Thèses sur le sujet « SIZE PREDICTION »
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Pandarum, Krishnavellie. « Size prediction for plus-size women's intimate apparel using a 3D body scanner ». Thesis, Nelson Mandela Metropolitan University, 2009. http://hdl.handle.net/10948/1153.
Texte intégralWong, Hing-sang Wilfred. « On the prediction of adult shortness and tallness ». Click to view the E-thesis via HKUTO, 2003. http://sunzi.lib.hku.hk/hkuto/record/B31971301.
Texte intégralOlesen, Mark Jørn. « Prediction of drop-size distributions based on ligament breakup ». Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1997. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp05/nq22488.pdf.
Texte intégralGomes, Pimentel Rogerio. « Measurement and Prediction of Droplet Size Distribution in Sprays ». Thesis, Université Laval, 2006. http://www.theses.ulaval.ca/2006/23623/23623.pdf.
Texte intégralGomes, Pimentel Rogério. « Measurement and prediction of droplet size distribution in sprays ». Doctoral thesis, Université Laval, 2006. http://hdl.handle.net/20.500.11794/18194.
Texte intégral黃慶生 et Hing-sang Wilfred Wong. « On the prediction of adult shortness and tallness ». Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2003. http://hub.hku.hk/bib/B31971301.
Texte intégralANDO, Hideki, et Yusuke TANAKA. « Register File Size Reduction through Instruction Pre-Execution Incorporating Value Prediction ». Institute of Electronics, Information and Communication Engineers, 2010. http://hdl.handle.net/2237/14941.
Texte intégralYao, Juncheng. « Characterization and Prediction of Water Droplet Size in Oil-Water Flow ». Ohio University / OhioLINK, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1470741069.
Texte intégralMoshgbar, Mojgan. « Prediction and real-time compensation of liner wear in cone crushers ». Thesis, Loughborough University, 1996. https://dspace.lboro.ac.uk/2134/27362.
Texte intégralTanaka, Yusuke, et Hideki Ando. « Reducing register file size through instruction pre-execution enhanced by value prediction ». IEEE, 2009. http://hdl.handle.net/2237/13892.
Texte intégralMichaels, Melissa A. « Quantitative Model for the Prediction of Hydrodynamic Size of Nonionic Reverse Micelles ». VCU Scholars Compass, 2006. http://scholarscompass.vcu.edu/etd/789.
Texte intégralAljandal, Waleed A. « Itemset size-sensitive interestingness measures for association rule mining and link prediction ». Diss., Manhattan, Kan. : Kansas State University, 2009. http://hdl.handle.net/2097/1119.
Texte intégralAhmad, Tameez. « Prediction of grain size composition of the armour coat in alluvial bed channels ». Thesis, University of Newcastle Upon Tyne, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.360275.
Texte intégralKumar, Senthil. « Earthquake size, recurrence and rupture mechanics of large surface-rupture earthquakes along the Himalayan Frontal Thrust of India / ». abstract and full text PDF (free order & ; download UNR users only), 2005. http://0-wwwlib.umi.com.innopac.library.unr.edu/dissertations/fullcit/3209126.
Texte intégral"August 2005." Includes bibliographical references. Online version available on the World Wide Web. Library also has microfilm. Ann Arbor, Mich. : ProQuest Information and Learning Company, [2005]. 1 microfilm reel ; 35 mm.
Hucal, Ivan Michael Brian. « Prediction of the size of unerupted canines and premolars in a northern Manitoban Aboriginal population ». Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2000. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape4/PQDD_0012/MQ53107.pdf.
Texte intégralKaonda, Mususu Kosta Mpongo. « Prediction of the recrystallised grain size distribution after deformation for the Nb free and model steel ». Thesis, University of Birmingham, 2017. http://etheses.bham.ac.uk//id/eprint/7680/.
Texte intégralOluyemi, Gbenga Folorunso. « Intelligent grain size profiling using neural network and application to sanding potential prediction in real time ». Thesis, Robert Gordon University, 2007. http://hdl.handle.net/10059/1258.
Texte intégralSushanta, Mitra. « Breakup Process of Plane Liquid Sheets and Prediction of Initial Droplet Size and Velocity Distributions in Sprays ». Thesis, University of Waterloo, 2001. http://hdl.handle.net/10012/931.
Texte intégralWang, Yanxin, et 王燕欣. « Hypoxic-ischemic injury in the neonatal rat model : prediction of irreversible infarction size by DiffusionWeighted MR Imaging ». Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2005. http://hub.hku.hk/bib/B35757577.
Texte intégralDonovan, James George. « Fracture Toughness Based Models for the Prediction of Power Consumption, Product Size, and Capacity of Jaw Crushers ». Diss., Virginia Tech, 2003. http://hdl.handle.net/10919/28544.
Texte intégralPh. D.
Wang, Yanxin. « Hypoxic-ischemic injury in the neonatal rat model prediction of irreversible infarction size by Diffusion Weighted MR Imaging / ». Click to view the E-thesis via HKUTO, 2005. http://sunzi.lib.hku.hk/hkuto/record/B35757577.
Texte intégralLindemann-Zutz, Karsten [Verfasser]. « Head size variation within broccoli (Brassica oleracea var. italica) plantings, causes and prediction for decision support / Karsten Lindemann-Zutz ». Hannover : Technische Informationsbibliothek und Universitätsbibliothek Hannover (TIB), 2015. http://d-nb.info/1078047472/34.
Texte intégralGilbert, Max [Verfasser], et Waltraud [Akademischer Betreuer] Schulze. « Prediction of protein-protein complexes by combining size exclusion chromatography and mass spectrometric analysis / Max Gilbert ; Betreuer : Waltraud Schulze ». Hohenheim : Kommunikations-, Informations- und Medienzentrum der Universität Hohenheim, 2021. http://nbn-resolving.de/urn:nbn:de:bsz:100-opus-19403.
Texte intégralViljoen, D. J. « Evaluation and performance prediction of cooling tower spray zones ». Thesis, Link to the online version, 2006. http://hdl.handle.net/10019/1286.
Texte intégralPriori, Daniel. « Comparison of neural network models applied to size prediction of atmospheric particles based on their two-dimensional light scattering patterns ». reponame:Repositório Institucional da UFSC, 2017. https://repositorio.ufsc.br/xmlui/handle/123456789/181236.
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A obtenção do tamanho projetado de partículas atmosféricas prismáticas é de imensa importância em diversos aspectos da vida prática. Partículas expelidas por erupções vulcânicas podem por em risco a aviação civil e militar. Cristais de gelo presentes em nuvens, dependendo de seu tamanho e formato, alteram as propriedades radiantes das nuvens que podem, por sua vez, afetar significativamente os modelos climáticos. Uma forma indireta de se obter informações sobre as partículas prismáticas é através da utilização de instrumentos que registram padrões bidimensionais de dispersão de luz. Estas imagens podem ser utilizadas para caracterizar uma partícula cristalina, fornecendo informações sobre tamanho, razão de proporção, forma, concavidade e rugosidade. Neste trabalho procurou-se aplicar técnicas de Aprendizado de Máquina, em especial alguns modelos de redes neurais artificiais e técnicas de análise de dados, de forma a encontrar um modelo que apresente um desempenho satisfatório na tarefa de predição do tamanho projetado das partículas cristalinas. Os modelos de redes neurais testados foram do tipo Feed Forward Multi-Layer Perceptron com regularização Bayesiana, as redes neurais do tipo Função de Base Radial, e as redes Deep Learning do tipo Autoencoders, a qual também foi aplicada com o propósito de redução dimensional. Também foram testadas as técnicas de análise de dados de redução dimensional utilizando Análise de Componentes Principais e invariância à rotação das imagens através da Transformada Rápida de Fourier. Os modelos apresentados foram aplicados a uma série de imagens e seus resultados comparados e analisados. O modelo desenvolvido que utiliza conceitos de Deep Learning com técnicas de Autoencoder foi aquele que obteve os melhores resultados (performance de 0.9914), em especial na predição de tamanho projetado para as partículas menores, as quais tiveram maiores dificuldades de predição nos outros modelos propostos nesse trabalho.
Abstract : Obtaining the projected size of atmospheric prismatic particles is of immense importance in many aspects of practical life. Particles expelled by volcanic eruptions may threat to civil and military aviation. Ice crystals present in clouds, depending on their size and shape, can modify the radiant properties of clouds that can significantly affect the climate models. An indirect way of obtaining information on prismatic particles is through the use of instruments that record two-dimensional light scattering patterns. These images can be used to characterize a crystalline particle, providing information on size, aspect ratio, shape, concavity and roughness. In this work we tried to apply Machine Learning techniques, especially some models of artificial neural networks and techniques of data analysis, in order to find a model that presents a satisfactory performance in the task of predicting the projected size of the crystalline particles. The models of neural networks tested were Feed Forward Multi-Layer Perceptron neural network with Bayesian regularization, Radial Basis Function neural network and Deep Learning network with Autoencoders, which was applied for dimensional reduction purpose as well. We also tested techniques of data dimensional reduction such as Principal Component Analysis and techniques for image rotation invariance such as the Fast Fourier Transform. The presented models were applied to a series of images and their results were compared and analysed. The developed model which used concepts of Deep Learning with techniques of Autoencoder was the one that obtained the best results (0.9914 of performance), and especially in the prediction of projected size of the smaller particles, which had greater difficulties of prediction when using the other models proposed in this work.
HARGUINDEGUY, MAITE. « Infrared thermography for freeze-drying applications : from ice crystal size prediction to primary drying process monitoring and design space determination ». Doctoral thesis, Politecnico di Torino, 2022. http://hdl.handle.net/11583/2959955.
Texte intégralNiazi, Erfan. « A Mesoscopic Model for Blood Flow Prediction Based on Experimental Observation of Red Blood Cell Interaction ». Thesis, Université d'Ottawa / University of Ottawa, 2018. http://hdl.handle.net/10393/38078.
Texte intégralFukuda, Jun. « Studies on development of analytical methods to quantify protein aggregates and prediction of soluble/insoluble aggregate-formation ». Kyoto University, 2015. http://hdl.handle.net/2433/199349.
Texte intégral0048
新制・課程博士
博士(農学)
甲第19025号
農博第2103号
新制||農||1030(附属図書館)
学位論文||H27||N4907(農学部図書室)
31976
京都大学大学院農学研究科応用生命科学専攻
(主査)教授 加納 健司, 教授 植田 和光, 教授 植田 充美
学位規則第4条第1項該当
Kabeel, Abdallah Mahmoud Bayoumi. « Nominal strength and size effect of quasi-brittle structures with holes ». Doctoral thesis, Universitat de Girona, 2015. http://hdl.handle.net/10803/289985.
Texte intégralLa principal contribució d'aquest treball és la dʼintroduïr un model analític capaç de generar diagrames de disseny que permeten obtenir la resistència nominal dʼestructures quasi-fràgils que continguin forats. Els models de zona cohesiva permeten predir la resistencia dʼestructures amb forats formades de materials quasi-fràgils amb una gran zona de procés de fallada confinada en un pla. Aquests models també són capaços de predir lʼefecte de la mida de lʼestructura en la resistència nominal. A mès els models de zona cohesiva són un dels pocs (o els únics) que consideren dʼuna manera explítica la llei cohesiva en la seva formulació. Per aquestes raons, la majoria de resultats presentats es basen en els models de zona cohesiva.
Duncan, Susan Cromwell. « Improving the prediction of differential item functioning : a comparison of the use of an effect size for logistic regression DIF and Mantel-Haenszel DIF methods ». Diss., Texas A&M University, 2003. http://hdl.handle.net/1969.1/5876.
Texte intégralMuhilambele, Vedasto Rutakorezibwa Muganyizi. « Measurement and prediction of capacity to reach for food through barriers in sheep and goats : effect of body size on horizontal and vertical reach in castrates and females ». Thesis, University of Reading, 1993. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.333543.
Texte intégralConn, Brian E. « Revealing the Magic in Silver Magic Number Clusters : The Development of Size-Evolutionary Patterns for Monolayer Coated Silver-Thiolate Nanoclusters ». University of Toledo / OhioLINK, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1481294367098454.
Texte intégralTaher, Leila. « Computational methods for splice site prediction ». [S.l.] : [s.n.], 2006. http://deposit.ddb.de/cgi-bin/dokserv?idn=978938631.
Texte intégralDurgin, Gregory David. « Advanced Site-Specific Propagation Prediction Techniques ». Thesis, Virginia Tech, 1998. http://hdl.handle.net/10919/36746.
Texte intégralMaster of Science
Parameswaran, Subramanian T. « Software for site specific propagation prediction ». Thesis, This resource online, 1994. http://scholar.lib.vt.edu/theses/available/etd-06232009-063433/.
Texte intégralBarnhart, Gregory J. « Predicting hail size using model vertical velocities ». Thesis, Monterey, Calif. : Naval Postgraduate School, 2008. http://bosun.nps.edu/uhtbin/hyperion-image.exe/08Mar%5FBarnhart.pdf.
Texte intégralThesis Advisor(s): Nuss, Wendell. "March 2008." Description based on title screen as viewed on April 25, 2008. Includes bibliographical references (p. 47-49). Also available in print.
Ferreira, Tatiele Dalfior 1988. « Developing a mathematical model for prediction of flammable gas cloud size based on CFD and response surface methodology = Desenvolvimento de um modelo matemático para prever o tamanho da nuvem de gás inflamável baseado em CFD e metodologia de superfície de resposta ». [s.n.], 2014. http://repositorio.unicamp.br/jspui/handle/REPOSIP/266122.
Texte intégralDissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Química
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Resumo: Este trabalho tem como objetivo desenvolver um modelo matemático capaz de prever o tamanho de nuvem de gás inflamável formada em uma típica plataforma de petróleo considerando condições reais de ventilação e de operação de uma planta de processo. Para tanto, foi realizado um estudo de dispersão de gás inflamável (gás natural) na plataforma em questão utilizando Fluidodinâmica Computacional (CFD). Os resultados deste estudo de dispersão serviram como base para a construção do modelo matemático utilizando Metodologia de Superfície de Resposta. Tal modelo permite o cálculo do tamanho de nuvem de gás inflamável no ambiente estudado usando duas variáveis principais: a taxa não-dimensional de vazamento (que contabiliza a relação entre a taxa de vazamento de gás e a taxa de ventilação na plataforma) e a direção adimensional de vazamento (que computa a relação entre as direções de vazamento de gás e do vento). O modelo desenvolvido mostrou-se eficaz, pois foi capaz de prever com considerável grau de confiabilidade os tamanhos de nuvem de gás inflamável quando comparados aos valores fornecidos por simulações com CFD
Abstract: This work proposes the development of a mathematical correlation for prediction of flammable gas cloud size in a typical offshore module. Real conditions regarding the ventilation and process plant operation were considered. A dispersion study of natural gas release in the module was conducted using Computational Fluid Dynamics (CFD) and the state of art as far as the gas dispersion modelling is concerned. A mathematical model was built based on the numerical results and Response Surface Methodology (RSM). The approach comprises into a single mathematical model the most relevant independent variables. The response surface curves calculate the flammable gas cloud volume as a function of the non-dimensional leak rate (that concerns the ventilation and the gas release rate) and the non-dimensional leak direction (which comprises the wind direction and the leak direction). The developed model had proved to be effective. It was able to predict flammable gas volume and good agreement with CFD results was observed
Mestrado
Sistemas de Processos Quimicos e Informatica
Mestra em Engenharia Química
Williams, Sheryl R. « Site-specific energy prediction for photovoltaic devices ». Thesis, Loughborough University, 2009. https://dspace.lboro.ac.uk/2134/28317.
Texte intégralIves, Charlotte. « Prediction of surgical site infections using spectrophotometry ». Thesis, University of Newcastle Upon Tyne, 2005. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.427284.
Texte intégralHuang, Bingding. « Improving protein docking with binding site prediction ». Doctoral thesis, [S.l. : s.n.], 2008. http://nbn-resolving.de/urn:nbn:de:bsz:14-ds-1216305428189-09951.
Texte intégralGibney, Matthew Joseph IV. « Predicting Package Defects : Quantification of Critical Leak Size ». Thesis, Virginia Tech, 2000. http://hdl.handle.net/10919/34857.
Texte intégralThe critical leak size is the size micro-defect that allows microbial penetration into the package. The critical leak size of air-filled defects was found to be 7 μm at all pressures tested. This size is considerably important to food packagers because this is when sterility of the package is lost. Previous leak studies have shown that the critical leak size for liquid-filled defects coincide with the threshold leak size and pressure. If this is in fact true, then air-filled defects should exhibit a larger critical leak size than the liquid-filled defects. In this study, air-filled defects were examined. A bioaerosol exposure chamber was used to test micro-defects, nickel microtubes of known diameters 2, 5, 7, 10, 20, and 50 μm hydraulic diameters, against pressure differentials of 0, -6.9, -13.8, and -34.5 kPa.
Master of Science
Good, Norman Markus. « Methods for estimating the component biomass of a single tree and a stand of trees using variable probability sampling techniques ». Thesis, Queensland University of Technology, 2001. https://eprints.qut.edu.au/37097/1/37097_Good_2001.pdf.
Texte intégralChan, Chi-fai, et 陳志輝. « Epigenetic modification site prediction : technical consideration and application ». Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2015. http://hdl.handle.net/10722/210159.
Texte intégralRichardson, Mark. « Errors in predicting snow's near-infrared optical grain size ». Thesis, University of Reading, 2014. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.625443.
Texte intégralEvans, Daniel Christopher. « Predicting Injection Site Drug Precipitation ». Diss., The University of Arizona, 2013. http://hdl.handle.net/10150/312666.
Texte intégralOnur, Emine Mercan. « PREDICTING THE PERMEABILITY OF SANDY SOILS FROM GRAIN SIZE DISTRIBUTIONS ». Kent State University / OhioLINK, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=kent1389550812.
Texte intégralCunningham, Gavin James. « Predicting entrainment of mixed size sediment grains by probabilistic methods ». Thesis, University of Aberdeen, 2000. http://digitool.abdn.ac.uk/R?func=search-advanced-go&find_code1=WSN&request1=AAIU122469.
Texte intégralWang, Rui. « Site-specific prediction and measurement of cotton fiber quality ». Diss., Mississippi State : Mississippi State University, 2004. http://library.msstate.edu/etd/show.asp?etd=etd-10122004-220250.
Texte intégralJohansson-Åkhe, Isak. « PePIP : a Pipeline for Peptide-Protein Interaction-site Prediction ». Thesis, Linköpings universitet, Institutionen för fysik, kemi och biologi, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-138411.
Texte intégralFoster, Eric D. « Acceptor splice site prediction in vertebrates using probabilistic models / ». Online version of thesis, 2007. http://hdl.handle.net/1850/4629.
Texte intégral