This thesis considers a variant of the classical problem for finding the longest common subsequence (LCS) called longest common subsequence problem with a gapped constraint (LCSGC). Given two sequences A, B, and a constrained sequence C, which is accomplished with a corresponding gapped constraint for each symbol, whose lengths are m, n, and r, respectively, the LCSGC problem is to find an LCS of A and B, such that C is also a subsequence of this LCS and the gapped constraints corresponding to C are satisfied. In this thesis, two algorithms with time complexities O(m2n2r) and O(mnr ¡Ñ min(m, n)) are proposed based on the dynamic programming technique for solving the LCSGC problem.

A self-healing material has the inherent ability to partially reverse damage such as crack formation that might have occurred during its service. Significant evidence exists in the literature to indicate that asphalt binder is a self-healing material. It is also well known that healing has a substantial affect on the performance of asphalt mixtures and consequently on the serviceable life of asphalt pavements. For example, shift factors from laboratory experimental data to field observed data show that laboratory data underpredict field observations. There is a need to understand the mechanisms that are responsible for healing in asphalt binders as well as to develop test methods that can be used to determine properties related to these mechanisms. This thesis presents details and findings from a two-part study that addresses each one of these two aspects. In the first part of this study, a test method based on the use of a Dynamic Shear Rheometer (DSR) was developed to determine the parameters of characteristic healing function of asphalt binders. In the second part of this study, Molecular Modeling (MM) techniques were used to determine the interrelationship between molecular structure, surface free energy, self diffusivity, and other healing properties of asphalt binders.The healing characteristic equation parameter (Ro) which represents the instantaneous healing nature of the asphalt binders is analogous to surface energy in terms of effect on healing in asphalt binders. Ro values for three asphalt binders AAM, AAD and ABD are calculated and compared with the surface energy values available from the literature. It was observed that the Ro values are proportional to surface energy values. Surface energy values for five asphalt binders AAM, AAD, AAB, AAG and AAF are calculated using MM method based on SHRP representative molecules. These values were observed to be proportional to the surface energy values from literature. Bulk and surface diffusion coefficients of asphalt molecules are calculated using MM method. Parametric analysis was done to determine the effect of chemical structure of asphalt on its diffusion properties. It was observed that the higher percentage of saturates in the chemical structure results into higher diffusion coefficients.

Non-invasive dynamic optical imaging of small animals requires the development of a novel fluorescence imaging modality. Herein, fluorescence imaging is demonstrated with sub-second camera integration times using agents specifically targeted to disease markers, enabling rapid detection of cancerous regions. The continuous-wave fluorescence imaging acquires data with an intensified or an electronmultiplying charge-coupled device. The work presented in this dissertation (i) assessed dose-dependent uptake using dynamic fluorescence imaging and pharmacokinetic (PK) models, (ii) evaluated disease marker availability in two different xenograft tumors, (iii) compared the impact of autofluorescence in fluorescence imaging of near-infrared (NIR) vs. red light excitable fluorescent contrast agents, (iv) demonstrated dual-wavelength fluorescence imaging of angiogenic vessels and lymphatics associated with a xenograft tumor model, and (v) examined dynamic multi-wavelength, whole-body fluorescence imaging with two different fluorescent contrast agents. PK analysis showed that the uptake of Cy5.5-c(KRGDf) in xenograft tumor regions linearly increased with doses of Cy5.5-c(KRGDf) up to 1.5 nmol/mouse. Above 1.5 nmol/mouse, the uptake did not increase with doses, suggesting receptor saturation. Target to background ratio (TBR) and PK analysis for two different tumor cell lines showed that while Kaposi’s sarcoma (KS1767) exhibited early and rapid uptake of Cy5.5-c(KRGDf), human melanoma tumors (M21) had non-significant TBR differences and early uptake rates similar to the contralateral normal tissue regions. The differences may be due to different compartment location of the target. A comparison of fluorescence imaging with NIR vs. red light excitable fluorescent dyes demonstrates that NIR dyes are associated with less background signal, enabling rapid tumor detection. In contrast, animals injected with red light excitable fluorescent dyes showed high autofluorescence. Dual-wavelength fluorescence images were acquired using a targeted 111In- DTPA-K(IRDye800)-c(KRGDf) to selectively detect tumor angiogenesis and an untargeted Cy5.5 to image lymphatics. After acquiring the experimental data, fluorescence image-guided surgery was performed. Dynamic, multi-wavelength fluorescence imaging was accomplished using a liquid crystal tunable filter (LCTF). Excitation light was used for reflectance images with a LCTF transmitting a shorter wavelength than the peak in the excitation light spectrum. Therefore, images can be dynamically acquired alternating frame by frame between emission and excitation light, which should enable image-guided surgery.

Analog-to-digital (A/D) conversion is a process that bridges the real analog world to digital signal processing. It takes a continuous-time, continuous amplitude signal as its input and outputs a discrete-time, discrete-amplitude signal. The resolution and sampling rate of an A/D converter vary depending on the application. Recently, there has been a growing demand for broadband (>1 MHz), high-resolution (>14bits) A/D converters. Applications that demand such converters include asymmetric digital subscriber line (ADSL) modems, cellular systems, high accuracy instrumentation, and medical imaging systems. This thesis suggests some design techniques for such high resolution and high sampling rate A/D converters. As the A/D converter performance keeps on increasing it becomes increasingly difficult for the input driver to settle to required accuracy within the sampling time. This is because of the use of larger sampling capacitor (increased resolution) and a decrease in sampling time (higher speed). So there is an increasing trend to have a driver integrated onchip along with A/D converter. The first contribution of this thesis is to present a new precharge scheme which enables integrating the input buffer with A/D converter in standard CMOS process. The buffer also uses a novel multi-path common mode feedback scheme to stabilize the common mode loop at high speeds. Another major problem in achieving very high Signal to Noise and Distortion Ratio (SNDR) is the capacitor mismatch in Digital to Analog Converters (DAC) inherent in the A/D converters. The mismatch between the capacitor causes harmonic distortion, which may not be acceptable. The analysis of Dynamic Element Matching (DEM) technique as applicable to broadband data-converters is presented and a novel second order notch-DEM is introduced. In this thesis we present a method to calibrate the DAC. We also show that a combination of digital error correction and dynamic element matching is optimal in terms of test time or calibration time. Even if we are using dynamic element matching techniques, it is still critical to get the best matching of unit elements possible in a given technology. The matching obtained may be limited either by random variations in the unit capacitor or by gradient effects. In this thesis we present layout techniques for capacitor arrays, and the matching results obtained in measurement from a test-chip are presented. Thus we present various design techniques for high speed and low noise A/D converters in this thesis. The techniques described are quite general and can be applied to most of the types of A/D converters.

Gas production has increased exponentially over the last 30 years, which is in response to the increasing demand for natural gas. This trend is speculated to continue to increase as legislation continues to be passed requiring power plants to reduce nitrogen oxide emissions. This recently happened in Colorado according to the Washington Post, giving more consideration to using natural gas. As natural gas becomes more popular there is a need to understand the production patterns and observable trends, integrating data from various sources. This research will attempt to do just that for wells producing from the Travis Peak formation. Using data from HPDI L.L.C., (www.hpdi.com) a visual representation was created for the areal distribution of peak gas rates and cumulative gas production. This allowed us to categorize wells by their production performance and we found that areas with relatively high peak gas rates also had high cumulative gas production. An analysis of these wells was done by completion year, and we found that wellhead prices of natural gas strongly influenced the annual number of new wells. We also found that the distribution of the annual number of new wells affected the average annual initial production rate and the peak gas rate of new wells. Wells located in areas of poor production performance were analyzed and it was apparent that newer wells performed relatively better than older ones and well stimulation is a major requirement for better gas production. Wells located in areas of good production performance were also analyzed and we found that the distribution of newer wells to older ones influenced the relative performance of individual wells. Overall, there was no observable trend between production variables in Travis Peak. No trend in production variable was found to be exclusively associated with good performing wells or poor performing wells.

The fatigue life of a Steel Catenary Riser (SCR) near its touch-down zone is substantially affected by its interaction with the seabed. Hence, accurate estimate of its fatigue life requires the understanding and realistic modeling of the interaction between them. The interaction between SCR and the seabed depends on many factors, such as soil properties, riser characteristics, and the development of trenching at the seafloor. Existing approaches for modeling the seabed in interaction with a SCR approximate the seabed soil by a linear or nonlinear spring and a dashpot which respectively represent the stiffness and damping of the soil. However, they do not take into account certain phenomena resulting from plastic deformation or degradation of the seabed soil, such as trenching. In this study, a more realistic approach is developed for simulating the interaction between a SCR and the seabed soil. In addition to the use of a realistic P-y curve (where P stands for the supporting or resistance force of the seafloor and y for the vertical penetration of the riser into the soil) to simulate the soil deformation during its interaction with a riser, it considers the development of a trench caused by continuous poundings of a riser on the seabed and then its feedback effect on the variation of the bending moment along the riser. In this study, it has been found that trenching underneath a SCR may decrease the maximum variation of bending moment near its touch-down zone. Since the variation of the moment dictates the fatigue damage to the SCR, the results based on this approach indicate that the trenching development at the seabed may increase the fatigue life of a SCR and therefore, it may have important application to the design of a SCR.

In oil/gas and chemical industries, dynamics is one of the most essential characteristics of any process. Time-dependent response is involved in most steps of both the physical/engineering processes and the equipment performance. The conventional Quantitative Risk Assessment (QRA) is unable to address the time dependent effect in such dynamic processes. In this dissertation, a methodology of Dynamic Operational Risk Assessment (DORA) is developed for operational risk analysis in oil/gas and chemical industries. Given the assumption that the component performance state determines the value of parameters in process dynamics equations, the DORA probabilistic modeling integrates stochastic modeling and process dynamics modeling to evaluate operational risk. The stochastic system-state trajectory is modeled based on the abnormal behavior or failure of the components. For each of the possible system-state trajectories, a process dynamics evaluation is carried out to check whether process variables, e.g., level, flow rate, temperature, pressure, or chemical concentration, remain in their desirable regions. Monte Carlo simulations are performed to calculate the probability of process variable exceeding the safety boundaries. Component testing/inspection intervals and repair time are critical parameters to define the system-state configuration; and play an important role for evaluating the probability of operational failure. Sensitivity analysis is suggested to assist selecting the DORA probabilistic modeling inputs. In this study, probabilistic approach to characterize uncertainty associated with QRA is proposed to analyze data and experiment results in order to enhance the understanding of uncertainty and improve the accuracy of the risk estimation. Different scenarios on an oil/gas separation system were used to demonstrate the application of DORA method, and approaches are proposed for sensitivity and uncertainty analysis. Case study on a knockout drum in the distillation unit of a refinery process shows that the epistemic uncertainty associated with the risk estimation is reduced through Bayesian updating of the generic reliability information using plant specific real time testing or reliability data. Case study on an oil/gas separator component inspection interval optimization illustrates the cost benefit analysis in DORA framework and how DORA probabilistic modeling can be used as a tool for decision making. DORA not only provides a framework to evaluate the dynamic operational risk in oil/gas and chemical industries, but also guides the process design and optimization of the critical parameters such as component inspection intervals.

Unmanned Aerial Vehicles (UAVs) are being used more frequently in surveillance scenarios for both civilian and military applications. One such application addresses a UAV patrolling a perimeter, where certain stations can receive alerts at random intervals. Once the UAV arrives at an alert site it can take two actions: 1. Loiter and gain information about the site. 2. Move on around the perimeter. The information that is gained is transmitted to an operator to allow him to classify the alert. The information is a function of the amount of time the UAV is at the alert site, also called the dwell time, and the maximum delay. The goal of the optimization is to classify the alert so as to maximize the expected discounted information gained by the UAV's actions at a station about an alert. This optimization problem can be readily solved using Dynamic Programming. Even though this approach generates feasible solutions, there are reasons to experiment with different approaches. A complication for Dynamic Programming arises when the perimeter patrol problem is expanded. This is that the number of states increases rapidly when one adds additional stations, nodes, or UAVs to the perimeter. This in effect greatly increases the computation time making the determination of the solution intractable. The following attempts to alleviate this problem by implementing a Reinforcement Learning technique to obtain the optimal solution, more specifically Q-Learning. Reinforcement Learning is a simulation-based version of Dynamic Programming and requires lesser information to compute sub-optimal solutions. The effectiveness of the policies generated using Reinforcement Learning for the perimeter patrol problem have been corroborated numerically in this thesis.

Views of strategy formulation can be mainly divided into two categories. One is I-O(Industrial Organization), the other one is RBV(Resource Based View)(Hitt, Ireland and Hoskisson, 1999¡G2003¡FSe-Hwa Wu, 2000¡FJoseph Shyu, 2000¡FCher-Min Fong, 2001¡FMing-Jer Tang, 2003).Both of vews have each suitable situation. If strategy is formulated from single view, it will cause defects (Robbins, 2003). Recent years, scholars provide solutions from integration¡Bcontingency and dynamic. However, thesis combines 3 features is still few. This paper attempts to find combined views to suit different situation in a dynamic framework. The research provides a static framework included¡G(1) If the contingency of inside and outside company are stable, companies ought to choose ¡uposition-based view¡v; (2)If the contingency of outside company are not stable but stable contingency of inside company, companies ought to choose ¡uvision-based view¡v; (3)If the contingency of outside company are not stable but stable contingency of inside company, companies ought to choose ¡uenvironment-based view¡v; (4)If the contingency of inside and outside company are both not stable, companies ought to choose ¡uresource-based view¡v; (5)If the contingency of inside and outside company are changing smoothly with controllable situation, companies ought to choose ¡uconstruction-based view¡v. The research provides a dynamic framework. From the long term view, a company needs to adjust itself to match the changing of situation in order to have sustainable competitive advantage.

Due to the progress of display manufacturing technology, TFT-LCD (Thin Film Transistor-Liquid Crystal Display) has been widely put in use gradually such as monitor¡Blaptop and LCD TV. We also can find TFT-LCD that has already entered the market of the consuming products from IT (Information Technology). And the competition of the panel industry, besides manufacturing technologies, the dynamic demands of upstream, downstream and consumers are related that will effect the performance of panel markers or whole supply chain. Which is called bullwhip effect. Especially, the configuration is vertical partition in Taiwan and the buffwhip effect would be more significant than other countries. This paper discusses the key factors of bullwhip effect and them constructs the system dynamic models to explore the difference. Finally, we will analyze the TFT-LCD members of Taiwan to figure out the decision rules to decrease bullwhip effect.