Detecting the Direction of a UWB Anchor or Tag Using Secondary Radiation

An ultra-wideband (UWB) tag is a device that can be attached to objects to locate them or for other operations such as unlocking a device based on proximity to another device. Common implementations utilize at least three antennas on the device that detects a precise location of a UWB tag. This disclosure describes techniques that leverage secondary radiation caused by the metal case of a laptop (or other devices) to accurately locate a UWB tag while utilizing just two antennas, simplifying hardware design and reducing cost

Role Of Active Surveillance And Volume Monitoring In Patients With Small Renal Masses

Introduction: Current standard treatment of small renal masses (SRM) is surgical resection, but it is not plausible in all patients. Since the behaviors of SRM are not completely understood, the management of such lesions remains controversial. We evaluated the rates of linear and volumetric growth and metastasis of solid SRM in patients followed by active surveillance (AS). Materials and Methods: We performed a retrospective medical records review of 38 patients followed by AS for solid SRM. We reviewed radiographic imaging and hospital records. Extracted variables included size of lesions at diagnosis and surveillance, duration of surveillance, available pathology and progression to metastasis. Results: Of the original 44 lesions, 36 lesions in 32 patients were included. Mean lesion size at initial presentation was 1.73cm. Mean duration of surveillance was 34.3 months. Benign and malignant lesions demonstrated mean linear growth rates of 0.19cm/yr vs. 0.31cm/yr and volumetric growth rates of 0.95cm3/yr vs. 2.91cm3/yr, respectively. Seven patients crossed over to surgery due to patient preference or significant interval lesion growth. Pathology was obtained in 25% of lesions, of which 44% proved to be malignant renal tumors known as renal cell carcinoma (RCC). There was no correlation between initial lesion size and growth rate. Progression to metastasis was not seen in any of the subjects. Neither of two deaths during surveillance was due to renal cancer. Conclusions: Most enhancing SRM grow slowly, making active surveillance a safe alternative to surgery in nonsurgical candidates. Changes in lesion volume may be a better predictor of cancer cell growth than linear growth

ESTIMATING THE IMPACT OF BUILDING INFORMATION MODELING (BIM) UTILIZATION ON BUILDING PROJECT PERFORMANCE

Many benefits of utilizing the Building Information Modeling (BIM) technology have been recognized and reported in the Architectural, Engineering and Construction (AEC) industry literature. However, it seems that the construction industry still hesitates to fully adopt BIM. As some researchers suggest, the root cause may be in the lack of understanding of whether and how BIM improves project outcomes. This research aims to shed some light on this matter by studying the impact of BIM utilization on building project performance. This research follows a model-based approach as opposed to statistically analyzing the project outcomes with and without BIM utilization. The construction project supply chain is modeled at the design and construction activity level to represent the project behavior in terms of cost over time. As traditional project management tools as well as statistical methods are not able to consider the dynamic nature of the projects such as feedbacks, time delays and non-linear relationships, this research uses system dynamics methodology to model the project supply chain. The project supply chain model is calibrated with two sets of the projects; with BIM and without BIM. The two calibrated models, Non-BIM and BIM-utilized, are used to estimate the outcomes of a hypothetical set of the projects. The outcomes are compared in terms of the project performance indexes to analyze the BIM impact on the project performance. Since relatively few projects that utilized BIM were found, this research employs expert elicitation (EE) technique to capture the required knowledge from the industry to estimate the parameters of the BIM-utilized model. The EE is used to build a causal model to capture the impact of BIM utilization on the Non-BIM project model parameters in the absence of sufficient BIM-utilized project data

Optimum Search Schemes for Approximate String Matching Using Bidirectional FM-Index

Finding approximate occurrences of a pattern in a text using a full-text index is a central problem in bioinformatics and has been extensively researched. Bidirectional indices have opened new possibilities in this regard allowing the search to start from anywhere within the pattern and extend in both directions. In particular, use of search schemes (partitioning the pattern and searching the pieces in certain orders with given bounds on errors) can yield significant speed-ups. However, finding optimal search schemes is a difficult combinatorial optimization problem. Here for the first time, we propose a mixed integer program (MIP) capable to solve this optimization problem for Hamming distance with given number of pieces. Our experiments show that the optimal search schemes found by our MIP significantly improve the performance of search in bidirectional FM-index upon previous ad-hoc solutions. For example, approximate matching of 101-bp Illumina reads (with two errors) becomes 35 times faster than standard backtracking. Moreover, despite being performed purely in the index, the running time of search using our optimal schemes (for up to two errors) is comparable to the best state-of-the-art aligners, which benefit from combining search in index with in-text verification using dynamic programming. As a result, we anticipate a full-fledged aligner that employs an intelligent combination of search in the bidirectional FM-index using our optimal search schemes and in-text verification using dynamic programming outperforms today's best aligners. The development of such an aligner, called FAMOUS (Fast Approximate string Matching using OptimUm search Schemes), is ongoing as our future work

Doctor of Philosophy

dissertationRecent years' advancements in sensing technology have generated an enormous amount of data in various fields and industries, including transportation. Public transportation systems, as a critical component within the transportation ecosystem, have also been experiencing much data growth. The availability of big data not only improves traditional transit service monitoring, but also enables high-resolution transit performance analysis that guides decision making. However, the potential of these datasets is not fully explored yet due to several challenges such as residing noises in data records and limited computational power. This dissertation tries to address three of those challenges: how to incorporate and analyze missing data due to lack of electronic footage, how to enable high-resolution performance measurements that require extensive computation, and how to interpret the high-resolution results? The first challenge was addressed in a quest to find missing data on the different fare payment methods without electronic footage, and their impact (among other factors) on bus Dwell Time (DT). Integrating information from multiple data sources, a combined approach of optimization and regression analysis was developed that offers a data-driven evaluation of existing fare payment structures and their individual effects on DT. Using the 35M bus rapid transit line operated by the Utah Transit Authority as a case study, the method demonstrates the robustness and strong predictive power in DT modeling. Then we introduce a new algorithm that is computationally elegant and mathematically efficient to address the second challenge of run-time reduction. An open-source toolbox written in C++ is developed to implement the algorithm. The toolbox is tested on the City of St. George's transit network to showcase dynamic transit accessibility analysis. The experimental evidence shows significant reduction on computational time. To address challenge three on interpreting the high-resolution transit accessibility results, the algorithm in the previous study was applied to the Salt Lake City's network to compute travel times at multiple departure times throughout the day. A series of indicators that are intuitive to interpret were developed to determine the varying causes of poor transit accessibility and identify areas with immediate needs for service improvements. This dissertation manifested that utilizing newly available datasets not only improves the resolution and accuracy of the transit service assessments, but also takes a step further to enable a comprehensive study of various factors (stop characteristics) impacting transit service efficiency and quantifying critical decision-making indices unveiling transit service effectiveness that were not possible before. Findings from this research are expected to lead to methodological advancements in data-driven approaches in public transit studies, and help transform the transit management mindset into a model of data-driven, sensing, and smart urban systems

Guide pin holes for blind mating of connectors

Portable electronics have a charging port to which a user can connect a power cable. In situations where a large number of devices are being charged, e.g., at airports, schools, etc., a clutch of cables forms near the charging station that causes visual clutter and inconvenience. Some devices have a female charging port that can be mated with a male charger without a cable, e.g., by visually aligning the male and female connectors before mating. However, when a user is visually impaired, or where there are several simultaneous devices being charged, the mating of connectors is a difficult task that can cause frustration and connector damage. This disclosure describes techniques that place a guide pin hole next to the charging port of a device. The charger has a male element that fits into the guide pin hole. The guide pin hole makes it convenient to slide a device into a charger

Inter-phase feedbacks in construction projects

Understanding diverse performance trajectories of projects is of interest to operations researchers and practitioners. Interactions between multiple phases of a project are commonly assumed to be important in project dynamics, yet the strength of these feedback mechanisms has not been rigorously evaluated. In this study we use data from 15 construction projects to estimate the feedbacks between design and construction phases. The estimated factors reveal that undiscovered design rework diminishes construction quality and production rate significantly and construction completion speeds up the detection of undiscovered design rework. Together, these feedbacks can explain as much as 20% of variability in overall project costs. Comparison of model predictions with a separate set of 15 projects shows good predictive power for cost and schedule outcomes and their uncertainty. The estimation and prediction framework offers a template for using data from multiple cases to estimate both case-specific and industry-wide parameters of project models, and for leveraging those estimates for project planning