Erratum to An Efficient Algorithm to Identify Strong‐Velocity Pulses in Multi‐Component Ground Motions

2019 ◽  
Vol 109 (6) ◽  
pp. 2767-2767
Author(s):  
Shrey K. Shahi ◽  
Jack W. Baker
Keyword(s):  
Efficient Algorithm ◽  
Ground Motions

An efficient algorithm to simulate hazard-targeted site-based synthetic ground motions

2020 ◽  
pp. 875529302097096
Author(s):  
Jawad Fayaz ◽  
Sarah Azar ◽  
Mayssa Dabaghi ◽  
Farzin Zareian
Keyword(s):  
Ground Motion ◽  
Efficient Algorithm ◽  
Ground Motions ◽  
Model Parameters ◽  
Graphic User Interface ◽  
Forward Selection ◽  
Intensity Measure ◽  
Input Event ◽  
Predictive Relations ◽  
Simulated Ground Motions

This study presents an efficient algorithm that can be used to simulate ground motion waveforms using the site-based approach developed by Dabaghi and Der Kiureghian, and Rezaeian and Der Kiureghian that not only correspond to a specified seismic scenario (e.g. magnitude, distance, site conditions) but are also certain to achieve a target ground motion intensity measure within a narrow range. The suggested algorithm alleviates the need to scale simulated ground motions generated using the above-mentioned site-based approach; the resulting hazard-targeted simulated ground motions have consistent amplitude and time- and frequency-domain characteristics, which are required for proper seismic demand analysis of structures. The proposed algorithm takes as input a set of seismic Event Parameters and the target hazard intensity measure [Formula: see text] and generates a corresponding set of Model Parameters (i.e. input to the site-based ground motion simulation model). These Model Parameters are then used to simulate ground motion waveforms that not only represent the set of input Event Parameters ( Mw, Rrup, Vs30) but also maintain the target [Formula: see text]. To generate the set of Model Parameters, predictive relations between the Model Parameters and [Formula: see text] of ground motions are developed. Among the Model Parameters, the ones classified as important by statistical procedures (such as Random Forests, Forward Selection) are used to develop the predictive relations. The developed relations are then validated against a large dataset of recorded ground motions. The final implementation is provided in terms of graphic-user interface (GUI) called “Hazard-Targeted Time-Series Simulator” ( HATSim), which efficiently simulates site-based ground motions with minimum inputs.

An efficient algorithm for identifying pulse-like ground motions based on significant velocity half-cycles

2017 ◽  
Vol 47 (3) ◽  
pp. 757-771 ◽  
Author(s):  
Changhai Zhai ◽  
Cuihua Li ◽  
Sashi Kunnath ◽  
Weiping Wen
Keyword(s):  
Efficient Algorithm ◽  
Ground Motions

Computational Micrograph Registration with Sieve Processes

1996 ◽  
Vol 54 ◽  
pp. 440-441
Author(s):  
P.J. Phillips ◽  
J. Huang ◽  
S. M. Dunn
Keyword(s):  
Planar Graph ◽  
Efficient Algorithm ◽  
Spatial Organization ◽  
Spatial Arrangement ◽  
Stereo Image ◽  
Image Model ◽  
Geometric Invariants ◽  
Point Set

In this paper we present an efficient algorithm for automatically finding the correspondence between pairs of stereo micrographs, the key step in forming a stereo image. The computation burden in this problem is solving for the optimal mapping and transformation between the two micrographs. In this paper, we present a sieve algorithm for efficiently estimating the transformation and correspondence.In a sieve algorithm, a sequence of stages gradually reduce the number of transformations and correspondences that need to be examined, i.e., the analogy of sieving through the set of mappings with gradually finer meshes until the answer is found. The set of sieves is derived from an image model, here a planar graph that encodes the spatial organization of the features. In the sieve algorithm, the graph represents the spatial arrangement of objects in the image. The algorithm for finding the correspondence restricts its attention to the graph, with the correspondence being found by a combination of graph matchings, point set matching and geometric invariants.

Energy efficient algorithm for lookup-tables on mobile devices

2016 ◽  
Vol 2016 (7) ◽  
pp. 1-6
Author(s):  
Sergey Makov ◽  
Vladimir Frantc ◽  
Viacheslav Voronin ◽  
Igor Shrayfel ◽  
Vadim Dubovskov ◽  
...  
Keyword(s):  
Mobile Devices ◽  
Efficient Algorithm ◽  
Energy Efficient ◽  
Lookup Tables
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