Institution
Vaughn College of Aeronautics and Technology
Education•New York, New York, United States•
About: Vaughn College of Aeronautics and Technology is a education organization based out in New York, New York, United States. It is known for research contribution in the topics: Gravitational microlensing & Planetary system. The organization has 727 authors who have published 708 publications receiving 14082 citations. The organization is also known as: College of Aeronautics.
Papers published on a yearly basis
Papers
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Ohio State University1, Massey University2, University of Warsaw3, Chungbuk National University4, Niels Bohr Institute5, University of Tasmania6, Las Cumbres Observatory Global Telescope Network7, Lund University8, National Institute for Space Research9, Texas A&M University10, Korea Astronomy and Space Science Institute11, University of Valencia12, Auckland University of Technology13, Nagoya University14, University of Notre Dame15, University of Auckland16, Victoria University of Wellington17, Vaughn College of Aeronautics and Technology18, Osaka University19, University of Concepción20, Qatar Foundation21, University of Salerno22, University of St Andrews23, Ames Research Center24, University of Liège25, Heidelberg University26, University of Göttingen27, University of Manchester28, Perimeter Institute for Theoretical Physics29, Space Telescope Science Institute30, Max Planck Society31, Keele University32, Liverpool John Moores University33, University of Canterbury34, University of Toulouse35, Institut d'Astrophysique de Paris36, Massachusetts Institute of Technology37, European Southern Observatory38, University of Rijeka39, Vienna University of Technology40
TL;DR: In this paper, the authors combine long-term photometric monitoring with a previously published high-resolution spectrum taken near peak to demonstrate that this is an RS CVn variable, so that planetary microlensing is not required to explain the light-curve deviations.
Abstract: The Galactic bulge source MOA-2010-BLG-523S exhibited short-term deviations from a standard microlensing light curve near the peak of an A(max) similar to 265 high-magnification microlensing event. The deviations originally seemed consistent with expectations for a planetary companion to the principal lens. We combine long-term photometric monitoring with a previously published high-resolution spectrum taken near peak to demonstrate that this is an RS CVn variable, so that planetary microlensing is not required to explain the light-curve deviations. This is the first spectroscopically confirmed RS CVn star discovered in the Galactic bulge.
21 citations
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TL;DR: This paper employs a two-layer blockchain architecture in TrafficChain to improve system efficiency, design a privacy-preserving scheme to protect users’ identities and travel traces, and devise LSTM based deep learning mechanisms that can defend against Byzantine attacks and Sybil attacks in the system.
Abstract: Intelligent Connected Vehicles (ICVs) can provide smart, safe, and efficient transportation services and have attracted intensive attention recently. Obtaining timely and accurate traffic information is one of the most important problems in transportation systems, which would allow people to select fast routes and avoid congestions, thus saving their travel time on the road. Currently, the most popular ways to obtain traffic information is to inquire navigation agents, e.g., Apple map, and Google map. However, these navigation agents are essentially centralized systems, which are vulnerable to service congestions, a single point of failure, and attacks. Furthermore, users' privacy gets compromised as the agents can know their home and work addresses and hence their identities, track them in real-time, etc. In this paper, we propose TrafficChain, a secure and privacy-preserving decentralized traffic information collection system on the blockchain, by taking advantage of fog/edge computing infrastructure. In particular, we employ a two-layer blockchain architecture in TrafficChain to improve system efficiency, design a privacy-preserving scheme to protect users' identities and travel traces, and devise LSTM based deep learning mechanisms that can defend against Byzantine attacks and Sybil attacks in our system. Furthermore, an incentive mechanism is designed to motivate users to participate in the system. Simulation results show that TrafficChain works very efficiently and is resilient to both Byzantine attacks and Sybil attacks.
21 citations
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TL;DR: A comparative evaluation of two data smoothing algorithms for use in a two step estimation-beforemodelling procedure for aircraft parameter identification concluded that the fixed lag smoother algorithm is an acceptable alternative to the modified-Bryson-Frazier algorithm in aircraft parameter Identification applications.
Abstract: Abstract This paper describes a comparative evaluation of two data smoothing algorithms for use in a two step estimation-beforemodelling procedure for aircraft parameter identification. A simple fixed lag smoother is compared with the usual, and more complex, modified-Bryson-Frazier smoother in the first, state estimation, step of the aircraft parameter identification procedure. The comparison is illustrated by application to the analysis of the Dutch Roll motion of the Embraer EMB-312 Tucano. Both algorithms were found to give results of comparable accuracy although the fixed lag smoother is computationally more efficient. It was concluded that the fixed lag smoother algorithm is an acceptable alternative to the modified-Bryson-Frazier algorithm in aircraft parameter identification applications.
21 citations
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Ohio State University1, Chungbuk National University2, Osaka University3, University of Warsaw4, Queen Mary University of London5, Las Cumbres Observatory Global Telescope Network6, Istituto Nazionale di Fisica Nucleare7, University of Salerno8, Nagoya University9, University of Notre Dame10, Massey University11, University of Auckland12, Victoria University of Wellington13, Vaughn College of Aeronautics and Technology14, Kyoto Sangyo University15, University of Concepción16, University of São Paulo17, National Institute for Space Research18, Texas A&M University19, Peking University20, Tel Aviv University21, Korea Astronomy and Space Science Institute22, Auckland University of Technology23, Harvard University24, University of Exeter25, Qatar Foundation26, University of St Andrews27, Royal Society28, European Southern Observatory29, Max Planck Society30, Liverpool John Moores University31
TL;DR: The mass of the lenses giving rise to Galactic microlensing events can be constrained by measuring the relative lenssource proper motion and lens flux as mentioned in this paper, which can be separated from that of the source, companions to the source and unrelated nearby stars with high-resolution images taken when the lens and source are spatially resolved.
Abstract: The mass of the lenses giving rise to Galactic microlensing events can be constrained by measuring the relative lenssource proper motion and lens flux. The flux of the lens can be separated from that of the source, companions to the source, and unrelated nearby stars with high-resolution images taken when the lens and source are spatially resolved.
21 citations
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TL;DR: In this article, a study of the response of a diffusion flame sheet to perturbations of reactant concentration which are introduced, either as changes in the free streams, or as appropriate initial distributions throughout the field.
Abstract: A study is made of the response of a diffusion flame sheet to perturbations of reactant concentration which are introduced, either as changes in the free streams, or as appropriate initial distributions throughout the field. Species’ and energy conservation requirements are approximated by linearized boundary-layer equations; general solutions are derived for species, enthalpy and temperature distributions, as well as for the flame sheet shape, and a number of specific problems are solved.
21 citations
Authors
Showing all 732 results
Name | H-index | Papers | Citations |
---|---|---|---|
Xiang Zhang | 154 | 1733 | 117576 |
Denis J. Sullivan | 61 | 332 | 14092 |
To. Saito | 51 | 183 | 9392 |
Arthur H. Lefebvre | 41 | 123 | 4896 |
Michele Meo | 40 | 223 | 5557 |
Robin S. Langley | 40 | 263 | 5601 |
Ning Qin | 37 | 283 | 5011 |
Holger Babinsky | 33 | 242 | 4068 |
B. S. Gaudi | 31 | 64 | 2560 |
Philip J. Longhurst | 29 | 80 | 2578 |
Michael Gaster | 27 | 66 | 3998 |
Don Harris | 26 | 129 | 2537 |
To. Saito | 25 | 56 | 2362 |
John F. O'Connell | 22 | 89 | 1763 |
Rade Vignjevic | 21 | 84 | 1563 |