1,740,516 research outputs found
Feature tracking & visualization in 'VISIT'
No full textThe study and analysis of large experimental or simulation datasets in the field of science and engineering pose a great challenge to the scientists. These complex simulations generate data varying over a period of time. Scientists need to glean large quantities of time-varying data to understand the underlying physical phenomenon. This is where visualization tools can assist scientists in their quest for analysis and understanding of scientific data. Feature Tracking, developed at Visualization & Graphics Lab (Vizlab), Rutgers University, is one such visualization tool. Feature Tracking is an automated process to isolate and analyze certain regions or objects of interest, called ‘features’ and to highlight their underlying physical processes in time-varying 3D datasets. In this thesis, we present a methodology and documentation on how to port ‘Feature Tracking’ into VisIt. VisIt is a freely available open-source visualization software package that has a rich feature set for visualizing and analyzing data. VisIt can successfully handle massive data quantities in the range of tera-scale. The technology covered by this thesis is an improvement over the previous work that focused on Feature Tracking in VisIt. In this thesis, the emphasis is on the visualization of features by assigning a constant color to the features (or objects) that move (or change their shape) over a period of time. Our algorithm gives scientists an option to choose only the features of interest amongst all the extracted objects. Scientists can then focus their attention solely on those objects that could help them in understanding the underlying mechanism better. We tested our algorithm on various datasets and present the results in this thesis.M.S.Includes bibliographical referencesby Naveen Atmakur
High-protein rice in high-yielding background, cv. Naveen.
Full text linkNot AvailableWhile the developing world is approaching towards food security, nutritional aspects must be addressed properly to combat malnutrition. As the staple food of half of the world’s population, rice is a major source of nutrition and needs to be nutritionally enriched with proteins, micronutrients, etc. With the objective of quantitative and qualitative improvement of grain protein content (GPC) in a popular high-yielding background, ‘Naveen’, we developed backcross popu-lation using high GPC (11%–13%) donor, ARC 10075. The range of GPC in BC3F4 lines was 7.13%–13.6%, estimated through calibrated NIR spectroscopy. Among the population lines, seven having phenotypic similarity with the recurrent parent, Naveen were identified based on high yield coupled with high pro-tein content (10%–12%). Further, elevated levels of glutelin and some of the essential amino acids such as lysine and threonine also indicated the qualitative im-provement of grain protein of these lines. Based on higher GPC and protein yield in multilocational test-ing two high-yielding lines, viz. CR2829-PLN-37 (CR Dhan 310), and CR 2829-PLN-100 (CR Dhan 311/Mukul) in the genetic background of cv. Naveen with an average 10.2% and 10.1% GPC respectively, in polished rice were released at the national and state level respectively. These high-yielding varieties with high GPC can significantly contribute towards better nourishment of millions of underprivileged children depending mainly on rice for their nutrition.Not Availabl
Naveen Kumar Singh's Quick Files
No full textThe Quick Files feature was discontinued and it’s files were migrated into this Project on March 11, 2022. The file URL’s will still resolve properly, and the Quick Files logs are available in the Project’s Recent Activity
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Measurement-based analysis of multiple-input multiple-output communications over the personal communication service spectrum
No full textThesis (M.Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2002.Includes bibliographical references (leaves 71-73).by Naveen N. Sunkavally.M.Eng
Bringing Semantics to Web Services: The OWL-S Approach
No full textService interface description languages such as WSDL, and related standards, are evolving rapidly to provide a foundation for interoperation between Web services. At the same time, Semantic Web service technologies, such as the Ontology Web Language for Services (OWL-S), are developing the means by which services can be given richer semantic specifications. Richer semantics can enable fuller, more flexible automation of service provision and use, and support the construction of more powerful tools and methodologies. Both sets of technologies can benefit from complementary uses and cross-fertilization of ideas. This paper shows how to use OWL-S in conjunction with Web service standards, and explains and illustrates the value added by the semantics expressed in OWL-S
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