Joint acquisition strategy of GNSS satellites for computational cost reduction

ABSTRACT ObjectivesThe SA.NT DataLink Next Generation Linkage Management System (NGLMS) stores linked data in the form of a graph (in the computer science sense) comprised of nodes (records) and edges (record relationships or similarities). This permits efficient pre-clustering techniques based on transitive closure to form groups of records which relate to the same individual (or other selection criteria). ApproachOnly information known (or at least highly likely) to be relevant is extracted from the graph as superclusters. This operation is computationally inexpensive when the underlying information is stored as a graph and may be able to be done on-the-fly for typical clusters. More computationally intensive analysis and/or further clustering may then be performed on this smaller subgraph. Canopy clustering and using blocking used to reduce pairwise comparisons are expressions of the same type of approach. ResultsSubclusters for manual review based on transitive closure are typically computationally inexpensive enough to extract from the NGLMS that they are extracted on-demand during manual clerical review activities. There is no necessity to pre-calculate these clusters. Once extracted further analysis is undertaken on these smaller data groupings for visualisation and presentation for review and quality analysis. More computationally expensive techniques can be used at this point to prepare data for visualisation or provide hints to manual reviewers.  Extracting high-recall groups of data records for review but providing them to reviews grouped further into high precision groups as the result of a second pass has resulted in a reduction of the time taken for clerical reviewers at SANT DataLink to manual review a group by 30–40%. The reviewers are able to manipulate whole groups of related records at once rather than individual records. ConclusionPre-clustering reduces the computational cost associated with higher order clustering and analysis algorithms. Algorithms which scale by n^2 (or more) are typical in comparison scenarios. By breaking the problem into pieces the computational cost can be reduced. Typically breaking a problem into many pieces reduces the cost in proportion to the number of pieces the problem can be broken into. This cost reduction can make techniques possible which would otherwise be computationally prohibitive.

Download Full-text

Computational cost reduction of H.264/AVC video coding standard for videoconferencing applications

10.1109/isspa.2007.4555508 ◽

2007 ◽

Author(s):

Vianney Munoz-Jimenez ◽

Anissa Zergainoh

Keyword(s):

Video Coding ◽

Cost Reduction ◽

Computational Cost

Download Full-text

A Simplified Milstein Scheme for SPDEs with Multiplicative Noise

Abstract and Applied Analysis ◽

10.1155/2014/140849 ◽

2014 ◽

Vol 2014 ◽

pp. 1-15 ◽

Cited By ~ 1

Author(s):

B. Ghayebi ◽

S. M. Hosseini

Keyword(s):

Cost Reduction ◽

Order Of Convergence ◽

Multiplicative Noise ◽

Research Question ◽

Computational Cost ◽

Order Of Accuracy ◽

Milstein Scheme ◽

Exponential Term ◽

Numerical Tests ◽

Computational Reduction

This paper deals with a research question raised by Jentzen and Röckner (A Milstein scheme for SPDEs, arXiv:1001.2751v4 (2012)), whether the exponential term in their introduced scheme can be replaced by a simpler mollifier. This replacement can lead to more simplification and computational reduction in simulation. So, in this paper, we essentially replace the exponential term with a Padé approximation of order 1 and denote the resulting scheme by simplified Milstein scheme. The convergence analysis for this scheme is carried out and it is shown that even with this replacement the order of convergence is maintained, while the resulting scheme is easier to implement and slightly more efficient computationally. Some numerical tests are given that confirm the order of accuracy and also computational cost reduction.

Download Full-text

Parametric space-frequency reduction for second-order system models

10.14293/p2199-8442.1.sop-math.qukeqc.v1 ◽

2018 ◽

Author(s):

Vanessa Cool ◽

Frank Naets ◽

Ward Rottiers ◽

Wim Desmet

Keyword(s):

Frequency Response ◽

Cost Reduction ◽

Frequency Response Function ◽

Performance Metrics ◽

Computational Cost ◽

Order System ◽

Model Parameters ◽

Frequency Content ◽

Space Frequency ◽

Set Up

This research focusses on the computational cost reduction of frequency domain simulations in many-query applications with varying model parameters. These analyses are often encountered during the design of mechanical structures, where frequency response function (FRF) amplitudes are still one of the key performance metrics to be considered. Moreover, often inputs (number and frequency content) can vary broadly, which makes it all the more challenging to set up the reduced model.

Download Full-text