological data. Oxford, UK: Basil Blackwell, 1988.

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Krueger, Arlin J. 1988 Antarctic Ozone Monitoring Nimbus-7 TOMS data atlas. [Washington, D.C.?]: National Aeronautics and Space Administration, Office Management, Scientific and Technical Information Division, 1988.

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J, Krueger A., and United States. National Aeronautics and Space Administration. Scientific and Technical Information Division, eds. 1988 Antarctic ozone monitoring Nimbus-7 TOMS data atlas. Washington, D.C: National Aeronautics and Space Administration, Scientific and Technical Information Division, 1989.

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Schwekendiek, Daniel. The data atlas of North Korea: Demography, society, economy. [Seoul]: Institute for Peace and Unification Studies (IPUS), 2009.

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Manzoni, Stefano. Physics with Photons Using the ATLAS Run 2 Data. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-24370-8.

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Peter, Haggett, ed. Atlas of disease distributions: Analytic approaches to epidemiological data. Oxford, UK: Blackwell Reference, 1992.

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Book chapters on the topic "Atlas data"

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Genske, Dieter D., and Giovanni Maurice Pradipta. "Atlas and Data." In Establishing Plus-Minus-Energy-Regions, 125–27. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-93596-2_17.

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Meissner, R., and Th Wever. "Presentation of Data." In DEKORP-Atlas, 11–14. Berlin, Heidelberg: Springer Berlin Heidelberg, 1990. http://dx.doi.org/10.1007/978-3-642-75662-7_5.

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Klokočník, Jaroslav, Jan Kostelecký, and Aleš Bezděk. "Data." In Gravitational Atlas of Antarctica, 11–15. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-56639-9_3.

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Buckland, S. T., and A. J. B. Anderson. "Multivariate Analysis of Atlas Data." In Statistics in Ornithology, 93–112. New York, NY: Springer New York, 1985. http://dx.doi.org/10.1007/978-1-4612-5138-5_8.

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Kolářová, Michaela, and Pavel Hamouz. "Data collection." In Atlas of Weed Mapping, 428–37. Chichester, UK: John Wiley & Sons, Ltd, 2016. http://dx.doi.org/10.1002/9781118720691.ch42.

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Lindau, Ralf. "Data and Data Treatment." In Climate Atlas of the Atlantic Ocean, 1–2. Berlin, Heidelberg: Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/978-3-642-59526-4_2.

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Maurer, Konrad, and Thomas Dierks. "Storing of Data." In Atlas of Brain Mapping, 37. Berlin, Heidelberg: Springer Berlin Heidelberg, 1991. http://dx.doi.org/10.1007/978-3-642-76043-3_6.

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Stiller, M., and R. Thomas. "Data Processing at the DEKORP Processing Center." In DEKORP-Atlas, 7–10. Berlin, Heidelberg: Springer Berlin Heidelberg, 1990. http://dx.doi.org/10.1007/978-3-642-75662-7_4.

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Boelaert, Nele. "Jet Reconstruction with 2010 ATLAS Data." In Dijet Angular Distributions in Proton-Proton Collisions, 99–103. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-24597-8_8.

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Karcher, W. "Data Presentation." In Spectral Atlas of Polycyclic Aromatic Compounds, 16–829. Dordrecht: Springer Netherlands, 1988. http://dx.doi.org/10.1007/978-94-009-1263-2_4.

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Conference papers on the topic "Atlas data"

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Zhang, Jinlong. "ATLAS data acquisition." In 2009 16th IEEE-NPSS Real Time Conference (RT). IEEE, 2009. http://dx.doi.org/10.1109/rtc.2009.5321758.

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Nilsson, Paul, and ATLAS Collaboration. "Distributed data analysis in ATLAS." In INTERNATIONAL CONFERENCE OF COMPUTATIONAL METHODS IN SCIENCES AND ENGINEERING 2009: (ICCMSE 2009). AIP, 2012. http://dx.doi.org/10.1063/1.4771863.

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Doglioni, Caterina, Else Lytken, and Arturo Sánchez Pineda. "The ATLAS Open Data project." In Sixth Annual Conference on Large Hadron Collider Physics. Trieste, Italy: Sissa Medialab, 2018. http://dx.doi.org/10.22323/1.321.0040.

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Cuenca Almenar, C., A. Corso-Radu, H. Hadavand, Y. Ilchenko, S. Kolos, K. Slagle, and A. Taffard. "ATLAS online data quality monitoring." In 2010 17th Real-Time Conference - IEEE-NPSS Technical Committee on Computer Applications in Nuclear and Plasma Sciences (RT 2010). IEEE, 2010. http://dx.doi.org/10.1109/rtc.2010.5750365.

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White, Martin. "Data quality monitoring in ATLAS, ID." In 17th International Workshop on Vertex detectors. Trieste, Italy: Sissa Medialab, 2009. http://dx.doi.org/10.22323/1.068.0044.

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Lohwasser, Kristin. "ATLAS Electroweak Measurements with early data." In Physics at LHC 2008. Trieste, Italy: Sissa Medialab, 2010. http://dx.doi.org/10.22323/1.055.0042.

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Teuscher, Richard. "Commissioning with physics data at ATLAS." In International Europhysics Conference on High Energy Physics. Trieste, Italy: Sissa Medialab, 2007. http://dx.doi.org/10.22323/1.021.0386.

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Waller, Peter. "ATLAS Data Quality Monitoring: Experience with First Collision Data." In 35th International Conference of High Energy Physics. Trieste, Italy: Sissa Medialab, 2011. http://dx.doi.org/10.22323/1.120.0511.

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Xu, Jialong, Tiejun Zu, Liangzhi Cao, and Hongchun Wu. "Development and Verification of a New Nuclear Data Processing System NECP-Atlas." In 2018 26th International Conference on Nuclear Engineering. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/icone26-81516.

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To process the evaluated nuclear data file (ENDF) libraries and generate the cross section data library for neutronics calculations, a new nuclear data processing system NECP-Atlas was developed by Nuclear Engineering Computational Physics Lab. of Xi'an Jiaotong University. Meanwhile, some flaws of the current widely used nuclear data processing systems were made up. Some new methods and techniques were proposed and integrated into NECP-Atlas. NECP-Atlas could process ENDF and generate point-wise evaluated nuclear data file (PENDF) and the multigroup cross section data library in WIMS-D format. Verification of NECP-Atlas was carried out by comparing the keff values for WLUP benchmark cases and benchmark experiments in the ICSBEP handbook using cross section data libraries processed by NECP-Atlas with those by NJOY2016. The results showed that NECP-Atlas processes the ENDF correctly and generates more reliable cross section data libraries.
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10

LELAS, Damir. "Jet reconstruction with first data in ATLAS." In Physics at LHC 2008. Trieste, Italy: Sissa Medialab, 2010. http://dx.doi.org/10.22323/1.055.0038.

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Reports on the topic "Atlas data"

1

Hogg, Christopher J., Lisa Eshelman, Denise Rae Bleakly, and Martin R. Arrambide. Sandia National Laboratories/New Mexico geographic data atlas. Office of Scientific and Technical Information (OSTI), September 1999. http://dx.doi.org/10.2172/903432.

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2

Purohit, Milind V. Research on data from the ATLAS experiment at CERN. Office of Scientific and Technical Information (OSTI), July 2015. http://dx.doi.org/10.2172/1204505.

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3

BERG, DALE E., and JOSE R. ZAYAS. Accurate GPS Time-Linked Data Acquisition System (ATLAS) User's Manual. Office of Scientific and Technical Information (OSTI), May 2001. http://dx.doi.org/10.2172/782703.

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4

Cole, G. L. Data processing techniques for the Geochemical Atlas of Costa Rica. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 1990. http://dx.doi.org/10.4095/128097.

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5

Schau, M., A. Rencz, L. Dredge, C. F. Chung, and L. Chorlton. Digital data atlas, Hall Lake area, Melville Peninsula, Northwest Territories. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 1993. http://dx.doi.org/10.4095/193358.

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6

Gaur, S., and T. B. Reed. An atlas of thermal data for biomass and other fuels. Office of Scientific and Technical Information (OSTI), June 1995. http://dx.doi.org/10.2172/82384.

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7

Brooks, R. The New and Improved Base Framework for National Atlas Data. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 1999. http://dx.doi.org/10.4095/219463.

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8

Bigl, Matthew, Caitlin Callaghan, Brandon Booker, Kathryn Trubac, Jacqueline Willan, Paulina Lintsai, and Marissa Torres. Energy Atlas—mapping energy-related data for DoD lands in Alaska : Phase 2—data expansion and portal development. Engineer Research and Development Center (U.S.), January 2022. http://dx.doi.org/10.21079/11681/43062.

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As the largest Department of Defense (DoD) land user in Alaska, the U.S. Army oversees over 600,000 hectares of land, including remote areas accessible only by air, water, and winter ice roads. Spatial information related to the energy resources and infrastructure that exist on and adjacent to DoD installations can help inform decision makers when it comes to installation planning. The Energy Atlas−Alaska portal provides a secure value-added resource to support the decision-making process for energy management, investments in installation infrastructure, and improvements to energy resiliency and sustainability. The Energy Atlas–Alaska portal compiles spatial information and provides that information through a secure online portal to access and examine energy and related resource data such as energy resource potential, energy corridors, and environmental information. The information database is hosted on a secure Common Access Card-authenticated portal that is accessible to the DoD and its partners through the Army Geospatial Center’s Enterprise Portal. This Enterprise Portal provides effective visualization and functionality to support analysis and inform DoD decision makers. The Energy Atlas–Alaska portal helps the DoD account for energy in contingency planning, acquisition, and life-cycle requirements and ensures facilities can maintain operations in the face of disruption.
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9

Callaghan, Caitlin, Matthew Bigl, Brandon Booker, Kyle Elliott, Paulina Lintsai, Marissa Torres, Kathryn Trubac, and Jacqueline Willan. Energy Atlas—mapping energy-related data for DoD lands in Alaska : Phase 1—assembling the data and designing the tool. Engineer Research and Development Center (U.S.), October 2021. http://dx.doi.org/10.21079/11681/42226.

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The U.S. Army is the largest Department of Defense (DoD) land user in Alaska, including remote areas only accessible by air, water, or wintertime ice roads. Understanding where energy resources and related infrastructure exist on and adjacent to DoD installations and training lands can help in-form Army decision-makers, especially in remote locations like Alaska. The Energy Atlas–Alaska provides a value-added resource to support decision-making for investments in infrastructure and diligent energy management, helping Army installations become more resilient and sustainable. The Energy Atlas–Alaska utilizes spatial information and provides a consistent GIS (geographic information system) framework to access and examine energy and related resource data such as energy resource potential, energy corridors, and environmental information. The database can be made accessible to DoD and its partners through an ArcGIS-based user interface that provides effective visualization and functionality to support analysis and to inform DoD decision-makers. The Energy Atlas–Alaska helps DoD account for energy in contingency planning, acquisition, and life-cycle requirements and ensures facilities can maintain operations in the face of disruption.
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10

Callaghan, Caitlin, Matthew Bigl, Brandon Booker, Kyle Elliott, Paulina Lintsai, Marissa Torres, Kathryn Trubac, and Jacqueline Willan. Energy Atlas—mapping energy-related data for DoD lands in Alaska : Phase 1—assembling the data and designing the tool. Engineer Research and Development Center (U.S.), October 2021. http://dx.doi.org/10.21079/11681/42226.

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Abstract:
The U.S. Army is the largest Department of Defense (DoD) land user in Alaska, including remote areas only accessible by air, water, or wintertime ice roads. Understanding where energy resources and related infrastructure exist on and adjacent to DoD installations and training lands can help in-form Army decision-makers, especially in remote locations like Alaska. The Energy Atlas–Alaska provides a value-added resource to support decision-making for investments in infrastructure and diligent energy management, helping Army installations become more resilient and sustainable. The Energy Atlas–Alaska utilizes spatial information and provides a consistent GIS (geographic information system) framework to access and examine energy and related resource data such as energy resource potential, energy corridors, and environmental information. The database can be made accessible to DoD and its partners through an ArcGIS-based user interface that provides effective visualization and functionality to support analysis and to inform DoD decision-makers. The Energy Atlas–Alaska helps DoD account for energy in contingency planning, acquisition, and life-cycle requirements and ensures facilities can maintain operations in the face of disruption.
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