Utilizing Time Redundancy for Particle Filter-Based Transfer Alignment

2016 ◽  
Vol 15 (04) ◽  
pp. 1650024 ◽  
Author(s):  
Suvendu Chattaraj ◽  
Abhik Mukherjee
Keyword(s):  
System Dynamics ◽  
Particle Filter ◽  
Protein Interactions ◽  
Estimation Accuracy ◽  
Transfer Alignment ◽  
Domain Specific ◽  
Support Points ◽  
Multiple Processors ◽  
Filter Algorithms ◽  
Frequent Measurement

Signal detection in the presence of high noise is a challenge in natural sciences. From understanding signals emanating out of deep space probes to signals in protein interactions for systems biology, domain specific innovations are needed. The present work is in the domain of transfer alignment (TA), which deals with estimation of the misalignment of deliverable daughter munitions with respect to that of the delivering mother platform. In this domain, the design of noise filtering scheme has to consider a time varying and nonlinear system dynamics at play. The accuracy of conventional particle filter formulation suffers due to deviations from modeled system dynamics. An evolutionary particle filter can overcome this problem by evolving multiple system models through few support points per particle. However, this variant has even higher time complexity for real-time execution. As a result, measurement update gets deferred and the estimation accuracy is compromised. By running these filter algorithms on multiple processors, the execution time can be reduced, to allow frequent measurement updates. Such scheme ensures better system identification so that performance improves in case of simultaneous ejection of multiple daughters and also results in better convergence of TA algorithms for single daughter.

The Extended Integrated Particle Filter Method (IPFx) as a High-Performance Earthquake Early Warning System

2021 ◽  
Author(s):  
Masumi Yamada ◽  
Koji Tamaribuchi ◽  
Stephen Wu
Keyword(s):  
Particle Filter ◽  
Early Warning ◽  
Seismic Intensity ◽  
Earthquake Early Warning ◽  
Japan Meteorological Agency ◽  
Estimation Accuracy ◽  
Filter Method ◽  
Source Estimation ◽  
Single Station ◽  
Seismic Networks

ABSTRACT An earthquake early warning (EEW) system rapidly analyzes seismic data to report the occurrence of an earthquake before strong shaking is felt at a site. In Japan, the integrated particle filter (IPF) method, a new source-estimation algorithm, was recently incorporated into the EEW system to improve the source-estimation accuracy during active seismicity. The problem of the current IPF method is that it uses the trigger information computed at each station in a specific format as the input and is therefore applicable to only limited seismic networks. This study proposes the extended IPF (IPFx) method to deal with continuous waveforms and merge all Japanese real-time seismic networks into a single framework. The new source determination algorithm processes seismic waveforms in two stages. The first stage (single-station processing) extracts trigger and amplitude information from continuous waveforms. The second stage (network processing) accumulates information from multiple stations and estimates the location and magnitude of ongoing earthquakes based on Bayesian inference. In 10 months of continuous online experiments, the IPFx method showed good performance in detecting earthquakes with maximum seismic intensity ≥3 in the Japan Meteorological Agency (JMA) catalog. By merging multiple seismic networks into a single EEW system, the warning time of the current EEW system can be improved further. The IPFx method provides accurate shaking estimation even at the beginning of event detection and achieves seismic intensity error <0.25  s after detecting an event. This method correctly avoided two major false alarms on 5 January 2018 and 30 July 2020. The IPFx method offers the potential of expanding the JMA IPF method to global seismic networks.

scholarly journals Engineering selective competitors for the discrimination of highly conserved protein-protein interaction modules

2019 ◽  
Vol 10 (1) ◽  
Author(s):  
Charlotte Rimbault ◽  
Kashyap Maruthi ◽  
Christelle Breillat ◽  
Camille Genuer ◽  
Sara Crespillo ◽  
...  
Keyword(s):  
Protein Interactions ◽  
Pdz Domain ◽  
Specific Inhibitor ◽  
Rational Approach ◽  
Protein Protein Interactions ◽  
Protein Protein Interaction ◽  
Domain Specific ◽  
Postsynaptic Protein ◽  
Protein Interfaces ◽  
Direct Generation

Abstract Designing highly specific modulators of protein-protein interactions (PPIs) is especially challenging in the context of multiple paralogs and conserved interaction surfaces. In this case, direct generation of selective and competitive inhibitors is hindered by high similarity within the evolutionary-related protein interfaces. We report here a strategy that uses a semi-rational approach to separate the modulator design into two functional parts. We first achieve specificity toward a region outside of the interface by using phage display selection coupled with molecular and cellular validation. Highly selective competition is then generated by appending the more degenerate interaction peptide to contact the target interface. We apply this approach to specifically bind a single PDZ domain within the postsynaptic protein PSD-95 over highly similar PDZ domains in PSD-93, SAP-97 and SAP-102. Our work provides a paralog-selective and domain specific inhibitor of PSD-95, and describes a method to efficiently target other conserved PPI modules.

scholarly journals A Comparative Study of Three Improved Algorithms Based on Particle Filter Algorithms in SOC Estimation of Lithium Ion Batteries

Energies ◽  
2017 ◽  
Vol 10 (8) ◽  
pp. 1149 ◽  
Author(s):  
Bizhong Xia ◽  
Zhen Sun ◽  
Ruifeng Zhang ◽  
Deyu Cui ◽  
Zizhou Lao ◽  
...  
Keyword(s):  
Comparative Study ◽  
Particle Filter ◽  
Lithium Ion Batteries ◽  
Lithium Ion ◽  
Soc Estimation ◽  
Filter Algorithms

Ship-Borne Transfer Alignment under Low Maneuver

2012 ◽  
Vol 152-154 ◽  
pp. 1155-1158 ◽  
Author(s):  
Xin Liu ◽  
Bo Wang ◽  
Zhi Hong Deng ◽  
Shun Ting Wang
Keyword(s):  
Dynamic Deformation ◽  
Angular Rate ◽  
Estimation Accuracy ◽  
Sea Waves ◽  
Transfer Alignment ◽  
Large Ship ◽  
Matching Filter ◽  
Simulation Results ◽  
Sea Wave

The transfer alignment processes of the ship-borne weapon and the shipboard aircraft are limited by ship0s maneuver, for large ship, it is hope that the transfer alignment can be executed just under the circumstances of sea wave without any intentional ship0s maneuver. Attitude plus angular rate matching and velocity plus attitude matching as the two possible methods which can give accurate estimations of misalignments between MINS and SINS just under swaying maneuver are studied in this paper. Simulation results show that under the circumstance of sea waves and parameters of ships dynamic deformation, attitude plus angular rate matching filter can give better estimations of misalignment angles than velocity plus attitude matching filter. In addition, the estimation accuracy of attitude plus angular rate matching filter is barely affected by sea condition.

State estimation in bioheat transfer: a comparison of particle filter algorithms

2017 ◽  
Vol 27 (3) ◽  
pp. 615-638 ◽  
Author(s):  
Bernard Lamien ◽  
Leonardo A.B. Varon ◽  
Helcio R.B. Orlande ◽  
Guillermo E. Elicabe
Keyword(s):  
Particle Filter ◽  
State Estimation ◽  
The Body ◽  
Computational Time ◽  
Model Parameters ◽  
Hyperthermia Treatment ◽  
Content Type ◽  
Sampling Importance Resampling ◽  
Importance Resampling ◽  
Filter Algorithms

Purpose The purpose of this paper is to focus on applications related to the hyperthermia treatment of cancer, with heating imposed either by a laser in the near-infrared range or by radiofrequency waves. The particle filter algorithms are compared in terms of computational time and solution accuracy. Design/methodology/approach The authors extend the analyses performed in their previous works to compare three different algorithms of the particle filter, as applied to the hyperthermia treatment of cancer. The particle filters examined here are the sampling importance resampling (SIR) algorithm, the auxiliary sampling importance resampling (ASIR) algorithm and Liu & West’s algorithm. Findings Liu & West’s algorithm resulted in the largest computational times. On the other hand, this filter was shown to be capable of dealing with very large uncertainties. In fact, besides the uncertainties in the model parameters, Gaussian noises, similar to those used for the SIR and ASIR filters, were added to the evolution models for the application of Liu & West’s filter. For the three filters, the estimated temperatures were in excellent agreement with the exact ones. Practical implications This work may help medical doctors in the future to prescribe treatment protocols and also opens the possibility of devising control strategies for the hyperthermia treatment of cancer. Originality/value The natural solution to couple the uncertain results from numerical simulations with the measurements that contain uncertainties, aiming at the better prediction of the temperature field of the tissues inside the body, is to formulate the problem in terms of state estimation, as performed in this work.

scholarly journals A particle-filter framework for robust cryoEM 3D reconstruction

2018 ◽  
Author(s):  
Mingxu Hu ◽  
Hongkun Yu ◽  
Kai Gu ◽  
Kunpeng Wang ◽  
Siyuan Ren ◽  
...  
Keyword(s):  
Parameter Estimation ◽  
Probability Density Function ◽  
Particle Filter ◽  
Probability Density ◽  
Density Function ◽  
Sequential Monte Carlo ◽  
High Dimensional ◽  
Dimensional Parameter ◽  
Support Points ◽  
Estimated Parameters

AbstractElectron cryo-microscopy (cryoEM) is now a powerful tool in determining atomic structures of biological macromolecules under nearly natural conditions. The major task of single-particle cryoEM is to estimate a set of parameters for each input particle image to reconstruct the three-dimensional structure of the macromolecules. As future large-scale applications require increasingly higher resolution and automation, robust high-dimensional parameter estimation algorithms need to be developed in the presence of various image qualities. In this paper, we introduced a particle-filter algorithm for cryoEM, which was a sequential Monte Carlo method for robust and fast high-dimensional parameter estimation. The cryoEM parameter estimation problem was described by a probability density function of the estimated parameters. The particle filter uses a set of random and weighted support points to represent such a probability density function. The statistical properties of the support points not only enhance the parameter estimation with self-adaptive accuracy but also provide the belief of estimated parameters, which is essential for the reconstruction phase. The implementation of these features showed strong tolerance to bad particles and enabled robust defocus refinement, demonstrated by the remarkable resolution improvement at the atomic level.

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