Next generation networks will provide customers with a service mix placing variable demands for resources on the underlying infrastructure, motivating automated telecommunications services management approaches. This thesis proposes the Autonomic Service Architecture (ASA) for automated service delivery over next generation networks. First, we propose an architectural blueprint for ASA. We describe our view of the next generation network infrastructure, which will be application oriented. We elaborate on the layered design of ASA, the virtualization of resources, and the separation between manual and autonomic functions in the service delivery lifecycle. The autonomic functions are delivered by the interaction between Autonomic Resource Brokers (ARBs). The architecture of an ARB is then detailed, with a description of its different components and the message exchanges needed. Next, we discuss a Peer-to-Peer (P2P) naming and mobility management approach for next generation networks using ASA. This P2P approach will help ensure the scalability, robustness, and flexibility that ASA needs to ensure service delivery over next generation networks. The proposed P2P naming and mobility management infrastructure is then detailed, and its performance is evaluated. Finally, we suggest several autonomic resource management algorithms for ASA. The first algorithm is based on the Transportation Model, commonly used in the Operations Research community for cost minimization in delivering a commodity from sources to destinations, adapted to perform allocation of virtual resources. The second algorithm is based on the Assignment Model, commonly used in the Operations Research community for cost minimization in assigning several jobs to several workers, adapted to perform autonomic assignment of dedicated virtual resources. The third algorithm is based on Inventory Control, commonly used in the Operations Research community to analyze inventory systems, placing and receiving orders when needed for a given product, adapted to predict the demand on virtual resources. The fourth algorithm is based on Reinforcement Learning, commonly used in the Machine Learning community by agents to find a control policy that will maximize the observed rewards over their lifetime, adapted to adjust the prices of virtual resources.

currently DNA and RNA sequencing are performed as standard parts of many scientific experiments. While the majority of the reads produced in these experiments do map to the genome of the organism of interest there are a significant fraction that do not. These reads have often been viewed as uninteresting and thus discarded, sometimes explained as errors created in the sequencing process. However, there may be a real possibility that these reads actually contain genomic sequences belonging to, but not currently in the genome ofthe organism investigated, as well as information about other organisms which live and thrivein the sample material. Considering this, it is of great interest to investigate these reads to see if they contain any usable information. In this project the unmapped reads from SOLiD sequencing of blood and saliva from a twin pair were assembled. The assembled parts were thencompared to different blast databases to investigate if similar genomic regions are reported inother species. We can conclude that indeed a large fraction of the contigs found in this assemblyhave homology to bacterial genes while other contigs share similarity to genomic regions foundin apes and other species closely related to us. All in all the results show that there is more to the unmapped reads than just sequencing errors.

Next generation networks will provide customers with a service mix placing variable demands for resources on the underlying infrastructure, motivating automated telecommunications services management approaches. This thesis proposes the Autonomic Service Architecture (ASA) for automated service delivery over next generation networks. First, we propose an architectural blueprint for ASA. We describe our view of the next generation network infrastructure, which will be application oriented. We elaborate on the layered design of ASA, the virtualization of resources, and the separation between manual and autonomic functions in the service delivery lifecycle. The autonomic functions are delivered by the interaction between Autonomic Resource Brokers (ARBs). The architecture of an ARB is then detailed, with a description of its different components and the message exchanges needed. Next, we discuss a Peer-to-Peer (P2P) naming and mobility management approach for next generation networks using ASA. This P2P approach will help ensure the scalability, robustness, and flexibility that ASA needs to ensure service delivery over next generation networks. The proposed P2P naming and mobility management infrastructure is then detailed, and its performance is evaluated. Finally, we suggest several autonomic resource management algorithms for ASA. The first algorithm is based on the Transportation Model, commonly used in the Operations Research community for cost minimization in delivering a commodity from sources to destinations, adapted to perform allocation of virtual resources. The second algorithm is based on the Assignment Model, commonly used in the Operations Research community for cost minimization in assigning several jobs to several workers, adapted to perform autonomic assignment of dedicated virtual resources. The third algorithm is based on Inventory Control, commonly used in the Operations Research community to analyze inventory systems, placing and receiving orders when needed for a given product, adapted to predict the demand on virtual resources. The fourth algorithm is based on Reinforcement Learning, commonly used in the Machine Learning community by agents to find a control policy that will maximize the observed rewards over their lifetime, adapted to adjust the prices of virtual resources.

Surface properties of polymers and competition adsorption of toluene and heptane on silica were studied using IR-visible sum frequency generation (SFG) vibrational spectroscopy. SFG is intrinsically surface sensitive because the second-order optical process is forbidden in media with inversion symmetry, such as bulk polymers and liquids. This nonlinear optical technique provides surface vibrational spectra under ambient conditions without the need of an ultra-high vacuum environment. Polymer surface properties, including surface relaxation temperature of poly(methyl methacrylate) (PMMA) and surface electronic states of poly[2-methoxy, 5-ethyl (2’-hexyloxy) para phenylenevinylene] (MEH-PPV), were investigated. It was found that there are significant differences between the surface and bulk properties for these polymers. For PMMA, a new surface structure relaxation was identified at 67°C, which does not match any known structure relaxation temperatures for bulk PMMA and is 40°C below the bulk glass transition temperature. For MEH-PPV, SFG electronic spectra, which were obtained by scanning the frequencies of incident visible and JR beams, indicated that the electronic states at the polymer/solid and air/polymer interfaces are red-shifted with respect to that of the bulk. Finally, SFG was employed to study the competition adsorption of toluene and heptane on silica surfaces. Experimental data showed that heptane adsorbed favorably compared to toluene. Using a Langmuir adsorption isotherm, the changes of Gibbs free energy for the adsorption processes were calculated to be —12.1 ± 1.8 (kJ/mol) for toluene and —16.5 ± 2.3 (kJ/mol) for heptane.

Entropy based design is a novel design method that incorporates the second law of thermodynamics with computational and experimental techniques to achieve the upper limits of performance and quality in engineering technologies. As the emerging technologies are pressing towards the theoretical limits of efficiency, the concept of entropy and entropy based design will have an increasing role of performance. Measuring entropy generation is a valuable diagnostic tool from which the areas with high destruction rates of available energy may be determined and re-designed. In this work, a general model is developed, based on previous analytical expressions for pressure drop and heat transfer, for predicting entropy generation in a microchannel. The model includes the effects due to developing and fully developed flow, entrance and exit geometries, cross-sectional shapes, aspect ratio, and different thermal boundary conditions. An experimental technique is presented that enables the measurement of the spatial istribution of entropy generation in a microchannel. The experimental method is a combination of Micro Particle Image velocimetry to measure the spatial distribution of velocity and Micro Laser Induced Fluorescence to determine the temperature data. This method provides certain advantages over conventional anemometry techniques. This method, offers the whole-field non-intrusive, and instantaneous measurement of entropy generation in the device; while, previous techniques are limited to single point, averaged measurements.

Entropy based design is a novel design method that incorporates the second law of thermodynamics with computational and experimental techniques to achieve the upper limits of performance and quality in engineering technologies. As the emerging technologies are pressing towards the theoretical limits of efficiency, the concept of entropy and entropy based design will have an increasing role of performance. Measuring entropy generation is a valuable diagnostic tool from which the areas with high destruction rates of available energy may be determined and re-designed. In this work, a general model is developed, based on previous analytical expressions for pressure drop and heat transfer, for predicting entropy generation in a microchannel. The model includes the effects due to developing and fully developed flow, entrance and exit geometries, cross-sectional shapes, aspect ratio, and different thermal boundary conditions. An experimental technique is presented that enables the measurement of the spatial istribution of entropy generation in a microchannel. The experimental method is a combination of Micro Particle Image velocimetry to measure the spatial distribution of velocity and Micro Laser Induced Fluorescence to determine the temperature data. This method provides certain advantages over conventional anemometry techniques. This method, offers the whole-field non-intrusive, and instantaneous measurement of entropy generation in the device; while, previous techniques are limited to single point, averaged measurements.

Airline planning is a complex and difficult process. The biggest airlines in the world plan for and operate fleets of over 700 aircraft using tens of thousands of crew members. As such, small percentages in savings translate to millions of dollars. In this thesis, we study the pairing and duty generation problem in the context of airline crew scheduling, and propose approaches to improve the computational speed and the solution quality. We propose several enumeration algorithms to generate all possible duty periods of a given schedule to improve on the time required to generate duty periods; and present a set of column generation models to improve on the solution quality. When tested on a real test case study, the proposed approaches are found to improve the computational times from 142 seconds down to less than one second, and the cost savings of 13.7%.

Considered is a class of cooperative control problems that has a special affine characterization. Included in this class of multi-agent problems are the so called radar deception problem, formation keeping and formation reconfiguration. An intrinsic geometric formulation of the associated constraints unifies this class of problems and it is the first time such a generalization has been presented. Based on this geometric formulation, a real-time motion planning algorithm is proposed to generate dynamically feasible reference trajectories for the class. The proposed approach explicitly considers actuator and operating constraints of the individual agents and constrained dynamics are derived intrinsically for the multi-agent system which makes these constraints transparent. Deriving the constrained dynamics eliminates the need for nonlinear programming to account for the system constraints, making the approach amenable to real-time control. Explicit consideration of actuator and operating limitations and nonholonomic constraints in the design of the reference trajectories addresses the important issue of dynamic feasibility. The motion planning algorithm developed here is verified through simulations for the radar deception, rigid formation keeping and formation reconfiguration problems. A key objective of this study is to advocate a change in paradigm in the approach to formation control by addressing the key issues of dynamic feasibility and computational complexity. The other important contributions of this study are: Unifying formulation of constrained dynamics for a class of problems in formation control through the intrinsic geometry of their nonholonomic and holonomic constraints; Deriving these constrained dynamics in any choice of frame that can even be coordinate free; Explicit consideration of actuator and operating limits in formation control to design dynamically feasible reference trajectories and Developing a real-time, distributed, scalable motion planning algorithm applicable to a class of autonomous multi-agent systems in formation control.

A graphical preprocessor for Spectral Element Method (SEM) is developed with an emphasis on user friendly graphical interface and instructive element construction. The interface of the preprocessor helps users with every step during mesh generation, aiding their understanding of SEM. This preprocessor's Graphical User Interface (GUI) and help system are comparable to other commercial tools. Moreover, this preprocessor is designed for educational purposes, and prior knowledge of Spectral Element formulation is not required to use this tool. The information window in the preprocessor shows stepby- step instructions for the user. The preprocessor provides a graphical interface which enables visualization while the mesh is being constructed, so that the entire domain can be discretized easily. In addition, by following informative steps during the mesh construction, the user can gain knowledge about the intricate details of computational fluid dynamics. This preprocessor provides a convenient way to implement h/p type nonconforming interfaces between elements. This aids the user in learning advanced numerical discretization techniques, such as the h/p nonconforming SEM. Using the preprocessor facilitates enhanced understanding of SEM, isoparametric mapping, h and p type nonconforming interfaces, and spectral convergence. For advanced users, this preprocessor provides a proficient and convenient graphical interface independent of the solvers. Any spectral element solver can utilize this preprocessor, by reading the format of the output file from the preprocessor. Given these features, this preprocessor is useful both for novice and advanced users.

The future of electric power distribution systems (DSs) is one that incorporates extensive amounts of advanced metering, distribution automation, and distributed generation technologies. Most DSs were designed to be radial systems and the major philosophies of their protection, namely, selectivity and sensitivity, were easily achieved. Settings for overcurrent protective devices (OCPDs) were static and based on the maximum load downstream of its location, with little concern of major configuration changes. However, the integration of distribution generators (DGs) in radial distributions systems (RDSs) causes bidirectional power flows and varying short circuit currents to be sensed by protective devices, thereby affecting these established protection principles. Several researchers have investigated methods to preserve the selectivity of overcurrent protection coordination in RDSs with DGs, but at the expense of protective device sensitivity due to an inherent change in system configuration. This thesis presents an investigation to adapt the pickup settings of the substation relay, based on configuration changes in a DS with DGs, using smart meter data from the prior year. An existing protection scheme causes the faulted areas of DSs with DGs to revert to a radial configuration, thereby allowing conventional OCPDs to isolate faults. Based on the location of the fault, the created radial segments are known and vary in length. The proposed methodology involves using demand information available via smart metering, to determine the seasonal maximum diversified demands in each of the radial segments that are formed. These seasonal maximum diversified demands are used to yield several pickup settings for the substation overcurrent relay of the DS. The existing protection approach enables the selectivity of radial overcurrent protection coordination to be maintained; the sensitivity of the substation relay is improved by adapting its pickup settings based on seasonal demand and system configuration changes. The results of the studies are reported through simulation in EMTP™ /PSCAD® using a multi-feeder test system that includes DGs and smart meters located at the secondary distribution load level. The results show that using seasonal settings for the substation relay based on configuration changes in a DS with DGs can improve the sensitivity of the substation relay.