Mobile Wound Assessment and 3D Modeling from a Single Image

The prevalence of camera-enabled mobile phones have made mobile wound assessment a viable treatment option for millions of previously difficult to reach patients. We have designed a complete mobile wound assessment platform to ameliorate the many challenges related to chronic wound care. Chronic wounds and infections are the most severe, costly and fatal types of wounds, placing them at the center of mobile wound assessment. Wound physicians assess thousands of single-view wound images from all over the world, and it may be difficult to determine the location of the wound on the body, for example, if the wound is taken at close range. In our solution, end-users capture an image of the wound by taking a picture with their mobile camera. The wound image is segmented and classified using modern convolution neural networks, and is stored securely in the cloud for remote tracking. We use an interactive semi-automated approach to allow users to specify the location of the wound on the body. To accomplish this we have created, to the best our knowledge, the first 3D human surface anatomy labeling system, based off the current NYU and Anatomy Mapper labeling systems. To interactively view wounds in 3D, we have presented an efficient projective texture mapping algorithm for texturing wounds onto a 3D human anatomy model. In so doing, we have demonstrated an approach to 3D wound reconstruction that works even for a single wound image

IEEE Access Special Section Editorial: Big Data Technology and Applications in Intelligent Transportation

During the last few years, information technology and transportation industries, along with automotive manufacturers and academia, are focusing on leveraging intelligent transportation systems (ITS) to improve services related to driver experience, connected cars, Internet data plans for vehicles, traffic infrastructure, urban transportation systems, traffic collaborative management, road traffic accidents analysis, road traffic flow prediction, public transportation service plan, personal travel route plans, and the development of an effective ecosystem for vehicles, drivers, traffic controllers, city planners, and transportation applications. Moreover, the emerging technologies of the Internet of Things (IoT) and cloud computing have provided unprecedented opportunities for the development and realization of innovative intelligent transportation systems where sensors and mobile devices can gather information and cloud computing, allowing knowledge discovery, information sharing, and supported decision making. However, the development of such data-driven ITS requires the integration, processing, and analysis of plentiful information obtained from millions of vehicles, traffic infrastructures, smartphones, and other collaborative systems like weather stations and road safety and early warning systems. The huge amount of data generated by ITS devices is only of value if utilized in data analytics for decision-making such as accident prevention and detection, controlling road risks, reducing traffic carbon emissions, and other applications which bring big data analytics into the picture

Solar astronomy

An overview is given of modern solar physics. Topics covered include the solar interior, the solar surface, the solar atmosphere, the Large Earth-based Solar Telescope (LEST), the Orbiting Solar Laboratory, the High Energy Solar Physics mission, the Space Exploration Initiative, solar-terrestrial physics, and adaptive optics. Policy and related programmatic recommendations are given for university research and education, facilitating solar research, and integrated support for solar research

Some applications of radar return data to the study of terrestrial and oceanic phenomena

Side-looking radar spacecraft application to mapping, imagery, altimetry, geology, pedology, glaciology, agriculture, and oceanograph

Solar-Terrestrial Science Strategy Workshop

The conclusions and recommendations reached at the Solar Terrestrial Science Strategy Workshop are summarized. The charter given to this diverse group was: (1) to establish the level of scientific understanding to be accomplished with the completion of the current and near term worldwide programs; (2) identify the significant scientific questions to be answered by future solar terrestrial programs, and the programs required to answer these questions; and (3) map out a program strategy, taking into consideration currently perceived space capabilities and constraints, to accomplish the identified program

proceedings of a workshop held at Göttingen September 27 - 29, 2006

An international workshop entitled: Modern Solar Facilities - Advanced Solar Science was held in Göttingen from September 27 until September 29, 2006. The workshop, which was attended by 88 participants from 24 different countries, gave a broad overview of the current state of solar research, with emphasis on modern telescopes and techniques, advanced observational methods and results, and on modern theoretical methods of modelling, computation, and data reduction in solar physics. This book collects written versions of contributions that were presented at the workshop as invited or contributed talks, and as poster contributions.Vom 27. bis 29. September 2006 fand in Göttingen ein internationaler Workshop zum Thema: Modern Solar Facilities - Advanced Solar Science statt, der von 88 Teilnehmern aus 24 verschiedenen Ländern besucht wurde und der einen breiten Überblick über den gegenwärtigen Stand der sonnenphysikalischen Forschung gab, unter Betonung moderner Teleskope und Techniken, fortschrittlicher Beobachtungsmethoden und Ergebnisse, sowie zu modernen theoretischen Verfahren der Modellierung, Berechnung und Datenreduktion in der Sonnenphysik. Dieser Band fasst die schriftlichen Versionen von Beiträgen zusammen, die auf der Konferenz als eingeladene oder angemeldete Vorträge, sowie als Posterbeiträge präsentiert worden sind.conferenc

Accurately constraining velocity information from spectral imaging observations using machine learning techniques

Determining accurate plasma Doppler (line-of-sight) velocities from spectroscopic measurements is a challenging endeavour, especially when weak chromospheric absorption lines are often rapidly evolving and, hence, contain multiple spectral components in their constituent line profiles. Here, we present a novel method that employs machine learning techniques to identify the underlying components present within observed spectral lines, before subsequently constraining the constituent profiles through single or multiple Voigt fits. Our method allows active and quiescent components present in spectra to be identified and isolated for subsequent study. Lastly, we employ a Ca II 8542 {\AA} spectral imaging dataset as a proof-of-concept study to benchmark the suitability of our code for extracting two-component atmospheric profiles that are commonly present in sunspot chromospheres. Minimisation tests are employed to validate the reliability of the results, achieving median reduced $\chi^2$ values equal to 1.03 between the observed and synthesised umbral line profiles.Comment: 23 pages, 8 figures. Improved formatting of abstract and reference