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Author: Grafiati
Published: 25 May 2024

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1

Leissa, Arthur W. Vibrations of continuous systems. New York: McGraw-Hill, 2011.

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2

Reuter, Christoph. Modeling aspects for the vibration and dynamic stability of translating elastic continua. Homburg, Germany: Normed Verlag, 2000.

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3

Rosen, I. Gary. Spline-based Rayleigh-Ritz methods for the approximation of the natural modes of vibration for flexible beams with tip bodies. Hampton, Va: Institute for Computer Applications in Science and Engineering, NASA Langley Research Center, 1985.

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4

Zhongguo qi che gong cheng xue hui. Proceedings of the FISITA 2012 World Automotive Congress: Volume 5: Advanced Transmission System and Driveline. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013.

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5

Guyader, Jean-Louis. Vibrations des milieux continus. HERMES SCIENCE, 2002.

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6

Guyader, Jean-Louis. Vibration in Continuous Media. Wiley & Sons, Incorporated, John, 2013.

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7

Vibration in Continuous Media. ISTE Publishing Company, 2006.

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8

Guyader, Jean-Louis. Vibration in Continuous Media. Wiley & Sons, Incorporated, John, 2013.

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9

Guyader, Jean-Louis. Vibration in Continuous Media. Wiley & Sons, Incorporated, John, 2013.

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10

Guyader, Jean-Louis. Vibration in Continuous Media. Wiley & Sons, Incorporated, John, 2013.

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11

Guyader, Jean-Louis. Vibration in Continuous Media. Wiley & Sons, Limited, John, 2006.

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12

Vibration Problems Icovp 2011 The 10th International Conference On Vibration Problems. Springer, 2011.

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13

Dasgupta, Anirvan, and Peter Hagedorn. Vibrations and Waves in Continuous Mechanical Systems. Wiley & Sons, Incorporated, John, 2007.

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14

Hagedorn, Peter, and Anirvan DasGupta. Vibrations and Waves in Continuous Mechanical Systems. Wiley & Sons, Incorporated, John, 2007.

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15

Vibrations and Waves in Continuous Mechanical Systems. Wiley, 2007.

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16

Hagedorn, Peter, and Anirvan DasGupta. Vibrations and Waves in Continuous Mechanical Systems. Wiley & Sons, Limited, John, 2007.

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17

ashrafizade, ali, Andrei L. Smirnov, and David J. Steigmann. Advances in Mechanics of Solids: In Memory of Professor E. M. Haseganu (Series on Stability, Vibration and Control of Systems). World Scientific Publishing Company, 2006.

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18

Vibration Problems Icovp 2007 Springer Proceedings in Physics Hardcover. Springer, 2008.

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19

Pedley, Timothy J., and Peter W. Carpenter. Flow Past Highly Compliant Boundaries and in Collapsible Tubes: Proceedings of the IUTAM Symposium Held at the University of Warwick, United Kingdom, 26-30 March 2001. Springer, 2013.

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20

Flow Past Highly Compliant Boundaries and in Collapsible Tubes: Proceedings Of The Iutam Symposium Held At The University Of Warwick, United Kingdom, . . . 2001. Springer, 2011.

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21

Tanasescu, Andreea. Dimensiuni ale gandirii coregrafice. Timp, spatiu, miscare - Volumul 1. Editura Universitara, 2020. http://dx.doi.org/10.5682/9786062812133.

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Dansul - arta vie, complexa - poate fi, cu greu, introdus in cutia limbajului scris ori vorbit; semnul plat (litera) nu poate reda vibratia dansanta a vietii, la fel cum marea n-ar putea fi inchisa intr-o camera. Dansul contemporan este jocul cu spatiul, timpul, emotia, este un domeniu al cercetarii continue, o cercetare libera, un dialog dinamic al fortelor interioare si exterioare ale omului pentru a se descoperi pe sine sau, mai departe - pentru a ajunge in inima universului. Miscarea contine dimensiuni infinite, a le pune in cuvinte inseamna a risca… Dar poate ca, pentru memoria dansului, merita riscul - gestul coregrafic trebuie uneori condensat, descris prin cuvinte pentru a putea sa traiasca mai departe, la fel de liber. In dans, metafora capata trup, emotia devine spatiu, timp. Scenele se succed, iar in urma lor, din miscarea trupurilor, ne ramane visul. Miscarea este gand, elan, zbatere si, adesea, ne aduce in lumina sufletul. Omul in miscare demonstreaza ca este mai mult decat ceea ce pare, iar dansul devine un instrument revelator de meta-realitati.
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22

Spline-based Rayleigh-Ritz methods for the approximation of the natural modes of vibration for flexible beams with tip bodies. Hampton, Va: Institute for Computer Applications in Science and Engineering, NASA Langley Research Center, 1985.

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23

Anishchenko, Vadim S. S., Tatyana E. Vadivasova, and Galina I. Strelkova. Deterministic Nonlinear Systems: A Short Course. Springer, 2016.

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24

Phillips, William, and Brian Cogan. Encyclopedia of Heavy Metal Music. Greenwood Press, 2009. http://dx.doi.org/10.5040/9798400662614.

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It has been reviled, dismissed, attacked, and occasionally been the subject of Congressional hearings, but still, the genre of music known as heavy metal maintains not only its market share in the recording and downloading industry, but also as a cultural force that has united millions of young and old fans across the globe. Characterized by blaring distorted guitars, drum solos, and dramatic vibrato, the heavy metal movement headbanged its way to the popular culture landscape with bands like Led Zeppelin and Black Sabbath the 1970s. Motley Crue and Metallica made metal a music phenomenon in the 1980s. Heavy metal continues to evolve today with bands like Mastodon and Lamb of God. Providing an extensive overview of the music, fashion, films, and philosophies behind the movement, this inclusive encyclopedia chronicles the history and development of heavy metal, including sub-movements such as death metal, speed metal, grindcore, and hair metal. Essential and highly entertaining reading for high school and undergraduate courses in popular music studies, communications, media studies, and cultural studies, the Encyclopedia of Heavy Metal Music and Culture offers a guide to the ultimate underground music, exploring its rich cultural diversity, resilience, and adaptability. Entries for musicians include a discography for those wanting to start or develop their music collections.
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25

Fox, Raymond. The Use of Self. Oxford University Press, 2011. http://dx.doi.org/10.1093/oso/9780190616144.001.0001.

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This monograph presents recent advances in neural network (NN) approaches and applications to chemical reaction dynamics. Topics covered include: (i) the development of ab initio potential-energy surfaces (PES) for complex multichannel systems using modified novelty sampling and feedforward NNs; (ii) methods for sampling the configuration space of critical importance, such as trajectory and novelty sampling methods and gradient fitting methods; (iii) parametrization of interatomic potential functions using a genetic algorithm accelerated with a NN; (iv) parametrization of analytic interatomic potential functions using NNs; (v) self-starting methods for obtaining analytic PES from ab inito electronic structure calculations using direct dynamics; (vi) development of a novel method, namely, combined function derivative approximation (CFDA) for simultaneous fitting of a PES and its corresponding force fields using feedforward neural networks; (vii) development of generalized PES using many-body expansions, NNs, and moiety energy approximations; (viii) NN methods for data analysis, reaction probabilities, and statistical error reduction in chemical reaction dynamics; (ix) accurate prediction of higher-level electronic structure energies (e.g. MP4 or higher) for large databases using NNs, lower-level (Hartree-Fock) energies, and small subsets of the higher-energy database; and finally (x) illustrative examples of NN applications to chemical reaction dynamics of increasing complexity starting from simple near equilibrium structures (vibrational state studies) to more complex non-adiabatic reactions. The monograph is prepared by an interdisciplinary group of researchers working as a team for nearly two decades at Oklahoma State University, Stillwater, OK with expertise in gas phase reaction dynamics; neural networks; various aspects of MD and Monte Carlo (MC) simulations of nanometric cutting, tribology, and material properties at nanoscale; scaling laws from atomistic to continuum; and neural networks applications to chemical reaction dynamics. It is anticipated that this emerging field of NN in chemical reaction dynamics will play an increasingly important role in MD, MC, and quantum mechanical studies in the years to come.
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26

Raff, Lionel, Ranga Komanduri, Martin Hagan, and Satish Bukkapatnam. Neural Networks in Chemical Reaction Dynamics. Oxford University Press, 2012. http://dx.doi.org/10.1093/oso/9780199765652.001.0001.

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This monograph presents recent advances in neural network (NN) approaches and applications to chemical reaction dynamics. Topics covered include: (i) the development of ab initio potential-energy surfaces (PES) for complex multichannel systems using modified novelty sampling and feedforward NNs; (ii) methods for sampling the configuration space of critical importance, such as trajectory and novelty sampling methods and gradient fitting methods; (iii) parametrization of interatomic potential functions using a genetic algorithm accelerated with a NN; (iv) parametrization of analytic interatomic potential functions using NNs; (v) self-starting methods for obtaining analytic PES from ab inito electronic structure calculations using direct dynamics; (vi) development of a novel method, namely, combined function derivative approximation (CFDA) for simultaneous fitting of a PES and its corresponding force fields using feedforward neural networks; (vii) development of generalized PES using many-body expansions, NNs, and moiety energy approximations; (viii) NN methods for data analysis, reaction probabilities, and statistical error reduction in chemical reaction dynamics; (ix) accurate prediction of higher-level electronic structure energies (e.g. MP4 or higher) for large databases using NNs, lower-level (Hartree-Fock) energies, and small subsets of the higher-energy database; and finally (x) illustrative examples of NN applications to chemical reaction dynamics of increasing complexity starting from simple near equilibrium structures (vibrational state studies) to more complex non-adiabatic reactions. The monograph is prepared by an interdisciplinary group of researchers working as a team for nearly two decades at Oklahoma State University, Stillwater, OK with expertise in gas phase reaction dynamics; neural networks; various aspects of MD and Monte Carlo (MC) simulations of nanometric cutting, tribology, and material properties at nanoscale; scaling laws from atomistic to continuum; and neural networks applications to chemical reaction dynamics. It is anticipated that this emerging field of NN in chemical reaction dynamics will play an increasingly important role in MD, MC, and quantum mechanical studies in the years to come.
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