Relevant bibliographies by topics / Dynamic field

Academic literature on the topic 'Dynamic field'

Author: Grafiati
Published: 30 May 2022
Last updated: 31 May 2022

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Journal articles on the topic "Dynamic field"

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Goldar, Dulal. "OS01W0028 Full-Field Dynamic Photoelastic Studies of Transversely Impacted Beams." Abstracts of ATEM : International Conference on Advanced Technology in Experimental Mechanics : Asian Conference on Experimental Mechanics 2003.2 (2003): _OS01W0028. http://dx.doi.org/10.1299/jsmeatem.2003.2._os01w0028.

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Kalegaev, V. V. "Dynamic geomagnetic field models." Geomagnetism and Aeronomy 51, no. 7 (December 2011): 855–65. http://dx.doi.org/10.1134/s0016793211070073.

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Zhang, Qingquan, Yao Yao, Ting Zhu, Ziqiao Zhou, Wei Xu, Ping Yi, and Sheng Xiao. "Dynamic Enhanced Field Division." ACM Transactions on Sensor Networks 15, no. 1 (February 21, 2019): 1–26. http://dx.doi.org/10.1145/3216721.

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Postma, Maarten Jacobus. "The dynamic field of pharmacoeconomics." Expert Review of Clinical Pharmacology 2, no. 2 (March 2009): 125–27. http://dx.doi.org/10.1586/17512433.2.2.125.

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Shinada, Hiroyuki. "Dynamic Micro-Magnetic Field Measurement." IEEJ Transactions on Fundamentals and Materials 112, no. 2 (1992): 87–90. http://dx.doi.org/10.1541/ieejfms1990.112.2_87.

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J. Chaplin and C. Wu. "Dynamic Modeling of Field Sprayers." Transactions of the ASAE 32, no. 6 (1990): 1857. http://dx.doi.org/10.13031/2013.31235.

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Gray, Jonathan, and Amanda D. Lotz. "A robust and dynamic field." Media, Culture & Society 35, no. 8 (November 2013): 1019–22. http://dx.doi.org/10.1177/0163443713508703.

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Westphal, V., M. A. Lauterbach, A. Di Nicola, and S. W. Hell. "Dynamic far-field fluorescence nanoscopy." New Journal of Physics 9, no. 12 (December 5, 2007): 435. http://dx.doi.org/10.1088/1367-2630/9/12/435.

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Lipiński, S., and A. Szajek. "Dynamic Crystal Field in CePb3." Acta Physica Polonica A 97, no. 1 (January 2000): 245–48. http://dx.doi.org/10.12693/aphyspola.97.245.

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Tsui, Ivy F. L., Cathie Garnis, and Catherine F. Poh. "A Dynamic Oral Cancer Field." American Journal of Surgical Pathology 33, no. 11 (November 2009): 1732–38. http://dx.doi.org/10.1097/pas.0b013e3181b669c2.

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Dissertations / Theses on the topic "Dynamic field"

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Chapman, Craig K. "Coarsening dynamical systems : dynamic scaling, universality and mean-field theories." Thesis, University of Glasgow, 2012. http://theses.gla.ac.uk/3255/.

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We study three distinct coarsening dynamical systems (CDS) and probe the underlying scaling laws and universal scaling functions. We employ a variety of computational methods to discover and analyse these intrinsic statistical objects. We consider mean-field type models, similar in nature to those used in the seminal work of Lifshitz, Slyozov and Wagner (LSW theory), and statistical information is then derived from these models. We first consider a simple particle model where each particle possesses a continuous positive parameter, called mass, which itself determines the particle’s velocity through a prescribed law of motion. The varying speeds of particles, caused by their differing masses, causes collisions to take place, in which the colliding particles then merge into a single particle while conserving mass. We computationally discover the presence of scaling laws of the characteristic scale (mean mass) and universal scaling functions for the distribution of particle mass for a family of power-law motion rules. We show that in the limit as the power-law exponent approaches infinity, this family of models approaches a probabilistic min-driven model. This min-driven model is then analysed through a mean-field type model, which yields a prediction of the universal scaling function. We also consider the conserved Kuramoto-Sivashinsky (CKS) equation and provide, in particular, a critique of the effective dynamics derived by Politi and ben-Avraham. We consider several different numerical methods for solving the CKS equation, both on fixed and adaptive grids, before settling on an implicit-explicit hybrid scheme. We then show, through a series of detailed numerical simulations of both the CKS equation and the proposed dynamics, that their particular reduction to a length-based CDS does not capture the effective dynamics of the CKS equation. Finally, we consider a faceted CDS derived from a one-dimensional geometric partial differential equation. Unusually, an obvious one-point mean-field theory for this CDS is not present. As a result, we consider the two-point distribution of facet lengths. We derive a mean-field evolution equation governing the two-point distribution, which serves as a two-dimensional generalisation of the LSW theory. Through consideration of the two-point theory, we subsequently derive a non-trivial one-point sub-model which we analytically solve. Our predicted one-point distribution bears a significant resemblance to the LSW distribution and stands in reasonable agreement with the underlying faceted CDS.
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Stoupis, James D. "Dynamic testing of loss of field protection." Thesis, This resource online, 1996. http://scholar.lib.vt.edu/theses/available/etd-08292008-063410/.

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Ambrose, Joseph Paul. "Dynamic field theory applied to fMRI signal analysis." Diss., University of Iowa, 2016. https://ir.uiowa.edu/etd/2035.

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In the field of cognitive neuroscience, there is a need for theory-based approaches to fMRI data analysis. The dynamic neural field model-based approach has been developing to meet this demand. This dissertation describes my contributions to this approach. The methods and tools were demonstrated through a case study experiment on response selection and inhibition. The experiment was analyzed via both the standard behavioral approach and the new model-based method, and the two methods were compared head to head. The methods were quantitatively comparable at the individual-level of the analysis. At the group level, the model-based method reveals distinct functional networks localized in the brain. This validates the dynamic neural field model-based approach in general as well as my recent contributions.
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Guest, A. R. "The dynamic breakage of Kimberlite in the near field /." [St. Lucia, Qld.], 2004. http://www.library.uq.edu.au/pdfserve.php?image=thesisabs/absthe18507.pdf.

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Monson, Peter A. "Dynamic mean field theory for fluids in mesoporous materials." Universitätsbibliothek Leipzig, 2015. http://nbn-resolving.de/urn:nbn:de:bsz:15-qucosa-184643.

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Cook, Steven Charles. "Dynamic Near Field Communication Pairing For Wireless Sensor Networks." BYU ScholarsArchive, 2013. https://scholarsarchive.byu.edu/etd/3737.

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Wireless sensor network (WSN) nodes communicate securely using pre-installed cryptographic keys. Although key pre-installation makes nodes less expensive, the technical process of installing keys prevents average users from deploying and controlling their own WSNs. Wireless pairing enables users to set up WSNs without pre-installing keys, but current pairing techniques introduce numerous concerns regarding security, hardware expense, and usability. This thesis introduces dynamic Near Field Communication (NFC) pairing, a new pairing technique designed for WSNs. This pairing overcomes the limitations of both key pre-installation and current pairing techniques. Dynamic NFC pairing is as secure as using pre-installed keys, requires only inexpensive NFC hardware, and is easy to use since the user simply holds nodes close together to add them to a network. A sample application shows the power of dynamic NFC pairing. The user adds sensors and actuators to a WSN by holding each node close to a central node or network coordinator. Data readings stream instantly from each sensor to a web page where the user may view data as well as click buttons to cause events to occur on the actuators. This happens quickly and securely without exposing the user to the complexity of cryptographic keys.
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Gorman, Geoffrey Allen. "Field deployable dynamic lighting system for turbid water imaging." Thesis, Massachusetts Institute of Technology, 2011. http://hdl.handle.net/1721.1/68945.

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Thesis (S.M.)--Joint Program in Oceanography/Applied Ocean Science and Engineering (Massachusetts Institute of Technology, Dept. of Mechanical Engineering; and the Woods Hole Oceanographic Institution), September 2011.
"September 2011." "©2011"--P. 2. Cataloged from PDF version of thesis.
Includes bibliographical references (p. 97-101).
The ocean depths provide an ever changing and complex imaging environment. As scientists and researches strive to document and study more remote and optically challenging areas, specifically scatter-limited environments. There is a requirement for new illumination systems that improve both image quality and increase imaging distance. One of the most constraining optical properties to underwater image quality are scattering caused by ocean chemistry and entrained organic material. By reducing the size of the scatter interaction volume, one can immediately improve both the focus (forward scatter limited) and contrast (backscatter limited) of underwater images. This thesis describes a relatively simple, cost-effective and field-deployable low-power dynamic lighting system that minimizes the scatter interaction volume with both subjective and quantifiable improvements in imaging performance.
by Geoffrey Allen Gorman.
S.M.
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Monson, Peter A. "Dynamic mean field theory for fluids in mesoporous materials." Diffusion fundamentals 16 (2011) 13, S. 1-2, 2011. https://ul.qucosa.de/id/qucosa%3A13742.

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Wray, Thomas. "Developments in dynamic field gradient focusing : microfluidics and integration." Thesis, University of Liverpool, 2012. http://livrepository.liverpool.ac.uk/7973/.

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Advances in modern science require the development of more robust and improved systems for electroseparations in chromatography. In response, the progress of a new analytical platform is discussed. DFGF (Dynamic Field Gradient Focusing) is a separation technique, first described in 1998, which exploits the differences in electrophoretic mobility and hydrodynamic area of analytes to result in separation. This is achieved by taking a channel and applying a hydrodynamic flow in one direction and a counteracting electric field gradient acting in the opposite direction, resulting in analytes reaching a focal point according to their electrophoretic mobility. Work through this project has seen innovations to improve existing DFGF devices, including the design and manufacture of a novel packing material, while developing the latest DFGF system. This incorporates a microfluidic separation channel, eliminating the need for packing material or monolith. The new microfluidic device also features whole-on-column UV detection. Improvements through the developments of this device are discussed, most notably the utilisation of a new rapid prototyping technique. Examples of applications undertaken with the new device are demonstrated including novel samples and integration with mass spectrometry and 2D-HPLC.
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Lomp, Oliver [Verfasser]. "Cognitive object recognition based on dynamic field theory / Oliver Lomp." München : Verlag Dr. Hut, 2017. http://d-nb.info/1140977741/34.

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Books on the topic "Dynamic field"

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Sørland, Geir Humborstad. Dynamic Pulsed-Field-Gradient NMR. Berlin, Heidelberg: Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-662-44500-6.

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Apaloo, Joseph, and Bruno Viscolani, eds. Advances in Dynamic and Mean Field Games. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-70619-1.

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Giese, Martin A. Dynamic Neural Field Theory for Motion Perception. Boston, MA: Springer US, 1999. http://dx.doi.org/10.1007/978-1-4615-5581-0.

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Giese, Martin A. Dynamic Neural Field Theory for Motion Perception. Boston, MA: Springer US, 1999.

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Giese, Martin A. Dynamic neural field theory for motion perception. Boston: Kluwer Academic Publishers, 1999.

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Roeder, C. W. Field measurements of dynamic wheel loads on modular expansion joints. [Olympia, Wash.]: Washington State Dept. of Transportation, 1995.

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Fortin, Jean Philippe. Analysis and comparison of field and laboratory dynamic rock properties. Sudbury, Ont: Laurentian University, School of Engineering, 2000.

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Holden, Jim. The Selling Fox: A Field Guide for Dynamic Sales Performance. New York: John Wiley & Sons, 2002.

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Holden, Jim. The selling fox: A field guide for dynamic sales performance. New York: Wiley, 2002.

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Oxford series in developmental cognitive neuroscience: A primer on dynamic field theory. New York: Oxford University Press, 2015.

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Book chapters on the topic "Dynamic field"

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Roehner, Bertrand M. "Dynamic random field models." In Advances in Spatial and Network Economics, 323–78. Berlin, Heidelberg: Springer Berlin Heidelberg, 1995. http://dx.doi.org/10.1007/978-3-642-79479-7_9.

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Fleet, Doreen. "The dynamic phenomenological field." In Pluralistic Sand-Tray Therapy, 37–50. London: Routledge, 2022. http://dx.doi.org/10.4324/9781003158707-4.

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Caines, Peter E., Minyi Huang, and Roland P. Malhamé. "Mean Field Games." In Handbook of Dynamic Game Theory, 1–28. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-27335-8_7-1.

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Caines, Peter E., Minyi Huang, and Roland P. Malhamé. "Mean Field Games." In Handbook of Dynamic Game Theory, 345–72. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-44374-4_7.

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Giannatempo, Giuseppe Maria, Tommaso Scarabino, Teresa Popolizio, Tullio Parracino, Ettore Serricchio, and Annalisa Simeone. "3.0 T Perfusion MRI Dynamic Susceptibility Contrast and Dynamic Contrast-Enhanced Techniques." In High Field Brain MRI, 113–31. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-44174-0_9.

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Van Meurs, G., D. Van Ree, H. Van De Velde, and W. Van Oosterom. "Flexible and Dynamic Site Investigation." In Field Screening Europe 2001, 113–17. Dordrecht: Springer Netherlands, 2002. http://dx.doi.org/10.1007/978-94-010-0564-7_18.

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Giese, Martin A. "Dynamic neural fields." In Dynamic Neural Field Theory for Motion Perception, 49–63. Boston, MA: Springer US, 1999. http://dx.doi.org/10.1007/978-1-4615-5581-0_4.

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Del Toro Iniesta, J. C. "Solar Polarimetry and Magnetic Field Measurements." In The Dynamic Sun, 183–209. Dordrecht: Springer Netherlands, 2001. http://dx.doi.org/10.1007/978-94-010-0760-3_7.

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Sørland, Geir Humborstad. "Analysis of Dynamic NMR Data." In Dynamic Pulsed-Field-Gradient NMR, 129–68. Berlin, Heidelberg: Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-662-44500-6_5.

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Melnikov, Nikolai B., and Boris I. Reser. "Mean-Field Theory." In Dynamic Spin-Fluctuation Theory of Metallic Magnetism, 35–43. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-92974-3_4.

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Conference papers on the topic "Dynamic field"

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Bailey, Donald G. "Streamed high dynamic range imaging." In 2012 International Conference on Field-Programmable Technology (FPT). IEEE, 2012. http://dx.doi.org/10.1109/fpt.2012.6412153.

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Ross, Charles, and Wim Bohm. "The Case for Dynamic Execution on Dynamic Hardware." In 15th Annual IEEE Symposium on Field-Programmable Custom Computing Machines (FCCM 2007). IEEE, 2007. http://dx.doi.org/10.1109/fccm.2007.10.

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Guneysu, Tim, Bodo Moller, and Christof Paar. "Dynamic Intellectual Property Protection for Reconfigurable Devices." In 2007 International Conference on Field-Programmable Technology. IEEE, 2007. http://dx.doi.org/10.1109/fpt.2007.4439246.

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Doboli, Alex, Patrick Kane, and Dave Van Ess. "Dynamic reconfiguration in a PSoC device." In 2009 International Conference on Field-Programmable Technology (FPT). IEEE, 2009. http://dx.doi.org/10.1109/fpt.2009.5377613.

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Zhang, Yinsheng. "Analysis on the Stochastic Dynamic Field." In 2019 IEEE 14th International Conference on Intelligent Systems and Knowledge Engineering (ISKE). IEEE, 2019. http://dx.doi.org/10.1109/iske47853.2019.9170342.

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Sahay, Pratap N. "Natural field variables in dynamic poroelasticity." In SEG Technical Program Expanded Abstracts 1994. Society of Exploration Geophysicists, 1994. http://dx.doi.org/10.1190/1.1822727.

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Mirrokni, Vahab, Renato Paes Leme, Rita Ren, and Song Zuo. "Dynamic Mechanism Design in the Field." In the 2018 World Wide Web Conference. New York, New York, USA: ACM Press, 2018. http://dx.doi.org/10.1145/3178876.3186041.

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Lang, Peter, Matthieu Michel, Neal Wade, Rolf Grunbaum, and Tomas Larsson. "Dynamic energy storage - Field operation experience." In 2013 IEEE Power & Energy Society General Meeting. IEEE, 2013. http://dx.doi.org/10.1109/pesmg.2013.6672820.

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Liu, Jinhua, Rui Fan, Hai Wang, Jianjun Liu, and Fei Wang. "Dynamic TDD Testbed and Field Measurements." In 2016 IEEE 83rd Vehicular Technology Conference (VTC Spring). IEEE, 2016. http://dx.doi.org/10.1109/vtcspring.2016.7504204.

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"DYNAMIC SENSOR NETWORKS: AN APPROACH TO OPTIMAL DYNAMIC FIELD COVERAGE." In 4th International Conference on Informatics in Control, Automation and Robotics. SciTePress - Science and and Technology Publications, 2007. http://dx.doi.org/10.5220/0001631202370242.

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Reports on the topic "Dynamic field"

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DeGiorgi, Virginia G. Stress Field Variations during Dynamic Loading. Fort Belvoir, VA: Defense Technical Information Center, October 1991. http://dx.doi.org/10.21236/ada242121.

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Nosochkov, Y., Y. Cai, M. H. Wang, /SLAC, S. Fartoukh, Massimo Giovannozzi, and /CERN. Initial Estimates of Dynamic Aperture and Field Quality Specifications. Office of Scientific and Technical Information (OSTI), September 2014. http://dx.doi.org/10.2172/1156650.

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Murray, A. B. Temporal Evolution of Ripple-Field Characteristics: A Defect-Dynamic Approach. Fort Belvoir, VA: Defense Technical Information Center, September 2005. http://dx.doi.org/10.21236/ada610260.

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Cummings, Molly E. Biological Response to the Dynamic Spectral-Polarized Underwater Light Field. Fort Belvoir, VA: Defense Technical Information Center, January 2010. http://dx.doi.org/10.21236/ada541131.

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Murray, A. B. Temporal Evolution of Ripple-Field Characteristics: A Defect-Dynamic Approach. Fort Belvoir, VA: Defense Technical Information Center, September 2005. http://dx.doi.org/10.21236/ada572568.

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Cummings, Molly E., Samir Ahmed, Heidi Dierssen, Alexander Gilerson, William F. Gilly, George Kattawar, Brad Seibel, and James Sullivan. Biological Response to the Dynamic Spectral-Polarized Underwater Light Field. Fort Belvoir, VA: Defense Technical Information Center, September 2013. http://dx.doi.org/10.21236/ada598460.

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Cummings, Molly E. Biological Response to the Dynamic Spectral-Polarized Underwater Light Field. Fort Belvoir, VA: Defense Technical Information Center, September 2011. http://dx.doi.org/10.21236/ada557141.

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Perdigão, Rui A. P. Earth System Dynamic Intelligence - ESDI. Meteoceanics, April 2021. http://dx.doi.org/10.46337/esdi.210414.

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Earth System Dynamic Intelligence (ESDI) entails developing and making innovative use of emerging concepts and pathways in mathematical geophysics, Earth System Dynamics, and information technologies to sense, monitor, harness, analyze, model and fundamentally unveil dynamic understanding across the natural, social and technical geosciences, including the associated manifold multiscale multidomain processes, interactions and complexity, along with the associated predictability and uncertainty dynamics. The ESDI Flagship initiative ignites the development, discussion and cross-fertilization of novel theoretical insights, methodological developments and geophysical applications across interdisciplinary mathematical, geophysical and information technological approaches towards a cross-cutting, mathematically sound, physically consistent, socially conscious and operationally effective Earth System Dynamic Intelligence. Going beyond the well established stochastic-dynamic, information-theoretic, artificial intelligence, mechanistic and hybrid techniques, ESDI paves the way to exploratory and disruptive developments along emerging information physical intelligence pathways, and bridges fundamental and operational complex problem solving across frontier natural, social and technical geosciences. Overall, the ESDI Flagship breeds a nascent field and community where methodological ingenuity and natural process understanding come together to shed light onto fundamental theoretical aspects to build innovative methodologies, products and services to tackle real-world challenges facing our planet.
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Isaju, Kazuyoshi, Naohiko Tsuru, Takahiro Wada, Yousuke Takahashi, Shun'ichi Doi, and Hiroshi Kaneko. Analysis of Dynamic Visual Field as a Visual Information While Driving. Warrendale, PA: SAE International, May 2005. http://dx.doi.org/10.4271/2005-08-0043.

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Depireux, Didier A., Jonathan Z. Simon, David J. Klein, and Shihab A. Shamma. Dynamics of Neural Responses in Ferret Primary Auditory Cortex: I. Spectro-Temporal Response Field Characterization by Dynamic Ripple Spectra. Fort Belvoir, VA: Defense Technical Information Center, January 1999. http://dx.doi.org/10.21236/ada439778.

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