<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Paper-Conference |</title><link>http://www.omodolapo.com/publication_types/paper-conference/</link><atom:link href="http://www.omodolapo.com/publication_types/paper-conference/index.xml" rel="self" type="application/rss+xml"/><description>Paper-Conference</description><generator>HugoBlox Kit (https://hugoblox.com)</generator><language>en-us</language><lastBuildDate>Fri, 14 Nov 2025 00:00:00 +0000</lastBuildDate><image><url>http://www.omodolapo.com/media/icon_hu_da05098ef60dc2e7.png</url><title>Paper-Conference</title><link>http://www.omodolapo.com/publication_types/paper-conference/</link></image><item><title>FedRand: A Federated Random Forest Learning Technique for Anomaly Detection in IoT Networks</title><link>http://www.omodolapo.com/publications/2025-babalola-fedrand/</link><pubDate>Fri, 14 Nov 2025 00:00:00 +0000</pubDate><guid>http://www.omodolapo.com/publications/2025-babalola-fedrand/</guid><description/></item></channel></rss>