In this thesis we study the essential spectrum of composition operators on the Hardy space of the unit disc and of the upper half-plane. Our starting point is the spectral analysis of the composition operators induced by translations of the upper half-plane. We completely characterize the essential spectrum of a class of composition operators that are induced by perturbations of translations

In this study, we investigate several facets of a due-date quotation problem and develop a model considering jointly due-date quotation, order acceptance and base-stock decisions in a hybrid make-to-stock (MTS) / make-to-order (MTO) and multi-class system with lead time sensitive Poisson demand and exponentially distributed service times. We seek to maximize profit considering lateness penalties and holding costs in the model. We consider three alternative due-date quotation policies each having different properties in terms of due-date flexibility as well as the utilization of state information. In order to evaluate the value of due-date flexibility as well as state information, the performances of the optimal policy and alternative policies are evaluated for various performance measures under different operating conditions. We also discuss the benefit of joint pooling of inventory and capacity under optimal policy and an accept-all policy.

The generalized moment of order k of a mass distribution sigma for a natural number k is given by integral of lambda to the power k with respect to mass distribution sigma and variable lambda. In extended moment problem, given a sequence of real numbers, it is required to find a mass distribution whose generalized moment of order k is k&#039 / th term of the sequence. The conditions of existence and uniqueness of the solution obtained by Hamburger are studied in this thesis by the use of orthogonal polynomials determined by a measure on real line. A chapter on the study of asymptotic behaviour of orthogonal functions on compact subsets of complex numbers is also included.

Existence of basis in locally convex space has been an important problem in functional analysis for more than 40 years. In this thesis the conditions for the existence of basis are examined. These thesis consist of three parts. The first part is about the exterior interpolative conditions. The second part deals with the inner interpolative conditions on nuclear frechet space. These are sufficient conditions on existence of basis. In the last part, it is shown that for a regular nuclear K&ouml / the space the inner interpolative conditions are satisfied and moreover another type of inner interpolative conditions are introduced.

In the electronics the quality, reliability, operational speed, device density and cost of circuits are fundamentally determined by carriers. If it is necessary to use better material than plastic carrier, it has to be made of ceramics or glass-ceramics. This study dealt with the ceramic based carrier production system. The types of the raw ceramics fired at low temperature (below 1000&deg / C) are called Low Temperature Co-Fired Ceramics (LTCC). In this study, a comprehensive thermal model is described for the high temperature oven which belongs to a Low Temperature Co-fired Ceramic (LTCC) substance production line. The model includes detailed energy balances with conduction, convection and radiation heat transfer mechanisms, view factor derivations for the radiative terms, thermocouple balances, heating filaments and cooling mechanisms for the system. Research was conducted mainly on process development and production conditions along with the system modeling of oven. Temperature control was made in high temperature co-firing oven. Radiation View Factors for substrate and thermocouples are determined. View factors between substrate and top-bottom-sides of the oven are calculated, and then inserted into the energy balances. The same arrangement was made for 3 thermocouples at the bottom of the oven. Combination of both expressions gave the final model. Modeling studies were held with energy balance simulations on MATLAB. Data analysis and DOE study were held with JMP Software.

In this study, we consider the Air Cargo Scheduling Problem based on a real life application. The aim is to move cargo and passengers that have different priorities and delivery time window, from a number of origin airports to destination airports by means of a transportation system. The system has predefined carrier routes and a heterogeneous fleet of aircraft. The problem is formulated as a heterogeneous vehicle, multi commodity, pick-up, and delivery network flow problem with a large set of system specific constraints. The proposed model determines set of movement requirements assigned on each route leg and number and type of aircraft assigned for each route in a reasonable amount of time. The model is tested with the real and generated data and the results are compared with the current methodology under different scenarios. The model produced better results in a short amount of time compared to the current methodology.

We consider a hierarchical maximal covering location problem to locate p health centers and q hospitals in such a way that maximum demand is covered, where health centers and hospitals have successively inclusive hierarchy. Demands are 3 types: demand requiring low-level service only, demand requiring high-level service only, and demand requiring both levels of service at the same time. All types of requirements of a demand point should be either covered by hospital providing both levels of service or referred to hospital via health center since a demand point is not covered unless all levels of requirements are satisfied. Thus, a health center cannot be opened unless it is suitable to refer its covered demand to a hospital. Referral is defined as coverage of health centers by hospitals. We also added partial coverage to this complex hierarchic structure, that is, a demand point is fully covered up to the minimum critical distance, non-covered after the maximum critical distance and covered with a decreasing quality while increasing distance to the facility between minimum and maximum critical distances. We developed an MIP formulation to solve the Hierarchical Maximal Covering Location Problem with referral in the presence of partial coverage. We solved small-size problems optimally using GAMS. For large-size problems we developed a Genetic Algorithm that gives near-optimal results quickly. We tested our Genetic Algorithm on randomly generated problems of sizes up to 1000 nodes.

In recent years, artificial neural networks (ANNs) have been employed for estimation and prediction purposes in many areas of civil/structural engineering. In this thesis, multilayered feedforward backpropagation algorithm is used for the approximate analysis and calibration of RC T-beam bridges and modeling of bridge ratings of these bridges. Currently bridges are analyzed using a standard FEM program. However, when a large population of bridges is concerned, such as the one considered in this project (Pennsylvania T-beam bridge population), it is impractical to carry out FEM analysis of all bridges in the population due to the fact that development and analysis of every single bridge requires considerable time as well as effort. Rapid and acceptably approximate analysis of bridges seems to be possible using ANN approach. First part of the study describes the application of neural network (NN) systems in developing the relationships between bridge parameters and bridge responses. The NN models are trained using some training data that are obtainedfrom finite-element analyses and that contain bridge parameters as inputs and critical responses as outputs. In the second part, ANN systems are used for the calibration of the finite element model of a typical RC T-beam bridge -the Manoa Road Bridge from the Pennsylvania&rsquo / s T-beam bridge population - based on field test data. Manual calibration of these models are extremely time consuming and laborious. Therefore, a neural network- based method is developed for easy and practical calibration of these models. The ANN model is trained using some training data that are obtained from finite-element analyses and that contain modal and displacement parameters as inputs and structural parameters as outputs. After the training is completed, fieldmeasured data set is fed into the trained ANN model. Then, FE model is updated with the predicted structural parameters from the ANN model. In the final part, Neural Networks (NNs) are used to model the bridge ratings of RC T-beam bridges based on bridge parameters. Bridge load ratings are calculated more accurately by taking into account the actual geometry and detailing of the T-beam bridges. Then, ANN solution is developed to easily compute bridge load ratings.

This thesis analyzes the relationship between users&rsquo / characteristics and users&rsquo / interface preferences. An online survey is developed for this study. This survey composed of two types of questions: (1) users&rsquo / personal information such as age, gender, country, cognitive structure, and also computer experience and (2) user interface elements. More than 2,500 participants from 120 different countries throughout the world completed our survey. Results were analyzed using cross tables. Our findings show that there is a relationship between users&rsquo / characteristics and users&rsquo / interface preferences. In the presence of this relationship, an artificial neural network model is developed for the estimation of the interface preferences based on the user characteristics.

In this thesis, a feature extraction algorithm based on 2D Local Discriminant Bases (LDB) search is developed for acoustic and hyperspectral data. The developed algorithm extracts the relevant features by both eliminating the irrelevant ones and/or by merging the ones that do not provide extra information on their own. It is implemented on real world data to separate aflatoxin contaminated or high risk hazelnuts from the sound ones by using impact acoustic and hyperspectral data. Impact acoustics data is used to sort cracked and intact shell hazelnuts with high classification accuracy. Hypespectral images of the shelled and roasted (SRT) hazelnuts are used for classification and the algorithm extracted the spectral and spatial-frequency features for that classification. Aflatoxin concentration of the SRT category hazelnuts is automatically decreased to 0.7 ppb from 608 ppb by eliminating the detected contaminated ones.