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Modulation Classification of Underwater Communication with Deep Learning Network.

Computational intelligence and neuroscience
Automatic modulation recognition has successfully used various machine learning methods and achieved certain results. As a subarea of machine learning, deep learning has made great progress in recent years and has made remarkable progress in the fiel...

Early Detection of Depression: Social Network Analysis and Random Forest Techniques.

Journal of medical Internet research
BACKGROUND: Major depressive disorder (MDD) or depression is among the most prevalent psychiatric disorders, affecting more than 300 million people globally. Early detection is critical for rapid intervention, which can potentially reduce the escalat...

Flexible model of network embedding.

Scientific reports
There has lately been increased interest in describing complex systems not merely as single networks but rather as collections of networks that are coupled to one another. We introduce an analytically tractable model that enables one to connect two l...

Automatically Appraising the Credibility of Vaccine-Related Web Pages Shared on Social Media: A Twitter Surveillance Study.

Journal of medical Internet research
BACKGROUND: Tools used to appraise the credibility of health information are time-consuming to apply and require context-specific expertise, limiting their use for quickly identifying and mitigating the spread of misinformation as it emerges.

Network context matters: graph convolutional network model over social networks improves the detection of unknown HIV infections among young men who have sex with men.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: HIV infection risk can be estimated based on not only individual features but also social network information. However, there have been insufficient studies using n machine learning methods that can maximize the utility of such information...

A neural network framework for predicting dynamic variations in heterogeneous social networks.

PloS one
Forecasting possible future relationships between people in a network requires a study of the evolution of their links. To capture network dynamics and temporal variations in link strengths between various types of nodes in a network, a dynamic weigh...

PACC: Large scale connected component computation on Hadoop and Spark.

PloS one
A connected component in a graph is a set of nodes linked to each other by paths. The problem of finding connected components has been applied to diverse graph analysis tasks such as graph partitioning, graph compression, and pattern recognition. Sev...

Artificial neural networks for predicting social comparison effects among female Instagram users.

PloS one
Systematic exposure to social media causes social comparisons, especially among women who compare their image to others; they are particularly vulnerable to mood decrease, self-objectification, body concerns, and lower perception of themselves. This ...

Targeted Bipartite Consensus of Opinion Dynamics in Social Networks With Credibility Intervals.

IEEE transactions on cybernetics
This article investigates the targeted bipartite consensus problem of opinion dynamics in cooperative-antagonistic networks. Each agent in the network is assigned with a convergence set to represent a credibility interval, in which its opinion is tru...