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"Ray, John"
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Detection of Informal Settlements from VHR Images Using Convolutional Neural Networks
Information about the location and extent of informal settlements is necessary to guide decision making and resource allocation for their upgrading. Very high resolution (VHR) satellite images can provide this useful information, however, different urban settlement types are hard to be automatically discriminated and extracted from VHR imagery, because of their abstract semantic class definition. State-of-the-art classification techniques rely on hand-engineering spatial-contextual features to improve the classification results of pixel-based methods. In this paper, we propose to use convolutional neural networks (CNNs) for learning discriminative spatial features, and perform automatic detection of informal settlements. The experimental analysis is carried out on a QuickBird image acquired over Dar es Salaam, Tanzania. The proposed technique is compared against support vector machines (SVMs) using texture features extracted from grey level co-occurrence matrix (GLCM) and local binary patterns (LBP), which result in accuracies of 86.65% and 90.48%, respectively. CNN leads to better classification, resulting in an overall accuracy of 91.71%. A sensitivity analysis shows that deeper networks result in higher accuracies when large training sets are used. The study concludes that training CNN in an end-to-end fashion can automatically learn spatial features from the data that are capable of discriminating complex urban land use classes.
Journal Article
UnDER: Unsupervised Dense Point Cloud Extraction Routine for UAV Imagery Using Deep Learning
Extraction of dense 3D geographic information from ultra-high-resolution unmanned aerial vehicle (UAV) imagery unlocks a great number of mapping and monitoring applications. This is facilitated by a step called dense image matching, which tries to find pixels corresponding to the same object within overlapping images captured by the UAV from different locations. Recent developments in deep learning utilize deep convolutional networks to perform this dense pixel correspondence task. A common theme in these developments is to train the network in a supervised setting using available dense 3D reference datasets. However, in this work we propose a novel unsupervised dense point cloud extraction routine for UAV imagery, called UnDER. We propose a novel disparity-shifting procedure to enable the use of a stereo matching network pretrained on an entirely different typology of image data in the disparity-estimation step of UnDER. Unlike previously proposed disparity-shifting techniques for forming cost volumes, the goal of our procedure was to address the domain shift between the images that the network was pretrained on and the UAV images, by using prior information from the UAV image acquisition. We also developed a procedure for occlusion masking based on disparity consistency checking that uses the disparity image space rather than the object space proposed in a standard 3D reconstruction routine for UAV data. Our benchmarking results demonstrated significant improvements in quantitative performance, reducing the mean cloud-to-cloud distance by approximately 1.8 times the ground sampling distance (GSD) compared to other methods.
Journal Article
Cancâun, Cozumel & the Yucatâan
Provides information on accommodations, restaurants, shopping, entertainment, and outdoor activities, along with suggested itineraries and an overview of the history and culture of the region.
Book
Choosing emergency medicine: Influences on medical students’ choice of emergency medicine
Relatively little is understood about which factors influence students' choice of specialty and when learners ultimately make this decision.
The objective is to understand how experiences of medical students relate to the timing of selection of Emergency Medicine (EM) as a specialty. Of specific interest were factors such as how earlier and more positive specialty exposure may impact the decision-making process of medical students.
A cross-sectional survey study of EM bound 4th year US medical students (MD and DO) was performed exploring when and why students choose EM as their specialty. An electronic survey was distributed in March 2015 to all medical students who applied to an EM residency at 4 programs representing different geographical regions. Descriptive analyses and multinomial logistic regressions were performed.
793/1372 (58%) responded. Over half had EM experience prior to medical school. When students selected EM varied: 13.9% prior to, 50.4% during, and 35.7% after their M3 year. Early exposure, presence of an EM residency program, previous employment in the ED, experience as a pre-hospital provider, and completion of an M3 EM clerkship were associated with earlier selection. Delayed exposure to EM was associated with later selection of EM.
Early exposure and prior life experiences were associated with choosing EM earlier in medical school. The third year was identified as the most common time for definitively choosing the specialty.
Journal Article
Batman : Troika
\"For the first time since the events of the Knightfall storyline, Bruce Wayne returns to his role as Gotham City's protector, Batman! The Knightfall Saga reaches its conclusion as Bruce Wayne returns to Gotham City in the never-before-collected Batman: Troika! A new era begins, as Batman reinvents himself to take on a new breed of foe. When the Bat-Family declares war against former KGB operatives with plans to take control of Gotham City's underworld, who will come out the victor? In the midst of all of this, Bruce Wayne must also cope with his decision to pass on the mantle of Batman to Jean-Paul Valley\"-- Provided by publisher.
Book
Chitosan as a Biomaterial: Influence of Degree of Deacetylation on Its Physiochemical, Material and Biological Properties
Chitosan is a biomaterial with a range of current and potential biomedical applications. Manipulation of chitosan degree of deacetylation (DDA) to achieve specific properties appears feasible, but studies investigating its influence on properties are often contradictory. With a view to the potential of chitosan in the regeneration of nerve tissue, the influence of DDA on the growth and health of olfactory ensheathing cells (OECs) was investigated. There was a linear increase in OEC proliferation as the DDA increased from 72 to 85%. This correlated with linear increases in average surface roughness (0.62 to 0.78 μm) and crystallinity (4.3 to 10.1%) of the chitosan films. Mitochondrial activity and membrane integrity of OECs was significantly different for OECs cultivated on chitosan with DDAs below 75%, while those on films with DDAs up to 85% were similar to cells in asynchronous growth. Apoptotic indices and cell cycle analysis also suggested that chitosan films with DDAs below 75% were cytocompatible but induced cellular stress, while OECs grown on films fabricated from chitosan with DDAs above 75% showed no significant differences compared to those in asynchronous growth. Tensile strength and elongation to break varied with DDA from 32.3 to 45.3 MPa and 3.6 to 7.1% respectively. DDA had no significant influence on abiotic and biotic degradation profiles of the chitosan films which showed approximately 8 and 20% weight loss respectively. Finally, perceived patterns in property changes are subject to change based on potential variations in DDA analysis. NMR examination of the chitosan samples here revealed significant differences depending upon which peaks were selected for integration; 6 to 13% in DDA values within individual samples. Furthermore, differences between DDA values determined here and those reported by the commercial suppliers were significant and this may also be a source of concern when selecting commercial chitosans for biomaterial research.
Journal Article
Batman, Knightquest : the crusade
\"Mentally defeated and physically broken, Bruce Wayne suffered a crippling blow while battling the brutal Bane. Now the mantle of the Bat must be passed on to another, and Jean-Paul Valley answers the call! Continued from Batman: Knigtfall Vol. 2 25th Anniversary Edition, this volume includes never-before-collected material. A new Batman's deadly crusade against the criminals of Gotham City begins! Bruce Wayne, battle-broken and out of commission after his epic showdown with Gotham's famous villain Bane, has appointed a new Dark Knight to keep the bad guys at bay. Jean-Paul Valley a.k.a. Azrael, has assumed the role of the Caped Crusader, but without Bruce's integrity as a calming influence, Jean-Paul is swiftly getting out of hand, alienating both Robin and Commissioner Gordon.\"-- Provided by publisher.
Book
Global discovery of lupus genetic risk variant allelic enhancer activity
Genome-wide association studies of Systemic Lupus Erythematosus (SLE) nominate 3073 genetic variants at 91 risk loci. To systematically screen these variants for allelic transcriptional enhancer activity, we construct a massively parallel reporter assay (MPRA) library comprising 12,396 DNA oligonucleotides containing the genomic context around every allele of each SLE variant. Transfection into the Epstein-Barr virus-transformed B cell line GM12878 reveals 482 variants with enhancer activity, with 51 variants showing genotype-dependent (allelic) enhancer activity at 27 risk loci. Comparison of MPRA results in GM12878 and Jurkat T cell lines highlights shared and unique allelic transcriptional regulatory mechanisms at SLE risk loci. In-depth analysis of allelic transcription factor (TF) binding at and around allelic variants identifies one class of TFs whose DNA-binding motif tends to be directly altered by the risk variant and a second class of TFs that bind allelically without direct alteration of their motif by the variant. Collectively, our approach provides a blueprint for the discovery of allelic gene regulation at risk loci for any disease and offers insight into the transcriptional regulatory mechanisms underlying SLE.
Thousands of genetic variants have been associated with lupus, but causal variants and mechanisms are unknown. Here, the authors combine a massively parallel reporter assay with genome-wide ChIP experiments to identify risk variants with allelic enhancer activity mediated through transcription factor binding.
Journal Article