This thesis shows how the relative efficiency of automotive companies can be evaluated and how the changes in productivity of these companies by time can be observed. There are 17 companies in the analysis which are the main automotive manufacturers of Turkish automotive industry. A method called stepwise approach is used to determine the input and output factors. The two input variables used are the company&rsquo / s Payment for Raw Materials and Components and Payment for Wages and Insurances of Employees / the three output variables are Domestic Sales, Exports and Capacity Usage. The panel data that covers the time period between years 2001 and 2005 is obtained from OSD (Automotive Manufacturers Association). The efficiency analysis is performed according to basic Data Envelopment Analysis (DEA) models which are Charnes, Cooper and Rhodes (CCR) models and Banker, Charnes and Cooper (BCC) models. The software LINGO 10 is used for solving the linear programming models. After finding the overall efficiency, technical efficiency and scale efficiency of each company for each year, the changes in the efficiencies are analyzed by using Malmquist Total Factor Productivity (TFP) Index. The results are illustrated by the help of many tables and graphs for better understanding. When the results in tables and graphs are analyzed, the negative effect of 2001 economic crisis on automotive industry can be observed. Besides, it is seen that the efficiency changes by time show variance from company to company because they produce 7 types of vehicles and there are important differences between them such as production technology, market, demand, etc.

In industrial processes decreasing variation is very important while achieving the targets. For manufacturers, finding out optimal settings of product and process parameters that are capable of producing desired results under great conditions is crucial. In most cases, the quality response is measured on a continuous scale. However, in some cases, the desired quality response may be qualitative (categorical). There are many effective methods to design robust products/process through industrial experimentation when the response variable is continuous. But methods proposed so far in the literature for robust design with categorical response variables have various limitations. This study offers a simple and effective method for the analysis of categorical response data for robust product or process design. This method handles both location and dispersion effects to explore robust settings in an effective way. The method is illustrated on two cases: A foam molding process design and an iron-casting process design.

In this thesis, mathematical modeling and heuristic approaches are developed for surface-to-air weapon-target allocation problem with time varying single shot hit probabilities (SSHP) against linearly approaching threats. First, a nonlinear mathematical model for the problem is formulated to maximize sum of the weighted survival probabilities of assets to be defended. Next, nonlinear objective function and constraints are linearized. Time varying SSHP values are approximated with appropriate closed forms and adapted to the linear model obtained. This model is tested on different scenarios and results are compared with those of the original nonlinear model. It is observed that the linear model is solved much faster than the nonlinear model and produces reasonably good solutions. It is inferred from the solutions of both models that engagements should be made as late as possible, when the threats are closer to the weapons, to have SSHP values higher. A construction heuristic is developed based on this scheme. An improvement heuristic that uses the solution of the construction heuristic is also proposed. Finally, all methods are tested on forty defense scenarios. Two fastest solution methods, the linear model and the construction heuristic, are compared on a large scenario and proposed as appropriate solution techniques for the weapon-target allocation problems.

In this thesis, a simulation study is held and a statistical model is fitted to the simulated data. This data is assumed to be the satisfaction of the customers who withdraw their salary from a particular bank. It is a longitudinal data which has bivariate and binary response. It is assumed to be collected from 200 individuals at four different time points. In such data sets, two types of dependence -the dependence within subject measurements and the dependence between responses- are important and these are considered in the model. The model is Marginalized Transition Random Effects Models, which has three levels. The first level measures the effect of covariates on responses, the second level accounts for temporal changes, and the third level measures the difference between individuals. Markov Chain Monte Carlo methods are used for the model fit. In the simulation study, the changes between the estimated values and true parameters are searched under two conditions, when the model is correctly specified or not. Results suggest that the better convergence is obtained with the full model. The third level which observes the individual changes is more sensitive to the model misspecification than the other levels of the model.

This study presents the theoretical analysis of an active flutter suppression methodology applied to a smart fin. The smart fin consists of a cantilever aluminum plate-like structure with surface bonded piezoelectric (PZT, Lead- Zirconate-Titanate) patches. A thermal analogy method for the purpose of modeling of piezoelectric actuators in MSC&reg / /NASTRAN based on the analogy between thermal strains and piezoelectric strains was presented. The results obtained by the thermal analogy were compared with the reference results and very good agreement was observed. The unsteady aerodynamic loads acting on the structure were calculated by using a linear two-dimensional Doublet-Lattice Method available in MSC&reg / /NASTRAN. These aerodynamic loads were approximated as rational functions of the Laplace variable by using one of the aerodynamic approximation schemes, Roger&amp / #8217 / s approximation, with least-squares method. These approximated aerodynamic loads together with the structural matrices obtained by the finite element method were used to develop the aeroelastic equations of motion of the smart fin in state-space form. The Hinf robust controllers were then designed for the state-space aeroelastic model of the smart fin by considering both SISO (Single-Input Single-Output) and MIMO (Multi-Input Multi-Output) system models. The verification studies of the controllers showed satisfactory flutter suppression performance around the flutter point and a significant improvement in the flutter speed of the smart fin was also observed.

The managing of complex business processes, which are changed due to globalization, calls for the development of powerful information systems that offer generic process modeling and process execution capabilities. Even though contemporary information systems are more and more utilized in enterprises, their actual impact in automatizing complex business process is still limited by the difficulties encountered in design phase. Actually this design phase is time consuming, often subjective and incomplete. In the scope of this study, a reverse approach is followed. Instead of starting with process design, the method of discovering interesting patterns from the navigation traces is taken as basis and a new data analysis methodology named &ldquo / From-to Chart Based Process Discovery&rdquo / is proposed. In this hybrid methodology &ldquo / from-to chart&rdquo / , which is fundamentally dedicated to material handling issues on production floor, is used as the front-end to monitor the transitions among activities of a realistic event log and convert these raw relations into optimum activity sequence. Then a revised version of process mining, which is the back-end of this methodology, upgrades optimum activity sequence into process model.

In mobile computing systems, predicting the next location of a mobile wireless user has gained interest over the past decade. Location prediction may have a wide-range of application areas such as network load balancing, advertising and web page prefetching. In the literature, there exist many location predictors which are divided into two main classes: domain-independent and domain-specific. Song et al. compare the prediction accuracy of the domain-independent predictors from four major families, namely, Markov-based, compression-based, PPM and SPM predictors on Dartmouth&#039 / s campus-wide Wi-Fi mobility data. As a result, the low-order Markov predictors are found as the best predictor. In another work, Bayir et al. propose a domain-specific location predictor (LPMP) as the application of a framework used for discovering mobile cell phone user profiles. In this thesis, we evaluate LPMP and the best Markov predictor with Dartmouth&#039 / s campus-wide Wi-Fi mobility data in terms of accuracy. We also propose a simple method which improves the accuracy of LPMP slightly in the location prediction part of LPMP. Our results show that the accuracy of the best Markov predictor is better than that of LPMP in total. However, interestingly, LPMP yields more accurate results than the best Markov predictor does for the users with the low prediction accuracy.

In this study, meta-analysis of diagnostic tests, Summary Receiver Operating Characteristic (SROC) curve, bivariate random effects and Hierarchical Summary Receiver Operating Characteristic (HSROC) curve theories have been discussed and accuracy in literature of Fine Needle Aspiration (FNA) biopsy that is used in the diagnosis of masses in breast cancer (malignant or benign) has been analyzed. FNA Cytological (FNAC) examination in breast tumor is, easy, effective, effortless, and does not require special training for clinicians. Because of the uncertainty related to FNAC&lsquo / s accurate usage in publications, 25 FNAC studies have been gathered in the meta-analysis. In the plotting of the summary ROC curve, the logit difference and sums of the true positive rates and the false positive rates included in the meta-analysis&lsquo / s codes have been generated by SAS. The formula of the bivariate random effects model and hierarchical summary ROC curve is presented in context with the literature. Then bivariate random effects implementation with the new SAS PROC GLIMMIX is generated. Moreover, HSROC implementation is generated by SAS PROC HSROC NLMIXED. Curves are plotted with RevMan Version 5 (2008). It has been stated that the meta-analytic results of bivariate random effects are nearly identical to the results from the HSROC approach. The results achieved through both random effects meta-analytic methods prove that FNA Cytology is a diagnostic test with a high level of distinguish over breast tumor.

In this thesis, we study two problems. The first one is the renorming problem in Banach lattices. We state the problem and give some known results related to it. Then we pass to construct a positive doubly power bounded operator with a nonpositive inverse on an infinite dimensional AL-space which generalizes the result of [10]. The second problem is related to the mean ergodicity of positive operators on KBspaces. We prove that any positive power bounded operator T in a KB-space E which satisfies lim n!1 dist1 n n&amp / #8722 / 1 Xk=0 Tkx, [&amp / #8722 / g, g] + BE= 0 (8x 2 E, kxk 1), () where BE is the unit ball of E, g 2 E+, and 0 &lt / 1, is mean ergodic and its fixed space Fix(T) is finite dimensional. This generalizes the main result of [12]. Moreover, under the assumption that E is a -Dedekind complete Banach lattice, we prove that if, for any positive power bounded operator T, the condition () implies that T is mean ergodic then E is a KB-space.

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 & Arabic / D.Th. (Religious Studies)