Academic literature on the topic 'Accelerating methods'
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Journal articles on the topic "Accelerating methods"
Papadrakakis, M. "Accelerating Vector Iteration Methods." Journal of Applied Mechanics 53, no. 2 (June 1, 1986): 291–97. http://dx.doi.org/10.1115/1.3171754.
Full textHustoft, Hanne Kolsrud, Leon Reubsaet, Tyge Greibrokk, Elsa Lundanes, and Helle Malerod. "Critical assessment of accelerating trypsination methods." Journal of Pharmaceutical and Biomedical Analysis 56, no. 5 (December 2011): 1069–78. http://dx.doi.org/10.1016/j.jpba.2011.08.013.
Full textGalletti, Mario, Maria Pia Anania, Sahar Arjmand, Angelo Biagioni, Gemma Costa, Martina Del Giorno, Massimo Ferrario, et al. "Advanced Stabilization Methods of Plasma Devices for Plasma-Based Acceleration." Symmetry 14, no. 3 (February 24, 2022): 450. http://dx.doi.org/10.3390/sym14030450.
Full textPatra, Tarak K. "Data-Driven Methods for Accelerating Polymer Design." ACS Polymers Au 2, no. 1 (December 28, 2021): 8–26. http://dx.doi.org/10.1021/acspolymersau.1c00035.
Full textOh, Se-Chang, Young-Bok Joo, Oh-Young Kwon, and Kyung-Moo Huh. "GPU Accelerating Methods for Pease FFT Processing." Journal of Institute of Control, Robotics and Systems 20, no. 1 (January 1, 2014): 37–41. http://dx.doi.org/10.5302/j.icros.2014.13.1960.
Full textUlhaq, Aman, Emma McCrory, and Eleni Besi. "Surgical Methods for Accelerating Orthodontic Tooth Movement." Orthodontic Update 13, no. 4 (October 2, 2020): 170–79. http://dx.doi.org/10.12968/ortu.2020.13.4.170.
Full textLi, Yu, Tao Zhang, Shuyu Sun, and Xin Gao. "Accelerating flash calculation through deep learning methods." Journal of Computational Physics 394 (October 2019): 153–65. http://dx.doi.org/10.1016/j.jcp.2019.05.028.
Full textKornfeld, Isaac. "Nonexistence of universally accelerating linear summability methods." Journal of Computational and Applied Mathematics 53, no. 3 (August 1994): 309–21. http://dx.doi.org/10.1016/0377-0427(94)90059-0.
Full textMoreno, Yenita, Ermiyati Ermiyati, Syurya Adi Pratama, and Suprasman Suprasman. "Evaluasi Time Schedule Menggunakan Network Planning (Studi Kasus: Pada Proyek Pembangunan Gedung Rawat Inap Kelas III Tahap III Rumah Sakit Umum Daerah Bangkinang, Riau)." INCODING: Journal of Informatics and Computer Science Engineering 3, no. 1 (April 26, 2023): 21–44. http://dx.doi.org/10.34007/incoding.v3i1.331.
Full textJain, Divya, Rashmi Bhardwaj, and Iqbal Ahmad. "Accelerating order of convergence using secant type methods." Journal of Interdisciplinary Mathematics 20, no. 2 (February 17, 2017): 417–26. http://dx.doi.org/10.1080/09720502.2015.1033845.
Full textDissertations / Theses on the topic "Accelerating methods"
Kerdreux, Thomas. "Accelerating conditional gradient methods." Thesis, Université Paris sciences et lettres, 2020. http://www.theses.fr/2020UPSLE002.
Full textThe Frank-Wolfe algorithms, a.k.a. conditional gradient algorithms, solve constrained optimization problems. They break down a non-linear problem into a series of linear minimization on the constraint set. This contributes to their recent revival in many applied domains, in particular those involving large-scale optimization problems. In this dissertation, we design or analyze versions of the Frank-Wolfe algorithms. We notably show that, contrary to other types of algorithms, this family is adaptive to a broad spectrum of structural assumptions, without the need to know and specify the parameters controlling these hypotheses
Dahlin, Johan. "Accelerating Monte Carlo methods for Bayesian inference in dynamical models." Doctoral thesis, Linköpings universitet, Reglerteknik, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-125992.
Full textBorde Riksbanken höja eller sänka reporäntan vid sitt nästa möte för att nå inflationsmålet? Vilka gener är förknippade med en viss sjukdom? Hur kan Netflix och Spotify veta vilka filmer och vilken musik som jag vill lyssna på härnäst? Dessa tre problem är exempel på frågor där statistiska modeller kan vara användbara för att ge hjälp och underlag för beslut. Statistiska modeller kombinerar teoretisk kunskap om exempelvis det svenska ekonomiska systemet med historisk data för att ge prognoser av framtida skeenden. Dessa prognoser kan sedan användas för att utvärdera exempelvis vad som skulle hända med inflationen i Sverige om arbetslösheten sjunker eller hur värdet på mitt pensionssparande förändras när Stockholmsbörsen rasar. Tillämpningar som dessa och många andra gör statistiska modeller viktiga för många delar av samhället. Ett sätt att ta fram statistiska modeller bygger på att kontinuerligt uppdatera en modell allteftersom mer information samlas in. Detta angreppssätt kallas för Bayesiansk statistik och är särskilt användbart när man sedan tidigare har bra insikter i modellen eller tillgång till endast lite historisk data för att bygga modellen. En nackdel med Bayesiansk statistik är att de beräkningar som krävs för att uppdatera modellen med den nya informationen ofta är mycket komplicerade. I sådana situationer kan man istället simulera utfallet från miljontals varianter av modellen och sedan jämföra dessa mot de historiska observationerna som finns till hands. Man kan sedan medelvärdesbilda över de varianter som gav bäst resultat för att på så sätt ta fram en slutlig modell. Det kan därför ibland ta dagar eller veckor för att ta fram en modell. Problemet blir särskilt stort när man använder mer avancerade modeller som skulle kunna ge bättre prognoser men som tar för lång tid för att bygga. I denna avhandling använder vi ett antal olika strategier för att underlätta eller förbättra dessa simuleringar. Vi föreslår exempelvis att ta hänsyn till fler insikter om systemet och därmed minska antalet varianter av modellen som behöver undersökas. Vi kan således redan utesluta vissa modeller eftersom vi har en bra uppfattning om ungefär hur en bra modell ska se ut. Vi kan också förändra simuleringen så att den enklare rör sig mellan olika typer av modeller. På detta sätt utforskas rymden av alla möjliga modeller på ett mer effektivt sätt. Vi föreslår ett antal olika kombinationer och förändringar av befintliga metoder för att snabba upp anpassningen av modellen till observationerna. Vi visar att beräkningstiden i vissa fall kan minska ifrån några dagar till någon timme. Förhoppningsvis kommer detta i framtiden leda till att man i praktiken kan använda mer avancerade modeller som i sin tur resulterar i bättre prognoser och beslut.
Lopes, Antonio Roldao. "Accelerating iterative methods for solving systems of linear equations using FPGAs." Thesis, Imperial College London, 2010. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.526401.
Full textGhadimi, Euhanna. "Accelerating Convergence of Large-scale Optimization Algorithms." Doctoral thesis, KTH, Reglerteknik, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-162377.
Full textQC 20150327
Singh, Karanpreet. "Accelerating Structural Design and Optimization using Machine Learning." Diss., Virginia Tech, 2020. http://hdl.handle.net/10919/104114.
Full textDoctor of Philosophy
This thesis presents an innovative application of artificial intelligence (AI) techniques for designing aircraft structures. An important objective for the aerospace industry is to design robust and fuel-efficient aerospace structures. The state of the art research in the literature shows that the structure of aircraft in future could mimic organic cellular structure. However, the design of these new panels with arbitrary structures is computationally expensive. For instance, applying standard optimization methods currently being applied to aerospace structures to design an aircraft, can take anywhere from a few days to months. The presented research demonstrates the potential of AI for accelerating the optimization of an aircraft structures. This will provide an efficient way for aircraft designers to design futuristic fuel-efficient aircraft which will have positive impact on the environment and the world.
Bryan, Paul David. "Accelerating microarchitectural simulation via statistical sampling principles." Diss., Georgia Institute of Technology, 2012. http://hdl.handle.net/1853/47715.
Full textParks, Paula L. "Moving at the speed of potential| A mixed-methods study of accelerating developmental students in a California community college." Thesis, Capella University, 2014. http://pqdtopen.proquest.com/#viewpdf?dispub=3611804.
Full textMost developmental community college students are not completing the composition sequence successfully. This mixed-methods study examined acceleration as a way to help developmental community college students complete the composition sequence more quickly and more successfully. Acceleration is a curricular redesign that includes challenging readings and assignments and reduces the number of required classes in the developmental composition sequence. Developmental students taking an accelerated composition class at the California community college studied were as successful as developmental students taking the traditional segmented basic skills course. Students who pass the accelerated course skip a developmental class and are eligible to take the college-level course, which saves them time and money. The students who were interviewed cited the main factors leading to their success: the academic support from faculty, academic support from fellow students, the personality/caring of the teacher, and an interest in the class theme. Data were from the first semester the college offered this class. Findings from the study indicate that the college studied should continue offering accelerated composition classes and should encourage attendance at professional development meetings so that all parts of the accelerated curriculum will be implemented in the future. Implementing all parts of the accelerated curriculum may increase the success rates. The college studied should also re-examine its traditional basic skills curriculum and the timed writing departmental final exam, which causes unnecessary stress and lowers expectations. More effort could be made to include readings from minority authors and to provide support, such as through learning communities.
O'Brien, Gerard. "Comparison and evaluation of United Nations and ARC based test methods for the determination of self-accelerating decomposition temperatures." Thesis, London South Bank University, 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.388169.
Full textDrzisga, Daniel [Verfasser], Barbara [Akademischer Betreuer] Wohlmuth, Matthias [Gutachter] Möller, Barbara [Gutachter] Wohlmuth, and Giancarlo [Gutachter] Sangalli. "Accelerating Isogeometric Analysis and Matrix-free Finite Element Methods Using the Surrogate Matrix Methodology / Daniel Drzisga ; Gutachter: Matthias Möller, Barbara Wohlmuth, Giancarlo Sangalli ; Betreuer: Barbara Wohlmuth." München : Universitätsbibliothek der TU München, 2020. http://d-nb.info/122693434X/34.
Full textMacedo, Alves de Lima Jean. "Développement et validation d'un nouveau critère de déformation progressive pour les REPs." Electronic Thesis or Diss., Ecully, Ecole centrale de Lyon, 2023. http://www.theses.fr/2023ECDL0011.
Full textDuring the design, construction and operation of a nuclear component, it is necessary to ensure its integrity whatever the operating conditions : nominal or accidental. The demonstration of the components’ resistance of the primary and secondary circuits to failure modes is necessary in order to validate the design of these structures. Among the possible failure modes is the phenomenon of ratcheting. The ratcheting check of nuclear power plant structures is mainly investigated by means of simplified methods or a complete inelastic analysis. Nevertheless, these methods are either conservatives or complex to use and implement. In this context, the aim of this thesis is to develop a new industrial design rule and/or new calculation methodology that is applicable to complex structures.The first chapter is addressed to the state of the art, in particular to the ratcheting phenomenon. The second chapter presents the modeling of metallic materials and the numerical methods to simulate cyclic calculations. We propose a new method for accelerating cyclic calculations in order to make the step-by-step integration method faster.The third chapter is devoted to the modeling of COTHAA tests. Constitutive models are evaluated in order to propose a robust model capable of simulating ratcheting. Results predicted by a simplified version of Chaboche model are found in good agreement as compared to experimental measurements. We also show the ability of the new acceleration method to simulate these tests. The fourth chapter is dedicated to the experimental study. We propose a new structural ratcheting test: the DEFPROG test. Secondly, we validate the model proposed in the third chapter on these experimental results. The fifth and last chapter is devoted to the proposal of the new design rule to forecast the risk of ratcheting. We propose and validate a new simplified method, while relying on experimental results and modeling
Books on the topic "Accelerating methods"
Tan, Yao-Hua. Accelerating global supply chains with IT-innovation: ITAIDE tools and methods. Heidelberg: Springer, 2011.
Find full textR, Cutler Neal, ed. Accelerating CNS drug development. Chichester: John Wily & Sons, 1998.
Find full textAccelerated learning in practice: Brain-based methods for accelerating motivation and achievement. Stafford: Network Educational Press, 2001.
Find full textAccelerated learning in practice: Brain-based methods for accelerating motivation and achievement. Stafford: Network Educational Press, 1998.
Find full textSlomski, J. F. Effectiveness of multigrid in accelerating convergence of multidimensional flows in chemical nonequilibrium. New York: American Institute of Aeronautics and Astronautics, 1990.
Find full textProch, D. Transparencies from the Workshop on Thin Film Coating Methods for Superconducting Accelerating Cavities. Hamburg: Deutsches Elektronen-Synchrotron DESY, MHF-SL Group, 2000.
Find full textMoyer, Brian. Aggregation issues in integrating and accelerating BEA's accounts: Improved methods for calculating GDP by industry. Cambridge, MA: National Bureau of Economic Research, 2005.
Find full textMaxwell, Wendy. Accelerating fluency: A holistic approach to the teaching of French through the integration of the gesture approach, drama and music. Bowen Island, B.C: Muffin Rhythm Co., 2003.
Find full textYu, Wenhua. Advanced FDTD methods: Parallelization, acceleration, and engineering applications. Boston: Artech House, 2011.
Find full textValcartier, Canada Defence Research Establishment. Acceleration-Invariant Approximation Method For Recursive Digital Filters. S.l: s.n, 1985.
Find full textBook chapters on the topic "Accelerating methods"
Robert, Christian P., and George Casella. "Controlling and Accelerating Convergence." In Introducing Monte Carlo Methods with R, 89–124. New York, NY: Springer New York, 2009. http://dx.doi.org/10.1007/978-1-4419-1576-4_4.
Full textLiu, Jianwei, Wout Hofman, and Yao-Hua Tan. "Procedure Redesign Methods." In Accelerating Global Supply Chains with IT-Innovation, 223–53. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-15669-4_13.
Full textTeixeira, Cristina C., Edmund Khoo, and Mani Alikhani. "Different Methods of Accelerating Tooth Movement." In Clinical Guide to Accelerated Orthodontics, 19–31. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-43401-8_2.
Full textZhang, Pei. "Analysis Methods for Beam Position Extraction from HOM." In Beam Diagnostics in Superconducting Accelerating Cavities, 43–60. Cham: Springer International Publishing, 2013. http://dx.doi.org/10.1007/978-3-319-00759-5_4.
Full textBenvenuti, C., Ph Bernard, D. Bloess, E. Chiaveri, C. Hauviller, and W. Weingarten. "Various Methods of Manufacturing Superconducting Accelerating Cavities." In A Cryogenic Engineering Conference Publication, 885–93. Boston, MA: Springer US, 1996. http://dx.doi.org/10.1007/978-1-4613-0373-2_114.
Full textFasman, Kenneth H. "Managing Accelerating Data Growth in the Genome Database." In Theoretical and Computational Methods in Genome Research, 145–51. Boston, MA: Springer US, 1997. http://dx.doi.org/10.1007/978-1-4615-5903-0_11.
Full textBenner, Peter, Pablo Ezzatti, Enrique S. Quintana-Ortí, and Alfredo Remón. "Accelerating BST Methods for Model Reduction with Graphics Processors." In Parallel Processing and Applied Mathematics, 549–58. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-31464-3_56.
Full textMonza, Emanuele, Victor Gil, and Maria Fatima Lucas. "Computational Enzyme Design at Zymvol." In Methods in Molecular Biology, 249–59. New York, NY: Springer US, 2021. http://dx.doi.org/10.1007/978-1-0716-1826-4_13.
Full textRoodi, Meysam, and Andreas Moshovos. "SW+: On Accelerating Smith-Waterman Execution of GATK HaplotypeCaller." In Computational Intelligence Methods for Bioinformatics and Biostatistics, 133–41. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-63061-4_13.
Full textBokes, Pavol, Julia Klein, and Tatjana Petrov. "Accelerating Reactions at the DNA Can Slow Down Transient Gene Expression." In Computational Methods in Systems Biology, 44–60. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-60327-4_3.
Full textConference papers on the topic "Accelerating methods"
Madhukar, Kumar, Bjorn Wachter, Daniel Kroening, Matt Lewis, and Mandayam Srivas. "Accelerating invariant generation." In 2015 Formal Methods in Computer-Aided Design (FMCAD). IEEE, 2015. http://dx.doi.org/10.1109/fmcad.2015.7542259.
Full textShmueli, Yaniv, Gil Shabat, Amit Bermanis, and Amir Averbuch. "Accelerating Particle filter using multiscale methods." In 2012 IEEE 27th Convention of Electrical & Electronics Engineers in Israel (IEEEI 2012). IEEE, 2012. http://dx.doi.org/10.1109/eeei.2012.6377009.
Full textKamvar, Sepandar D., Taher H. Haveliwala, Christopher D. Manning, and Gene H. Golub. "Extrapolation methods for accelerating PageRank computations." In the twelfth international conference. New York, New York, USA: ACM Press, 2003. http://dx.doi.org/10.1145/775152.775190.
Full textTse, Anson H. T., David B. Thomas, and Wayne Luk. "Accelerating Quadrature Methods for Option Valuation." In 2009 17th IEEE Symposium on Field Programmable Custom Computing Machines. IEEE, 2009. http://dx.doi.org/10.1109/fccm.2009.36.
Full textAnwar Atif, Touheed, Uchenna Chukwu, Jesse Berwald, and Raouf Dridi. "Accelerating NISQ variational methods using geometry." In Quantum Computing, Communication, and Simulation III, edited by Philip R. Hemmer and Alan L. Migdall. SPIE, 2023. http://dx.doi.org/10.1117/12.2655793.
Full textWeinstock, Jan Henrik, Rainer Leupers, and Gerd Ascheid. "Accelerating MPSoC Simulation Using Parallel SystemC and Processor Sleep Models." In RAPIDO '17: Methods and Tools. New York, NY, USA: ACM, 2017. http://dx.doi.org/10.1145/3023973.3023975.
Full textKassahun, Yohannes, Jose de Gea, Mark Edgington, Jan Hendrik Metzen, and Frank Kirchner. "Accelerating neuroevolutionary methods using a Kalman filter." In the 10th annual conference. New York, New York, USA: ACM Press, 2008. http://dx.doi.org/10.1145/1389095.1389365.
Full textGholoobi, Amin, and Stavros Stavrou. "Accelerating TOA/TDOA packet based localization methods." In 2014 IEEE Conference on Wireless Sensors (ICWiSe). IEEE, 2014. http://dx.doi.org/10.1109/icwise.2014.7042657.
Full textMetsch, Jan-Henrik, Jonathan Neuhauser, Jerome Jouffroy, Taous-Meriem Laleg-Kirati, and Johann Reger. "Accelerating Extremum Seeking Convergence by Richardson Extrapolation Methods." In 2022 IEEE 61st Conference on Decision and Control (CDC). IEEE, 2022. http://dx.doi.org/10.1109/cdc51059.2022.9992618.
Full textLin, Hsien-I., and Chung-Sheng Cheng. "A study on accelerating convolutional neural networks." In PROCEEDINGS OF THE INTERNATIONAL CONFERENCE OF COMPUTATIONAL METHODS IN SCIENCES AND ENGINEERING 2019 (ICCMSE-2019). AIP Publishing, 2019. http://dx.doi.org/10.1063/1.5138068.
Full textReports on the topic "Accelerating methods"
Moyer, Brian, Marshall Reinsdorf, and Robert Yuskavage. Aggregation Issues in Integrating and Accelerating BEA's Accounts: Improved Methods for Calculating GDP by Industry. Cambridge, MA: National Bureau of Economic Research, January 2005. http://dx.doi.org/10.3386/w11073.
Full textAlexander, Francis, Tammie Borders, Angie Sheffield, and Marc Wonders. Workshop Report for Next-Gen AI for Proliferation Detection: Accelerating the Development and Use of Explainability Methods to Design AI Systems Suitable for Nonproliferation Mission Applications. Office of Scientific and Technical Information (OSTI), September 2020. http://dx.doi.org/10.2172/1768761.
Full textSands, Anna, Julia Turner, and Amrita Saha. Trade Policy for Sustainable and Inclusive Agriculture. Institute of Development Studies, January 2023. http://dx.doi.org/10.19088/ids.2023.010.
Full textNation, John A. Novel Methods of Acceleration. Fort Belvoir, VA: Defense Technical Information Center, September 1988. http://dx.doi.org/10.21236/ada204929.
Full textNation, John A. Novel Methods of Acceleration. Fort Belvoir, VA: Defense Technical Information Center, January 1993. http://dx.doi.org/10.21236/ada264828.
Full textRuggiero, A. Tracking of Acceleration with HNJ Method. Office of Scientific and Technical Information (OSTI), February 2008. http://dx.doi.org/10.2172/939969.
Full textRuggiero A. Tracking of Acceleration with HNJ Method. Office of Scientific and Technical Information (OSTI), February 2008. http://dx.doi.org/10.2172/1061891.
Full textBoyd, J. Spectral methods and sum acceleration algorithms. Final report. Office of Scientific and Technical Information (OSTI), March 1995. http://dx.doi.org/10.2172/52830.
Full textUrbatsch, T. J. Iterative acceleration methods for Monte Carlo and deterministic criticality calculations. Office of Scientific and Technical Information (OSTI), November 1995. http://dx.doi.org/10.2172/212566.
Full textMatsushima, Hirohide, Yoichi Jinja, and Ryo Suzuki. Development of Quantitative Evaluation Method of Acceleration Shock in Motorcycles. Warrendale, PA: SAE International, October 2005. http://dx.doi.org/10.4271/2005-32-0048.
Full text