University of Agder

SFI Offshore Mechatronics

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1 to 10 of 391 Results

Replication Data for: Selection against hybrids maintains genetic divergence between populations of a coastal cleaner fish translocated across a genetic break Feb 24, 2026 Blanco Gonzalez, Enrique, 2026, "Replication Data for: Selection against hybrids maintains genetic divergence between populations of a coastal cleaner fish translocated across a genetic break", https://doi.org/10.18710/VPXHVP, DataverseNO, V1 This dataset contains all the information needed to reproduce the analyses performed in the manuscript "Selection against hybrids maintains genetic divergence between populations of a coastal cleaner fish translocated across a genetic break" accepted for publication in Evolutionary Applications.
00_ReadMe.txt Feb 24, 2026 - Replication Data for: Selection against hybrids maintains genetic divergence between populations of a coastal cleaner fish translocated across a genetic break Plain Text - 4.8 KB - MD5: 983da98a3fdee573d87018e73cd2518b Description of the dataset.
Selection_against_hybrid_wrasses_GenotypeData.txt Feb 24, 2026 - Replication Data for: Selection against hybrids maintains genetic divergence between populations of a coastal cleaner fish translocated across a genetic break Plain Text - 69.4 KB - MD5: f79f71b3bdca13bd6dfa4b65ee818a05 A table containing the genotype data saved as three-digit Genepop in txt format
Selection_against_hybrid_wrasses_Morphology.txt Feb 24, 2026 - Replication Data for: Selection against hybrids maintains genetic divergence between populations of a coastal cleaner fish translocated across a genetic break Plain Text - 6.8 KB - MD5: d56925fec42fed48375beaa3e24aaa8c A table containing the morphological data in txt format
Python scripts for Soft Ordering 1-D CNN to Estimate the Capacity Factor of Windfarms for Identifying the Age-Related Performance Degradation. Feb 24, 2026 Mathew, Manuel Sathyajith; Kandukuri, Surya Teja; Omlin, Christian, 2026, "Python scripts for Soft Ordering 1-D CNN to Estimate the Capacity Factor of Windfarms for Identifying the Age-Related Performance Degradation.", https://doi.org/10.18710/LNXUIR, DataverseNO, V1 The supplementary materials provide the complete codebase for the Soft Ordering 1-D Convolutional Neural Network (1-D CNN) model for estimating the capacity factor of wind farms, as presented in "Soft Ordering 1-D CNN to Estimate the Capacity Factor of Windfarms for Identifying the Age-Related Performance Degradation" (PHME 2024). This research was...
00_ReadMe.md Feb 24, 2026 - Python scripts for Soft Ordering 1-D CNN to Estimate the Capacity Factor of Windfarms for Identifying the Age-Related Performance Degradation. Markdown Text - 5.8 KB - MD5: 1100ca3456432e3de7660367408bf319 Description of the dataset.
00_ReadMe.txt Feb 24, 2026 - Python scripts for Soft Ordering 1-D CNN to Estimate the Capacity Factor of Windfarms for Identifying the Age-Related Performance Degradation. Plain Text - 6.5 KB - MD5: e5cab828e3e375849aec71ffd9f6c8a6 Description of the dataset.
main.py Feb 24, 2026 - Python scripts for Soft Ordering 1-D CNN to Estimate the Capacity Factor of Windfarms for Identifying the Age-Related Performance Degradation. Python Source Code - 14.2 KB - MD5: d69365b0d4241ba0018aae90f31927d5 Main script file
model.py Feb 24, 2026 - Python scripts for Soft Ordering 1-D CNN to Estimate the Capacity Factor of Windfarms for Identifying the Age-Related Performance Degradation. Python Source Code - 4.0 KB - MD5: a3d78306f675376e4895213660a14255 Model configuration
preprocess_data.py Feb 24, 2026 - Python scripts for Soft Ordering 1-D CNN to Estimate the Capacity Factor of Windfarms for Identifying the Age-Related Performance Degradation. Python Source Code - 5.2 KB - MD5: e006c550ef9aee497f120f172918073f Data preprocessing

Replication Data for: Selection against hybrids maintains genetic divergence between populations of a coastal cleaner fish translocated across a genetic break

Feb 24, 2026

Blanco Gonzalez, Enrique, 2026, "Replication Data for: Selection against hybrids maintains genetic divergence between populations of a coastal cleaner fish translocated across a genetic break", https://doi.org/10.18710/VPXHVP, DataverseNO, V1

This dataset contains all the information needed to reproduce the analyses performed in the manuscript "Selection against hybrids maintains genetic divergence between populations of a coastal cleaner fish translocated across a genetic break" accepted for publication in Evolutionary Applications.

00_ReadMe.txt

Feb 24, 2026 - Replication Data for: Selection against hybrids maintains genetic divergence between populations of a coastal cleaner fish translocated across a genetic break

Plain Text - 4.8 KB -

Description of the dataset.

Selection_against_hybrid_wrasses_GenotypeData.txt

Feb 24, 2026 - Replication Data for: Selection against hybrids maintains genetic divergence between populations of a coastal cleaner fish translocated across a genetic break

Plain Text - 69.4 KB -

A table containing the genotype data saved as three-digit Genepop in txt format

Selection_against_hybrid_wrasses_Morphology.txt

Feb 24, 2026 - Replication Data for: Selection against hybrids maintains genetic divergence between populations of a coastal cleaner fish translocated across a genetic break

Plain Text - 6.8 KB -

A table containing the morphological data in txt format

Python scripts for Soft Ordering 1-D CNN to Estimate the Capacity Factor of Windfarms for Identifying the Age-Related Performance Degradation.

Feb 24, 2026

Mathew, Manuel Sathyajith; Kandukuri, Surya Teja; Omlin, Christian, 2026, "Python scripts for Soft Ordering 1-D CNN to Estimate the Capacity Factor of Windfarms for Identifying the Age-Related Performance Degradation.", https://doi.org/10.18710/LNXUIR, DataverseNO, V1

The supplementary materials provide the complete codebase for the Soft Ordering 1-D Convolutional Neural Network (1-D CNN) model for estimating the capacity factor of wind farms, as presented in "Soft Ordering 1-D CNN to Estimate the Capacity Factor of Windfarms for Identifying the Age-Related Performance Degradation" (PHME 2024). This research was...

00_ReadMe.md

Feb 24, 2026 - Python scripts for Soft Ordering 1-D CNN to Estimate the Capacity Factor of Windfarms for Identifying the Age-Related Performance Degradation.

Markdown Text - 5.8 KB -

Description of the dataset.

00_ReadMe.txt

Feb 24, 2026 - Python scripts for Soft Ordering 1-D CNN to Estimate the Capacity Factor of Windfarms for Identifying the Age-Related Performance Degradation.

Plain Text - 6.5 KB -

Description of the dataset.

main.py

Feb 24, 2026 - Python scripts for Soft Ordering 1-D CNN to Estimate the Capacity Factor of Windfarms for Identifying the Age-Related Performance Degradation.

Python Source Code - 14.2 KB -

Main script file