Abstract: Clustering is an unsupervised method used to group data points based on their similarity. It has many applications in data mining and preprocessing. Algorithms used for arbitrarily shaped ...
Based Detection, Linguistic Biomarkers, Machine Learning, Explainable AI, Cognitive Decline Monitoring Share and Cite: de Filippis, R. and Al Foysal, A. (2025) Early Alzheimer’s Disease Detection from ...
Abstract: This research work introduces a clustering-based in-place sorting algorithm, cluster sort. It is designed in such a way that it improves sorting efficiency by using data locality. It works ...
ClustSim is a Python program designed to construct simulated single molecule localization microscopy (SMLM) data in 2D or 3D. This implementation is capable of simulating clusters with varying degrees ...
Maharashtra Deputy Chief Minister Eknath Shinde Saturday announced the implementation of Slum Cluster Redevelopment on plots larger than 50 acres in Mumbai. In a statement before the Legislative ...
Nagpur, Dec 13 Maharashtra Deputy Chief Minister and Urban Development and Housing Minister Eknath Shinde on Saturday announced that Slum Cluster Redevelopment will be implemented on plots larger than ...
Organizations deploy a hierarchy of clusters – cameras, private clusters, public clouds – for analyzing live video feeds from their cameras. Video analytics queries have many implementation options ...
KAT is a suite of tools that analyse jellyfish hashes or sequence files (fasta or fastq) using kmer counts. The following tools are currently available in KAT: kmer: Produces a k-mer hash containing ...
Four distinct threat activity clusters have been observed leveraging a malware loader known as CastleLoader, strengthening the previous assessment that the tool is offered to other threat actors under ...
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