Dynamic Modelling of Discrete Time Reliability Systems

1996 ◽  
pp. 83-96
Author(s):  
Moshe Shaked ◽  
J. George Shanthikumar ◽  
Jose Benigno Valdez-Torres
Keyword(s):  
Discrete Time ◽  
Dynamic Modelling ◽  
Reliability Systems

A finite-memory discrete-time convolution approach for the nonlinear dynamic modelling of S/H–ADC devices

2003 ◽  
Vol 25 (1) ◽  
pp. 33-44 ◽  
Author(s):  
D. Mirri ◽  
G. Pasini ◽  
P.A. Traverso ◽  
F. Filicori ◽  
G. Iuculano
Keyword(s):  
Discrete Time ◽  
Nonlinear Dynamic ◽  
Dynamic Modelling ◽  
Finite Memory ◽  
Convolution Approach

Multi-State Reliability Systems Under Discrete Time Semi-Markovian Hypothesis

2011 ◽  
Vol 60 (1) ◽  
pp. 80-87 ◽  
Author(s):  
Ourania Chryssaphinou ◽  
Nikolaos Limnios ◽  
Sonia Malefaki
Keyword(s):  
Discrete Time ◽  
Reliability Systems

Dynamic Modelling of a Planar Parallel Robot Manipulator Using the Discrete Time Transfer Matrix Method

2019 ◽  
Author(s):  
Mengqiu Chu ◽  
Guoning Si ◽  
Xuping Zhang ◽  
Haijie Li
Keyword(s):  
Transfer Matrix ◽  
Discrete Time ◽  
Transfer Matrix Method ◽  
Matrix Method ◽  
Parallel Manipulator ◽  
Virtual Work ◽  
Research Effort ◽  
Dynamic Modelling ◽  
Time Transfer ◽  
Simulation Results

Abstract This paper aims to develop a new computationally efficient method for the dynamic modelling of a Planar Parallel Manipulator (PPM) based on the Discrete Time Transfer Matrix Method (DT-TMM). In this preliminary work, we use a 3-PRR PPM as a study case to demonstrate the major procedures and principles of employing the DT-TMM for the dynamic modelling of a PPM. The major focus of this work is to present the basic principles of the DT-TMM for the dynamic modelling of a PPM: decomposing the whole parallel manipulator to the individual components, establishing the dynamics of each component/link, linearizing the component/element dynamics to obtain the transfer matrix of each component/link, and assembling the component dynamics into the system dynamics of the PPM using the transfer matrices of all components/elements. To make the work more readable, the brief introduction of the inverse kinematics and the inverse dynamics is also included. The numerical simulations are conducted based on the 3-PRR PPM with rigid links in this preliminary research effort. The simulation results are compared with those from the model using the principle virtual work method and ADAMS software. The numerical simulation results and comparison demonstrate the effectiveness of the dynamic modelling method using DT-TMM for the PPM.

scholarly journals Vaccination against COVID-19 and society return to normality in England: a modelling study of impacts of different types of naturally acquired and vaccine induced immunity

2021 ◽  
Author(s):  
Fujian Song ◽  
Max O Bachmann
Keyword(s):  
Outcome Measures ◽  
Discrete Time ◽  
Population Dynamic ◽  
Real World ◽  
Vaccine Efficacy ◽  
Dynamic Modelling ◽  
Mass Vaccination ◽  
Cumulative Number ◽  
Different Types ◽  
Induced Immunity

Objectives: To project impacts of mass vaccination against COVID-19, and investigate possible impacts of different types of naturally acquired and vaccine-induced immunity on future dynamics of SARS-CoV-2 transmission from 2021 to 2029 in England. Design: deterministic, discrete-time population dynamic modelling. Participants: Population in England. Interventions: mass vaccination programmes. Outcome measures: daily and cumulative number of deaths from COVID-19. Results: If vaccine efficacy is ≥70%, the vaccine-induced sterilising immunity lasts ≥182 days, and the reinfectivity is greatly reduced (by ≥40%), annual mass vaccination programmes can prevent further COVID-19 outbreaks in England. Under such optimistic scenarios, the cumulative number of COVID-19 deaths is estimated to be from 113,000 to 115,000 by the end of 2029 in England. However, under plausible scenarios with lower vaccine efficacy, shorter durability of immunity, and smaller reduction in reinfectivity, repeated vaccination programmes could not prevent further COVID-19 outbreaks. Conclusions: Under optimistic scenarios, mass immunisation using efficacious vaccines may enable society safely to return to normality. Because of great uncertainty in the impacts of mass vaccination on COVID-19 pandemics, it is crucial to monitor vaccination effects in the real world, and to better understand characteristics of naturally acquired and vaccine induced immunity against SARS-CoV-2.

The Effect of Partly Missing Covariates on Statistical Power in Randomized Controlled Trials With Discrete-Time Survival Endpoints

Methodology ◽  
2017 ◽  
Vol 13 (2) ◽  
pp. 41-60
Author(s):  
Shahab Jolani ◽  
Maryam Safarkhani
Keyword(s):  
Randomized Controlled Trials ◽  
Discrete Time ◽  
Treatment Effect ◽  
Survival Data ◽  
Controlled Trials ◽  
Missing Covariates ◽  
Indicator Method ◽  
Imputation Methods ◽  
Randomized Controlled ◽  
Baseline Covariates

Abstract. In randomized controlled trials (RCTs), a common strategy to increase power to detect a treatment effect is adjustment for baseline covariates. However, adjustment with partly missing covariates, where complete cases are only used, is inefficient. We consider different alternatives in trials with discrete-time survival data, where subjects are measured in discrete-time intervals while they may experience an event at any point in time. The results of a Monte Carlo simulation study, as well as a case study of randomized trials in smokers with attention deficit hyperactivity disorder (ADHD), indicated that single and multiple imputation methods outperform the other methods and increase precision in estimating the treatment effect. Missing indicator method, which uses a dummy variable in the statistical model to indicate whether the value for that variable is missing and sets the same value to all missing values, is comparable to imputation methods. Nevertheless, the power level to detect the treatment effect based on missing indicator method is marginally lower than the imputation methods, particularly when the missingness depends on the outcome. In conclusion, it appears that imputation of partly missing (baseline) covariates should be preferred in the analysis of discrete-time survival data.

Discrete-Time Delay Dynamics of Boundedly Rational Monopoly

2012 ◽  
Author(s):  
Akio Matsumato ◽  
Ferenc Szidarovsky
Keyword(s):  
Time Delay ◽  
Discrete Time ◽  
Discrete Time Delay
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