RN-XCM: A Neural Network for Classifying Skill Level in Multi-Axis Tracking Tasks

The aviation industry's reliance on automation raises concerns about pilot complacency, necessitating continuous pilot proficiency measures. To that end, real-time pilot skill feedback is vital—through alerts on declining skill levels or scalable levels of autonomy. Current cybernetic methods are limited as they assume linearity and time...

Low-Power Gesture Recognition Using Convolutional Neural Networks and Ambient Lighting

This paper presents a study focused on developing an efficient signal processing pipeline and identifying suitable machine learning models for real-time gesture recognition using a testbed consisting of an Arduino Nano 33 BLE and three OPT101 photodiodes. Our research aims to address the challenges of limited computational power whilst...

Dealing with competing requirements surrounding machine learning performance and explainability: Designing a decision support framework for choosing specific machine learning models while dealing with competing model requirements; A case study for the RvIG

For the future demand prediction of identification documents the National Office for Identity Data is interested in a new prediction model based on machine learning techniques. Due to the existence of many different machine learning algorithms and the often competing model requirements regarding model performance and explainability it can be...

Constrained Concealment Attacks against Reconstruction-based Anomaly Detectors in Industrial Control Systems

Recently, reconstruction-based anomaly detection was proposed as an effective technique to detect attacks in dynamic industrial control networks. Unlike classical network anomaly detectors that observe the network traffic, reconstruction-based detectors operate on the measured sensor data, leveraging physical process models learned a priori....

A comparison between artificial neural networks and ARIMA models in traffic forecasting

Motivation: Traffic forecasting is becoming a vital component of our travel experience. It plays a key role in intelligent transportation systems that allow us to make smarter use of existing transportation networks. This study focuses on the possible role of artificial neural networks in these systems and what data can be best feed in to them...

Outlier detection in multivariate time series: Exploiting reconstructions from random projections