Effects of Undercooling and Transformation Time on Microstructure and Strength of Fe–C–Mn–Si Superbainitic Steel

Strength of Materials - A metallographic method, dilatometry, and X-ray diffraction were applied to investigate the effects of undercooling and holding time on bainitic transformation,...     

Distribution-free uncertainty quantification for kernel methods by gradient perturbations

Machine Learning - We propose a data-driven approach to quantify the uncertainty of models constructed by kernel methods. Our approach minimizes the needed distributional assumptions, hence,...     

A lightweight autonomous MAV for indoor search and rescue

Micro Aerial Vehicles (MAVs) have great potentials to be applied for indoor search and rescue missions. In this paper, we propose a modular lightweight design of an autonomous MAV with integrated hardware and software. The MAV is equipped with the 2D laser scanner, camera, mission computer and flight controller, running all the computation onboard in real time. The onboard perception system includes a laser‐based SLAM module and a custom‐designed visual detection module. A dual Kalman filter design provides robust state estimation by multiple sensor fusion. Specifically, the fusion module provides robust altitude measurement in the circumstance of surface changing. In addition, indoor‐outdoor transition is explicitly handled by the fusion module. In order to efficiently navigate through obstacles and adapt to multiple tasks, a task tree‐based mission planning method is seamlessly integrated with path planning and control modules. The MAV is capable of searching and rescuing victims from unknown indoor environments effectively. It was validated by our award‐winning performance at the 2017 International Micro Air Vehicle Competition (IMAV 2017), held in Toulouse, France. The performance video is available on https://youtu.be/8H19ppS_VXM .     

An effectiveness analysis of altmetrics indices for different levels of artificial intelligence publications

Scientometrics - Altmetrics indices are increasingly applied to measure scholarly influence in recent years because they can reflect the influence of research outputs more timely comparing with...     

The impacts of cattle access points on deposited sediment levels in headwater streams in Ireland

Cattle access to streams has been linked globally with degradation of stream water quality, driven largely by bank erosion and resultant instream, fine sediment deposition. The majority of evidence on such effects is however based in arid and semiarid regions of the United States and Australia, with few studies relating to cool temperate climates such as Northwest Europe. In this study, “Quorer” resuspendable sediment samples were taken from riffle geomorphic units upstream (control) and at two points downstream (pressure and recovery) of cattle access points in headwater streams in agricultural catchments in Ireland to assess levels of deposited stream sediment. Samples were taken in April/May (2016) prior to the grazing season and in October (2016) at the end of the grazing season. Sites in good‐high ecological status catchments and less than good ecological status catchments were included in the study. Higher levels of sediment were found downstream of cattle access points in both good‐high status and less than good status catchments; however, the impacts of access points were spatially confined to, in most cases, the area immediately downstream of the point of access. There was a strong correlation between deposited sediment mass and organic matter (OM) mass, with levels of OM increasing linearly with deposited sediment mass. Levels of measured sediment were negatively correlated with riparian habitat health (measured using a qualitative habitat assessment). The results of this study highlight the need for measures to prevent cattle access to headwater streams where access points can be many in order to manage local habitat quality and downstream water quality issues.     

Context-Based Path Prediction for Targets with Switching Dynamics

International Journal of Computer Vision - Anticipating future situations from streaming sensor data is a key perception challenge for mobile robotics and automated vehicles. We address the problem...