807 research outputs found
The trouble with VAK
No full textDevelopments within education, psychology and the neurosciences have shed a great deal of light on how we learn while, at the same time, confirming for us all that learning is a profoundly complex process and far from understood. Against this background, and in this position paper, we consider the recent rise in interest in the concept of learning styles as VAK (visual, auditory, kinaesthetic) in primary schools in England and Wales and begin to identify and interrogate some of the more bizarre and outrageous claims frequently used to legitimise and lend support to its validity. Through the casual acceptance and promotion of VAK, and its wider association with the notions of accelerated and brain-based learning, the complexity of learning as a whole is becoming increasingly trivialised and scholarship at all levels within certain sectors of the education community compromised
Tactile Feedback for Artery Detection in Minimally Invasive Robotic Surgery –Preliminary Results of a New Approach
No full textMinimally invasive robotic surgery (MIRS) entails
total absence of haptic feedback due to the spatial separation
of patient and surgeon. In conventional surgery, however,
palpation to detect superficial arteries by a slight pulsation is
an important, commonly applied, and security-relevant procedure.
Therefore, an ultrasound based unidirectional sensor for
MIRS was developed feeding back kinesthetic impulses to the
surgeon-sided haptic input device
A Collection of Florida and Georgia Crackers
No full textThis collection of Crackers includes five Florida Crackers, that is, native-born Floridians and a Georgia Cracker. Left to right are Rob Walker, Mr. Keen, John Henry Blackburn, cattleman and author Joe G. Warner and cattleman Hollis Webb in hat and tie. Georgia-born Carl D. King, author of Model-T Days, stands in the rear, 3rd from right
Effect and Improvement Areas for Port State Control Inspections to Decrease the Probability of Casualty
Get PDFThis report is the fourth part of a PhD project called "The Econometrics of Maritime Safety – Recommendations to Enhance Safety at Sea" and is based on 183,000 port state control inspections and 11,700 casualties from various data sources. Its overall objective is to provide recommendations to improve safety at sea. The fourth part looks into measuring the effect of inspections on the probability of casualty on either seriousness or casualty first event to show the differences across the regimes. It further gives a link of casualties that were found during inspections with either the seriousness of casualties and casualty first events which reveals three areas of improvement possibilities to potentially decrease the probability of a casualty – the ISM code, machinery and equipment and ship and cargo operations.maritime safety;correspondence analysis;binary logistic regression;probability of casualty;improvement;Port State Control Effectiveness;casualty first events;detention;port state control deficiences;target factor
Map building fusing acoustic and visual information using autonomous underwater vehicles
Get PDFAuthor Posting. © The Author(s), 2012. This is the author's version of the work. It is posted here by permission of John Wiley & Sons for personal use, not for redistribution. The definitive version was published in Journal of Field Robotics 30 (2013): 763–783, doi:10.1002/rob.21473.We present a system for automatically building 3-D maps of underwater terrain fusing
visual data from a single camera with range data from multibeam sonar. The six-degree
of freedom location of the camera relative to the navigation frame is derived as part of the
mapping process, as are the attitude offsets of the multibeam head and the on-board velocity
sensor. The system uses pose graph optimization and the square root information smoothing
and mapping framework to simultaneously solve for the robot’s trajectory, the map, and
the camera location in the robot’s frame. Matched visual features are treated within the
pose graph as images of 3-D landmarks, while multibeam bathymetry submap matches are
used to impose relative pose constraints linking robot poses from distinct tracklines of the
dive trajectory. The navigation and mapping system presented works under a variety of
deployment scenarios, on robots with diverse sensor suites. Results of using the system to
map the structure and appearance of a section of coral reef are presented using data acquired
by the Seabed autonomous underwater vehicle.The work described herein was funded by the National Science Foundation Censsis ERC under grant number
EEC-9986821, and by the National Oceanic and Atmospheric Administration under grant number
NA090AR4320129
Detection of unanticipated faults for autonomous underwater vehicles using online topic models
Get PDF© The Author(s), 2017. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Journal of Field Robotics 35 (2018): 705-716, doi:10.1002/rob.21771.For robots to succeed in complex missions, they must be reliable in the face of subsystem failures and environmental challenges. In this paper, we focus on autonomous underwater vehicle (AUV) autonomy as it pertains to self‐perception and health monitoring, and we argue that automatic classification of state‐sensor data represents an important enabling capability. We apply an online Bayesian nonparametric topic modeling technique to AUV sensor data in order to automatically characterize its performance patterns, then demonstrate how in combination with operator‐supplied semantic labels these patterns can be used for fault detection and diagnosis by means of a nearest‐neighbor classifier. The method is evaluated using data collected by the Monterey Bay Aquarium Research Institute's Tethys long‐range AUV in three separate field deployments. Our results show that the proposed method is able to accurately identify and characterize patterns that correspond to various states of the AUV, and classify faults at a high rate of correct detection with a very low false detection rate.Office of Naval Research Grant Number: N00014‐14‐1‐0199;
David and Lucile Packard Foundatio
Long-baseline acoustic navigation for under-ice autonomous underwater vehicle operations
No full textAuthor Posting. © The Author(s), 2008. This is the author's version of the work. It is posted here by permission of John Wiley & Sons for personal use, not for redistribution. The definitive version was published in Journal of Field Robotics 25 (2008): 861-879, doi:10.1002/rob.20250.The recent Arctic GAkkel Vents Expedition (AGAVE) to the Arctic Ocean’s Gakkel
Ridge (July/August 2007) aboard the Swedish ice-breaker I/B Oden employed autonomous
underwater vehicles (AUVs) for water-column and ocean bottom surveys.
These surveys were unique among AUV operations to date in requiring georeferenced
navigation in proximity to the seafloor beneath permanent and moving
ice cover. We report results for long-baseline (LBL) acoustic navigation during autonomous
under-ice surveys near the seafloor and adaptation of the LBL concept
for several typical operational situations including navigation in proximity to the
ship during vehicle recoveries. Fixed seafloor transponders were free-fall deployed
from the ship for deep positioning. The ship’s helicopter collected acoustic travel
times from several locations to geo-reference the transponders’ locations, subject
to the availability of openings in the ice. Two shallow beacons suspended from the
ship provided near-surface spherical navigation in ship-relative coordinates. During
routine recoveries, we used this system to navigate the vehicles into open water
near the ship before commanding them to surface. In cases where a vehicle was
impaired, its position was still determined acoustically through some combination
of its acoustic modem, the fixed seafloor transponders, the ship-deployed transponders,
and an on-board backup relay transponder. The techniques employed included
ranging adapted for a moving origin and hyperbolic navigation.Major funding for AGAVE was provided by the National Science Foundation (PP-0425838, ATM-
0428122), the National Aeronautics and Space Administration (Z601701), and the Woods Hole
Oceanographic Institution
Autonomous four-dimensional mapping and tracking of a coastal upwelling front by an autonomous underwater vehicle
Get PDF© The Author(s), 2015. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Journal of Field Robotics 33 (2016): 67-81, doi:10.1002/rob.21617Coastal upwelling is a wind-driven ocean process that brings cooler, saltier, and nutrient-rich deep water upward to the surface. The boundary between the upwelling water and the normally stratified water is called the “upwelling front.” Upwelling fronts support enriched phytoplankton and zooplankton populations, thus they have great influences on ocean ecosystems. Traditional ship-based methods for detecting and sampling ocean fronts are often laborious and very difficult, and long-term tracking of such dynamic features is practically impossible. In our prior work, we developed a method of using an autonomous underwater vehicle (AUV) to autonomously detect an upwelling front and track the front's movement on a fixed latitude, and we applied the method in scientific experiments. In this paper, we present an extension of the method. Each time the AUV crosses and detects the front, the vehicle makes a turn at an oblique angle to recross the front, thus zigzagging through the front to map the frontal zone. The AUV's zigzag tracks alternate in northward and southward sweeps, so as to track the front as it moves over time. This way, the AUV maps and tracks the front in four dimensions—vertical, cross-front, along-front, and time. From May 29 to June 4, 2013, the Tethys long-range AUV ran the algorithm to map and track an upwelling front in Monterey Bay, CA, over five and one-half days. The tracking revealed spatial and temporal variabilities of the upwelling front.This work was supported by the David and Lucile Packard
Foundation
Sharp predictions from eternal inflation patches in D-brane inflation
No full text© 2017 IOP Publishing Ltd and Sissa Medialab srl . We numerically generate the six-dimensional landscape of D3-brane inflation and identify patches of eternal inflation near sufficiently flat inflection points of the potential. We show that reasonable measures that select patches of eternal inflation in the landscape yield sharp predictions for the spectral properties of primordial perturbations on observable scales. These include a scalar tilt of .936, a running of the scalar tilt -.00103, undetectably small tensors and non-Gaussianity, and no observable spatial curvature. Our results explicitly demonstrate that precision cosmology probes the combination of the statistical properties of the string landscape and the measure implied by the universe's quantum state.sponsorship: We thank Tolya Dymarsky, Jonathan Frazer, James Hartle, Rob Speare, Thomas Bachlechner and Matt Kleban for useful discussions. We thank the KITP and the Physics Department at UCSB for their hospitality. The work of TH is supported in part by the Belgian National Science Foundation (FWO) grant G.001.12 Odysseus and by the European Research Council grant no. ERC-2013-CoG 616732 HoloQosmos. (Belgian National Science Foundation (FWO) grant|G.001.12 Odysseus, European Research Council|ERC-2013-CoG 616732 HoloQosmos)status: Publishe
Health human resources planning and the production of health: Development of an extended analytical framework for needs-based health human resources planning.
Get PDFTraditional approaches to health human resources planning emphasize the role of demographic change on the needs for health human resources. Conceptual frameworks have been presented that recognize the limited role of demographic change and the broader determinants of health human resource requirements. Nevertheless, practical applications of health human resources planning continue to base plans on the size and demographic mix of the population applied to simple population-provider or population-utilization ratios. In this paper an analytical framework is developed based on the production of health care services and the multiple determinants of health human resource requirements. In this framework attention is focused on estimating the ‘flow’ of services required to meet the needs of the population that is then translated into the required ‘stock’ of providers to deliver this ‘flow’ of services. The requirements for human resources in the future is shown to depend on four elements: the size and demographic mix of the population (demography), the levels of risks to health and morbidity in the population (epidemiology), the services deemed appropriate to address the levels of risks to health and morbidity (standards of care), and the rate of service delivery by providers (productivity). Application of the framework is illustrated using hypothetical scenarios.health human resources planning, demography, epidemiology, standards of care, productivity
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