Zobrazeno 1 - 10
of 1 047
pro vyhledávání: '"hilbert curve"'
Publikováno v:
Big Data Mining and Analytics, Vol 7, Iss 3, Pp 668-681 (2024)
Prediction of enhancer-promoter interactions (EPIs) is key to regulating gene expression and diagnosing genetic diseases. Due to limited resolution, biological experiments perform not as well as expected while precisely identifying specific interacti
Externí odkaz:
https://doaj.org/article/0d280fd5822a4394bed6baa6761aba8a
Publikováno v:
Journal of Cheminformatics, Vol 16, Iss 1, Pp 1-25 (2024)
Abstract Motivation Chemical space embedding methods are widely utilized in various research settings for dimensional reduction, clustering and effective visualization. The maps generated by the embedding process can provide valuable insight to medic
Externí odkaz:
https://doaj.org/article/25abc78a00da42f9ab51d45c9c09cc5c
Publikováno v:
IEEE Access, Vol 12, Pp 128179-128186 (2024)
To effectively deal with the complex and changeable network environment and meet the high standard of information transmission security, this paper designs a convenient and efficient image encryption algorithm on the incommensurate fractional-order n
Externí odkaz:
https://doaj.org/article/189cc502238544e7808c668e8bc31570
Publikováno v:
Open Ceramics, Vol 17, Iss , Pp 100509- (2024)
The Hilbert curve fractal pattern was used to create a self-filling structure with designed porosity that would be ideal for applications such as biomedical components, circuit boards, and building materials. 3-Dimensional Hilbert curve structures we
Externí odkaz:
https://doaj.org/article/4ded168fd89b4dc288c7423738c38b31
Publikováno v:
ISPRS International Journal of Geo-Information, Vol 13, Iss 7, p 253 (2024)
The widespread use of Light Detection and Ranging (LiDAR) technology has led to a surge in three-dimensional point cloud data; although, it also poses challenges in terms of data storage and indexing. Efficient storage and management of LiDAR data ar
Externí odkaz:
https://doaj.org/article/703831716f36475a80d2be89a9e3d999
Publikováno v:
Actuators, Vol 13, Iss 7, p 249 (2024)
The research on additive manufacturing (AM) path planning mainly focuses on the traditional three-axis AM path planning and five-degree-of-freedom (DOF) AM path planning, while there is less research on six-DOF AM path planning. In the traditional AM
Externí odkaz:
https://doaj.org/article/c94c775080fb4682b27b11f550620c11
Publikováno v:
ISPRS International Journal of Geo-Information, Vol 13, Iss 3, p 93 (2024)
Yunnan Province, residing in the eastern segment of the Qinghai–Tibet Plateau and the western part of the Yunnan–Guizhou Plateau, faces significant challenges due to its intricate geological structures and frequent geohazards. These pose monument
Externí odkaz:
https://doaj.org/article/fea775937d6f4211b3da52477c236772
Publikováno v:
Friction, Vol 11, Iss 7, Pp 1307-1319 (2022)
Abstract Shallow Hilbert curve patterns with easily programmable texture density were selected for laser texturing of stainless steel substrates. Two different texture path segment lengths (12 and 24 µm) and four different laser power percentages (5
Externí odkaz:
https://doaj.org/article/80945365759545b1838409b89af9403e
Publikováno v:
Journal of Communications Software and Systems, Vol 18, Iss 3, Pp 236-243 (2022)
With the development of communication systems and antennas, various challenges arise that require antennas of small size with enhanced performance. Metamaterials (MTM) defects introduced a considerable solution to such a challenge. Therefore, in this
Externí odkaz:
https://doaj.org/article/2d86a8c02f6648389500146cc7263e0c
Autor:
Camilo Valdes, Vitalii Stebliankin, Daniel Ruiz-Perez, Ji In Park, Hajeong Lee, Giri Narasimhan
Publikováno v:
Frontiers in Bioinformatics, Vol 3 (2023)
Abundance profiles from metagenomic sequencing data synthesize information from billions of sequenced reads coming from thousands of microbial genomes. Analyzing and understanding these profiles can be a challenge since the data they represent are co
Externí odkaz:
https://doaj.org/article/1ac0f57778c14f34ad351acde6704114