scispace - formally typeset
Search or ask a question
Institution

Clarkson University

EducationPotsdam, New York, United States
About: Clarkson University is a education organization based out in Potsdam, New York, United States. It is known for research contribution in the topics: Particle & Turbulence. The organization has 4414 authors who have published 10009 publications receiving 305356 citations. The organization is also known as: Thomas S. Clarkson Memorial School of Technology & Thomas S. Clarkson Memorial College of Technology.


Papers
More filters
Journal ArticleDOI
TL;DR: The very mild conditions required for the photodegradation and the high rate at which it occurs suggest applications for iron(III) cross-linked alginate hydrogels as light-controlled biocompatible scaffolds.

149 citations

Journal ArticleDOI
TL;DR: This work describes development and optimization of a generic method for the immobilization of enzymes in chemically synthesized gold polypyrrole (Au-PPy) nanocomposite and their application in amperometric biosensors, which has proved to be an effective way for stable enzyme attachment.

149 citations

Journal ArticleDOI
TL;DR: In this article, the influence of bath composition, mass transfer and applied potential on the trivalent chromium electrodeposition from a bath containing ammonium formate and sodium acetate as the complexing agents was studied by the potentiostatic current efficiency and rotating disk electrode experiments.

149 citations

Journal ArticleDOI
TL;DR: Computer vision algorithms that recognize and locate partially occluded objects using a generate-test paradigm that iteratively generates and tests hypotheses for compatibility with the scene until it identifies all the scene objects.
Abstract: We present computer vision algorithms that recognize and locate partially occluded objects. The scene may contain unknown objects that may touch or overlap giving rise to partial occlusion. The algorithms revolve around a generate-test paradigm. The paradigm iteratively generates and tests hypotheses for compatibility with the scene until it identifies all the scene objects. Polygon representations of the object's boundary guide the hypothesis generation scheme. Choosing the polygon representation turns out to have powerful consequences in all phases of hypothesis generation and verification. Special vertices of the polygon called ``corners'' help detect and locate the model in the scene. Polygon moment calculations lead to estimates of the dissimilarity between scene and model corners, and determine the model corner location in the scene. An association graph represents the matches and compatibility constraints. Extraction of the largest set of mutually compatible matches from the association graph forms a model hypothesis. Using a coordinate transform that maps the model onto the scene, the hypothesis gives the proposed model's location and orientation. Hypothesis verification requires checking for region consistency. The union of two polygons and other polygon operations combine to measure the consistency of the hypothesis with the scene. Experimental results give examples of all phases of recognizing and locating the objects.

148 citations

Journal ArticleDOI
TL;DR: In this article, the authors combine the merits of the unscented Kalman filter and the recursive nonlinear dynamic data reconciliation (URNDDR) technique to obtain the UnScented Recursive Nonlinear Dynamic Data Reconciliation (URRD) technique, which provides state and parameter estimates that satisfy bounds and other constraints imposed on them.

148 citations


Authors

Showing all 4454 results

NameH-indexPapersCitations
Xuan Zhang119153065398
Michael R. Hoffmann10950063474
Philip K. Hopke9192940612
Sudipta Seal8651432788
Egon Matijević8146625015
Mark J. Ablowitz7437427715
Kim R. Dunbar7447020262
Maureen E. Callow7018814957
Igor M. Sokolov6967320256
James A. Callow6818614424
Michal Borkovec6623519638
Sergiy Minko6625618723
Corwin Hansch6634226798
David H. Russell6647717172
Nitash P. Balsara6241115083
Network Information
Related Institutions (5)
Georgia Institute of Technology
119K papers, 4.6M citations

93% related

University of Maryland, College Park
155.9K papers, 7.2M citations

91% related

ETH Zurich
122.4K papers, 5.1M citations

91% related

University of California, Santa Barbara
80.8K papers, 4.6M citations

91% related

Texas A&M University
164.3K papers, 5.7M citations

91% related

Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202315
202259
2021395
2020394
2019414
2018428