Journal articles on the topic 'Data projection'
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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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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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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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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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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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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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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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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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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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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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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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Luan, Guang Yu, Xue Dong Zhu, Ai Chuan Li, Zhen Su Lv, and Ren Sheng Che. "Frame Reconstruction with Missing Data from Multiple Images." Applied Mechanics and Materials 239-240 (December 2012): 1158–64. http://dx.doi.org/10.4028/www.scientific.net/amm.239-240.1158.
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To solve the missing data problem that is caused by reasons, such as occlusion, frame reconstruction by a two-level strategy in multiple images was considered. The method first performed a projective reconstruction combining singular value decomposition (SVD) and subspace method with missing data, which estimated projective shape, projection matrices, projective depths and missing data iteratively. Then it converted the projective solution to a Euclidean one with the unknown focal length and the constant principal point by enforcing constraints. Using the constraints and the fact that scale measurement matrix can recover numberless projection matrices and point matrices, the set equations of the transformation matrix from the projective reconstruction to Euclidean reconstruction were obtained. Experimental results using real images are provided to illustrate the performance of the proposed method.
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Demers, Alain, Zhenguo Qiu, Ron Dewar, and Amanda Shaw. "Validation of Canproj for projecting Canadian cancer incidence data." Health Promotion and Chronic Disease Prevention in Canada 40, no. 9 (September 2020): 267–80. http://dx.doi.org/10.24095/hpcdp.40.9.02.
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Introduction Cancer projections can provide key information to help prioritize cancer control strategies, allocate resources and evaluate current treatments and interventions. Canproj is a cancer-projection tool that builds on the Nordpred R-package by adding a selection of projection models. The objective of this project was to validate the Canproj R-package for the short-term projection of cancer rates. Methods We used national cancer incidence data from 1986 to 2014 from the National Cancer Incidence Reporting System and Canadian Cancer Registry. Cross-validation was used to estimate the accuracy of the projections generated by Canproj and relative bias (RB) was used as validation measure. The Canproj automatic model selection decision tree was also assessed. Results Five of the six models had mean RB between 5% and 10% and median RB around 5%. For some of the cancer sites that were more difficult to project, a shorter time period improved reliability. The Nordpred model was selected 79% of the time by Canproj automatic model selection although it had the smallest RB only 24% of the time. Conclusion The Canproj package was able to provide projections that closely matched the real data for most cancer sites.
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Nolze, Gert. "Azimuthal Projections: Data Rotation and Projection Switching in Real Time." Microscopy and Microanalysis 19, no. 4 (May 3, 2013): 950–58. http://dx.doi.org/10.1017/s1431927613001414.
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AbstractPole figures are often used to present crystal orientation data. The huge number of single orientation measurements acquired by electron backscatter diffraction (EBSD) poses a challenge for pole figure representation due to the large number of calculations required. This significantly reduces the speed at which the data may be rotated and affects the ability to switch between different projection types. In the present work, it will be shown that satisfactory representation of orientation data in different projection types can generally be achieved by an imaging of a spherical projection. With this approach, explicit calculation of the projections is no longer required, allowing for both real-time dataset rotation and real-time switching between all projection types relevant to materials science. The technique can be applied to any other directional property distribution, for example, not only for EBSD orientation presentation.
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Ek, Alan R., Bryan L. Randall, Jerold T. Hahn, and Roland G. Buchman. "STEMS Model Projection Capability with Plot and Tree Data Aggregation." Northern Journal of Applied Forestry 2, no. 4 (December 1, 1985): 121–27. http://dx.doi.org/10.1093/njaf/2.4.121.
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Abstract Projections of forest plot characteristics were made using the STEMS individual-tree based stand growth model for jack pine, red pine, maple-birch and aspen cover types from Michigan, Minnesota, and Wisconsin for periods of up to 50 years. Tree lists were constructed from forest survey records using various plot and tree aggregation methods, then projected and compared to projections of the same data without aggregation. The loss in projection precision due to aggregation was then weighed against savings in computer processing time as compared to the unaggregated projections. Differences between aggregated and unaggregated projections increased with greater aggregation and with longer projection periods, but in most cases were less than 10% at 50 years when the plot data were aggregated by stand density class. The largest differences were observed for pulpwood and sawtimber volumes. However, these differences were in part a function of merchantability limits based on tree size. Results indicate that dramatic cost savings can be realized with little loss in precision. North. J. Appl. For. 2:121-127, Dec. 1985.
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Hahn, Georg, Paul Fearnhead, and Idris A. Eckley. "BayesProject: Fast computation of a projection direction for multivariate changepoint detection." Statistics and Computing 30, no. 6 (August 1, 2020): 1691–705. http://dx.doi.org/10.1007/s11222-020-09966-2.
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Abstract This article focuses on the challenging problem of efficiently detecting changes in mean within multivariate data sequences. Multivariate changepoints can be detected by projecting a multivariate series to a univariate one using a suitable projection direction that preserves a maximal proportion of signal information. However, for some existing approaches the computation of such a projection direction can scale unfavourably with the number of series and might rely on additional assumptions on the data sequences, thus limiting their generality. We introduce BayesProject, a computationally inexpensive Bayesian approach to compute a projection direction in such a setting. The proposed approach allows the incorporation of prior knowledge of the changepoint scenario, when such information is available, which can help to increase the accuracy of the method. A simulation study shows that BayesProject is robust, yields projections close to the oracle projection direction and, moreover, that its accuracy in detecting changepoints is comparable to, or better than, existing algorithms while scaling linearly with the number of series.
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Bickel, Peter J., Gil Kur, and Boaz Nadler. "Projection pursuit in high dimensions." Proceedings of the National Academy of Sciences 115, no. 37 (August 27, 2018): 9151–56. http://dx.doi.org/10.1073/pnas.1801177115.
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Projection pursuit is a classical exploratory data analysis method to detect interesting low-dimensional structures in multivariate data. Originally, projection pursuit was applied mostly to data of moderately low dimension. Motivated by contemporary applications, we here study its properties in high-dimensional settings. Specifically, we analyze the asymptotic properties of projection pursuit on structureless multivariate Gaussian data with an identity covariance, as both dimension p and sample size n tend to infinity, with p/n→γ∈[0,∞]. Our main results are that (i) if γ=∞, then there exist projections whose corresponding empirical cumulative distribution function can approximate any arbitrary distribution; and (ii) if γ∈(0,∞), not all limiting distributions are possible. However, depending on the value of γ, various non-Gaussian distributions may still be approximated. In contrast, if we restrict to sparse projections, involving only a few of the p variables, then asymptotically all empirical cumulative distribution functions are Gaussian. And (iii) if γ=0, then asymptotically all projections are Gaussian. Some of these results extend to mean-centered sub-Gaussian data and to projections into k dimensions. Hence, in the “small n, large p” setting, unless sparsity is enforced, and regardless of the chosen projection index, projection pursuit may detect an apparent structure that has no statistical significance. Furthermore, our work reveals fundamental limitations on the ability to detect non-Gaussian signals in high-dimensional data, in particular through independent component analysis and related non-Gaussian component analysis.
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Vanella, Patrizio, Philipp Deschermeier, and Christina B. Wilke. "An Overview of Population Projections—Methodological Concepts, International Data Availability, and Use Cases." Forecasting 2, no. 3 (September 2, 2020): 346–63. http://dx.doi.org/10.3390/forecast2030019.
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Population projections serve various actors at subnational, national, and international levels as a quantitative basis for political and economic decision-making. Usually, the users are no experts in statistics or forecasting and therefore lack the methodological and demographic background to completely understand methods and limitations behind the projections they use to inform further analysis. Our contribution primarily targets that readership. Therefore, we give a brief overview of different approaches to population projection and discuss their respective advantages and disadvantages, alongside practical problems in population data and forecasting. Fundamental differences between deterministic and stochastic approaches are discussed, with special emphasis on the advantages of stochastic approaches. Next to selected projection data available to the public, we show central areas of application of population projections, with an emphasis on Germany.
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Wilson, Tom, and Philip Rees. "A brief guide to producing a national population projection." Australian Population Studies 5, no. 1 (May 30, 2021): 77–100. http://dx.doi.org/10.37970/aps.v5i1.84.
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Background There are surprisingly few resources available which offer an introductory guide to preparing a national population projection using a cohort-component model. Many demography textbooks cover projections quite briefly, and many academic papers on projections focus on advanced technical issues.
Aims The aim of this paper is to provide a short and accessible guide to producing a national-scale population projection using the cohort-component model.
Data and methods The paper describes the cohort-component model from a population accounting perspective, presents all the necessary projection calculations, and covers the key steps which form part of the projections preparation process – from gathering input data to validating outputs. An accompanying Excel workbook implements the model and contains example projections for Australia.
Conclusions Calculating a national population projection using a cohort-component model involves fairly simple algebra, but the broader projections preparation process is more complex, and requires careful consideration and judgement.
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Ding, Weiyi, and Xiaoxian Tang. "Projections of Tropical Fermat-Weber Points." Mathematics 9, no. 23 (December 1, 2021): 3102. http://dx.doi.org/10.3390/math9233102.
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This paper is motivated by the difference between the classical principal component analysis (PCA) in a Euclidean space and the tropical PCA in a tropical projective torus as follows. In Euclidean space, the projection of the mean point of a given data set on the principle component is the mean point of the projection of the data set. However, in tropical projective torus, it is not guaranteed that the projection of a Fermat-Weber point of a given data set on a tropical polytope is a Fermat-Weber point of the projection of the data set. This is caused by the difference between the Euclidean metric and the tropical metric. In this paper, we focus on the projection on the tropical triangle (the three-point tropical convex hull), and we develop one algorithm and its improved version, such that for a given data set in the tropical projective torus, these algorithms output a tropical triangle, on which the projection of a Fermat-Weber point of the data set is a Fermat-Weber point of the projection of the data set. We implement these algorithms in R language and test how they work with random data sets. We also use R language for numerical computation. The experimental results show that these algorithms are stable and efficient, with a high success rate.
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HE, YUN, XU CAO, FEI LIU, JIANWEN LUO, and JING BAI. "INFLUENCE OF LIMITED-PROJECTION ON FLUORESCENCE MOLECULAR TOMOGRAPHY." Journal of Innovative Optical Health Sciences 05, no. 03 (July 2012): 1250020. http://dx.doi.org/10.1142/s1793545812500204.
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Challenges remain in imaging fast biological processes in vivo with fluorescence molecular tomography (FMT) due to the long data acquisition time. Data acquisition with limited projections can greatly reduce the time consumption, but the influence of limited-projection on reconstruction quality is currently unclear. Both numerical simulations and a phantom experiment are conducted to analyze this problem. Through a systematic investigation of all the results reconstructed from different numbers of projections, we evaluate the influence of limited-projection data on FMT. A mouse experiment is also performed to validate our work. A general relationship between the number of projections and reconstruction quality is obtained which indicates that the projection number of three is preferred for fast FMT experiment.
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Tian, Zonglin, Xiaorui Zhai, Gijs van Steenpaal, Lingyun Yu, Evanthia Dimara, Mateus Espadoto, and Alexandru Telea. "Quantitative and Qualitative Comparison of 2D and 3D Projection Techniques for High-Dimensional Data." Information 12, no. 6 (June 3, 2021): 239. http://dx.doi.org/10.3390/info12060239.
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Projections are well-known techniques that help the visual exploration of high-dimensional data by creating depictions thereof in a low-dimensional space. While projections that target the 2D space have been studied in detail both quantitatively and qualitatively, 3D projections are far less well understood, with authors arguing both for and against the added-value of a third visual dimension. We fill this gap by first presenting a quantitative study that compares 2D and 3D projections along a rich selection of datasets, projection techniques, and quality metrics. To refine these insights, we conduct a qualitative study that compares the preference of users in exploring high-dimensional data using 2D vs. 3D projections, both without and with visual explanations. Our quantitative and qualitative findings indicate that, in general, 3D projections bring only limited added-value atop of the one provided by their 2D counterparts. However, certain 3D projection techniques can show more structure than their 2D counterparts, and can stimulate users to further exploration. All our datasets, source code, and measurements are made public for ease of replication and extension.
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Liu, Weiping, Jennifer Fung, Craig Abbey, John W. Sedat, and David A. Agard. "Automatic/interactive bead alignment in electron tomographic image processing." Proceedings, annual meeting, Electron Microscopy Society of America 52 (1994): 932–33. http://dx.doi.org/10.1017/s0424820100172395.
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In the electron tomographic (EM) reconstruction process the mutual alignment between projections of different view angles is a crucial step. The routinely used alignment method is based on fiducial markers': a single-axis tilt projection series is collected with gold particles distributed on the specimen, the positions of high density gold beads on the projections are found, and the relationship between the specimen and the digital projection coordinate systems is determined from least-square fitting these found bead positions. There are four alignment parameters for each projection: two in shifts, one in in-plane rotation, and one in magnification. In the threedimensional studies of subcellular biological structures, we routinely collect data sets of more than 100 projections in the tilt range of ±75 ° with our automated EM set-up. Normally around 10 bead positions are used on each projection to achieve the alignment. Bead alignment used to be a laborious task since approximately 1000 bead positions need to be hand-picked for each data set.
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Graham, Jim. "An Automated Approach for Clipping Geographic Data before Projection that Maintains Data Integrity and Minimizes Distortion for Virtually Any Projection Method." Cartographica: The International Journal for Geographic Information and Geovisualization 57, no. 4 (December 1, 2022): 257–69. http://dx.doi.org/10.3138/cart-2021-0015.
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Selecting a map projection is key to minimizing distortion and thus clear communication of spatial data and accurate spatial analysis. Methods exist for selecting projections based on the intended area of use but not for finding polygons that can be used to clip geographic data to ensure the data are projected correctly and within desired distortion limits. The projection methods available in the Proj library were examined to determine the nature of the errors and distortions they created based on global data and a wide variety of available settings. Approaches were then identified for each projection including simple bounding boxes and more complex clipping polygons. To make sure that errors were not introduced into the projected data, data integrity polygons (DIPs) were created by placing a grid of cells over the Earth and then finding a cell near the origin that was within the specified criteria. Adjacent cells were added to the DIPs that met the criteria until no additional cells could be added. The criteria included projected cell sides could not intersect with themselves or other cells, the order of the cell corners could not be reversed, and distortion within the cell had to be within specified limits. I found that up to two DIPs with a limit on length distortion of a factor of 4 provided a general solution for all but three projection methods. Limitations included the time to find DIPs at high resolution. Clipping polygons and visualizations of the results were made available on a website.
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Randall, Bryan L., Alan R. Ek, Jerold T. Hahn, and Roland G. Buchman. "STEMS Model Projection Capability with Incomplete Tree List Input Data." Northern Journal of Applied Forestry 5, no. 3 (September 1, 1988): 190–94. http://dx.doi.org/10.1093/njaf/5.3.190.
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Abstract Projections were made using the STEMS individual tree based stand growth model for plots in red pine, maple-birch, and aspen cover types for periods up to 50 years. Effects of incomplete tree list input data on plots in the form of small tree censorship (omission of small trees) and tree list aggregation (by size class) were examined by comparing projections made for complete plot tree lists (controls) with projections made after these tree lists were censored and aggregated (treatments). Basal area and number of trees estimates proved highly sensitive to censorship, while volume estimates were much less sensitive. Augmentation of censored distributions by an “average” small tree distribution for the cover type resulted in significant improvement of these estimates. Projection model capability using input data aggregated by size class depended on the degree of aggregation. For some types of aggregation, for example by 2-in. dbh classes, the STEMS model retains much of its predictive utility. North. J. Appl. For. 5:190-194, Sept. 1988.
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Kapp, Oscar H., and Chin-Tu Chen. "RECONSTRUCTION FROM LIMITED PROJECTION DATA." INVESTIGATIVE RADIOLOGY 28, no. 12 (December 1993): 1212. http://dx.doi.org/10.1097/00004424-199312000-00148.
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Posse, Christian. "Projection pursuit exploratory data analysis." Computational Statistics & Data Analysis 20, no. 6 (December 1995): 669–87. http://dx.doi.org/10.1016/0167-9473(95)00002-8.
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Aspri, Andrea, Yury Korolev, and Otmar Scherzer. "Data driven regularization by projection." Inverse Problems 36, no. 12 (December 1, 2020): 125009. http://dx.doi.org/10.1088/1361-6420/abb61b.
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Poerio, Dominic V., and Steven D. Brown. "Dual-Domain Calibration Transfer Using Orthogonal Projection." Applied Spectroscopy 72, no. 3 (August 8, 2017): 378–91. http://dx.doi.org/10.1177/0003702817724164.
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We report the use of dual-domain regression models, which were built utilizing a wavelet prism decomposition and paired with transfer by orthogonal projection, for the calibration transfer of near-infrared (NIR) spectra. The new method is based on obtaining specific frequency components for a spectrum via wavelet analysis, projecting the frequency components of the primary instrument onto the subspace orthogonal to the mean instrumental difference between spectra from the primary and the secondary instrument, and weighting each frequency component model according to the cross-validation error of the frequency components of the projected primary instrument’s spectra to generate a stacked ensemble model robust to contributions to the spectra from instrumental variations. The method, which does not require property values from the secondary data set, is tested on three NIR data sets, and is compared with orthogonal projection in the wavelength domain, orthogonal signal correction, and with model updating approaches. For the data sets we examined, we show that the prediction performance of the new method is competitive with orthogonal projections in the wavelength domain, as well as orthogonal signal correction and model updating approaches, both of which require property values for spectra from the secondary instrument. Examination of the spectral data reconstructed from the projected frequency components indicates that aspects of the data that may be attributable to instrumental or physical phenomena (i.e., instrumental baseline shifts or discretized intensity changes which may be attributed to scatter) are suppressed, but those associated with the chemical phenomena are retained. The benefits of orthogonal projection on each individual frequency component are further corroborated by the fact that the models based on frequency component projection generalize better to unseen instruments compared with the other methods.
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Ball, Vaughn, Luis Tenorio, Christian Schiøtt, Michelle Thomas, and J. P. Blangy. "Three-term amplitude-variation-with-offset projections." GEOPHYSICS 83, no. 5 (September 1, 2018): N51—N65. http://dx.doi.org/10.1190/geo2017-0763.1.
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A three-term (3T) amplitude-variation-with-offset projection is a weighted sum of three elastic reflectivities. Parameterization of the weighting coefficients requires two angle parameters, which we denote by the pair [Formula: see text]. Visualization of this pair is accomplished using a globe-like cartographic representation, in which longitude is [Formula: see text], and latitude is [Formula: see text]. Although the formal extension of existing two-term (2T) projection methods to 3T methods is trivial, practical implementation requires a more comprehensive inversion framework than is required in 2T projections. We distinguish between projections of true elastic reflectivities computed from well logs and reflectivities estimated from seismic data. When elastic reflectivities are computed from well logs, their projection relationships are straightforward, and they are given in a form that depends only on elastic properties. In contrast, projection relationships between reflectivities estimated from seismic may also depend on the maximum angle of incidence and the specific reflectivity inversion method used. Such complications related to projections of seismic-estimated elastic reflectivities are systematized in a 3T projection framework by choosing an unbiased reflectivity triplet as the projection basis. Other biased inversion estimates are then given exactly as 3T projections of the unbiased basis. The 3T projections of elastic reflectivities are connected to Bayesian inversion of other subsurface properties through the statistical notion of Bayesian sufficiency. The triplet of basis reflectivities is computed so that it is Bayes sufficient for all rock properties in the hierarchical seismic rock-physics model; that is, the projection basis contains all information about rock properties that is contained in the original seismic.
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Timonidis, Nestor, Rembrandt Bakker, and Paul Tiesinga. "Prediction of a Cell-Class-Specific Mouse Mesoconnectome Using Gene Expression Data." Neuroinformatics 18, no. 4 (May 24, 2020): 611–26. http://dx.doi.org/10.1007/s12021-020-09471-x.
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Abstract Reconstructing brain connectivity at sufficient resolution for computational models designed to study the biophysical mechanisms underlying cognitive processes is extremely challenging. For such a purpose, a mesoconnectome that includes laminar and cell-class specificity would be a major step forward. We analyzed the ability of gene expression patterns to predict cell-class and layer-specific projection patterns and assessed the functional annotations of the most predictive groups of genes. To achieve our goal we used publicly available volumetric gene expression and connectivity data and we trained computational models to learn and predict cell-class and layer-specific axonal projections using gene expression data. Predictions were done in two ways, namely predicting projection strengths using the expression of individual genes and using the co-expression of genes organized in spatial modules, as well as predicting binary forms of projection. For predicting the strength of projections, we found that ridge (L2-regularized) regression had the highest cross-validated accuracy with a median r2 score of 0.54 which corresponded for binarized predictions to a median area under the ROC value of 0.89. Next, we identified 200 spatial gene modules using a dictionary learning and sparse coding approach. We found that these modules yielded predictions of comparable accuracy, with a median r2 score of 0.51. Finally, a gene ontology enrichment analysis of the most predictive gene groups resulted in significant annotations related to postsynaptic function. Taken together, we have demonstrated a prediction workflow that can be used to perform multimodal data integration to improve the accuracy of the predicted mesoconnectome and support other neuroscience use cases.
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Ye, Yangbo, Hengyong Yu, and Ge Wang. "Exact Interior Reconstruction from Truncated Limited-Angle Projection Data." International Journal of Biomedical Imaging 2008 (2008): 1–6. http://dx.doi.org/10.1155/2008/427989.
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Using filtered backprojection (FBP) and an analytic continuation approach, we prove that exact interior reconstruction is possible and unique from truncated limited-angle projection data, if we assume a prior knowledge on a subregion or subvolume within an object to be reconstructed. Our results show that (i) the interior region-of-interest (ROI) problem and interior volume-of-interest (VOI) problem can be exactly reconstructed from a limited-angle scan of the ROI/VOI and a 180 degree PI-scan of the subregion or subvolume and (ii) the whole object function can be exactly reconstructed from nontruncated projections from a limited-angle scan. These results improve the classical theory of Hamaker et al. (1980).
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Indrati, Rini, Siti Daryati, Dewi Kartikasari, Sri Mulyati, and Marichatul Jannah. "RADIATION DOSE AND ANATOMICAL INFORMATION IN SACRUM BONE EXAMINATION WITH AP AND AXIAL AP PROJECTIONS." Jurnal Riset Kesehatan 10, no. 1 (May 28, 2021): 77–83. http://dx.doi.org/10.31983/jrk.v10i1.6777.
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The projections for the sacrum are axial anteroposterior with the beam 15 degrees toward the cephalad, and axial posteroanterior in the direction of the beam 15 degrees caudally. Some practitioners take steps to examine the sacrum with AP projections in a perpendicular beam direction. Around the sacrum are reproductive organs that are sensitive to radiation, so it is necessary to select the right projection to reduce the radiation dose and show clear anatomical information. This study aims to determine the projection of an examination that produces clear anatomical information at a minimal dose. This is an experimental study with one shot post-test only. Samples in the form of radiographs were obtained from perpendicular AP and axial AP projections assessed by radiologists regarding the clarity of anatomical information. The radiation dose was measured using TLD on the ovaries and gonads. Data were analyzed by t-test and Wilcoxon test with an error level of 5%. The AP axial projection shows better anatomical information than the perpendicular AP projection. The axial AP projection shows a smaller dose of the ovaries and gonads. There is a difference in anatomical information between AP and axial AP projections with a p-value = 0.017. There was a difference in radiation dose between AP and axial AP projections on the right ovary (p-value = 0.002), left ovary (p-value 0.001) and gonads (p-value = 0.008).
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Bagheri, Seyedeh Fatemeh, Alireza Amirteimoori, Sohrab Kordrostami, and Mansour Soufi. "Performance Analysis in Production Systems with Uncertain Data: A Stochastic Data Envelopment Analysis Approach." Complexity 2022 (October 12, 2022): 1–14. http://dx.doi.org/10.1155/2022/9198737.
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The problem of determining an optimal benchmark to inefficient decision-making units (DMUs) is an important issue in the field of performance analysis. Previous methods for determining the projection points of inefficient DMUs have only focused on one objective and other features have been ignored. This paper attempts to determine the best projection point for each DMU when the inputs and outputs data are in stochastic form and presents an alternative definition for the best projection by considering three main aspects: technical efficient, minimal cost, and maximal revenue as much as possible. Considering the important role of the electricity industry in the economic growth of each country, a practical example has been implemented on 16 regional electricity companies in Iran in 9 consecutive periods. The efficiency score along with the projection points of the three technical models (BCC model of Banker et al. (1984)), cost, and stochastic revenue are compared with the projection point obtained from the model presented in this article, which simultaneously meets these three objectives, showing the improvement of companies’ performance.
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Strebe, Daniel. "Given the problem of projection, are heat maps an oxymoron?" Abstracts of the ICA 1 (July 15, 2019): 1–2. http://dx.doi.org/10.5194/ica-abs-1-352-2019.
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<p><strong>Abstract.</strong> With the proliferation of data analysis and visualization tools, we see more and more heat maps. But should we? Are such displays meaningful? At large scales, heat maps need not be controversial (though common tools can blight even simple cases). But what about small-scale maps? Is anyone thinking about the effects of projection on heat maps? How do map projections change the semantics of heat maps? What projections permit meaningful heat maps? How should heat maps be calculated in the presence of a map projection? We explore these problems and questions in this presentation to offer critique and advice.</p><p>For the purposes of this discussion, a heat map is a representation of the density or magnitude of a spatial phenomenon on two dimensions, treating the density or magnitude as a continuous measure whether or not the underlying phenomenon is continuous. If the data are too sparse in the presentation space, then the fiction of continuity ought to be avoided; a heat map would not be an appropriate visualization. While real world examples of heat maps that violate this principle are easy to find, we take the principle for granted and do not elaborate further here.</p><p>Unfortunately, there are several other ways to construct ineffective heat maps. One of the primary offenses is to ignore the effect of map projection on the presentation of density. It should be clear that a projection whose area measure varies widely across the presentation space necessarily distorts density. If the heat map is a presentation of density &ndash; which most are &ndash; then poor choice of projection would contradict the purpose of a heat map. The result would be a blatant fiction. Surprisingly, the Mercator projection often can be found in small scale heat maps, for the reason that the projection is common, is the default in many sets of tooling, and is sometimes the only projection available with the set of map construction tools. And yet, as far as density variation goes, a worse case than Mercator cannot be found among common projections.</p><p>Even if density remains constant across the map, a poor heat map could be generated if the analysis for the heat map mixes phenomenon space, which is geographic, with projected space, which is not. Common tools commit this fallacy. The result is that a phenomenon whose density diminishes radially (for example) from a hot point might show as concentric circles of decreasing intensity on the projected map, whereas we would expect elongations of the heat field in accordance with the projection’s distortion metric.</p><p>We conclude that, while it is possible to construct responsible heat maps of geographic data, there are several pitfalls. Among these pitfalls, we find that common tools conspire to assist in the presentation of fiction instead of fact.</p>
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Xia, Yan, Martin Berger, Sebastian Bauer, Shiyang Hu, Andre Aichert, and Andreas Maier. "An Improved Extrapolation Scheme for Truncated CT Data Using 2D Fourier-Based Helgason-Ludwig Consistency Conditions." International Journal of Biomedical Imaging 2017 (2017): 1–14. http://dx.doi.org/10.1155/2017/1867025.
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We improve data extrapolation for truncated computed tomography (CT) projections by using Helgason-Ludwig (HL) consistency conditions that mathematically describe the overlap of information between projections. First, we theoretically derive a 2D Fourier representation of the HL consistency conditions from their original formulation (projection moment theorem), for both parallel-beam and fan-beam imaging geometry. The derivation result indicates that there is a zero energy region forming a double-wedge shape in 2D Fourier domain. This observation is also referred to as the Fourier property of a sinogram in the previous literature. The major benefit of this representation is that the consistency conditions can be efficiently evaluated via 2D fast Fourier transform (FFT). Then, we suggest a method that extrapolates the truncated projections with data from a uniform ellipse of which the parameters are determined by optimizing these consistency conditions. The forward projection of the optimized ellipse can be used to complete the truncation data. The proposed algorithm is evaluated using simulated data and reprojections of clinical data. Results show that the root mean square error (RMSE) is reduced substantially, compared to a state-of-the-art extrapolation method.
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Casas, Gianmarco Goycochea, Leonardo Pereira Fardin, Simone Silva, Ricardo Rodrigues de Oliveira Neto, Daniel Henrique Breda Binoti, Rodrigo Vieira Leite, Carlos Alberto Ramos Domiciano, et al. "Improving Yield Projections from Early Ages in Eucalypt Plantations with the Clutter Model and Artificial Neural Networks." Pertanika Journal of Science and Technology 30, no. 2 (March 11, 2022): 1257–72. http://dx.doi.org/10.47836/pjst.30.2.22.
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A common issue in forest management is related to yield projection for stands at young ages. This study aimed to evaluate the Clutter model and artificial neural networks for projecting eucalypt stands production from early ages, using different data arrangements. In order to do this, the changes in the number of measurement intervals used as input in the Clutter model and artificial neural networks (ANNs) are tested. The Clutter model was fitted considering two sets of data: usual, with inventory measurements (I) paired at intervals each year (I1–I2, I2–I3, …, In–In+1); and modified, with measurements paired at all possible age intervals (I1–I2, I1–I3, …, I2–I3, I2–I4, …, In–In+1). The ANN was trained with the modified dataset plus soil type and geographic coordinates as input variables. The yield projections were made up to the final ages of 6 and 7 years from all possible initial ages (2, 3, 4, 5, or 6 years). The methods are evaluated using the relative error (RE%), bias, correlation coefficient (ryŷ), and relative root mean square error (RMSE%). The ANN was accurate in all cases, with RMSE% from 8.07 to 14.29%, while the Clutter model with the modified dataset had values from 7.95 to 23.61%. Furthermore, with ANN, the errors were evenly distributed over the initial projection ages. This study found that ANN had the best performance for stand volume projection surpassing the Clutter model regardless of the initial or final age of projection.
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Chen, Shuo, Chen Gong, Jian Yang, Ying Tai, Le Hui, and Jun Li. "Data-Adaptive Metric Learning with Scale Alignment." Proceedings of the AAAI Conference on Artificial Intelligence 33 (July 17, 2019): 3347–54. http://dx.doi.org/10.1609/aaai.v33i01.33013347.
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The central problem for most existing metric learning methods is to find a suitable projection matrix on the differences of all pairs of data points. However, a single unified projection matrix can hardly characterize all data similarities accurately as the practical data are usually very complicated, and simply adopting one global projection matrix might ignore important local patterns hidden in the dataset. To address this issue, this paper proposes a novel method dubbed “Data-Adaptive Metric Learning” (DAML), which constructs a data-adaptive projection matrix for each data pair by selectively combining a set of learned candidate matrices. As a result, every data pair can obtain a specific projection matrix, enabling the proposed DAML to flexibly fit the training data and produce discriminative projection results. The model of DAML is formulated as an optimization problem which jointly learns candidate projection matrices and their sparse combination for every data pair. Nevertheless, the over-fitting problem may occur due to the large amount of parameters to be learned. To tackle this issue, we adopt the Total Variation (TV) regularizer to align the scales of data embedding produced by all candidate projection matrices, and thus the generated metrics of these learned candidates are generally comparable. Furthermore, we extend the basic linear DAML model to the kernerlized version (denoted “KDAML”) to handle the non-linear cases, and the Iterative Shrinkage-Thresholding Algorithm (ISTA) is employed to solve the optimization model. Intensive experimental results on various applications including retrieval, classification, and verification clearly demonstrate the superiority of our algorithm to other state-of-the-art metric learning methodologies.
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Ivan, Michael E., Michael M. Safaee, Nikolay L. Martirosyan, Ana Rodríguez-Hernández, Barbara Sullinger, Priyanka Kuruppu, Julian Habdank-Kolaczkowski, and Michael T. Lawton. "Anatomical triangles defining routes to anterior communicating artery aneurysms: the junctional and precommunicating triangles and the role of dome projection." Journal of Neurosurgery 132, no. 5 (May 2020): 1517–28. http://dx.doi.org/10.3171/2018.12.jns183264.
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OBJECTIVEAnterior communicating artery (ACoA) aneurysms are common intracranial aneurysms. Despite advances in endovascular therapy, microsurgical clipping remains an important treatment for aneurysms with broad necks, large size, intraluminal thrombus, complex branches, or previous coiling. Anatomical triangles identify safe corridors for aneurysm access. The authors introduce the A1-A2 junctional triangle and the A1-A1 precommunicating triangle and examine relationships between dome projection, triangular corridors of access, and surgical outcomes.METHODSPreoperative catheter and CT angiograms were evaluated to characterize aneurysm dome projection. Aneurysm projection was categorized into quadrants and octants. Preoperative, intraoperative, and postoperative factors were correlated to aneurysm dome projection and patient outcomes using univariate and multivariate analyses.RESULTSA total of 513 patients with microsurgically treated ACoA aneurysms were identified over a 13-year period, and 400 had adequate imaging and follow-up data for inclusion. Surgical clipping was performed on 271 ruptured and 129 unruptured aneurysms. Good outcomes were observed in 91% of patients with unruptured aneurysms and 86% of those with ruptured aneurysms, with a mortality rate < 1% among patients with unruptured aneurysms. Increasing age (p < 0.01), larger aneurysm size (p = 0.03), and worse preoperative modified Rankin Scale score (p < 0.01) affected outcomes adversely. Aneurysms projecting superiorly and posteriorly required dissection in the junctional triangle, and multivariate analysis demonstrated worse clinical outcomes in these patients (p < 0.01).CONCLUSIONSAnteriorly and inferiorly projecting aneurysms involve only the precommunicating triangle, are simpler to treat microsurgically, and have more favorable outcomes. Superior and posterior dome projections make ACoA aneurysms more difficult to visualize and require opening the junctional triangle. Added visualization through the junctional triangle is recommended for these aneurysms in order to facilitate dissection of efferent branch arteries, careful clip application, and perforator preservation. Dome projection can be determined preoperatively from images and can help anticipate dissection routes through the junctional triangle.
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Nijzink, Remko C., and Stanislaus J. Schymanski. "Technical note: Do different projections matter for the Budyko framework?" Hydrology and Earth System Sciences 26, no. 17 (September 14, 2022): 4575–85. http://dx.doi.org/10.5194/hess-26-4575-2022.
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Abstract. The widely used Budyko framework defines the water and energy limits of catchments. Generally, catchments plot close to these physical limits, and Budyko (1974) developed a curve that predicted the positions of catchments in this framework. Often, the independent variable is defined as an aridity index, which is used to predict the ratio of actual evaporation over precipitation (Ea/P). However, the framework can be formulated with the potential evaporation as the common denominator for the dependent and independent variables, i.e., P/Ep and Ea/Ep. It is possible to mathematically convert between these formulations, but if the parameterized Budyko curves are fit to data, the different formulations could lead to differences in the resulting parameter values. Here, we tested this for 357 catchments across the contiguous United States. In this way, we found that differences in n values due to the projection used could be ± 0.2. If robust fitting algorithms were used, the differences in n values reduced but were nonetheless still present. The distances to the curve, often used as a metric in Budyko-type analyses, systematically depended on the projection, with larger differences for the non-contracted sides of the framework (i.e., Ep/P>1 or P/Ep>1). When using the two projections for predicting Ea, we found that uncertainties due to the projections used could exceed 1.5 %. An important reason for the differences in n values, curves and resulting estimates of Ea could be found in data points that clearly appear as outliers in one projection but less so in the other projection. We argue here that the non-contracted side of the framework in the two projections should always be assessed, especially for data points that appear as outliers. At least, one should consider the additional uncertainty of the projection and assess the robustness of the results in both projections.
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Diao, Chen, Ai-Hua Zhang, and Bin Wang. "Spectral Clustering with Local Projection Distance Measurement." Mathematical Problems in Engineering 2015 (2015): 1–13. http://dx.doi.org/10.1155/2015/829514.
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Constructing a rational affinity matrix is crucial for spectral clustering. In this paper, a novel spectral clustering via local projection distance measure (LPDM) is proposed. In this method, the Local-Projection-Neighborhood (LPN) is defined, which is a region between a pair of data, and other data in the LPN are projected onto the straight line among the data pairs. Utilizing the Euclidean distance between projective points, the local spatial structure of data can be well detected to measure the similarity of objects. Then the affinity matrix can be obtained by using a new similarity measurement, which can squeeze or widen the projective distance with the different spatial structure of data. Experimental results show that the LPDM algorithm can obtain desirable results with high performance on synthetic datasets, real-world datasets, and images.
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Anna, Nur, Syamsul Ridjal, and Herman Sjahruddin. "Implementasi Financial Projection Sebagai Strategi Pengelolaan Keuangan." Jurnal Ekonomi dan Bisnis Dharma Andalas 22, no. 2 (August 2, 2020): 302–14. http://dx.doi.org/10.47233/jebd.v22i2.109.
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ABSTRACT
This research was conducted to analyze the implementation of financial projections as a financial management strategy at PT. PLN (Persero). The population of this study is the financial statement of PT. PLN (Persero) 2014-2018. Sampling was carried out using purposive sampling method. The sample used was 5 years of financial statement. The data analysis method used is quantitative descriptive analysis technique, which is an analysis that describes by calculating the company’s financial projections report using certain formulas. Financial projection indicators used in this study use growth rate method to determine sales projections and common size analysis to determine the project balance sheet and income statement. Based on the results of the study showed an increase in sales projection of 16%, as well as balance sheet and income projections which both experienced an increase of 18% for the projected balance sheet and 5% for the profit and loss projection.
ABSTRAK
Penelitian ini dilakukan untuk menganalisis implementasi financial projection sebagai strategi pengelolaan keuangan pada PT. PLN (Persero). Populasi dari penelitian ini adalah laporan keuangan PT. PLN (Persero) Tahun 2014 – 2018. Penarikan sampel yang dilakukan menggunakan metode purposive sampling. Sampel yang digunakan sebanyak 5 tahun laporan keuangan. Metode analisis data yang digunakan adalah teknik analisis deskriftif kuantitatif, yaitu suatu analisis yang mendeskripsikan dengan cara menghitung laporan proyeksi keuangan perusahaan menggunakan rumus-rumus tertentu. Indikator financial projection yang digunakan dalam penelitian ini menggunakan metode tingkat pertumbuhan untuk mengetahui proyeksi penjualan dan analisis common size untuk mengetahui proyeksi neraca dan laba rugi. Berdasarkan hasil penelitian menunjukkan peningkatan pada proyeksi penjualan sebesar 16%, begitu pula dengan proyeksi neraca dan laba rugi yang sama-sama mengalami peningkatan sebesar 18% untuk proyeksi neraca dan 5% untuk proyeksi laba rugi.
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IMAI, Hideyuki, and Yoshiharu SATO. "Exploratory Projection Pursuit for Fuzzy Data." Journal of Japan Society for Fuzzy Theory and Systems 7, no. 6 (1995): 1239–46. http://dx.doi.org/10.3156/jfuzzy.7.6_1239.
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Yi, Zeng, James W. Vaupel, and Wang Zhenglian. "Household Projection Using Conventional Demographic Data." Population and Development Review 24 (1998): 59. http://dx.doi.org/10.2307/2808051.
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Choi, Jaesung. "Projection analysis for split-plot data." Korean Journal of Applied Statistics 30, no. 3 (June 30, 2017): 335–44. http://dx.doi.org/10.5351/kjas.2017.30.3.335.
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Aguilar, Jesús S., José C. Riquelme, and Miguel Toro. "Data set Editing by Ordered Projection." Intelligent Data Analysis 5, no. 5 (November 19, 2001): 405–17. http://dx.doi.org/10.3233/ida-2001-5504.
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Darabi, Nadiyeh, and S. Mohammad E. Hosseini-Nasab. "Projection-based classification for functional data." Statistics 54, no. 3 (April 7, 2020): 544–58. http://dx.doi.org/10.1080/02331888.2020.1750015.
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Dyckerhoff, Rainer. "Data depths satisfying the projection property." Allgemeines Statistisches Archiv 88, no. 2 (May 2004): 163–90. http://dx.doi.org/10.1007/s101820400167.
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Varmuza, Kurt, Peter Filzmoser, and Bettina Liebmann. "Random projection experiments with chemometric data." Journal of Chemometrics 24, no. 3-4 (April 8, 2010): 209–17. http://dx.doi.org/10.1002/cem.1295.
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Yi, Huangjian, Xu Zhang, Jinye Peng, Fengjun Zhao, Xiaodong Wang, Yuqing Hou, Duofang Chen, and Xiaowei He. "Reconstruction for Limited-Projection Fluorescence Molecular Tomography Based on a Double-Mesh Strategy." BioMed Research International 2016 (2016): 1–11. http://dx.doi.org/10.1155/2016/5682851.
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Limited-projection fluorescence molecular tomography (FMT) has short data acquisition time that allows fast resolving of the three-dimensional visualization of fluorophore within small animal in vivo. However, limited-projection FMT reconstruction suffers from severe ill-posedness because only limited projections are used for reconstruction. To alleviate the ill-posedness, a feasible region extraction strategy based on a double mesh is presented for limited-projection FMT. First, an initial result is rapidly recovered using a coarse discretization mesh. Then, the reconstructed fluorophore area in the initial result is selected as a feasible region to guide the reconstruction using a fine discretization mesh. Simulation experiments on a digital mouse and small animal experiment in vivo are performed to validate the proposed strategy. It demonstrates that the presented strategy provides a good distribution of fluorophore with limited projections of fluorescence measurements. Hence, it is suitable for reconstruction of limited-projection FMT.
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Rees, P. "Estimating and projecting the populations of urban communities." Environment and Planning A: Economy and Space 26, no. 11 (November 1994): 1671–97. http://dx.doi.org/10.1177/0308518x9402601101.
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The author describes a model for estimating and projecting the populations of communities living in small areas within cities. The model provides a means of updating the demographic inputs needed for projection between censuses and means of developing scenarios of demographic change and housing development. The method for estimating small-area populations between censuses is evaluated with recently published 1991 Census data. Single-year age-group detail is provided and the associated databases are embedded in a flexible user interface. Illustrative projections are discussed and interpreted for the northern English city of Bradford.