scholarly journals A Comparative Study to Find a Suitable Model for an Improved Real-Time Monitoring of The Interventions to Contain COVID-19 Outbreak in The High Incidence States of India

2020 ◽  
Author(s):  
Amrutha G.S ◽  
Abhibhav Sharma ◽  
Anudeepti Sharma
Keyword(s):  
Real Time ◽  
Reproduction Number ◽  
Transmission Rate ◽  
Control Strategies ◽  
Infected Individual ◽  
Time Estimation ◽  
World Health ◽  
Suitable Model ◽  
The Real ◽  
High Incidence

Background On March 11, 2020, The World Health Organization (WHO) declared coronavirus disease (COVID-19) as a global pandemic. There emerged a need for reliable models to estimate the imminent incidence and overall assessment of the outbreak, in order to develop effective interventions and control strategies. One such vital metrics for monitoring the transmission trends over time is the time-dependent effective reproduction number (Rt). Rt is an estimate of secondary cases caused by an infected individual at a time during the outbreak, given that a certain population proportion is already infected. Misestimated Rt is particularly concerning when probing the association between the changes in transmission rate and the changes in the implemented policies. In this paper, we substantiate the implementation of the instantaneous reproduction number (Rins) method over the conventional method to estimate Rt viz case reproduction number (Rcase), by unmasking the real-time estimation ability of both methodologies using credible datasets. Materials & Methods We employed the daily incidence dataset of COVID-19 for India and high incidence states to estimate Rins and Rcase. We compared the real-time projection obtained through these methods by corroborating those states that are containing a high number of COVID19 cases and are conducting high and efficient COVID-19 testing. The Rins and Rcase were estimated using R0 and EpiEstim packages respectively in R software 4.0.0. Results Although, both the Rins and Rcase for the selected states were higher during the lockdown phases (March 25 - June 1, 2020) and subsequently stabilizes co-equally during the unlock phase (June 1- August 23, 2020), Rins demonstrated variations in accordance with the interventions while Rcase remained generalized and under- & overestimated. A larger difference in Rins and Rcase estimates were also observed for states that are conducting high testing. Conclusion Of the two methods, Rins elucidated a better real-time progression of the COVID-19 outbreak conceptually and empirically, than that of Rcase. However, we also suggest considering the assumptions corroborated in the implementations which may result in misleading conclusions in the real world.

scholarly journals Power Hardware-in-the-Loop: Response of Power Components in Real-Time Grid Simulation Environment

Energies ◽  
2021 ◽  
Vol 14 (3) ◽  
pp. 593
Author(s):  
Moiz Muhammad ◽  
Holger Behrends ◽  
Stefan Geißendörfer ◽  
Karsten von Maydell ◽  
Carsten Agert
Keyword(s):  
Real Time ◽  
Power Distribution ◽  
Control Strategies ◽  
Power Grid ◽  
Energy System ◽  
Hardware In The Loop ◽  
Distribution Grid ◽  
Compensation Strategy ◽  
Software Environment ◽  
The Real

With increasing changes in the contemporary energy system, it becomes essential to test the autonomous control strategies for distributed energy resources in a controlled environment to investigate power grid stability. Power hardware-in-the-loop (PHIL) concept is an efficient approach for such evaluations in which a virtually simulated power grid is interfaced to a real hardware device. This strongly coupled software-hardware system introduces obstacles that need attention for smooth operation of the laboratory setup to validate robust control algorithms for decentralized grids. This paper presents a novel methodology and its implementation to develop a test-bench for a real-time PHIL simulation of a typical power distribution grid to study the dynamic behavior of the real power components in connection with the simulated grid. The application of hybrid simulation in a single software environment is realized to model the power grid which obviates the need to simulate the complete grid with a lower discretized sample-time. As an outcome, an environment is established interconnecting the virtual model to the real-world devices. The inaccuracies linked to the power components are examined at length and consequently a suitable compensation strategy is devised to improve the performance of the hardware under test (HUT). Finally, the compensation strategy is also validated through a simulation scenario.

scholarly journals Joint structure for the real-time estimation and control of automotive dry clutch engagement

2018 ◽  
Vol 51 (15) ◽  
pp. 1062-1067 ◽  
Author(s):  
Mojtaba Sharifzadeh ◽  
Mario Pisaturo ◽  
Arash Farnam ◽  
Adolfo Senatore
Keyword(s):  
Real Time ◽  
Time Estimation ◽  
The Real ◽  
Joint Structure ◽  
Clutch Engagement ◽  
Real Time Estimation ◽  
Dry Clutch ◽  
Estimation And Control ◽  
And Control

scholarly journals Early Transmission Dynamics of Novel Coronavirus (COVID-19) in Nigeria

2020 ◽  
Vol 17 (9) ◽  
pp. 3054 ◽  
Author(s):  
Oyelola A. Adegboye ◽  
Adeshina I. Adekunle ◽  
Ezra Gayawan
Keyword(s):  
Doubling Time ◽  
Reproduction Number ◽  
Infected Individual ◽  
Credible Interval ◽  
World Health ◽  
Time Interval ◽  
Serial Interval ◽  
Imported Cases ◽  
Novel Coronavirus ◽  
Health Organization

On 31 December 2019, the World Health Organization (WHO) was notified of a novel coronavirus disease in China that was later named COVID-19. On 11 March 2020, the outbreak of COVID-19 was declared a pandemic. The first instance of the virus in Nigeria was documented on 27 February 2020. This study provides a preliminary epidemiological analysis of the first 45 days of COVID-19 outbreak in Nigeria. We estimated the early transmissibility via time-varying reproduction number based on the Bayesian method that incorporates uncertainty in the distribution of serial interval (time interval between symptoms onset in an infected individual and the infector), and adjusted for disease importation. By 11 April 2020, 318 confirmed cases and 10 deaths from COVID-19 have occurred in Nigeria. At day 45, the exponential growth rate was 0.07 (95% confidence interval (CI): 0.05–0.10) with a doubling time of 9.84 days (95% CI: 7.28–15.18). Separately for imported cases (travel-related) and local cases, the doubling time was 12.88 days and 2.86 days, respectively. Furthermore, we estimated the reproduction number for each day of the outbreak using a three-weekly window while adjusting for imported cases. The estimated reproduction number was 4.98 (95% CrI: 2.65–8.41) at day 22 (19 March 2020), peaking at 5.61 (95% credible interval (CrI): 3.83–7.88) at day 25 (22 March 2020). The median reproduction number over the study period was 2.71 and the latest value on 11 April 2020, was 1.42 (95% CrI: 1.26–1.58). These 45-day estimates suggested that cases of COVID-19 in Nigeria have been remarkably lower than expected and the preparedness to detect needs to be shifted to stop local transmission.

Modeling Technique of Prosthetic Heart Valves

1984 ◽  
Vol 106 (1) ◽  
pp. 83-88 ◽  
Author(s):  
T. Kitamura ◽  
T. Kijima ◽  
H. Akashi
Keyword(s):  
Real Time ◽  
Heart Valves ◽  
Time Estimation ◽  
Modeling Technique ◽  
Computational Time ◽  
Prosthetic Heart Valves ◽  
The Real ◽  
Hemodynamic State ◽  
Real Time Estimation

This paper demonstrates a modeling technique of prosthetic heart valves. In the modeling, a pumping cycle is divided into four phases, in which the state of the valve and flow is different. The pressure-flow relation across the valve is formulated separately in each phase. This technique is developed to build a mathematical model used in the real time estimation of the hemodynamic state under artificial heart pumping. The model built by this technique is simple enough for saving the computational time in the real time estimation. The model is described by the first-order ordinary differential equation with 12 parameters. These parameters can be uniquely determined beforehand from in-vitro experimental data. It is shown that the model can adapt, with sufficient accuracy, to a change in the practical pumping condition and the viscosity of the fluid in their practical range, and is also demonstrated that the estimated backflow volume by model agrees closely with the actual one.

scholarly journals A Mobile Kalman-Filter Based Solution for the Real-Time Estimation of Spatio-Temporal_newline Gait Parameters

2016 ◽  
Vol 24 (7) ◽  
pp. 764-773 ◽  
Author(s):  
Alberto Ferrari ◽  
Pieter Ginis ◽  
Michael Hardegger ◽  
Filippo Casamassima ◽  
Laura Rocchi ◽  
...  
Keyword(s):  
Kalman Filter ◽  
Real Time ◽  
Time Estimation ◽  
The Real ◽  
Gait Parameters ◽  
Real Time Estimation

scholarly journals Hardware-in-the-Loop Operations With an Emulator Rig for SOFC Hybrid Systems

2017 ◽  
Author(s):  
Mario L. Ferrari ◽  
Alessandro Sorce ◽  
Aristide F. Massardo
Keyword(s):  
Fuel Cell ◽  
Real Time ◽  
Hybrid Systems ◽  
Control Strategies ◽  
Experimental Tests ◽  
Outlet Temperature ◽  
Hardware In The Loop ◽  
Set Point ◽  
The Real ◽  
System Components

This paper shows the Hardware-In-the-Loop (HIL) technique developed for the complete emulation of Solid Oxide Fuel Cell (SOFC) based hybrid systems. This approach is based on the coupling of an emulator test rig with a real-time software for components which are not included in the plant. The experimental facility is composed of a T100 microturbine (100 kW electrical power size) modified for the connection to an SOFC emulator device. This component is composed of both anodic and cathodic vessels including also the anodic recirculation system which is carried out with a single stage ejector, driven by an air flow in the primary duct. However, no real stack material was installed in the plant. For this reason, a real-time dynamic software was developed in the Matlab-Simulink environment including all the SOFC system components (the fuel cell stack with the calculation of the electrochemical aspects considering also the real losses, the reformer, and a cathodic recirculation based on a blower, etc.). This tool was coupled with the real system utilizing a User Datagram Protocol (UDP) data exchange approach (the model receives flow data from the plant at the inlet duct of the cathodic vessel, while it is able to operate on the turbine changing its set-point of electrical load or turbine outlet temperature). So, the software is operated to control plant properties to generate the effect of a real SOFC in the rig. In stand-alone mode the turbine load is changed with the objective of matching the measured Turbine Outlet Temperature (TOT) value with the calculated one by the model. In grid-connected mode the software/hardware matching is obtained through a direct manipulation of the TOT set-point. This approach was essential to analyze the matching issues between the SOFC and the micro gas turbine devoting several tests on critical operations, such as start-up, shutdown and load changes. Special attention was focused on tests carried out to solve the control system issues for the entire real hybrid plant emulated with this HIL approach. Hence, the innovative control strategies were developed and successfully tested considering both the Proportional Integral Derivative and advanced approaches. Thanks to the experimental tests carried out with this HIL system, a comparison between different control strategies was performed including a statistic analysis on the results The positive performance obtainable with a Model Predictive Control based technique was shown and discussed. So, the HIL system presented in this paper was essential to perform the experimental tests successfully (for real hybrid system development) without the risks of destroying the stack in case of failures. Mainly surge (especially during transient operations, such as load changes) and other critical conditions (e.g. carbon deposition, high pressure difference between the fuel cell sides, high thermal gradients in the stack, excessive thermal stress in the SOFC system components, etc.) have to be carefully avoided in complete plants.

scholarly journals Global convergence of COVID-19 basic reproduction number and estimation from early-time SIR dynamics

2020 ◽  
Author(s):  
Gabriel G. Katul ◽  
Assaad Mrad ◽  
Sara Bonetti ◽  
Gabriele Manoli ◽  
Anthony J. Parolari
Keyword(s):  
Global Convergence ◽  
Basic Reproduction Number ◽  
Reproduction Number ◽  
Control Strategies ◽  
Early Period ◽  
Early Time ◽  
World Health ◽  
Potential Control ◽  
The Usa ◽  
Early Phases

AbstractThe SIR (‘susceptible-infectious-recovered’) formulation is used to uncover the generic spread mechanisms observed by COVID-19 dynamics globally, especially in the early phases of infectious spread. During this early period, potential controls were not effectively put in place or enforced in many countries. Hence, the early phases of COVID-19 spread in countries where controls were weak offer a unique perspective on the ensemble-behavior of COVID-19 basic reproduction number Ro. The work here shows that there is global convergence (i.e. across many nations) to an uncontrolled Ro = 4.5 that describes the early time spread of COVID-19. This value is in agreement with independent estimates from other sources reviewed here and adds to the growing consensus that the early estimate of Ro = 2.2 adopted by the World Health Organization is low. A reconciliation between power-law and exponential growth predictions is also featured within the confines of the SIR formulation. Implications for evaluating potential control strategies from this uncontrolled Ro are briefly discussed in the context of the maximum possible infected fraction of the population (needed for assessing health care capacity) and mortality (especially in the USA given diverging projections). Model results indicate that if intervention measures still result in Ro> 2.7 within 49 days after first infection, intervention is unlikely to be effective in general for COVID-19. Current optimistic projections place mortality figures in the USA in the range of 100,000 fatalities. For fatalities to be confined to 100,000 requires a reduction in Ro from 4.5 to 2.7 within 17 days of first infection assuming a mortality rate of 3.4%.

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