Self-excited systems are open loop unstable plants having a nonlinearity that prevents an exponentially increasing time response. The resulting limit cycle is induced by any slight disturbance that causes the response of the system to grow to the saturation level of the nonlinearity. Because there is no external disturbance, control of these self-excited systems requires that the open loop system dynamics are altered so that any unstable open loop poles are stabilized in the closed loop. This work examines a variety of adaptive control approaches for controlling a thermoacoustic instability, a physical self-excited system. Initially, a static feedback controller loopshaping design and associated system identification method is presented. This design approach is shown to effectively stabilize an unstable Rijke tube combustor while preventing the creation of additional controller induced instabilities. The loopshaping design method is then used in conjunction with a trained artificial neural network to demonstrate stabilizing control in the presence of changing plant dynamics over a wide variety of operating conditions. However, because the ANN is designed specifically for a single combustor/actuator arrangement, its limited portability is a distinct disadvantage. Filtered-X least mean squares (LMS) adaptive feedback control approaches are examined when applied to both stable and unstable plants. An identification method for approximating the relevant plant dynamics to be modeled is proposed and shown to effectively stabilize the self-excited system in simulations and experiments. The adaptive feedback controller is further analyzed for robust performance when applied to the stable, disturbance rejection control problem. It is shown that robust stability cannot be guaranteed because arbitrarily small errors in the plant model can generate gradient divergence and unstable feedback loops. Finally, a time-averaged-gradient (TAG) algorithm is investigated for use in controlling self-excited systems such as the thermoacoustic instability. The TAG algorithm is shown to be very effective in stabilizing the unstable dynamics using a variety of controller parameterizations, without the need for plant estimation information from the system to be controlled. / Ph. D.

Fracture systems or networks always control the stability, deformability, fluid and gas storage capacity and permeability, and other mechanical and hydraulic behavior of rock masses. The characterization of fracture systems is of great significance for understanding and analyzing the impact of fractures to rock mass behavior. Fracture trace data have long been used by engineers and geologists to character fracture system. For subsurface fractures, however, boreholes, wells, tunnels and other cylindrical samplings of fractures often provide high quality fracture trace data and have not been sufficiently utilized. The research work presented herein is intended to interpret fracture traces on borehole walls and other cylindrical surfaces by using stereology. The relationships between the three-dimension fracture intensity measure, P32, and the lower dimension fracture intensity measures are studied. The analytical results show that the conversion factor between the three-dimension fracture intensity measure and the two-dimension intensity measure on borehole surface is not dependent on fracture size, shape or circular cylinder radius, but is related to the orientation of the cylinder and the orientation distribution of fractures weight by area. The conversion factor between the two intensity measures is determined to be in the range of [1.0, π/2]. The conversion factors are also discussed when sampling in constant sized or unbounded fractures with orientation of Fisher distribution. At last, the author proposed estimators for mean fracture size (length and width) with borehole/shaft samplings in sedimentary rocks based on a probabilistic model. The estimators and the intensity conversion factors are tested and have got satisfactory results by Monte Carlo simulations. / Ph. D.

The Himalayan orogen provides an incredible natural laboratory to test models for continent-continent collision. The highest peaks of the Himalayas are composed of the Greater Himalayan Sequence (GHS), which is bound by a north-dipping low angle detachment fault above (South Tibetan detachment; STD) and by a thrust fault below (Main Central thrust; MCT). Assuming simultaneous movement on these features, the GHS can be modeled as a southward extruding wedge or channel. Channel flow models describe the coupling between mid-crustal flow, driven by gradients in lithostatic pressure between the Tibetan Plateau and the Indian plate, and focused denudation on the range front. Although the general geometry and shear sense criteria for these bounding shear zones has been documented, prior to this investigation, relatively few attempts had been made to quantify the spatial and temporal variation in flow path history for rocks from an exhumed section of the proposed mid-crustal channel. Results from this investigation demonstrate that mid-crustal flow at high deformation temperatures was distributed throughout the proposed channel. As these rocks began to exhume to shallower crustal conditions and therefore lower temperatures, deformation began to become partitioned away from the core of the channel and into the bounding shear zones. Based on these results a new method (Rigid Grain Net) to measure the relative contributions of pure and simple shear (vorticity) is proposed. Detailed thermobarometric analysis was conducted on rocks from the highest structural level in the Khumbu region, Nepal to construct pressure-temperature-time-deformation paths during the tectonic evolution of the GHS between ~32-16 Ma. Another aspect of the project suggests that the most active feature of the region is the N-S trending Ama Drime Massif (ADM). By combining new structural interpretation with existing remote sensing data this investigation proposes that the ADM is being exhumed during extension that is coupled with denudation in the trans-Himalayan Arun River gorge. Together these data provide important insights into the dynamic links between regional-scale climate and crustal-scale tectonics. / Ph. D.

Multi-disciplinary ship synthesis models and multi-objective optimization techniques are increasingly being used in ship design. Multi-disciplinary models allow designers to break away from the traditional design spiral approach and focus on searching the design space for the best overall design instead of the best discipline-specific design. Complex design problems such as these often have high levels of uncertainty associated with them, and since most optimization algorithms tend to push solutions to constraint boundaries, the calculated "best" solution might be infeasible if there are minor uncertainties related to the model or problem definition. Consequently, there is a need to address uncertainty in optimization problems to produce effective and reliable results. This thesis focuses on adding a third objective, uncertainty, to the effectiveness and cost objectives already present in a multi-disciplinary ship synthesis model. Uncertainty is quantified using a "confidence of success" (CoS) calculation based on the mean value method. CoS is the probability that a design will satisfy all constraints and meet performance objectives. This work proves that the CoS concept can be applied to synthesis models to estimate uncertainty early in the design process. Multiple sources of uncertainty are realistically quantified and represented in the model in order to investigate their relative importance to the overall uncertainty. This work also presents methods to encourage a uniform distribution of points across the Pareto front. With a well defined front, designs can be selected and refined using a gradient based optimization algorithm to optimize a single objective while holding the others fixed. / Master of Science

The mango tree is one the important sources of income in the rural economy of Senegal. However, mango producers in Ziguinchor are facing fruit fly infestations leading to important losses in income. The aim of this study is to measure the impact of the losses encountered by mango farmers in Ziguinchor over three years 2012, 2013, and 2014 and conduct an econometric study to examine household characteristics associated with high level of losses. At the household level, the total yearly losses on average from fruit fly infestations represent 17.09 % of the average total household income in Ziguinchor (Casamance). The losses associated with variability of production are much smaller than losses from decreases of average yield. Furthermore, the results show that the number of hectares, level production, and use of Keitt varieties are three factors statistically significant, with a significant positive influence on losses from infestation. The use of fruit fly control technologies does not appear to significantly reduce losses. / Master of Science

Historically, the primary objective of traditional stormwater best management practices (BMPs) was to attenuate peak runoff discharges from urban areas. There has been growing demand to construct BMPs that improve stormwater runoff quality to reduce pollutant loading into downstream water bodies. A BMP located in Herndon, Virginia was retrofitted in 2009. Previously a dry detention pond, the new BMP design contains permanent wet pools as well as elements of Low Impact Development practices. A performance analysis was conducted on the retrofit to determine if the BMP was removing pollutants from stormwater runoff. Two mass-based methods were utilized for the performance analysis: the Summation of Loads Method and Effluent Probability Method. The Kaplan-Meier method and Robust Regression on ordered statistics (ROS) were used to make it possible to include censored datasets in the analysis. Analysis with the SOL method showed removal of suspended sediment, nitrogen, iron, and copper. Export of dissolved solids, phosphorus, organic carbon, and manganese was observed. The results of the Effluent Probability Method showed statistically significant reductions of sediment, iron, and copper across the entire range of monitored storm event sizes (p-value≤0.05). There was no statistical difference between the influent and effluent loads of nitrogen. Negative performance of dissolved solids, phosphorus, organic carbon, and manganese were observed for the entire range of monitored storm event sizes. The results of both methods indicated that the BMP retrofit is effectively removing sediment but failing to achieve significant nutrient reductions. This may be due to the creation of anoxic conditions from the oxygen demand of the micropool sediments and microbial degradation of vegetation within the BMP. Removal of the sediment bed and harvesting of the vegetation would likely improve the performance of the BMP. / Master of Science

Geolocation accuracy is a very crucial and a life-or-death factor for rescue teams. Natural disasters or man-made disasters are just a few convincing reasons why fast and accurate position location is necessary. One way to unleash the potential of positioning systems is through the use of collaborative positioning. It consists of simultaneously solving for the position of two nodes that need to locate themselves. Although the literature has addressed the benefits of collaborative positioning in terms of accuracy, a theoretical foundation on the performance of collaborative positioning has been disproportionally lacking. This dissertation uses information theory to perform a theoretical analysis of the value of collaborative positioning.The main research problem addressed states: 'Is collaboration always beneficial? If not, can we determine theoretically when it is and when it is not?' We show that the immediate advantage of collaborative estimation is in the acquisition of another set of information between the collaborating nodes. This acquisition of new information reduces the uncertainty on the localization of both nodes. Under certain conditions, this reduction in uncertainty occurs for both nodes by the same amount. Hence collaboration is beneficial in terms of uncertainty. However, reduced uncertainty does not necessarily imply improved accuracy. So, we define a novel theoretical model to analyze the improvement in accuracy due to collaboration. Using this model, we introduce a variational analysis of collaborative positioning to deter- mine factors that affect the improvement in accuracy due to collaboration. We derive range conditions when collaborative positioning starts to degrade the performance of standalone positioning. We derive and test criteria to determine on-the-fly (ahead of time) whether it is worth collaborating or not in order to improve accuracy. The potential applications of this research include, but are not limited to: intelligent positioning systems, collaborating manned and unmanned vehicles, and improvement of GPS applications. / Ph. D.

Yes / A key prediction of the Capital Asset Pricing Model (CAPM) is that idiosyncratic risk is not priced by investors because in the absence of frictions it can be fully diversified away. In the presence of constraints on diversification, refinements of the CAPM conclude that the part of idiosyncratic risk that is not diversified should be priced. Recent empirical studies yielded mixed evidence with some studies finding positive correlation between idiosyncratic risk and stock returns, while other studies reported none or even negative correlation. We revisit the problem whether idiosyncratic risk is priced by the stock market and what are the probable causes for the mixed evidence produced by other studies, using monthly data for the US market covering the period from 1980 until 2013. We find that one-period volatility forecasts are not significantly correlated with stock returns. The mean-reverting unconditional volatility, however, is a robust predictor of returns. Consistent with economic theory, the size of the premium depends on the degree of 'knowledge' of the security among market participants. In particular, the premium for Nasdaq-traded stocks is higher than that for NYSE and Amex stocks. We also find stronger correlation between idiosyncratic risk and returns during recessions, which may suggest interaction of risk premium with decreased risk tolerance or other investment considerations like flight to safety or liquidity requirements. The difference between the correlations of the idiosyncratic volatility estimators used by other studies and the true risk metric the mean-reverting volatility is the likely cause for the mixed evidence produced by other studies. Our results are robust with respect to liquidity, momentum, return reversals, unadjusted price, liquidity, credit quality, omitted factors, and hold at daily frequency. / National Research Foundation of Korea (2016S1A2A2912265)

Yes / Although a cornerstone of traditional finance theory, empirical evidence in support of a positive mean-variance relation is far from conclusive, with the behavior of retail investors commonly thought to be one of the root causes of departures from this expected relationship. The behavior of institutional investors, conventionally thought to be sophisticated and rational, has recently come under closer scrutiny, including in relation to investor sentiment. Drawing together these two strands of literature, this paper examines the impact of institutional investor sentiment on the mean-variance relation in six regions, including Asia (excl. Japan), Eastern Europe, Eurozone, Japan, Latin America, and the US, and across thirtyeight markets. Empirical evidence supports the differential impact of institutional investor sentiment on the mean-variance relation (i.e., positive or negative), both across regions and across markets. In particular, for markets with cultural proneness to overreaction and a low level of market integrity institutional investor sentiment tends to distort the risk-return tradeoff.

Yes / Context: Adult age-at-death is presented in a number of different ways by anthropologists. Ordinal categories predominate in osteoarchaeology, but do not reflect individual variation in ageing, with too many adults being classified as ‘middle adults’. In addition, mean ages (derived from reference samples) are overly-relied upon when developing and testing methods. In both cases, ‘age mimicry’ is not adequately accounted for. Objectives: To highlight the many inherent biases created when developing, testing and applying age-estimation methods without fully considering the impact of ‘age mimicry’ and individual variation. Methods: The paper draws on previously published research (Web of Science, Pub Med, Google Scholar) on age estimation methods and their use in anthropology. Results and Conclusions: There is a lack of consistency in the methods used to estimate age, and for the mode of combining them. Ordinal categories are frequently used in osteoarchaeology, whereas forensic anthropologists are more likely to produce case-specific age ranges. Mean ages reflect the age structure of reference samples, and should not be used to estimate age for individuals from populations with a different age-at-death structure. Individual-specific age ranges and/or probability densities should be used to report individual age. Further research should be undertaken on how to create unbiased, combined method age estimates.