Adaptive technique for estimating the parameters of a nonlinear mathematical lung model

1977 ◽  
Vol 15 (2) ◽  
pp. 149-154 ◽  
Author(s):  
M. D. Nada ◽  
D. A. Linkens
Keyword(s):  
Lung Model ◽  
Adaptive Technique

Near Wall Turbulence Effects on Particle Transport and Deposition in Human Tracheobronchial Multi-Level Bifurcation Model

2015 ◽  
Author(s):  
Amir A. Mofakham ◽  
Lin Tian ◽  
Goodarz Ahmadi
Keyword(s):  
Boundary Conditions ◽  
Particle Deposition ◽  
Flow Simulation ◽  
Tracheobronchial Tree ◽  
Lung Model ◽  
Wall Turbulence ◽  
Nano Particles ◽  
Turbulent Regime ◽  
Computationally Efficient ◽  
Multi Level

Transport and deposition of micro and nano-particles in the upper tracheobronchial tree were analyzed using a multi-level asymmetric lung bifurcation model. The multi-level lung model is flexible and computationally efficient by fusing sequence of individual bifurcations with proper boundary conditions. Trachea and the first two generations of the tracheobronchial airway were included in the analysis. In these regions, the airflow is in turbulent regime due to the disturbances induced by the laryngeal jet. Anisotropic Reynolds stress transport turbulence model (RSTM) was used for mean the flow simulation, together with the enhanced two-layer model boundary conditions. Particular attention is given to evaluate the importance of the “quadratic variation of the turbulent fluctuations perpendicular to the wall” on particle deposition in the upper tracheobroncial airways.

Gas exchange during initial stages of N 2 O uptake and elimination in a lung model.

1973 ◽  
Vol 34 (6) ◽  
pp. 775-789 ◽  
Author(s):  
D A Scrimshire ◽  
P J Tomlin
Keyword(s):  
Gas Exchange ◽  
Lung Model

HIGH FREQUENCY PERCUSSIVE VENTILATION CAN MIMIC AIRWAY PRESSURE RELEASE VENTILATION IN A TEST LUNG MODEL

2004 ◽  
Vol 32 (Supplement) ◽  
pp. A38
Author(s):  
Faera L Byerly ◽  
Bruce A Cairns ◽  
Kathy A Short ◽  
John A Haithcock ◽  
Lynn Shapiro ◽  
...  
Keyword(s):  
High Frequency ◽  
Airway Pressure ◽  
Airway Pressure Release Ventilation ◽  
Lung Model ◽  
Test Lung ◽  
Pressure Release ◽  
Pressure Release Ventilation

scholarly journals Augmenting Bug Localization with Part-of-Speech and Invocation

2017 ◽  
Vol 27 (06) ◽  
pp. 925-949 ◽  
Author(s):  
Yu Zhou ◽  
Yanxiang Tong ◽  
Taolue Chen ◽  
Jin Han
Keyword(s):  
Software Maintenance ◽  
Large Scale ◽  
Bug Localization ◽  
Bug Reports ◽  
Part Of Speech ◽  
Adaptive Technique ◽  
Bug Report ◽  
Software Maintenance And Evolution ◽  
Speech Features ◽  
Localization Approach

Bug localization represents one of the most expensive, as well as time-consuming, activities during software maintenance and evolution. To alleviate the workload of developers, numerous methods have been proposed to automate this process and narrow down the scope of reviewing buggy files. In this paper, we present a novel buggy source-file localization approach, using the information from both the bug reports and the source files. We leverage the part-of-speech features of bug reports and the invocation relationship among source files. We also integrate an adaptive technique to further optimize the performance of the approach. The adaptive technique discriminates Top 1 and Top N recommendations for a given bug report and consists of two modules. One module is to maximize the accuracy of the first recommended file, and the other one aims at improving the accuracy of the fixed defect file list. We evaluate our approach on six large-scale open source projects, i.e. ASpectJ, Eclipse, SWT, Zxing, Birt and Tomcat. Compared to the previous work, empirical results show that our approach can improve the overall prediction performance in all of these cases. Particularly, in terms of the Top 1 recommendation accuracy, our approach achieves an enhancement from 22.73% to 39.86% for ASpectJ, from 24.36% to 30.76% for Eclipse, from 31.63% to 46.94% for SWT, from 40% to 55% for ZXing, from 7.97% to 21.99% for Birt, and from 33.37% to 38.90% for Tomcat.

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