Готові списки джерел за темами / Data projection

Добірка наукової літератури з теми "Data projection"

Автор: Grafiati
Опубліковано: 14 березня 2023

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Статті в журналах з теми "Data projection"

1

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.

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Анотація:
Projection (or dimensionality reduction) techniques have been used as a means to handling the growing dimensionality of data sets as well as providing a way to visualize information coded into point relationships. Their role is essential in data interpretation and simultaneous use of different projections and their visualizations improve data understanding and increase the level of confidence in the result. For that purpose, projections should be fast to allow multiple views of the same data set. In this work we present a novel fast technique for projecting multi-dimensional data sets into bidimensional (2D) spaces that preserves neighborhood relationships. Additionally, a new technique for improving 2D projections from multi-dimensional data is presented, that helps reduce the inherent loss of information yielded by dimensionality reduction. The results are stimulating and are presented in the form of comparative visualizations against known and new 2D projection techniques. Based on the projection improvement approach presented here, a new metric for quality of projection is also given, that matches well the visual perception of quality. We discuss the implication of using improved projections in visual exploration of large data sets and the role of interaction in visualization of projected subspaces.
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2

Raymer, 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.

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Background: Education planning requires accurate and efficient projection models. Current projection models either do not make use of all available information and are reliant on idiosyncratic expert judgement, or are too complex to be maintained and explained. Aims: To test whether a multiregional projection model performs better than current methodology in explaining and projecting school enrolments in a school system with student mobility. Data and methods: A multiregional cohort model was developed for projecting enrolments for multiple schools or districts simultaneously. For illustration, data were obtained for all government schools in the Australian Capital Territory (ACT) for the years 2008–2016. Multiregional projections were compared with a cohort transition model and the ACT Education Directorate’s own projections. Results: (i) There is great diversity in the sources of school enrolment growth that need to be accommodated in enrolment projections; and (ii) multiregional projections perform slightly better than traditional methods with less effort and more transparency. Conclusion: A sources of growth approach guides the understanding of enrolment change, which is critical for making informed projections.
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3

Lehmann, 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.

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4

Vlassis, 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.

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High-dimensional data generated by a system with limited degrees of freedom are often constrained in low-dimensional manifolds in the original space. In this article, we investigate dimension-reduction methods for such intrinsically low-dimensional data through linear projections that preserve the manifold structure of the data. For intrinsically one-dimensional data, this implies projecting to a curve on the plane with as few intersections as possible. We are proposing a supervised projection pursuit method that can be regarded as an extension of the single-index model for nonparametric regression. We show results from a toy and two robotic applications.
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5

Kessler, 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.

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As developments in the field of map projections occur (e.g., the deriving of a new map projection), it would be reasonable to expect that those developments that are important from a teaching standpoint would be included in cartography textbooks. However, researchers have not examined whether map projection material presented in cartography textbooks is keeping pace with developments in the field and whether that material is important for cartography students to learn. To provide such an assessment, I present the results of a content analysis of projection material discussed in 24 cartography textbooks published during the twentieth and early twenty-first centuries. Results suggest that some material, such as projection properties, was discussed in all textbooks across the study period. Other material, such as methods used to illustrate distortion patterns, and the importance of datums, was either inconsistently presented or rarely mentioned. Comparing recent developments in projections to the results of the content analysis, I offer three recommendations that future cartography textbooks should follow when considering what projection material is important. First, textbooks should discuss the importance that defining a coordinate system has in the digital environment. Second, textbooks should summarize the results from experimental studies that provide insights into how map readers understand projections and how to choose appropriate map projections. Third, textbooks should review the impacts of technology on projections, such as the web Mercator projection, programming languages, and the challenges of projecting raster data.
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6

Schreck, 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.

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The analysis of high-dimensional data is an important, yet inherently difficult problem. Projection techniques such as Principal Component Analysis, Multi-dimensional Scaling and Self-Organizing Map can be used to map high-dimensional data to 2D display space. However, projections typically incur a loss in information. Often, uncertainty exists regarding the precision of the projection as compared with its original data characteristics. While the output quality of these projection techniques can be discussed in terms of aggregate numeric error values, visualization is often helpful for better understanding the projection results. We address the visual assessment of projection precision by an approach integrating an appropriately designed projection precision measure directly into the projection visualization. To this end, a flexible projection precision measure is defined that allows the user to balance the degree of locality at which the measure is evaluated. Several visual mappings are designed for integrating the precision measure into the projection visualization at various levels of abstraction. The techniques are implemented in an interactive system, including methods supporting the user in finding appropriate settings of relevant parameters. We demonstrate the usefulness of the approach for visual analysis of classified and unclassified high-dimensional data sets. We show how our interactive precision quality visualization system helps to examine the preservation of original data properties in projected space.
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7

KhaIiI 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.

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Principal components analysis (PCA) is effective at compressing information in multivariate data sets by computing orthogonal projections that maximize the amount of data variance. Unfortunately, information content in hyper spectral images does not always coincide with such projections. We propose an application of projection pursuit (pp), which seeks to find a set of projections that are "interesting" in the sense that they deviate from the Gaussian distribution assumption. Once these projections are obtained, they can be used for image compression, segmentation, or enhancement for visual analysis. To find these projections, a two –step iterative process is followed where we first search for a projection that maximizes a projection index based on the information divergence of the projections estimated probability distribution from the Gaussian distribution and then reduce the rank by projections the data on to the subspace orthogonal to the previous projection . To calculate each projections, we use a simplified approach to maximizing the projection index, which does not require optimization algorithm. It searches for a solution by obtaining a set of candidate projections from the data and choosing the one with the highest projection index. The effectiveness of the method is demonstrated through simulated examples as well as data from the hyper spectral digital imagery collection experiment and the spatially enhanced broadband and array spectrograph system.
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8

Spur, 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.

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Abstract. Immersive geospatial visualization finds increasing application for navigation, exploration, and analysis. Many such require the display of data at different scales, often in views with three-dimensional geometry. Multi-view solutions, such as focus+context, overview+detail, and distorted projections can show different scales at the same time, and help place an area of interest within its surroundings. By inverting the principle of stereographic projection – projecting spatial features from a map onto a virtual sphere which surrounds the viewer – we present a novel technique for immersive geospatial focus+context that aims to mitigate problems with existing solutions. This sphere can intersect the map, dividing it into two parts: the inside of the sphere, which stays unchanged, and the outside, which gets projected to the surface, resulting in an inversion of the lens metaphor by distorting the context instead of the focus. This detail-in-context visualization maximizes the amount of context that can be legibly shown by the smooth compression inherent to the stereographic projection, and by utilizing otherwise unused screen space in the sky. The projection method allows for easy control over the projection and distortion characteristics by varying only two main parameters – the sphere’s radius and its position. The omnidirectional nature of our system makes it particularly well-suited for immersive displays by accommodating typical immersive exploration and fully utilizing the additional visual space available. Applying our system to an urban environment, we were able to solicit positive reactions during feedback sessions with experts from urbanism.
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9

Chen, 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.

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Adopting the framework of projection from Systemic Functional Linguistics, the present study explored the deployment of projection in summary writing by three levels of college EFL learners from a university in mainland China. Data were collected from one summary writing by three classes of different levels’ learners in an English program from a university in the southern part of mainland China. Quantitative analysis showed that projections increased dramatically from Year 1 to Year 2 and dropped slightly from Year 2 to Year 3. Qualitative analysis revealed that the use of projecting verbs showed huge differences among the three levels of learners. Year 1 students used only a very limited range of projecting verbs. Year 2 learners used a more comprehensive range of such verbs but tended to use them repetitively and inappropriately. In contrast, year 3 students used a much more comprehensive range of projecting verbs in their summary writing and construed projection at different levels. It is recommended that more attention should be paid to the teaching of projection at phrase and text levels in EAP.
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10

Chen, 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.

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Анотація:
Adopting the framework of projection from Systemic Functional Linguistics, the present study explored the deployment of projection in summary writing by three levels of college EFL learners from a university in mainland China. Data were collected from one summary writing by three classes of different levels’ learners in an English program from a university in the southern part of mainland China. Quantitative analysis showed that projections increased dramatically from Year 1 to Year 2 and dropped slightly from Year 2 to Year 3. Qualitative analysis revealed that the use of projecting verbs showed huge differences among the three levels of learners. Year 1 students used only a very limited range of projecting verbs. Year 2 learners used a more comprehensive range of such verbs but tended to use them repetitively and inappropriately. In contrast, year 3 students used a much more comprehensive range of projecting verbs in their summary writing and construed projection at different levels. It is recommended that more attention should be paid to the teaching of projection at phrase and text levels in EAP.
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Дисертації з теми "Data projection"

1

McWilliams, Brian Victor Parulian. "Projection based models for high dimensional data." Thesis, Imperial College London, 2011. http://hdl.handle.net/10044/1/9577.

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In recent years, many machine learning applications have arisen which deal with the problem of finding patterns in high dimensional data. Principal component analysis (PCA) has become ubiquitous in this setting. PCA performs dimensionality reduction by estimating latent factors which minimise the reconstruction error between the original data and its low-dimensional projection. We initially consider a situation where influential observations exist within the dataset which have a large, adverse affect on the estimated PCA model. We propose a measure of “predictive influence” to detect these points based on the contribution of each point to the leave-one-out reconstruction error of the model using an analytic PRedicted REsidual Sum of Squares (PRESS) statistic. We then develop a robust alternative to PCA to deal with the presence of influential observations and outliers which minimizes the predictive reconstruction error. In some applications there may be unobserved clusters in the data, for which fitting PCA models to subsets of the data would provide a better fit. This is known as the subspace clustering problem. We develop a novel algorithm for subspace clustering which iteratively fits PCA models to subsets of the data and assigns observations to clusters based on their predictive influence on the reconstruction error. We study the convergence of the algorithm and compare its performance to a number of subspace clustering methods on simulated data and in real applications from computer vision involving clustering object trajectories in video sequences and images of faces. We extend our predictive clustering framework to a setting where two high-dimensional views of data have been obtained. Often, only either clustering or predictive modelling is performed between the views. Instead, we aim to recover clusters which are maximally predictive between the views. In this setting two block partial least squares (TB-PLS) is a useful model. TB-PLS performs dimensionality reduction in both views by estimating latent factors that are highly predictive. We fit TB-PLS models to subsets of data and assign points to clusters based on their predictive influence under each model which is evaluated using a PRESS statistic. We compare our method to state of the art algorithms in real applications in webpage and document clustering and find that our approach to predictive clustering yields superior results. Finally, we propose a method for dynamically tracking multivariate data streams based on PLS. Our method learns a linear regression function from multivariate input and output streaming data in an incremental fashion while also performing dimensionality reduction and variable selection. Moreover, the recursive regression model is able to adapt to sudden changes in the data generating mechanism and also identifies the number of latent factors. We apply our method to the enhanced index tracking problem in computational finance.
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2

Sibley, Christy N. "Analyzing Navy Officer Inventory Projection Using Data Farming." Thesis, Monterey, California. Naval Postgraduate School, 2012. http://hdl.handle.net/10945/6868.

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Approved for public release, distribution unlimited
The 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.
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3

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.

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4

Ebert, 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.

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5

Cropanese, Frank C. "Synthesis of low k1 projection lithography utilizing interferometry /." Link to online version, 2005. https://ritdml.rit.edu/dspace/handle/1850/1235.

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6

Folgieri, 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.

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In this work we focused on methods to solve classification problems characterized by high dimensionality and low cardinality data. These features are relevant in bio-molecular data analysis and particularly in class prediction whith microarray data. Many methods have been proposed to approach this problem, characterized by the so called curse of dimensionality (term introduced by Richard Bellman (9)). Among them, gene selection methods, principal and independent component analysis, kernel methods. In this work we propose and we experimentally analyze two ensemble methods based on two randomized techniques for data compression: Random Subspaces and Random Projections. While Random Subspaces, originally proposed by T. K. Ho, is a technique related to feature subsampling, Random Projections is a feature extraction technique motivated by the Johnson-Lindenstrauss theory about distance preserving random projections. The randomness underlying the proposed approach leads to diverse sets of extracted features corresponding to low dimensional subspaces with low metric distortion and approximate preservation of the expected loss of the trained base classifiers. In the first part of the work we justify our approach with two theoretical results. The first regards unsupervised learning: we prove that a clustering algorithm minimizing the objective (quadratic) function provides a -closed solution if applied to compressed data according to Johnson-Lindenstrauss theory. The second one is related to supervised learning: we prove that Polynomials kernels are approximatively preserved by Random Projections, up to a degradation proportional to the square of the degree of the polynomial. In the second part of the work, we propose ensemble algorithms based on Random Subspaces and Random Projections, and we experimentally compare them with single SVM and other state-of-the-art ensemble methods, using three gene expression data set: Colon, Leukemia and DLBL-FL - i.e. Diffuse Large B-cell and Follicular Lymphoma. The obtained results confirm the effectiveness of the proposed approach. Moreover, we observed a certain performance degradation of Random Projection methods when the base learners are SVMs with polynomial kernel of high degree.
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7

Bolton, 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.

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8

Kishimoto, Paul Natsuo. "Transport demand in China : estimation, projection, and policy assessment." Thesis, Massachusetts Institute of Technology, 2018. http://hdl.handle.net/1721.1/120664.

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Thesis: Ph. D. in Engineering Systems, Massachusetts Institute of Technology, School of Engineering, Institute for Data, Systems, and Society, 2018.
Cataloged 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
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9

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.

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Pilots or autonomous aircraft need to know where they are in relation to the environment. On board aircraft there are inertial sensors that are prone to drift which requires corrections by referencing against known items, places, or signals. One such method of referencing is with global navigation satellite systems, and others, that are highlighted in this work, are based on using visual sensors. In particular the use of Synthetic Aperture Radar is emerging as a viable alternative. To use radar images in qualitative or quantitative analysis they must be registered with geographical information. Position data on an aircraft or spacecraft is not sufficient to determine with certainty what or where it is one is looking at in a radar image without referencing other images over the same area. It is demonstrated in this thesis that a digital elevation model can be split up and classified into different types of radar scatterers. Different parts of the terrain yielding different types of echoes increases the amount of radar specific characteristics in simulated reference images. This work also presents an interpretation of the imaging geometry of SAR such that existing methods in Computer Vision may be used to estimate the position from which a radar image has been taken. This is a direct image matching without requiring registration that is necessary for other proposals of SAR-based navigation solutions. By determination of position continuously from radar images, aircraft could navigate independently of day light, weather, and satellite data.
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10

Gentle, David John. "Tomographic image reconstruction from incomplete projection data with application to industry." Thesis, University of Surrey, 1990. http://epubs.surrey.ac.uk/842931/.

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The major objective of this work has been to investigate methods of reconstructing tomographic images from incomplete projection data. Furthermore the practical application of such techniques to industrial non-destructive testing has been considered with particular regard to the nuclear industry. Two distinct situations are considered, region of interest (ROI) tomography and limited angle of view (LV) tomography. ROI tomography relates to situations where data is limited in linear extent and can be used for high spatial resolution imaging of particular areas of interest within larger structures. Data collection times are reduced by concentrating on the ROI and the imaging of structures which cannot fit in the field of view of the scanner can be made possible. It has been shown that corrected ROI images can be of equal quality to those reconstructed from complete data. The situation where data is limited in angular range is known as LV tomography. Practical applications of such situations can include in situ imaging of objects which cannot be accessed at all required angles, and the imaging of time varying objects where limitations on the data collection times restrict the angular range of measurements. The use of the Gerchberg-Papoulis algorithm has been shown to significantly reduce the resulting artifacts. The initial work involved investigation into the minimum data requirements for tomographic imaging of objects without compromising image quality. The relative performance of filtered backprojection and ART iterative reconstruction algorithms were investigated and the superiority of ART in situations of limited data was demonstrated. The most important causes of SPECT image degradation are scattering and attenuation of photons. For scatter correction the dual energy window and Wiener deconvolution correction methods have been investigated and the results compared. A number of attenuation correction algorithms have also been investigated and their comparative performance evaluated.
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Книги з теми "Data projection"

1

Snyder, John Parr. Computer-assisted map projection research. Alexandria, VA: Dept. of the Interior, U.S. Geological Survey, 1985.

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2

Snyder, John Parr. Computer-assisted map projection research. Alexandria, VA: Dept. of the Interior, U.S. Geological Survey, 1985.

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3

Map projections: Georeferencing spatial data. Redlands, CA: Environmental Systems Research Institute, 1994.

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4

Geological 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.

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5

Padó, Sebastian. Cross-lingual annotation projection models for role-semantic information. Saarbrücken: Saarland University, 2007.

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6

Knapp, 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.

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7

Golubyatnikov, V. P. Uniqueness questions in reconstruction of multidimensional objects from tomography-type projection data. Utrecht: VSP, 2000.

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8

Steve, Kopp, and Environmental Systems Research Institute (Redlands, Calif.), eds. Understanding map projections: GIS by ESRI. Redlands, CA: ESRI, 2000.

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9

W, 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.

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10

W, 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.

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Частини книг з теми "Data projection"

1

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.

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Wang, 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.

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3

Sánchez 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.

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4

Lin, 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.

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Ginsburg, 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.

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6

Lê 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.

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7

Diaconis, 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.

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8

Khare, 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.

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Wilson, 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.

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Lê 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.

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Тези доповідей конференцій з теми "Data projection"

1

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.

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In optical disc system, the precise measurement and evaluation of focused micro-laser-spot (usually less than lum in diameter) is very important. To meet this requirement, a new method using the concept of CT scanner has been developed. A knife-edge scans the spot on the image plane. Differentiating the signal received by the detecter under the knife-edge, we get a one-dimension (1-D) projection of 2-D laser spot. Rotating the knife-edge slightly, we can get different projections at different angles. The projections measured are processed by taking the convolution and back-projecttion, just done as in the CT scanner. In this way, we get the 2-D profiles of the spot, i.e. the Point Spread Function (PSF) of the optical head. The shape and size of the spot can be got directly from the profile. The 2-D Fourier Transform of PSF results in the OTF of the optical head, which discribes the quality of the optical system quantitatively.
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2

Perez-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.

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3

Tasoulis, 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.

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4

Kapp, 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.

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Yan, 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.

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6

Strauch, 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.

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7

Cardoso 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.

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Abstract During drilling, surveys to determine the wellbore trajectory are performed at every drilling connection. However, due to the offset between the survey instrument and the bit (typically between 30-100 ft), this survey represents the sensor's position which is lagged compared to the bit. This paper describes a method to automatically calculate projections to the bit in real-time utilizing multiple data sources: WITSML stream, BHA components and rotary trend analysis while rotary drilling. The projection to the bit calculation routine is performed in real time every 30 seconds. This paper presents results of projections for four horizontal unconventional wells drilled in West Texas. Nearly 75,000 projections were generated on the four wells, validated with 839 survey stations, with median divergence of the projections from the nearest survey stations being less than one foot.
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Segoufin, 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.

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9

Bajcsy, 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.

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Carraher, 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.

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Звіти організацій з теми "Data projection"

1

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.

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2

Verbrugge, 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.

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In the December 2022 Summary of Economic Projections (SEP), the median projection for four-quarter core PCE inflation in the fourth quarter of 2025 is 2.1 percent. This same SEP has unemployment rising by nine-tenths, to 4.6 percent, by the end of 2023. We assess the plausibility of this projection using a specific nonlinear model that embeds an empirically successful nonlinear Phillips curve specification into a structural model, identifying it via an underutilized data-dependent method. We model core PCE inflation using three components that align with those noted by Chair Powell in his December 14, 2022, press conference: housing, core goods, and core-services-less-housing. Our model projects that conditional on the SEP unemployment rate path and a rapid deceleration of core goods prices, core PCE inflation moderates to only 2.75 percent by the end of 2025: inflation will be higher for longer. A deep recession would be necessary to achieve the SEP’s projected inflation path. A simple reduced-form welfare analysis, which abstracts from any danger of inflation expectations becoming unanchored, suggests that such a recession would not be optimal.
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3

Rofman, 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.

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This paper presents a first approximation to assess the impact of the COVID-19 outbreak on Argentinas pension system in both the short and medium/long-term. To this end, we have used the Pension Projection Model of the Inter-American Development Bank (IDB) to design and analyze possible scenarios and outcomes, based on alternative scenarios. According to the data analyzed and the projections, the impact of COVID-19 on Argentinas pension system in the short run seems to have been limited, particularly given the rapid recovery during the last months of 2021. The long-term impact is harder to predict. Given the macroeconomic effects of the efforts made by authorities to protect the system and pensioners during the pandemic on the one hand; and the effects of COVID-19 within the labor market on the other, overall consequences are still to be fully understood.
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4

Hirst, 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.

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Hoa 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.

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Garner, 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.

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Cooper, 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.

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Roberts, 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.

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9

Cowell, 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.

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This study considers existing off-grid initiatives that are being implemented in support of more rapid electrification in sub-Saharan Africa. After first reviewing the successes and obstacles of commonly implemented off-grid solutions, we suggest groundwater irrigation powered via off-grid solar (OGS) systems as a productivity-focused electrification solution that could be valuable to off-grid development initiatives moving forward. This solution encourages the establishment of OGS pumping infrastructure in unelectrified areas in proximity to nonirrigated agriculture that have promising and sustainable groundwater abstraction potential. Using open-access spatial data to estimate the alignment of these resources is an important first step in determining potential study sites for on-the-ground research and pilot projects. This study focuses on applying the above approach to Ethiopia to produce a spatial layer representing areas that are recommended for further assessment of their OGS groundwater irrigation viability. We follow the spatial analysis with a projection of potential gains from investment in OGS groundwater pumping systems under different scenarios to highlight the solution’s viability with regional context. This assessment provides an initial methodology for identifying, examining, and expanding upon potential markets where OGS irrigation can become an economically viable solution.
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Naguib, 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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We shed new light on the short-term dynamic effects of cyclones on local economic growth in India. We proxy local GDP growth with night-time light intensity data and construct a cyclone index that varies across months and districts depending on windspeed exposures. Using local projections on highly granular data for the period 1993M1-2011M12, we find that yearly estimations hide large short-term differential impacts and that the negative impact of cyclones is the largest between 4 and 8 months after the event.
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