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301 to 310 of 37,669 Results
EnSpm_tpase_alignment.treefile
May 6, 2025 - The expanded Bostrychia moritziana genome unveils evolution in the most diverse and complex order of red algae
Unknown - 17.3 KB - MD5: 855a1710018e4d26cf0ec2b181ea435f
Exp_contr_ML_red_algal_phylogeny.tre
May 6, 2025 - The expanded Bostrychia moritziana genome unveils evolution in the most diverse and complex order of red algae
Unknown - 503 B - MD5: e7e628e1f79ebab29b3d61e6d71ade63
Griffithsia_pacifica_blob_GC_masked.fa
May 6, 2025 - The expanded Bostrychia moritziana genome unveils evolution in the most diverse and complex order of red algae
application/x-fasta - 120.4 MB - MD5: 2867fbe2b37dbd9b7d6454c622f0534d
GRIPA_TE_clean_iso.fa
May 6, 2025 - The expanded Bostrychia moritziana genome unveils evolution in the most diverse and complex order of red algae
application/x-fasta - 3.0 MB - MD5: bcc765feb538f8c370bf4deda5675c62
KAPAL_TE_clean_iso.fa
May 6, 2025 - The expanded Bostrychia moritziana genome unveils evolution in the most diverse and complex order of red algae
application/x-fasta - 1.9 MB - MD5: 191a7b902fd2350644d94c4ec555a80b
Manually_curated_proteins.fa
May 6, 2025 - The expanded Bostrychia moritziana genome unveils evolution in the most diverse and complex order of red algae
application/x-fasta - 35.1 KB - MD5: f852c7e8062a4895ca7f94f54bcf1fa8
Manually_curated_repeats.fa
May 6, 2025 - The expanded Bostrychia moritziana genome unveils evolution in the most diverse and complex order of red algae
application/x-fasta - 327.9 KB - MD5: 4ba4e4deaaad53c46e6a334fa3a9a968
TALE_phylogeny_v2.treefile
May 6, 2025 - The expanded Bostrychia moritziana genome unveils evolution in the most diverse and complex order of red algae
Unknown - 10.0 KB - MD5: 4b04e4c6f3d508a00cb98dc0246a4567
Realtime identification of Dispersed Radio signals using ML - A Case Study on the Crab Pulsar
May 5, 2025
Kazantsev, Andrei; Karuppusamy, Ramesh, 2025, "Realtime identification of Dispersed Radio signals using ML - A Case Study on the Crab Pulsar", https://doi.org/10.17617/3.HQYC8O, Edmond, V1
Robust realtime identification of dispersed radio astronomical signals that last much less than a second is challenging. Here we explore the utility of machine learning techniques to identify such signals and use data taken on the Crab pulsar using the Effelsberg 100m Radio Telescope. The data corresponds to the frequency range of 1240-1510 MHz, an...
AAA_README.txt
May 5, 2025 - Realtime identification of Dispersed Radio signals using ML - A Case Study on the Crab Pulsar
Plain Text - 2.0 KB - MD5: c9e5a026a375996def26e79cf1cd026c
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