6 papers · ranked by Valyu relevance
Hadeer Kamal, Amira Y. Haikal, Mahmoud M. Saafan
Traffic collisions and congestion represent significant challenges within intelligent transportation systems (ITS). Consequently, a vehicular ad-hoc network (VANET) has been established. Numerous architectures have been incorporated into VANETs to manage the extensive data generated by vehicles. Collaboration with fog…
Namasi G Sankar, Georgios Miliotis, Simon Caton
Genome assembly is important in infectious disease surveillance, antimicrobial resistance monitoring, and cancer genomics. The task of reconstructing full genomic sequences from fragmented reads, can be framed as a large scale combinatorial optimisation problem. Recent advances in quantum computing have introduced new…
Fabio Cumbo, Kabir Dhillon, M. Hassan Najafi, Sercan Aygun + 1 more
The exponential growth of genomic databases necessitates alignment-free methods for comparing genomes. While MinHash-based tools have revolutionized this field by efficiently estimating the Average Nucleotide Identity based on k-mer sets, they inherently discard structural genomic information. We introduce HyperSketch…
Gyungwon Yun, Jin Pyo Kang, Ho‐Sung Lee, Ik‐Hyeon Jeon + 5 more
Although probabilistic computing offers a route to quantum-inspired optimization at room temperature, existing probabilistic bits (p-bits) often depend on non-CMOS devices or circuit-intensive randomness. Here, we report a CMOS-compatible p-bit that harnesses intrinsic random telegraph noise (RTN) in a fully depleted…
Mohamed Selmy, A. Abdulnabi, A. A. Ali, E. M. Saied + 1 more
Nanogrids have emerged as a crucial solution for contemporary residential power systems, providing a robust framework for integrating distributed energy resources (DERs), comprising solar photovoltaics (PVs), wind turbines (WTs), energy storage systems (ESSs), and diesel generators (DGs). However, the uncertainty of…
Julius F. Witte, Artur Lissin, Isabel Schober, Christian Ebeling + 16 more
The vast amount of existing data on microbial strains holds immense potential to revolutionize bioindustry through the application of Artificial Intelligence (AI). However, the training of robust predictive AI models requires large-scale, unified, and non-redundant microbial datasets, which is currently severely…