Single-beam echosounders are an inexpensive, practical and non-invasive means of remote sensing the seabed. Ideally, the common single-beam echosounder should be able to tell fishers, navigators, engineers and scientists what the seabed consists of in addition to water depth. Low-frequency underwater acoustic systems (<10 kHz) can do this in some circumstances, but are expensive, offer limited resolution and potentially hazardous to marine mammals. High-frequency systems, such as single and multibeam echosounders, are very effective at mapping bathymetry, but do not characterize the seabed directly. Instead, these systems divide the seabed into self-similar segments or classes, and then rely on ground-truth data (usually sediment grab samples) to assign seabed-type labels such as sand, etc., to the classes. However, inadequate and inaccurate ground-truth is a major problem. Single-beam seabed classification methods also suffer from a lack of discriminatory power and from artefacts such as water depth and seabed slope. The cause of these problems is that the methods lack a basis in physics and are mainly statistical. Then, the central objective in this dissertation is to develop physics-based methods to improve classification and to address the problem of ground-truth by inferring seabed characteristics directly from the acoustics. An overview of current methods is presented along with case studies of single-beam surveys to introduce the current seabed classification method called QTC VIEW™ and to identify specific problems. A physical basis is established in scattering and geometrical theories and observations of field and model data. This leads to new classification and characterization methods that overcome the shortcomings of current seabed classification methods. Advancements also include new physical models of echosounding. The new methods are presented, implemented and evaluated. Highlights of experimental results include a new testbed located in Patricia Bay, British Columbia. The testbed consists of exhaustive ground-truth, surveys and novel controlled experiments with various single-beam echosounders, ranging in frequency from 12 to 200 kHz. Simulated echo time series data from the numerical BORIS model and a new analytic model are used to augment the testbed. Evaluation of experimental results shows the new physics-based methodology improves seabed classification significantly and enables seabed characterization by an uncalibrated single-beam echosounder. / Graduate

Sites in a 66-station geodetic network in central Greece have been occupied up to six times since 1989 using GPS surveying, and accurate positions have been computed using fiducially-improved or precise orbits. Site velocities are calculated under the assumption that they are constant with time, after correcting for co-seismic effects, and that the position of the fixed base station (and hence the entire network) may be subject to small errors. Low-order polynomial expressions do not fit the velocity field well. The pattern of observed strain closely resembles that derived from independent geodetic observations made over a hundred-year time-scale. Significant geodetic strain is observed across the Gulf of Korinthos, even after the co-seismic displacement field of the Ms=6.2 1995 Egion earthquake has been removed by forward modelling. Geodetic strain is higher in the western than eastern Gulf, in contrast to the seismic strain which is similar throughout. Seismic strain matches geodetic strain in the east, but a significant deficit of seismic moment exists in the west which may represent a high earthquake hazard in the medium term. The Ms=6.6 1995 Grevena earthquake struck a previously seismically quiet region well covered by a recent triangulation / trilateration survey. Ninety-one points from this network were reoccupied with GPS immediately after the earthquake, and site displacements computed. To invert for the earthquake source parameters from the geodetic displacement field, a novel inversion scheme is used which combines the Monte-Carlo and simplex approaches. A priori parameters are not required, even though the inverse problem is strongly nonlinear. The resulting focal mechanism agrees well with the global CMT solution and locally observed aftershocks, but implies a significantly higher scalar moment than do seismological studies. A network for observing post-seismic deformation has been established, which in view of the low background seismicity seems likely to provide significant results.

Atmospheric inversion has recently become an important tool in estimating CO2 sinks and sources albeit that the existing inversion results are often uncertain and differ considerably in terms of the spatiotemporal variations of the inverted carbon flux. More measurements combined with terrestrial ecosystem information are expected to improve the estimates of global surface carbon fluxes which are used to understand the relationships between variabilities of the terrestrial carbon cycle and anomalies of climatic factors. Inversions using more observations have often been hampered by the intense diurnal variations of CO2 concentrations at continental sites. Diurnal variations of the surface flux are included with atmospheric boundary dynamics in order to improve the atmospheric inversion accuracy. Modeling experiments conducted in this study show that inverse estimates of the carbon flux are more sensitive to the variation of the atmospheric boundary layer dynamics than to the diurnal variation in the surface flux. It is however generally better to consider both diurnal variations in the inversion than to consider only either of them. Forest carbon dynamics is closely related to stand age. This useful terrestrial ecosystem information has been used as an additional constraint to the atmospheric inversion. The inverse estimates with this constraint over North America exhibit an improved correlation with carbon sink estimates derived from eddy-covariance measurements and remotely-sensed data, indicating that the use of age information can improve the accuracy of atmospheric inversions. Terrestrial carbon uptake is found mainly in northern land, and a strong flux density is revealed in southeastern North America in an improved multi-year inversion from 2002 to 2007. The global interannual variability of the flux is dominated by terrestrial ecosystems. The interannual variabilities of regional terrestrial carbon cycles could be mostly explained by monthly anomalies of climatic conditions or short-time extreme meteorological events. Monthly anomalies of the inverted fluxes have been further analyzed against the monthly anomalies of temperature and precipitation to quantitatively assess the responses of the global terrestrial carbon cycle to climatic variabilities and to determine the dominant mechanisms controlling the variations of terrestrial carbon exchange.

In this thesis, we demonstrate a new type of resonant, nonlinear, light-matter interaction facilitated by the unique electromagnetic vacuum density-of-state (DOS) structure of Photonic Band Gap (PBG) materials. Strong light localization inside PBG waveguides allows extremely strong coupling between laser fields and embedded two-level quantum dots (QD). The resulting Mollow splitting is large enough to traverse the precipitous DOS jump created by a waveguide mode cutoff. This allows the QD Bloch vector to sense the non-smoothness of the vacuum structure and evolve in novel ways that are forbidden in free space. These unusual strong-coupling effects are described using a "vacuum structure term" of the Bloch equation, combined with field-dependent relaxation rates experienced by the QD Bloch vector. This leads to alternation between coherent evolution and enhanced relaxation. As a result, dynamic high-contrast switching of QD populations can be realized with a single beam of picosecond pulses. During enhanced relaxation to a slightly inverted steady state at the pulse peak, the Bloch vector rapidly switches from anti-parallel to parallel alignment with the pulse torque vector. This then leads to a highly inverted state through subsequent coherent "adiabatic following" near the pulse tail, providing a robust mechanism for picosecond, femto-Joule all-optical switching. The simultaneous input of a second, weaker (signal) driving beam at a different frequency on top of the stronger (holding) beam enables rich modulation effects and unprecedented coherent control over the QD population. This occurs through resonant coupling of the signal pulse with the Mollow sideband transitions created by the holding pulse, leading to either augmentation or negation of the final QD population achieved by the holding pulse alone. This effect is applied to ultrafast all-optical logic AND, OR and NOT gates in the presence of significant (0.1 THz) nonradiative dephasing and (about 1%) inhomogeneous broadening. Further numerical studies of pulse evolutions inside the proposed devices demonstrate satisfactory population contrast within a PBG waveguide length of about 10 micro meter. These results provide the building blocks for low-power, ultrafast, multi-wavelength channel, on-chip, all-optical computing.

Atmospheric inversion has recently become an important tool in estimating CO2 sinks and sources albeit that the existing inversion results are often uncertain and differ considerably in terms of the spatiotemporal variations of the inverted carbon flux. More measurements combined with terrestrial ecosystem information are expected to improve the estimates of global surface carbon fluxes which are used to understand the relationships between variabilities of the terrestrial carbon cycle and anomalies of climatic factors. Inversions using more observations have often been hampered by the intense diurnal variations of CO2 concentrations at continental sites. Diurnal variations of the surface flux are included with atmospheric boundary dynamics in order to improve the atmospheric inversion accuracy. Modeling experiments conducted in this study show that inverse estimates of the carbon flux are more sensitive to the variation of the atmospheric boundary layer dynamics than to the diurnal variation in the surface flux. It is however generally better to consider both diurnal variations in the inversion than to consider only either of them. Forest carbon dynamics is closely related to stand age. This useful terrestrial ecosystem information has been used as an additional constraint to the atmospheric inversion. The inverse estimates with this constraint over North America exhibit an improved correlation with carbon sink estimates derived from eddy-covariance measurements and remotely-sensed data, indicating that the use of age information can improve the accuracy of atmospheric inversions. Terrestrial carbon uptake is found mainly in northern land, and a strong flux density is revealed in southeastern North America in an improved multi-year inversion from 2002 to 2007. The global interannual variability of the flux is dominated by terrestrial ecosystems. The interannual variabilities of regional terrestrial carbon cycles could be mostly explained by monthly anomalies of climatic conditions or short-time extreme meteorological events. Monthly anomalies of the inverted fluxes have been further analyzed against the monthly anomalies of temperature and precipitation to quantitatively assess the responses of the global terrestrial carbon cycle to climatic variabilities and to determine the dominant mechanisms controlling the variations of terrestrial carbon exchange.

In this thesis, we demonstrate a new type of resonant, nonlinear, light-matter interaction facilitated by the unique electromagnetic vacuum density-of-state (DOS) structure of Photonic Band Gap (PBG) materials. Strong light localization inside PBG waveguides allows extremely strong coupling between laser fields and embedded two-level quantum dots (QD). The resulting Mollow splitting is large enough to traverse the precipitous DOS jump created by a waveguide mode cutoff. This allows the QD Bloch vector to sense the non-smoothness of the vacuum structure and evolve in novel ways that are forbidden in free space. These unusual strong-coupling effects are described using a "vacuum structure term" of the Bloch equation, combined with field-dependent relaxation rates experienced by the QD Bloch vector. This leads to alternation between coherent evolution and enhanced relaxation. As a result, dynamic high-contrast switching of QD populations can be realized with a single beam of picosecond pulses. During enhanced relaxation to a slightly inverted steady state at the pulse peak, the Bloch vector rapidly switches from anti-parallel to parallel alignment with the pulse torque vector. This then leads to a highly inverted state through subsequent coherent "adiabatic following" near the pulse tail, providing a robust mechanism for picosecond, femto-Joule all-optical switching. The simultaneous input of a second, weaker (signal) driving beam at a different frequency on top of the stronger (holding) beam enables rich modulation effects and unprecedented coherent control over the QD population. This occurs through resonant coupling of the signal pulse with the Mollow sideband transitions created by the holding pulse, leading to either augmentation or negation of the final QD population achieved by the holding pulse alone. This effect is applied to ultrafast all-optical logic AND, OR and NOT gates in the presence of significant (0.1 THz) nonradiative dephasing and (about 1%) inhomogeneous broadening. Further numerical studies of pulse evolutions inside the proposed devices demonstrate satisfactory population contrast within a PBG waveguide length of about 10 micro meter. These results provide the building blocks for low-power, ultrafast, multi-wavelength channel, on-chip, all-optical computing.

Chemical and biological contaminants can enter a drinking water distribution system through one of the many access points to the network and can spread quickly affecting a very large area. This is of great concern, and water utilities need to consider effective tools and mitigation strategies to improve water network security. This work presents two components that have been integrated into EPA’s Water Security Toolkit, an open-source software package that includes a set of tools to help water utilities protect the public against potential contamination events. The first component is a novel water quality modeling framework referred to as Merlion. The linear system describing contaminant spread through the network at the core of Merlion provides several advantages and potential uses that are aligned with current emerging water security applications. This computational framework is able to efficiently generate an explicit mathematical model that can be easily embedded into larger mathematical system. Merlion can also be used to efficiently simulate a large number of scenarios speeding up current water security tools by an order of magnitude. The last component is a pair of mixed-integer linear programming (MILP) formulations for efficient source inversion and optimal sampling. The contaminant source inversion problem involves determining the source of contamination given a small set of measurements. The source inversion formulation is able to handle discrete positive/negative measurements from manual grab samples taken at different sampling cycles. In addition, sensor/sample placement formulations are extended to determine the optimal locations for the next manual sampling cycle. This approach is enabled by a strategy that significantly reduces the size of the Merlion water quality model, giving rise to a much smaller MILP that is solvable in a real-time setting. The approach is demonstrated on a large-scale water network model with over 12,000 nodes while considering over 100 timesteps. The results show the approach is successful in finding the source of contamination remarkably quickly, requiring a small number of sampling cycles and a small number of sampling teams. These tools are being integrated and tested with a real-time response system.

The construction of a substitution box (S-box) with high nonlinearity and high resiliency is an important research area in cryptography. In this thesis, t-resilient nxm S-box construction methods depending on linear block codes presented in &quot / A Construction of Resilient Functions with High Nonlinearity&quot / by T. Johansson and E. Pasalic in 2000, and two years later in &quot / Linear Codes in Generalized Construction of Resilient Functions with Very High Nonlinearity&quot / by E. Pasalic and S. Maitra are compared and the former one is observed to be more promising in terms of nonlinearity. The first construction method uses a set of nonintersecting [n-d,m,t+1] linear block codes in deriving t-resilient S-boxes of nonlinearity 2^(n-1)-2^(n-d-1),where d is a parameter to be maximized for high nonlinearity. For some cases, we have found better results than the results of Johansson and Pasalic, using their construction. As a distinguished reference for nxn S-box construction methods, we study the paper &quot / Differentially Uniform Mappings for Cryptography&quot / presented by K.Nyberg in Eurocrypt 1993. One of the two constructions of this paper, i.e., the inversion mapping described by Nyberg but first noticed in 1957 by L. Carlitz and S. Uchiyama, is used in the S-box of Rijndael, which is chosen as the Advanced Encryption Standard. We complete the details of some theorem and proposition proofs given by Nyberg.

Landslides have occurred throughout the Holocene geologic epoch and they continue to occur in the Peace River Lowlands of Alberta and British Columbia. This study was conducted to provide an understanding of the processes and extents of one such landslide situated on a major slope at the Town of Peace River, Alberta by means of geophysical techniques with the aim of reducing the geohazard risk to lives and infrastructures. The geophysical characterization involved the acquisition, processing, and joint interpretation of seismic reflection, seismic refraction tomography, vertical seismic profile, and electrical resistivity tomography datasets, thereby providing important information about the subsurface geometry of the landslide, insights into the material properties of the unstable mass in contrast to that of the stable rock, and possible causes of the landslide. This contribution shows that putting considerable efforts into the acquisition and processing of geophysical datasets can yield valuable functional details. / Geophysics

The Gaussian geostatistical model has been widely used in Bayesian modeling of spatial data. A core difficulty for this model is at inverting the n x n covariance matrix, where n is a sample size. The computational complexity of matrix inversion increases as O(n3). This difficulty is involved in almost all statistical inferences approaches of the model, such as Kriging and Bayesian modeling. In Bayesian inference, the inverse of covariance matrix needs to be evaluated at each iteration in posterior simulations, so Bayesian approach is infeasible for large sample size n due to the current computational power limit. In this dissertation, we propose two approaches to address this computational issue, namely, the auxiliary lattice model (ALM) approach and the Bayesian site selection (BSS) approach. The key feature of ALM is to introduce a latent regular lattice which links Gaussian Markov Random Field (GMRF) with Gaussian Field (GF) of the observations. The GMRF on the auxiliary lattice represents an approximation to the Gaussian process. The distinctive feature of ALM from other approximations lies in that ALM avoids completely the problem of the matrix inversion by using analytical likelihood of GMRF. The computational complexity of ALM is rather attractive, which increase linearly with sample size. The second approach, Bayesian site selection (BSS), attempts to reduce the dimension of data through a smart selection of a representative subset of the observations. The BSS method first split the observations into two parts, the observations near the target prediction sites (part I) and their remaining (part II). Then, by treating the observations in part I as response variable and those in part II as explanatory variables, BSS forms a regression model which relates all observations through a conditional likelihood derived from the original model. The dimension of the data can then be reduced by applying a stochastic variable selection procedure to the regression model, which selects only a subset of the part II data as explanatory data. BSS can provide us more understanding to the underlying true Gaussian process, as it directly works on the original process without any approximations involved. The practical performance of ALM and BSS will be illustrated with simulated data and real data sets.