IEEE

Optimizing Minimum Spanning Tree Algorithm for Efficient Graph Processing in Big Data

Abstract: Optimizing Minimum Spanning Tree (MST) techniques improve large data graph processing. Developing improved methods to manage large-scale data set computational complexity is the goal. To ...
Frontiers

EEG-based minimum spanning tree analysis reveals network disruptions in Alzheimer’s disease spectrum: an observational study

Introduction: Alzheimer’s disease (AD) is characterized by disrupted brain connectivity, but the network changes across disease stages remain poorly understood. This observational cross-sectional ...
IEEE

Data-Driven Topology Generation with Physics-Guidance in LV Distribution Networks

Abstract: Low-voltage distribution networks (LVDNs) topology is significant for distributed energy resources (DERs) integration, and network operation management, among others. However, topology ...
Frontiers

Deciphering macrophage differentiation and cell death dynamics in heart failure: a single-cell sequencing odyssey

Aims: We hypothesize that specific macrophage differentiation trajectories in heart failure (HF) are coupled with subtype-specific and context-dependent engagement of programmed cell death (PCD) ...
GitHub

step-by-step-animation

Add a description, image, and links to the step-by-step-animation topic page so that developers can more easily learn about it.
C&EN

Chitosan-Based Flocculant Heavy Metal Removal Prediction Using Machine Learning Models

Department of Civil and Environmental Engineering, King Fahd University of Petroleum and Minerals, Dhahran 31261, Saudi Arabia Interdisciplinary Research Center for Membranes and Water Security, King ...