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Dissertations / Theses on the topic 'Combination model'

Author: Grafiati

Published: 3 June 2025

Last updated: 31 July 2025

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1

Xu, Mingyang 1974. "Model combination by decomposition and aggregation." Thesis, Massachusetts Institute of Technology, 2004. http://hdl.handle.net/1721.1/33641.

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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Nuclear Engineering, 2004.<br>Includes bibliographical references (p. 265-282).<br>This thesis focuses on a general problem in statistical modeling, namely model combination. It proposes a novel feature-based model combination method to improve model accuracy and reduce model uncertainty. In this method, a set of candidate models are first decomposed into a group of components or features and then components are selected and aggregated into a composite model based on data. However, in implementing this new method, some central ch

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2

Patterson, Merryl Joy. "Testing the weighted salience model of conceptual combination." Diss., Texas A&M University, 2003. http://hdl.handle.net/1969.1/270.

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In two experiments the Weighted Salience Model (WSM) of conceptual combination was examined. Several of the hypotheses set forth in the WSM were evaluated, including the importance of salience of constituent features, differential interpretation strategies based on similarity, an initial reliance on the modifier as opposed to the head, and a context effect of salience reorganization. Results confirmed that the hierarchy of output dominance within constituent features was important in determining features in final combinations. Additionally, similar pairs were defined with property interpreta

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Cook, G. D. "Data selection and model combination in connectionist speech recognition." Thesis, University of Cambridge, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.597919.

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The hybrid connectionist-hidden Markov model (HMM) approach to large vocabulary continuous speech recognition has been shown to be competitive with HMM based systems. However, the recent availability of extremely large amounts of acoustic training data has highlighted a problem with the connectionist acoustic modelling paradigm. The effective use of such large amounts of data is difficult due to the computational requirements of training large connectionist models. This dissertation details research aimed at increasing the performance of connectionist acoustic models through the effective use

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Lipanova, Iuliia <1993&gt. "A model-combination approach to pricing for weather derivatives." Master's Degree Thesis, Università Ca' Foscari Venezia, 2016. http://hdl.handle.net/10579/8814.

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The main object of this study is to find a model that can explain and predict the behavior of weather time series. Different models of GARCH-type are fitted on the series of the average temperature. Autoregressive, seasonal and trend components are included in mean and variance equations. The seasonal components are constructed as a combination of simple harmonic functions, the frequencies of which are found with Fast Fourier Transform. Forecast combination approach is applied to define the best model and thus this model is used as an underlying to price weather derivatives. Numerical examples

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Makhtar, Mokhairi. "Contributions to Ensembles of Models for Predictive Toxicology Applications. On the Representation, Comparison and Combination of Models in Ensembles." Thesis, University of Bradford, 2012. http://hdl.handle.net/10454/5478.

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The increasing variety of data mining tools offers a large palette of types and representation formats for predictive models. Managing the models then becomes a big challenge, as well as reusing the models and keeping the consistency of model and data repositories. Sustainable access and quality assessment of these models become limited to researchers. The approach for the Data and Model Governance (DMG) makes easier to process and support complex solutions. In this thesis, contributions are proposed towards ensembles of models with a focus on model representation, comparison and usage. Predic

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6

Eastwood, Mark. "Building well-performing classifier ensembles : model and decision level combination." Thesis, Bournemouth University, 2010. http://eprints.bournemouth.ac.uk/18389/.

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There is a continuing drive for better, more robust generalisation performance from classification systems, and prediction systems in general. Ensemble methods, or the combining of multiple classifiers, have become an accepted and successful tool for doing this, though the reasons for success are not always entirely understood. In this thesis, we review the multiple classifier literature and consider the properties an ensemble of classifiers - or collection of subsets - should have in order to be combined successfully. We find that the framework of Stochastic Discrimination provides a well-def

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Harland, Zac. "Forecasting financial markets using linear, nonlinear & model combination methods." Thesis, City University London, 2010. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.544436.

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8

Mei, Zhenyu, and Ye Tian. "Optimized combination model and algorithm of parking guidance information configuration." SpringerOpen, 2011. http://hdl.handle.net/10150/610136.

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Operators of parking guidance and information (PGI) systems often have difficulty in providing the best car park availability information to drivers in periods of high demand. A new PGI configuration model based on the optimized combination method was proposed by analyzing of parking choice behavior. This article first describes a parking choice behavioral model incorporating drivers perceptions of waiting times at car parks based on PGI signs. This model was used to predict the influence of PGI signs on the overall performance of the traffic system. Then relationships were developed for estim

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9

Zucchelli, D. "Combination Methods for Software Verification." Doctoral thesis, Università degli Studi di Milano, 2008. http://hdl.handle.net/2434/45877.

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The thesis is devoted to the development of formal methods for software verification. Indeed, two are among the most widespread techniques that allow to rigorously specify the possible executions of a system and check whether it contains bugs. On the one hand, the correctness of a program can be guaranteed by showing the unsatisfiability of a formula modulo a theory which usually axiomatizes the involved datatypes; on the other hand, the model checking techniques are used to certify that every possible run of the system satisfies the desired properties. The contributions of the thesis are the

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10

Brejova, Bronislava. "Evidence Combination in Hidden Markov Models for Gene Prediction." Thesis, University of Waterloo, 2005. http://hdl.handle.net/10012/1036.

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This thesis introduces new techniques for finding genes in genomic sequences. Genes are regions of a genome encoding proteins of an organism. Identification of genes in a genome is an important step in the annotation process after a new genome is sequenced. The prediction accuracy of gene finding can be greatly improved by using experimental evidence. This evidence includes homologies between the genome and databases of known proteins, or evolutionary conservation of genomic sequence in different species. <br /><br /> We propose a flexible framework to incorporate several different

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MADORMO, FILOMENA. "Model Averaging using performance and distance measures." Doctoral thesis, Università degli Studi di Milano-Bicocca, 2015. http://hdl.handle.net/10281/88349.

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In this work we introduce the problem of forecast combination using performance and distance measures for binary outcome. The thesis is focused on model averaging for parametric and non parametric approaches, with a special attention on temporal dependent and independent models. In terms of results, we combine single models using performance measures and we investigate how distance measure based on the Mahalanobis distance can lead to interesting results for model combination. In order to assess the stability and the predictive capability of the models at hand, we employ different cross-val

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Pham, Thuy Van. "Using isotope effects to model transition states for carbocation-nucleophile combination reactions." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape7/PQDD_0003/NQ41271.pdf.

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13

Galkina, Anastasiia [Verfasser]. "Combination of Flatness and Model Predictive Control for Mechatronical Applications / Anastasiia Galkina." Aachen : Shaker, 2018. http://d-nb.info/1186590793/34.

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Davis, Paulina R. "IMMUNOTHERAPY IN COMBINATION WITH BEHAVIORAL ENRICHMENT IN A CANINE MODEL OF AGING." UKnowledge, 2014. http://uknowledge.uky.edu/pharmacol_etds/6.

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Alzheimer’s disease (AD) is characterized by cognitive decline and hallmark neuropathology, including β-amyloid (Aβ). Therapeutic strategies for AD are focusing on reducing Aβ. Canines develop Aβ neuropathology and cognitive decline with age similar to AD patients. In previous studies, immunization with Aβ1-42 (VAC) in aged canines decreased brain Aβ but did not improve cognition. Behavioral enrichment (ENR) improved cognition without reducing brain Aβ. We hypothesized that VAC combined with ENR would provide cognitive benefits and reduce Aβ neuropathology, as compared individual VAC and ENR t

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15

Wang, Jo-Yu. "Portfolio based VaR model : a combination of extreme value theory (EVT) and dynamic conditional correlation (DCC) model." Thesis, University of Southampton, 2013. https://eprints.soton.ac.uk/348328/.

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This thesis fills a gap in the risk management literature and expands the understanding of the portfolio value at risk (VaR) by providing a theoretical market risk measurement of a portfolio (called “GEV-DCC model”), which combines the tail dynamic conditional correlation (tail-DCC) and extreme value theory. According to the spirit of VaR, the tail distribution is more important than the entire distribution, as well as the correlation in the tail area between various assets. The main advantage of this approach is the increase of accuracy in the parameter estimation of the tail distribution and

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Nan, Fany. "Forecasting next-day electricity prices: from different models to combination." Doctoral thesis, Università degli studi di Padova, 2009. http://hdl.handle.net/11577/3426510.

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As a result of deregulation of most power markets around the world electricity price modeling and forecasting have obtained increasing importance in recent years. Large number of models has been studied on a wide range of power markets, from linear time series and multivariate regression models to more complex non linear models with jumps, but results are mixing and there is no single model that provides convincing superior performance in forecasting spot prices. This study considers whether combination forecasts of spot electricity prices are statistically superior to a wide range of single m

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Peake, Sandra Lois. "Combination anti-cytokine immunotherapy in an ovine model of gram-negative septic shock." Title page, contents and summary only, 2000. http://web4.library.adelaide.edu.au/theses/09PH/09php3576.pdf.

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Bibliography: leaves 288-336. This thesis examines the role of ant-cytokine monoclonal antibodies (mAb) as an adjunctive treatment in an animal model of septic shock. In particular, the role of combination immunotherapies directed against more than one cytokine is investigated.

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18

Dyussekeneva, Karima. "New product sales forecasting : the relative accuracy of statistical, judgemental and combination forecasts." Thesis, University of Bath, 2011. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.550612.

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This research investigates three approaches to new product sales forecasting: statistical, judgmental and the integration of these two approaches. The aim of the research is to find a simple, easy-to-use, low cost and accurate tool which can be used by managers to forecast the sales of new products. A review of the literature suggested that the Bass diffusion model was an appropriate statistical method for new product sales forecasting. For the judgmental approach, after considering different methods and constraints, such as bias, complexity, lack of accuracy, high cost and time involvement, t

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Weiss, Christoph. "Essays in hierarchical time series forecasting and forecast combination." Thesis, University of Cambridge, 2018. https://www.repository.cam.ac.uk/handle/1810/274757.

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This dissertation comprises of three original contributions to empirical forecasting research. Chapter 1 introduces the dissertation. Chapter 2 contributes to the literature on hierarchical time series (HTS) modelling by proposing a disaggregated forecasting system for both inflation rate and its volatility. Using monthly data that underlies the Retail Prices Index for the UK, we analyse the dynamics of the inflation process. We examine patterns in the time-varying covariation among product-level inflation rates that aggregate up to industry-level inflation rates that in turn aggregate up to t

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李寶昇 and Po-sing Li. "The study of the combination of technical analysis and qualitative model in financial forecasting." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1998. http://hub.hku.hk/bib/B31269035.

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Zografos, V. "Pose-invariant, model-based object recognition, using linear combination of views and Bayesian statistics." Thesis, University College London (University of London), 2009. http://discovery.ucl.ac.uk/18954/.

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This thesis presents an in-depth study on the problem of object recognition, and in particular the detection of 3-D objects in 2-D intensity images which may be viewed from a variety of angles. A solution to this problem remains elusive to this day, since it involves dealing with variations in geometry, photometry and viewing angle, noise, occlusions and incomplete data. This work restricts its scope to a particular kind of extrinsic variation; variation of the image due to changes in the viewpoint from which the object is seen. A technique is proposed and developed to address this problem, wh

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Ferreira, Raoni Simões. "A wikification prediction model based on the combination of latent, dyadic and monadic features." Universidade de São Paulo, 2016. http://www.teses.usp.br/teses/disponiveis/55/55134/tde-29112016-164654/.

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Most of the reference information, nowadays, is found in repositories of documents semantically linked, created in a collaborative fashion and freely available in the web. Among the many problems faced by content providers in these repositories, one of the most important is Wikification, that is, the placement of links in the articles. These links have to support user navigation and should provide a deeper semantic interpretation of the content. Wikification is a hard task since the continuous growth of such repositories makes it increasingly demanding for editors. As consequence, they have th

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Tian, Tian. "Domain Adaptation and Model Combination for the Annotation of Multi-source, Multi-domain Texts." Thesis, Paris 3, 2019. http://www.theses.fr/2019PA030003.

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Internet propose aujourd’hui aux utilisateurs de services en ligne de commenter, d’éditer et de partager leurs points de vue sur différents sujets de discussion. Ce type de contenu est maintenant devenu la ressource principale pour les analyses d’opinions sur Internet. Néanmoins, à cause des abréviations, du bruit, des fautes d’orthographe et toutes autres sortes de problèmes, les outils de traitements automatiques des langues, y compris les reconnaisseurs d’entités nommées et les étiqueteurs automatiques morphosyntaxiques, ont des performances plus faibles que sur les textes bien-formés (Ritt

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Twyman, Alexandra Dawn. "INTEGRATION OF FEATURAL AND GEOMETRIC INFORMATION IN REORIENTATION: EVIDENCE FOR AN ADAPTIVE COMBINATION MODEL." Diss., Temple University Libraries, 2011. http://cdm16002.contentdm.oclc.org/cdm/ref/collection/p245801coll10/id/158224.

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Psychology<br>Ph.D.<br>This paper examines the integration of geometric and feature cues in spatial memory with a modified version of the spatial reorientation task. Proponents of the geometric module position argue that there is an encapsulated reorientation module, and that true reorientation is accomplished only via geometry (Lee & Spelke, 2010). Features can be used in a second and separate step, but only to locate a goal rather than as a reorientation cue. In contrast, proponents of the adaptive combination approach argue that geometry and feature cues are integrated in spatial memory and

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Li, Po-sing. "The study of the combination of technical analysis and qualitative model in financial forecasting /." Hong Kong : University of Hong Kong, 1998. http://sunzi.lib.hku.hk/hkuto/record.jsp?B19878059.

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Peterson, Todd. "A COMBINATION THERAPY OF NICOTINAMIDE AND PROGESTERONE FOR FUNCTIONAL RECOVERY FOLLOWING TRAUMATIC BRAIN INJURY." OpenSIUC, 2013. https://opensiuc.lib.siu.edu/dissertations/695.

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Traumatic Brain Injury (TBI) is a leading cause of death and disability in the United States for which there are no federally approved pharmacological treatments. Preclinical trials with nicotinamide (NAM) and progesterone (Prog) treatment demonstrate beneficial neuroprotection and recovery of function following TBI. The primary goal of this study was to assess both neuroprotection and recovery of function in an animal model of TBI after combination treatment of both NAM and Prog. Animals received a cortical contusion injury over the sensorimotor cortex and were treated with either nicotinamid

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Freitas, Paulo Sérgio Abreu. "The combination of neural estimates in prediction and decision problems." Doctoral thesis, Universidade de Lisboa: Faculdade de Ciências, 2008. http://hdl.handle.net/10400.13/98.

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In this dissertation, different ways of combining neural predictive models or neural-based forecasts are discussed. The proposed approaches consider mostly Gaussian radial basis function networks, which can be efficiently identified and estimated through recursive/adaptive methods. Two different ways of combining are explored to get a final estimate – model mixing and model synthesis –, with the aim of obtaining improvements both in terms of efficiency and effectiveness. In the context of model mixing, the usual framework for linearly combining estimates from different models is extended, t

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Walter, Tobias [Verfasser]. "Bridging Technological Spaces : Towards the Combination of Model-Driven Engineering and Ontology Technologies / Tobias Walter." Koblenz : Universitätsbibliothek Koblenz, 2011. http://d-nb.info/1013822927/34.

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Barrow, Devon K. "Active model combination : an evaluation and extension of bagging and boosting for time series forecasting." Thesis, Lancaster University, 2012. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.659174.

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Since the seminal work by Bates and Granger (1969), the practice of combining two or more models, rather than selecting the single best, has consistently been shown to lead to improvements in accuracy. In forecasting, model combination aims to find an optimal weighting given a set of precalculated forecasts. In contrast, machine learning includes methods which simultaneously optimise individual models and the weights used to combine them. Bagging and boosting combine the results of complementary and diverse models generated by actively perturbing, reweighting and resampling training data. Desp

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Smit, Johannes Petrus. "Model for microwave absorption and heat transfer in a combination washer dryer / by J.P. Smit." Thesis, North-West University, 2013. http://hdl.handle.net/10394/9697.

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The work presented within this dissertation focusses on the development of affinite element method (FEM) model for the microwave absorption and heat transfer within a microwave combination washer dryer (MCWD). FEM will be used to aid in the implementation of more advanced fluid dynamics such as laminar or turbulent flow, that may be present within the system. The intended use of the model is to aid a South African based company in the development of a control system for the MCWD. The model development presented focusses on the washing cycle of the MCWD and will therefore not take into account

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Soble, Michelle Joy 1961. "THE EFFECTS OF GLUTATHIONE DEPLETION BY L-BUTHIONINE-(S,R) SULFOXIMINE ON THE ANTITUMOR EFFICACY OF MODEL SULFHYDRYL-DEPENDENT ANTICANCER AGENTS (BSO)." Thesis, The University of Arizona, 1986. http://hdl.handle.net/10150/276859.

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Yang, Jianning. "Mechanism-Based Computational Models to Study Pharmacological Actions of Anticancer Drugs." The Ohio State University, 2009. http://rave.ohiolink.edu/etdc/view?acc_num=osu1249622434.

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Schaser, Matt Saxon. "Material Specific Load Combination Factors for Option 2 FAD Curves." Cleveland State University / OhioLINK, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=csu1386078154.

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Bella, Sanjuán Antonio. "Model Integration in Data Mining: From Local to Global Decisions." Doctoral thesis, Universitat Politècnica de València, 2012. http://hdl.handle.net/10251/16964.

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El aprendizaje autom�atico es un �area de investigaci�on que proporciona algoritmos y t�ecnicas que son capaces de aprender autom�aticamente a partir de experiencias pasadas. Estas t�ecnicas son esenciales en el �area de descubrimiento de conocimiento de bases de datos (KDD), cuya fase principal es t�ÿpicamente conocida como miner�ÿa de datos. El proceso de KDD se puede ver como el aprendizaje de un modelo a partir de datos anteriores (generaci�on del modelo) y la aplicaci�on de este modelo a nuevos datos (utilizaci�on del modelo). La fase de utilizaci�on del modelo es muy importante, porque l

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Holden, Mark Paul. "EXTENDING THE CATEGORY ADJUSTMENT MODEL: LOCATION MEMORY BIASES IN 3-DIMENSIONAL SPACE." Diss., Temple University Libraries, 2011. http://cdm16002.contentdm.oclc.org/cdm/ref/collection/p245801coll10/id/158122.

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Psychology<br>Ph.D.<br>The ability to remember spatial locations is critical to human functioning, both in an evolutionary and an everyday sense. And yet, spatial memories and judgments often show systematic errors. Explanations for such errors have ranged from assumptions that memories are nonmetric, to the use of imperfect inferences, to the optimal combination of multiple sources of information. More recently, bias has been explained through the Category Adjustment Model - a Bayesian model in which fine-grained and categorical information are optimally combined (Huttenlocher, Hedges, & Dunc

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Zubas, Laimonas. "Modelling of methane emissions utilising a Lagrangian atmospheric dispersion model in combination with Earth observation data." Thesis, University of Leicester, 2015. http://hdl.handle.net/2381/31998.

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Space-borne methane observations provide increased spatial coverage and complement the precise, but sparse network of in-situ measurement sites. In this study, a method has been developed to investigate regional-scale methane budgets using space-borne methane observations, utilising the UK Met Office Numerical Atmospheric Modelling Environment (NAME). Lagrangian atmospheric dispersion models, such as NAME, allow us to investigate fluxes at a lesser computational cost and potentially, a higher spatial resolution. An inversion algorithm was created and tested on synthetic ground measurement data

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Yeung, Shunmay. "Antimalarial drug resistence and artemisinin based combination therapy : a bio-economic model for elucidating policy choices." Thesis, London School of Hygiene and Tropical Medicine (University of London), 2006. http://researchonline.lshtm.ac.uk/682350/.

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Antimalarial drug resistance is a major cause of the increasing burden due to P. falciparum malaria. Artemisinin-based combination therapies (ACTs) are now recognised to be the ideal choice for the first-line treatment of uncomplicated malaria, in order to achieve two beneficial outcomes: improvement of treatment efficacy and delay in the development of drug resistance. However uncertainties remain about the current and future benefits, risks and costs of ACTs and in particular how these outcomes are affected by differences in malaria epidemiology, health care settings, human behaviour and imp

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Court, Philip Wathen. "A combination of a stationary and non-stationary model to predict corporate failure in South Africa." Thesis, Rhodes University, 1994. http://hdl.handle.net/10962/d1002800.

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Business failure should be of concern in most industralised countries and the importance of accurately evaluating the phenomenon from a management and investment point of view is enormous. Were it possible to predict failure with a certain degree of confidence, steps could be taken to rectify the situation and the benefit would accrue to all of the stakeholders in the macroenvironment. In essence, the profitability of a business is influenced by two sets of variables. In the first instance, it is influenced by a variety of internal (microeconomic) variables which are firm- specific and which m

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Bose, Aishwarya. "Effective web service discovery using a combination of a semantic model and a data mining technique." Thesis, Queensland University of Technology, 2008. https://eprints.qut.edu.au/26425/1/Aishwarya_Bose_Thesis.pdf.

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With the advent of Service Oriented Architecture, Web Services have gained tremendous popularity. Due to the availability of a large number of Web services, finding an appropriate Web service according to the requirement of the user is a challenge. This warrants the need to establish an effective and reliable process of Web service discovery. A considerable body of research has emerged to develop methods to improve the accuracy of Web service discovery to match the best service. The process of Web service discovery results in suggesting many individual services that partially fulfil the user’s

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Bose, Aishwarya. "Effective web service discovery using a combination of a semantic model and a data mining technique." Queensland University of Technology, 2008. http://eprints.qut.edu.au/26425/.

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With the advent of Service Oriented Architecture, Web Services have gained tremendous popularity. Due to the availability of a large number of Web services, finding an appropriate Web service according to the requirement of the user is a challenge. This warrants the need to establish an effective and reliable process of Web service discovery. A considerable body of research has emerged to develop methods to improve the accuracy of Web service discovery to match the best service. The process of Web service discovery results in suggesting many individual services that partially fulfil the user’s

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Ye, Kangfeng. "Model checking of state-rich formalisms (by linking to combination of state-based formalism and process algebra)." Thesis, University of York, 2016. http://etheses.whiterose.ac.uk/15526/.

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Computer-based systems are becoming more and more complex. It is really a grand challenge to assure the dependability of these systems with the growing complexity, especially for high integrity and safety critical systems that require extremely high dependability. Circus, as a formal language, is designed to tackle this problem by providing precision preservation and correctness assurance. It is a combination of Z, CSP, refinement calculus and Dijkstra's guarded commands. A main objective of Circus is to provide calculational style refinement that differentiates itself from other integrated fo

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Wang, Jie Stamey James D. "Sample size determination for Emax model, equivalence / non-inferiority test and drug combination in fixed dose trials." Waco, Tex. : Baylor University, 2008. http://hdl.handle.net/2104/5182.

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Sakai, Takeru. "Leptin restores the insulinotropic effect of exenatide in a mouse model of type 2 diabetes with increased adiposity induced by streptozotocin and high-fat diet." Kyoto University, 2015. http://hdl.handle.net/2433/195969.

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Monteith, Kristine Perry. "Automatic Generation of Music for Inducing Emotive and Physiological Responses." BYU ScholarsArchive, 2012. https://scholarsarchive.byu.edu/etd/3753.

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Music and emotion are two realms traditionally considered to be unique to human intelligence. This dissertation focuses on furthering artificial intelligence research, specifically in the area of computational creativity, by investigating methods of composing music that elicits desired emotional and physiological responses. It includes the following: an algorithm for generating original musical selections that effectively elicit targeted emotional and physiological responses; a description of some of the musical features that contribute to the conveyance of a given emotion or the elicitation o

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Hausauer, Justin. "Sparse Grid Combination Techniques for Solving High-Dimensional Parabolic Equations with an Application to the LIBOR Market Model." Research Showcase @ CMU, 2015. http://repository.cmu.edu/dissertations/519.

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In this thesis, we consider the use of the sparse grid combination technique with finite difference methods to solve parabolic partial differential equations. Convergence results are obtained in L2 for arbitrary dimensions via Fourier analysis arguments under the assumption that the initial data lies in the Sobolev space H4 mix. Numerical results are presented for model problems and for problems from the field of option pricing.

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Lin, Teng-Shih, and 林登仕. "Dimension Combination Strategy Model." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/32167777908443854656.

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碩士<br>僑光科技大學<br>資訊科技研究所<br>102<br>Thanks to the development of science and technology of today, and the upgrading of the software and hardware, the speed of the computer operation become faster; the mass data mining have no need to wait for a long time. This thesis applies the technique of the Data Reduction in the data mining field; through this Data Reduction technique, reject the useless data from the millions of, or even more than ten millions items of data, then improve the data mining speed and help the users to find out more precise data. This research uses the data dimension reduction

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Huang, Pi-Shu, and 黃碧書. "Diagnosis of Corporate Financial Distress with Combination of Forecast Model." Thesis, 2005. http://ndltd.ncl.edu.tw/handle/73229478943405930516.

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碩士<br>樹德科技大學<br>金融保險研究所<br>93<br>During the past, the evaluation of the corporate financial distress was not given top priority in Taiwan. In the year after the Asian financial crisis in 1997, heavily influenced by global economic recession, Taiwan has seen the continued appearances of bearish stocks, which in turn posed a major threat to the local financial structure. Many debt ridden companies, due to lack of proper cash flow management and failure to utilize capital resources efficiently, had suffered serious cash flow difficulties. Many cases of production stoppage, invalid bills of exc

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Frazão, Xavier Marques. "Deep learning model combination and regularization using convolutional neural networks." Master's thesis, 2014. http://hdl.handle.net/10400.6/5605.

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Convolutional neural networks (CNNs) were inspired by biology. They are hierarchical neural networks whose convolutional layers alternate with subsampling layers, reminiscent of simple and complex cells in the primary visual cortex [Fuk86a]. In the last years, CNNs have emerged as a powerful machine learning model and achieved the best results in many object recognition benchmarks [ZF13, HSK+12, LCY14, CMMS12]. In this dissertation, we introduce two new proposals for convolutional neural networks. The first, is a method to combine the output probabilities of CNNs which we call Weighted

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Chang, Yuan-Ling, and 張元齡. "Classification Improvement Based on Feature Combination and Topic Vector Model." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/43119144947629463394.

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碩士<br>真理大學<br>資訊工程學系碩士班<br>100<br>We demonstrate a feature processing procedure which emphasizes on the combination of original features with redundancy trimming steps. This procedure shows better classification result than traditional classification models. In our experiment, several key feature processing steps were proposed according to the type od the feature. These steps contains numerical to categorical feature value conversion, feature combination, feature redundancy discrimination, and latent structure discovery based on the concatenation of original features and extended feature set.

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Drachal, Krzysztof. "Novel Bayesian model combination schemes with model uncertainty: An application to prices of selected energy commodities." Doctoral thesis, 2020. https://depotuw.ceon.pl/handle/item/3635.

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The aim of this dissertation is to apply the selected Bayesian model combination schemes in case of forecasting the prices of the selected energy commodities. These methods have the following advantages. First, the estimation is done in a recursive way, i.e., the forecast in time t is formulated only on the basis of the data available during time t -1, which corresponds with the real-life situation, of, for example, an investor on the market. Secondly, the coefficients of a multilinear individual, i.e., being put into the model combination scheme, regression model, as well as, the weights ascr

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