scholarly journals Aeroelastic mode decomposition framework and mode selection mechanism in fluid–membrane interaction

2022 ◽  
Vol 108 ◽  
pp. 103428
Author(s):  
Guojun Li ◽  
Rajeev Kumar Jaiman ◽  
Boo Cheong Khoo
Keyword(s):  
Mode Selection ◽  
Selection Mechanism ◽  
Membrane Interaction ◽  
Mode Decomposition ◽  
Fluid Membrane

A Review of Full Eulerian Methods for Fluid Structure Interaction Problems

2011 ◽  
Vol 79 (1) ◽  
Author(s):  
Shu Takagi ◽  
Kazuyasu Sugiyama ◽  
Satoshi Ii ◽  
Yoichiro Matsumoto
Keyword(s):  
Large Deformations ◽  
Temporal Change ◽  
Fluid Flows ◽  
Numerical Approach ◽  
Deformation Tensor ◽  
Membrane Interaction ◽  
Solid Deformation ◽  
Fluid Membrane ◽  
Incompressible Fluid Flows ◽  
Eulerian Methods

We have recently developed a novel numerical method for fluid–solid and fluid–membrane interaction problems. The method is based on a finite difference fractional step technique, corresponding to a standard numerical approach for simulating incompressible fluid flows, and applicable to treating nonlinear constitutive laws of solid/membrane and large deformations. The temporal change of the solid deformation is described in the Eulerian frame by updating the advection equations for a left Cauchy-Green deformation tensor, which is used to express the constitutive equations for materials and membranes. This method is reviewed in detail with some numerical results.

scholarly journals Mode Selection Mechanism in B-Type Pulsators: Observational Clues

2004 ◽  
Vol 193 ◽  
pp. 267-270
Author(s):  
Mikołaj Jerzykiewicz
Keyword(s):  
Mode Selection ◽  
Selection Mechanism ◽  
Clear Cut

AbstractLinear nonadiabatic calculations for models of B-type pulsators predict many more unstable modes than actually observed, therefore a mode selection mechanism must operate in these stars. To investigate this problem quantitatively, available data for singly-periodic and multi-periodic β Cephei variables are compared. No clear-cut differences are found. The slight difference in [m/H], noted recently by Daszyńska et al. (2003), may indicate the solution.

scholarly journals EEG Artifact Removal System for Depression Using a Hybrid Denoising Approach

2021 ◽  
Author(s):  
Chamandeep Kaur ◽  
◽  
Preeti Singh ◽  
Sukhtej Sahni ◽  
◽  
...  
Keyword(s):  
Signal To Noise Ratio ◽  
Wavelet Packet ◽  
Mode Selection ◽  
Classification Performance ◽  
Support Vector ◽  
Fluctuation Analysis ◽  
Analysis Tool ◽  
Denoising Method ◽  
Mode Decomposition ◽  
Mixing Problem

Introduction: A number of computer- aided diagnosis systems for depression are being offered to be used by the clinicians as a method to authorize the diagnosis. EEG may be used as an objective analysis tool for identification of depression in the initial stage so as to avoid it from reaching a severe and permanent state. However, artifact contamination reduces the accuracy in EEG signal processing systems. Methods: This work proposes a novel denoising method based on EMD (Empirical Mode Decomposition) with detrended fluctuation analysis (DFA) and wavelet packet transform. As the first stage, real EEG recordings corresponding to depression patients are decomposed into various mode functions by applying EMD. Then, DFA is used as the mode selection criteria. Further wavelet packets decomposition (WPD) based evaluation is used to extract the cleaner signal. Results: Simulations have been carried out on real EEG databases for depression to demonstrate the effectiveness of the proposed techniques. To conclude the efficacy of the proposed technique, SNR and MAE have been identified. The results show improved signal to noise ratio and lower values of MAE for the combined EMD-DFA-WPD technique. Also, Random Forest and SVM (Support Vector Machine) based classification shows improved accuracy of 98.51% and 98.10% for the proposed denoising technique. Whereas the accuracy of the EMD- DFA is 98.01% and 95.81% and EMD combined with DWT technique is 98.0% and 97.21% for the EMD- DFA technique for RF and SVM respectively as compared to the proposed method. Also, the classification performance for both the classifiers has been compared with and without denoising to highlight the effectiveness of the proposed technique. Conclusion: Proposed denoising system results in better classification of depressed and healthy individuals resulting in better diagnosing system. These results can be further analyzed using other approaches as a solution to the mode mixing problem of EMD approach.

Modeling and computation of fluid–membrane interaction

2009 ◽  
Vol 71 (12) ◽  
pp. e1553-e1559
Author(s):  
Masaki Kazama ◽  
Seiro Omata
Keyword(s):  
Membrane Interaction ◽  
Fluid Membrane

scholarly journals A VARIATIONAL MODE DECOMPOSITION BASED APPROACH FOR CARDIOPULMONARY RESUSCITATION ESTIMATION AND ASSESSMENT

2019 ◽  
Vol 57 (1) ◽  
pp. 92
Author(s):  
Tran Thi Thao ◽  
Pham Van Truong
Keyword(s):  
Cardiopulmonary Resuscitation ◽  
Mode Selection ◽  
Pulseless Electrical Activity ◽  
Thoracic Impedance ◽  
Variational Mode Decomposition ◽  
Mode Decomposition ◽  
Cpr Quality ◽  
Key Steps ◽  
Causes Of Deaths ◽  
Key Indicators

Cardiac arrests remain leading causes of deaths for thousands of people annually. One of the most common methods for cardiac arrest treatment is cardiopulmonary resuscitation (CPR) that provides chest compressions. It has been shown that the quality of chest compression is considered as one of key indicators for assessment of CPR performance. In this paper, we present an approach for CPR quality evaluation using ECG contaminated with CPR artifact and thoracic impedance. The proposed approach contains two key steps: First, the CPR artifact signal is estimated via variational mode decomposition (VMD) and a mode selection algorithm based on mode’s frequency and frequency of thoracic impedance signal. In the second step, CPR parameters performed on the estimated CPR signals are computed and compared with those derived by reference CPR. The proposed approach is applied for a dataset including patients presenting with asystole, ventricular tachycardia, and pulseless electrical activity. Quantitative results validate the performance of the proposed approach for CPR quality assessment.

scholarly journals Mode selection mechanism in traveling and standing waves revealed by Min wave reconstituted in artificial cells

2022 ◽  
Author(s):  
Sakura Takada ◽  
Natsuhiko Yoshinaga ◽  
Nobuhide Doi ◽  
Kei Fujiwara
Keyword(s):  
Mode Selection ◽  
Standing Waves ◽  
Reaction Diffusion ◽  
Wave Mode ◽  
Spatiotemporal Pattern ◽  
Selection Mechanism ◽  
Artificial Cells ◽  
Pattern Formations ◽  
Selection Of ◽  
Wave Modes

Reaction-diffusion coupling (RDc) generates spatiotemporal patterns, including two dynamic wave modes: traveling and standing waves. Although mode selection plays a significant role in the spatiotemporal organization of living cell molecules, the mechanism for selecting each wave mode remains elusive. Here, we investigated a wave mode selection mechanism using Min waves reconstituted in artificial cells, emerged by the RDc of MinD and MinE. Our experiments and theoretical analysis revealed that the balance of membrane binding and dissociation from the membrane of MinD determines the mode selection of the Min wave. We successfully demonstrated that the transition of the wave modes can be regulated by controlling this balance and found hysteresis characteristics in the wave mode transition. These findings highlight a novel role of the balance between activators and inhibitors as a determinant of the mode selection of waves by RDc and depict a novel mechanism in intracellular spatiotemporal pattern formations.

Novel mode-selection mechanism for realizing a live MPEG-4 ASP encoder

2005 ◽  
Author(s):  
Sung-Wen Wang ◽  
Yi-Shin Tung ◽  
Hsien-Shuo Chen ◽  
Ja-Ling Wu ◽  
Sheng-Ho Wang
Keyword(s):  
Mode Selection ◽  
Selection Mechanism
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