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1,091 to 1,100 of 1,206 Results
InterviewsExtracts_OGDUseBR_StatesDF_Dataset.tab
Tab-Delimited - 56.7 KB - MD5: cc32e067943e5f3ba38d6eb73cd86ac8
Extract of interviews about OGD use with Brazilian States and Federal District
Mathematical model for soil bioremediation contaminated by hydrocarbons
Sep 13, 2022 - Centro de Engenharia Biológica
Martins, Gilberto; Campos, Sara; Ferreira, Ana; Castro, Rita; Duarte, Salomé; Cavaleiro, Ana Júlia, 2022, "Mathematical model for soil bioremediation contaminated by hydrocarbons", https://doi.org/10.34622/datarepositorium/2BUM2J, Repositório de Dados da Universidade do Minho, V1
This is a mathematical model developed to assist in the prediction and decision making regarding the in situ bioremediation of hydrocarbon-contaminated soils. The model considered the most relevant processes involved in mass transfer and biodegradation (aerobic, anoxic and anaero...
hydrocarbon soil model_v30_08_2022.aqu
Unknown - 39.3 KB - MD5: 1fe37d127c4996f4d6806b6177651fc3
AQUASIM executable file of the soil model
hydrocarbon soil model_v30_08_2022.prn
Unknown - 67.4 KB - MD5: bc9179fb5b2b00cbbd4b748063651dd3
This file presents the description of all variables, processes, compartments and plots.
Readme.txt
Plain Text - 1.4 KB - MD5: 20a4eaae812bb4b592e5df7223918b80
Readme file describing the steps for model implementation.
MoLa InVicon AR: Dataset for Action Recognition
Jun 14, 2022 - Centro de Investigação Algoritmi
R. P. Rodrigues, Nelson; M. C. da Costa, Nuno; Novais, Rita; Fonseca, Jaime; University of Minho; Borges, Joao, 2022, "MoLa InVicon AR: Dataset for Action Recognition", https://doi.org/10.34622/datarepositorium/WWUTUT, Repositório de Dados da Universidade do Minho, V2
This system is then spatially and temporally calibrated with the camera sensor, automatically obtaining image data with (multi-person) pose annotations (2D and 3D). Finally, we demonstrate the feasibility of using the system’s generated data (which was made publicly available), t...
INVICON.zip.001
Unknown - 1000.0 MB - MD5: 2cbe52e4430f6e0f17199cecaea1f057
INVICON.zip.002
Unknown - 1000.0 MB - MD5: b526f297b0da9d6ee9d051b515c93833
INVICON.zip.003
Unknown - 1000.0 MB - MD5: e41aec42f418bde0a04bfbe18c2701aa
INVICON.zip.004
Unknown - 1000.0 MB - MD5: bde7bf176277823aa5f1d6870648c449
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