Education•Norfolk, Virginia, United States•
About: Old Dominion University is a education organization based out in Norfolk, Virginia, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 8853 authors who have published 23297 publications receiving 616881 citations. The organization is also known as: ODU.
Papers published on a yearly basis
Harvard University1, University of Reims Champagne-Ardenne2, College of William & Mary3, Old Dominion University4, University of Lisbon5, University of Burgundy6, California Institute of Technology7, Centre national de la recherche scientifique8, Université catholique de Louvain9, University of York10, University College London11, National Institute of Standards and Technology12, University of Waterloo13, National Center for Atmospheric Research14, University of Cologne15, Karlsruhe Institute of Technology16, Langley Research Center17
TL;DR: The new HITRAN is greatly extended in terms of accuracy, spectral coverage, additional absorption phenomena, added line-shape formalisms, and validity, and molecules, isotopologues, and perturbing gases have been added that address the issues of atmospheres beyond the Earth.
Abstract: This paper describes the contents of the 2016 edition of the HITRAN molecular spectroscopic compilation. The new edition replaces the previous HITRAN edition of 2012 and its updates during the intervening years. The HITRAN molecular absorption compilation is composed of five major components: the traditional line-by-line spectroscopic parameters required for high-resolution radiative-transfer codes, infrared absorption cross-sections for molecules not yet amenable to representation in a line-by-line form, collision-induced absorption data, aerosol indices of refraction, and general tables such as partition sums that apply globally to the data. The new HITRAN is greatly extended in terms of accuracy, spectral coverage, additional absorption phenomena, added line-shape formalisms, and validity. Moreover, molecules, isotopologues, and perturbing gases have been added that address the issues of atmospheres beyond the Earth. Of considerable note, experimental IR cross-sections for almost 300 additional molecules important in different areas of atmospheric science have been added to the database. The compilation can be accessed through www.hitran.org. Most of the HITRAN data have now been cast into an underlying relational database structure that offers many advantages over the long-standing sequential text-based structure. The new structure empowers the user in many ways. It enables the incorporation of an extended set of fundamental parameters per transition, sophisticated line-shape formalisms, easy user-defined output formats, and very convenient searching, filtering, and plotting of data. A powerful application programming interface making use of structured query language (SQL) features for higher-level applications of HITRAN is also provided.
TL;DR: The definitions, architecture, fundamental technologies, and applications of IoT are systematically reviewed and the major challenges which need addressing by the research community and corresponding potential solutions are investigated.
Abstract: In recent year, the Internet of Things (IoT) has drawn significant research attention. IoT is considered as a part of the Internet of the future and will comprise billions of intelligent communicating `things'. The future of the Internet will consist of heterogeneously connected devices that will further extend the borders of the world with physical entities and virtual components. The Internet of Things (IoT) will empower the connected things with new capabilities. In this survey, the definitions, architecture, fundamental technologies, and applications of IoT are systematically reviewed. Firstly, various definitions of IoT are introduced; secondly, emerging techniques for the implementation of IoT are discussed; thirdly, some open issues related to the IoT applications are explored; finally, the major challenges which need addressing by the research community and corresponding potential solutions are investigated.
TL;DR: Wang et al. as mentioned in this paper developed a novel 3D CNN model for action recognition, which extracts features from both the spatial and the temporal dimensions by performing 3D convolutions, thereby capturing the motion information encoded in multiple adjacent frames.
Abstract: We consider the automated recognition of human actions in surveillance videos. Most current methods build classifiers based on complex handcrafted features computed from the raw inputs. Convolutional neural networks (CNNs) are a type of deep model that can act directly on the raw inputs. However, such models are currently limited to handling 2D inputs. In this paper, we develop a novel 3D CNN model for action recognition. This model extracts features from both the spatial and the temporal dimensions by performing 3D convolutions, thereby capturing the motion information encoded in multiple adjacent frames. The developed model generates multiple channels of information from the input frames, and the final feature representation combines information from all channels. To further boost the performance, we propose regularizing the outputs with high-level features and combining the predictions of a variety of different models. We apply the developed models to recognize human actions in the real-world environment of airport surveillance videos, and they achieve superior performance in comparison to baseline methods.
BirdLife International1, United Nations Environment Programme2, Zoological Society of London3, Statistics Netherlands4, University of North Carolina at Chapel Hill5, Old Dominion University6, Conservation International7, Food and Agriculture Organization8, University of Virginia9, Royal Society for the Protection of Birds10, University of Queensland11, University of Cambridge12, National Center for Atmospheric Research13, World Wide Fund for Nature14, South African National Parks15, UNESCO16, University of British Columbia17, Tata Institute of Fundamental Research18, The Nature Conservancy19, Patuxent Wildlife Research Center20, American Bird Conservancy21, Stellenbosch University22, International Union for Conservation of Nature and Natural Resources23
TL;DR: Most indicators of the state of biodiversity showed declines, with no significant recent reductions in rate, whereas indicators of pressures on biodiversity showed increases, indicating that the Convention on Biological Diversity’s 2010 targets have not been met.
Abstract: In 2002, world leaders committed, through the Convention on Biological Diversity, to achieve a significant reduction in the rate of biodiversity loss by 2010. We compiled 31 indicators to report on progress toward this target. Most indicators of the state of biodiversity (covering species' population trends, extinction risk, habitat extent and condition, and community composition) showed declines, with no significant recent reductions in rate, whereas indicators of pressures on biodiversity (including resource consumption, invasive alien species, nitrogen pollution, overexploitation, and climate change impacts) showed increases. Despite some local successes and increasing responses (including extent and biodiversity coverage of protected areas, sustainable forest management, policy responses to invasive alien species, and biodiversity-related aid), the rate of biodiversity loss does not appear to be slowing.
TL;DR: This review paper summarizes the current state-of-the-art IoT in industries systematically and identifies research trends and challenges.
Abstract: Internet of Things (IoT) has provided a promising opportunity to build powerful industrial systems and applications by leveraging the growing ubiquity of radio-frequency identification (RFID), and wireless, mobile, and sensor devices. A wide range of industrial IoT applications have been developed and deployed in recent years. In an effort to understand the development of IoT in industries, this paper reviews the current research of IoT, key enabling technologies, major IoT applications in industries, and identifies research trends and challenges. A main contribution of this review paper is that it summarizes the current state-of-the-art IoT in industries systematically.
Showing all 8853 results
|Shaker A. Zahra||104||293||63532|
|Patrick G. Hatcher||91||401||27519|
|John E. Sipe||83||719||27000|
|Thomas F. Cash||77||147||21400|
|Peter F. Bernath||77||821||37240|
Related Institutions (5)
Arizona State University
109.6K papers, 4.4M citations
University of Maryland, College Park
155.9K papers, 7.2M citations
Pennsylvania State University
196.8K papers, 8.3M citations
95.2K papers, 2.9M citations
University of Connecticut
81.2K papers, 2.9M citations