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Institution

Vaughn College of Aeronautics and Technology

EducationNew 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
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Proceedings ArticleDOI
01 Nov 2015
TL;DR: The Autonomous Decentralized Test System (ADTS) is designed, which is aiming at enhancing ATS's survival probability and online maintainability and is also useful for solving test information standardization and ATS compatible problems.
Abstract: with the development of high technologies, the structure and capability of ATS has been greatly improved, such as footprint, compatibility, and cost and test efficiency. However, the survival ability of ATS is always slighted by researchers. In order to improve the survival ability of ATS, adopting the idea of autonomous decentralized systems, this paper designs the Autonomous Decentralized Test System (ADTS), which is aiming at enhancing ATS's survival probability and online maintainability. The new requirements of online specialties for ADTS are advised including online expansibility, online fault-tolerance and online maintenance. Firstly, with the consideration of requirements thoroughly, a model called double circle Autonomous Decentralized Test System was put forward, which is analyzed form three aspects: functional analysis, online characteristics analysis and autonomous ability analysis. After a demonstration, the model is proved that it has autonomous controllability, autonomous correspondences and invulnerability in structure. Secondly, ADTS test information standardization methods were studied. An approach that using automatic markup language technology to solve ATSs' test information standardization problems was promoted. Thirdly, ADTS's semantic characteristics is analyzed, then divided its data type into notification data and control data; the autonomous decentralized test protocol based on quality of service is brought forward then undergo a process of performance assessment. Fourthly, ADTS resource configure optimum method is put forward, the concept named “common test core” is invented, and the method for consisting Autonomous Decentralized Test System based on common test core was given. ADTS extends its value; which can improve ATS's survivorship and maintainability. The method is also useful for solving test information standardization and ATS compatible problems.

1 citations

Proceedings ArticleDOI
21 Aug 2020
TL;DR: In this paper, a user authentication system using an individual's pen tablet handwriting data is proposed, which is concerned with the numerical value of a person handwriting data getting from the digital pen and tablet device.
Abstract: Identifying a user or a person through handwriting-data is a popular technique. Many researches have been done in this area most of which are image or pattern-based analysis. The accuracy level depends on the quality of the image or pattern. In this paper, we proposed user authentication system using an individual's pen tablet handwriting data. The proposed system is concerned with the numerical value of a person handwriting data getting from the digital pen and tablet device. Hence, user authentication through pen tablet data ensures more accuracy by working with user's real time handwritten data. In the proposed system, 24 persons writing samples(1262 .csv files and 23 class)are used for extracting features to identify a user based on their handwriting attributes. Six completely separated features are extracted after data analysis and pre-processing. The extracted features are mainly concerned with the vital attributes of a user's handwriting. The extracted features are used for classification. With this concern, we utilized different classification algorithms such as Support Vector Machine (SVM), Logistic Regression (LR), Linear Discriminant Analysis (LDA) and Random Forest (RF) classifier. From the implementation, different algorithms show different accuracy level. The testing accuracy rate of SVM, LR, LDA and RF is 87%, 85%, 76% and 77% respectively. The experimental analysis shows that we got more robust and satisfactory results which ensure the practicality of our system.

1 citations

Journal ArticleDOI
TL;DR: In this article, a three-dimensional transient thermal analysis was carried out on both butt and lap joint welded titanium reinforced mild steel sheets using ANSYS Mechanical to simulate the GMAW transient heat source.

1 citations

Journal ArticleDOI
TL;DR: In an introduction to an article by Mr S. B. Gates on Trailing Edge Flaps, which appeared in these columns in 1937, the Editor felt constrained to admit his bewilderment over the number and variety of types of high-lift aid which then existed as discussed by the authors.
Abstract: WRITING an introduction to an article by Mr S. B. Gates on Trailing‐Edge Flaps, which appeared in these columns in 1937, the Editor felt constrained to admit his bewilderment over the number and variety of types of high‐lift aid which then existed. Without intending any disrespect, I imagine that the progress of years must have added to his embarrassment. It has certainly added to the number of devices in use and under test.

1 citations

Journal ArticleDOI
TL;DR: A CFD parallel adaptive algorithm is self-developed by combining the multi-block Lattice Boltzmann Method (LBM) with Adaptive Mesh Refinement (AMR) and the mesh refinement criterion of AMR.
Abstract: In this paper, a CFD parallel adaptive algorithm is self-developed by combining the multi-block Lattice Boltzmann Method (LBM) with Adaptive Mesh Refinement (AMR). The mesh refinement criterion of ...

1 citations


Authors

Showing all 732 results

NameH-indexPapersCitations
Xiang Zhang1541733117576
Denis J. Sullivan6133214092
To. Saito511839392
Arthur H. Lefebvre411234896
Michele Meo402235557
Robin S. Langley402635601
Ning Qin372835011
Holger Babinsky332424068
B. S. Gaudi31642560
Philip J. Longhurst29802578
Michael Gaster27663998
Don Harris261292537
To. Saito25562362
John F. O'Connell22891763
Rade Vignjevic21841563
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
20236
20223
202145
202033
201934
201841