Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Fabrizio F. Borelli"'
Publikováno v:
IEEE Access, Vol 8, Pp 126443-126459 (2020)
Domain-Specific Languages (DSLs) serve a wide variety of purposes in the development of complex applications. The Internet of Things (IoT) brings additional complexity to software development due to its inherent distribution and inclusion of a massiv
Externí odkaz:
https://doaj.org/article/6459b87c148e439785b38a7b9dfbdb02
Publikováno v:
ISCC
2018 IEEE Symposium on Computers and Communications (ISCC)
2018 IEEE Symposium on Computers and Communications (ISCC)
The Internet of Things (IoT) is getting momentum, which drives us to design solutions able to deal with huge amounts of data coming from different sorts of sensors in order to make decisions to adapt system behavior automatically. While in recent yea
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4f5aafc781e0506607ab8efe39fbca72
https://doi.org/10.1109/iscc.2018.8538451
https://doi.org/10.1109/iscc.2018.8538451
Autor:
Ivan Zyrianoff, Fabrizio F. Borelli, Carlos Kamienski, Isaac Pinheiro, Gabriela Biondi, Marc Jentsch
The advent of the Internet of Things (IoT) and its innumerous applications for Smart Cities emphasizes the need for context-aware systems able to adapt behavior automatically to instant environment conditions. Currently, there is a gap in terms of un
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::dcd92a9259448a68e9cff8cfaf9a201e
https://publica.fraunhofer.de/handle/publica/250224
https://publica.fraunhofer.de/handle/publica/250224
Publikováno v:
Anais do Simpósio Brasileiro de Computação Ubíqua e Pervasiva (SBCUP).
Context-Aware Management Systems have been proposed in the last years to perform automatic decision making for the Internet of Things. Although scalability is an indispensable feature for those systems, there are no comprehensive results reporting th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ae83ee1d11f88611a5dc3afb2171b02e
https://doi.org/10.5753/sbcup.2017.3311
https://doi.org/10.5753/sbcup.2017.3311
Autor:
Fabrizio F. Borelli, Ferry Pramudianto, Ivan Zyrianoff, Willian Rosa, Carlos Kamienski, Djamel Sadok, Isaac Pinheiro, Gabriela Biondi
Publikováno v:
WF-IoT
The importance of energy in our society has been growing drastically but still, public buildings are very inefficient when it comes to managing energy. Current management systems are usually designed for automating lighting and HVAC. We see the poten
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::726087d251d00df17982a7fb8f8e8993
https://doi.org/10.1109/wf-iot.2015.7389139
https://doi.org/10.1109/wf-iot.2015.7389139
Autor:
Fabrizio F. Borelli, Luiz C. S. Rozante, David Correa Martins-Jr, Raphael Y. de Camargo, Danilo Carastan-Santos, Siang Wun Song
Publikováno v:
CCGRID
Gene regulatory networks inference is one of the crucial problems of the Systems Biology field. It is still an open problem, mainly because of its high dimensionality (thousands of genes) with a limited number of samples (dozens), making it difficult
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a41c556a6dfc6171931932a2224768f0
https://doi.org/10.1109/ccgrid.2015.29
https://doi.org/10.1109/ccgrid.2015.29
Publikováno v:
BMC Bioinformatics
Background Gene regulatory networks (GRN) inference is an important bioinformatics problem in which the gene interactions need to be deduced from gene expression data, such as microarray data. Feature selection methods can be applied to this problem.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1cceb83f62df26c85cf3e270be8c5d99
https://pubmed.ncbi.nlm.nih.gov/24564268
https://pubmed.ncbi.nlm.nih.gov/24564268
Autor:
Luiz C. S. Rozante, Fabrizio F. Borelli, Beatriz Stransky, David Martins, Raphael Y. de Camargo
Publikováno v:
ICCABS
Gene regulatory networks (GRN) inference is an important bioinformatics problem in which the gene interactions need to be deduced from gene expression data, such as microarray data. Feature selection methods can be applied to this problem. A feature
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6d45bb40adb504ce953e0cf24cb07972
https://doi.org/10.1109/iccabs.2012.6182628
https://doi.org/10.1109/iccabs.2012.6182628