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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.
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Garment “fitting” from tailor-made to ready-to-wear clothing, has evolved over time. Ready to-wear and standardized sizes appeared in the middle 19th century. Today garment fitting is one of the most important criteria in the consumer buying decision making process. This is particularly so with “body hugging” garments, such as intimate apparel; or the bra that moulds the form of the wearer to produce “smooth” outer garment silhouettes. The South African bra retailer and manufacturers sizing charts are generally based upon body dimension data collected using traditional anthropometric methods. Professional measurers are not able to capture the hidden areas of the breast such as the inframmatory fold line, the volume, shape and contour of the breast using tape measures, calipers and other measuring devices. Traditional anthropometry also does not have the ability to systemically observe the bottom line of the breast base and extract accurate data on breast volume which are key factors in designing underwire bras and in the pattern making of the bra cup panels. Exploratory retail and consumer studies have indicated that consumers, notably plus size women, experience considerable problems and dissatisfaction with poorly fitting bras. There is therefore clearly a need in South Africa to conduct a 3D anthropometric study, focusing especially on the plus-sized women’s bra market segment, as there is very little or limited studies, to date, conduct for this market segment of the population. This pilot study collected 3D torso body measurement data from a convenient sample of 176 plus sized women, recruited from Playtex (Pty) Ltd. situated in Durban, KwaZulu Natal, South Africa. The study evaluates the 3D breast volume measurement data extraction process, using an expert system developed by [TC]2 integrated into the propriety NX12-3D full body scanner software and that taken using the traditional dress-makers tape-measure. The objective is to establish the relationship between the 3D torso and breast volume data measurement output as extracted by the expert system when compared to the South African bra manufacturers sizing chart, for use in pattern making for bra cup panel designs and in the designing of underwire bras for large breasted or plus size women. The results contained in this dissertation cannot be extrapolated to the larger population of South Africa and is limited to the 176 plus size women selected by Body Mass Index; recruited from KwaZulu Natal, South Africa.
2
Wong, 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.
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Olesen, 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.
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Gomes, Pimentel Rogerio. "Measurement and Prediction of Droplet Size Distribution in Sprays." Thesis, Université Laval, 2006. http://www.theses.ulaval.ca/2006/23623/23623.pdf.
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Gomes, Pimentel Rogério. "Measurement and prediction of droplet size distribution in sprays." Doctoral thesis, Université Laval, 2006. http://hdl.handle.net/20.500.11794/18194.
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黃慶生 and 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.
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ANDO, Hideki, and 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.
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Yao, 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.
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Moshgbar, Mojgan. "Prediction and real-time compensation of liner wear in cone crushers." Thesis, Loughborough University, 1996. https://dspace.lboro.ac.uk/2134/27362.
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In the comminution industry, cone crushers are widely used for secondary and subsequent stages of size reduction. For a given crusher, the achieved size reduction is governed by the closed-side setting. Hadfield Steel is commonly used to line the crushing members to minimize wear. Yet, liner wear caused by some rock types can still be excessive. Enlargement of discharge opening induced by wear of liners produces a drift in product size which, if unchecked, can lead to high volumes of re-circulating load. Alteration of closed-side setting is now commonly achieved via hydraulic means. However, compensation of liner wear still involves plant shut down and loss of production.
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Tanaka, Yusuke, and Hideki Ando. "Reducing register file size through instruction pre-execution enhanced by value prediction." IEEE, 2009. http://hdl.handle.net/2237/13892.
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Michaels, Melissa A. "Quantitative Model for the Prediction of Hydrodynamic Size of Nonionic Reverse Micelles." VCU Scholars Compass, 2006. http://scholarscompass.vcu.edu/etd/789.
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The sizes of nonionic reverse micelles were investigated as a function of the molecular structure of the surfactant, the type of oil, the total concentration of surfactant [NP], the ratio of NP4 to total surfactant (r), the water to surfactant molar ratio (ω), temperature, salt concentration, and polar phase. The basis of our investigation was nonylphenol polyethoxylates - NP4 and NP7. Micelle sizes were determined using dynamic light scattering (DLS). A central composite experimental design was used to quantitatively model reverse micelle size as a function of ω, [NP], and r. The model has demonstrated the capability of predicting the mean diameter of micelles from 4 to 13 nm with a precision of ± 2 nm as measured by DLS. This quantitative correlation between the size of reverse micelles and the synthetic variables provides the foundation for choosing experimental conditions to control reverse micelle size.
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Aljandal, 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.
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Ahmad, 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.
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Kumar, 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.
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Thesis (Ph. D.)--University of Nevada, Reno, 2005.<br>"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.
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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.
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Kaonda, 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/.
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Grain size refinement can be achieved by recrystallisation during hot deformation, with multiple deformation steps during rolling or forging being used to generate fine grain sizes. Whilst the mode (or average) grain size after recrystallisation can be determined from standard equations the full grain size distribution is required for predicting a range of mechanical properties. In this work an approach has been proposed to allow prediction of the full grain size distribution by varying the value of the D’ parameter value in the Dutta - Sellars equation developed to predict the recrystallised mode/average grain sizes. It has been found that D’ is a function of strain at high strain values (above 0.3) and the relative position of the grain size in the grain size range (D*). Results for recrystallised grain size distributions for a range of steel grades (including model Fe - Ni steels, commercial Nb-microalloyed plate and high alloy (9Cr) forging steel) with different initial grain sizes and following deformation to different deformation strains, show that the predictions give good agreement with the experimental data except for samples with larger mode grain sizes deformed to a strain of 0.15.
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Oluyemi, 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.
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Production of hydrocarbon from both consolidated and unconsolidated clastic reservoir rocks poses a risk of sand production especially if a well articulated programme of sand management strategy is not put in place to deal with the problem at the onset of field development. A well articulated programme of sand management would include sand production potential prediction in real time if it is going to be effective at all in achieving the goal of dealing with likely sand problem. Sanding potential prediction in real time is considered an element of sand management strategy that involves the evaluation of risk of sand failure/production and the prediction of the likely sand rate and volume to facilitate optimum design of both downhole and surface equipment especially as related to sand control. Sanding potential prediction is therefore very crucial to reducing costs of field developments to make hitherto unattractive development environments profitable. This undoubtedly will impact positively the present drive to increase worldwide production of hydrocarbon . Specifically, real time sanding potential prediction enables timely reservoir management decisions relating to the choice, design and installation of sand control methods. It is also an important input to sand monitoring and topside management. The current sanding potential prediction models in the industry are found to lack the robustness to predict sanding potential in real time. They also are unable to provide the functionality to track the grain size distributions of the sand producing formation and that of the produced sand. This functionality can be useful in the application of grain size distribution to sanding potential prediction. The scope of this work therefore covers the development of coupled models for grain size distribution and sanding potential predictions in real time. A previous work has introduced the use of a commercial neural network technique for grain size distribution prediction. This work has built upon this by using a purposefully coded neural network in conjunction with statistical techniques to develop a model for grain size distribution prediction in both horizontal and vertical directions and extending the application to failure analysis and prediction of strength and sanding potential in formation rocks. The theoretical basis for this work consists in the cross relationships between formation petrophysical properties and grain size distribution parameters on one hand and between grain size distribution parameters and formation strength parameters on the other hand. Hoek and Brown failure criterion, through an analytical treatment, serves as the platform for the development of the failure model, which is coupled to the grain size distribution and Unconfined Compressive Strength (UCS) models. The results obtained in this work have further demonstrated the application of neural network to grain size distribution prediction. They also demonstrate that grain size distribution information can be used in monitoring changes in formation strength and by extension, the formation movement within the failure envelope space especially during production from a reservoir formation.
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Sushanta, 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.
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Spray models are increasingly becoming the principal tools in the design and development of gas turbine combustors. Spray modeling requires a knowledge of the liquid atomization process, and the sizes and velocities of subsequently formed droplets as initial conditions. In order to have a better understanding of the liquid atomization process,the breakup characteristics of plane liquid sheets in co-flowing gas streams are investigated by means of linear and nonlinear hydrodynamic instability analyses. The liquid sheet breakup process is studied for initial sinuous and varicose modes of disturbance. It is observed that the sheet breakup occurs at half-wavelength intervals for an initial sinuous disturbance and at full-wavelength intervals for an initial varicose disturbance. It is also found that under certain operating conditions, the breakup process is dictated by the initial varicose disturbance compare to its sinuous counterpart. Further, the breakup process is studied for the combined mode and it is found that the sheet breakup occurs at half- or full-wavelength intervals depending on the proportion of the individual sinuous and varicose disturbances. In general, the breakup length decreases with the increase in the Weber number, gas-to-liquid velocity and density ratios. A predictive model of the initial droplet size and velocity distributions for the subsequently formed spray is also formulated here. The present model incorporates the deterministic aspect of spray formation by calculating the breakup length and the mass-mean diameter and the stochastic aspect by statistical means through the maximum entropy principle based on Bayesian entropy. The two sub-models are coupled together by the various source terms signifying the liquid-gas interaction and a prior distribution based on instability analysis, which provides information regarding the unstable wave elements on the two liquid-gas interfaces. Experimental investigation of the breakup characteristics of the liquid sheet is performed by a high speed CCD camera and the measurement of the initial droplet size and distributions is conducted by phase-Doppler interferometry. Good agreement of the theoretical breakup length with the experiment is obtained for a planar, an annular and a gas turbine nozzle. The predicted initial droplet size and velocity distributions show reasonably satisfactory agreement with experimental data for all the three types of nozzles. Hence this spray model can be utilized to predict the initial droplet size and velocity distributions in sprays, which can then be implemented as a front-end subroutine to the existing computer codes.
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Wang, Yanxin, and 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.
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Donovan, 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.
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There is little process control employed at aggregate crushing plants and essentially no optimization at the primary or jaw crushing stage. Jaw crusher selection is very dependent on the subjective judgment/experience of individuals, the characterization of rock material using inadequate and unrepresentative tests, and the desire to limit secondary breakage, resulting in the conservative selection and operation of jaw crushers. A method for predicting the power consumption, product size, and volumetric capacity of jaw crushers based on fracture toughness has been proposed in this study. A new fracture toughness test, the Edge Notched Disk Wedge Splitting test, has been developed and verified in order to rapidly assess the fracture toughness of six quarry rocks. A High Energy Crushing Test system has been used to simulate the operational settings of a jaw crusher so that comparison of fracture toughness, specific comminution energy, and breakage distribution could be performed. The results indicate that the specific comminution energy required to reduce a rock particle to a given size increases with fracture toughness. The breakage distribution has also been shown to be dependent upon fracture toughness as long as the elastic modulus is taken into account. Laboratory jaw crushing experiments show that the capacity of a jaw crusher is dependent upon fracture toughness and the elastic modulus. Models for the prediction of power consumption, breakage function/product size, and volumetric capacity have been developed based on these results. At the experimental level, the models were able to predict the specific comminution energy to within 1% and t10 (characteristic crushing parameter) to within 10%. Prediction of the product size distribution produced by a lab-scale jaw crusher, for four different rocks, was within ± 5% (in terms of percent passing). The models allow for the selection of a jaw crusher based on the nature of the rock being broken and the average amount of size reduction done on the feed material. The models can also be used to optimize feed and operational settings, as well to determine the product size produced for a given rock and reduction ratio.<br>Ph. D.
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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.
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Lindemann-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.
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Gilbert, Max [Verfasser], and 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.
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Viljoen, D. J. "Evaluation and performance prediction of cooling tower spray zones." Thesis, Link to the online version, 2006. http://hdl.handle.net/10019/1286.
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Priori, 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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Dissertação (mestrado) - Universidade Federal de Santa Catarina, Centro Tecnológico, Programa de Pós-Graduação em Ciência da Computação, Florianópolis, 2017.<br>Made available in DSpace on 2017-11-21T03:19:07Z (GMT). No. of bitstreams: 1
348590.pdf: 15855456 bytes, checksum: bd421609cb55782e75a869acf96bf852 (MD5)
Previous issue date: 2017<br>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.<br>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.
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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.
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Niazi, 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.
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In some species, including humans, red blood cells (RBCs) under low shear stress tend to clump together and form into regular stacks called rouleaux. These stacks are not static, and constantly move and break apart. This phenomenon is referred to as red blood cell aggregation and disaggregation. When modelled as a single liquid, blood behaves as a non-Newtonian fluid. Its viscosity varies, mainly due to the aggregation of RBCs. The aim of this research is to develop a mesoscale computational model for the simulation of RBCs in plasma. This model considers RBC interaction and aggregation to predict blood-flow characteristics such as viscosity, rouleaux size and velocity distribution.
In this work, the population-balance modelling (PBM) approach is utilized to model the RBC aggregation process. The PBM approach is a known method that is used for modelling agglomeration and breakage in two-phase flow fluid mechanics to find aggregate size. The PBM model is coupled to the incompressible Navier-Stokes equations for the plasma. Both models are numerically solved simultaneously. The population-balance equation has been used previously in a more restricted form, the Smoluchowski equation, to model blood viscosity, but it has never been fully coupled with the Navier-Stokes equation directly for the numerical modelling of blood flow. This approach results in a comprehensive model which aims to predict RBC aggregate size and their velocities for different flow configurations, as well as their effects on the apparent macro-scale viscosity.
The PBM approach does not treat the microscopic physics of aggregation directly but rather uses experimental correlations for aggregation and disaggregation rates to account for the effects of aggregation on the bulk. To find the aggregation rate, a series of experiments on RBC sedimentation due to gravity is designed. In these tests, aggregated RBCs (rouleaux) tend to settle faster than single RBCs and, due to low shear stresses, disaggregation is very low and can be neglected. A high-speed camera is used to acquire video-microscopic pictures of the process. The size of the aggregates and their velocities are extracted using image processing techniques. For image processing, a general Matlab program is developed which can analyze all the images and report the velocity and size distribution of rouleaux.
An experimental correlation for disaggregation rate is found using results from a previous steady-state Couette flow experiment. Aggregation and disaggregation rates from these experiments are used to complete the PBM model. Pressure-driven channel flow experiments are then used for the final validation of the model. Comparisons of the apparent viscosity of whole blood in previous experiments show reasonable agreement with the developed model. This model fills a gap between micro-scale and macro-scale treatments and should be more accurate than traditional macro-scale models while being cheaper than direct treatment of RBCs at the micro-scale.
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Fukuda, 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.
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Kyoto University (京都大学)<br>0048<br>新制・課程博士<br>博士(農学)<br>甲第19025号<br>農博第2103号<br>新制||農||1030(附属図書館)<br>学位論文||H27||N4907(農学部図書室)<br>31976<br>京都大学大学院農学研究科応用生命科学専攻<br>(主査)教授 加納 健司, 教授 植田 和光, 教授 植田 充美<br>学位規則第4条第1項該当
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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.
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The main contribution of this work is to introduce analytical models able to create simple design charts that would allow designers to quickly determine the strength of quasi-brittle structures containing circular holes. Cohesive Zone Models are an excellent tool to model quasi-brittle structures with holes in which a large failure process zone is confined in a plane. Also, the CZM is able to predict the effect of the structure size on its strength. Moreover, it is one of the few models (or the only model) that takes into account the material cohesive law explicitly. Therefore, most of the presented models in this work are based on the cohesive zone model.<br>La 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.
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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.
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Psychometricians and test developers use DIF analysis to determine if there is possible bias in a given test item. This study examines the conditions under which two predominant methods for determining differential item function compare with each other in item bias detection using an effect size statistic as the basis for comparison. The main focus of the present research was to test whether or not incorporating an effect size for LR DIF will more accurately detect DIF and to compare the utility of an effect size index across MH DIF and LR DIF methods. A simulation study was used to compare the accuracy of MH DIF and LR DIF methods using a p value or supplemented with an effect size. Effect sizes were found to increase the accuracy of DIF and the possibility of the detection of DIF across varying ability distributions, population distributions, and sample size combinations. Varying ability distributions and sample size combinations affected the detection of DIF, while population distributions did not seem to affect the detection of DIF.
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Muhilambele, 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.
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Conn, 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.
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Taher, Leila. "Computational methods for splice site prediction." [S.l.] : [s.n.], 2006. http://deposit.ddb.de/cgi-bin/dokserv?idn=978938631.
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Durgin, Gregory David. "Advanced Site-Specific Propagation Prediction Techniques." Thesis, Virginia Tech, 1998. http://hdl.handle.net/10919/36746.
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This thesis describes advanced techniques for site-specific propagation prediction. The need for accurate site-specific propagation is discussed in the context of current trends in the wireless industry. The first half of the report is dedicated to measuring and modeling continuous wave (CW) local-area path loss. Specifically, the text uses examples from a 5.85 GHz CW measurement campaign in and around suburban homes. Not only do these measurements demonstrate the validity of the original models and techniques presented in the thesis, but the results themselves may prove particularly useful for developing in-home wireless devices operating in the National Information Infrastructure band. This unlicensed spectrum was allocated in January of 1997 and holds promising applications for public and private telecommunications, home-based wireless internet, wireless local loops, and any number of wideband wireless applications.
There is an in-depth development of deterministic propagation prediction techniques in the latter half of the thesis. The use of geometrical optics for terrestrial microwave propagation is discussed as well as an overview of the numerous ray tracing techniques that exist in the literature. Finally, a new 3D ray launching method is presented which improves upon many of the existing ray tracing algorithms. The thesis demonstrates how this algorithm is capable of recovering very detailed channel information from a wideband deterministic propagation prediction.<br>Master of Science
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Parameswaran, Subramanian T. "Software for site specific propagation prediction." Thesis, This resource online, 1994. http://scholar.lib.vt.edu/theses/available/etd-06232009-063433/.
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Barnhart, 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.
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Thesis (M.S. in Meteorology)--Naval Postgraduate School, March 2008.<br>Thesis 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.
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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.
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Orientador: Sávio Souza Venâncio Vianna<br>Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Química<br>Made available in DSpace on 2018-08-24T13:25:34Z (GMT). No. of bitstreams: 1
Ferreira_TatieleDalfior_M.pdf: 4562241 bytes, checksum: 69c742236e806f040cfc237f2ba91cf4 (MD5)
Previous issue date: 2014<br>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<br>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<br>Mestrado<br>Sistemas de Processos Quimicos e Informatica<br>Mestra em Engenharia Química
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Williams, Sheryl R. "Site-specific energy prediction for photovoltaic devices." Thesis, Loughborough University, 2009. https://dspace.lboro.ac.uk/2134/28317.
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This thesis presents an energy prediction tool for photovoltaic (PV) modules, based on the measure-correlate-predict principle. The tool allows quantification of the impact of the different environmental factors influencing PV device efficiency for different sites as they deviate from standardised test conditions and combines their effects for energy yield prediction of different module technologies operating in different climates. Amongst these environmental influences, the impact of angle of incidence has been particularly under-researched. In this work, a systematic investigation of the influence of angle of incidence on PV module performance is realised. This is achieved using both short-term module characterisation and long-term energy yield measurement campaigns. A customised purpose built dual axis tracker for mounting paired sets of modules on a fixed south-facing, 45-degree tilted rack is used to investigate the differences in module performance. The quality and quantity of the composition of the incident irradiance is described for various sky conditions at high latitude locations. Furthermore, an understanding of the entangled effects on photocurrent of both the angle of incidence and spectral variation is presented. This is achieved by analysing data from a system developed especially in this work which integrates an instantaneous all-sky mapping of irradiance from a monochromatic CCD camera with precision measurements of small-aperture normal irradiance from a collimated pyranometer in the short-term measurement campaign. The proposed energy prediction tool is validated using long-term datasets from several locations and is compared to other current methods. This was conducted under the European-funded PV-Catapult and IP Performance projects. The tool's prediction uncertainty falls within the ±5% for crystalline and ±10% for thin films, which is the same accuracy as other methods and within the measurement uncertainty of outdoor measurements.
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Ives, 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.
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Huang, 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.
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Gibney, Matthew Joseph IV. "Predicting Package Defects: Quantification of Critical Leak Size." Thesis, Virginia Tech, 2000. http://hdl.handle.net/10919/34857.
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Threshold leak sizes and leak rates were calculated for a number of liquid food products exhibiting a wide range of surface tension and viscosity values. From this data, one can see that mathematically, under typical pressure differentials generated in food packages (less than or equal to ±34.5 kPa), a leak will never start through a 2 μm defect. The calculated leak rates were compared to calculated evaporation rates. The evaporation rate exceeds the leak rate at lower sized microholes (2, and 5 μm diameter) under typical pressure differentials found in food packages. If the liquid, typically aqueous in food products, is evaporating off faster than the leak itself, then there will be solids left behind that could effectively plug the leak.
<p>The 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.<br>Master of Science
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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.
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This thesis developed multistage sampling methods for estimating the aggregate biomass of selected tree components, such as leaves, branches, trunk and total, in woodlands in central and western Queensland. To estimate the component biomass of a single tree randomised branch sampling (RBS) and importance sampling (IS) were trialed. RBS and IS were found to reduce the amount of time
and effort to sample tree components in comparison with other standard destructive sampling methods such as ratio sampling, especially when sampling small components such as leaves and small twigs. However, RBS did not estimate leaf and small twig biomass to an acceptable
degree of precision using current methods for creating path selection probabilities. In addition to providing an unbiased estimate of tree component biomass, individual estimates were used for developing allometric regression equations. Equations based on large components
such as total biomass produced narrower confidence intervals than equations developed using
ratio sampling. However, RBS does not estimate small component biomass such as leaves and small wood components with an acceptable degree of precision, and should be mainly used in conjunction with IS for estimating larger component biomass. A whole tree was completely enumerated to set up a sampling space with which RBS could be evaluated under a number of scenarios. To achieve a desired precision, RBS sample size and
branch diameter exponents were varied, and the RBS method was simulated using both analytical and re-sampling methods. It was found that there is a significant amount of natural variation present when relating the biomass of small components to branch diameter, for example. This finding validates earlier decisions to question the efficacy of RBS for estimating small component biomass in eucalypt species. In addition, significant improvements can be made to increase the precision of RBS by increasing the number of samples taken, but more
importantly by varying the exponent used for constructing selection probabilities. To further evaluate RBS on trees with differing growth forms from that enumerated, virtual
trees were generated. These virtual trees were created using L-systems algebra. Decision rules for creating trees were based on easily measurable characteristics that influence a tree's growth and form. These characteristics included; child-to-child and children-to-parent branch diameter relationships, branch length and branch taper. They were modelled using probability
distributions of best fit. By varying the size of a tree and/or the variation in the model describing
tree characteristics; it was possible to simulate the natural variation between trees of similar size
and fonn. By creating visualisations of these trees, it is possible to determine using visual means whether RBS could be effectively applied to particular trees or tree species. Simulation also aided in identifying which characteristics most influenced the precision of RBS, namely, branch length and branch taper. After evaluation of RBS/IS for estimating the component biomass of a single tree, methods for estimating the component biomass of a stand of trees (or plot) were developed and evaluated. A sampling scheme was developed which incorporated both model-based and design-based
biomass estimation methods. This scheme clearly illustrated the strong and weak points
associated with both approaches for estimating plot biomass. Using ratio sampling was more efficient than using RBS/IS in the field, especially for larger tree
components. Probability proportional to size sampling (PPS) -size being the trunk diameter at breast height - generated estimates of component plot biomass that were comparable to those generated using model-based approaches. The research did, however, indicate that PPS is more precise than the use of regression prediction ( allometric) equations for estimating larger components such as trunk or total biomass, and the precision increases in areas of greater biomass. Using more reliable auxiliary information for identifying suitable strata would reduce the amount of within plot variation, thereby increasing precision. PPS had the added advantage
of being unbiased and unhindered by numerous assumptions applicable to the population of interest, the case with a model-based approach. The application of allometric equations in predicting the component biomass of tree species other than that for which the allometric was developed is problematic. Differences in wood density need to be taken into account as well as differences in growth form and within species variability, as outlined in virtual tree simulations. However, the development and application of allometric prediction equations in local species-specific contexts is more desirable than PPS.
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Chan, Chi-fai, and 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.
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Richardson, 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.
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Knowledge of snow's spatial distribution in terms of snow water equivalent (SWE) is important for hydrological forecasting, but current SWE products commonly disagree on regional scales. Assimilating passive microwave observations into a forecast from a physically-based snow model has been suggested to reduce or remove this disagreement, in which case the snow model must produce properties that are relevant to radiative transfer in snow. Here, the SNOWCAN model produces profiles of grain size for comparison with field measurements using contact probe spectroscopy and the impact of considering grain shape or conglomeration type (chain or cluster) is estimated. Prediction error in near-infrared optical grain size is estimated to be ±0.094 mm for all grains, or a possible best-case of ±0.083 mm if grain shape is included. The Helsinki University of Technology microwave radiative transfer model is used with the Cold Land Processes Experiment field data to make a preliminary estimate of the associated errors in simulated microwave brightness temperature difference, which is commonly used in SWE products such as Globsnow. Grain size error is associated with a ±5.1 K error and including grain shape, at best, reduces this error to ±4.5 K. Increasing stratigraphic detail by simulating more layers is an alternative method to reduce error, and layering error is found to increase linearly with snow depth. A single-layer simulation of 100 cm depth is associated with a ±8.7 K error relative to a pack described at the measurement resolution, whereas a 2-layer model is associated with a ±3.9 K error. Further work is required to determine the impact of grain: shape in the microwave regime, rather than the near infrared, but these results suggest that increased stratigraphic detail is a higher priority than including grain shape in order to improve the assimilation of passive microwave observations.
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Evans, Daniel Christopher. "Predicting Injection Site Drug Precipitation." Diss., The University of Arizona, 2013. http://hdl.handle.net/10150/312666.
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Administering drug therapy through the intravenous route ensures rapid, and complete, bioavailability, which can be critical in an emergency situation. However, bypassing all of its protective barriers leaves the body vulnerable to harm if the parenteral formulation becomes unstable when mixed with the blood. An example of this formulation instability is the precipitation of poorly water-soluble drugs after mixing with the blood's aqueous environment. This happens when parenteral formulations rely too heavily upon the solution pH, and excipients, to increase the drug solubility. This precipitation in the blood can damage venous cell membranes producing symptoms ranging from mild skin irritation to death. To screen potential drug formulations for problems such as injection site drug precipitation, pharmaceutical companies have traditionally used costly and time consuming animal studies. To reduce the amount of pre-clinical animal studies necessary to find an optimal IV formulation, an in vitro device to detect injection site drug precipitation is introduced. In addition to the device, software that simulates the dilution of a parenteral drug formulation with blood upon administration has been developed and is introduced. Both the device and software were tested on commercially available formulations plus one formulation currently in clinical trials. The results and capabilities of the new device were compared to those obtained using an earlier in vitro device. Finally, a robust model for early screening of injection site precipitation is developed using both the in vitro device and software.
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Onur, 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.
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Cunningham, 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.
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The bedload transport of mixed size sediment is an important process in river engineering. Bedload transport controls channel stability and has a significant bearing on the hydraulic roughness of the channel. The prediction of bedload transport traditionally relies upon defining some critical value of fluid force above which particles of a particular diameter are assumed to be put into transport. The suggestion here is that the transport of bed material is size dependent with large grains being more difficult to remove from the bed surface than small grains and that all grains of the same size start to move under identical conditions. While it is relatively straightforward to assess the forces required to engender transport in a bed of uniform size grains, it is not so simple where there are a number of different grain sizes present. Multitudinous experimental studies have revealed that where there are a number of grain sizes present, large grains tend to become mobilised under lower fluid forces and small grains mobilised under higher fluid forces than those required for beds of uniform material. These results led to the development of so-called hiding functions which are used to model the variation of particle mobility with its relative size within the mixture. These functions derive their name from the tendency of large grains to shelter smaller grains from the action of the flow. Determining the relative mobility of each fraction in a mixture under given hydraulic conditions is the key to predicting how the composition of the bed load will relate to that of the bed surface material. Experiments were carried out in a rectangular, glass sided channel, in a sediment recirculation mode, under varying hydraulic conditions with a set of six different sediment mixtures. Laser Doppler Anemometry (LDA) was used to attain instantaneous velocity measurements at a number of locations in the flow. A Laser Displacement Meter was used to measure the detailed topography of small sections of the bed surface. Novel analysis techniques facilitated the determination of the grain size distribution of the bed surface by a grid-by-number method. The minimum force required to entrain each grain could also be estimated by a grain pivoting analysis. This information represents the resistance of the bed grains to erosion by flowing water. With the critical conditions for the bed grains known, it is possible to estimate the proportion of each fraction entrained from the bed surface under given hydraulic conditions. To estimate the bedload composition it is first necessary to scale by the proportion each size comprises on the bed surface and then, by a function of grain diameter to account for size dependency of travel velocity. For mean hydraulic conditions the proportion of the bed mobilised can be simply determined by inspection of a cumulative distribution of critical conditions. In reality, although it may be possible to entrain some grains at the mean velocity/shear stress, the majority of transport may be anticipated to occur during high magnitude events. Turbulence may be incorporated by adopting a probabilistic approach to the prediction of grain entrainment. By considering the joint probability distribution of bed shear stress and critical shear stress, one may attain the probability of grain entrainment. Comparison of the probability of erosion of each fraction facilitates a prediction of the bedload composition. Results show that the probabilistic approach provides a significant improvement over deterministic methods for the prediction of bedload composition.
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Wang, 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.
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Johansson-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.
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Protein-peptide interactions play a major role in several biological processes, such as cellproliferation and cancer cell life-cycles. Accurate computational methods for predictingprotein-protein interactions exist, but few of these method can be extended to predictinginteractions between a protein and a particularly small or intrinsically disordered peptide. In this thesis, PePIP is presented. PePIP is a pipeline for predicting where on a given proteina given peptide will most probably bind. The pipeline utilizes structural aligning to perusethe Protein Data Bank for possible templates for the interaction to be predicted, using thelarger chain as the query. The possible templates are then evaluated as to whether they canrepresent the query protein and peptide using a Random Forest classifier machine learningalgorithm, and the best templates are found by using the evaluation from the Random Forest in combination with hierarchical clustering. These final templates are then combined to givea prediction of binding site. PePIP is proven to be highly accurate when testing on a set of 502 experimentally determinedprotein-peptide structures, suggesting a binding site on the correct part of the protein- surfaceroughly 4 out of 5 times.
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Foster, Eric D. "Acceptor splice site prediction in vertebrates using probabilistic models /." Online version of thesis, 2007. http://hdl.handle.net/1850/4629.
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