Alternative 2D and 3D Form Characterization Approaches to the Automated Identification of Biological Species

Few have sought to compare the performance of alternative types of morphological data for biological species identification. This investigation contrasts results of form characterization via form factors, superposed landmark coordinates, landmark-registered semilandmark outlines, 3D semilandmark networks, and raw digital images for a test set of seven Recent planktonic foraminifer species. While all data types performed better than the qualitative assessment of morphological variation by human taxonomists, landmark-registered semilandmark outlines and raw digital images delivered the best performance in the context of approaches that could reasonably serve as the basis for fully automated species identification systems

The Causes of Extinction: Setting the Modern Biodiversity Crisis in Context

This talk will delve into the basis of the linkage between the causes of ancient extinctions in the context of the modern biodiversity crisis. With its decidedly biblical overtones, the phenomenon of extinction has intrigued and puzzled religious leaders, philosophers, and scientists for (literally) millennia. If the capacity of humans to effect the environment has reached the intensity level of a major natural process, and this capacity cannot be curtailed over a reasonable time frame, it is disturbing to note that the state of the environment at present is, in many ways, similar to its state just prior to the end-Permian extinction event, which was the largest extinction event in the whole of Earth history and the last time sea level stood as low as it does today.Ohio State University. Mershon Center for International Security Studies.event web page, event photos, MP4 vide

Machining-based coverage path planning for automated structural inspection

The automation of robotically delivered nondestructive evaluation inspection shares many aims with traditional manufacture machining. This paper presents a new hardware and software system for automated thickness mapping of large-scale areas, with multiple obstacles, by employing computer-aided drawing (CAD)/computer-aided manufacturing (CAM)-inspired path planning to implement control of a novel mobile robotic thickness mapping inspection vehicle. A custom postprocessor provides the necessary translation from CAM numeric code through robotic kinematic control to combine and automate the overall process. The generalized steps to implement this approach for any mobile robotic platform are presented herein and applied, in this instance, to a novel thickness mapping crawler. The inspection capabilities of the system were evaluated on an indoor mock-inspection scenario, within a motion tracking cell, to provide quantitative performance figures for positional accuracy. Multiple thickness defects simulating corrosion features on a steel sample plate were combined with obstacles to be avoided during the inspection. A minimum thickness mapping error of 0.21 mm and a mean path error of 4.41 mm were observed for a 2 m² carbon steel sample of 10-mm nominal thickness. The potential of this automated approach has benefits in terms of repeatability of area coverage, obstacle avoidance, and reduced path overlap, all of which directly lead to increased task efficiency and reduced inspection time of large structural assets