2,051 research outputs found
Steven Bryant’s Solace: a conductor’s analysis and performance guide
No full textThe purpose of this study was to examine Solace, a musical composition for wind ensemble, by Steven Bryant composed for the University of North Carolina at Greensboro Wind Ensemble and premiered at the 2013 College Band Directors National Association National Conference. Through a conductor's analysis and performance guide, the author provided insight and background knowledge to all future performers and interpreters of the work through unique first hand accounts from commission to premiere performance. The research method included three processes: 1. A detailed analysis of the musical score, 2. The observation of rehearsals and recording sessions during preparation for the premiere performance of Solace by the University of North Carolina at Greensboro Wind Ensemble, Kevin M. Geraldi, conductor, 3. Extensive interviews of Steven Bryant, composer and Kevin M. Geraldi, conductor. Through examination of prior research on electro-acoustic works for wind ensemble, the author examined Solace within those constructs. Because of the blurring of lines between electronics and acoustic sound, the author further identified Solace as a unique musical composition within the electro-acoustic genre
More “Vitiating Paradoxes”: A Response to Steven D. Smith
No full textIn this article, the author presents his views in response to the article The Last Chapter? by critic Steven D. Smith. Topics discussed include importance of critical legal studies (CLS) theory in reflecting political aspects of religious freedom, views of Smith in his book The Rise and Decline of American Religious Freedom, and the relationship of egalitarianism with religious freedom
Theorists, Get Over Yourselves: A Response to Steven D. Smith
No full textIn this article, the author presents his views in response to the article The Last Chapter? by critic of contemporary liberal theory Steven D. Smith in reference to his book Defending American Religious Neutrality. Topics discussed include the political aspects associated with religious freedom, role of secularism in eroding religious freedom, and conflicts between religion and modern secular egalitarianism
Impact of coupling an ocean model to WRF nor’easter simulations
No full textThe impact of ocean-atmosphere coupling and its possible seasonal dependence upon Weather Research and Forecasting (WRF) model simulations of seven, winter-time cyclone events was investigated. Model simulations were identical aside from the degree of ocean model coupling (static SSTs, 1D mixed-layer model, full-physics 3D ocean model). Both 1D and 3D ocean model coupling simulations show that SSTs following the passage of a nor’easter did tend to cool more strongly during the early season (Oct-Dec) and were more likely to warm late in the season (Feb-Apr). Model simulations produce SST differences of up to 1.14 K, but this change did not lead to significant change in storm track ( 1) and have low-to-moderate threat scores (0.31 – 0.59). Analysis of the storm environment and the overall simulation failed to reveal any statistically significant differences in model error attributable to ocean-atmosphere coupling. Despite this result, ocean model coupling can reduce dynamical field error at a single level by up to 20%, and this was slightly greater (1-2%) with 3D ocean model coupling as compared to 1D ocean model coupling. Thus, while 3D ocean model coupling tended to generally produce more realistic simulations, its impact would likely be more profound for longer-term simulations.© Copyright 2015 American Meteorological Society (AMS). Permission to use figures, tables, and brief excerpts from this work in scientific and educational works is hereby granted provided that the source is acknowledged. Any use of material in this work that is determined to be “fair use” under Section 107 of the U.S. Copyright Act September 2010 Page 2 or that satisfies the conditions specified in Section 108 of the U.S. Copyright Act (17 USC §108, as revised by P.L. 94-553) does not require the AMS’s permission. Republication, systematic reproduction, posting in electronic form, such as on a web site or in a searchable database, or other uses of this material, except as exempted by the above statement, requires written permission or a license from the AMS. Additional details are provided in the AMS Copyright Policy, available on the AMS Web site located at (http://www.ametsoc.org/) or from the AMS at 617-227-2425 or [email protected] reviewe
Impact of Coupling an Ocean Model to WRF Nor’easter Simulations
No full textThe impact of ocean–atmosphere coupling and its possible seasonal dependence upon Weather Research and Forecasting (WRF) Model simulations of seven, wintertime cyclone events was investigated. Model simulations were identical aside from the degree of ocean model coupling (static SSTs, 1D mixed layer model, full-physics 3D ocean model). Both 1D and 3D ocean model coupling simulations show that SSTs following the passage of a nor’easter did tend to cool more strongly during the early season (October–December) and were more likely to warm late in the season (February–April). Model simulations produce SST differences of up to 1.14 K, but this change did not lead to significant changes in storm track ( 1) and have low-to-moderate threat scores (0.31–0.59). Analysis of the storm environment and the overall simulation failed to reveal any statistically significant differences in model error attributable to ocean–atmosphere coupling. Despite this result, ocean model coupling can reduce dynamical field error at a single level by up to 20%, and this was slightly greater (1%–2%) with 3D ocean model coupling as compared to 1D ocean model coupling. Thus, while 3D ocean model coupling tended to generally produce more realistic simulations, its impact would likely be more profound for longer-term simulations.© Copyright 2015 American Meteorological Society (AMS). Permission to use figures, tables, and brief excerpts from this work in scientific and educational works is hereby granted provided that the source is acknowledged. Any use of material in this work that is determined to be “fair use” under Section 107 of the U.S. Copyright Act September 2010 Page 2 or that satisfies the conditions specified in Section 108 of the U.S. Copyright Act (17 USC §108, as revised by P.L. 94-553) does not require the AMS’s permission. Republication, systematic reproduction, posting in electronic form, such as on a web site or in a searchable database, or other uses of this material, except as exempted by the above statement, requires written permission or a license from the AMS. Additional details are provided in the AMS Copyright Policy, available on the AMS Web site located at (http://www.ametsoc.org/) or from the AMS at 617-227-2425 or [email protected] reviewe
"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.
Destination marketing: An integrated marketing communication approach
No full textTravellers are spoilt by choice of available holiday destinations. In today’s fiercely competitive tourism markets, destination competitiveness demands an effective marketing organisation. Two themes underpin Destination Marketing. The first is the challenges associated with promoting multi-attributed destinations in dynamic and heterogeneous markets, and the second is the divide between tourism ‘practitioners’ and academics. Written by a former ‘practitioner’, Destination Marketing bridges industry and academia by synthesising a wealth of academic literature of practical value to DMOs. \ud
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Key learning outcomes are to enhance students’ understanding of the fundamental issues relating to:\ud
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• the multi-dimensional nature of destination competitiveness\ud
• rationale for the establishment of DMOs\ud
• structure, roles, goals and functions of DMOs\ud
• the shift in thinking towards destination management\ud
• key opportunities, challenges and constraints facing DMOs\ud
• complexities of marketing multi-attributed destinations as tourism brands\ud
• philosophy of integrated marketing communications \ud
• design, implementation and monitoring of effective destination marketing communication strategies\ud
• the potential for visitor relationship management\ud
• necessity of disaster response planning\ud
• destination marketing performance metrics\ud
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About the Author\ud
Dr Steven Pike (PhD) spent 17 years in the tourism industry, working in destination marketing organisations. He is currently Senior Lecturer in the School of Advertising, Marketing and Public relations at Queensland University of Technology in Brisbane, Australia
Unified mathematical treatment of complex cascaded bipartite networks: The case of collections of journal papers
No full textIn this study, a mathematical treatment is proposed for analysis of entities and relations among entities in
complex networks consisting of cascaded bipartite networks. This treatment is applied to the case of
collections of journal papers. In this case, entities are distinguishable objects and concepts, such as papers,
references, paper authors, reference authors, paper journals, reference journals, institutions, terms, and term
definitions. Relations are associations between entity-types such as papers and the references they cite, or
paper authors and the papers they write. An entity-relationship model is introduced that explicitly shows
direct links between entity-types and possible useful indirect relations. From this a matrix formulation and
generalized matrix arithmetic are introduced that allow easy expression of relations between entities and
calculation of weights of indirect links and co-occurrence links. Occurrence matrices, equivalence
matrices, membership matrices and co-occurrence matrices are described. A dynamic model of growth
describes recursive relations in occurrence and co-occurrence matrices as papers are added to the paper
collection. Graph theoretic matrices are introduced to allow information flow studies of networks of papers
linked by their citations. Similarity calculations and similarity fusion are explained. Derivation of feature
vectors for pattern recognition techniques is presented. The relation of the proposed mathematical
treatment to seriation, clustering, multidimensional scaling, and visualization techniques is discussed. It is
shown that most existing bibliometric analysis techniques for dealing with collections of journal papers are
easily expressed in terms of the proposed mathematical treatment: co-citation analysis, bibliographic
coupling analysis, author co-citation analysis, journal co-citation analysis, Braam-Moed-vanRaan (BMV)
co-citation/co-word analysis, latent semantic analysis, hubs and authorities, and multidimensional scaling.
This report discusses an extensive software toolkit that was developed for this research for analyzing and
visualizing entities and links in a collection of journal papers. Additionally, an extensive case study is
presented, analyzing and visualizing 60 years of anthrax research through a collection of journal papers.
When dealing with complex networks that consist of cascaded bipartite networks, the treatment presented
here provides a general mathematical framework for all aspects of analysis of static network structure and
network dynamic growth. As such, it provides a basic paradigm for thinking about and modeling such
networks: computing direct and indirect links, expressing and analyzing statistical distributions of network
characteristics, describing network growth, deriving feature vectors, clustering, and visualizing network
structure and growth
Agrostis howellii (Howell's bentgrass), Aster curtus (white-topped aster), Aster vialis (wayside aster), Delphinium leucophaeum (hot rock larkspur), Delphinium pavonaceaum (peacock larkspur), Erigeron decumbens var. decumbens (Willamette daisy), Horkelia congesta ssp. congesta (shaggy horkelia), Lomatium bradshawii (Bradshaw's desert parsley), Lupinus sulphureus ssp. kincaidii (Kincaid's lupine), Montia howellii (Howell's montia), Sidalcea spp. (Willamette Valley checkermallows)
No full textprepared by Steven D. Gisler, Native Plant Conservation Program, Oregon Department of Agriculture with contributions by Oregon Department of Agriculture staff for U.S. Fish and Wildlife Service, Grant OR-EP-2, segment 13.Title from PDF cover (viewed on December 2, 2019).This archived document is maintained by the State Library of Oregon as part of the Oregon Documents Depository Program. It is for informational purposes and may not be suitable for legal purposes.Includes bibliographical references.Mode of access: Internet from the Oregon Government Publications Collection.Text in English
Fake It Till You Make It: Data Augmentation Using Generative Adversarial Networks for All the Crypto You Need on Small Devices
No full textDeep learning-based side-channel analysis performance heavily depends on the dataset size and the number of instances in each target class. Both small and imbalanced datasets might lead to unsuccessful side-channel attacks. The attack performance can be improved by generating traces synthetically from the obtained data instances instead of collecting them from the target device, but this is a cumbersome and challenging task. We propose a novel data augmentation approach based on conditional Generative Adversarial Networks (cGAN) and Siamese networks, enhancing the attack capability. We also present a quantitative comparative deep learning-based side-channel analysis between a real raw signal leakage dataset and an artificially augmented leakage dataset. The analysis is performed on the leakage datasets for both symmetric and public-key cryptographic implementations. We investigate non-convergent networks’ effect on the generation of fake leakage signals using two cGAN based deep learning models. The analysis shows that the proposed data augmentation model results in a well-converged network that generates realistic leakage traces, which can be used to mount deep learning-based side-channel analysis successfully even when the dataset available from the device is not optimal. Our results show that the datasets enhanced with “faked” leakage traces are breakable (while not without augmentation), which might change how we perform deep learning-based side-channel analysis.Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Cyber Securit
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