Evaluation of 1D and 2D Deep Convolutional Neural Networks for Driving Event Recognition.

Driving event detection and driver behavior recognition have been widely explored for many purposes, including detecting distractions, classifying driver actions, detecting kidnappings, pricing vehicle insurance, evaluating eco-driving, and managing shared and leased vehicles. Some systems can recognize the main driving events (e.g., accelerating, braking, and turning) by using in-vehicle devices, such as inertial measurement unit (IMU) sensors. In general, feature extraction is a commonly used technique to obtain robust and meaningful information from the sensor signals to guarantee the effectiveness of the subsequent classification algorithm. However, a general assessment of deep neural networks merits further investigation, particularly regarding end-to-end models based on Convolutional Neural Networks (CNNs), which combine two components, namely feature extraction and the classification parts. This paper primarily explores supervised deep-learning models based on 1D and 2D CNNs to classify driving events from the signals of linear acceleration and angular velocity obtained with the IMU sensors of a smartphone placed in the instrument panel of the vehicle. Aggressive and non-aggressive behaviors can be recognized by monitoring driving events, such as accelerating, braking, lane changing, and turning. The experimental results obtained are promising since the best classification model achieved accuracy values of up to 82.40%, and macro- and micro-average F1 scores, respectively, equal to 75.36% and 82.40%, thus, demonstrating high performance in the classification of driving events.

IVIA - Ibero-American VLBI Initiative -Progress on the Brazilian side.

IVIA is a joint initiative of at least 8 Latin-American countries plus Portugal and Spain to make good use of large telecommunications antennas that are out of service in these countries, because most international communications are now using submarine cables. The first step will be to refurbish the antennas and then to start doing single dish observations of radiosources. In a second step the antennas will be equipped with VLBI (Very Long Base Interferometry) equipment, to establish a VLBI network. This project will be able to effectively promote scientific integration in Ibero-America. The work is starting in several countries; here we present several scientific cases for the use of the antennas, and we report on the first Brasilian activities.