131,598 research outputs found
Varon, Frank D.
No full textCentro Asturiano membership record of Frank D. Varon; Socio Number: 138060.https://digitalcommons.usf.edu/asturiano_membership/5895/thumbnail.jp
Experimental application of a dynamic observer to capture and predict the dynamics of a flat-plate boundary layer
No full textThe recent approach, proposed by Guzman-Inigo et al. \cite{GuzmanInigo2014}, using System Identification to derive a Reduced Order Model from snapshots of a flow is applied to a transitional boundary layer growing over a flat-plate. It is shown that such an approach can indeed be applied to experimental PIV snapshots. Using a proper learning dataset and a proper local sensor, it is shown that the evolution of boundary layer can be properly estimated from the time evolution of the local probe and with no more than ten POD modes for the Reduced Order Model. The influence of the various parameters on the efficiency of the system identification technique is discussed
Architectural composition
No full textAn introductory architecture book, written and illustrated by D. Varon (Professor of Architecture at Syracuse University and at University of Illinois)" The first portion of the books contains eleven short chapters about various design concepts. The second portion of the book contains plates of drawings with supplemental notes explaining how to convey architectural elements in drawings. An appendix includes plates of drawings of structures exemplifying architectural forms and styles
Separating respiratory influences from the tachogram: Methods and their sensitivity to the type of respiratory signal
No full textRespiration is one of the main modulators causing heart rate variability (HRV). However, when interpreting studies of HRV, the effect of respiration is largely ignored. We, therefore, previously proposed to take respiratory influences into account by separating the tachogram in a component that is related to respiration and one that contains all residual variations. In this study, we aim to investigate the sensitivity of two of such separation methods, i.e. one based on an ARMAX model and another one based on orthogonal subspace projection (OSP), towards different respiratory signal types, such as nasal airflow (the reference), thoracic and abdominal efforts, and three ECG-derived respiratory (EDR) signals. The sensitivity of both separation methods to the type of respiratory signal is evaluated by assessing the information transfer from the reference respiratory signal to the residual tachogram, where the latter is obtained using each time a different type of respiratory signal. The results show that OSP is the least sensitive to the different types of respiratory signals. Even when an EDR signal obtained using kernel principal component analysis is used, OSP yields a correct separation in 13 out of 18 recordings, demonstrating that in many cases, the separation of the tachogram can successfully be conducted even if only the ECG is available
MeSH term explosion and author rank improve expert recommendations
No full textInformation overload is an often-cited phenomenon that reduces the productivity, efficiency and efficacy of scientists. One challenge for scientists is to find appropriate collaborators in their research. The literature describes various solutions to the problem of expertise location, but most current approaches do not appear to be very suitable for expert recommendations in biomedical research. In this study, we present the development and initial evaluation of a vector space model-based algorithm to calculate researcher similarity using four inputs: 1) MeSH terms of publications; 2) MeSH terms and author rank; 3) exploded MeSH terms; and 4) exploded MeSH terms and author rank. We developed and evaluated the algorithm using a data set of 17,525 authors and their 22,542 papers. On average, our algorithms correctly predicted 2.5 of the top 5/10 coauthors of individual scientists. Exploded MeSH and author rank outperformed all other algorithms in accuracy, followed closely by MeSH and author rank. Our results show that the accuracy of MeSH term-based matching can be enhanced with other metadata such as author rank
Going Beyond Counting First Authors in Author Co-citation Analysis
No full textThe 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
Replication Data for: Satellite discovery of anomalously large methane point sources from oil/gas production
No full textGHGSat-D methane data for: Satellite discovery of anomalously large methane point sources from oil/gas production, Figure 1. The data are stored as Python Numpy .npy files
"Closing the R&D Gap, Evaluating the Sources of R&D Spending"
No full textBoth spending and tax policies have been implemented in the United States with the goal of stimulating private sector research and development (R&D). Karier questions whether current R&D policy, especially the research and experimentation tax credit, can contribute to closing the gap between nondefense expenditures on R&D in the United States and such expenditures in other countries, such as Japan and Germany. He also explores possible changes to our current R&D policy to make it more effective.
Replication Data for: Satellite discovery of anomalously large methane point sources from oil/gas production
No full textGHGSat-D methane data for: Satellite discovery of anomalously large methane point sources from oil/gas production, Figure 1. The data are stored as Python Numpy .npy files
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