During the past few years, various healthcare models and e-Health 2.0 technologies have been developed in order to effectively deliver the right information to the right process to provide effective and efficient healthcare services. On the other hand, healthcare delivery is evolving from disease-centered to patient-centered where patients are active participants in their healthcare delivery. Thus communications and collaboration among different healthcare actors is taking place on a much larger scale. There is also an increasing demand for personalized health systems facilitating the effective management of information, simplifying communication and collaboration, and supporting applications and services for meeting different users' specific requirements and ongoing needs. In order to properly address the aforementioned challenges, a framework is needed to advance information integration and interoperability of health applications and services in a controlled manner. In this thesis, we present a framework which allows patients and other healthcare actors to collaboratively develop personalized online health applications according to their specific and ongoing needs and requirements. For this purpose, we illustrate how Web 2.0 collaborative technologies, such as mashups, can represent an adequate foundation for implementing such framework. The value and capabilities of mashups in healthcare have already been studied and demonstrated, and this technology is able to provide an interoperable framework for communication and integration between healthcare processes and applications. We believe that integration and interoperability of health applications/services can be defined at the following levels: Process Level, System Level, and Data Level. The interoperability and integration of services at the system and data levels have already been intensively researched. However, not enough consideration has been given to interoperability issues at the process level. Healthcare must have interoperable systems and interoperable people who will use the systems. Therefore, a shift from a technology-driven implementation to a process-driven conceptual model is needed. Our aim in this thesis is to further research how Web 2.0 technologies and tools, such a mashups, can facilitate the exchange of processes between various healthcare entities and actors, and the role of mashup patterns for enhancing the interoperability and integration of healthcare services and applications.

Nowadays there are many technologies and design tools available to accurately obtain and model the geometric shape and the color of objects. However, these methods are not able to provide any information about the elasticity of the objects. This thesis presents a general-purpose scheme for measuring, constructing and representing geometric and elastic behavior of deformable objects without a priori knowledge on the shape and the material that the objects under study are made of. The proposed solution is based on an advantageous combination of neural network architectures and an original force-deformation measurement procedure. An innovative non-uniform selective data acquisition algorithm based on self-organizing neural architectures (namely neural gas and growing neural gas) is developed to selectively and iteratively identify regions of interest and guide the acquisition of data only on those points that are relevant for both the geometric model and the mapping of the elastic behavior, starting from a sparse point-cloud of an object. Multi-resolution object models are obtained using the initial sparse model or the (growing or) neural gas map if a more compressed model is desired, and augmenting it with the higher resolution measurements selectively collected over the regions of interest. A feedforward neural network is then employed to capture the complex relationship between an applied force, its magnitude, its angle of application and its point of interaction, the object pose and the deformation stage of the object on one side, and the object surface deformation for each region with similar geometric and elastic behavior on the other side. The proposed framework works directly from raw range data and obtains compact point-based models. It can deal with different types of materials, distinguishes between the different stages of deformation of an object and models homogeneous and non-homogeneous objects as well. It also offers the desired degree of control to the user.

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This dissertation addresses a class of fundamental logistical problems where two or more potential users (or players) compete for a common set of resources. Each user has a criterion (cost or performance requirement) that he/she wishes to optimize. The users' criteria are often in conflict, that is, choosing a decision that optimizes one user's criterion may not also optimize the criteria of others. How should the resources be utilized to satisfy the user demands? In this dissertation, optimization and game theoretical models are employed to examine the equilibrium points and efficiently find the frontier of non-dominated solutions to three logistics problems with competing users: (1) single machine scheduling, (2) network resource allocation and (3) assignment to multiple servers (queues). New cooperative game theoretic methods are developed to negotiate on the Pareto frontier. In addition, a Stackelberg leader-follower game framework is introduced in a queueing system which includes both competitive users and competitive servers. The existence of a unique equilibrium is shown. The models and methodologies developed in the dissertation can be applied in many areas, such as Internet pricing, scheduling resources among competitors, network routing of users' requirements, analysis of competitive market, etc.

First, this thesis presents four types of dynamic models for one-link flexible manipulators: Euler-Bernoulli model, Euler-Bernoulli model with rotatory inertia, Timoshenko model, and Euler-Bernoulli model with tip mass through Hamilton Principle, and exact modal frequencies and vibration modes are derived through Laplace transformation and eigenanalysis. The numerical analysis is conducted to verify the established models and investigate the influences of rotatory inertia, shear deformation and tip mass. Second, this thesis presents the exact dynamic solutions of Euler-Bernoulli model for the step torque input and design of a dynamics simulator for one-link flexible manipulators based on the exact dynamic solutions. Several types of sensor models have been specified in the designed simulator to provide various sensory data sets required for feedback controls. A simulation study is performed to verify the designed simulator and to demonstrate the usage of the dynamics simulator for controller design and evaluations.

The distributed processing capabilities of local area networks has led to the development of "client-server" applications for microcomputers. Two separate computer programs, the client and the server, comprise the client-server system. The server program receives and services requests sent to it by the client program. More than one copy of the client program may be connected at a time to the server via the network with each instance of the client program operating on a separate computer. Two difficulties are encountered when testing such a system. First, since each client station is operated by one or more human-users, extensive evaluation is costly when several clients are operated for a substantial amount of time. A second problem is an inherent inaccessibility to information about internal system states. This thesis presents a method for automating performance evaluations of the server component of the client-server software system. Two changes to the original system are required. First, the human-user inputs to the system are generated using probability distributions. Second, an additional computer program, the test monitor, is added to the system in order to automate the accumulation and storage of test data.

In this dissertation, the class of problems where a performance index must be optimized at the final time of operation of a batch process, is studied for various process conditions. First, optimal state feedback laws for end-point optimization of dynamic systems are derived where the state model is a nonlinear function of the manipulated input and the system states. The necessary conditions for optimality are cast in terms of the system Lie brackets and the adjoint states. An optimal state feedback law is derived which is independent of adjoint states. The nature of the optimal state feedback law (static or dynamic) is characterized in terms of the system dynamics. In the next phase of this work, this optimal feedback approach is extended to include the effect of measurable disturbances. It is found that depending on the degree of singularity with respect to manipulated input and/or disturbance input, the feedforward/feedback laws are either static or dynamic. In the final phase of this research, optimal state feedback laws are derived for on-line optimization of batch processes with two manipulated inputs where one input appears nonlinearly and the other appears linearly in the state model. As illustrative examples of application of the proposed state feedback laws, several end-point optimization problems in batch chemical reactors are considered. / Source: Dissertation Abstracts International, Volume: 57-03, Section: B, page: 1964. / Major Professor: Srinivas Palanki. / Thesis (Ph.D.)--The Florida State University, 1996.

For any nontrivial system or a group of such systems to operate harmoniously, there must exist protection policies, which outline what are allowed, as well as what should not be done. The complexity of the protection policies is proportional to the complexity of the systems involved and the connections between those systems. Due to continuous development of new technologies, especially the information technology, the complexity of most systems, as well as that of the connections between them, constantly increases. Consequently, there is a need for a framework in which such complex protection policies can be systematically analyzed. / A new concept of Connected Protection Structures (CPSs) is developed based on the original capability-pass-permit model of dynamic protection structure of Kohout and Gaines. The structures are defined in terms of fuzzy relations. CPSs provide a needed framework for the analysis of protection policies of a given group of connecting systems. A stand-alone system can also be dealt with by the CPSs as a special case. The main objective of the analysis is to uncover any possible harmful actions that are allowed but should not be performed, i.e. potential violations. CPSs take into account both internal protection policies which govern interactions within one system, and external protection policies which govern interactions across connecting systems. Computational techniques that lead to the determination of potential violations, and a software that implements the techniques are developed. Ways to construct CPSs from given protection policies, as well as a suggestion on how to incorporate the resulting CPSs into a protection mechanism for a generic application, are also presented. / Source: Dissertation Abstracts International, Volume: 52-10, Section: B, page: 5377. / Major Professor: Ladislav J. Kohout. / Thesis (Ph.D.)--The Florida State University, 1991.

The first chapter of this dissertation estimates the relative contributions of two major exchanges on crude oil futures to the price discovery process-- Chicago Mercantile Exchange (CME) and Intercontinental Exchange (ICE), using trade-by-trade data in 2008. The study also empirically analyzes the effects of trading characteristics on the information share of these two markets. Trading characteristics examined in the study include trading volume, trade size, and trading costs. On average, CME is characterized by greater volume and trade size but also slightly greater bid-ask spread. CME leads the process of price discovery and this leadership is caused by relative trade size and volatility before the financial crisis of 2008; however post-crisis period this leadership is caused by trading volume. Moreover, this study presents evidence that, in times of large uncertainty in the market, the market maker charges a greater bid-ask spread for the more informative market. / The second chapter examines the influence of expected oil price volatility, the behavior of the Organization of Petroleum Exporting Countries (OPEC), and the US Dollar exchange rate volatility on the backwardation of crude oil futures during the period from January 1986 to December 2008. The results indicate that oil futures are strongly and weakly backwardated 57% and 69% of the time, respectively. The regression analysis of weak backwardation shows that oil volatility, OPEC overproduction (difference between quota and the actual production), and the volatility of the US Dollar against the Japanese Yen have a positive significant effect on oil backwardation, while OPEC production quota imposed on its members has a negative significant effect on oil backwardation. However the volatility of US Dollar against the British Pound has no significant effect on oil backwardation. The regression analysis of strong backwardation produces qualitatively the same results except that volatility has no effect. In a sub-period analysis, evidence also indicates that trading volume of oil funds and backwardation are negatively related, suggesting that oil funds increase the demand of futures relative to that of spot. / Keywords: Oil futures, price discovery, trading characteristics, bid-ask spread, financial crisis, backwardation, OPEC, oil funds, and exchange rate.