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8,531 to 8,540 of 8,585 Results
displacement_dSine_vxShip_4_vyShip_9.npz
Jun 26, 2026 - Replication Data for: Detecting silent whales using seabed fibre optic cables
Unknown - 21.4 MB - MD5: b6d5b9507b709ff8f40afc042d77d4f3
displacement_dSine_vxShip_8_vyShip_6.npz
Jun 26, 2026 - Replication Data for: Detecting silent whales using seabed fibre optic cables
Unknown - 21.4 MB - MD5: 43c078b23ebbb6c111e52fe7b0edf369
displacement_dSine_vxShip_9_vyShip_1.npz
Jun 26, 2026 - Replication Data for: Detecting silent whales using seabed fibre optic cables
Unknown - 21.4 MB - MD5: 769ee4ec9937cd005e9bed64ccc71cfa
Measurement data for master's thesis: Deploying Latency-Critical VNFs for Resilient Smart Grid Functions in a 5G Edge Cloud Environment
Jul 4, 2026
Grue, Håkon Segrem, 2026, "Measurement data for master's thesis: Deploying Latency-Critical VNFs for Resilient Smart Grid Functions in a 5G Edge Cloud Environment", https://doi.org/10.18710/RIPGIB, DataverseNO, V1
The experiments in this master's thesis were conducted in the Smart Grid Laboratory of SINTEF at NTNU, a detailed explanation is found in chapter 3 of the master's thesis. There were four physical servers in the experimental setup: the PMU-server, PDC-server, srsRAN-server, and Open5GS-server. They were time synchronized using NTP. The PMU-server h...
00_ReadMe.txt
Jul 4, 2026 - Measurement data for master's thesis: Deploying Latency-Critical VNFs for Resilient Smart Grid Functions in a 5G Edge Cloud Environment
Plain Text - 6.1 KB - MD5: 248b02ade61f256a8ab20b067d6c6b00
experimental_results.zip
Jul 4, 2026 - Measurement data for master's thesis: Deploying Latency-Critical VNFs for Resilient Smart Grid Functions in a 5G Edge Cloud Environment
ZIP Archive - 11.4 GB - MD5: 7f0b52f0df69e14d41d2c7b49c5b12ab
isolation_results.zip
Jul 4, 2026 - Measurement data for master's thesis: Deploying Latency-Critical VNFs for Resilient Smart Grid Functions in a 5G Edge Cloud Environment
ZIP Archive - 912.8 MB - MD5: c9c8f6a324f4ba6cb757f6bff6d62f78
Replication Data for: Hyperspectral imaging of seagrass and macroalgae using un-crewed aerial- and surface vehicles for coastal mapping
Jul 6, 2026
Nevstad, Malin Bø, 2026, "Replication Data for: Hyperspectral imaging of seagrass and macroalgae using un-crewed aerial- and surface vehicles for coastal mapping", https://doi.org/10.18710/5PKUTZ, DataverseNO, V1
Hyperspectral imaging data collected of the Remøy southern bay in August-September 2022 for the Seabee research infrastructure project. See the associated publication for more details on field methodology.
00_README.txt
Jul 6, 2026 - Replication Data for: Hyperspectral imaging of seagrass and macroalgae using un-crewed aerial- and surface vehicles for coastal mapping
Plain Text - 10.3 KB - MD5: 6912542148f18464f57032ecefc8e4fc
Accuracy and kappa.csv
Jul 6, 2026 - Replication Data for: Hyperspectral imaging of seagrass and macroalgae using un-crewed aerial- and surface vehicles for coastal mapping
Comma Separated Values - 654 B - MD5: 83bbf768aa187db0019c583fcf07dc81
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