Deficiencies of the kinetics order method for the study of thermoluminescence

2007 ◽  
Vol 101 (3) ◽  
pp. 033518 ◽  
Author(s):  
Zheng Xu ◽  
Fujun Zhang ◽  
Suling Zhao ◽  
Liwei Wang ◽  
A. N. Georgobiani ◽  
...  
Keyword(s):  
Order Method ◽  
Kinetics Order

Routing Optimization with Efficient Second Order Distributed Approach Using Congestion Control Rules

2017 ◽  
Vol 7 (7) ◽  
pp. 363
Author(s):  
Jaya Pratha Sebastiyar ◽  
Martin Sahayaraj Joseph
Keyword(s):  
Congestion Control ◽  
Second Order ◽  
Back Pressure ◽  
Order Method ◽  
Delay Performance ◽  
Routing Optimization ◽  
Distributed Approach ◽  
Control Rules ◽  
Primal Dual ◽  
Queue Stability

Distributed joint congestion control and routing optimization has received a significant amount of attention recently. To date, however, most of the existing schemes follow a key idea called the back-pressure algorithm. Despite having many salient features, the first-order sub gradient nature of the back-pressure based schemes results in slow convergence and poor delay performance. To overcome these limitations, the present study was made as first attempt at developing a second-order joint congestion control and routing optimization framework that offers utility-optimality, queue-stability, fast convergence, and low delay.  Contributions in this project are three-fold. The present study propose a new second-order joint congestion control and routing framework based on a primal-dual interior-point approach and established utility-optimality and queue-stability of the proposed second-order method. The results of present study showed that how to implement the proposed second-order method in a distributed fashion.

Stabilization for a class of delayed switched inertial neural networks via non-reduced order method

2021 ◽  
pp. 014233122098594
Author(s):  
Xuan Chen ◽  
Dongyun Lin
Keyword(s):  
Neural Networks ◽  
Comparative Research ◽  
Lyapunov Functional ◽  
Sufficient Conditions ◽  
Global Stabilization ◽  
Order Method ◽  
Reduced Order ◽  
Global Asymptotic Stabilization ◽  
Inertial Neural Networks ◽  
Barbalat Lemma

This paper tackles the issue of global stabilization for a class of delayed switched inertial neural networks (SINN). Distinct from the frequently employed reduced-order technique, this paper studies SINN directly through non-reduced order method. By constructing a novel Lyapunov functional and using Barbalat Lemma, sufficient conditions for the global asymptotic stabilization issue and global exponential stabilization issue of the considered SINN are established. Numerical simulations further confirm the feasibility of the main results. The comparative research shows that global stabilization results of this paper complement and improve some existing work.

A fifth-order method for two-electron integral derivative transformation

1992 ◽  
Vol 196 (6) ◽  
pp. 624-629 ◽  
Author(s):  
Martin Head-Gordon ◽  
Gary W. Trucks ◽  
Michael J. Frisch
Keyword(s):  
Order Method ◽  
Fifth Order

scholarly journals Direct numerical simulation of TS-waves over suction panel steps from manufacturing tolerances

2021 ◽  
Author(s):  
H. Lüdeke ◽  
R. von Soldenhoff
Keyword(s):  
Numerical Simulations ◽  
Linear Stability ◽  
Direct Numerical Simulations ◽  
Linear Stability Theory ◽  
High Fidelity ◽  
Order Method ◽  
Direct Simulation ◽  
High Order Method ◽  
Manufacturing Tolerances ◽  
Tollmien Schlichting

AbstractTo determine allowable tolerances between successive suction panels at hybrid laminar wings with suction surfaces, direct numerical simulations of Tollmien–Schlichting waves over different steps are carried out for realistic suction rates on a wind tunnel configuration. Simulations at given suction panel positions over forward and backward facing steps are carried out by the use of a high-order method for the direct simulation of Tollmien–Schlichting wave growth. Comparisons between high-fidelity direct numerical simulations and quick linear stability calculations have shown capabilities and limits of the well-validated linear stability theory design approach.

scholarly journals Reverse order method for teaching cataract surgery to residents

2019 ◽  
Vol 4 (1) ◽  
pp. e000190
Author(s):  
Gustavo Ricci Malavazzi ◽  
Jonathan Clive Lake ◽  
Eduardo Sone Soriano ◽  
Walton Nose
Keyword(s):  
Cataract Surgery ◽  
New Method ◽  
Reverse Order ◽  
First Year ◽  
Order Method ◽  
Chronological Order ◽  
Posterior Capsule Rupture ◽  
Second Year ◽  
Teaching Modules ◽  
Capsule Rupture

ObjectiveTo implement a method to train residents in the performance of phacoemulsification surgery, with the steps completed in reverse chronological order and with the easiest step being undertaken first.Methods and analysisWe created a method for training ophthalmology residents in which we taught phacoemulsification surgery in a series of steps learnt in reverse order. Each resident advanced through the teaching modules only after being approved in the final step and then progressed to the complete performance of surgeries. We analysed the rates of complications in the 2 years after introducing the new method.ResultsThe new method allowed for a standardised approach that enabled replicated teaching of phacoemulsification regardless of instructor or student. After implementing the new method, residents performed 1817 phacoemulsification surgeries in the first year and 1860 in the second year, with posterior capsule rupture rates of 8.42% and 7.9%, respectively.ConclusionsTeaching residents to perform the steps of phacoemulsification in a standardised reverse order resulted in low rates of complications.

A second-order method for convex1-regularized optimization with active-set prediction

2016 ◽  
Vol 31 (3) ◽  
pp. 605-621 ◽  
Author(s):  
N. Keskar ◽  
J. Nocedal ◽  
F. Öztoprak ◽  
A. Wächter
Keyword(s):  
Second Order ◽  
Order Method ◽  
Active Set ◽  
Regularized Optimization

Theoretical Aspects of a Multidomain High-Order Method for CAA

2003 ◽  
Author(s):  
Ronan Guenanff ◽  
Pierre Sagaut ◽  
Eric Manoha ◽  
Marc Terracol ◽  
Roger Lewandowsky
Keyword(s):  
High Order ◽  
Order Method ◽  
High Order Method
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