L'écriture de spécifications pour des logiciels en général et en particulier pour des applications sécurisées demande de développer des techniques qui facilitent la détection et la prévention des erreurs de conception, dès les premières phases du développement. Ce besoin est motivé par les coûts et délais des phases de vérification et validation. De nombreuses méthodes de spécification, tant formelles qu'informelles ont été proposées et, comme nous le verrons dans cette thèse, les approches formelles donnent des spécifications de meilleure qualité.L'ingénierie des systèmes sécurisés propose l'utilisation de modèles de conception de la sécurité pour représenter les applications sécurisées. Dans de nombreux cas, ces modèles se basent sur les notations graphiques d'UML avec des extensions, sous forme de profils comme SecureUML, pour exprimer la sécurité. Néanmoins, les notations d'UML, même étendues avec des assertions OCL, sont insuffisantes pour garantir la correction de ces modèles. Ceci est notamment du aux limites des outils d'animation utilisés pour valider des modèles UML étendus en OCL. Nous proposons de combiner des langages formels comme Z avec UML pour valider des applications en animant leurs spécifications, indépendamment de futurs choix d'implémentation. Le but de cette thèse est de présenter une approche pour analyser par animation des modèles de conception de la sécurité. Nous utilisons un outil pré-existant, RoZ, pour traduire les aspects fonctionnels du modèle UML en Z. Cependant, RoZ ne couvre pas la modélisation des aspects sécuritaires. Dans cette thèse, nous avons complété l'outil RoZ en l'associant à un noyau de sécurité qui spécifie les concepts du modèle RBAC (Role Based Access Control). Nous utilisons l'animation pour explorer dynamiquement et ainsi valider les aspects sécuritaires de l'application.Notre approche et les outils qui la supportent intègrent UML, SecureUML (un langage de modélisation de la sécurité), RBAC, RoZ, Z et Jaza, un animateur pour le langage Z. L'animation des spécifications prend la forme de scénarios définis par l'utilisateur qui permettent de se convaincre que la spécification décrit correctement ses besoins. Notre approche permet une validation dès la phase de spécification, qui prend en considération l'interaction entre les modèles fonctionnel et sécuritaire, et qui fait abstraction des choix de l'implémentation. Les éléments du modèle fonctionnel peuvent être utilisés comme contexte dans la définition des permissions du modèle de sécurité. Notre approche ne met pas de contrainte sur ce modèle fonctionnel ce qui permet de l'utiliser pour une vaste gamme d'applications.

Although higher correlation between gauge and radar at hourly or daily accumulations are reported, it is rarely observed at higher time resolution (e.g. 10 -minute). This study investigates six major rainfall events in year 2000 in the greater Winnipeg area with durations varying from four to nine hours. The correlation between gauge and radar measurements of precipitation is found to be only 0.3 at 10-minute resolution and 0.55 at hourly resolution using Marshall-Palmer’s Z-R relationship (Z=200R1.6). The rainfalls are classified into convective and stratiform regions using Steiner et al. (1995)’s algorithm and two different Z-R relationships are tested to minimize the error associated with the variability of drop-size-distribution, however no improvement is observed. The performance of the artificial neural network is explored as a reflectivity-rainfall mapping function. Three different types of neural networks are explored: the back propagation network, the radial basis function network, and the generalized regression neural network. It is observed that the neural network’s performance is better than the Z-R relationship to estimate the rainfall events which was used for training and validation (correlation 0.67). When this network is tested on a new rainfall its performance is found quite similar to that obtained from the Z-R relationship (correlation 0.33). Based on this observation neural network may be recommended as a post-processing tool but may not be very useful for operational purposes - at least as used in this study. Variability in weather and precipitation scenarios affects the radar measurements which apparently makes it impossible for the neural network or the Z-R relationship to show consistent performance at every rainfall event. To account for variability in weather and rainfall scenarios conventional correction schemes for attenuation and hail contamination are applied and a trajectory model is developed to account for rainfall advection due to wind drift. The trajectory model uses velocity obtained from the single-doppler observation. A space-time interpolation technique is applied to generate reflectivity maps at one-minute resolution based on the direction obtained from the correlation based tracking algorithm. The trajectory model uses the generated reflectivity maps having one-minute resolution which help to account for the travel time by the rainfall mass to reach to the ground. It was found that the attenuation correction algorithm adversely increases the reflectivity. This study assumes that the higher reflectivity caused by hail contaminated regions is one reason for the overestimation in the attenuation correction process. It was observed that the hail capping method applied prior to the attenuation correction algorithm helps to improve the situation. A statistical expression to account for radome attenuation is also developed. It is observed that the correlation between the gauge and the radar measurement is 0.81 after applying the various algorithms. Although Marshall-Palmer’s relationship is recommended for stratiform precipitation only, this study found it suitable for both convective and stratiform precipitation when attenuation is properly taken into account. The precipitation processing model developed in this study generates more accurate rainfall estimates at the surface from radar observations and may be a better choice for rainfall-runoff modellers.

We construct geometric models for K-homology with coefficients based on the theory of Z/k-manifolds. To do so, we generalize the operations and relations Baum and Douglas put on spinc-manifolds to spinc Z/kZ-manifolds. We then de fine a model for K-homology with coefficients in Z/k using cycles of the form ((Q,P), (E,F), f) where (Q, P) is a spinc Z/k-manifold, (E, F) is a Z/k-vector bundle over (Q, P) and f is a continuous map from (Q, P) into the space whose K-homology we are modelling. Using results of Rosenberg and Schochet, we then construct an analytic model for K-homology with coefficients in Z/k and a natural map from our geometric model to this analytic model. We show that this map is an isomorphism in the case of finite CW-complexes. Finally, using direct limits, we produced geometric models for K-homology with coefficients in any countable abelian group.

This thesis describes an analysis of the process e⁺e^— → l⁺l^- (where l = e, μ,, τ) at centre-of-mass energies between 88 GeV and 94 GeV, using the data collected by the DELPHI detector between the years 1991 and 1993. The leptonic decays of the Z° boson are selected without attempting to separate the three lepton types, thus making it an inclusive lepton analysis. The theory behind lepton pair production is introduced and the extraction of various electroweak parameters from the experimental observables is discussed. The LEP collider and the DELPHI detector are described, with special emphasis being given to the sub-detectors used in the analysis. The criteria used to select a high purity leptonic sample are described along with calculations of various backgrounds and efficiencies. The sample of selected leptonic events is then used to measure the cross-sections and forward-backward asymmetries. Finally, a fit to these cross-sections and asymmetries, together with the hadronic (e⁺e^- → qq̄) cross-sections, is carried out. Various Z° parameters are obtained: the mass and total width Mz-91.1876 ± 0.0052 GeV/c², Γ_z = 2.4971 ± 0.0061 GeV, the ratio of the hadronic to leptonic partial widths R_l = 20.73 ± 0.09, and the pole leptonic asymmetry (A°_FB)¹ = 0.0195 ± 0.0042. Using these results and the value of the strong coupling constant (α_s), determined by the DELPHI collaboration, the number of light neutrino species is determined to be N_ν = 3.045 ± 0.035. The leptonic partial width is found to be: Γ_l = 83.82 ± 0.29 MeV. Using the measured leptonic forward-backward asymmetries, the squared vector and axial-vector couplings of the Z° to charged leptons are found to be (ĝ_v¹)^{2</sup = (1.65 ± 0.36) x 10^-3 and (ĝ_a¹)}2</sup> = 0.2505 ± 0.0009. These values can be used to determine the effective rho parameter and the effective weak mixing angle: p̂ = 1.0020 ± 0.0036, and sin² θ^eff_lept = 0.2297 ± 0.0024. A full Standard Model fit to the data gives the values of the strong coupling constant, α_s, and the mass of the top quark, m_top, as being: α_s = 0.123 ± 0.010, m_top = 178⁺²²_-25 (expt)<sup>+18<sup>_-16(Higg s)GeV/c², where 60 < m_Higgs (GeV/c²) < 1000 with a central value of 300 GeV/c². All the results obtained agree with the results from the lepton-identified analyses (analyses in which leptonic events are selected on the basis of their individual flavour) and with the predictions of the Standard Model.

The purpose of this work was to study the ability of the Slacks-Based Model of Data Envelopment Analysis in the prediction of corporate failure of non-manufacturing companies as compared to Altman’s Z’’ score model. This research looks at non-manufacturing firms specifically and attempts to classify companies without looking at the asset size of the firm. A DEA model based on the Altman’s Z’’ score financial ratios was created as well as a revised DEA model. The overall accuracy of the models showed the revised DEA model to be more accurate than the original DEA model as well as the Altman Z’’ score. This indicated that bankruptcy could be predicted without the use of total assets or liabilities as variables. This also showed the ability of an SBM DEA model to predict bankruptcy.

The purpose of this work was to study the ability of the Slacks-Based Model of Data Envelopment Analysis in the prediction of corporate failure of non-manufacturing companies as compared to Altman’s Z’’ score model. This research looks at non-manufacturing firms specifically and attempts to classify companies without looking at the asset size of the firm. A DEA model based on the Altman’s Z’’ score financial ratios was created as well as a revised DEA model. The overall accuracy of the models showed the revised DEA model to be more accurate than the original DEA model as well as the Altman Z’’ score. This indicated that bankruptcy could be predicted without the use of total assets or liabilities as variables. This also showed the ability of an SBM DEA model to predict bankruptcy.

Although higher correlation between gauge and radar at hourly or daily accumulations are reported, it is rarely observed at higher time resolution (e.g. 10 -minute). This study investigates six major rainfall events in year 2000 in the greater Winnipeg area with durations varying from four to nine hours. The correlation between gauge and radar measurements of precipitation is found to be only 0.3 at 10-minute resolution and 0.55 at hourly resolution using Marshall-Palmer’s Z-R relationship (Z=200R1.6). The rainfalls are classified into convective and stratiform regions using Steiner et al. (1995)’s algorithm and two different Z-R relationships are tested to minimize the error associated with the variability of drop-size-distribution, however no improvement is observed. The performance of the artificial neural network is explored as a reflectivity-rainfall mapping function. Three different types of neural networks are explored: the back propagation network, the radial basis function network, and the generalized regression neural network. It is observed that the neural network’s performance is better than the Z-R relationship to estimate the rainfall events which was used for training and validation (correlation 0.67). When this network is tested on a new rainfall its performance is found quite similar to that obtained from the Z-R relationship (correlation 0.33). Based on this observation neural network may be recommended as a post-processing tool but may not be very useful for operational purposes - at least as used in this study. Variability in weather and precipitation scenarios affects the radar measurements which apparently makes it impossible for the neural network or the Z-R relationship to show consistent performance at every rainfall event. To account for variability in weather and rainfall scenarios conventional correction schemes for attenuation and hail contamination are applied and a trajectory model is developed to account for rainfall advection due to wind drift. The trajectory model uses velocity obtained from the single-doppler observation. A space-time interpolation technique is applied to generate reflectivity maps at one-minute resolution based on the direction obtained from the correlation based tracking algorithm. The trajectory model uses the generated reflectivity maps having one-minute resolution which help to account for the travel time by the rainfall mass to reach to the ground. It was found that the attenuation correction algorithm adversely increases the reflectivity. This study assumes that the higher reflectivity caused by hail contaminated regions is one reason for the overestimation in the attenuation correction process. It was observed that the hail capping method applied prior to the attenuation correction algorithm helps to improve the situation. A statistical expression to account for radome attenuation is also developed. It is observed that the correlation between the gauge and the radar measurement is 0.81 after applying the various algorithms. Although Marshall-Palmer’s relationship is recommended for stratiform precipitation only, this study found it suitable for both convective and stratiform precipitation when attenuation is properly taken into account. The precipitation processing model developed in this study generates more accurate rainfall estimates at the surface from radar observations and may be a better choice for rainfall-runoff modellers.

Leptonic decay modes of Z-boson constitute one of the important class of the decays for checking predictions and improving parameters of the standard model. In next generation of the accelerators, it will be produced more than 10^8 Z-boson pear year. Therefore, It appears real possibility to analyze the rare decays of Z, which are absent at tree level in standard model. Moreover, the rare decays are quite sensitive to the existence of new physics beyond the standard model. One of the possible source for the new physics is noncommutative theories (NC). Noncommutative theories have rich phenomenological implications due to the appearance of new interactions, which are forbidden in standard model. In this thesis, we examine the Z $rightarrow nu bar{nu} gamma$ decay in noncommutative standard model. We study the sensitivity of the decay width on the noncommutative scale parameter Lambda and parameters $C_{0i}$ and $C_{ij}$, which defines the direction of background electric and magnetic fields.

The withdrawal of water sources concluded the reuse of treated wastewaters, especially for non-potable purposes. Agricultural use of the reclaimed wastewaters is one of the reuse options. However health considerations of the reuse of reclaimed wastewaters for public related purposes are underestimated, since wastewaters contain a variety of microbial pathogens, which may be transmitted to workers and consumers through the crops irrigated. Of these, parasitic eggs have a special place, as they are capable of surviving in the soil for months or even years, depending on environmental conditions. There is insufficient accumulated information on the health related criteria for the reuse of treated wastewaters in Turkey. The aim of this study was therefore to determine the helminthic eggs in raw sewage and in effluents of ASKi municipal wastewater treatment plant in Ankara. The study involved examining to decide whether these organisms exist in the wastewaters at all, and if so in what concentrations. Modified Bailenger&rsquo / s method, which published in the &ldquo / WHO Laboratory Manual of Parasitological and Bacteriological Techniques&rdquo / and &ldquo / U.S.EPA ICR Microbial Laboratory Manual&rdquo / were used in developing the specific methods used in this study.

ABSTRACT CHARACTERIZATION OF KIZILCAHAMAM GEOTHERMAL FIELD BY TRACER TESTING Tevfik Kaya M.S, Petroleum and Natural Gas Engineering Department Supervisor : Assoc. Prof. Dr. Serhat Akin Co-Supervisor : Prof. Dr. Mahmut Parlaktuna September 2005, 107 Pages Kizilcahamam Geothermal Field which is 70 km far from Ankara, has been utilized for Geothermal District Heating System, 25 MWt, 2500 residences capacity, greenhouses heating, thermal facilities since 1994. The average production rate is 350m3/h during the heating season , 150m3/h during the summer season for hot water and yearly average reinjection rate is 114m3/h from the field. The long term projections has been studied concerning on expected pressure decline by matching 10 years field history data which contain dynamic level and temperature data. The pressure decline is 140 kPa in the field between 1999 and 2005 with the existing reinjection rate, if the existing rates do not change, the additional pressure decline which is 120 kPa will be occurred up to 2011. In order to get more information from the field, the fluorescein as tracer has been injected in to the MTA-1, and the samples were collected from the MTA-2, Fethi Bey, IHL-1 and IHL-3 for 3 months. The fluorescein concentration has been detected by using fluorimeter, and tracer concentration time plots were analyzed. The fluoreiscein was detected in short breakthrough time in MTA-2 and Fethi Bey which are close to reinjection well, breakthrough time is longer in IHL-1 and IHL-3. The interpretation of tracer test shows that there is communication between all wells. Tracer concentration time plots were compared with different mathematical models, the best match was obtained with multi-fractured model. These results show that Kizilcahamam field is not homogeneous field. It is expected that increasing the reinjection rate will decrease the pressure decline in the field.