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Journal articles on the topic 'Computational analysis'

Author: Grafiati

Published: 4 June 2021

Last updated: 9 June 2025

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1

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 concerns the modelling of inviscid incompressible cavity flow using the potential flow. The numerical methods employed the finite differences approach. The time and space discretization is achieved using second-order schemes. The studies reveal that the finite differences approach is a computationally efficient approach and large computations can be performed on a single computer. The analysis of the flow physics reveals the presence of the recirculation region inside the cavity as well at the corners of the cavity

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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 (February 28, 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 model and block-cyclic structure of matrices of simplified arguments of basis functions for mutually inverse discrete cosine transforms of types II, III are given. The computational model characterizes the accumulation of rounding errors at the stages of adding input data, computing cyclic convolutions, combining the results of convolutions. Discrete cyclic convolutions can be implemented using fast algorithms or a type of system that corresponds to digital filters with finite pulse characteristics. The possibility of parallel computation of the reduced number of cyclic convolutions makes the analysis of errors insensitive to rearrangement of their computations. The multiplication operations performed when computing the cyclic convolution uses a smaller number of basis coefficients equal to N/4 or N/2 depending on the size of transform. The formats of representation of real numbers in computer systems are considered, which also determine the magnitude of the computational error of transforms. The results of direct and fast computation of discrete cosine transform of type II based on cyclic convolutions with size N=58 in the format wit floating point of double precision and computation error between them are presented. The apriori process of studying the transform errors of the corresponding type and size by the method of mathematical modeling and computational experiment is approximate, which allows to predict the statistical averages of the accuracy of computing the discrete Fourier transform of arbitrary size based on cyclic convolutions.

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LESSNER, Daniel. "ANALYSIS OF TERM MEANING "COMPUTATIONAL THINKING"." Journal of Technology and Information 6, no. 1 (April 1, 2014): 71–88. http://dx.doi.org/10.5507/jtie.2014.006.

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7

Planitz, Max, and R. E. Moore. "Computational Functional Analysis." Mathematical Gazette 70, no. 451 (March 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 (July 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 (June 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 sequences inside the episodes. We also implemented tools to detect subject scale degrees, cadences, and pedals, as well as a method for segmenting the fugue into exposition and episodic parts. Our algorithms were tested on a corpus of 36 fugues by J. S. Bach and Dmitri Shostakovich. We provide formalized ground-truth data on this corpus as well as a dynamic visualization of the ground truth and of our computed results. The complete system showed acceptable or good results for about one half of the fugues tested, enabling us to depict their design.

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Bhardwaj, Shalini, and Yashwant Buke. "Computational Fluid Dynamics Analysis of A Turbocharger System." International Journal of Scientific Research 3, no. 5 (June 1, 2012): 161–64. http://dx.doi.org/10.15373/22778179/may2014/49.

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11

Hassanian, Reza, and Morris Riedel. "Mechanical Elements Analysis of Stewart Platform: Computational Approach." International Journal of Science and Research (IJSR) 11, no. 4 (April 5, 2022): 1166–71. http://dx.doi.org/10.21275/sr22420092335.

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Gao, Feng, Gang Li, Rui Hu, and Hiroshi Okada. "Computational Fluid Dynamic Analysis of Coronary Artery Stenting." International Journal of Bioscience, Biochemistry and Bioinformatics 4, no. 3 (2014): 155–59. http://dx.doi.org/10.7763/ijbbb.2014.v4.330.

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Joseph, Prince. "Comparative Analysis of Computational Based Motif Refinement Methods." International Journal of Science and Research (IJSR) 12, no. 10 (October 5, 2023): 163–66. http://dx.doi.org/10.21275/sr231002163600.

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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 (September 30, 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 analysis, and with special methods targeting specific classes of computations, the IGA has been very effective in computational cardiovascular medicine. We provide an overview of these IGA-based computational cardiovascular-medicine methods and present examples of the computations performed.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium provided the original work is properly cited.

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Amyot, Romain, Noriyuki Kodera, and Holger Flechsig. "Atom Filtering Algorithm and GPU-Accelerated Calculation of Simulation Atomic Force Microscopy Images." Algorithms 17, no. 1 (January 17, 2024): 38. http://dx.doi.org/10.3390/a17010038.

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Simulation of atomic force microscopy (AFM) computationally emulates experimental scanning of a biomolecular structure to produce topographic images that can be correlated with measured images. Its application to the enormous amount of available high-resolution structures, as well as to molecular dynamics modelling data, facilitates the quantitative interpretation of experimental observations by inferring atomistic information from resolution-limited measured topographies. The computation required to generate a simulated AFM image generally includes the calculation of contacts between the scanning tip and all atoms from the biomolecular structure. However, since only contacts with surface atoms are relevant, a filtering method shall highly improve the efficiency of simulated AFM computations. In this report, we address this issue and present an elegant solution based on graphics processing unit (GPU) computations that significantly accelerates the computation of simulated AFM images. This method not only allows for the visualization of biomolecular structures combined with ultra-fast synchronized calculation and graphical representation of corresponding simulated AFM images (live simulation AFM), but, as we demonstrate, it can also reduce the computational effort during the automatized fitting of atomistic structures into measured AFM topographies by orders of magnitude. Hence, the developed method will play an important role in post-experimental computational analysis involving simulated AFM, including expected applications in machine learning approaches. The implementation is realized in our BioAFMviewer software (ver. 3) package for simulated AFM of biomolecular structures and dynamics.

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Wang, Xin, Zhi Yu, Le Yang, and Ji Li. "Design and Analysis of a Non-Iterative Estimator for Target Location in Multistatic Sonar Systems with Sensor Position Uncertainties." Mathematics 8, no. 1 (January 15, 2020): 129. http://dx.doi.org/10.3390/math8010129.

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Target location is the basic application of a multistatic sonar system. Determining the position/velocity vector of a target from the related sonar observations is a nonlinear estimation problem. The presence of possible sensor position uncertainties turns this problem into a more challenging hybrid parameter estimation problem. Conventional gradient-based iterative estimators suffer from the problems of initialization difficulties and local convergence. Even if there is no problem with initialization and convergence, a large computational cost is required in most cases. In view of these drawbacks, we develop a computationally efficient non-iterative position/velocity estimator. The main numerical computation involved is the weighted least squares optimization, which makes the estimator computationally efficient. Parameter transformation, model linearization and two-stage processing are exploited to prevent the estimator from iterative computation. Through performance analysis and experimental verification, we find that the proposed estimator reaches the hybrid Cramér–Rao bound and has linear computational complexity.

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Cortés, J. C., J. V. Romero, M. D. Roselló, Francisco-J. Santonja, and Rafael-J. Villanueva. "Solving Continuous Models with Dependent Uncertainty: A Computational Approach." Abstract and Applied Analysis 2013 (2013): 1–10. http://dx.doi.org/10.1155/2013/983839.

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This paper presents a computational study on a quasi-Galerkin projection-based method to deal with a class of systems of random ordinary differential equations (r.o.d.e.’s) which is assumed to depend on a finite number of random variables (r.v.’s). This class of systems of r.o.d.e.’s appears in different areas, particularly in epidemiology modelling. In contrast with the other available Galerkin-based techniques, such as the generalized Polynomial Chaos, the proposed method expands the solution directly in terms of the random inputs rather than auxiliary r.v.’s. Theoretically, Galerkin projection-based methods take advantage of orthogonality with the aim of simplifying the involved computations when solving r.o.d.e.’s, which means to compute both the solution and its main statistical functions such as the expectation and the standard deviation. This approach requires the previous determination of an orthonormal basis which, in practice, could become computationally burden and, as a consequence, could ruin the method. Motivated by this fact, we present a technique to deal with r.o.d.e.’s that avoids constructing an orthogonal basis and keeps computationally competitive even assuming statistical dependence among the random input parameters. Through a wide range of examples, including a classical epidemiologic model, we show the ability of the method to solve r.o.d.e.’s.

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C., Mohan Raj. "Analysis of Various Automotive Mufflers: Computational Fluid Dynamics Approach." Revista Gestão Inovação e Tecnologias 11, no. 4 (July 10, 2021): 1339–48. http://dx.doi.org/10.47059/revistageintec.v11i4.2191.

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Kumar, Sachin. "Computational Analysis for Random Winglet Designs on Light Aircraft." Journal of Advanced Research in Mechanical Engineering and Technology 05, no. 01 (March 19, 2018): 01–16. http://dx.doi.org/10.24321/2454.8650.201801.

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Sahu, Rishabh Kumar, Saurabh Sharma, and Vivek Swaroop Vishal Kumar. "Experimental Investigations and Computational Analysis on Subsonic Wind Tunnel." International Journal of Trend in Scientific Research and Development Volume-3, Issue-3 (April 30, 2019): 1708–11. http://dx.doi.org/10.31142/ijtsrd23511.

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Madhu, S., P. Murali, R. Ramasai, M. Venkat Vardhan, and K. Bhanu Prakash. "Computational Fluid Dynamics (CFD) Analysis of A Go-Kart." International Journal of Research Publication and Reviews 5, no. 11 (November 2024): 3418–24. http://dx.doi.org/10.55248/gengpi.5.1124.3262.

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22

Alkhimova, Larisa E., Maria G. Babashkina, and Damir A. Safin. "Computational analysis of aspirin." Journal of Molecular Structure 1251 (March 2022): 131975. http://dx.doi.org/10.1016/j.molstruc.2021.131975.

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Sharov, Artem V., Tatyana M. Burkhanova, Tugba Taskın Tok, Maria G. Babashkina, and Damir A. Safin. "Computational Analysis of Molnupiravir." International Journal of Molecular Sciences 23, no. 3 (January 28, 2022): 1508. http://dx.doi.org/10.3390/ijms23031508.

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In this work, we report in-depth computational studies of three plausible tautomeric forms, generated through the migration of two acidic protons of the N4-hydroxylcytosine fragment, of molnupiravir, which is emerging as an efficient drug to treat COVID-19. The DFT calculations were performed to verify the structure of these tautomers, as well as their electronic and optical properties. Molecular docking was applied to examine the influence of the structures of the keto-oxime, keto-hydroxylamine and hydroxyl-oxime tautomers on a series of the SARS-CoV-2 proteins. These tautomers exhibited the best affinity behavior (−9.90, −7.90, and −9.30 kcal/mol, respectively) towards RdRp-RTR and Nonstructural protein 3 (nsp3_range 207–379-MES).

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24

Rettinger, Robert. "Computational Complexity in Analysis." Electronic Proceedings in Theoretical Computer Science 24 (June 3, 2010): 3. http://dx.doi.org/10.4204/eptcs.24.3.

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25

Karlin, S., and L. R. Cardon. "Computational DNA Sequence Analysis." Annual Review of Microbiology 48, no. 1 (October 1994): 619–54. http://dx.doi.org/10.1146/annurev.mi.48.100194.003155.

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EDDY, S. R. "Computational Analysis of RNAs." Cold Spring Harbor Symposia on Quantitative Biology 71 (January 1, 2006): 117–28. http://dx.doi.org/10.1101/sqb.2006.71.003.

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Egnor, S. E. Roian, and Kristin Branson. "Computational Analysis of Behavior." Annual Review of Neuroscience 39, no. 1 (July 8, 2016): 217–36. http://dx.doi.org/10.1146/annurev-neuro-070815-013845.

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Baek, W. K., R. I. Stephens, and B. Dopker. "Integrated Computational Durability Analysis." Journal of Engineering for Industry 115, no. 4 (November 1, 1993): 492–99. http://dx.doi.org/10.1115/1.2901795.

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A computer aided analysis method is described for durability assessment in the early design stages using multibody dynamic analysis, finite element stress analysis, and fatigue life prediction methods. From multibody dynamic analysis of a mechanical system, dynamic loads of a mechanical component were calculated. Finite element stress analysis with substructuring techniques produced accurate stress fields for the component. From the dynamic loads and the stress field of the component, a dynamic stress history at the critical location was produced using the superposition principle. Using Neuber’s rule, a local strain time history was produced from the dynamic stress history. The local strain based fatigue life prediction method was then used to predict “crack initiation” life of the critical component. The predicted fatigue crack initiation life was verified by experimental durability tests. This methodology can be combined with identification of weak links and optimization techniques such that the design optimization for an entire mechanical system based upon durability is possible during the early product development stage.

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Dobner, H.-J. "Contributions to computational analysis." Bulletin of the Australian Mathematical Society 41, no. 2 (April 1990): 231–35. http://dx.doi.org/10.1017/s0004972700018049.

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In this paper some new results concerning computational analysis are established. The fundamental concepts of interval analysis and fixed point theorems suitable for computational purposes are developed and applied to concrete examples illustrating this new method of proving mathematical statements.

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Vahabzadeh, Yousef, Nima Chamanara, Karim Achouri, and Christophe Caloz. "Computational Analysis of Metasurfaces." IEEE Journal on Multiscale and Multiphysics Computational Techniques 3 (2018): 37–49. http://dx.doi.org/10.1109/jmmct.2018.2829871.

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Brown, Guy J., and Martin Cooke. "Computational auditory scene analysis." Computer Speech & Language 8, no. 4 (October 1994): 297–336. http://dx.doi.org/10.1006/csla.1994.1016.

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Vo, A. V., and D. F. Laefer. "A BIG DATA APPROACH FOR COMPREHENSIVE URBAN SHADOW ANALYSIS FROM AIRBORNE LASER SCANNING POINT CLOUDS." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences IV-4/W8 (September 23, 2019): 131–37. http://dx.doi.org/10.5194/isprs-annals-iv-4-w8-131-2019.

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<p><strong>Abstract.</strong> Because of the importance of access to sunlight, shadow analysis is a common consideration in urban design, especially for dense urban developments. As shadow computation is computationally expensive, most urban shadow analysis tools have to date circumvented the high computational costs by representing urban complexity only through simplified geometric models. The simplification process removes details and adversely affects the level of realism of the ultimate results. In this paper, an alternative approach is presented by utilizing the highest level of detail and resolution captured in the geometric input data source, which is an extremely high-resolution airborne laser scanning point cloud (300 points/m2). To cope with the high computational demand caused by the use of this dense and detailed input data set, the Comprehensive Urban Shadow algorithm is introduced to distribute the computation for parallel processing on a Hadoop cluster. The proposed comprehensive urban shadow analysis solution is scalable, reasonably fast, and capable of preserving the original resolution and geometric detail of the original point cloud data.</p>

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Anagnostopoulou, Christina, and Chantal Buteau. "Can computational music analysis be both musical and computational?" Journal of Mathematics and Music 4, no. 2 (July 2010): 75–83. http://dx.doi.org/10.1080/17459737.2010.520455.

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Otoguro, Yuto, Hiroki Mochizuki, Kenji Takizawa, and Tayfun E. Tezduyar. "Space–Time Variational Multiscale Isogeometric Analysis of a tsunami-shelter vertical-axis wind turbine." Computational Mechanics 66, no. 6 (August 31, 2020): 1443–60. http://dx.doi.org/10.1007/s00466-020-01910-5.

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AbstractWe present computational flow analysis of a vertical-axis wind turbine (VAWT) that has been proposed to also serve as a tsunami shelter. In addition to the three-blade rotor, the turbine has four support columns at the periphery. The columns support the turbine rotor and the shelter. Computational challenges encountered in flow analysis of wind turbines in general include accurate representation of the turbine geometry, multiscale unsteady flow, and moving-boundary flow associated with the rotor motion. The tsunami-shelter VAWT, because of its rather high geometric complexity, poses the additional challenge of reaching high accuracy in turbine-geometry representation and flow solution when the geometry is so complex. We address the challenges with a space–time (ST) computational method that integrates three special ST methods around the core, ST Variational Multiscale (ST-VMS) method, and mesh generation and improvement methods. The three special methods are the ST Slip Interface (ST-SI) method, ST Isogeometric Analysis (ST-IGA), and the ST/NURBS Mesh Update Method (STNMUM). The ST-discretization feature of the integrated method provides higher-order accuracy compared to standard discretization methods. The VMS feature addresses the computational challenges associated with the multiscale nature of the unsteady flow. The moving-mesh feature of the ST framework enables high-resolution computation near the blades. The ST-SI enables moving-mesh computation of the spinning rotor. The mesh covering the rotor spins with it, and the SI between the spinning mesh and the rest of the mesh accurately connects the two sides of the solution. The ST-IGA enables more accurate representation of the blade and other turbine geometries and increased accuracy in the flow solution. The STNMUM enables exact representation of the mesh rotation. A general-purpose NURBS mesh generation method makes it easier to deal with the complex turbine geometry. The quality of the mesh generated with this method is improved with a mesh relaxation method based on fiber-reinforced hyperelasticity and optimized zero-stress state. We present computations for the 2D and 3D cases. The computations show the effectiveness of our ST and mesh generation and relaxation methods in flow analysis of the tsunami-shelter VAWT.

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Cui, Zhe, Jayaram Kancherla, Kyle W. Chang, Niklas Elmqvist, and Héctor Corrada Bravo. "Proactive visual and statistical analysis of genomic data in Epiviz." Bioinformatics 36, no. 7 (November 29, 2019): 2195–201. http://dx.doi.org/10.1093/bioinformatics/btz883.

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Abstract Motivation Integrative analysis of genomic data that includes statistical methods in combination with visual exploration has gained widespread adoption. Many existing methods involve a combination of tools and resources: user interfaces that provide visualization of large genomic datasets, and computational environments that focus on data analyses over various subsets of a given dataset. Over the last few years, we have developed Epiviz as an integrative and interactive genomic data analysis tool that incorporates visualization tightly with state-of-the-art statistical analysis framework. Results In this article, we present Epiviz Feed, a proactive and automatic visual analytics system integrated with Epiviz that alleviates the burden of manually executing data analysis required to test biologically meaningful hypotheses. Results of interest that are proactively identified by server-side computations are listed as notifications in a feed. The feed turns genomic data analysis into a collaborative work between the analyst and the computational environment, which shortens the analysis time and allows the analyst to explore results efficiently. We discuss three ways where the proposed system advances the field of genomic data analysis: (i) takes the first step of proactive data analysis by utilizing available CPU power from the server to automate the analysis process; (ii) summarizes hypothesis test results in a way that analysts can easily understand and investigate; (iii) enables filtering and grouping of analysis results for quick search. This effort provides initial work on systems that substantially expand how computational and visualization frameworks can be tightly integrated to facilitate interactive genomic data analysis. Availability and implementation The source code for Epiviz Feed application is available at http://github.com/epiviz/epiviz_feed_polymer. The Epiviz Computational Server is available at http://github.com/epiviz/epiviz-feed-computation. Please refer to Epiviz documentation site for details: http://epiviz.github.io/.

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Ichimura, Tsuyoshi, Ryoichiro Agata, Takane Hori, Kenji Satake, Kazuto Ando, Toshitaka Baba, and Mueno Hori. "Tsunami Analysis Method with High-Fidelity Crustal Structure and Geometry Model." Journal of Earthquake and Tsunami 11, no. 05 (December 2017): 1750018. http://dx.doi.org/10.1142/s179343111750018x.

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Higher fidelity seafloor topography and crustal structure models have become available with accumulation of observation data. Previous studies have shown that the consideration of such high-fidelity models produces significant effects, in some cases, on crustal deformation results that are used as inputs for tsunami analysis. However, it is difficult to apply high-fidelity model of crustal deformation computations to tsunami computations because of large computational costs. In this paper, we propose a new crustal deformation computation method for estimating inputs for tsunami computations, which is based on a finite element analysis method with remarkable reduction of computation costs by efficient use of the arithmetic space and the solution space. This finite element analysis method enables us to conduct [Formula: see text]-times crustal deformation computations using high-fidelity models with a degree of freedom on the order of [Formula: see text] for the 2011 Tohoku earthquake example. Tsunami computations with typical settings are conducted as an application example to present the advantages and characteristics of the proposed method. Comparisons between results of the proposed and the conventional method reveal that large shallow fault slip around the trench axis may lead to significant differences in tsunami waveforms and inundation height distributions in some cases.

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Pardhanani, Anand, and Graham F. Carey. "Optimization of computational grids." Numerical Methods for Partial Differential Equations 4, no. 2 (1988): 95–117. http://dx.doi.org/10.1002/num.1690040202.

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Babuška, I., F. Nobile, and R. Tempone. "Reliability of computational science." Numerical Methods for Partial Differential Equations 23, no. 4 (2007): 753–84. http://dx.doi.org/10.1002/num.20263.

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Zhang, Guiming, and Jin Xu. "Multi-GPU-Parallel and Tile-Based Kernel Density Estimation for Large-Scale Spatial Point Pattern Analysis." ISPRS International Journal of Geo-Information 12, no. 2 (January 18, 2023): 31. http://dx.doi.org/10.3390/ijgi12020031.

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Kernel density estimation (KDE) is a commonly used method for spatial point pattern analysis, but it is computationally demanding when analyzing large datasets. GPU-based parallel computing has been adopted to address such computational challenges. The existing GPU-parallel KDE method, however, utilizes only one GPU for parallel computing. Additionally, it assumes that the input data can be held in GPU memory all at once for computation, which is unrealistic when conducting KDE analysis over large geographic areas at high resolution. This study develops a multi-GPU-parallel and tile-based KDE algorithm to overcome these limitations. It exploits multiple GPUs to speedup complex KDE computation by distributing computation across GPUs, and approaches density estimation with a tile-based strategy to bypass the memory bottleneck. Experiment results show that the parallel KDE algorithm running on multiple GPUs achieves significant speedups over running on a single GPU, and higher speedups are achieved on KDE tasks of a larger problem size. The tile-based strategy renders it feasible to estimate high-resolution density surfaces over large areas even on GPUs with only limited memory. Multi-GPU parallel computing and tile-based density estimation, while incurring very little computational overhead, effectively enable conducting KDE for large-scale spatial point pattern analysis on geospatial big data.

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Gourary, M. M., S. G. Rusakov, S. L. Ulyanov, M. M. Zharov, and B. J. Mulvaney. "Circuit Distortion Analysis Based on the Simplified Newton's Method." Journal of Electrical and Computer Engineering 2011 (2011): 1–11. http://dx.doi.org/10.1155/2011/540305.

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A new computational technique for distortion analysis of nonlinear circuits is presented. The new technique is applicable to the same class of circuits, namely, weakly nonlinear and time-varying circuits, as the periodic Volterra series. However, unlike the Volterra series, it does not require the computation of the second and third derivatives of device models. The new method is computationally efficient compared with a complete multitone nonlinear steady-state analysis such as harmonic balance. Moreover, the new technique naturally allows computing and characterizing the contributions of individual circuit components to the overall circuit distortion. This paper presents the theory of the new technique, a discussion of the numerical aspects, and numerical results.

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Sabadini, Irene, and Daniele C. Struppa. "Computational algebraic analysis methods in Clifford analysis." Mathematical Methods in the Applied Sciences 25, no. 16-18 (2002): 1415–27. http://dx.doi.org/10.1002/mma.379.

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Hozak, Yaroslav, and Sergiy Paliy. "Modern small networks for image classification. Feature analysis." Management of Development of Complex Systems, no. 60 (November 29, 2024): 221–29. https://doi.org/10.32347/2412-9933.2024.60.221-229.

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With the increasing demand for deploying deep learning models on resource-constrained devices, such as smartphones, IoT sensors, and edge computing platforms, the need for efficient convolutional neural networks (CNNs) has become paramount. This paper offers a comprehensive review of several state-of-the-art lightweight CNN architectures designed to address these challenges by reducing computational complexity and memory usage, while maintaining competitive performance in image classification tasks. Key architectures reviewed include MobileNets, ShuffleNet, DiceNet, and ESPNet, each of which employs distinct strategies to optimize network efficiency. MobileNets introduce the concept of depthwise separable convolutions, which decompose the standard convolution operation into a depthwise convolution and a point-wise convolution (1x1). This drastically reduces the number of parameters and computations compared to traditional convolutions. ShuffleNet, on the other hand, leverages group convolutions and channel shuffling to enhance efficiency, allowing feature maps to be split and recombined, which reduces computational cost without significantly compromising accuracy. DiceNet builds upon these concepts by introducing multi-branch architecture with different dilation rates to capture features at multiple scales, enhancing both accuracy and efficiency in low-resource environments. ESPNet employs efficient spatial pyramidal structures, along with point-wise convolutions, to handle diverse spatial features at different scales while being highly computationally efficient. Despite these advancements, a common bottleneck across these architectures is the reliance on point-wise (1x1) convolutions, which, while more efficient than standard convolutions, still contribute significantly to the overall computational cost, particularly in deeper layers of the network. Furthermore, filter sizes are often optimized for performance in a cloud-based setting but may not be ideal for edge environments where computational and energy efficiency are crucial. We see the potential in changing filter sizes in some layers to 2x2 which is the smallest possible filter for spatial information extraction. Also it worth paying attention to the way the information is spread across channels as well as how the channels number is formed by replacing 1x1 convolution with a generic but yet predictable mathematical operation.

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Kuraishi, Takashi, Kenji Takizawa, and Tayfun E. Tezduyar. "Space–time Isogeometric flow analysis with built-in Reynolds-equation limit." Mathematical Models and Methods in Applied Sciences 29, no. 05 (May 2019): 871–904. http://dx.doi.org/10.1142/s0218202519410021.

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We present a space–time (ST) computational flow analysis method with built-in Reynolds-equation limit. The method enables solution of lubrication fluid dynamics problems with a computational cost comparable to that of the Reynolds-equation model for the comparable solution quality, but with the computational flexibility to go beyond the limitations of the Reynolds-equation model. The key components of the method are the ST Variational Multiscale (ST-VMS) method, ST Isogeometric Analysis (ST-IGA), and the ST Slip Interface (ST-SI) method. The VMS feature of the ST-VMS serves as a numerical stabilization method with a good track record, the moving-mesh feature of the ST framework enables high-resolution flow computation near the moving fluid–solid interfaces, and the higher-order accuracy of the ST framework strengthens both features. The ST-IGA enables more accurate representation of the solid-surface geometries and increased accuracy in the flow solution in general. With the ST-IGA, even with just one quadratic NURBS element across the gap of the lubrication fluid dynamics problem, we reach a solution quality comparable to that of the Reynolds-equation model. The ST-SI enables moving-mesh computation when the spinning solid surface is noncircular. The mesh covering the solid surface spins with it, retaining the high-resolution representation of the flow near the surface, and the SI between the spinning mesh and the rest of the mesh accurately connects the two sides of the solution. We present detailed 2D test computations to show how the method performs compared to the Reynolds-equation model, compared to finite element discretization, at different circumferential and normal mesh refinement levels, when there is an SI in the mesh, and when the no-slip boundary conditions are weakly-enforced.

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Fish, Jacob, and Sergey Kuznetsov. "Computational continua." International Journal for Numerical Methods in Engineering 84, no. 7 (October 25, 2010): 774–802. http://dx.doi.org/10.1002/nme.2918.

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Fan, Jianqing, Fang Han, and Han Liu. "Challenges of Big Data analysis." National Science Review 1, no. 2 (February 5, 2014): 293–314. http://dx.doi.org/10.1093/nsr/nwt032.

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Abstract Big Data bring new opportunities to modern society and challenges to data scientists. On the one hand, Big Data hold great promises for discovering subtle population patterns and heterogeneities that are not possible with small-scale data. On the other hand, the massive sample size and high dimensionality of Big Data introduce unique computational and statistical challenges, including scalability and storage bottleneck, noise accumulation, spurious correlation, incidental endogeneity and measurement errors. These challenges are distinguished and require new computational and statistical paradigm. This paper gives overviews on the salient features of Big Data and how these features impact on paradigm change on statistical and computational methods as well as computing architectures. We also provide various new perspectives on the Big Data analysis and computation. In particular, we emphasize on the viability of the sparsest solution in high-confidence set and point out that exogenous assumptions in most statistical methods for Big Data cannot be validated due to incidental endogeneity. They can lead to wrong statistical inferences and consequently wrong scientific conclusions.

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Bell, John B., Alejandro L. Garcia, and Sarah A. Williams. "Computational fluctuating fluid dynamics." ESAIM: Mathematical Modelling and Numerical Analysis 44, no. 5 (August 26, 2010): 1085–105. http://dx.doi.org/10.1051/m2an/2010053.

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Yoon, Daegeun, and Donghyun You. "An adaptive memory method for accurate and efficient computation of the Caputo fractional derivative." Fractional Calculus and Applied Analysis 24, no. 5 (October 1, 2021): 1356–79. http://dx.doi.org/10.1515/fca-2021-0058.

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Abstract A fractional derivative is a temporally nonlocal operation which is computationally intensive due to inclusion of the accumulated contribution of function values at past times. In order to lessen the computational load while maintaining the accuracy of the fractional derivative, a novel numerical method for the Caputo fractional derivative is proposed. The present adaptive memory method significantly reduces the requirement for computational memory for storing function values at past time points and also significantly improves the accuracy by calculating convolution weights to function values at past time points which can be non-uniformly distributed in time. The superior accuracy of the present method to the accuracy of the previously reported methods is identified by deriving numerical errors analytically. The sub-diffusion process of a time-fractional diffusion equation is simulated to demonstrate the accuracy as well as the computational efficiency of the present method.

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Kaur, Sumit, and R. K. Bansal. "COMPARATIVE ANALYSIS OF SUPERPIXEL SEGMENTATION METHODS." International Journal of Engineering Technologies and Management Research 5, no. 3 (February 10, 2020): 1–9. http://dx.doi.org/10.29121/ijetmr.v5.i3.2018.172.

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Superpixel segmentation showed to be a useful preprocessing step in many computer vision applications. Superpixel’s purpose is to reduce the redundancy in the image and increase efficiency from the point of view of the next processing task. This led to a variety of algorithms to compute superpixel segmentations, each with individual strengths and weaknesses. Many methods for the computation of superpixels were already presented. A drawback of most of these methods is their high computational complexity and hence high computational time consumption. K mean based SLIC method shows better performance as compare to other while evaluating on the bases of under segmentation error and boundary recall, etc parameters.

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Saito, Yoshifuru. "Wavelet Analysis for Computational Electromagnetics." IEEJ Transactions on Fundamentals and Materials 116, no. 10 (1996): 833–39. http://dx.doi.org/10.1541/ieejfms1990.116.10_833.

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Vendrusculo, Laurimar Gonçalves, Paulo Sérgio Graziano Magalhães, Sidney Rosa Vieira, and José Ruy Porto de Carvalho. "Computational system for geostatistical analysis." Scientia Agricola 61, no. 1 (February 2004): 100–107. http://dx.doi.org/10.1590/s0103-90162004000100017.

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Geostatistics identifies the spatial structure of variables representing several phenomena and its use is becoming more intense in agricultural activities. This paper describes a computer program, based on Windows Interfaces (Borland Delphi), which performs spatial analyses of datasets through geostatistic tools: Classical statistical calculations, average, cross- and directional semivariograms, simple kriging estimates and jackknifing calculations. A published dataset of soil Carbon and Nitrogen was used to validate the system. The system was useful for the geostatistical analysis process, for the manipulation of the computational routines in a MS-DOS environment. The Windows development approach allowed the user to model the semivariogram graphically with a major degree of interaction, functionality rarely available in similar programs. Given its characteristic of quick prototypation and simplicity when incorporating correlated routines, the Delphi environment presents the main advantage of permitting the evolution of this system.

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