C++ implementations for analyzing sets, graph paths, and functions, using OOP and DSA principles and menu-driven interfaces. - Ehmad-7/Sets-Graphs-Functions-Analysis ...

Recent developments in the quantitative analysis of complex networks, based largely on graph theory, have been rapidly translated to studies of brain network organization. The brain's structural ...

Gap analysis starts with the identification of gaps. In small businesses, accounting is often inefficient, so you might want to analyze that function. To find functional gaps, you have to clearly ...

Functional Magnetic Resonance Imaging (fMRI) is an imaging technique that allows to explore brain function in vivo. Many methods dedicated to analyzing these data are based on graph modeling, each ...

For weighted graphs, the edge eij has a real value. If G is an unweighted graph, then E is a sparse matrix with elements of either 0 or 1. When analyzing the fMRI data, the functional connectivity ...

GCSE CCEA Double Award Analysing experimental data (CCEA) Graph Find out how you can analyse, interpret and critically evaluate a range of experimental data. Part of Combined Science Practical skills ...

Analyzing functional connectivity patterns from resting-state functional magnetic resonance imaging (fMRI) requires unraveling its interrelations across spatial, temporal, and frequency domains. To ...

Analysing text reuse is a task that is of particular relevance to architectural history. The new platform Graph automates this process by applying large-scale textual processing for detecting similar ...

Graph Neural Networks (GNNs) are commonly used for functional connectivity analysis but are often limited by predefined graph structures and fixed thresholding strategies. In densely connected graphs, ...