3,441 to 3,450 of 3,851 Results
Oct 9, 2023 -
Microbiology, physicochemical and structural data of goat and sheep cheese whey samples added with sugar and pectin
Tabular Data - 2.6 KB - 18 Variables, 24 Observations - UNF:6:Ag2Vsl/tjNynewPw/tOoLA==
Microbiology, physicochemical and structural data of goat and sheep cheese whey samples added with sugar and pectin |
Oct 9, 2023
Tribst, Alline Artigiani Lima; Martins Filho, Cesar Melo, 2023, "NIR backscattering and particle size of goat and sheep cheese whey samples after thermal treatment and acidification or fermentation", https://doi.org/10.25824/redu/9HCUK5, Repositório de Dados de Pesquisa da Unicamp, V1, UNF:6:DN/gB/8lMv+Z7CcyNf512g== [fileUNF]
These data refer to characterization of sheep and goat cheese whey pasteurized at different binomials and acidified (pH 5.5-2.5) or fermented (with or without Alcalase). Results includes particle size distribution and NIR-backscattering measured during storage at 4ºC (28 days) |
Tabular Data - 2.3 KB - 11 Variables, 23 Observations - UNF:6:DN/gB/8lMv+Z7CcyNf512g==
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Oct 4, 2023
Toledo, Gabriela Pereira; Mazza, Ricardo Augusto, 2023, "Experimental database of air-water slug flow in a long vertical pipe", https://doi.org/10.25824/redu/XJ05CB, Repositório de Dados de Pesquisa da Unicamp, V1
Experimental data for air-water slug flow in a long vertical pipe. It contains data for bubble and liquid slug lengths, bubble and liquid slug velocities, frequency, pressure and pressure gradient, and volumetric void fraction. Both raw and processed data are available. |
RAR Archive - 704.6 MB -
MD5: f433c739362def50a6edfa4c2471c854
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Sep 26, 2023
Nazatto, Thales Eduardo; Rubira, Cecília Mary Fischer, 2023, "Replication data for: A semi-autonomic framework for developing machine learning-based applications using fairness metrics", https://doi.org/10.25824/redu/QO3CGG, Repositório de Dados de Pesquisa da Unicamp, V1, UNF:6:AKrwwHRJZHgVPGKAxY7QvQ== [fileUNF]
This research proposes a presents a semi-autonomous framework to train machine learning models that identifies more optimized configurations across different contexts. Several case studies were conducted to determine the feasibility and extensibility of the proposed framework. Th... |
Sep 26, 2023 -
Replication data for: A semi-autonomic framework for developing machine learning-based applications using fairness metrics
Tabular Data - 5.9 MB - 15 Variables, 48842 Observations - UNF:6:OHfKRD3JlsvMnf3iK3R/CA==
Adult Income Dataset |
Sep 26, 2023 -
Replication data for: A semi-autonomic framework for developing machine learning-based applications using fairness metrics
RAR Archive - 459.0 KB -
MD5: 2d283c56971c459d10911f31488c8b02
Codes used to count lines on case studies 2 and 3 |
Sep 26, 2023 -
Replication data for: A semi-autonomic framework for developing machine learning-based applications using fairness metrics
RAR Archive - 37.6 KB -
MD5: 4e4b84e25d2b9887f3359e12d504b062
System configuration files used in each experiment |
Sep 26, 2023 -
Replication data for: A semi-autonomic framework for developing machine learning-based applications using fairness metrics
Unknown - 79.2 KB -
MD5: 7747fc3ebd57a0f879ec58841ee33286
German Credit Dataset, used in case study 1 |
