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Details are given herein of the development, refinement and application of a higher-order accurate 3-D finite difference model for non-cohesive suspended sediment transport processes, in non-stratified estuarine and coastal waters. The velocity fields are computed using a 2-D horizontal depth-integrated model, in combination with either an assumed logarithmic velocity profile or a velocity profile obtained from field data. Also, for convenience in handling variable bed topographies and for better vertical resolution, a δ-stretching co-ordinate system has been used. In order to gain insight into the relative merits of various numerical schemes for modelling the convection of high concentration gradients, in terms of both accuracy and efficiency, thirty six existing finite difference schemes and two splitting techniques have been reviewed and compared by applying them to the following cases: i) 1-D and 2-D pure convection, ii) 1-D and 2-D convection and diffusion, and iii) 1-D non-linear Burger's equation. Modifications to some of the considered schemes have also been proposed, together with two new higher-order accurate finite difference schemes for modelling the convection of high concentration gradients. The schemes were derived using a piecewise cubic interpolation and an universal limiter (proposed scheme 1) or a modified form of the TVD filter (proposed scheme 2). The schemes have been tested for: i) 1-D and 2-D pure convection, and ii) 2-D convection and diffusion problems. The schemes have produced accurate, oscillation-free and non-clipped solutions, comparable with the ULTIMATE fifth- and sixth-order schemes. However, the proposed schemes need only three (proposed scheme 1) or five cell stencils. Hence, they are very attractive and can be easily implemented to solve convection dominated problems for complex bathymetries with flooding and drying. The 3-D sediment transport equation was solved using a splitting technique, with two different techniques being considered. With this technique the 3-D convective-diffusion equation for suspended sediment fluxes was split into consecutive 1-D convection, diffusion and convective-diffusion equations. The modified and proposed higher-order accurate finite difference schemes mentioned above were then used to solve the consecutive 1-D equations. The model has been calibrated and verified by applying it to predict the development of suspended sediment concentration profiles under non-equilibrium conditions in three test flumes. The results of numerical predictions were compared with existing analytical solutions and experimental data. The numerical results were in excellent agreement with the analytical solutions and were in reasonable agreement with the experimental data. Finally, the model has also been applied to predict sediment concentration and velocity profiles in the Humber Estuary, UK. Reasonable agreement was obtained between the model predictions and the corresponding field measurements, particularly when considered in the light of usual sediment transport predictions. The model is therefore thought to be a potentially useful tool for hydraulic engineers involved in practical case studies

This work focuses on using forward and adjoint transport in a hybrid application of 3-D deterministic (PENTRAN) and Monte Carlo (MCNP5) codes to model a series of neutron detector blocks. These blocks, or “channels,” contain a unique set of moderators with 4 atm He-3 proportional detectors tuned to detect and profile a gross energy spectrum of a passing neutron (SNM) source. Ganging the units together as a large area system enables one to apply time gating the source-detector response to maximize signal to noise responses from a passing source with minimal background; multiple units may be positioned as a collective synthetic aperture detector array to be used as a way of performing real time neutron spectroscopy for detecting special nuclear materials in moving vehicles.

International Telemetering Conference Proceedings / October 23-26, 2000 / Town & Country Hotel and Conference Center, San Diego, California / With wireless communications becoming the rule rather than the exception, satellite operators need tools to effectively monitor increasingly large and complex satellite constellations. Visual data monitoring increases the monitoring capacity of satellite operators by several orders of magnitude, enabling them to track hundreds of thousands of parameters in real-time on a single screen. With this powerful new tool, operators can proactively address potential problems before they become customer complaints.

International Telemetering Conference Proceedings / October 25-28, 1999 / Riviera Hotel and Convention Center, Las Vegas, Nevada / Recent years have seen a sharp rise in the size of satellite constellations. The monitoring and analysis tools in use today, however, were developed for smaller constellations and are ill-equipped to handle the increased volume of telemetry data. A new technology that can accommodate vast quantities of data is 3-D visualization. Data is abstracted to show the degree to which it deviates from normal, allowing an analyst to absorb the status of thousands of parameters in a single glance. Trend alarms notify the user of dangerous trends before data exceeds normal limits. Used appropriately, 3-D visualization can extend the life of a satellite by ten to twenty percent.

International Telemetering Conference Proceedings / October 21, 2002 / Town & Country Hotel and Conference Center, San Diego, California / The objective of the project is to continuously track a handheld device in an office, with centimeter accuracy in the three dimensions. A 3-D ray-tracing algorithm has been developed to simulate the impulse response of the indoor channel. The algorithm can evaluate the impulse response at multiple receiver locations. Non-linear optimization has been used to eliminate the need for multiple runs of simulation. The optimization program also significantly reduces the number of rays launched. The algorithm incorporates bandwidth effects on multipath resolution of the system.

Effective power delivery in Double-sided 3-D glass interposer packages was proposed, investigated, and demonstrated towards achieving high logic-to-memory bandwidth. Such 3-D interposers enable a simpler alternative to direct 3-D stacking by providing low-loss, wide-I/O channels between the logic device on one side of the ultra-thin glass interposer and memory stack on the other side, eliminating the need for complex TSVs in the logic die. A simplified PDN design approach with power-ground planes was proposed to overcome resonance challenges from (a) added parasitic inductance in the lateral power delivery path from the printed wiring board (PWB), due to die placement on the bottom side of the interposer, and (b) the low-loss property of the glass substrate. Based on this approach, this dissertation developed three important suppression solutions using, (a) the 3-D interposer package configuration, (b) the selection of embedded and SMT-based decoupling capacitors, and (c) coaxial power-ground planes with TPVs. The self-impedance of the 3-D glass interposer PDN was simulated using electromagnetic solvers, including printed-wiring-board (PWB) and chip-level models. Two-metal and four-metal layer test vehicles were fabricated on 30-μm and 100-μm thick glass substrates using a panel-based double-side fabrication process, for potential lower cost and improved electrical performance. The PDN test structures were characterized upto 20 GHz, to demonstrate the measured verification of (a) 3-D glass interposer power delivery network and (b) resonance suppression. The data and analysis presented in this dissertation prove that the objectives of this research were met successfully, leading to the first demonstration of effective PDN design in ultra-thin (30-100μm), and 3-D double-sided glass BGA packages, by suppressing the PDN noise from mode resonances.

This thesis addressed the problem of recognizing 3-D objects, using shape information extracted from range images, and parameterized volumetric models. The domains of the geometric shapes explored is that of complex curved objects with articulated parts, and a great deal of similarity between some of the parts. These objects are exemplified by animal shapes, however the general characteristics and complexity of these shapes are present in a wide range of other natural and man-made objects. In model-based object recognition three main issues constrain the design of a complete solution: representation, feature extraction, and interpretation. this thesis develops an integrated approach that addresses these three issues in the context of the above mentioned domain of objects. For representation I propose a composite description using globally deformable superquadratics and a set of volumetric primitives called geons: this description is shown to have representational and discriminative properties suitable for recognition. Feature extraction comprises a segmentation process which develops a method to extract a parts-based description of the objects as assemblies of defoemable superquadratics. Discontinuity points detected from the images are linked using 'active contour' minimization technique, and deformable superquadratic models are fitted to the resulting regions afterwards. Interpretation is split into three components: classification of parts, matching, and pose estimation. A Radical Basis Function [RBF] classifier algoritm is presented in order to classify the superquadratics shapes derived from the segmentation into one of twelve geon classes. The matching component is decomposed into two stages: first, an indexing scheme which makes effective use of the output of the [RBF] classifier in order to direct the search to the models which contain the parts identified. this makes the search more efficient, and with a model library that is organised in a meaningful and robust way, permits growth without compromising performance. Second, a method is proposed where the hypotheses picked from the index are searched using an Interpretation Tree algorithm combined with a quality measure to evaluate the bindings and the final valid hypotheses based on Possibility Theory, or Theory of Fuzzy Sets. The valid hypotheses ranked by the matching process are then passed to the pose estimation module. This module uses a Kalman Filter technique that includes the constraints on the articulations as perfect measurements, and as such provides a robust and generic way to estimate pose in object domains such as the one approached here. These techniques are then combined to produce an integrated approach to the object recognition task. The thesis develops such an integrated approach, and evaluates its perfomance inthe sample domain. Future extensions of each technique and the overall integration strategy are discussed.

Historically, Devonian Corniferous hydrocarbon production in south-central Kentucky has been a major contributor to the total hydrocarbon resources within Butler, Edmonson, and Warren counties. The Corniferous adds to the already large hydrocarbon totals produced from the Illinois Basin; however, this hydrocarbon contribution does not come without major pitfalls and inconsistencies. The south-central Kentucky Devonian Corniferous rocks comprise a diverse and complex hydrocarbon system made up of multiple migration pathways, trapping mechanisms, and seals. The multiple Corniferous units all derive production from the same source rock: the New Albany Shale. A Geographic Information System (GIS) containing data on surface elevations, structure contours and faults, geophysical well logs, well-scale oil and gas production, and lease to regional-scale oil and gas production has been compiled to produce a threedimensional (3-D) model using kriging with barriers to explain spatially the complexities of the Devonian Corniferous in south-central Kentucky. This model identifies the potential source rocks, the hydrocarbon charging and migration pathways, reservoirs, and reservoir seals. This model also utilizes kernel density estimation for developing an understanding of the spatial relationship of stratigraphic units being targeted within the Devonian relative to the spatially modeled Devonian Corniferous structures. This model also indicates locations and depths of key producing zones within south-central Kentucky. This project also explains the potential reasoning leading to the development of the Devonian Corniferous as a major hydrocarbon resource by placing it in the context of the underlying Silurian Corniferous and the multiple Siluro-Devonian unconformities positioned throughout the entire Siluro-Devonian section. This project bridges the gap between: 1) potential buried Silurian-age reef systems located south of the Pennyrile Fault zone, 2) the pervasive high porosity sections found in the lower Clear Creek Limestone unit, and 3) the development of expansive secondary partial dolomitization related to unconformable surfaces in the Middle and Upper Devonian Corniferous.

Pain experienced as a result of a disabling medical condition is a frequent problem in the clinical community and can often be present in any individual with this kind of health concern. Such pain is typically characterized by severe implications reflected on both a person‘s personal life, as well as on a country‘s health and economic systems. Research on pain has revealed that patients not only experience several types of pain that could prove to be challenging to address, but also that each individual can interpret the same type, location and severity of this pain in different subjective ways, making the need for more effective pain measurement methods an imperative and troublesome effort. In retrospect, the healthcare field is currently trying to enhance the available medical methods with alternatives that would be more efficient in providing accurate pain assessment. Most efforts revolve around traditional methods of measuring pain characteristics, which typically involve the 2-Dimensional (2-D) representation of the human body, often used to collect information regarding the type and location of pain. However, these 2-D pain drawings can be limited in their ability to efficiently visualize pain characteristics for diagnosis purposes. Nonetheless, patients have been shown to prefer such drawings. This research develops an alternative interactive software solution to help in addressing the aforementioned situation, by employing the capabilities that advancements in 3-Dimension (3-D) technology offer. Subsequently, in the anticipation that limitations of current 2-D pain visualization will be solved, the developed approach facilitates the measurement of pain experiences via a 3-D visualization model of the patient. To ensure that it can effectively perform in real-world medical practice, the 3-D pain drawing is evaluated in this research through real-life case studies that are carried out in designated settings. The research findings have shown that the developed approach can potentially make significant contributions to society, science/technology and healthcare provision, with patients and clinicians suggesting that 3-D technology can be a promising means in the pursuit for more effective pain measurement solutions.