Highlights
A modification of SIR model, SIRSi model, was fitted to data of the Covid-19 outbreak.
The model is able to estimate the duration and peaks of the outbreak.
Additionally, the model allows to infer unreported and asymptomatic cases.
The model contains a feedback loop considering different immunity responses.
In this work, the linear feedback limited control strategy is proposed to indicate how the Wolbachia‐infected mosquitoes should be introduced in the seasonal environment to reduce the non‐Wolbachia mosquito population. The numerical simulations show that the proposed strategy reduces the population level of non‐Wolbachia mosquitos, avoiding mosquito spread and, consequently, reducing the number of cases of vector‐borne diseases.
This work discusses the development of a hybrid estimation algorithm based on computer vision and microelectromechanical system sensors. A mathematical enviroment was developed to simulate the dynamics of the quadrotor and its sensors, a 3D simulation software was also developed, simulating a on-board camera. The results obtained were compared to a TRIAD/MEMS attitude and position estimation technique. A fourty times increase in precision was shown, at the cost of five times additional computational processing time.
The outbreak of Covid-19 led the world to an unprecedent health and economical crisis. In an attempt to responde to this emergency researchers worldwide are intensively studying the Covid-19 pandemic dynamics. In this work, a SIRSi compartmental model is proposed, which is a modification of the known classical SIR model. The proposed SIRSi model considers differences in the immunization within a population, and the possibility of unreported or asymptomatic cases. The model is adjusted to three major cities of São Paulo State, in Brazil, namely, São Paulo, Santos and Campinas, providing estimates on the duration and peaks of the outbreak.
This work proposes the computer vision application for the position and attitude estimation of an unmanned aerial vehicle (UAV) quadrotor navigating in an indoor Global Positioning System (GPS) denied environment. The system, composed of the quadrotor and one camera fixed outside the vehicle, was simulated in a 3D virtual environment. The results showed that computer vision improved the attitude and position estimation of the quadrotor.
Synchronization plays an important role in telecommunication systems and integrated circuits. The Master-Slave is a commonly used strategy for clock signal distribution. However, due to the wireless networks development and the higher operation frequency of integrated circuits, the Mutually-Connected clock distribution strategies are becoming important, and the Fully-Connected strategy appears as a convenient engineering solution. The main drawback of the Fully-Connected architecture is the definition of control algorithms that assure the stability of the network sinchronization. In hybrid synchronization techniques groups of nodes synchronized by the Fully-Connected architecture are synchronized with network master clocks by using the Master-Slave tecnique. In this arrangement, if a route of clock signal distribution becomes inoperative, the group of Fully-Connected nodes retain for some time the original phase and frequency received from the network. The Fully-Connected architecture complexity imposes difficulties to satisfy both stability and performance requirements in the control system design. For that reason the multi-variable LQG/LTR and the SDRE control techniques are applied in order to fulfill both stability and performance requirements. The performance of both techniques are compared, and the results seems to confirm the improvement in the transient response and in the precision of the clock distribution process.
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