Data stream clustering algorithms have emerged as a pivotal ... where incremental clustering aids in the simplification and relevance evaluation of massive vehicular and sensor data [3].

Anomaly is consistent with interpreted down-dip extension of previously reported anomalous Cu-Au in rock chip sampling (with ...

We also compared it to two popular clustering algorithms and show that this approach is much more efficient. Published in: 2015 2nd IEEE International Conference on Spatial Data Mining and ...

Stream clustering algorithms were introduced to gain useful knowledge from these streams in real-time. The quality of the obtained clusterings, i.e. how good they reflect the data, can be assessed by ...

Result analysis and experimental evaluation ... the-art algorithm 3P-Growth (Kiran et al., 2022b, 2017a) is a two-scan algorithm designed to mine PPPs from temporal static data. However, the ...

AI data centers and Bitcoin mining operations, known for their consistent and heavy energy usage, provide an ideal use case for this surplus. Redirecting idle energy, especially from plants ...

Objective To determine distinct patterns of patients with autoimmune diseases harbouring anti-Ku antibodies and their respective prognosis.Methods Anti-Ku-positive patients were retrieved through four ...

It can also be called “predictive policing”. In our report Automated Racism - How police data and algorithms code discrimination into policing, we exposed how police are using two types of “crime ...