Assume that F is a nonlinear operator on a real Hilbert space H which is strongly monotone and Lipschitzian on a nonempty closed convex subset C of H. Assume also that C is the intersection of the fixed point sets of a finite number of nonexpansive mappings on H. We make a slight modification of the iterative algorithm in Xu and Kim (Journal of Optimization Theory and Applications, Vol. 119, No. 1, pp. 185-201, 2003), which generates a sequence {xn} from an arbitrary initial point x0 in H. The sequence {xn} is shown to converge in norm to the unique solution u* of the variational inequality, under the conditions different from Xu and Kim¡¦s ones imposed on the parameters. Applications to constrained generalized pseudoinverse are included. The results presented in this paper are complementary ones to Xu and Kim¡¦s theorems (Journal of Optimization Theory and Applications, Vol. 119, No. 1, pp. 185-201, 2003).

In this study, the capacitated vehicle routing problem with shift based time constraints is taken into consideration. The study stemmed from an application in a cross dock. The considered cross dock is assumed to feed directly the production lines of its customer. The customer has a just-in-time production system that requires producing only in necessary quantities at the necessary times. This necessitates the arrival of the parts/products collected from different suppliers at the customer at the beginning of each shift of production. The shift times constitute deadlines for the products to be collected from the suppliers and used in each shift. The collection problem then can be seen as the capacitated vehicle routing problem with shift based time constraints. The objective of the collection problem is to minimize the routing costs. For the accomplishment of this objective it is required to decide on products of which shift(s) should be taken from a supplier when a vehicle arrives at that supplier. For the solution of the problem a mathematical model is formulated. Since the dealt problem is NP-Hard, meta-heuristic solution approaches based on variable neighborhood search and simulated annealing are proposed. Computational experimentation is conducted on the test problems which are tailored from the capacitated vehicle routing instances from the literature.

Wavelet methods possess versatile properties for statistical applications. We would like to explore the advantages of using wavelets in the analyses in two different research areas. First of all, we develop an integrated tool for online detection of network anomalies. We consider statistical change point detection algorithms, for both local changes in the variance and for jumps detection, and propose modified versions of these algorithms based on moving window techniques. We investigate performances on simulated data and on network traffic data with several superimposed attacks. All detection methods are based on wavelet packets transformations. We also propose a Bayesian model for the analysis of high-throughput data where the outcome of interest has a natural ordering. The method provides a unified approach for identifying relevant markers and predicting class memberships. This is accomplished by building a stochastic search variable selection method into an ordinal model. We apply the methodology to the analysis of proteomic studies in prostate cancer. We explore wavelet-based techniques to remove noise from the protein mass spectra. The goal is to identify protein markers associated with prostate-specific antigen (PSA) level, an ordinal diagnostic measure currently used to stratify patients into different risk groups.

Today's hardware is becoming more and more parallel. While embarrassingly parallel codes, such as high-performance computing ones, can readily take advantage of this increased number of cores, most other types of code cannot easily scale using traditional data and/or task parallelism and cores are therefore left idling resulting in lost opportunities to improve performance. The opportunistic computing paradigm, on which this thesis rests, is the idea that computations should dynamically adapt to and exploit the opportunities that arise due to idling resources to enhance their performance or quality. In this thesis, I propose to utilize algorithmic properties to develop programming models that leverage this idea thereby providing models that increase and improve the parallelism that can be exploited. I exploit three distinct algorithmic properties: i) algorithmic diversity, ii) the semantic content of data-structures, and iii) the variable nature of results in certain applications. This thesis presents three main contributions: i) the N-way model which leverages algorithmic diversity to speed up hitherto sequential code, ii) an extension to the N-way model which opportunistically improves the quality of computations and iii) a framework allowing the programmer to specify the semantics of data-structures to improve the performance of optimistic parallelism.

Il est souhaitable qu'une analyse syntaxique -en traitement automatique des langues naturelles- soit réalisée avec plus ou moins de précision en fonction du contexte, c'est-à-dire que sa granularité soit réglable. Afin d'atteindre cet objectif, nous présentons ici des études préliminaires permettant d'appréhender les contextes technique et scientifique qui soulèvent ce problème. Nous établissons un cadre pour les développements à réaliser et pour leur évaluation. Nous choisissons un formalisme d'analyse par satisfaction de contraintes (celui des Grammaires de Propriétés) ayant l'avantage de permettre l'utilisation des mêmes ressources linguistiques avec un degré de précision réglable. Nous introduisons une reformulation mathématique du formalisme des Grammaires de Propriétés et nous définissons une mesure (la densité de satisfaction), qui permet de contrôler la granularité de l'analyse. Puis nous décrivons un ensemble d'outils modulaires (LPLSuite) et de ressources (lexique et sous-lexiques DicoLPL) développés pour permettre une analyse syntaxique et susceptibles d'être embarqués<br />dans des applications de haut niveau. Nous présentons et évaluons ensuite plusieurs analyseurs syntaxiques dans ce formalisme, le dernier (SeedParser) étant destiné à mettre en oeuvre une véritable analyse à granularité variable. L'évaluation de ces outils est l'objet d'une étude approfondie. Enn, nous présentons quelques applications développées à l'aide de nos outils.

L'analyse des données fonctionnelles constitue une branche de la statistique dont le développement s'est fortement intensifié ces dernières années. Dans cette thèse, on s'intéresse à des problèmes de régression fonctionnelle pour lesquels il s'agit d'expliquer les variations d'une variable d'intérêt réelle à partir d'une variable explicative fonctionnelle, c'est-à-dire à valeur dans un espace de dimension éventuellement infinie. On considère plus précisément des modèles de régression linéaire. Deux types d'estimation sont proposés: l'estimation de quantiles conditionnels et l'estimation de la moyenne conditionnelle (cette dernière étant considérée dans le cas où la variable explicative est non bruitée, puis lorsque celle-ci est soumise à des erreurs de mesure). Dans chaque cas, des estimateurs basés sur les fonctions splines sont proposés, solutions de problèmes de minimisation pénalisés, la pénalisation intervenant pour contourner le problème lié au fait que la variable explicative est à valeurs dans un espace de dimension infinie. Finalement, on s'intéresse aux aspects pratique de cette étude, au moyen de simulations, puis sur un jeu de données réelles concernant la prévision de pics de pollution à l'ozone à Toulouse.

Title from PDF of title page. / Document formatted into pages; contains 123 pages. / Thesis (M.S.)--University of South Florida, 2001. / Includes bibliographical references. / Text (Electronic thesis) in PDF format. / ABSTRACT: Simulating the processes of rainfall and runoff are at the core of hydrologic modeling. Geomorphologic features, rainfall variability, soil types, and water table depths strongly influence hydrological process in Florida ecosystems. Topographic characteristics of the terrain define the stream paths and landscape. Alteration of these characteristics as a result of urban and/or agricultural developments, for example, can highly influence wetlands and river basin response. There are two predominant landforms in Florida: wetlands, where Variable Saturated Areas form near streams causing saturation excess runoff, and uplands where runoff is mainly generated by infiltration excess. The objective of this work is to analyze the impacts of geomorphologic and hydrologic characteristics on runoff mechanisms in humid environments such as Florida. In general, most research at the hillslope scale use hypothetical values of rainfall, sometimes non-realistic values, and single slope forms to explain the geomorphic and hydrologic process on Variable Saturated Areas. In this thesis, the complexity of hillslope processes on actual Florida topography is assessed by coupling a Digital Elevation Model with a two-dimensional variable saturated-unsaturated flow model called HYDRUS-2D. Actual rainfall records and soil parameters from the Characterization Data for Selected Florida Soils, Soil Survey were used to evaluate hydrologic impacts. A commerical software package, River Tools was used to display and extract topographic information from the Digital Elevation Models.Results show that when inflitration excess runoff is dominant, infiltration and runoff are very sensitive to time resolution, especially for convective storms. When saturation excess occurs, runoff is not affected by rainfall intensity. However, saturated hydraulic conductivity, depth to the water table, slope and curvature highly influence the extent of Variable Saturated Areas. Results indicate runoff in shallow water table environments is produced mainly by subsurface storm runoff, running below the surface, except in hillslopes with concave curvature and mild slopes. Additionally, concave hillslopes generate more saturation excess runoff than straight and convex hillslopes. / System requirements: World Wide Web browser and PDF reader. / Mode of access: World Wide Web.

Waterflooding is a common type of oil recovery techniques where water is pumped into the reservoir for increased productivity. Reservoir states change with time, as such, different injection and production settings will be required to lead the process to optimal operation which is actually a dynamic optimization problem. This could be solved through optimal control techniques which traditionally can only provide an open-loop solution. However, this solution is not appropriate for reservoir production due to numerous uncertain properties involved. Models that are updated through the current industrial practice of ‘history matching’ may fail to predict reality correctly and therefore, solutions based on history-matched models may be suboptimal or non-optimal at all. Due to its ability in counteracting the effects uncertainties, direct feedback control has been proposed recently for optimal waterflooding operations. In this work, two feedback approaches were developed for waterflooding process optimization. The first approach is based on the principle of receding horizon control (RHC) while the second is a new dynamic optimization method developed from the technique of self-optimizing control (SOC). For the SOC methodology, appropriate controlled variables (CVs) as combinations of measurement histories and manipulated variables are first derived through regression based on simulation data obtained from a nominal model. Then the optimal feedback control law was represented as a linear function of measurement histories from the CVs obtained. Based on simulation studies, the RHC approach was found to be very sensitive to uncertainties when the nominal model differed significantly from the conceived real reservoir. The SOC methodology on the other hand, was shown to achieve an operational profit with only 2% worse than the true optimal control, but 30% better than the open-loop optimal control under the same uncertainties. The simplicity of the developed SOC approach coupled with its robustness to handle uncertainties proved its potentials to real industrial applications.

Understanding joint and causal relationships among multiple endogenous variables has been of much interest to researchers in the field of activity and travel behavior modeling. Structural equation models have been widely developed for modeling and analyzing the causal relationships among travel time, activity duration, car ownership, trip frequency and activity frequency. In the model, travel time and activity duration are treated as continuous variables, while car ownership, trip frequency and activity frequency as ordered discrete variables. However, many endogenous variables of interest in travel behavior are not continuous or ordered discrete but unordered discrete in nature, such as mode choice, destination choice, trip chaining pattern and time-of-day choice (it can be classified into a few categories such as AM peak, midday, PM peak and off-peak). A modeling methodology with involvement of unordered discrete variables is highly desired for better understanding the causal relationships among these variables. Under this background, the proposed dissertation study will be dedicated into seeking an appropriate modeling methodology which aids in identifying the causal relationships among activity and travel variables including unordered discrete variables. In this dissertation, the proposed modeling methodologies are applied for modeling the causal relationship between three pairs of endogenous variables: trip chaining pattern vs. mode choice, activity timing vs. duration and trip departure time vs.mode choice. The data used for modeling analysis is extracted from Swiss Travel Microcensus 2000. Such models provide us with rigorous criteria in selecting a reasonable application sequence of sub-models in the activity-based travel demand model system.

This work is motivated by the Variable Specific Impulse Magnetoplasma Rocket (VASIMR) experiment. This device uses a helicon antenna to generate a plasma inside a dielectric tube, which is radially confined and directed towards the rocket nozzle by an axial magnetic field. An ion cyclotron heating antenna further heats the ions, and a magnetic nozzle accelerates the plasma along the confining magnetic field as it leaves the rocket, ultimately allowing it to detach from the magnetic field and produce thrust. The experimental research presented here provides insight into the physical mechanisms of power flow in a helicon system by providing an overall system power balance in the form of heat flux measurements, and exploring changes in the heat fluxes in different parts of the system in response to varying operational parameters. An infrared (IR) camera measures the total heat flux into the dielectric tube surface, and axially scanned bolometer and UV photodiode probes measure the radial power loss from particles and radiation. Results from IR camera measurements on three different helicon systems are presented: the VASIMR VX-50 experiment, the VASIMR VX-CR experiment, and the University of Texas at Austin (UT) helicon experiment. These results demonstrate the development of the IR camera diagnostic for use on helicon systems of varying scale and geometry, and show reasonable agreement as to the fraction of input power lost to the dielectric tube walls. On the UT experiment, the results presented account for essentially all of the input power, providing a full system power balance. The data from all three experiments indicate that radial transport of ions to the interior wall is the dominant mechanism of power loss, with UV radiation contributing a small percentage. Additional experiments on the UT helicon explore energy and particle transport to the wall due to capacitive coupling of ions near the antenna. These experiments show clear damage to the dielectric tube surface directly under the antenna, due to physical plasma etching of the surface by bombarding ions that are accelerated into the wall by local electric fields from the antenna. / text