Literatura académica sobre el tema "Magnetic Model Identification"
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Artículos de revistas sobre el tema "Magnetic Model Identification"
Shabani, R., S. Tariverdilo y H. Salarieh. "Nonlinear identification of electro-magnetic force model". Journal of Zhejiang University SCIENCE A 11, n.º 3 (12 de febrero de 2010): 165–74. http://dx.doi.org/10.1631/jzus.a0900203.
Texto completoVa´zquez, J. A., E. H. Maslen, H. J. Ahn y D. C. Han. "Model Identification of a Rotor With Magnetic Bearings". Journal of Engineering for Gas Turbines and Power 125, n.º 1 (27 de diciembre de 2002): 149–55. http://dx.doi.org/10.1115/1.1499730.
Texto completoLin, C. E. y H. L. Jou. "Force model identification for magnetic suspension systems via magnetic field measurement". IEEE Transactions on Instrumentation and Measurement 42, n.º 3 (junio de 1993): 767–71. http://dx.doi.org/10.1109/19.231612.
Texto completoRugkwamsook, P. y C. E. Korman. "Identification of magnetic aftereffect model parameters: Temperature dependence". IEEE Transactions on Magnetics 34, n.º 4 (julio de 1998): 1863–65. http://dx.doi.org/10.1109/20.706728.
Texto completoArmando, Eric, Radu Iustin Bojoi, Paolo Guglielmi, Gianmario Pellegrino y Michele Pastorelli. "Experimental Identification of the Magnetic Model of Synchronous Machines". IEEE Transactions on Industry Applications 49, n.º 5 (septiembre de 2013): 2116–25. http://dx.doi.org/10.1109/tia.2013.2258876.
Texto completoPellegrino, Gianmario, Barbara Boazzo y Thomas M. Jahns. "Magnetic Model Self-Identification for PM Synchronous Machine Drives". IEEE Transactions on Industry Applications 51, n.º 3 (mayo de 2015): 2246–54. http://dx.doi.org/10.1109/tia.2014.2365627.
Texto completoHall, Sebastian, Francisco J. Marquez-Fernandez y Mats Alakula. "Dynamic Magnetic Model Identification of Permanent Magnet Synchronous Machines". IEEE Transactions on Energy Conversion 32, n.º 4 (diciembre de 2017): 1367–75. http://dx.doi.org/10.1109/tec.2017.2704114.
Texto completoZiolkowski, Marek, Hartmut Brauer y Milko Kuilekov. "Interface identification in magnetic fluid dynamics". Serbian Journal of Electrical Engineering 1, n.º 1 (2003): 61–69. http://dx.doi.org/10.2298/sjee0301061z.
Texto completoLi, Guoxin, Zongli Lin, Paul E. Allaire y Jihao Luo. "Modeling of a High Speed Rotor Test Rig With Active Magnetic Bearings". Journal of Vibration and Acoustics 128, n.º 3 (2 de diciembre de 2005): 269–81. http://dx.doi.org/10.1115/1.2172254.
Texto completoMofidian, S. M. Mahdi y Hamzeh Bardaweel. "Theoretical study and experimental identification of elastic-magnetic vibration isolation system". Journal of Intelligent Material Systems and Structures 29, n.º 18 (10 de julio de 2018): 3550–61. http://dx.doi.org/10.1177/1045389x18783869.
Texto completoTesis sobre el tema "Magnetic Model Identification"
Wroblewski, Adam C. "Model Identification, Updating, and Validation of an Active Magnetic Bearing High-Speed Machining Spindle for Precision Machining Operation". Cleveland State University / OhioLINK, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=csu1318379242.
Texto completoMendes, Tiago. "Identification of the modulators of and the molecular pathways involved in the BIN1-Tau interaction". Thesis, Lille 2, 2018. http://www.theses.fr/2018LIL2S033/document.
Texto completoThe main neuropathological hallmarks of Alzheimer’s disease (AD) are the extracellular senile plaques composed of amyloid-β peptide (Aβ) and the intracellular neurofibrillary tangles composed of hyperphosphorylated Tau. The mechanisms leading to the formation of these lesions is not well understood and our lab has recently characterized the bridging integrator 1 (BIN1) gene, the second most associated genetic risk factor of AD and the first genetic risk factor to have a potential link to Tau pathology. The interaction between BIN1 and Tau proteins has been described in vitro and in vivo, which suggests that BIN1 might help us to understand Tau pathology in the context of AD. However, the role of BIN1-Tau interaction in the pathophysiological process of AD is not known, and whether this interaction is a potential therapeutic target remains to be determined. The aim of this project is to better understand the actors of BIN1-Tau interaction through the identification of the modulators and the molecular pathways involved therein, as well as to understand how BIN1-Tau interaction is modulated in the context of AD. We employed biochemistry, nuclear magnetic resonance, and confocal microscopy. We used rat primary neuronal cultures (PNC) as the cellular model and developed the proximity ligation assay (PLA) as the main readout of the BIN1-Tau interaction in cultured neurons. We determined that the interaction occurs between BIN1’s SH3 domain and Tau’s PRD domain, and demonstrated that it is modulated by Tau and BIN1 phosphorylation: phosphorylation of Tau at Threonine 231 decreases its interaction with BIN1, while phosphorylation of BIN1 at Threonine 348 (T348) increases its interaction with Tau. We developed a novel, semi-automated high content screening (HCS) assay based on a commercial compound library, also using PNC as the cellular model and PLA as the readout of BIN1-Tau interaction. We identified several compounds that are able to modulate the BIN1-Tau interaction, most notably U0126, an inhibitor of MEK-1/2, which reduced the interaction, and Cyclosporin A, an inhibitor of Calcineurin, which increased the interaction through increasing the BIN1 phosphorylation at T348. Furthermore, Cyclin-dependent kinases (CDK) were also shown as regulator of this phosphorylation site. These results suggest that the couple Calcineurin/CDK regulates BIN1 phosphorylation at T348 and consequently the BIN1-Tau interaction. We also developed a mouse model of tauopathy in which we overexpressed human BIN1. We observed that the overexpression of BIN1 rescued the long-term memory deficits and reduced the presence of intracellular inclusions of phosphorylated Tau, caused by Tau overexpression, and this was associated with an increase of BIN1-Tau interaction. Also, using post-mortem human brain samples, we observed that the levels of the neuronal BIN1 isoform were decreased in AD brains, whereas the relative levels of BIN1 phosphorylated at T348 were increased, suggesting a compensatory mechanism. Altogether, this study demonstrated the complexity and the dynamics of BIN1-Tau interaction in neurons, revealed modulators of and molecular pathways potentially involved in this interaction, and showed that variations in BIN1 expression or activity have direct effects on learning and memory, possibly linked to the regulation of its interaction with Tau
Leplus, François. "Sur la modélisation numérique des transformateurs monophasé et triphasé : Application aux montages redresseurs et gradateurs". Lille 1, 1989. http://www.theses.fr/1989LIL10073.
Texto completoOlofsson, K. Erik J. "Nonaxisymmetric experimental modal analysis and control of resistive wall MHD in RFPs : System identification and feedback control for the reversed-field pinch". Doctoral thesis, KTH, Fusionsplasmafysik, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-94096.
Texto completoQC 20120508
Libros sobre el tema "Magnetic Model Identification"
Horing, Norman J. Morgenstern. Superfluidity and Superconductivity. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198791942.003.0013.
Texto completoCapítulos de libros sobre el tema "Magnetic Model Identification"
Honc, Daniel. "Modelling and Identification of Magnetic Levitation Model CE 152/Revised". En Advances in Intelligent Systems and Computing, 35–43. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-91192-2_4.
Texto completoCzerwiński, Kamil y Maciej Ławryńczuk. "Identification of Discrete-Time Model of Active Magnetic Levitation System". En Advances in Intelligent Systems and Computing, 599–608. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-60699-6_58.
Texto completoSzewczyk, Roman. "Two Step, Differential Evolution-Based Identification of Parameters of Jiles-Atherton Model of Magnetic Hysteresis Loops". En Advances in Intelligent Systems and Computing, 635–41. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-77179-3_60.
Texto completoAlaggio, R., F. Benedettini, F. D’Innocenzo, G. D’Ovidio, D. Sebastiani y D. Zulli. "Modal Identification of Superconducting Magnetic Levitating Bogie". En Conference Proceedings of the Society for Experimental Mechanics Series, 227–36. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-15248-6_24.
Texto completoZhou, Yujian, Jinhua She, Wangyong He, Danyun Li, Zhentao Liu y Yonghua Xiong. "On-Line Identification of Moment of Inertia for Permanent Magnet Synchronous Motor Based on Model Reference Adaptive System". En Intelligent Robotics and Applications, 492–98. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-27535-8_44.
Texto completoMartynenko, Gennadii y Volodymyr Martynenko. "Identification of Computational Models of the Dynamics of Gas Turbine Unit Rotors with Magnetic Bearings by Incomplete Data for Design Automation". En Lecture Notes in Networks and Systems, 451–63. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-66717-7_38.
Texto completoJanghel, Rekh Ram. "Deep-Learning-Based Classification and Diagnosis of Alzheimer's Disease". En Feature Dimension Reduction for Content-Based Image Identification, 193–217. IGI Global, 2018. http://dx.doi.org/10.4018/978-1-5225-5775-3.ch011.
Texto completoChong, Shin-Horng, Roong-Soon Allan Chan y Norhaslinda Hasim. "Enhanced Nonlinear PID Controller for Positioning Control of Maglev System". En Control Based on PID Framework - The Mutual Promotion of Control and Identification for Complex Systems. IntechOpen, 2021. http://dx.doi.org/10.5772/intechopen.96769.
Texto completo"Identification of strain energy function for magneto elastomer from pseudo pure shear test under the variance of magnetic field". En Constitutive Models for Rubber VI, 475–80. CRC Press, 2009. http://dx.doi.org/10.1201/noe0415563277-89.
Texto completoTsumori, F., H. Kotera y S. Ishikawa. "Identification of strain energy function for magneto elastomer from pseudo pure shear test under the variance of magnetic field". En Constitutive Models for Rubber VI, 459–64. CRC Press, 2009. http://dx.doi.org/10.1201/noe0415563277.ch75.
Texto completoActas de conferencias sobre el tema "Magnetic Model Identification"
Vázquez, José A., Eric H. Maslen, Hyeong-Joon Ahn y Dong-Chul Han. "Model Identification of a Rotor With Magnetic Bearings". En ASME Turbo Expo 2001: Power for Land, Sea, and Air. American Society of Mechanical Engineers, 2001. http://dx.doi.org/10.1115/2001-gt-0566.
Texto completoPratt, Richard L. y Andrew J. Petruska. "Magnetic Needle Steering Model Identification Using Expectation-Maximization". En 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE, 2019. http://dx.doi.org/10.1109/iros40897.2019.8968001.
Texto completoYu, Z. C., D. Wen y H. Y. Zhang. "The Identification Model of Magnetic Bearing Supporting System". En 2008 International Conference on Computer Science and Software Engineering. IEEE, 2008. http://dx.doi.org/10.1109/csse.2008.1324.
Texto completoZhang, Maoqing, Zhongcheng Yu, Haini Qu y Yong Sun. "The DTNN Identification Model of Magnetic Bearing Supporting System". En Proceedings of the International Conference. World Scientific Publishing Company, 2008. http://dx.doi.org/10.1142/9789812799524_0349.
Texto completoPellegrino, Gianmario, Barbara Boazzo y Thomas M. Jahns. "Magnetic Model Self-Identification for PM Synchronous machine drives". En 2014 International Conference on Optimization of Electrical and Electronic Equipment (OPTIM). IEEE, 2014. http://dx.doi.org/10.1109/optim.2014.6850934.
Texto completoOrtombina, L., D. Pasqualotto, F. Tinazzi y M. Zigliotto. "Magnetic Model Identification for Synchronous Reluctance Motors Including Transients". En 2019 IEEE Energy Conversion Congress and Exposition (ECCE). IEEE, 2019. http://dx.doi.org/10.1109/ecce.2019.8913164.
Texto completoConway, R., S. Felix y R. Horowitz. "Parametric Uncertainty Identification and Model Reduction for Dual-Stage Robust H2 Track-following Control Synthesis". En 2006 Asia-Pacific Magnetic Recording Conference. IEEE, 2006. http://dx.doi.org/10.1109/apmrc.2006.365907.
Texto completoSun, Zhe, Jingjing Zhao, Zhengang Shi y Suyuan Yu. "Identification of Flexible Rotor Suspended by Magnetic Bearings". En 2013 21st International Conference on Nuclear Engineering. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/icone21-16220.
Texto completoMiranda, Jherson A. y Edgar A. Manzano. "Parametric Identification of an Active Magnetic Bearing System Using NARMAX Model". En 2020 IEEE XXVII International Conference on Electronics, Electrical Engineering and Computing (INTERCON). IEEE, 2020. http://dx.doi.org/10.1109/intercon50315.2020.9220203.
Texto completoArmando, E., R. Bojoi, P. Guglielmi, G. Pellegrino y M. Pastorelli. "Experimental methods for synchronous machines evaluation by an accurate magnetic model identification". En 2011 IEEE Energy Conversion Congress and Exposition (ECCE). IEEE, 2011. http://dx.doi.org/10.1109/ecce.2011.6063994.
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