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 .     

Continuation methods for approximate large scale object sequencing

Machine Learning - We propose a set of highly scalable algorithms for the combinatorial data analysis problem of seriating similarity matrices. Seriation consists of finding a permutation of data...     

Overview of Physical and Chemical,Operational Properties of Nitrous Oxide Used as a Propellant for Low-thrust Rocket Engines

The results of a system analysis of the efficiency of nitrous oxide(N_2O) as a propellant component for small space vehicles(SSV) were presented. A criterion for mass efficiency of the SSV propulsion system(PS) is determined. The current global state-of-the-art of SSV PSs is shown. The application field of nitrous oxide in SSV PSs is calculated and mass efficiency of N_2O application is quantitatively determined. An overview of physical and chemical as well as operational properties of nitrous oxide as a promising, non-toxic component of rocket propellant is provided. Main physical and chemical constants of gaseous and liquid nitrous oxide; chemical properties of N_2O, thermal stability of N_2O, catalytic decomposition of N_2O, a mechanism of decomposition of N_2O, catalysts for decomposition of N_2O, ballast additives to N_2O, application of nitrous oxide, nitrous oxide as a rocket propellant, production of nitrous oxide, toxicity of nitrous oxide, fire hazard of N_2O, requirements to equipment when handling N_2O; storage and transportation of N_2O are considered. It is demonstrated that nitrous oxide is a chemical compound meeting the requirements to rocket propellants, including those related to the environmental friendliness of propellants. With 75 references.     

Parameter estimation for a morphochemical reaction-diffusion model of electrochemical pattern formation

The process of electrodeposition can be described in terms of a reaction-diffusion partial differential equation (PDE) system that models the dynamics of the morphology profile and the chemical composition. Here we fit such a model to the different patterns present in a range of electrodeposited and electrochemically modified alloys using PDE constrained optimization. Experiments with simulated data show how the parameter space of the model can be divided into zones corresponding to the different physical patterns by examining the structure of an appropriate cost function. We then use real data to demonstrate how numerical optimization of the cost function can allow the model to fit the rich variety of patterns arising in experiments. The computational technique developed provides a potential tool for tuning experimental parameters to produce desired patterns.     

Universities through the eyes of bibliographic databases: a retroactive growth comparison of Google Scholar,Scopus and Web of Science

Scientometrics - The purpose of this study is to ascertain the suitability of GS’s url-based method as a valid approximation of universities’ academic output measures, taking into...     

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...