Relevant bibliographies by topics / Computational analysis

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Computational analysis'

Author: Grafiati
Published: 4 June 2021
Last updated: 25 July 2025

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Journal articles on the topic "Computational analysis"

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Liu, G. R. "Computational methods for certified solutions, adaptive analysis, real-time computation, and inverse analysis of mechanics problem." Proceedings of The Computational Mechanics Conference 2011.24 (2011): _—1_—_—5_. http://dx.doi.org/10.1299/jsmecmd.2011.24._-1_.

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ILIE, Marcel, Augustin Semenescu, Gabriela Liliana STROE, and Sorin BERBENTE. "NUMERICAL COMPUTATIONS OF THE CAVITY FLOWS USING THE POTENTIAL FLOW THEORY." ANNALS OF THE ACADEMY OF ROMANIAN SCIENTISTS Series on ENGINEERING SCIENCES 13, no. 2 (2021): 78–86. http://dx.doi.org/10.56082/annalsarscieng.2021.2.78.

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Computational fluid dynamics of turbulent flows requires large computational resources or are not suitable for the computations of transient flows. Therefore methods such as Reynolds-averaged Navier-Stokes equations are not suitable for the computation of transient flows. The direct numerical simulation provides the most accurate solution, but it is not suitable for high-Reynolds number flows. Large-eddy simulation (LES) approach is computationally less demanding than the DNS but still computationally expensive. Therefore, alternative computational methods must be sought. This research concern
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Juneja, Shall, Deepayan Mukherjee, and Sachi Garg. "Computational Analysis of RNA Nucleotide Sequences." International Journal of Trend in Scientific Research and Development Volume-3, Issue-2 (2019): 369–72. http://dx.doi.org/10.31142/ijtsrd21342.

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Fajdiga, Gorazd. "Computational fatigue analysis of contacting mechanical elements." Tehnicki vjesnik - Technical Gazette 22, no. 1 (2015): 169–75. http://dx.doi.org/10.17559/tv-20140429122305.

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Protsko, I. O., and D. V. Ostrovka. "ANALYSIS OF THE ERROR OF COMPUTATION FAST TRANSFORMS OF FOURIER CLASS BASED ON CYCLIC CONVOLUTIONS." Ukrainian Journal of Information Technology 2, no. 1 (2020): 52–56. http://dx.doi.org/10.23939/ujit2020.02.052.

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The features of the computational model of discrete transforms of Fourier class based on cyclic convolutions to determine the algorithmic calculation error are analyzed. Based on the approach of efficient computation of discrete transforms of Fourier class of arbitrary size N, using of a hashing array to transform a discrete basis matrix into a set of block-cyclic submatrices, the components of computational costs are considered. These components of computational costs depend on the type of transform, the size and the block-cycle structure of the transformation core. Examples of computational
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LESSNER, Daniel. "ANALYSIS OF TERM MEANING "COMPUTATIONAL THINKING"." Journal of Technology and Information 6, no. 1 (2014): 71–88. http://dx.doi.org/10.5507/jtie.2014.006.

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Planitz, Max, and R. E. Moore. "Computational Functional Analysis." Mathematical Gazette 70, no. 451 (1986): 69. http://dx.doi.org/10.2307/3615858.

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Fink, James P., and R. E. Moore. "Computational Functional Analysis." Mathematics of Computation 47, no. 175 (1986): 372. http://dx.doi.org/10.2307/2008105.

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Giraud, Mathieu, Richard Groult, Emmanuel Leguy, and Florence Levé. "Computational Fugue Analysis." Computer Music Journal 39, no. 2 (2015): 77–96. http://dx.doi.org/10.1162/comj_a_00300.

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One of the pinnacles of form in classical Western music, the fugue is often used in the teaching of music analysis and composition. Fugues alternate between instances of a subject and other patterns and modulatory sections, called episodes. Musicological analyses are generally built on these patterns and sections. We have developed several algorithms to perform an automated analysis of a fugue, starting from a score in which all the voices are separated. By focusing on the diatonic similarities between pitch intervals, we detect subjects and countersubjects, as well as partial harmonic sequenc
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Takizawa, Kenji, Yuri Bazilevs, Tayfun E. Tezduyar, Ming-Chen Hsu, and Takuya Terahara. "Computational Cardiovascular Medicine With Isogeometric Analysis." Journal of Advanced Engineering and Computation 6, no. 3 (2022): 167. http://dx.doi.org/10.55579/jaec.202263.381.

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Isogeometric analysis (IGA) brought superior accuracy to computations in both fluid and solid mechanics. The increased accuracy has been in representing both the problem geometry and the variables computed. Beyond using IGA basis functions in space, with IGA basis functions in time in a space–time (ST) context, we can have increased accuracy also in representing the motion of solid surfaces. Around the core methods such as the residual-based variational multiscale (VMS), ST-VMS and arbitrary Lagrangian–Eulerian VMS methods, with complex-geometry IGA mesh generation methods and immersogeometric
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Dissertations / Theses on the topic "Computational analysis"

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Pocock, Matthew Richard. "Computational analysis of genomes." Thesis, University of Cambridge, 2004. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.615724.

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Cattinelli, I. "INVESTIGATIONS ON COGNITIVE COMPUTATION AND COMPUTATIONAL COGNITION." Doctoral thesis, Università degli Studi di Milano, 2011. http://hdl.handle.net/2434/155482.

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This Thesis describes our work at the boundary between Computer Science and Cognitive (Neuro)Science. In particular, (1) we have worked on methodological improvements to clustering-based meta-analysis of neuroimaging data, which is a technique that allows to collectively assess, in a quantitative way, activation peaks from several functional imaging studies, in order to extract the most robust results in the cognitive domain of interest. Hierarchical clustering is often used in this context, yet it is prone to the problem of non-uniqueness of the solution: a different permutation of the same i
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Shenoy, A. "Computational analysis of facial expressions." Thesis, University of Hertfordshire, 2010. http://hdl.handle.net/2299/4359.

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This PhD work constitutes a series of inter-disciplinary studies that use biologically plausible computational techniques and experiments with human subjects in analyzing facial expressions. The performance of the computational models and human subjects in terms of accuracy and response time are analyzed. The computational models process images in three stages. This includes: Preprocessing, dimensionality reduction and Classification. The pre-processing of face expression images includes feature extraction and dimensionality reduction. Gabor filters are used for feature extraction as they are
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Etherington, Graham John. "Computational analysis of foodborne viruses." Thesis, University of East Anglia, 2004. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.423473.

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Wen, Wen. "Computational texture analysis and segmentation." Thesis, University of Strathclyde, 1991. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.358812.

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Buchala, Samarasena. "Computational analysis of face images." Thesis, University of Hertfordshire, 2006. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.431938.

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Hussain, R. "Computational geometry using fourier analysis." Thesis, De Montfort University, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.391483.

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Ikoma, Hayato. "Computational microscopy for sample analysis." Thesis, Massachusetts Institute of Technology, 2014. http://hdl.handle.net/1721.1/91427.

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Thesis: S.M., Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2014.<br>46<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (pages 41-44).<br>Computational microscopy is an emerging technology which extends the capabilities of optical microscopy with the help of computation. One of the notable example is super resolution fluorescence microscopy which achieves sub-wavelength resolution. This thesis explores the novel application of computational imaging methods to fluorescence microscopy and oblique il
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Xu, Yangjian. "Computational analysis of fretting fatigue." Düsseldorf VDI-Verl, 2009. http://d-nb.info/996624554/04.

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Li, Xiang. "Computational analysis of ultraviolet reactors /." Online version of thesis, 2009. http://hdl.handle.net/1850/11175.

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Books on the topic "Computational analysis"

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Anastassiou, George A., and Oktay Duman, eds. Computational Analysis. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-28443-9.

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Laub, Alan J. Computational matrix analysis. Society for Industrial and Applied Mathematics, 2012.

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Neuman, Yair. Computational Personality Analysis. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-42460-6.

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Im, Chang-Hwan, ed. Computational EEG Analysis. Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-0908-3.

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Meredith, David, ed. Computational Music Analysis. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-25931-4.

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Laube, Patrick. Computational Movement Analysis. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-10268-9.

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Abraham, Ajith, Aboul-Ella Hassanien, and Vaclav Sná¿el, eds. Computational Social Network Analysis. Springer London, 2010. http://dx.doi.org/10.1007/978-1-84882-229-0.

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Anastassiou, George A. Intelligent Mathematics: Computational Analysis. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-17098-0.

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Zhang, David, Wangmeng Zuo, and Peng Wang. Computational Pulse Signal Analysis. Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-4044-3.

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F, Rosenthal David, and Okuno Hiroshi G, eds. Computational auditory scene analysis. Lawrence Erlbaum Associates, 1998.

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Book chapters on the topic "Computational analysis"

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Betounes, David. "Computational Analysis." In Partial Differential Equations for Computational Science. Springer New York, 1998. http://dx.doi.org/10.1007/978-1-4612-2198-2_5.

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Weihrauch, Klaus. "7. Computational Complexity." In Computable Analysis. Springer Berlin Heidelberg, 2000. http://dx.doi.org/10.1007/978-3-642-56999-9_7.

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Hart, George W. "Multidimensional Computational Methods." In Multidimensional Analysis. Springer New York, 1995. http://dx.doi.org/10.1007/978-1-4612-4208-6_7.

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Dascalu, Mihai. "Computational Discourse Analysis." In Analyzing Discourse and Text Complexity for Learning and Collaborating. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-03419-5_4.

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Wang, DeLiang. "Computational Scene Analysis." In Challenges for Computational Intelligence. Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-71984-7_8.

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Hausser, Roland. "Computational language analysis." In Foundations of Computational Linguistics. Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/978-3-662-04337-0_2.

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Gudmundsson, Joachim, Patrick Laube, and Thomas Wolle. "Computational Movement Analysis." In Springer Handbook of Geographic Information. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-540-72680-7_22.

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Hausser, Roland. "Computational language analysis." In Foundations of Computational Linguistics. Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/978-3-662-03920-5_2.

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Aigner, Wolfgang, Silvia Miksch, Heidrun Schumann, and Christian Tominski. "Computational Analysis Support." In Human–Computer Interaction Series. Springer London, 2023. http://dx.doi.org/10.1007/978-1-4471-7527-8_6.

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AbstractThis chapter is concerned with computational methods to support the analysis of time-oriented data. A general overview of temporal data analysis is provided and specific application examples will be used for demonstration.
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Elwert, Frederik. "Computational Text Analysis." In The Routledge Handbook of Research Methods in the Study of Religion, 2nd ed. Routledge, 2021. http://dx.doi.org/10.4324/9781003222491-12.

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Conference papers on the topic "Computational analysis"

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Li, Shaoheng, and Peter Kner. "Self-interference digital holography with computational adaptive optics." In Adaptive Optics: Methods, Analysis and Applications. Optica Publishing Group, 2024. http://dx.doi.org/10.1364/aopt.2024.oth4f.3.

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Self-interference Digital Holography (SIDH) based single molecule localization microscopy has the potential to perform large volume 3D super-resolution imaging without mechanical refocusing of the sample. This work presents a fast, guide-star-free computational Adaptive Optics method for SIDH.
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Yang, Changhuei. "Computational Microscopy for Pathology Analysis." In Frontiers in Optics. Optica Publishing Group, 2024. https://doi.org/10.1364/fio.2024.fm1b.1.

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In this talk, I will discuss some of our recent computational microscopy and deep learning work, that showcase some of these shifts in the context of pathology. I will talk about APIC – an improved computational microscopy method to collect and process image data, which brings significant workflow advantages to pathology. I will also talking about the use of Deep Learning in image analysis, and point out some of the surprising and impactful ways Deep Learning can improve pathology. Full-text article not available; see video presentation
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Yeo, Hyeonsoo, and Mark Potsdam. "Rotor Structural Loads Analysis Using Coupled Computational FluidDynamics/Computational Structural Dynamics." In Vertical Flight Society 70th Annual Forum & Technology Display. The Vertical Flight Society, 2014. http://dx.doi.org/10.4050/f-0070-2014-9548.

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Coupled CFD/CSD (RCAS/Helios and CAMRAD II/Helios) analyses are performed and the calculated rotor structural loads are compared with the flight test data obtained from the NASA/Army UH-60A Airloads Program. Three challenging level flight conditions are investigated: 1) high speed with advancing blade negative lift, 2) low speed with blade-wake interaction, and 3) high thrust with dynamic stall. The predicted flap bending and torsion moments, pitch link and lag damper loads, in general, show reasonably good correlation with the test data. A nonlinear lag damper model is essential for the accur
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Nayar, Shree. "Advances in Computational Imaging." In Adaptive Optics: Analysis, Methods & Systems. OSA, 2015. http://dx.doi.org/10.1364/aoms.2015.jt1a.2.

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Majak, Jüri, and M. Di Sciuva. "Preface: Computational Mechanics." In INTERNATIONAL CONFERENCE OF NUMERICAL ANALYSIS AND APPLIED MATHEMATICS ICNAAM 2019. AIP Publishing, 2020. http://dx.doi.org/10.1063/5.0026521.

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Bechhoefer, Eric. "Low Computational, Nonlinear Component Trend Analysis." In Vertical Flight Society 75th Annual Forum & Technology Display. The Vertical Flight Society, 2019. http://dx.doi.org/10.4050/f-0075-2019-14606.

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This paper is concerned with a nonlinear, computationally efficient method for trending component health. While conceptually simple, the goal of component trending is to reduce spurious noise in the measured component health and to estimate the remaining useful life (RUL). The need for lower computational effort allows this to be done on an embedded system. This would be important for display on a cockpit multi-function display. Additionally, we describe a new method for state smoothing. This is a forward-backward technique with no computational overhead associated with updating the plant nois
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Chamis, C. C., and R. H. Johns. "Computational Engine Structural Analysis." In ASME 1986 International Gas Turbine Conference and Exhibit. American Society of Mechanical Engineers, 1986. http://dx.doi.org/10.1115/86-gt-70.

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A significant research activity at the NASA Lewis Research Center is the computational simulation of complex multidisciplinary engine structural problems. This simulation is performed using computational engine structural analysis (CESA) which consists of integrated multidisciplinary computer codes in conjunction with computer post-processing for “problem-specific” application. A variety of the computational simulations of specific cases are described in some detail in this paper. These case studies include (1) aeroelastic behavior of bladed rotors, (2) high velocity impact of fan blades, (3)
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Gupta, M. Satyanarayana, Nirmith Kumar Mishra, Mosin, Aishwarya Jaiswal, and Ankadala Jyoshnavi. "Computational analysis over wings." In PROCEEDINGS OF THE 1ST INTERNATIONAL CONFERENCE ON FRONTIER OF DIGITAL TECHNOLOGY TOWARDS A SUSTAINABLE SOCIETY. AIP Publishing, 2023. http://dx.doi.org/10.1063/5.0113273.

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Degtyarev, Alexander, Vasily Khramushin, and Julia Shichkina. "Tensor methodology and computational geometry in direct computational experiments in fluid mechanics." In INTERNATIONAL CONFERENCE OF NUMERICAL ANALYSIS AND APPLIED MATHEMATICS (ICNAAM 2016). Author(s), 2017. http://dx.doi.org/10.1063/1.4992291.

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Venkatesh, Suresh, Naren Viswanathan, and David Schurig. "W-Band Sparse Synthetic Aperture for Computational Imaging." In Adaptive Optics: Analysis, Methods & Systems. OSA, 2015. http://dx.doi.org/10.1364/aoms.2015.jt5a.17.

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Reports on the topic "Computational analysis"

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George, D. L. Computational techniques in gamma-ray skyshine analysis. Office of Scientific and Technical Information (OSTI), 1988. http://dx.doi.org/10.2172/6077591.

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Gentile, Ann C., Youssef M. Marzouk, James M. Brandt, and Philippe Pierre Pebay. Meaningful statistical analysis of large computational clusters. Office of Scientific and Technical Information (OSTI), 2005. http://dx.doi.org/10.2172/958384.

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Lax, P., and M. Berger. Applied analysis/computational mathematics. Final report 1993. Office of Scientific and Technical Information (OSTI), 1993. http://dx.doi.org/10.2172/10113926.

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Babuska, Ivo, Y. Li, and K. L. Jerina. Reliability of Computational Analysis of Plasticity Problems. Defense Technical Information Center, 1991. http://dx.doi.org/10.21236/ada239646.

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Davis, George B., and Kathleen M. Carley. Computational Analysis of Merchant Marine GPS Data. Defense Technical Information Center, 2006. http://dx.doi.org/10.21236/ada471469.

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Plotts, Dylan. Computational Notebooks: Designing for Exploratory Data Analysis. Iowa State University, 2020. http://dx.doi.org/10.31274/cc-20240624-409.

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Barhen, J., C. W. Glover, and V. A. Protopopescu. Advanced computational tools for 3-D seismic analysis. Office of Scientific and Technical Information (OSTI), 1996. http://dx.doi.org/10.2172/450786.

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Grandhi, Ramana V. Computational Mechanics Approach for Multidisciplinary Nonlinear Sensitivity Analysis. Defense Technical Information Center, 2003. http://dx.doi.org/10.21236/ada416568.

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Rzhetsky, Andrey, and Dimitris Anastassiou. COMPUTATIONAL ANALYSIS AND SIMULATION OF BACTERIAL MOLECULAR NETWORKS. Office of Scientific and Technical Information (OSTI), 2009. http://dx.doi.org/10.2172/968434.

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Konstantin Mischaikow, Michael Schatz, William Kalies, and Thomas Wanner. Multiscale analysis of nonlinear systems using computational homology. Office of Scientific and Technical Information (OSTI), 2010. http://dx.doi.org/10.2172/979569.

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