The strategy for node and network robust based on graph coloring theory and diversity is introduced first, the graph derived from the algorithm with 35 nodes and 4 coloring plan is analyzed in detail; 4 kinds of benchmark network that usually using are also used for contrastive analyze to the...
Here, we present a graph theory-based analysis of the FRC network in murine lymph nodes, where generation of the network topology is performed using high-resolution confocal microscopy and 3D reconstruction. This approach facilitates the analysis of physical cell-to-cell connectivity, and estimation ...
In this paper, we propose graph attention based network representation (GANR) which utilizes the graph attention architecture and takes graph structure as the supervised learning information. Compared with node classification based representations, GANR can be used to learn representation for any given ...
The mobile anchor node planning path exists the node access repetition,and can not improve the localization accuracy.In order to solve this problem,this paper puts forward Mobile Anchor node Path Planning(MAPP) algorithm,quotes the graph theory knowledge,translates sensor nodes into figure vertices,an...
ClusteringGraph theoryKernel k-meansCommuntiy detectionThis work presents recent developments in graph node distances and tests them empirically on social network databases of various sizes and types. We compare two versions of a distance-based kernel k-m...
With the ongoing advancements in deep learning technology research, an increasing number of studies have emerged that focus on applying deep learning techniques for dynamic network link prediction. Xian et al.15proposed a link prediction model, GraphLP, based on network reconstruction theory, which le...
The kernel performs the underlying I/O operation on the physical device in question (disk, network card, etc.) and replies to the syscall. In the real world, the kernel might have to do a number of things to fulfill your request including waiting for the device to be ready, updating its...
QuickQanavais a C++17 library developed for rendering graphs and relational content within a Qt/QML application. It offers QML components and C++ classes designed for visualizing medium-sized directed graphs in a C++/QML application. QuickQanava emphasizes the presentation of relational content in a...
We introduce GCN and propose an unsupervised deep hashing model NRDH, which treats each image as a node of a graph and utilize GCN to learn the similarity between images. (2) We design a GCN-based AE network, which effectively learns the latent node representation of each image in the uns...
Our backend is usinggrpc-javawithnettywhich as I understand has no specific "max number of streams" setting currently implemented (which was my original theory - requests get stuck in some queue and gradually get aborted). Also the requests are fully unary (not using streaming). ...