Comprehensive properties assessment of asphalt binder under aqueous solutions with different pH values and its gradient damage behaviors

This study characterized the morphology, high-temperature property, rheological property, adhesion, cohesion, and chemical component of asphalt binder under aqueous solutions of different pH values. Then the physicochemical properties of asphalt binder were comprehensively evaluated by the improved radar chart. The properties of asphalt...

How do you feel?: Measuring User-Perceived Value for Rejecting Machine Decisions in Hate Speech Detection

Hate speech moderation remains a challenging task for social media platforms. Human-AI collaborative systems offer the potential to combine the strengths of humans' reliability and the scalability of machine learning to tackle this issue effectively. While methods for task handover in human-AI collaboration exist that consider the costs of...

Value- Aware Active Learning

In many practical applications, machine learning models are embedded into a pipeline involving a human actor that decides whether to trust the machine prediction or take a default route (e.g., classify the example herself). Selective classifiers have the option to abstain from making a prediction on an example they do not feel confident about...

Online Iterative Adaptive Dynamic Programming Approach for Solving the Zero-Sum Game for Nonlinear Continuous-Time Systems with Partially Unknown Dynamics

The current study presents an online iterative adaptive dynamic programming approach to resolve the zero-sum game (ZSG) for nonlinear continuous-time (CT) systems containing a partially unknown dynamic. The Hamilton-Jacobian-Issacs (HJI) equation is solved along the state trajectory according to the value function approximation and the policy...

Prior-Guided Deep Interference Mitigation for FMCW Radars

In this article, the interference mitigation (IM) problem is tackled as a regression problem. A prior-guided deep learning (DL)-based IM approach is proposed for frequency-modulated continuous-wave (FMCW) radars. Considering the complex-valued nature of radar signals, a complex-valued convolutional neural network, which is different from the...

Radar-based Human Activities Classification with Complex-valued Neural Networks

Human activities classification in assisted living is one of the emerging applications of radar. The conventional analysis considers micro-Doppler signatures as the chosen input for feature extraction or deep learning classification algorithms, or, less frequently, other radar data formats such as the range-time, the range-Doppler, or the...

Complex-Valued Neural Networks for Radar-based Human-Motion Classification

Nowadays, radar has been applied to human activity classification in the aging-in-place for health monitoring. The complex-valued neural networks (CVNNs) have been only minimally explored, especially on complex-valued radar signals, and there is an outstanding question on whether CVNNs can contribute to improving classification performance. This...