• Refine Query
  • Source
  • Publication year
  • to
  • Language
  • 1265
  • 440
  • 229
  • 124
  • 93
  • 37
  • 27
  • 26
  • 22
  • 20
  • 16
  • 12
  • 11
  • 11
  • 10
  • Tagged with
  • 2791
  • 320
  • 317
  • 288
  • 233
  • 229
  • 191
  • 181
  • 179
  • 160
  • 155
  • 138
  • 137
  • 132
  • 130
  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
391

Phylogenetic analysis of multiple genes based on spectral methods

Abeysundera, Melanie 28 October 2011 (has links)
Multiple gene phylogenetic analysis is of interest since single gene analysis often results in poorly resolved trees. Here the use of spectral techniques for analyzing multi-gene data sets is explored. The protein sequences are treated as categorical time series and a measure of similarity between a pair of sequences, the spectral covariance, is used to build trees. Unlike other methods, the spectral covariance method focuses on the relationship between the sites of genetic sequences. We consider two methods with which to combine the dissimilarity or distance matrices of multiple genes. The first method involves properly scaling the dissimilarity measures derived from different genes between a pair of species and using the mean of these scaled dissimilarity measures as a summary statistic to measure the taxonomic distances across multiple genes. We introduced two criteria for computing scale coefficients which can then be used to combine information across genes, namely the minimum variance (MinVar) criterion and the minimum coefficient of variation squared (MinCV) criterion. The scale coefficients obtained with the MinVar and MinCV criteria can then be used to derive a combined-gene tree from the weighted average of the distance or dissimilarity matrices of multiple genes. The second method is based on the singular value decomposition of a matrix made up of the p-vectors of pairwise distances for k genes. By decomposing such a matrix, we extract the common signal present in multiple genes to obtain a single tree representation of the relationship between a given set of taxa. Influence functions for the components of the singular value decomposition are derived to determine which genes are most influential in determining the combined-gene tree.
392

Polyhedral approaches to scheduling shutdowns in production planning

Waterer, Hamish 08 1900 (has links)
No description available.
393

Synthesis and thermal decomposition of alkyl-olefin chelate complexes of iron and ruthenium

Steiger, George Edward 08 1900 (has links)
No description available.
394

Variance Analysis for Nonlinear Systems

Yu, Wei 06 1900 (has links)
In the past decades there has been onsiderable commercial and academic interest in methods for monitoring control system performance for linear systems. Far less has been written on control system performance for nonlinear dynamic / stochastic systems. This thesis presents research results on three control performance monitoring topics for the nonlinear systems: i) Controller assessment of a class of nonlinear systems: The use of autoregressive moving average (ARMA) models to assess the control loop performance for linear systems is well known. Classes of nonlinear dynamic / stochastic systems for which a similar result can be obtained are established for SISO discrete systems. For these systems, the performance lower bounds can be estimated from closed-loop routine operating data using nonlinear autoregressive moving average with exogenous inputs (NARMAX) models. ii) Variance decomposition of nonlinear systems / time series: We develop a variance decomposition approach to quantify the effects of different sources of disturbances on the nonlinear dynamic / stochastic systems. A method, called ANOVA-like decomposition, is employed to achieve this variance decomposition. Modifications of ANOVA-like decomposition are proposed so that the NOVA-like decomposition can be used to deal with the time dependency and the initial condition. iii) Parameter uncertainty effects on the variance decomposition: For the variance decomposition in the second part, the model parameters are assumed to be exactly known. However, parameters of empirical or mechanistic models are uncertain. The uncertainties associated with parameters should be included when the model is used for variance analysis. General solutions of the parameter uncertainty effects on the variance decomposition for the general nonlinear systems are proposed. Analytical solutions of the parameter uncertainty effects on the variance decomposition are provided for models with linear parameters. / Thesis (Ph.D, Chemical Engineering) -- Queen's University, 2007-10-17 16:02:26.376 / This work was sponsored by NSERC Discovery, NSERC Equipment, Shell Global Solutions, OGSST and QGA
395

IMPROVED DOCUMENT SUMMARIZATION AND TAG CLOUDS VIA SINGULAR VALUE DECOMPOSITION

Provost, JAMES 25 September 2008 (has links)
Automated summarization is a difficult task. World-class summarizers can provide only "best guesses" of which sentences encapsulate the important content from within a set of documents. As automated systems continue to improve, users are still not given the means to observe complex relationships between seemingly independent concepts. In this research we used singular value decompositions to organize concepts and determine the best candidate sentences for an automated summary. The results from this straightforward attempt were comparable to world-class summarizers. We then included a clustered tag cloud, using a singular value decomposition to measure term "interestingness" with respect to the set of documents. The combination of best candidate sentences and tag clouds provided a more inclusive summary than a traditionally-developed summarizer alone. / Thesis (Master, Computing) -- Queen's University, 2008-09-24 16:31:25.261
396

Combining Decomposition and Hybrid Algorithms for the Satellite Range Scheduling Problems

Feng, Ti Kan 21 March 2012 (has links)
Multiple-resource satellite scheduling problem (MuRRSP) is a complex and difficult scheduling problem, which schedules a large number of task requests onto ground-station antennas in order to communicate with the satellites. We first examined several exact algorithms that were previously implemented in the machine scheduling field. They are column generation and logic-based Benders decomposition. A new hybrid approach that combines both column generation and logic-based Benders decomposition is proposed. The hybrid performed well when there is a large number of machines. Next, we presented a connection between the parallel machine scheduling problem and MuRRSP in order to solve MuRRSP with exact algorithms. Furthermore, we proposed a strengthened cut in the sub-problem of the logic-based Benders decomposition. The resulting algorithm proved to be very effective. Barbulescu’s benchmark problems were solved and proved optimal with an average run-time less than one-hour. To the best of our knowledge, previous efforts to solve MuRRSP were all heuristic based and no optimal schedules existed.
397

Combining Decomposition and Hybrid Algorithms for the Satellite Range Scheduling Problems

Feng, Ti Kan 21 March 2012 (has links)
Multiple-resource satellite scheduling problem (MuRRSP) is a complex and difficult scheduling problem, which schedules a large number of task requests onto ground-station antennas in order to communicate with the satellites. We first examined several exact algorithms that were previously implemented in the machine scheduling field. They are column generation and logic-based Benders decomposition. A new hybrid approach that combines both column generation and logic-based Benders decomposition is proposed. The hybrid performed well when there is a large number of machines. Next, we presented a connection between the parallel machine scheduling problem and MuRRSP in order to solve MuRRSP with exact algorithms. Furthermore, we proposed a strengthened cut in the sub-problem of the logic-based Benders decomposition. The resulting algorithm proved to be very effective. Barbulescu’s benchmark problems were solved and proved optimal with an average run-time less than one-hour. To the best of our knowledge, previous efforts to solve MuRRSP were all heuristic based and no optimal schedules existed.
398

Microwave-assisted decomposition of environmental samples, and the analysis of plutonium and radiostrontium

Garcia, Ramon 05 1900 (has links)
No description available.
399

INFLUENCE OF MOISTURE REGIME AND TREE SPECIES ON NITROGEN CYCLING AND DECOMPOSITION DYNAMICS IN DECIDUOUS FORESTS OF MAMMOTH CAVE NATIONAL PARK, KENTUCKY, USA

Fabio, Eric 01 January 2006 (has links)
The study of biogeochemical cycles and their role in ecosystem function has helped to highlight the impacts of human activities on natural processes. However, our understanding of the effects of nitrogen (N) deposition on forested ecosystems remains limited due to the variable controls on N cycling. Soils, microclimate, and vegetation can influence rates and processes of N cycling, singly or in concert at multiple scales. Understanding how these factors influence N cycling across the landscape will help to elucidate the impacts of N deposition. The objectives of this study were to characterize variation in soils, microclimate and vegetation characteristics, and N cycling and decomposition dynamics across the landscape in a region impacted by N deposition. Relationships among these factors were explored to determine the main factors influencing N cycling and decomposition. Strong differences in net N mineralization and nitrification were found between forest stands with contrasting species composition and moisture availability. Nitrate production and leaching were related to sugar maple abundance, and base cation leaching was correlated with nitrate concentrations in soil solutions. Decomposition experiments were installed to examine the effects of substrate quality, microclimate and N availability on decay rates. Nitrogen amendments for the most part did not affect decomposition rates of wood and cellulose, and mass loss rates were correlated with microclimate and forest floor characteristics. In contrast, microclimate did not seem to affect leaf litter decay rates, and the results suggest that the presence of invertebrates may influence mass loss to a greater degree than moisture or litter quality. This work highlights the large degree of variability in N processing across the landscape and suggests that differences in microclimate and species composition may help to predict the impacts of chronic N deposition on N cycling and retention.
400

The opioid peptide dynorphin A : Biophysical studies of peptide–receptor and peptide–membrane interactions

Björnerås, Johannes January 2014 (has links)
The work presented in this thesis concerns the opioid peptide dynorphin A (DynA). DynA functions primarily as a neurotransmitter and belongs to the family of typical opioid peptides. These peptides are a part of the opioid system, together with the opioid receptors, a family of GPCR membrane proteins. The opioid system system is involved or implicated in several physiological processes such as analgesia, addiction, depression and other types of neurological disorders. In this thesis, two biologically relevant aspects of DynA have been investigated with biophysical methods. First, interactions between DynA and an opioid receptor, and second, the direct membrane interactions of DynA. The DynA–receptor studies were focused on the selectivity-modulating second extracellular loop (EL2) of the kappa-opioid receptor (KOR). A protein engineering approach was used in which the EL2 was grafted onto a soluble protein scaffold. The results show that DynA binds with low affinity but high specificity to EL2 in the construct protein environment. The strength of the interaction is in the micromolar range, and we argue that this interaction is part of the receptor recognition event. With bicelles as a mimetic, membrane interactions were probed for wild-type DynA and for two DynA peptide variants linked to a neurological disorder. R6W–DynA and L5S–DynA were shown to be very different in terms of bicelle association, penetration and structure induction. In these experiments, as well as in investigations of DynA dynamics in bicelles, the lipid environment was shown to have much larger effects on peptide dynamics than on structure; and both these properties depend on lipid charge. Additionally, in a methodological project, DHPC/DMPC bicelle morphology as a function of total PC concentration was characterised by diffusion NMR in combination with two-way decomposition. The results may contribute to providing guidelines for the appropriate use of bicelles as a membrane mimetic. / <p>At the time of the doctoral defense, the following papers were unpublished and had a status as follows: Paper 3: Manuscript. Paper 5: Manuscript.</p>

Page generated in 0.1082 seconds