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Location-based Services (LBSs) are important building blocks for a wide spectrum of context-aware applications. The Global Positioning System (GPS) has provided almost ubiquitous positioning services in outdoor environments and enabled many outdoor LBSs such as routing navigation, location check-in and field analysis. However, the indoor LBSs equivalents, e.g., routing the visually-impaired, are not yet pervasively available due to many unaddressed challenges in indoor positioning system deployments. The overarching goal of this project is to develop practical systems to address such challenges and finally build an Open Global Indoor Positioning System (OGIPS). OGIPS is a supplementation to GPS indoors and the combination of OGIPS and GPS is anticipated to provide truly global positioning services to virtually anyone. The Wi-Fi Positioning System (WPS) is a dominant enabling technology of OGIPS for its sheer prevalence in pervasiveness, reliability and performance. This doctoral study project identified three major challenges for building OGIPS based on WPSs and proposed corresponding solutions. The first challenge is how to deploy WPSs with zero cost. WPS deployment requires Radio Map calibration, which, in current industrial practice, relies on high-cost scene analysis. To reduce the deployment cost, it is possible to leverage the free Crowdsourced data. In fact, an enormous amount of Wi-Fi signal measurements could be collected by Implicit Crowdsourcing, that is, collecting unlabeled data in an unobtrusive manner during normal courses of the smartphone users, e.g., strolling around shopping malls. The challenges is then reformulated as how to perform Radio Map calibration via Implicit Crowdsourcing. This project formulates the targeted problem with a novel Hyper-Graph Matching framework, which lends various merits to the system in terms of scalability, extendability and robustness. The elegant problem formulation allows the system to exploit the accomplishments of Graph Matching researches in the past decades, especially in Computer vision. We designed, implemented the system, HyperLoc, and validated it with extensive experiments with both simulated and real-world data. Experimental results indicates that HyperLoc is able to construct zero-cost WPSs in real-world settings. The overall positioning performance of HyperLoc, a zero-cost system, is comparable to high-cost manually-calibrated WPSs . To our knowledge, HyperLoc is the first work to apply Graph Matching techniques to Radio Map calibrations and the first work that develops a practical and scalable zero-cost WPS implementation in real-world settings. The second challenge is how to maintain WPSs performance over time with zero cost. The Radio Map describes the signal environment in relation to the physical environment of a venue. However, the relation often changes substantially upon changes of radio propagation patterns, caused by many factors, e.g., change of the layout of the venue. To maintain consistent and reliable performance, Radio Maps must be versionized and re-calibrated. Here we arrive at the second challenge, that is, how to effectively manage Radio Map versioning with zero cost. This project proposed a novel Radio Map versioning control system, RAEDS, by detecting system anomalous events that degrade indoor positioning performance substantially. The system generalizes arbitrary Radio Map degrading factors as Radio Map anomalous events, which could be modeled and hence detected using state-of-the-art event detection techniques. We designed, implemented and evaluated RAEDS with both synthetic and real-world experiments. The results showed that RAEDS is able to detect anomalous events accurately with a low false alarm rate. To our knowledge, RAEDS is the first work to apply advanced event detection techniques in WPS health monitoring for system versioning control. The combination of HyperLoc and RAEDS is anticipated to enable a practical zero-cost WPS in real-world settings. However, many challenges still present. The OGIPS architecture shall be carefully designed to accommodate the domain-specific requirements of OGIPS in addition to the general requirements of highly-available and scalable systems. Hence the third challenge is how to architect OGIPS to meet the desired requirements. Practical design goals are discussed comprehensively and a proposed design of the architecture and implementations is described in details. Guidelines and recommendations in system implementations were made. More importantly, the proposed OGIPS design is orthogonal to HyperLoc and RAEDS. That means OGIPS is able to flexibly integrate other zero-cost WPSs implementations at high-level. This merit allows other researchers to reuse the proposed architecture with their proprietary zero-cost WPS implementations. The proposed solutions in this work are expected to pave the path towards building OGIPS in real-world settings. Future research efforts will be devoted to improving the adaptiveness and robustness of the proposed systems in terms of device heterogeneity, adaptiveness to user patterns and insufficient data. Finally, the findings of this thesis are expected to contribute to the research communities sharing the same conviction, that is, to make the indoor positioning service accessible to virtually anyone, anytime and anywhere.

Digital Image Correlation (DIC) is a widely used full-field measurement technique in the field of experimental mechanics because of its simplicity and ease of implementation. However, owing to the inherent complexity of DIC error sources, the problem of DIC error reduction and uncertainty quantification is still unsolved and has received considerable attention in recent years. The existing work on DIC error reduction is usually focused on specific error sources, e.g. local smoothing techniques are normally applied to reduce errors due to image acquisition noise. Moreover, DIC uncertainty quantification methods are usually derived from a subset-based DIC framework with an assumption of Gaussian image noise. Established methods are normally subject to an ad-hoc choice of parameterisation and might only be able to achieve a local optimum. On the other hand, originally developed in geo-statistics, Kriging is known as optimal interpolation to predict interpolated values using random variables as a realization of a Gaussian process. The Kriging technique has the excellent capability in global optimisation and uncertainty quantification. It is advisable to make an attempt to introduce the Kriging method to DIC to facilitate the solution of error and uncertainty issue. The main purpose of this thesis is to offer a generic and global method that can reduce general DIC errors and quantify measurement uncertainty for displacement and strain results based on Kriging regression from Gaussian Process (GP) and Bayesian perspective. Firstly, a new global DIC approach known as Kriging-DIC was developed through incorporating the Kriging regression model into the classical global DIC algorithm as a full-field shape function. The displacement field of the Region of Interest (RoI) is formulated as a best linear unbiased realisation that contains correlations between all the samples. The measurement errors of control points are accounted for through a global regularisation technique using a global error factor. With the aid of the Mean Squared Error (MSE) determined from the Kriging model, a self-adaptive updating strategy was developed to achieve an optimal control grid without artificial supervision. The developed Kriging DIC method was compared with subset-based DIC, FE-DIC and B-Spline DIC by using synthetic images and open-access experimental data. The effectiveness and robustness of Kriging DIC was verified by numerical examples and an experimental I-section beam test. Secondly, a Kriging-based DIC uncertainty quantification method was proposed to quantify uncertainty of displacement and strain results of the subset-based DIC through a post-processing analysis based on Kriging regression. The subset-by-subset uncertainty was estimated through the subset-based DIC framework and derived as a function of the inverse of the Hessian matrix and residual of Sum of Squared Difference (SSD). This local subset-based uncertainty was then integrated into Kriging regression formula allowing uncertainty quantification of displacement field from a global sense. Based on Cholesky decomposition and covariance matrix solved by the Kriging formula, a multivariate normal sampling process was used to quantify the strain uncertainty whereas displacement gradients were calculated by a Finite Difference technique. Both numerical case studies and an experimental cantilever beam test were employed to test the method, which was found to be able to improve the accuracy of displacement and strain results and quantify corresponding uncertainties. Furthermore, a new approach was developed to calculate strain results by means of Kriging gradients, which was also compared with a state-of-the-art PLS local fitting algorithm. In summary, the main contribution of this thesis is the development of a global DIC algorithm (i.e. Kriging-DIC) and a Kriging-based DIC uncertainty quantification approach. These two methods provide great potential to globally improve DIC measurement accuracy and quantify uncertainties of displacement and strain results.

Due to pending legislations and market pressure, lead-free solders will replace Sn–Pb solders in 2006. Among the lead-free solders being studied, eutectic Sn–Ag, Sn–Cu and Sn–Ag–Cu are promising candidates and Sn–3.8Ag–0.7Cu could be the most appropriate replacement due to its overall balance of properties. In order to garner more understanding of lead-free solders and their application in flip-chip scale packages, the properties of lead free solders, including the wettability, intermetallic compound (IMC) growth and distribution, mechanical properties, reliability and corrosion resistance, were studied and are presented in this thesis.

During the last two decades, the oil and gas industry started production from unconventional reservoirs, thanks to the rapid development of hydraulic fracturing technology. Fractures such as joints, faults, veins, and bedding planes are ubiquitous in unconventional formations such as laminated reservoirs. These discontinuities always form complex networks affecting the hydrological and mechanical behavior of subsurface rocks. Ideally, hydraulic fractures are expected to communicate these fracture networks to form a continuous path for fluid flow. However, the interaction mechanism between hydraulic fracture and natural fractures may result in different propagation paths to form various fracture geometries and stimulated reservoir volume (SRV). In order to optimize the fracturing treatment and predict the SRV in fractured reservoirs, it is necessary to investigate the fracture propagation pattern from the simple interaction modes between hydraulic fracture and natural fractures to complicated single and multi-stage fracture propagation in laminated reservoir perspectives. This research is divided into three sections. In the first section, a novel model was proposed based on a lattice-based simulator, XSite, to predict interaction modes between hydraulic fracture and natural fractures considering the effect of formation mechanical properties, stress state, and fluid injection parameters. To build this predictive model, a number of fracturing simulations were executed to provide pressure time and interaction modes data. The conception interaction pressurization rate index (IPRI) obtained from pressure time data was proposed as an indicator to characterize the interaction modes. Several lab experiments were used to verify the accuracy of the predictive model. In the second section, a more common fracture model was built to study the hydraulic fracture propagation in the laminated reservoir, which contains the natural interfaces and caprock layers, both significantly affecting the hydraulic fracture geometry. The results indicated that injection rate and caprock Young’s modulus prone to the fracture propagation in the horizontal direction or along the interfaces, thus stress anisotropy and interfaces and caprocks tensile strength favor to the fracture propagation in the vertical direction as a tensile fracture. In the third section of this research, a representative multi-stage model was developed to study the influence of formation properties and injection parameters on fracture evolution in the laminated reservoir. Tension and shear stimulated area were proposed to quantify the fracture propagation modes and directions in formation. A statistical method was used to build the predictive model to evaluate the formation stimulation potential based on considering contribution of all influential parameters. A series of artificially generated in possible range influencing factors verified the accuracy of the proposed model. These three sections progressively investigate the propagation of hydraulic fracture in laminated reservoirs and develop a model for evaluating the reservoir's stimulation potential, which provides a guide for fracturing field operations.

There have been extensive studies of classification and prediction of cancer outcome with composite gene features that combine functionally related genes together as a single feature to improve the classification and prediction accuracy. Various algorithms have been proposed for feature extraction, feature activity inference, and feature selection, which all claim to improve the prediction accuracy. However, due to the limited test data sets used by each independent study, inconsistent test procedures, and conflicting results, it is difficult to obtain a comprehensive understanding of the relative performances of these algorithms. In this study, various algorithms for the three steps in using composite features for cancer outcome prediction were implemented and an extensive comparison and evaluation were performed by applying testing to seven microarray data sets covering two cancer types and three different clinical outcomes. Also by integrating algorithms in all three different steps, we aimed to investigate how to get the best cancer prediction by using different combinations of these techniques.

Various diseases have been linked to the human microbiota, but the underlying molecular mechanisms of the human microbiota in disease pathogenesis are often poorly understood. Using acne as a disease model, my study aims to understand the functional capability changes and the molecular response of the skin microbiota to host metabolite signaling in disease pathogenesis. By metagenomic analysis, I found that the genes of a pathogenic gene island in the skin bacterium, Propionibacterium acnes, were significantly enriched in acne subjects. By metatranscriptomic analysis, I found that the transcriptional profiles of the skin microbiota separated acne patients from healthy individuals. The vitamin B12 biosynthesis pathway in P. acnes, was significantly down-regulated in acne patients. Through in-vivo and in-vitro experiments, I further demonstrated that host vitamin B12 modulates the activities of the skin microbiota and plays a signaling role in acne pathogenesis. To understand the molecular mechanism underlying the transcriptional regulation of P. acnes genes by vitamin B12, I analyzed ten putative regulatory elements in multiple P. acnes genomes and identified sequence variations among different strains. It suggests that the vitamin B12 modulation of P. acnes transcription is individual microbiome-dependent. My findings suggest a novel bacterial pathogenesis pathway in acne. My study also provides evidence that metabolite-mediated interactions between the host and the skin microbiota play essential roles in disease development. To further elucidate how the skin microbiota interacts with the host in disease pathogenesis, I have developed a protocol for enriching bacterial RNA from human skin biopsy samples, which lays a foundation for simultaneously analyzing the interactions between the skin microbiota and host cells at the transcriptional level.

Microtubules are an essential component of the cytoskeleton that provide structural integrity and facilitate important functions in cells. In this work, I will explore several aspects of microtubule mechanics and function using a wide range of biophysical techniques. I am particularly interested in the effects of stabilizing agents, including small molecule inhibitors of microtubule dynamics (such as taxol or epothilone), and microtubule-binding proteins, such as tau. First, using advanced spectral analytical techniques, we studied the effects of tau proteins on the mechanical properties of single microtubule (MT) filaments under controlled in vitro conditions. We found that the short forms of 3-repeat (3R) and 4-repeat (4R) wild-type (WT) tau proteins reduce the stiffness of taxol-assembled MTs compared to a no tau control, despite the fact that the microtubule diameter is known to increase when these tau proteins bind. In contrast, single point tau mutants P301L, R406W and ΔN296, which are all linked to devastating neurological diseases, do not have significant effects on microtubule stiffness compared to a no tau control, raising interesting questions about possible mechanical origins of tauopathy diseases.Next, we examined the effects of tau proteins on in vitro transport properties of kinesin-bound cargoes on microtubules. In comparison to the no tau control, kinesin-bound quantum dot cargoes had lower velocity and shorter run lengths in the presence of tau when moving on taxol-assembled microtubules. Most of the single point tau mutants that we tested showed similar slowing of cargo translocation, with speed reductions similar to those observed with WT tau. One exception was the 4R short R406W mutant tau, in which the velocities of kinesin-bound cargoes were significantly lower than in WT case. The disease mechanism for mutant has been particularly puzzling, so our results may suggest a more prominent role in disruption of axonal transport than was previously appreciated.Next, we investigated the effects of microtubule-stabilizing chemicals epothilone-A and -B on 1) microtubule mechanics, 2) the transport properties of kinesins and 3) the ability of WT tau proteins modify the stiffness of microtubules assembled with epothilone. We found that microtubules assembled in the presence of epothilone-A or -B were less stiff compared to taxol-assembled MTs, and the addition of WT tau further reduced the stiffness. However, the differences in stiffness/persistence length between epothilone-assembled microtubules and taxol-assembled microtubules diminished after the addition of WT tau. Kinesin translocation speed was sensitive to the type of stabilizing chemical, and the changes in velocity in the presence of tau were also depended on the assembly condition. Epothiolone and taxol compunds are both frequently used in cancer chemotherapies, and our results shed light on the possible molecular mechanisms of neurological side effects (such as debilitating nerve pain) when these agents are used.Lastly, we looked at the effects of tau on intracellular trafficking in COS-7 cells. We found that the microtubule network in the cells were dramatically modified after the introduction of tau via transient transfection, with substantial bundling, aggregation and membrane-association in the presence of tau. However, there were no obvious differences in the microtubule network structures between cells that were transfected with mutant tau and wild-type tau. Interestingly, despite the major modification of the cytoskeletal structures in the presence of tau, the measured velocities of lysosomes in directed transport in cells that were transfected with tau were not significantly different compared to the lysosome velocities in cells with no tau.Taken together, studies provide important new insights into how tau proteins and other small molecule stabilizers modulate the mechanical and functional properties of cytoskeletal microtubules and how misregulations in tau may be related to the development of neurodegeneration and dementia diseases.

Lewis base (trimethylsilylquinine and trimethylsilylquinidine) catalyzed acyl halide-aldehyde cyclocondensation (AAC) reactions have been developed to prepare synthetically important bispropionate units previously by the Nelson group. A new Lewis base-catalyzed diastereoselective Mukaiyama aldol reaction has extended this bispropionate unit preparation methodology to all-syn bispropionates which widely occurred in polypropionate natural products. By using phenoxides as Lewis base catalysts, enol silanes were activated and underwent a Felkin attack on an aldehyde through an antiperiplanar transition state to generate all-syn bispropionate product in high yields and excellent diastereoselectivities.All-syn bispropionate prepared from the Lewis base-catalyzed diastereoselective Mukaiyama aldol reaction has been untilized in natural product synthesis of erythronolide B establishing ¡°syn,syn,syn¡± stereochemical relationships from C2-C5.Studies towards the total synthesis of the cytotoxic marine macrolide amphidinolide H have been disclosed. By exploiting AAC methodology, several key stereochemical relationships present in major fragments 198 and 199 were established. A highly enantioselective synthesis of methyl ketone 200 was realized from commercially available (S)-(−)-glycidol. Iodide 198 was coupled with boronic ester 199 via an efficient Suzuki reaction to form a C7-C20 fragment.

This research provides realistic techniques to visualize the process of damage to residential building caused by hurricane force winds. Three methods are implemented to make the visualization useful for educating the public about mitigation measures for their homes. First, the underline physics uses Quick Collision Response Calculation. This is an iterative method, which can tune the accuracy and the performance to calculate collision response between building components. Secondly, the damage process is designed as a Time-scalable Process. By attaching a damage time tag for each building component, the visualization process is treated as a geometry animation allowing users to navigate in the visualization. The detached building components move in response to the wind force that is calculated using qualitative rather than quantitative techniques. The results are acceptable for instructional systems but not for engineering analysis. Quick Damage Prediction is achieved by using a database query instead of using a Monte-Carlo simulation. The database is based on HAZUS® engineering analysis data which gives it validity. A reasoning mechanism based on the definition of the overall building damage in HAZUS® is used to determine the damage state of selected building components including roof cover, roof sheathing, wall, openings and roof-wall connections. Exposure settings of environmental aspects of the simulated environment, such as ocean, trees, cloud and rain are integrated into a scene-graph based graphics engine. Based on the graphics engine and the physics engine, a procedural modeling method is used to efficiently render residential buildings. The resulting program, Hurricane!, is an instructional program for public education useful in schools and museum exhibits.