Auswahl der wissenschaftlichen Literatur zum Thema „Rare maps“

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Zeitschriftenartikel zum Thema "Rare maps"

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Vick, Nancy J., und Nancy L. Romero. „Cataloging Rare Maps“. Cataloging & Classification Quarterly 10, Nr. 4 (19.03.1990): 3–18. http://dx.doi.org/10.1300/j104v10n04_02.

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Sands, Duncan. „Misiurewicz Maps are Rare“. Communications in Mathematical Physics 197, Nr. 1 (01.09.1998): 109–29. http://dx.doi.org/10.1007/s002200050444.

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Aspenberg, Magnus. „Rational Misiurewicz Maps are Rare“. Communications in Mathematical Physics 291, Nr. 3 (30.07.2009): 645–58. http://dx.doi.org/10.1007/s00220-009-0813-5.

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Shyam Prasad, M., N. G. Rudraswami, Agnelo Alexandre De Araujo und V. D. Khedekar. „Rare, metal micrometeorites from the Indian Ocean“. Meteoritics & Planetary Science 54, Nr. 2 (14.10.2018): 290–99. http://dx.doi.org/10.1111/maps.13206.

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Waller, Rosalie Griffin, Robert J. Klein, Joseph Vijai, James D. McKay, Alyssa Clay-Gilmour, Xiaomu Wei, Michael J. Madsen et al. „Sequencing at lymphoid neoplasm susceptibility loci maps six myeloma risk genes“. Human Molecular Genetics 30, Nr. 12 (05.03.2021): 1142–53. http://dx.doi.org/10.1093/hmg/ddab066.

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Abstract Inherited genetic risk factors play a role in multiple myeloma (MM), yet considerable missing heritability exists. Rare risk variants at genome-wide association study (GWAS) loci are a new avenue to explore. Pleiotropy between lymphoid neoplasms (LNs) has been suggested in family history and genetic studies, but no studies have interrogated sequencing for pleiotropic genes or rare risk variants. Sequencing genetically enriched cases can help discover rarer variants. We analyzed exome sequencing in familial or early-onset MM cases to identify rare, functionally relevant variants near GWAS loci for a range of LNs. A total of 149 distinct and significant LN GWAS loci have been published. We identified six recurrent, rare, potentially deleterious variants within 5 kb of significant GWAS single nucleotide polymorphisms in 75 MM cases. Mutations were observed in BTNL2, EOMES, TNFRSF13B, IRF8, ACOXL and TSPAN32. All six genes replicated in an independent set of 255 early-onset MM or familial MM or precursor cases. Expansion of our analyses to the full length of these six genes resulted in a list of 39 rare and deleterious variants, seven of which segregated in MM families. Three genes also had significant rare variant burden in 733 sporadic MM cases compared with 935 control individuals: IRF8 (P = 1.0 × 10−6), EOMES (P = 6.0 × 10−6) and BTNL2 (P = 2.1 × 10−3). Together, our results implicate six genes in MM risk, provide support for genetic pleiotropy between LN subtypes and demonstrate the utility of sequencing genetically enriched cases to identify functionally relevant variants near GWAS loci.
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Wojewoda, Władysław. „Morphology of some rare and threatened Polish Basidiomycota“. Acta Mycologica 38, Nr. 1-2 (20.08.2014): 3–20. http://dx.doi.org/10.5586/am.2003.001.

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Morphological analysis and orginal illustrations of microscopic elements of 20 species of <i>Basidiomycota</i> (19 of <i>Basidiomycetes</i> and 1 of <i>Urediniomycetes</i>) are the subject of this article. The species arc rare in Poland according to recent distributional maps. The maps of 17 of them: <i>Amylocorticium cebennese, A. subincamatum, A. subsulphureum, Bovista paludosa, Clavariadelphus truncatus, Clavulicium macounii, Conohypha albocremea, Daedaleopsis tricolor, Fomitiporia hippophaeicola, Hymenochaele cruenta, Irpicodon pendulus, Punclularia strigisozonata, Scotomyces subviolaceus, Syzygospora pallida, Thanatephorus sterigmaticus, Trichaptum biforme</i> and <i>Tubulicrinis borealis</i>, were published by Wojewoda (2002) in the "Atlas of the geographical distribution of fungi in Poland", Fasc. 2. The further 3 maps of <i>Coniophora olivacea, Helicobasidium pupureum</i> and <i>Veluticeps ambigua</i> will be published soon in the same series in Fasc. 3.
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Zweimüller, Roland. „Hitting-time limits for some exceptional rare events of ergodic maps“. Stochastic Processes and their Applications 129, Nr. 5 (Mai 2019): 1556–67. http://dx.doi.org/10.1016/j.spa.2018.05.011.

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Ito, Motoo, und Scott Messenger. „Rare earth element measurements and mapping of minerals in the Allende CAI, 7R19-1, by NanoSIMS ion microprobe“. Meteoritics & Planetary Science 51, Nr. 4 (17.03.2016): 818–32. http://dx.doi.org/10.1111/maps.12623.

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Liu, Nan, Andrew Steele, Larry R. Nittler, Rhonda M. Stroud, Bradley T. De Gregorio, Conel M. O'D Alexander und Jianhua Wang. „Coordinated EDX and micro-Raman analysis of presolar silicon carbide: A novel, nondestructive method to identify rare subgroup SiC“. Meteoritics & Planetary Science 52, Nr. 12 (28.09.2017): 2550–69. http://dx.doi.org/10.1111/maps.12954.

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Verhoeven, J. D., A. J. Bevolo, D. T. Peterson, H. H. Baker, O. D. McMasters und E. D. Gibson. „Hydride formation on polishing rare earth alloys and reflected electron loss maps“. Metallography 18, Nr. 3 (August 1985): 277–90. http://dx.doi.org/10.1016/0026-0800(85)90047-3.

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Dissertationen zum Thema "Rare maps"

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Tennessee, State of. „Washington County Geographic Features“. Digital Commons @ East Tennessee State University, 1986. https://dc.etsu.edu/rare-maps/8.

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This Washington County, Tennessee map includes geographic features including streams and mountain peaks, as well man made features such as highways, railroads, communities, and cemeteries. While the publication date is not included, it was received by the Documents, Law and Maps Department in 1986. However, due to the spelling of a few of the landmarks, the actual publication likely predates 1983. Some points of interest include the Veteran's Administration Mountain Home which is now the site of the Quillen College of Medicine and White Rock Ridge located where Buffalo Mountain Park would be established a decade later in 1994.
https://dc.etsu.edu/rare-maps/1007/thumbnail.jpg
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Division, Johnson City GIS. „Johnson City Annexations, 1960-2003“. Digital Commons @ East Tennessee State University, 2003. https://dc.etsu.edu/rare-maps/12.

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Produced by the Johnson City GIS Division on September 9, 2003, this map denotes the annexations of Johnson City and the surrounding area from 1960 to 2003. The map scale indicates a ratio of 1:24,000. In the text box on the left side, the ID, date, and annexation names are listed. As part of the legend, each 5 year annexation period is color coded. This map was donated by the Johnson City GIS Division and now resides in the map collection of Sherrod Library's Government Information, Law and Maps Department.
https://dc.etsu.edu/rare-maps/1011/thumbnail.jpg
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Division, Johnson City GIS. „Johnson City, Tennessee Streets, 2003“. Digital Commons @ East Tennessee State University, 2003. https://dc.etsu.edu/rare-maps/13.

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Produced by the Johnson City GIS Division on September 9, 2003, this map denotes the streets of Johnson City. The legend includes fire stations, neighborhoods, and schools. A city street index is also included. The map was designed by Gregory Plumb, GIS Coordinator and Ann Howland, GIS Database Specialist. This map was donated by the Johnson City GIS Division and now resides in the map collection of Sherrod Library's Government Information, Law and Maps Department.
https://dc.etsu.edu/rare-maps/1012/thumbnail.jpg
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District, First Tennessee-Virginia Development. „Johnson City, Tennessee Information Map (Undated)“. Digital Commons @ East Tennessee State University, 2021. https://dc.etsu.edu/rare-maps/14.

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Prepared by the First Tennessee-Virginia Development District and sponsored by the Johnson City Conventions & Visitors Bureau, this undated map shows major highways, landmarks, and business centers around Johnson City, Tennessee and the surrounding Washington County. Some landmarks, roads, and businesses have been added by hand at an indeterminate time post publication. Scale is 1 inch = 1 mile
https://dc.etsu.edu/rare-maps/1013/thumbnail.jpg
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Transportation, Tennessee Department of. „General Highway Map - Washington County, Tennessee - 1991“. Digital Commons @ East Tennessee State University, 1991. https://dc.etsu.edu/rare-maps/40.

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General highway map of Washington County, Tennessee prepared by the Tennessee Department of Transportation, Bureau of Planning and Development-Planning Division in cooperation with the U.S. Department of Transportation, Federal Highway Administration. Field data obtained in 1977. Field Examination made in 1984. The road names shown on this map were approved by the Washington County Commission in 1985. Legend denotes multiple categories including dwellings and businesses as well as county infrastructure. Several insets of specific communities and areas of interest are included. Lines of longitude and latitude are listed along the outside border. Scale for general map - 1/2" = 1 mile Scale for insets - 1" = 0.3 mile
https://dc.etsu.edu/rare-maps/1039/thumbnail.jpg
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Transportation, Tennessee Department of. „General Highway Map - Sullivan County, Tennessee - 1963“. Digital Commons @ East Tennessee State University, 1985. https://dc.etsu.edu/rare-maps/38.

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General highway map of Sullivan County, Tennessee prepared by the Tennessee Department of Transportation, Bureau of Planning and Development-Planning Division in cooperation with the U.S. Department of Transportation, Federal Highway Administration. Field data obtained in 1978. Field Examination made in 1985. The road names shown on this map were approved by the Sullivan County Commission in 1985. Legend denotes multiple categories including dwellings and businesses as well as county infrastructure. An inset of Friendship Road can be found on the lower portion. Lines of longitude and latitude are listed along the outside border. Scale for general map - 1/2" = 1 mile
https://dc.etsu.edu/rare-maps/1037/thumbnail.jpg
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Transportation, Tennessee Department of. „General Highway Map - Washington County, Tennessee - 1985“. Digital Commons @ East Tennessee State University, 1985. https://dc.etsu.edu/rare-maps/47.

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General highway map of Washington County, Tennessee prepared by the Tennessee Department of Transportation, Bureau of Planning and Development-Planning Division in cooperation with the U.S. Department of Transportation, Federal Highway Administration. Field data obtained in 1977. Field Examination made in 1984. The road names shown on this map were approved by the Washington County Commission in 1985. Legend denotes multiple categories including dwellings and businesses as well as county infrastructure. Several insets of specific communities and areas of interest are included. Lines of longitude and latitude are listed along the outside border. Scale - 1" = 1 mile
https://dc.etsu.edu/rare-maps/1046/thumbnail.jpg
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Division, Johnson City GIS. „East Tennessee State University Campus Map - 2013“. Digital Commons @ East Tennessee State University, 2013. https://dc.etsu.edu/rare-maps/50.

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2013 campus map of East Tennessee State University in Johnson City, Tennessee. Created 12/4/2013 by Johnson City GIS. Buildings can be identified using the building index on the left half of the map. Fire suppression system features are also included on index. No scale is included.
https://dc.etsu.edu/rare-maps/1049/thumbnail.jpg
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Division, Johnson City GIS. „East Tennessee State University, VA Campus/Mountain Home - 1995“. Digital Commons @ East Tennessee State University, 1995. https://dc.etsu.edu/rare-maps/52.

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1995 map of East Tennessee State University's VA Campus. Created 5/30/1995 by Johnson City GIS. Buildings can be identified using the building index on the left side of map. Parking info and the parking lot legend can be found on the bottom half. Some buildings are shaded using a colored pencil at an indeterminate time post publication. No scale is included.
https://dc.etsu.edu/rare-maps/1051/thumbnail.jpg
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Division, Johnson City GIS. „East Tennessee State University Campus Map - 1998“. Digital Commons @ East Tennessee State University, 1998. https://dc.etsu.edu/rare-maps/48.

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1998 campus map of East Tennessee State University in Johnson City, Tennessee. Created by Johnson City GIS, Tennessee. A point of interest is the newly built Sherrod Library (as of 1998) identified as building 22/23. "New" is handwritten in black ink denoting the new library location. "Old" is handwritten on the old library location. These were added at an indeterminate time post publication. A building index can be found on the top right quadrant. Scale is 1" = 200 feet.
https://dc.etsu.edu/rare-maps/1047/thumbnail.jpg
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Bücher zum Thema "Rare maps"

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Rare maps of Pakistan. Lahore: Ferozsons, 2000.

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Straley, Gerald Bane. The rare vascular plants of British Columbia. (Toronto, Ont.): World Wildlife Fund (Canada), 1985.

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Straley, Gerald Bane. The rare vascular plants of British Columbia. [Toronto, Ont.]: World Wildlife Fund (Canada), 1985.

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Gullan, P. K. Rare or threatened plants in Victoria. East Melbourne, Vic: Dept. of Conservation and Environment, 1990.

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Khan, Iqbal Nafees. Hand list of rare maps preserved at Sindh archives, Karachi. Karachi: Sindh Archives, 2006.

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Day, Robin. The rare vascular plants of Prince Edward Island. Ottawa, Ont., Canada: Canadian Museum of Nature, 1991.

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Uncommon value: A rare book dealer's world. Ann Arbor, Mich: Arbor Libri Press, 1995.

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Lal, Bhargava Moti. Indian Ocean strategies through the ages, with rare and antique maps. New Delhi: Reliance Pub. House, 1990.

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Books, Asher Rare. 205 rare and important atlases, books, manuscripts, charts, maps and views. Ijmuiden, NE: Asher Rare Books, 2001.

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Nelson, Christopher. Mapping the Civil War: Featuring rare maps from the Library of Congress. [Washington, D.C.]: Starwood Pub., 1992.

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Buchteile zum Thema "Rare maps"

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Clarke, Colin. „Maps“. In Race, Class, and the Politics of Decolonization, 29–36. New York: Palgrave Macmillan US, 2016. http://dx.doi.org/10.1057/9781137540782_2.

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Nagnibeda, Ekaterina, und Elena Kustova. „Reaction Rate Coefficients“. In Heat and Mass Transfer, 171–90. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-01390-4_7.

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Onge, Jeffrey St. „The Circulation of Rage“. In Affect, Emotion, and Rhetorical Persuasion in Mass Communication, 183–94. New York, NY: Routledge, 2019.: Routledge, 2018. http://dx.doi.org/10.4324/9781351242370-14.

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Yuan, Zhi, Thomas Stützle und Mauro Birattari. „MADS/F-Race: Mesh Adaptive Direct Search Meets F-Race“. In Trends in Applied Intelligent Systems, 41–50. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-13022-9_5.

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Roberg-Larsen, Hanne, und Steven Ray Wilson. „CHAPTER 3. Low-flow Rate Separations of Lipids“. In New Developments in Mass Spectrometry, 49–73. Cambridge: Royal Society of Chemistry, 2020. http://dx.doi.org/10.1039/9781788013109-00049.

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Reimann, Peter, und Peter Talkner. „Invariant Densities and Escape Rates for Maps with Weak Gaussian Noise“. In New Trends in Kramers’ Reaction Rate Theory, 143–75. Dordrecht: Springer Netherlands, 1995. http://dx.doi.org/10.1007/978-94-011-0465-4_7.

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Prieto, Gorka, und Jesús Vázquez. „Calculation of False Discovery Rate for Peptide and Protein Identification“. In Mass Spectrometry Data Analysis in Proteomics, 145–59. New York, NY: Springer New York, 2019. http://dx.doi.org/10.1007/978-1-4939-9744-2_6.

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Cardenas, Valerie A., und Colin Studholme. „Co-analysis of Maps of Atrophy Rate and Atrophy State in Neurodegeneration“. In Medical Image Computing and Computer-Assisted Intervention – MICCAI 2004, 680–87. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-30136-3_83.

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Luo, Zeyu, Xian-Bo Wang und Zhi-Xin Yang. „Fault Representations of Bearing Race Based on Grayscale Maps and CNN Networks“. In Proceedings of IncoME-V & CEPE Net-2020, 61–68. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-75793-9_7.

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Fiorentino, Costanza, A. R. Donvito, P. D’Antonio und S. Lopinto. „Experimental Methodology for Prescription Maps of Variable Rate Nitrogenous Fertilizers on Cereal Crops“. In Lecture Notes in Civil Engineering, 863–72. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-39299-4_93.

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Konferenzberichte zum Thema "Rare maps"

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Petrushin, Valery A. „Mining rare and frequent events in multi-camera surveillance video using self-organizing maps“. In Proceeding of the eleventh ACM SIGKDD international conference. New York, New York, USA: ACM Press, 2005. http://dx.doi.org/10.1145/1081870.1081975.

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Cavaluzzi, Jack, Chase Gilmore, Bilal Khan und Minh Hong Tran. „Probability of the Loss of Offsite Power and Damage to Road Network due to a Rare Event“. In 2012 20th International Conference on Nuclear Engineering and the ASME 2012 Power Conference. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/icone20-power2012-54582.

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The main goal of the project was to better understand the impact to a nuclear power plant due to the unavailability of critical infrastructure. We evaluated the use of rare event analysis to establish rare event occurrences in the vicinity of the plant. For the purpose of this report, rare events were considered extreme scenarios of natural disasters. The initial data was acquired by viewing STP FSARs and topographical maps of the region. The two specific factors that were extracted by analyzing the initial data of the plant design and location were the road networks and the electrical grid system. These two variables were then analyzed in light of the rare event analysis model that was used as a building block for this project. The rare event analysis also provided information regarding the types of data and distributions that were likely to be seen as a result. For the road networks, the road layout around the plant was mapped and the relevant data was used to consider the possible routes to the plants in case of a rare event. Data regarding LOOP Events were gathered mainly from NRC Documents and Institutional Sources. These data were used to analyze how many events occurred per year and the downtime associated with the rare event.
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Anderson, Mark. „Compressor Map Corrections for Highly Non-Linear Fluid Properties“. In ASME Turbo Expo 2021: Turbomachinery Technical Conference and Exposition. American Society of Mechanical Engineers, 2021. http://dx.doi.org/10.1115/gt2021-60275.

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Abstract Turbomachinery systems are often subject to variations in ambient conditions and applied loads in operation. Standard maps (perhaps the most common being pressure ratio verses mass flow for compressors) are usually presented in terms of fixed inflow conditions. To account for changes in performance due to varying inlet conditions, compressors maps are often presented in standardized form where the mass flow and rotational speeds are normalized as a function of the reference condition total pressure and temperature. These methods are very widely used, particularly in the turbo charger industry. With these normalized maps, the actual performance of a compressor in a given environment can be deduced simply and easily with very reasonable accuracy in most cases. The underlaying assumption of this conventional normalization process is that the fluid behaves as a perfect gas. While this is usually sufficient for air compressors, the method is not viable where the fluid properties are not near perfect gas conditions, which is certainly the case for supercritical applications. The highly variable fluid properties near the critical point, and the challenges they present in design, have been well documented in the literature. The two most critical properties to consider in the design process are the density and the speed of sound. The density determines the volumetric flow for a given mass flow and this in turn determines the incidence angle, a primary driver of performance. The speed of sound directly affects the range of the compressor via choking. Choking range can be further complicated by the fact that under certain conditions, the choked state can be reached at Mach numbers less than one. While rare, this situation can occur when the inflow conditions are found close to the liquid side of the saturation dome. To account for these effects, a new method is proposed to generate normalized maps of performance that can be used to determine actual performance of a wide range of inlet conditions for highly non-linear thermodynamic properties. Although not as simple as the conventional perfect gas method that can be applied in a “back-of-the-envelope” style, the new method can be applied very rapidly using a spreadsheet-based method directly calling high fidelity NIST thermodynamic models. The end result of this tool is that a compressor map that has been painstakingly generated with testing or CFD can be applied to any inlet condition and the range and performance predicted very rapidly with high accuracy.
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Benny, Dayana, Kumary R. Soumya und K. Nageswara Rao. „New Dynamic Self-Organizing Feature Maps for the classification of extracted feature vectors of characters“. In 2015 International Conference on Robotics, Automation, Control and Embedded Systems (RACE). IEEE, 2015. http://dx.doi.org/10.1109/race.2015.7097273.

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Donica, Ala, Andrei Crăciun und Natalia Raileanu. „Monitoringul daunatorilor defoliatori arboretelor de cvercinee prin capcane feromonale (studiu de caz)“. In Impactul antropic asupra calitatii mediului. Institute of Ecology and Geography, Republic of Moldova, 2019. http://dx.doi.org/10.53380/9789975330800.25.

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Studies on the monitoring of the most damaging defoliant species of oaks (Lymantria dispar and Totrix viridana) through pheromone traps in forest ecosystems are some of the rare achievements in this field, for our country. It has been shown that during the vegetation season there is an alternation of defoliant species, with the presence and development of the II generations, harmful to the foliar limb (the quantity of pests being higher during the first generations and reduced in the second generation). The activity of phytophagus insects was directly influenced by the climatic conditions in the studied areas, the presence of the nutrition source - oaks and the presence of the infestation source. Based on the evidence of males captured in the pheromone traps, digital maps of the spatial distribution of the imago of studied species were developed, which allowed the determination of the position, the direction of spreading and the size of the pests (the necessary studies in sustainable forest management).
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Saussie, David, Ouassima Akhrif und Lahcen Saydy. „Aircraft pitch rate control design with guardian maps“. In Automation (MED 2010). IEEE, 2010. http://dx.doi.org/10.1109/med.2010.5547842.

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Hughes, Karl, und Edmund Cracknell. „Gamma-Ray Imaging for Generating 3D Dose Rate Maps“. In ASME 2011 14th International Conference on Environmental Remediation and Radioactive Waste Management. ASMEDC, 2011. http://dx.doi.org/10.1115/icem2011-59123.

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The use of gamma-ray imaging has become established in the nuclear industry, especially in the fields of decommissioning and clean-up, for identifying the origins of elevated gamma dose rates. Since their first use in the mid 1990s, gamma-ray imaging devices, such as the Babcock RadScan, have been used to produce colour overlay plots that indicate, in two dimensions, the locations and distribution of radioactive contaminants. This information is invaluable in helping project managers to plan clean-up and shielding activities, ensuring that all work carried out is cost effective and ALARP. Recent work undertaken by Babcock demonstrates the capability to generate 3D maps of dose rate fields from the output of gamma-ray imaging work. The combination of gamma-ray imaging survey and resultant dose map is a very powerful tool for planning decommissioning. The conventional gamma-ray image provides an unambiguous identification of the origins of the dose rates present whilst the 3D dose map allows the dose uptake to personnel to be determined. Furthermore, the ability to quantify the effect of clean-up or shielding on the dose rates is possible, providing project teams with a metric for determining the best option available. A simple procedure is followed to generate 3D dose maps from gamma-ray imaging data. Firstly a model of the plant area is constructed. This model can be generated from existing plant drawings, from laser scan surveys, or from simple physical measurements taken on plant. The model includes information about the shielding properties of the plant structures, and can be easily modified to demonstrate the effect of adding more shielding, or of reducing any of the source terms. The data from a gamma-ray imager, such as RadScan, are analysed to generate distributions of radionuclide specific activities. These activities are entered into the model and form the source term. The advantage of using a gamma ray imager to generate the source term is that the location and distribution of the source is accurately represented in the model, thus ensuring that accurate dose maps are generated. Once the model has been completed it is analysed using a radiation transport modelling code such as Attila to produce the 3D dose maps (although other codes are available which could perform the same function). This paper describes an example of how this technique has been used to generate 3D dose maps for a customer and builds on earlier work with RadScan which provides quantitative in-cell assay.
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Li, Huijun, Huan Wang und Gerd Ascheid. „Channel Correlation Maps for Rate-Adaptive MIMO-OFDMA Systems“. In 2014 IEEE Vehicular Technology Conference (VTC 2014-Spring). IEEE, 2014. http://dx.doi.org/10.1109/vtcspring.2014.7022858.

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Kim, Tae-Seok, Gentian Jakllari, Srikanth V. Krishnamurthy und Michalis Faloutsos. „A Unified Metric for Routing and Rate Adaptation in Multi-Rate Wireless Mesh Networks“. In 2011 IEEE 8th International Conference on Mobile Ad-Hoc and Sensor Systems (MASS). IEEE, 2011. http://dx.doi.org/10.1109/mass.2011.31.

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Castle, Robert, Georg Klein und David W. Murray. „Video-rate localization in multiple maps for wearable augmented reality“. In 2008 12th IEEE International Symposium on Wearable Computers. IEEE, 2008. http://dx.doi.org/10.1109/iswc.2008.4911577.

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Berichte der Organisationen zum Thema "Rare maps"

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Evans, Julie, Kendra Sikes und Jamie Ratchford. Vegetation classification at Lake Mead National Recreation Area, Mojave National Preserve, Castle Mountains National Monument, and Death Valley National Park: Final report (Revised with Cost Estimate). National Park Service, Oktober 2020. http://dx.doi.org/10.36967/nrr-2279201.

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Vegetation inventory and mapping is a process to document the composition, distribution and abundance of vegetation types across the landscape. The National Park Service’s (NPS) Inventory and Monitoring (I&M) program has determined vegetation inventory and mapping to be an important resource for parks; it is one of 12 baseline inventories of natural resources to be completed for all 270 national parks within the NPS I&M program. The Mojave Desert Network Inventory & Monitoring (MOJN I&M) began its process of vegetation inventory in 2009 for four park units as follows: Lake Mead National Recreation Area (LAKE), Mojave National Preserve (MOJA), Castle Mountains National Monument (CAMO), and Death Valley National Park (DEVA). Mapping is a multi-step and multi-year process involving skills and interactions of several parties, including NPS, with a field ecology team, a classification team, and a mapping team. This process allows for compiling existing vegetation data, collecting new data to fill in gaps, and analyzing the data to develop a classification that then informs the mapping. The final products of this process include a vegetation classification, ecological descriptions and field keys of the vegetation types, and geospatial vegetation maps based on the classification. In this report, we present the narrative and results of the sampling and classification effort. In three other associated reports (Evens et al. 2020a, 2020b, 2020c) are the ecological descriptions and field keys. The resulting products of the vegetation mapping efforts are, or will be, presented in separate reports: mapping at LAKE was completed in 2016, mapping at MOJA and CAMO will be completed in 2020, and mapping at DEVA will occur in 2021. The California Native Plant Society (CNPS) and NatureServe, the classification team, have completed the vegetation classification for these four park units, with field keys and descriptions of the vegetation types developed at the alliance level per the U.S. National Vegetation Classification (USNVC). We have compiled approximately 9,000 existing and new vegetation data records into digital databases in Microsoft Access. The resulting classification and descriptions include approximately 105 alliances and landform types, and over 240 associations. CNPS also has assisted the mapping teams during map reconnaissance visits, follow-up on interpreting vegetation patterns, and general support for the geospatial vegetation maps being produced. A variety of alliances and associations occur in the four park units. Per park, the classification represents approximately 50 alliances at LAKE, 65 at MOJA and CAMO, and 85 at DEVA. Several riparian alliances or associations that are somewhat rare (ranked globally as G3) include shrublands of Pluchea sericea, meadow associations with Distichlis spicata and Juncus cooperi, and woodland associations of Salix laevigata and Prosopis pubescens along playas, streams, and springs. Other rare to somewhat rare types (G2 to G3) include shrubland stands with Eriogonum heermannii, Buddleja utahensis, Mortonia utahensis, and Salvia funerea on rocky calcareous slopes that occur sporadically in LAKE to MOJA and DEVA. Types that are globally rare (G1) include the associations of Swallenia alexandrae on sand dunes and Hecastocleis shockleyi on rocky calcareous slopes in DEVA. Two USNVC vegetation groups hold the highest number of alliances: 1) Warm Semi-Desert Shrub & Herb Dry Wash & Colluvial Slope Group (G541) has nine alliances, and 2) Mojave Mid-Elevation Mixed Desert Scrub Group (G296) has thirteen alliances. These two groups contribute significantly to the diversity of vegetation along alluvial washes and mid-elevation transition zones.
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Montgomery, Doug, Mark Carson, Timothy Winters, Michayla Newcombe und Timothy Carlin. NIST IPv6 Profile. National Institute of Standards and Technology, November 2020. http://dx.doi.org/10.6028/nist.sp.500-267ar1.

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This profile establishes a basic taxonomy of IPv6 capabilities, defined in terms of IETF specifications, resulting in specific capability labels for common network functions and usage scenarios. The profile maps each such labeled capability to one or more specific technical specifications, or parts of specifications. Each labeled capability adopts by reference the normative requirements of the cited specifications. In rare cases the profile may augment or modify the normative requirements of a base specification. The defined capability labels effectively form a vocabulary for expressing IPv6 requirements for, and documenting the IPv6 capabilities of, specific products. It is expected that, when combined with specific acquisition and product testing programs, this profile can facilitate the efficient adoption of IPv6 technologies in many industry sectors.
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Montgomery, Doug, Mark Carson, Timothy Winters, Michayla Newcombe und Timothy Carlin. USGv6 Profile. National Institute of Standards and Technology, November 2020. http://dx.doi.org/10.6028/nist.sp.500-267br1.

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This profile establishes a basic taxonomy of IPv6 capabilities, defined in terms of IETF specifications, resulting in specific capability labels for common network functions and usage scenarios. The profile maps each such labeled capability to one or more specific technical specifications, or parts of specifications. Each labeled capability adopts by reference the normative requirements of the cited specifications. In rare cases the profile may augment or modify the normative requirements of a base specification. The defined capability labels effectively form a vocabulary for expressing IPv6 requirements for, and documenting the IPv6 capabilities of, specific products. It is expected that this profile, when combined with the USGv6 Test Program, can facilitate the efficient adoption of IPv6 technologies in Federal information systems.
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Thomas, Douglas, und Mellon Michael. Sublimation of terrestrial permafrost and the implications for ice-loss processes on Mars. Engineer Research and Development Center (U.S.), Juli 2021. http://dx.doi.org/10.21079/11681/41244.

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Sublimation of ice is rate-controlled by vapor transport away from its outer surface and may have generated landforms on Mars. In ice-cemented ground (permafrost), the lag of soil particles remaining after ice loss decreases subsequent sublimation. Varying soil-ice ratios lead to differential lag development. Here we report 52 years of sublimation measurements from a permafrost tunnel near Fairbanks, Alaska, and constrain models of sublimation, diffusion through porous soil, and lag formation. We derive the first long-term in situ effective diffusion coefficient of ice-free loess, a Mars analog soil, of 9.05 × 10⁻⁶ m² s⁻¹, ~5× larger than past theoretical studies. Exposed ice-wedge sublimation proceeds ~4× faster than predicted from analogy to heat loss by buoyant convection, a theory frequently employed in Mars studies. Our results can be used to map near-surface ice-content differences, identify surface processes controlling landform formation and morphology, and identify target landing sites for human exploration of Mars.
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de Caritat, Patrice, Brent McInnes und Stephen Rowins. Towards a heavy mineral map of the Australian continent: a feasibility study. Geoscience Australia, 2020. http://dx.doi.org/10.11636/record.2020.031.

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Heavy minerals (HMs) are minerals with a specific gravity greater than 2.9 g/cm3. They are commonly highly resistant to physical and chemical weathering, and therefore persist in sediments as lasting indicators of the (former) presence of the rocks they formed in. The presence/absence of certain HMs, their associations with other HMs, their concentration levels, and the geochemical patterns they form in maps or 3D models can be indicative of geological processes that contributed to their formation. Furthermore trace element and isotopic analyses of HMs have been used to vector to mineralisation or constrain timing of geological processes. The positive role of HMs in mineral exploration is well established in other countries, but comparatively little understood in Australia. Here we present the results of a pilot project that was designed to establish, test and assess a workflow to produce a HM map (or atlas of maps) and dataset for Australia. This would represent a critical step in the ability to detect anomalous HM patterns as it would establish the background HM characteristics (i.e., unrelated to mineralisation). Further the extremely rich dataset produced would be a valuable input into any future machine learning/big data-based prospectivity analysis. The pilot project consisted in selecting ten sites from the National Geochemical Survey of Australia (NGSA) and separating and analysing the HM contents from the 75-430 µm grain-size fraction of the top (0-10 cm depth) sediment samples. A workflow was established and tested based on the density separation of the HM-rich phase by combining a shake table and the use of dense liquids. The automated mineralogy quantification was performed on a TESCAN® Integrated Mineral Analyser (TIMA) that identified and mapped thousands of grains in a matter of minutes for each sample. The results indicated that: (1) the NGSA samples are appropriate for HM analysis; (2) over 40 HMs were effectively identified and quantified using TIMA automated quantitative mineralogy; (3) the resultant HMs’ mineralogy is consistent with the samples’ bulk geochemistry and regional geological setting; and (4) the HM makeup of the NGSA samples varied across the country, as shown by the mineral mounts and preliminary maps. Based on these observations, HM mapping of the continent using NGSA samples will likely result in coherent and interpretable geological patterns relating to bedrock lithology, metamorphic grade, degree of alteration and mineralisation. It could assist in geological investigations especially where outcrop is minimal, challenging to correctly attribute due to extensive weathering, or simply difficult to access. It is believed that a continental-scale HM atlas for Australia could assist in derisking mineral exploration and lead to investment, e.g., via tenement uptake, exploration, discovery and ultimately exploitation. As some HMs are hosts for technology critical elements such as rare earth elements, their systematic and internally consistent quantification and mapping could lead to resource discovery essential for a more sustainable, lower-carbon economy.
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Mitler, Henri E. Algorithm for the mass-loss rate of a burning wall. Gaithersburg, MD: National Bureau of Standards, 1987. http://dx.doi.org/10.6028/nbs.ir.87-3682.

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7

Buckle, J. L., J. M. Carson, K. L. Ford, R. Fortin und W F Miles. Radioactivity map of Canada, natural air absorbed dose rate. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 2014. http://dx.doi.org/10.4095/293353.

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8

Carson, J. M., P. B. Holman und K. L. Ford. Natural air absorbed dose rate radioactivity map of Manitoba, Manitoba. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 2008. http://dx.doi.org/10.4095/224862.

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9

Carson, J. M., P. B. Holman, R. B. K. Shives, K. L. Ford, K. Ashton und W. Slimmon. Total air absorbed dose rate map, Saskatchewan, NTS 74N/6. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 2001. http://dx.doi.org/10.4095/212470.

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10

Balaram, V. Rare-earth element analysis of iron-formation reference samples by inductively coupled plasma mass spectrometry (ICP-MS). Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 1993. http://dx.doi.org/10.4095/164254.

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