Although service oriented architecture has reached a particular maturity level especially in the technological dimension, there is a lack of common and acceptable approach to design a software system through composition and integration of web services. In this thesis, a service oriented system design approach for Service Oriented Architecture based software development is introduced to fill this gap. This new methodology basically offers a procedural top-down decomposition of a given software system allowing several abstraction levels. At the higher levels of the decomposition, the system is divided into abstract nodes that correspond to process models in the decomposition tree. Any node is a process and keeps the sequence and the state information for the possible sub-processes in this decomposition tree. Nodes which are defined as process models may include some sub-nodes to present details for the intermediate levels of the model. Eventually at the leaf level, process models are decomposed into existing web services as the atomic units of system execution. All processes constructing the system decomposition tree are modeled with BPEL (Business Process Execution Language) to expose the algorithmic details of the design. This modeling technique is also supported with a graphical modeling language referred to as SOSEML (Service Oriented Software Engineering Modeling Language) that is also newly introduced in this thesis.

As the tick-by-tick data of financial transactions become easier to reach, processing that much of information in an efficient and correct way to estimate the integrated volatility gains importance. However, empirical findings show that, this much of data may become unusable due to microstructure effects. Most common way to get over this problem is to sample the data in equidistant intervals of calendar, tick or business time scales. The comparative researches on that subject generally assert that, the most successful sampling scheme is a calendar time sampling which samples the data every 5 to 20 minutes. But this generally means throwing out more than 99 percent of the data. So it is obvious that a more efficient sampling method is needed. Although there are some researches on using alternative techniques, none of them is proven to be the best. Our study is concerned with a sampling scheme that uses the information in different scales of frequency and is less prone to microstructure effects. We introduce a new concept of business intensity, the sampler of which is named Optimizable Multiresolution Quadratic Variation Filter. Our filter uses multiresolution analysis techniques to decompose the data into different scales and quadratic variation to build up the new business time scale. Our empirical findings show that our filter is clearly less prone to microstructure effects than any other common sampling method. We use the classified tick-by-tick data for Turkish Interbank FX market. The market is closed for nearly 14 hours of the day, so big jumps occur between closing and opening prices. We also propose a new smoothing algorithm to reduce the effects of those jumps.

Dealing with missing data in spatio-temporal time series constitutes important branch of general missing data problem. Since the statistical properties of time-dependent data characterized by sequentiality of observations then any interruption of consecutiveness in time series will cause severe problems. In order to make reliable analyses in this case missing data must be handled cautiously without disturbing the series statistical properties, mainly as temporal and spatial dependencies. In this study we aimed to compare several imputation methods for the appropriate completion of missing values of the spatio-temporal meteorological time series. For this purpose, several missing imputation methods are assessed on their imputation performances for artificially created missing data in monthly total precipitation and monthly mean temperature series which are obtained from the climate stations of Turkish State Meteorological Service. Artificially created missing data are estimated by using six methods. Single Arithmetic Average (SAA), Normal Ratio (NR) and NR Weighted with Correlations (NRWC) are the three simple methods used in the study. On the other hand, we used two computational intensive methods for missing data imputation which are called Multi Layer Perceptron type Neural Network (MLPNN) and Monte Carlo Markov Chain based on Expectation-Maximization Algorithm (EM-MCMC). In addition to these, we propose a modification in the EM-MCMC method in which results of simple imputation methods are used as auxiliary variables. Beside the using accuracy measure based on squared errors we proposed Correlation Dimension (CD) technique for appropriate evaluation of imputation performances which is also important subject of Nonlinear Dynamic Time Series Analysis.

Current approaches integrating large scale data and information from a variety of sources to reveal molecular basis of cellular events do not adequately benefit from pathway information. Here, we portray a network structure based pathway enrichment system that fuses and exploits model and data: signalling pathways are taken as the biological models while microarray and ChIP-seq data are the sample input data sources among many other alternatives. Our model- and data-driven hybrid system allows to quantitatively assessing the biological activity of a cyclic pathway and simultaneous enrichment of the significant paths leading to the ultimate cellular response. Signal Transduction Score Flow (SiTSFlow) algorithm is the fundamental constituent of proposed network structure based pathway enrichment system. SiTSFlow algorithm converts each pathway into a cascaded graph and then gene scores are mapped onto the protein nodes. Gene scores are transferred to en route of the pathway to form a final activity score describing behaviour of a specific process in the pathway while enriching of the gene node scores. Because of cyclic pathways, the algorithm runs in an iterative manner and it terminates when the node scores converge. The converged final activity score provides a quantitative measure to assess the biological significance of a process under the given experimental conditions. The conversion of cyclic pathways into cascaded graphs is performed by using a linear time multiple source Breadth First Search Algorithm. Furthermore, proposed network structure based pathway enrichment system works in linear time in terms of nodes and edges of given pathways. In order to explore various biological responses of several processes in a global signalling network, the selected small pathways have been unified based on their common gene and process nodes. The merge algorithm for pathways also runs in linear time in terms of nodes and edges of given pathways. In the experiments, SiTSFlow algorithm proved the convergence behaviour of activity scores for several cyclic pathways and for a global signalling network. The biological results obtained by assessing of experimental data by described network structure based pathway enrichment system were in correlation with the expected cellular behaviour under the given experimental conditions.

Toute coexistence religieuse peut être facteur de conflits religieux ou symbole de respect de liberté, de tolérance ou de vivre ensemble, dépendamment de la façon dont elle est comprise, ou de la nature des religions coexistantes. Même quand chaque religion partage une vision du monde différente par rapport aux autres, on constate que la coexistence entre religions révélées (christianisme, islam, judaïsme – et bouddhisme dans certains cas) est plus facile, car ces religions partagent d’une façon ou d’une autre certaines valeurs communes. Par contre, il est très difficile de concevoir une logique de dialogue entre des religions dites « révélées » et des religions traditionnelles. Pourtant, la rencontre du christianisme avec des cultures religieuses traditionnelles africaines montre que malgré les difficultés, il y a possibilité d’avoir des échanges fructueux aussi avec les religions traditionnelles. Dans le contexte haïtien, la rencontre du christianisme avec le vaudou ne laisse pas toujours la possibilité aux observateurs d’entrevoir que la religion est signe de paix et de cohésion sociale. Étant donné que leur antagonisme se caractérise souvent par des facteurs comme l’intolérance, l’irrespect de la liberté de l’autre, etc., le problème est surtout dans la gestion des rapports religieux. Néanmoins, dans certains cas où les intérêts religieux sont traités en second plan, il y a lieu de constater que le tableau de la coexistence religieux haïtien est riche en symbole de paix et de compréhension mutuelle. Donc, ce travail de recherche cherche à comprendre la conception que le christianisme se fait du vaudou et vice versa, dans le but de voir avec exactitude les facteurs de divergences acceptables (et non acceptables) et ceux qui pourraient être à la base d’un éventuel dialogue interreligieux entre christianisme et vaudou dans le contexte haïtien. Pour améliorer les rapports entre adeptes du vaudou et chrétiens en Haïti, ce travail propose des méthodes pouvant aboutir à un vivre ensemble religieux pacifié, plus tolérant et d’une connaissance réciproque et intelligente de l’autre. Le but du dialogue présenté n’est pas que le christianisme et le vaudou travaillent ensemble à tous les points de vue, ni même qu’ils s’acceptent complètement, il s’agit plutôt d’une proposition d’une vie commune dans la paix, sans calomnies et stéréotypes réciproques. / Any religious coexistence can be a factor of religious conflict or symbol of respect for freedom, tolerance or live together, depending on the way in which it is included, or the nature of the religions in coexistence. Even when each religion shares a vision of the world different compared to the other, it is found that the coexistence between religions (Christianity, Islam and Judaism - and Buddhism in some cases) is more effective, because these religions share in one way or another some common values. On the other hand, it is constantly difficult to conceive of a pluralistic approach in a logic of dialogue between revealed religions and traditional religions. Yet, the meeting of Christianity with traditional African religious cultures shows that despite the difficulties, there is a possibility to have fruitful exchanges also with the traditional religions. In the context of Haiti, the meeting of Christianity with the voodoo does not leave always the possibility for observers to foresee that the religion is a sign of peace and social cohesion. Given that their antagonism is often characterized by factors such as intolerance, the disrespect of the freedom of the other, etc., the problem is especially in the management of religious relationships. Nevertheless, in some cases where the religious interests are treated in the second plan, it has to be noted that the coexistence of these religions in Haiti can be rich in symbol of peace and mutual understanding. Therefore, this research work seeks to understand the design of Christianity from the perspective of voodoo and vice versa, in the aim to see with accuracy the factors of acceptable (and inacceptable) differences and those that could be the basis of a possible interreligious Dialogue between Christianity and Voodoo in the Haitian context.To improve the relationship between the followers of the voodoo and Christians in Haiti, this work finally proposes some methods that can lead to a peaceful religious coexistence, toward more tolerant and a reciprocal knowledge and intelligent approach to the other. The goal of the dialogue presented in this dissertation is neither that Christianity and the Voodoo should work together in all points of view, nor even that they completely recognize mutually their belief, it is rather a proposal for a common life in peace, without slander and reciprocal stereotypes

There exists in the modern worlda form of non-Christianised religious thought which develops the basic ideas of indigenous African religion beyond their beginnings, and is represented in authorssuch as Kamalu, Osabutey-Aguedze, etc. The spheres of interest in such authors fiJay be analysed in terms of the following areas: Intervening ideological conditions bearing on African life (particularr; theological and cosmological ideas): The historical background of African life; The roots of African life, as manifested in its traditions, and tts ethical and cultural heritage; Means for the innovative development of African life, found in African concepts of knowledge, mysticism and magic; The perceived destiny of African life. The thesis concludes with an indication of areas of agreement and debate in post-traditional African thought, of problems faced by such thought; and of other possible priorities for future study. / Religious Studies and Arabic / D.Th. (Religious Studies)

Regression analysis is very popular among researchers in various fields but almost all the researchers use the classical methods which assume that X is nonstochastic and the error is normally distributed. However, in real life problems, X is generally stochastic and error can be nonnormal. Maximum likelihood (ML) estimation technique which is known to have optimal features, is very problematic in situations when the distribution of X (marginal part) or error (conditional part) is nonnormal. Modified maximum likelihood (MML) technique which is asymptotically giving the estimators equivalent to the ML estimators, gives us the opportunity to conduct the estimation and the hypothesis testing procedures under nonnormal marginal and conditional distributions. In this study we show that MML estimators are highly efficient and robust. Moreover, the test statistics based on the MML estimators are much more powerful and robust compared to the test statistics based on least squares (LS) estimators which are mostly used in literature. Theoretically, MML estimators are asymptotically minimum variance bound (MVB) estimators but simulation results show that they are highly efficient even for small sample sizes. In this thesis, Weibull and Generalized Logistic distributions are used for illustration and the results given are based on these distributions. As a future study, MML technique can be utilized for other types of distributions and the procedures based on bivariate data can be extended to multivariate data.

In time series models, autoregressive processes are one of the most popular stochastic processes, which are stationary under certain conditions. In this study we consider nonstationary autoregressive models of order one, which have iid random errors. One of the important nonstationary time series models is the unit root process in AR (1), which simply implies that a shock to the system has permanent effect through time. Therefore, testing unit root is a very important problem. However, under nonstationarity, any estimator of the autoregressive coefficient does not have a known exact distribution and the usual t &ndash / statistic is not accurate even if the sample size is very large. Hence,Wiener process is invoked to obtain the asymptotic distribution of the LSE under normality. The first four moments of under normality have been worked out for large n. In 1998, Tiku and Wong proposed the new test statistics and whose type I error and power values are calculated by using three &ndash / moment chi &ndash / square or four &ndash / moment F approximations. The test statistics are based on the modified maximum likelihood estimators and the least square estimators, respectively. They evaluated the type I errors and the power of these tests for a family of symmetric distributions (scaled Student&rsquo / s t). In this thesis, we have extended this work to skewed distributions, namely, gamma and generalized logistic.