Academic literature on the topic 'Data projection'
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Journal articles on the topic "Data projection"
Tejada, Eduardo, Rosane Minghim, and Luis Gustavo Nonato. "On Improved Projection Techniques to Support Visual Exploration of Multi-Dimensional Data Sets." Information Visualization 2, no. 4 (December 2003): 218–31. http://dx.doi.org/10.1057/palgrave.ivs.9500054.
Full textRaymer, James, Nicholas Biddle, and Qing Guan. "A multiregional sources of growth model for school enrolment projections." Australian Population Studies 1, no. 1 (November 19, 2017): 26–40. http://dx.doi.org/10.37970/aps.v1i1.10.
Full textLehmann, Dirk J., and Holger Theisel. "General Projective Maps for Multidimensional Data Projection." Computer Graphics Forum 35, no. 2 (May 2016): 443–53. http://dx.doi.org/10.1111/cgf.12845.
Full textVlassis, Nikos, Yoichi Motomura, and Ben Kröse. "Supervised Dimension Reduction of Intrinsically Low-Dimensional Data." Neural Computation 14, no. 1 (January 1, 2002): 191–215. http://dx.doi.org/10.1162/089976602753284491.
Full textKessler, Fritz. "Map Projection Education in General Cartography Textbooks: A Content Analysis." Cartographic Perspectives, no. 90 (August 16, 2018): 6–30. http://dx.doi.org/10.14714/cp90.1449.
Full textSchreck, Tobias, Tatiana von Landesberger, and Sebastian Bremm. "Techniques for Precision-Based Visual Analysis of Projected Data." Information Visualization 9, no. 3 (September 2010): 181–93. http://dx.doi.org/10.1057/ivs.2010.2.
Full textKhaIiI Ibrahim Kadhim. "Principal Components Analysis as enhancement Operator and Compression factor." journal of the college of basic education 17, no. 72 (June 17, 2019): 25–33. http://dx.doi.org/10.35950/cbej.v17i72.4495.
Full textSpur, M., V. Tourre, G. Moreau, and P. Le Callet. "VIRTUAL DATA SPHERE: INVERSE STEREOGRAPHIC PROJECTION FOR IMMERSIVE MULTI-PERSPECTIVE GEOVISUALIZATION." ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences V-4-2022 (May 18, 2022): 235–42. http://dx.doi.org/10.5194/isprs-annals-v-4-2022-235-2022.
Full textChen, Shukun, Winfred Wenhui Xuan, and Wei Yu. "Beyond Reporting Verbs: Exploring Chinese EFL Learners’ Deployment of Projection in Summary Writing." SAGE Open 12, no. 2 (April 2022): 215824402210933. http://dx.doi.org/10.1177/21582440221093356.
Full textChen, Shukun, Winfred Wenhui Xuan, and Wei Yu. "Beyond Reporting Verbs: Exploring Chinese EFL Learners’ Deployment of Projection in Summary Writing." SAGE Open 12, no. 2 (April 2022): 215824402210933. http://dx.doi.org/10.1177/21582440221093356.
Full textDissertations / Theses on the topic "Data projection"
McWilliams, Brian Victor Parulian. "Projection based models for high dimensional data." Thesis, Imperial College London, 2011. http://hdl.handle.net/10044/1/9577.
Full textSibley, Christy N. "Analyzing Navy Officer Inventory Projection Using Data Farming." Thesis, Monterey, California. Naval Postgraduate School, 2012. http://hdl.handle.net/10945/6868.
Full textThe Navys Strategic Planning and Analysis Directorate (OPNAV N14) uses a complex model to project officer status in the coming years. The Officer Strategic Analysis Model (OSAM) projects officer status using an initial inventory, historical loss rates, and dependent functions for accessions, losses, lateral transfers, and promotions that reflect Navy policy and U.S. law. OSAM is a tool for informing decision makers as they consider potential policy changes, or analyze the impact of policy changes already in place, by generating Navy Officer inventory projections for a specified time horizon. This research explores applications of data farming for potential improvement of OSAM. An analysis of OSAM inventory forecast variations over a large number of scenarios while changing multiple input parameters enables assessment of key inputs. This research explores OSAM through applying the principles of design of experiments, regression modeling, and nonlinear programming. The objectives of this portion of the work include identifying critical parameters, determining a suitable measure of effectiveness, assessing model sensitivities, evaluating performance across a spectrum of loss adjustment factors, and determining appropriate values of key model inputs for future use in forecasting Navy officer inventory.
Eslava-Gomez, Guillermina. "Projection pursuit and other graphical methods for multivariate data." Thesis, University of Oxford, 1989. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.236118.
Full textEbert, Matthias. "Non-ideal projection data in X-ray computed tomography." [S.l. : s.n.], 2002. http://www.bsz-bw.de/cgi-bin/xvms.cgi?SWB10605022.
Full textCropanese, Frank C. "Synthesis of low k1 projection lithography utilizing interferometry /." Link to online version, 2005. https://ritdml.rit.edu/dspace/handle/1850/1235.
Full textFolgieri, R. "Ensembles based on Random Projection for gene expression data analysis." Doctoral thesis, Università degli Studi di Milano, 2008. http://hdl.handle.net/2434/45878.
Full textBolton, Richard John. "Multivariate analysis of multiproduct market research data." Thesis, University of Exeter, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.302542.
Full textKishimoto, Paul Natsuo. "Transport demand in China : estimation, projection, and policy assessment." Thesis, Massachusetts Institute of Technology, 2018. http://hdl.handle.net/1721.1/120664.
Full textCataloged from PDF version of thesis. "Some pages in the original document contain text that runs off the edge of the page"--Disclaimer Notice page.
Includes bibliographical references.
China's rapid economic growth in the twenty-first century has driven, and been driven by, concomitant motorization and growth of passenger and freight mobility, leading to greater energy demand and environmental impacts. In this dissertation I develop methods to characterize the evolution of passenger transport demand in a rapidly-developing country, in order to support projection and policy assessment. In Essay #1, I study the role that vehicle tailpipe and fuel quality standards ("emissions standards") can play vis-à-vis economy-wide carbon pricing in reducing emissions of pollutants that lead to poor air quality. I extend a global, computable general equilibrium (CGE) model resolving 30 Chinese provinces by separating freight and passenger transport subsectors, road and non-road modes, and household-owned vehicles; and then linking energy demand in these subsectors to a province-level inventory of primary pollutant emissions and future policy targets. While climate policy yields an air quality co-benefit by inducing shifts away from dirtier fuels, this effect is weak within the transport sector. Current emissions standards can drastically reduce transportation emissions, but their overall impact is limited by transport's share in total emissions, which varies across provinces. I conclude that the two categories of measures examined are complementary, and the effectiveness of emissions standards relies on enforcement in removing older, higher-polluting vehicles from the roads. In Essay #2, I characterize Chinese households' demand for transport by estimating the recently-developed, Exact affine Stone index (EASI) demand system on publicly-available data from non-governmental, social surveys. Flexible, EASI demands are particularly useful in China's rapidly-changing economy and transport system, because they capture ways that income elasticities of demand, and household transport budgets, vary with incomes; with population and road network densities; and with the supply of alternative transport modes. I find transport demand to be highly elastic ([epsilon][subscript x] = 1.46) at low incomes, and that income-elasticity of demand declines but remains greater than unity as incomes rise, so that the share of transport in households' spending rises monotonically from 1.6 % to 7.5 %; a wider, yet lower range than in some previous estimates. While no strong effects of city-level factors are identified, these and other non-income effects account for a larger portion of budget share changes than rising incomes. Finally, in Essay #3, I evaluate the predictive performance of the EASI demand system, by testing the sensitivity of model fit to the data available for estimation, in comparison with the less flexible, but widely used, Almost Ideal demand system (AIDS). In rapidly-evolving countries such as China, survey data without nationwide coverage can be used to characterize transport systems, but the omission of cities and provinces could bias results. To examine this possibility, I estimate demand systems on data subsets and test their predictions against observations for the withheld fraction. I find that simple EASI specifications slightly outperform AIDS under cross-validation; these offer a ready replacement in standalone and CGE applications. However, a trade-off exists between accuracy and the inclusion of policy-relevant covariates when data omit areas with high values of these variables. Also, while province-level fixed-effects control for unobserved heterogeneity across units that may bias parameter estimates, they increase prediction error in out-of-sample applications-revealing that the influence of local conditions on household transport expenditure varies significantly across China's provinces. The results motivate targeted transport data collection that better spans variation on city types and attributes; and the validation technique aids transport modelers in designing and validating demand specifications for projection and assessment.
by Paul Natsuo Kishimoto.
Ph. D. in Engineering Systems
Divak, Martin. "Simulated SAR with GIS data and pose estimation using affine projection." Thesis, Luleå tekniska universitet, Institutionen för system- och rymdteknik, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-66303.
Full textGentle, David John. "Tomographic image reconstruction from incomplete projection data with application to industry." Thesis, University of Surrey, 1990. http://epubs.surrey.ac.uk/842931/.
Full textBooks on the topic "Data projection"
Snyder, John Parr. Computer-assisted map projection research. Alexandria, VA: Dept. of the Interior, U.S. Geological Survey, 1985.
Find full textSnyder, John Parr. Computer-assisted map projection research. Alexandria, VA: Dept. of the Interior, U.S. Geological Survey, 1985.
Find full textMap projections: Georeferencing spatial data. Redlands, CA: Environmental Systems Research Institute, 1994.
Find full textGeological Survey (U.S.), ed. Plotting azimuthal stress data on standard map projections using Geoplot. [Reston, Va.?]: U.S. Dept. of the Interior, Geological Survey, 1986.
Find full textPadó, Sebastian. Cross-lingual annotation projection models for role-semantic information. Saarbrücken: Saarland University, 2007.
Find full textKnapp, David. BOREAS soils data over the SSA in raster format and AEAC projection. Greenbelt, Md: National Aeronautics and Space Administration, Goddard Space Flight Center, 2000.
Find full textGolubyatnikov, V. P. Uniqueness questions in reconstruction of multidimensional objects from tomography-type projection data. Utrecht: VSP, 2000.
Find full textSteve, Kopp, and Environmental Systems Research Institute (Redlands, Calif.), eds. Understanding map projections: GIS by ESRI. Redlands, CA: ESRI, 2000.
Find full textW, Crockett Thomas, and Langley Research Center, eds. A scalable parallel cell-projection volume rendering algorithm for three-dimensional unstructured data. Hampton, Va: National Aeronautics and Space Administration, Langley Research Center, 1997.
Find full textW, Crockett Thomas, and Langley Research Center, eds. A scalable parallel cell-projection volume rendering algorithm for three-dimensional unstructured data. Hampton, Va: National Aeronautics and Space Administration, Langley Research Center, 1997.
Find full textBook chapters on the topic "Data projection"
Anderson, Alan J. B. "Population projection." In Interpreting Data, 139–43. Boston, MA: Springer US, 1989. http://dx.doi.org/10.1007/978-1-4899-3192-4_11.
Full textWang, Jianzhong. "Random Projection." In Geometric Structure of High-Dimensional Data and Dimensionality Reduction, 131–48. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-27497-8_7.
Full textSánchez Gassen, Nora E. "Base-year data projection." In Germany’s future electors, 169–80. Wiesbaden: Springer Fachmedien Wiesbaden, 2014. http://dx.doi.org/10.1007/978-3-658-06942-1_5.
Full textLin, Binbin, Chiyuan Zhang, and Xiaofei He. "Orthogonal Projection Analysis." In Intelligent Science and Intelligent Data Engineering, 1–8. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-31919-8_1.
Full textGinsburg, Seymour, and Chang-jie Tang. "Projection of Object Histories." In Foundations of Data Organization, 345–58. Boston, MA: Springer US, 1987. http://dx.doi.org/10.1007/978-1-4613-1881-1_28.
Full textLê Cao, Kim-Anh, and Zoe Marie Welham. "Projection to latent structures." In Multivariate Data Integration Using R, 47–58. Boca Raton: Chapman and Hall/CRC, 2021. http://dx.doi.org/10.1201/9781003026860-7.
Full textDiaconis, Persi, and Julia Salzman. "Projection pursuit for discrete data." In Institute of Mathematical Statistics Collections, 265–88. Beachwood, Ohio, USA: Institute of Mathematical Statistics, 2008. http://dx.doi.org/10.1214/193940307000000482.
Full textKhare, Kedar. "Image Reconstruction from Projection Data." In Fourier Optics and Computational Imaging, 285–92. Chichester, UK: John Wiley & Sons, Ltd, 2015. http://dx.doi.org/10.1002/9781118900352.ch21.
Full textWilson, Tom, Jeromey Temple, Peter McDonald, Ariane Utomo, and Bianca Brijnath. "Projection Methods, Data and Assumptions." In The Changing Migrant Composition of Australia’s Population, 11–22. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-88939-5_3.
Full textLê Cao, Kim-Anh, and Zoe Marie Welham. "Projection to Latent Structure (PLS)." In Multivariate Data Integration Using R, 137–76. Boca Raton: Chapman and Hall/CRC, 2021. http://dx.doi.org/10.1201/9781003026860-13.
Full textConference papers on the topic "Data projection"
Xiang-yang, Yang, Wu Min-shian, and Chin Kuo-fan. "Measuring Two Dimensional OTF Applying CT Principle." In Optical Data Storage. Washington, D.C.: Optica Publishing Group, 1985. http://dx.doi.org/10.1364/ods.1985.thdd3.
Full textPerez-Gonzalez, F., and F. Balado. "Quantized projection data hiding." In Proceedings of ICIP 2002 International Conference on Image Processing. IEEE, 2002. http://dx.doi.org/10.1109/icip.2002.1040094.
Full textTasoulis, Sotiris, Lu Cheng, Niko Valimaki, Nicholas J. Croucher, Simon R. Harris, William P. Hanage, Teemu Roos, and Jukka Corander. "Random projection based clustering for population genomics." In 2014 IEEE International Conference on Big Data (Big Data). IEEE, 2014. http://dx.doi.org/10.1109/bigdata.2014.7004291.
Full textKapp, Oscar H., and Chin-Tu Chen. "Reconstruction from limited projection data." In SPIE/IS&T 1992 Symposium on Electronic Imaging: Science and Technology, edited by Raj S. Acharya, Carol J. Cogswell, and Dmitry B. Goldgof. SPIE, 1992. http://dx.doi.org/10.1117/12.59533.
Full textYan, Donghui, Yingjie Wang, Jin Wang, Honggang Wang, and Zhenpeng Li. "K-nearest Neighbor Search by Random Projection Forests." In 2018 IEEE International Conference on Big Data (Big Data). IEEE, 2018. http://dx.doi.org/10.1109/bigdata.2018.8622307.
Full textStrauch, George E., Jiajian Jax Lin, and Jelena Tesic. "Overhead Projection Approach For Multi-Camera Vessel Activity Recognition." In 2021 IEEE International Conference on Big Data (Big Data). IEEE, 2021. http://dx.doi.org/10.1109/bigdata52589.2021.9671274.
Full textCardoso Braga, Daniel, Mohammadreza Kamyab, Brian Harclerode, and Deep Joshi. "Combining Live Drilling Data Stream with a Cloud Data Analytics Pipeline to Perform Real-Time Automated Projections to the Bit." In SPE/IADC International Drilling Conference and Exhibition. SPE, 2021. http://dx.doi.org/10.2118/204065-ms.
Full textSegoufin, Luc, and Victor Vianu. "Projection Views of Register Automata." In SIGMOD/PODS '20: International Conference on Management of Data. New York, NY, USA: ACM, 2020. http://dx.doi.org/10.1145/3375395.3387651.
Full textBajcsy, Peter, Antoine Vandecreme, and Mary Brady. "Re-projection of terabyte-sized images." In 2013 IEEE International Conference on Big Data. IEEE, 2013. http://dx.doi.org/10.1109/bigdata.2013.6691786.
Full textCarraher, Lee A., Philip A. Wilsey, Anindya Moitra, and Sayantan Dey. "Random Projection Clustering on Streaming Data." In 2016 IEEE 16th International Conference on Data Mining Workshops (ICDMW). IEEE, 2016. http://dx.doi.org/10.1109/icdmw.2016.0105.
Full textReports on the topic "Data projection"
Dahlke, Garland R. Revalidation of a REA, IMF and BF Projection Model Using Real-time Ultrasound Imaging and Feeding Data in Cattle. Ames (Iowa): Iowa State University, January 2012. http://dx.doi.org/10.31274/ans_air-180814-111.
Full textVerbrugge, Randal J., and Saeed Zaman. Post-COVID Inflation Dynamics: Higher for Longer. Federal Reserve Bank of Cleveland, January 2023. http://dx.doi.org/10.26509/frbc-wp-202306.
Full textRofman, Rafael, Joaquín Baliña, and Emanuel López. Evaluating the Impact of COVID-19 on Pension Systems in Latin America and the Caribbean. The Case of Argentina. Inter-American Development Bank, October 2022. http://dx.doi.org/10.18235/0004508.
Full textHirst, E. Data and projections on US electric-utility DSM programs: 1989--1997. Office of Scientific and Technical Information (OSTI), December 1994. http://dx.doi.org/10.2172/10180552.
Full textHoa T. Nguyen, Daithi Stone, and E. Wes Bethel. Statistical Projections for Multi-resolution, Multi-dimensional Visual Data Exploration and Analysis. Office of Scientific and Technical Information (OSTI), January 2016. http://dx.doi.org/10.2172/1235087.
Full textGarner, James M., Michael Maher, and Michael A. Minnicino. Free Fall Experimental Data for Non-Lethal Artillery Projectile Parts. Fort Belvoir, VA: Defense Technical Information Center, September 2004. http://dx.doi.org/10.21236/ada426567.
Full textCooper, Gene R., and Kevin S. Fansler. Comparison of Meteorological Data With Fitted Values Extracted from Projectile Trajectory. Fort Belvoir, VA: Defense Technical Information Center, October 1994. http://dx.doi.org/10.21236/ada285921.
Full textRoberts, Neal P. Ballistic Analysis of Firing Table Data for 155MM, M825 Smoke Projectile. Fort Belvoir, VA: Defense Technical Information Center, September 1990. http://dx.doi.org/10.21236/ada228776.
Full textCowell, Chandler, Michael P. Gallaher, Justin Larson, and Aaron Schwartz. The Potential for SolarPowered Groundwater Irrigation in Sub-Saharan Africa: An Exploratory Analysis. RTI Press, November 2022. http://dx.doi.org/10.3768/rtipress.2022.op.0079.2211.
Full textNaguib, Costanza, Martino Pelli, David Poirier, and Jeanne Tschopp. The Impact of Cyclones on Local Economic Growth: Evidence from Local Projections. CIRANO, August 2022. http://dx.doi.org/10.54932/xvof3031.
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