ORCID Profile
0000-0003-3439-918X
Current Organisations
Universidade Federal de Minas Gerais
,
Murdoch University
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Publisher: IEEE
Date: 07-2016
Publisher: Elsevier BV
Date: 11-2020
Publisher: Elsevier BV
Date: 11-2023
Publisher: Elsevier BV
Date: 04-2018
Publisher: Springer Science and Business Media LLC
Date: 07-09-2018
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2020
Publisher: Springer Science and Business Media LLC
Date: 16-04-2021
DOI: 10.1038/S41467-021-22607-0
Abstract: Brazil experienced a large dengue virus (DENV) epidemic in 2019, highlighting a continuous struggle with effective control and public health preparedness. Using Oxford Nanopore sequencing, we led field and classroom initiatives for the monitoring of DENV in Brazil, generating 227 novel genome sequences of DENV1-2 from 85 municipalities (2015–2019). This equated to an over 50% increase in the number of DENV genomes from Brazil available in public databases. Using both phylogenetic and epidemiological models we retrospectively reconstructed the recent transmission history of DENV1-2. Phylogenetic analysis revealed complex patterns of transmission, with both lineage co-circulation and replacement. We identified two lineages within the DENV2 BR-4 clade, for which we estimated the effective reproduction number and pattern of seasonality. Overall, the surveillance outputs and training initiative described here serve as a proof-of-concept for the utility of real-time portable sequencing for research and local capacity building in the genomic surveillance of emerging viruses.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2023
Publisher: American Association for the Advancement of Science (AAAS)
Date: 09-2023
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 04-2022
Publisher: SAGE Publications
Date: 09-2016
Abstract: An autonomous underwater vehicle needs to possess a certain degree of autonomy for any particular underwater mission to fulfil the mission objectives successfully and ensure its safety in all stages of the mission in a large-scale operating field. In this article, a novel combinatorial conflict-free task assignment strategy, consisting of an interactive engagement of a local path planner and an adaptive global route planner, is introduced. The method takes advantage of the heuristic search potency of the particle swarm optimization algorithm to address the discrete nature of routing-task assignment approach and the complexity of nondeterministic polynomial-time-hard path planning problem. The proposed hybrid method is highly efficient as a consequence of its reactive guidance framework that guarantees successful completion of missions particularly in cluttered environments. To examine the performance of the method in a context of mission productivity, mission time management, and vehicle safety, a series of simulation studies are undertaken. The results of simulations declare that the proposed method is reliable and robust, particularly in dealing with uncertainties, and it can significantly enhance the level of a vehicle’s autonomy by relying on its reactive nature and capability of providing fast feasible solutions.
Publisher: IEEE
Date: 2011
DOI: 10.1109/ISMS.2011.23
Publisher: Springer Science and Business Media LLC
Date: 18-11-2018
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2023
Publisher: Walter de Gruyter GmbH
Date: 2012
Abstract: Precise control of the stepper motor has always been a topic of interest and also a challenging issue among control engineering researchers due to the nonlinear nature of the motor dynamic. Abrupt influences of the uncertainties on the model’s dynamic and control performance, on the other hand, must be taken into account for providing a control methodology including the characteristics of adaption and flexibility. Lack of these items in most of the classic control approaches results in degradation of the control action. The main purpose of this paper is to provide an intelligent approach for improving the functionality of conventional PID controller in the problem of trajectory tracking in permanent magnet stepper motor (PMSM). Combination of a meta-heuristic algorithm called imperialist competitive algorithm (ICA) and fuzzy logic is employed for online tuning of PID controller. This, consequently, establishes an intelligent structure, fuzzy-PID controller (FPID), which is more flexible and accurate both in certain and uncertain situations. Using a systematic approach in designing the optimal fuzzy structure based on the ICA is our contribution here which leads to better performance of PMSM. Comparing the results of simulations, done in Matlab Simulink, between the suggested control strategy and performance of the PID, expresses the remarkable capability of FPID in overcoming the complexity of control of the nonlinear and uncertain systems.
Publisher: IEEE
Date: 09-2016
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2023
Publisher: SAGE Publications
Date: 22-10-2013
Abstract: This article presents an investigation into the application of a constrained imperialist competitive algorithm with a new penalty function to optimize an adaptive fuzzy proportional–integral–derivative controller for a pneumatic actuator. The integral absolute error and the maximum overshoot of the control system are considered as the cost functions. The constrained imperialist competitive algorithm–based optimization scheme is thus conducted to obtain the best structure of the fuzzy proportional–integral–derivative controller involving optimum shape and location of membership functions and suitable value of scale factors. Then, a simulation study based on the identified model of the pneumatic actuator and three control approaches namely conventional proportional–integral–derivative control, genetic algorithm–based adaptive fuzzy proportional–integral–derivative control and the proposed constrained imperialist competitive algorithm–based adaptive fuzzy proportional–integral–derivative control is carried out to evaluate the performance of the proposed controllers. Finally, an experimental rig is developed to verify the simulation outcomes. It is found that the constrained imperialist competitive algorithm–based fuzzy controller converges faster to an optimum solution compared to the genetic algorithm method. Besides, the superiority of the proposed constrained imperialist competitive algorithm–based design over other controllers is demonstrated.
Publisher: IEEE
Date: 09-2012
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 12-2020
Publisher: Elsevier BV
Date: 06-2017
Publisher: Elsevier BV
Date: 09-2018
No related grants have been discovered for Amirmehdi Yazdani.