Zobrazeno 1 - 10
of 115
pro vyhledávání: '"Angelo Ciaramella"'
Autor:
Angelo Ciaramella, Emanuel Di Nardo, Daniela Terracciano, Lia Conte, Ferdinando Febbraio, Amelia Cimmino
Publikováno v:
BMC Bioinformatics, Vol 23, Iss S6, Pp 1-16 (2023)
Abstract Background Recent studies have indicated that a special class of long non-coding RNAs (lncRNAs), namely Transcribed-Ultraconservative Regions are transcribed from specific DNA regions (T-UCRs), 100 $$\%$$ % conserved in human, mouse, and rat
Externí odkaz:
https://doaj.org/article/24ec3e0ec7a44ca0b9db2bb5f1271ee7
Autor:
Gaia Mattei, Pietro P. C. Aucelli, Angelo Ciaramella, Luigi De Luca, Alberto Greco, Gennaro Mellone, Francesco Peluso, Salvatore Troisi, Gerardo Pappone
Publikováno v:
Sensors, Vol 24, Iss 4, p 1090 (2024)
The ARGO-USV (Unmanned Surface Vehicle for ARchaeological GeO-application) is a technological project involving a marine drone aimed at devising an innovative methodology for marine geological and geomorphological investigations in shallow areas, usu
Externí odkaz:
https://doaj.org/article/130f0f449a7e42299a537553a6d0d0f6
Power Prediction of a 15,000 TEU Containership: Deep-Learning Algorithm Compared to a Physical Model
Autor:
Alessandro La Ferlita, Yan Qi, Emanuel Di Nardo, Karoline Moenster, Thomas E. Schellin, Ould EL Moctar, Christoph Rasewsky, Angelo Ciaramella
Publikováno v:
Journal of Marine Science and Engineering, Vol 11, Iss 10, p 1854 (2023)
The authors proposed a direct comparison between white- and black-box models to predict the engine brake power of a 15,000 TEU (twenty-foot equivalent unit) containership. A Simplified Naval Architecture Method (SNAM), based on limited operational da
Externí odkaz:
https://doaj.org/article/86d4fb508f8c42afad9a38d5493bbe8b
Autor:
Alessandro La Ferlita, Yan Qi, Emanuel Di Nardo, Ould el Moctar, Thomas E. Schellin, Angelo Ciaramella
Publikováno v:
Journal of Marine Science and Engineering, Vol 11, Iss 4, p 850 (2023)
Two methods were compared to predict a ship’s fuel consumption: the simplified naval architecture method (SNAM) and the deep neural network (DNN) method. The SNAM relied on limited operational data and employed a simplified technique to estimate a
Externí odkaz:
https://doaj.org/article/f9a009283fcd4905bdc6cd62c31961c4
Publikováno v:
BMC Bioinformatics, Vol 21, Iss S10, Pp 1-15 (2020)
Abstract Background High throughput methods, in biological and biomedical fields, acquire a large number of molecular parameters or omics data by a single experiment. Combining these omics data can significantly increase the capability for recovering
Externí odkaz:
https://doaj.org/article/a2a66b9c8d444104b57a862f037c86be
Autor:
Paolo Cazzaniga, Maria Raposo, Daniela Besozzi, Ivan Merelli, Antonino Staiano, Angelo Ciaramella, Riccardo Rizzo, Luca Manzoni
Publikováno v:
BMC Bioinformatics, Vol 22, Iss S2, Pp 1-3 (2021)
Externí odkaz:
https://doaj.org/article/6329ed5e810a40da99281827df891db8
Publikováno v:
PeerJ Computer Science, Vol 6, p e258 (2020)
Record linkage aims to identify records from multiple data sources that refer to the same entity of the real world. It is a well known data quality process studied since the second half of the last century, with an established pipeline and a rich lit
Externí odkaz:
https://doaj.org/article/209ad0ed4f7f42e7ac3d62374a6f089a
Publikováno v:
PeerJ Computer Science, Vol 5, p e237 (2019)
In this work, we propose a novel Feature Selection framework called Sparse-Modeling Based Approach for Class Specific Feature Selection (SMBA-CSFS), that simultaneously exploits the idea of Sparse Modeling and Class-Specific Feature Selection. Featur
Externí odkaz:
https://doaj.org/article/85e8fa3a5e684beca306704699575ce3
Autor:
Angelo Ciaramella, Antonino Staiano
Publikováno v:
Algorithms, Vol 12, Iss 6, p 123 (2019)
As of today, bioinformatics is one of the most exciting fields of scientific research. There is a wide-ranging list of challenging problems to face, i.e., pairwise and multiple alignments, motif detection/discrimination/classification, phylogenetic t
Externí odkaz:
https://doaj.org/article/f59172e91b6d4c52ab9edf306fb928ba
Publikováno v:
Structures, 41, 1220-1234. Elsevier
The seismic analysis of reinforced concrete (RC) structures generally requires significant computational effort, which can be challenging or at least time-consuming also for the modern computing systems. Particularly, huge computational effort is req
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fb4dcc8ea1c786a489debba703770df8
https://doi.org/10.1016/j.istruc.2022.05.008
https://doi.org/10.1016/j.istruc.2022.05.008