Navegando por Autor "Silva, Cristiano Maciel da"
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Item An overview of Brazilian working age adults vulnerability to COVID‐19.(2022) Souza, Fernanda Sumika Hojo de; Souza, Natália Satchiko Hojo de; Oliveira, Daniela Carine Ramires de; Silva, Cristiano Maciel da; Guidoni, Daniel LudovicoBrazil is a country of continental dimensions, where many smaller countries would ft. In addition to demographic, socioeconomic, and cultural diferences, hospital infrastructure and healthcare varies across all 27 federative units. Therefore, the evolution of COVID-19 pandemic did not manifest itself in a homogeneous and predictable trend across the nation. In late 2020 and early 2021, new waves of the COVID-19 outbreak have caused an unprecedented sanitary collapse in Brazil. Unlike the frst COVID-19 wave, in subsequent waves, preliminary evidence has pointed to an increase in the daily reported cases among younger people being hospitalized, overloading the healthcare system. In this comprehensive retrospective cohort study, confrmed cases of hospitalization, ICU admission, IMV requirement and in-hospital death from Brazilian COVID-19 patients throughout 2020 until the beginning of 2021 were analyzed through a spatio-temporal study for patients aged 20–59 years. All Brazilian federative units had their data disaggregated in six periods of ten epidemiological weeks each. We found that there is a wide variation in the waves dynamic due to SARS-CoV-2 infection, both in the frst and in subsequent outbreaks in diferent federative units over the analyzed periods. As a result, atypical waves can be seen in the Brazil data as a whole. The analysis showed that Brazil is experiencing a numerical explosion of hospitalizations and deaths for patients aged 20–59 years, especially in the state of São Paulo, with a similar proportion of hospitalizations for this age group but higher proportion of deaths compared to the frst wave.Item Planejando a infraestrutura de comunicação baseada em níveis de serviço para veículos conectados.(2021) Silva, Lucas Diniz; Silva, Cristiano Maciel da; Sarubbi, João Fernando Marchry; Silva, Cristiano Maciel da; Sarubbi, João Fernando Marchry; Souza, Fernanda Sumika Hojo de; Pitangui, Cristiano GrijóO presente trabalho aborda heurísticas computacionais na busca de soluções para a mobilidade da sociedade do século XXI. A Rede Delta é a métrica utilizada para caracterizar o desempenho da rede veicular. A partir dela três estratégias são propostas para realizarem a alocação das unidades de comunicação em uma determinada malha rodoviária. A primeira estratégia opera de forma gulosa, realizando alocações nos locais com o melhor desempenho momentâneo. A segunda estratégia consiste em uma otimização da primeira, evitando ótimos locais. A terceira estratégia utiliza um algoritmo genético com busca local para realizar a alocação. A escolha de alguns parâmetros para a execução do algoritmo genético, bem como os locais mais promissores para a implantação das unidades são estudados ao longo do trabalho. As estratégias propostas foram comparadas com a estratégia intuitiva de se alocar as unidades de comunicação nas áreas de maior tráfego da via. Os resultados mostram que as estratégias conseguem resultados superiores à intuitiva para todos os cenários. As estratégias também são comparadas entre si e os resultados mostram que a segunda e a terceira estratégia conseguem um resultado levemente superior a primeira, o que indica que as decisões gulosas foram bem planejadas, porém não são as melhores.Item Rage : a novel strategy for solving non-polynomial problems through the random generation of solutions and incremental reduction of the number of candidates : a case study applied to the design of the network infrastructure for connected vehicles.(2023) Silva, Cristiano Maciel da; Sarubbi, João Fernando Machry; Mokhtari, Somayeh; Santos, Leonardo Alvarenga Lopes dos; Silva, Lucas Diniz; Souza, Fernanda Sumika Hojo de; Guidoni, Daniel Ludovico; Nogueira, José Marcos SilvaThis work presents RAGE, a novel strategy designed for solving combinatorial optimization problems where we intend to select a subset of elements from a very large set of candidates. For solving the combinatorial problem, RAGE generates a customizable number of random solutions, computes the objective function for each solution, and then scores each candidate element in terms of the value returned by the objective function. After that, RAGE removes a customizable number of candidate elements presenting the smallest score when considering all solutions generated. This cycle is called one iteration. The heuristic loops performing iterations until there are left the exact number of candidates that we are looking for. In order to evaluate the efficiency of RAGE, we perform experiments showing how RAGE behaves when we change the number of random solutions generated per round, and the number of candidate elements removed per round. Finally, we apply RAGE for solving an NP-Hard problem related to the allocation of infrastructure for vehicular communication. The results show that RAGE requires 40,000 evaluations of the objective function to achieve the same result found by the baseline using 175,000 evaluations of the objective function, which, in this case study, represents a drastic reduction of the computational overhead in order to reach the same target.Item A temporal study of Brazilian pregnant and postpartum women vulnerability for COVID-19 : characteristics, risk factors and outcomes.(2022) Souza, Natália Satchiko Hojo de; Guidoni, Daniel Ludovico; Silva, Cristiano Maciel da; Souza, Fernanda Sumika Hojo deBackground During the COVID-19 second wave in Brazil, there has been a significant increase in the number of daily cases and deaths, including pregnant and postpartum women. We assess risk factors and outcomes for this priority group compared to the COVID-19 non-pregnant cohort in two epidemic waves. Methods In this retrospective cohort study we evaluated data of hospitalized pregnant, postpartum, and nonpregnant women aged 15-44 years, between epidemiological weeks 2020−8 and 2021−15, who tested positive for SARSCoV-2, retrieved from the Influenza Epidemiological Surveillance Information System maintained by Ministry of Health of Brazil. We analysed in-hospital case fatality rate, crude and adjusted risk ratios on different outcomes aiming to compare data in two waves. Findings The study included pregnant women (n = 7,132), postpartum women (n = 2,405) and nonpregnant women (n = 76,278) hospitalized with COVID-19. Case fatality rates of pregnant women were lower in both waves compared to nonpregnant women, but higher among postpartum women. The risk for admission to the intensive care unit and invasive mechanical ventilation requirement in both waves was significantly higher among postpartum women compared to nonpregnant women. Cardiac disease, diabetes, obesity, and asthma were the most frequent underlying medical conditions in all patient groups. These comorbidities were significantly less frequent among pregnant women. Interpretation Pregnant women with COVID-19 are at lower risk of poor outcome compared to nonpregnant women. On the other hand, postpartum women are at higher risk of adverse outcomes compared to pregnant and nonpregnant women, especially during the second wave. There was a significant increase in the in-hospital case fatality rate for all patient groups during the second wave of COVID-19.Item Toward an efficient data dissemination protocol for vehicular ad-hoc networks.(2022) Guidoni, Daniel Ludovico; Gottsfritz, Euclydes Nasorri; Meneguette, Rodolfo Ipolito; Silva, Cristiano Maciel da; Rocha Filho, Geraldo Pereira; Souza, Fernanda Sumika Hojo deData Dissemination protocols are used for several vehicular applications, varying from warning messages to real-time video delivery. The majority of literature solutions consider the distance from the sender to choose the vehicle to forward the message. Basically, the solutions introduce a delay in the forwarding procedure, which is inversely proportional to the distance from the sender vehicle. In order to improve the forwarding procedure, this work introduces the concept of Road Covered Area to improve the overall data dissemination process and we describe how to calculate the road covered area by a node transmission. We present the D&RCA, the combination of Distance and Road Covered Area strategies to enhance the re-transmission during communication. Instead of considering the distance, we propose a function to combine the distance and road covered area to introduce a small delay before re-transmissions. We compare the proposed protocol with literature solutions considering the metrics of number of collisions, network coverage and communication latency for different density of vehicles in the network. When the network has 700 vehicles/km2 , the data dissemination latency and number of collisions of the proposed D&RCA is, respectively, 1.24 and 1.32 times smaller than the literature solutions. When we increase the density of vehicles, all evaluated solutions present a network coverage above 90%.