Abstract

Abstract
Associated with the exploitation of metallic minerals in Europe during the 20th century, several mining areas were abandoned without adequate environmental intervention. Furthermore, these areas lack studies to characterize the impact of pollution on the hydrogeological system. The area surrounding the tungsten mine of Regoufe, in northern Portugal, is one such area exploited during the Second World War. The accumulation of sulfide-rich tailings may have caused an acid mine drainage (AMD), where the leaching processes caused by seepage water led to soil contamination, evidenced by its acid character and anomalous concentrations of some Potentially Toxic Elements (PTE) reported in previous studies. The present research proposes an innovative approach that seeks the integration of different geophysical techniques to characterize the impact of mining activity on the subsurface. Electrical resistivity (ER) and electromagnetic (EM) were used to measure subsurface electrical properties. In addition, seismic refraction and Multichannel Analysis of Surface Waves (MASW) were performed to characterize the geometry, depth, and geomechanical behavior of the soil and rock bodies. The integration of these techniques allowed the interpretation of hydrogeological sections and a 3D resistivity volume to gain insight into the distribution of potentially contaminating fluids and tailings material present in the mining valley.

Abstract
Special care must be taken when considering robots designed to operate collaboratively, such as a swarm, to prevent these agents from being damaged due to unwanted collisions. This work proposes integrating techniques used to move robots, using the Robot Operating System (ROS) and Python's Scikit-Fuzzy module. Thus, this work developed a fuzzy-controlled collaborative obstacle avoidance system for a type of robot whose dynamics are based on motors' vibration. Thus, these robots were designed to participate in a swarm, and the collision must be avoided. In the search for navigation stability, optimal values were sought for the engines' pulse width modulation (PWM).

Abstract

Abstract

Abstract
Blob features are particularly common in acoustic imagery, as isolated objects (e.g., moorings, mines, rocks) appear as blobs in the acquired images. This work focuses the application of the SIFT, SURF, KAZE and U-SURF feature extraction algorithms for blob feature tracking towards Simultaneous Localization and Mapping applications. We introduce a modified feature extraction and matching pipeline intended to improve feature detection and matching precision, tackling performance deterioration caused by the differences between optical and acoustic imagery. Experimental evaluation was undertaken resorting to datasets collected from a water tank structure.