Directional illumination analysis using the local exponential frame

We have developed an efficient method of directional illumination analysis in the local angle domain using local exponential frame beamlets. The space-domain wavefields with different shot-receiver geometries are decomposed into the local angle domain by using the local exponential beamlets, which form a tight frame with the redundancy ratio two and are implemented by a linear combination of local cosine and local sine transforms. Because of the fast algorithms of the local cosine/sine transforms, this method is much more efficient than the previously used decomposition methods in directional illumination analysis, such as the local slant-stacking method and the Gabor-Daubechies frame method. The results of directional illumination (DI) maps and the acqui-sition dip responses (ADR) for the 2D SEG/EAGE salt model and the 45-shot 3D SEG/EAGE model demonstrated the validity and feasibility of our method. Compared with the illumination results using local slant-stacking decomposition, the new method produces illumination maps of similar quality, but it does so a few times faster. Furthermore, because of its high computational efficiency and saving in memory usage, the new method makes the 3D directional illumination analysis readily applicable in the industry.

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Enhancing Both Efficiency and Representational Capability of Isomap by Extensive Landmark Selection

Mathematical Problems in Engineering ◽

10.1155/2015/241436 ◽

2015 ◽

Vol 2015 ◽

pp. 1-18 ◽

Cited By ~ 2

Author(s):

Dong Liang ◽

Chen Qiao ◽

Zongben Xu

Keyword(s):

Manifold Learning ◽

Computational Efficiency ◽

New Method ◽

Data Sets ◽

Learning Approaches ◽

Real World Data ◽

Efficiency Property ◽

Data Points ◽

Low Dimensional ◽

High Computational Efficiency

The problems of improving computational efficiency and extending representational capability are the two hottest topics in approaches of global manifold learning. In this paper, a new method called extensive landmark Isomap (EL-Isomap) is presented, addressing both topics simultaneously. On one hand, originated from landmark Isomap (L-Isomap), which is known for its high computational efficiency property, EL-Isomap also possesses high computational efficiency through utilizing a small set of landmarks to embed all data points. On the other hand, EL-Isomap significantly extends the representational capability of L-Isomap and other global manifold learning approaches by utilizing only an available subset from the whole landmark set instead of all to embed each point. Particularly, compared with other manifold learning approaches, the data manifolds with intrinsic low-dimensional concave topologies and essential loops can be unwrapped by the new method more successfully, which are shown by simulation results on a series of synthetic and real-world data sets. Moreover, the accuracy, robustness, and computational complexity of EL-Isomap are analyzed in this paper, and the relation between EL-Isomap and L-Isomap is also discussed theoretically.

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A New Method for Railway Fastener Detection Using the Symmetrical Image and Its EA-HOG Feature

International Journal of Pattern Recognition and Artificial Intelligence ◽

10.1142/s021800142055006x ◽

2019 ◽

Vol 34 (02) ◽

pp. 2055006

Author(s):

Jiajia Liu ◽

Jianying Yuan ◽

Yongfang Jia

Keyword(s):

Computer Vision ◽

Sparse Representation ◽

Efficient Method ◽

Important Task ◽

New Method ◽

Automatic Inspection ◽

Test Image ◽

Recognition Result ◽

The Status ◽

Railway Operation

Railway fastener recognition and detection is an important task for railway operation safety. However, the current automatic inspection methods based on computer vision can effectively detect the intact or completely missing fasteners, but they have weaker ability to recognize the partially worn ones. In our method, we exploit the EA-HOG feature fastener image, generate two symmetrical images of original test image and turn the detection of the original test image into the detection of two symmetrical images, then integrate the two recognition results of symmetrical image to reach exact recognition of original test image. The potential advantages of the proposed method are as follows: First, we propose a simple yet efficient method to extract the fastener edge, as well as the EA-HOG feature of the fastener image. Second, the symmetry images indeed reflect some possible appearance of the fastener image which are not shown in the original images, these changes are helpful for us to judge the status of the symmetry samples based on the improved sparse representation algorithm and then obtain an exact judgment of the original test image by combining the two corresponding judgments of its symmetry images. The experiment results show that the proposed approach achieves a rather high recognition result and meets the demand of railway fastener detection.

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Remarks on “On a General Class of Multipoint Root-Finding Methods of High Computational Efficiency”

SIAM Journal on Numerical Analysis ◽

10.1137/100805340 ◽

2011 ◽

Vol 49 (3) ◽

pp. 1317-1319 ◽

Cited By ~ 35

Author(s):

Miodrag S. Petković

Keyword(s):

Computational Efficiency ◽

General Class ◽

Root Finding ◽

High Computational Efficiency

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A CONFORMING POINT INTERPOLATION METHOD (CPIM) BY SHAPE FUNCTION RECONSTRUCTION FOR ELASTICITY PROBLEMS

International Journal of Computational Methods ◽

10.1142/s0219876210002295 ◽

2010 ◽

Vol 07 (03) ◽

pp. 369-395 ◽

Cited By ~ 9

Author(s):

X. XU ◽

G. R. LIU ◽

Y. T. GU ◽

G. Y. ZHANG

Keyword(s):

Convergence Rate ◽

Computational Efficiency ◽

Shape Function ◽

Interpolation Method ◽

Numerical Studies ◽

Point Interpolation Method ◽

Elasticity Problems ◽

Point Interpolation ◽

Continuous Displacement ◽

High Computational Efficiency

A conforming point interpolation method (CPIM) is proposed based on the Galerkin formulation for 2D mechanics problems using triangular background cells. A technique for reconstructing the PIM shape functions is proposed to create a continuous displacement field over the whole problem domain, which guarantees the CPIM passing the standard patch test. We prove theoretically the existence and uniqueness of the CPIM solution, and conduct detailed analyses on the convergence rate; computational efficiency and band width of the stiffness matrix of CPIM. The CPIM does not introduce any additional degrees of freedoms compared to the linear FEM and original PIM; while convergence rate of quadratic CPIM is in between that of linear FEM and quadratic FEM which results in the high computational efficiency. Intensive numerical studies verify the properties of the CPIM.

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Modeling and Experimental Validation of the VARTM Process for Thin-Walled Preforms

Polymers ◽

10.3390/polym11122003 ◽

2019 ◽

Vol 11 (12) ◽

pp. 2003

Author(s):

Da Wu ◽

Ragnar Larsson ◽

Mohammad S. Rouhi

Keyword(s):

Shell Model ◽

Computational Efficiency ◽

Large Scale ◽

Strongly Coupled ◽

Thin Walled Structures ◽

Simulation Based ◽

Thin Walled ◽

High Computational Efficiency ◽

Insight Into ◽

Vartm Process

In this paper, recent shell model is advanced towards the calibration and validation of the Vacuum-assisted Resin Transfer Molding (VARTM) process in a novel way. The model solves the nonlinear and strongly coupled resin flow and preform deformation when the 3-D flow and stress problem is simplified to a corresponding 2-D problem. In this way, the computational efficiency is enhanced dramatically, which allows for simulations of the VARTM process of large scale thin-walled structures. The main novelty is that the assumptions of the neglected through-thickness flow and the restricted preform deformation along the normal of preform surface suffice well for the thin-walled VARTM process. The model shows excellent agreement with the VARTM process experiment. With good accuracy and high computational efficiency, the shell model provides an insight into the simulation-based optimization of the VARTM process. It can be applied to either determine locations of the gate and vents or optimize process parameters to reduce the deformation.

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Analytical Modeling of In-Process Temperature in Powder Bed Additive Manufacturing Considering Laser Power Absorption, Latent Heat, Scanning Strategy, and Powder Packing

Materials ◽

10.3390/ma12050808 ◽

2019 ◽

Vol 12 (5) ◽

pp. 808 ◽

Cited By ~ 47

Author(s):

Jinqiang Ning ◽

Daniel Sievers ◽

Hamid Garmestani ◽

Steven Liang

Keyword(s):

Additive Manufacturing ◽

Computational Efficiency ◽

Molten Pool ◽

Laser Power ◽

Analytical Modeling ◽

Single Track ◽

Scanning Strategy ◽

Powder Bed ◽

Powder Packing ◽

High Computational Efficiency

Temperature distribution gradient in metal powder bed additive manufacturing (MPBAM) directly controls the mechanical properties and dimensional accuracy of the build part. Experimental approach and numerical modeling approach for temperature in MPBAM are limited by the restricted accessibility and high computational cost, respectively. Analytical models were reported with high computational efficiency, but the developed models employed a moving coordinate and semi-infinite medium assumption, which neglected the part dimensions, and thus reduced their usefulness in real applications. This paper investigates the in-process temperature in MPBAM through analytical modeling using a stationary coordinate with an origin at the part boundary (absolute coordinate). Analytical solutions are developed for temperature prediction of single-track scan and multi-track scans considering scanning strategy. Inconel 625 is chosen to test the proposed model. Laser power absorption is inversely identified with the prediction of molten pool dimensions. Latent heat is considered using the heat integration method. The molten pool evolution is investigated with respect to scanning time. The stabilized temperatures in the single-track scan and bidirectional scans are predicted under various process conditions. Close agreements are observed upon validation to the experimental values in the literature. Furthermore, a positive relationship between molten pool dimensions and powder packing porosity was observed through sensitivity analysis. With benefits of the absolute coordinate, and high computational efficiency, the presented model can predict the temperature for a dimensional part during MPBAM, which can be used to further investigate residual stress and distortion in real applications.

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Full-wave directional illumination analysis in the frequency domain

Geophysics ◽

10.1190/1.3131383 ◽

2009 ◽

Vol 74 (4) ◽

pp. S85-S93 ◽

Cited By ~ 22

Author(s):

Jun Cao ◽

Ru-Shan Wu

Keyword(s):

Frequency Domain ◽

Wave Equations ◽

Survey Design ◽

Decomposition Methods ◽

Frequency Dependent ◽

Reflected Waves ◽

Full Wave ◽

Full Wave Analysis ◽

Extensive Computation ◽

Local Angle

Directional illumination analysis based on one-way wave equations has been studied extensively; however, its inherent limitations, e.g., one-way propagation, wide-angle error, and amplitude inaccuracy, can severely hinder its applications for accurate survey design and true-reflection imaging corrections in complex media. We have analyzed the illumination in the frequency domain using full two-way wave propagators considering the extensive computation and huge storage required for time-domain methods, and the fact that the illumination is frequency dependent. This full-wave analysis can provide frequency-dependent full-angle true-amplitude illumination not only for the downgoing waves but also for the upgoing waves, including turning waves and reflected waves. Two methods were considered to decompose the full wavefield into the local angle domain: a direct full-dimensional decomposition and more efficient split-step decomposition composed of three lower-dimensional decompositions. The results of illumination analysis demonstrated the advantages of this method. The two decomposition methods produced similar results.

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Inferring cellular regulatory networks with Bayesian model averaging for linear regression (BMALR)

Molecular BioSystems ◽

10.1039/c4mb00053f ◽

2014 ◽

Vol 10 (8) ◽

pp. 2023-2030 ◽

Cited By ~ 6

Author(s):

Xun Huang ◽

Zhike Zi

Keyword(s):

Linear Regression ◽

Molecular Interactions ◽

Computational Efficiency ◽

Bayesian Model ◽

Prediction Accuracy ◽

Regulatory Networks ◽

Bayesian Model Averaging ◽

Model Averaging ◽

High Prediction ◽

High Computational Efficiency

A new method that uses Bayesian model averaging for linear regression to infer molecular interactions in biological systems with high prediction accuracy and high computational efficiency.

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A new method for calculating the Jacobian for a robot manipulator

Robotica ◽

10.1017/s0263574700002125 ◽

1983 ◽

Vol 1 (4) ◽

pp. 205-209 ◽

Cited By ~ 13

Author(s):

Jadran Lenarčič

Keyword(s):

Computational Efficiency ◽

Execution Time ◽

Robot Manipulator ◽

Degree Of Freedom ◽

New Method ◽

Trigonometric Functions

SUMMARYA new method for calculating the Jacobian for a general n degree-of-freedom robot manipulator is presented and compared with some known other methods. The computational efficiency of the method is estimated in terms of the number of multiplications, additions/subtractions, trigonometric functions required, and the execution time on a VAX 11/750 computer. It is shown that the new method proposed in this paper is one of the most efficient when applied on a robot manipulator with successively parallel or rectangular joint rotations.

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