An Integrated Big and Fast Data Analytics Platform for Smart Urban Transportation Management

(c) 20xx IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.[EN] Smart urban transportation management can be considered as a multifaceted big data challenge. It strongly relies on the information collected into multiple, widespread, and heterogeneous data sources as well as on the ability to extract actionable insights from them. Besides data, full stack (from platform to services and applications) Information and Communications Technology (ICT) solutions need to be specifically adopted to address smart cities challenges. Smart urban transportation management is one of the key use cases addressed in the context of the EUBra-BIGSEA (Europe-Brazil Collaboration of Big Data Scientific Research through Cloud-Centric Applications) project. This paper specifically focuses on the City Administration Dashboard, a public transport analytics application that has been developed on top of the EUBra-BIGSEA platform and used by the Municipality stakeholders of Curitiba, Brazil, to tackle urban traffic data analysis and planning challenges. The solution proposed in this paper joins together a scalable big and fast data analytics platform, a flexible and dynamic cloud infrastructure, data quality and entity matching algorithms as well as security and privacy techniques. By exploiting an interoperable programming framework based on Python Application Programming Interface (API), it allows an easy, rapid and transparent development of smart cities applications.This work was supported by the European Commission through the Cooperation Programme under EUBra-BIGSEA Horizon 2020 Grant [Este projeto e resultante da 3a Chamada Coordenada BR-UE em Tecnologias da Informacao e Comunicacao (TIC), anunciada pelo Ministerio de Ciencia, Tecnologia e Inovacao (MCTI)] under Grant 690116.Fiore, S.; Elia, D.; Pires, CE.; Mestre, DG.; Cappiello, C.; Vitali, M.; Andrade, N.... (2019). An Integrated Big and Fast Data Analytics Platform for Smart Urban Transportation Management. IEEE Access. 7:117652-117677. https://doi.org/10.1109/ACCESS.2019.2936941S117652117677

Uma contribuição aos codigos de treliça periodicamente variante no tempo

Orientador: Reginaldo Palazzo JuniorDissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia EletricaResumo: Neste trabalho são apresentados estudos sobre modulação por codificação em treliça - TCM - periodicamente variantes no tempo superlineares. São verificados os desempenhos de alguns sistemas combinados periodicamente variantes no tempo em termos de ganho asslntótlco de codiflcação e comparados com os sistemas invariantes no tempo que lhes deram origem. Os processos de codificação e descodificação, a obtenção das diversas combinações, a estrutura e características dos códigos TCM periodicamente variantes no tempo são discutidos e uma análise da proteção desigual de conjuntos de bits nestes códigos é apresentada. A análise das vantagens do sistema combinado variante no tempo em relação ao invariante no tempo faz parte das conclusões e sugestões são apresentadas para futuros trabalhos neste temaAbstract: Thls research reports studies on Superlinear Periodically Time Varying Trellis Coded Modulation resulting from an interleavlng approach of Time Invarlant Trellis Coded Modulation. The performance of some of these schemes under the asymtoptlc coding gain as well as comparisons with the previous time invarlant ones are presented. The codlng and decodlng processes, the way the combinations are performed, the structure and characteristics as well as an analysis of the unequal error protection provided by these TCM codes are presented. Finally, the advantages and disadvantages of these new schemes are part of the conclusion as are the suggestions for future researchMestradoMestre em Engenharia Elétric