A rule-based event detection system for real-life underwater domain

A Domain-independent Rule-based Framework for Event Extraction

We describe the design, development, and API of ODIN (Open Domain INformer), a domainindependent, rule-based event extraction (EE) framework. The proposed EE approach is: simple (most events are captured with simple lexico-syntactic patterns), powerful (the language can capture complex constructs, such as events taking other events as arguments, and regular expressions over syntactic graphs), r...

RUBDES: A Rule Based Distributed Event System

A Wavelet-Based System for Event Detection

Sensors are increasingly being used for continuous monitoring purposes, the process of which generates huge volumes of data that need to be mined for interesting events in realtime. The purpose of this research is to develop a method to identify these events, and to provide users with an architecture that will allow them to analyze events online and in real-time, to act upon them, and to archiv...

Entropy Based Fuzzy Rule Weighting for Hierarchical Intrusion Detection

Predicting different behaviors in computer networks is the subject of many data mining researches. Providing a balanced Intrusion Detection System (IDS) that directly addresses the trade-off between the ability to detect new attack types and providing low false detection rate is a fundamental challenge. Many of the proposed methods perform well in one of the two aspects, and concentrate on a su...

Sound Event Detection for Real Life Audio DCASE Challenge

We explore logistic regression classifier (LogReg) and deep neural network (DNN) on the DCASE 2016 Challenge for task 3, i.e., sound event detection in real life audio. Our models use the Mel Frequency Cepstral Coefficients (MFCCs) and their deltas and accelerations as detection features. The error rate metric favors the simple logistic regression model with high activation threshold on both se...