Light Detection And Ranging (LiDAR) mapping has been emerging over the past few years as a mainstream tool for the dense acquisition of three dimensional point data. Besides the conventional mapping missions, LiDAR systems have proven to be very useful for a wide spectrum of applications such as forestry, structural deformation analysis, urban mapping, and reverse engineering. The wide application scope of LiDAR lead to the development of many laser scanning technologies that are mountable on multiple platforms (i.e., airborne, mobile terrestrial, and tripod mounted), this caused variations in the characteristics and quality of the generated point clouds. As a result of the increased popularity and diversity of laser scanners, one should address the heterogeneous LiDAR data post processing (i.e., registration and segmentation) problems adequately. Current LiDAR integration techniques do not take into account the varying nature of laser scans originating from various platforms. In this dissertation, the author proposes a methodology designed particularly for the registration and segmentation of heterogeneous LiDAR data. A data characterization and filtering step is proposed to populate the points’ attributes and remove non-planar LiDAR points. Then, a modified version of the Iterative Closest Point (ICP), denoted by the Iterative Closest Projected Point (ICPP) is designed for the registration of heterogeneous scans to remove any misalignments between overlapping strips. Next, a region-growing-based heterogeneous segmentation algorithm is developed to ensure the proper extraction of planar segments from the point clouds. Validation experiments show that the proposed heterogeneous registration can successfully align airborne and terrestrial datasets despite the great differences in their point density and their noise level. In addition, similar testes have been conducted to examine the heterogeneous segmentation and it is shown that one is able to identify common planar features in airborne and terrestrial data without resampling or manipulating the data in any way. The work presented in this dissertation provides a framework for the registration and segmentation of airborne and terrestrial laser scans which has a positive impact on the completeness of the scanned feature. Therefore, the derived products from these point clouds have higher accuracy as seen in the full manuscript.

In recent years, financial simulations have gotten computationally intensive due to larger portfolio sizes, and an increased demand to perform real-time risk analysis. In this paper, we propose a hardware implementation that uses a recursive analytical method to price the Collateralized Debt Obligations. A novel convolution approach based on FIFOs for storage is implemented for the recursive convolution. It is also used to address one of the main drawbacks of the analytical approach. The FIFO-based convolution approach is compared against two different convolution approaches outperforming them with a much smaller memory usage. The CDO core designed with the FIFO-based convolution method is implemented and tested on a Virtex-5 FPGA and compared against a C implementation, running on a 2.8GHz Intel Processor, resulting in a 41-fold speed up. A brief comparison against a Monte Carlo based hardware implementation for structured instruments yields mixed results.

In recent years, financial simulations have gotten computationally intensive due to larger portfolio sizes, and an increased demand to perform real-time risk analysis. In this paper, we propose a hardware implementation that uses a recursive analytical method to price the Collateralized Debt Obligations. A novel convolution approach based on FIFOs for storage is implemented for the recursive convolution. It is also used to address one of the main drawbacks of the analytical approach. The FIFO-based convolution approach is compared against two different convolution approaches outperforming them with a much smaller memory usage. The CDO core designed with the FIFO-based convolution method is implemented and tested on a Virtex-5 FPGA and compared against a C implementation, running on a 2.8GHz Intel Processor, resulting in a 41-fold speed up. A brief comparison against a Monte Carlo based hardware implementation for structured instruments yields mixed results.

Master of Science / Department of Architectural Engineering and Construction Science / Julia A. Keen / This report addresses the operation, use, and design of air-to-air variable refrigerant flow systems, also known as VRF. Relatively new to the United States, these HVAC systems have potential to reduce energy consumption and utility costs in the correct applications. Although useful in many applications, the best building types for VRF are those requiring a large number of zones and with low ventilation air requirements. The report explains design and system selection considerations and accordingly presents two flowcharts to help designers implement this system. To show how the system compares to traditional technologies in terms of efficiency and cost, the report presents results from several studies comparing VRF to other systems. In addition, an energy modeling study is conducted to clarify the effect of climate on the system; this study established air-to-air VRF as having highest energy consumption in dry, southern climates, based on energy use and operating costs. With this report, HVAC designers can learn when air-to-air VRF is an acceptable method for providing heating and cooling in a building.

Doctor of Philosophy / Department of Electrical and Computer Engineering / Balasubramaniam Natarajan / Dale E. Schinstock / In this dissertation, two applications related to vision-based localization and mapping are considered: (1) improving navigation system based satellite location estimates by using on-board camera images, and (2) deriving position information from video stream and using it to aid an auto-pilot of an unmanned aerial vehicle (UAV). In the first part of this dissertation, a method for analyzing a minimization process called bundle adjustment (BA) used in stereo imagery based 3D terrain reconstruction to refine estimates of camera poses (positions and orientations) is presented. In particular, imagery obtained with pushbroom cameras is of interest. This work proposes a method to identify cases in which BA does not work as intended, i.e., the cases in which the pose estimates returned by the BA are not more accurate than estimates provided by a satellite navigation systems due to the existence of degrees of freedom (DOF) in BA. Use of inaccurate pose estimates causes warping and scaling effects in the reconstructed terrain and prevents the terrain from being used in scientific analysis. Main contributions of this part of work include: 1) formulation of a method for detecting DOF in the BA; and 2) identifying that two camera geometries commonly used to obtain stereo imagery have DOF. Also, this part presents results demonstrating that avoidance of the DOF can give significant accuracy gains in aerial imagery. The second part of this dissertation proposes a vision based system for UAV navigation. This is a monocular vision based simultaneous localization and mapping (SLAM) system, which measures the position and orientation of the camera and builds a map of the environment using a video-stream from a single camera. This is different from common SLAM solutions that use sensors that measure depth, like LIDAR, stereoscopic cameras or depth cameras. The SLAM solution was built by significantly modifying and extending a recent open-source SLAM solution that is fundamentally different from a traditional approach to solving SLAM problem. The modifications made are those needed to provide the position measurements necessary for the navigation solution on a UAV while simultaneously building the map, all while maintaining control of the UAV. The main contributions of this part include: 1) extension of the map building algorithm to enable it to be used realistically while controlling a UAV and simultaneously building the map; 2) improved performance of the SLAM algorithm for lower camera frame rates; and 3) the first known demonstration of a monocular SLAM algorithm successfully controlling a UAV while simultaneously building the map. This work demonstrates that a fully autonomous UAV that uses monocular vision for navigation is feasible, and can be effective in Global Positioning System denied environments.

Master of Science / Department of Civil Engineering / Kyle Riding / Some limestone coarse aggregate in concrete pavement can break down under repeated freeze-thaw cycles. Application of rock salt may increase the severity of exposure conditions because of trace compounds, such as calcium sulfate, in rock salt. Subsequently, limestone aggregate in concrete was subjected to freeze-thaw cycling in two methods: salt-treating the aggregate before batching concrete, and half-immersing concrete specimens in rock salt solution during freeze-thaw cycling. Concrete and saw-cut limestone specimens were also subjected to wet-dry cycles in varying salt solutions to examine the influence of trace compounds in rock salt. Freeze-thaw test results indicate that the test methods used were not severe enough to determine if a limestone aggregate was durable or not. The wet-dry testing was also not severe enough to determine the effects of trace compounds in salt solution.

Master of Science / Department of Computing and Information Sciences / Gurdip Singh / Deluge is a protocol used for remote re-programming of nodes in a wireless sensor networks by injecting messages into a network of motes without having the motes directly connected to the PC. It uses the 3-way handshake protocol consisting of 3 types of messages: advertise, request and data. The protocol is very useful but is restricted to homogeneous networks wherein all nodes must be programmed with the same code. This project is an attempt to modify the existing protocol to work for heterogeneous networks where different motes function differently and have to be programmed differently. The project was developed using Java and nesC (a dialect of C) which supports component based programming. The nodes run an operating system called tinyOS which is specifically designed for sensor networks. The system was tested on a network of micaZ and TelosB motes.

Master of Science / Department of Electrical and Computer Engineering / Caterina M. Scoglio / Forecasting of network traffic plays a very important role in many domains such as congestion control, adaptive applications, network management and traffic engineering. Characterizing the traffic and modeling are necessary for efficient functioning of the network. A good traffic model should have the ability to capture prominent traffic characteristics, such as long-range dependence (LRD), self-similarity, and heavy-tailed distribution. Because of the persistent dependence, modeling LRD time series is a challenging task. In this thesis, we propose a non-linear time series model, Generalized AutoRegressive Conditional Heteroskedasticity (GARCH) of order p and q, with innovation process generalized to the class of heavy-tailed distributions. The GARCH model is an extension of the AutoRegressive Conditional Heteroskedasticity (ARCH) model, has been used in many financial data analysis. Our model is fitted on a real data from the Abilene Network which is a high-performance Internet-2 backbone network connecting research institutions with 10Gbps bandwidth links. The analysis is done on 24 hours data of three different links aggregated every 5 minutes. The orders are selected based on the minimum modified Akaike Information Criterion (AICC) using Introduction to Time Series Modeling (ITSM) tool. For our model the best minimum order was found to be (1,1). The goodness of fit is evaluated based on the Q-Q (t-distributed) plot and the ACF plot of the residuals and our results confirm the goodness of fit of our model. The forecast analysis is done using a simple one-step prediction. The first 24 hrs of the data set are used as the training part to model the traffic; the next 24 hrs are used for performing the forecast and the comparison. The actual traffic data and the predicted traffic data is compared to evaluate the performance of the model. Based on the prediction error the performance metrics are evaluated. A comparative study of GARCH model with other existing models is performed and our results confirms the simplicity and the better performance of our model. The complexity of the model is measured based on the number of parameters to be estimated. From this study, the GARCH model is found to have the ability to forecast aggregated traffic but further investigation need to be conducted on a less aggregated traffic. Based on the forecast model developed from the GARCH model, we also intend to develop a dynamic bandwidth allocation algorithm as a future work.

Master of Science / Department of Architectural Engineering and Construction Science / Fred L. Hasler / On-site energy production is becoming increasingly prevalent in building systems design with a renewed public awareness of sustainability, decreased energy resources, and an increase in the requirements of local and federal energy codes. Systems such as photovoltaics and solar thermal collectors have been implemented in designs to meet these challenges. The emerging technology of hybrid photovoltaic thermal (PVT) offers the potential to combine these systems into one contained module. A hybrid PVT system can simultaneously produce thermal and electrical energy, maximizing the use of available surface area available for energy production. Hybrid PVT can be implemented using PVT air collectors, PVT liquid collectors, and ventilated PV facades. Hybrid PVT is gaining interest at the academic level and is being applied at the residential level. Several commercial hybrid PVT products are currently manufactured, but options are limited. This report will evaluate PV, solar thermal collector, and hybrid PVT technologies, discuss the various components required for these systems, and present advantages and disadvantages of these systems. For an example elementary school design, the report will compare monthly energy production of the various systems, evaluating their ability to supply the peak loads of an example building design. Estimated first costs and operating and maintenance costs will be evaluated. The report will also quantify the ideal balance of PV and solar thermal collectors for the example based on loads and simple payback. Conclusions will be made about the current state of hybrid PVT and what steps need to be taken for it to be effectively implemented in the commercial building market.

Doctor of Philosophy / Department of Secondary Education / Jacqueline D. Spears / Retention of women in the architectural engineering workforce is important to the diversity and future success of the profession. However, little research has been done on why women leave the engineering workforce, making it difficult for engineering employers to accommodate the needs of women employees as a means of increasing retention. This research study identifies the retention rate of women in architectural engineering and determines why women leave the profession. The study consisted of a written survey coupled with follow-up telephone interviews only with those who completed the survey and were no longer employed. A mailed survey was sent to all female graduates between the years 1990 and 2005 from a Midwest state university architectural engineering program. Individual telephone interviews were then conducted with these women who had identified themselves as no longer employed in a field related to architectural engineering. The study revealed a retention rate of 66%. It did not identify one single factor as the reason women leave the architectural engineering workforce but rather many factors that seem to contribute to or influence this decision. The primary factors that surfaced included work environment, family/work balance, and mentoring. These factors influencing retention are consistent with prior research on this topic in engineering and architecture. Four recommendations specifically promote retention in response to these findings: 1) offer alternate working arrangements to better accommodate family responsibilities, 2) develop mentoring programs to support female employees in their career progression, 3) develop programs to discuss issues that are specific to women in a male dominated workforce to help women be better equipped for obstacles they may encounter during their career progression, and 4) promote and assist women to re-enter the workforce, recognizing that some women will make the choice to take a break from their career.