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Global Optimization Algorithms for Image Registration and Clustering
Zheng, Cuicui New Jersey Institute of Technology ProQuest Disser 2020 해외박사(DDOD)
Global optimization is a classical problem of finding the minimum or maximum value of an objective function. It has applications in many areas, such as biological image analysis, chemistry, mechanical engineering, financial analysis, deep learning and image processing. For practical applications, it is important to understand the efficiency of global optimization algorithms. This dissertation develops and analyzes some new global optimization algorithms and applies them to practical problems, mainly for image registration and data clustering.First, the dissertation presents a new global optimization algorithm which approximates the optimum using only function values. The basic idea is to use the points at which the function has been evaluated to decompose the domain into a collection of hyper-rectangles. At each step of the algorithm, it chooses a hyper-rectangle according to a certain criterion and the next function evaluation is at the center of the hyper-rectangle. The dissertation includes a proof that the algorithm converges to the global optimum as the number of function evaluations goes to infinity, and also establishes the convergence rate. Standard test functions are used to experimentally evaluate the algorithm. The second part focuses on applying algorithms from the first part to solve some practical problems. Image processing tasks often require optimizing over some set of parameters. In the image registration problem, one attempts to determine the best transformation for aligning similar images. Such problems typically require minimizing a dissimilarity measure with multiple local minima. The dissertation describes a global optimization algorithm and applies it to the problem of identifying the best transformation for aligning two images. Global optimization algorithms can also be applied to the data clustering problem. The basic purpose of clustering is to categorize data into different groups by their similarity. The objective cost functions for clustering usually are non-convex. $k$-means is a popular algorithm which can find local optima quickly but may not obtain global optima. The different starting points for $k$-means can output different local optima. This dissertation describes a global optimization algorithm for approximating the global minimum of the clustering problem. The third part of the dissertation presents variations of the proposed algorithm that work with different assumptions on the available information, including a version that uses derivatives.
Zipori, Esther New Jersey Institute of Technology ProQuest Disser 2022 해외박사(DDOD)
This dissertation is concerned with the present and future of urban streets in the United States. The goal is to document and analyze current visions, policies, and strategies related to the form and use of American urban streets. The dissertation examines current mobility trends and offers a framework for organizing visions of the future of urban streets, evaluating them through three lenses: safety, comfort, and delight, assessing physical conditions in accordance with livability standards toward sustainable development. At the same time, it demonstrates the way 12 scenarios (NACTO Blueprint for Autonomous Urbanism, Sidewalk Labs: Quayside Project, Public Square by FXCollaborative, AIANY Future Street, The National Complete Street Coalition, Vision Zero, Smart Columbus, Waymo by Alphabet, The Hyperloop, Tesla “Autopilot,” Ford City of Tomorrow, SOM City of Tomorrow) have intentionally or unintentionally influenced contemporary use of American urban streets. Ultimately, the study shows that while sustainable alternative mobilities continue to emerge, the dominance of the automobility system has led to a stagnation of sustainable urban street development in the United States.
In Partnership? Pedestrian Plazas in New York City
Topal, Hanife Vardi New Jersey Institute of Technology ProQuest Disser 2020 해외박사(DDOD)
Traditional public spaces —such as public parks, streets, and public squares—have long been part of the urban landscape. In today’s congested cities, however, creating such public spaces is difficult because they require capital investment, vacant land, and ongoing maintenance. Possibly in response to these obstacles, new types of urban public spaces have emerged.Pedestrian plazas, one of these new types, is the topic of this research, with a focus on the New York City Plaza Program, which was the first such program in the U.S. For this research, the design, management, and use characteristics of five completed pedestrian plazas were examined, with attention also given to the partnerships behind the creation and maintenance of these plazas. The role the partners played in the plaza program was also investigated to understand its impact on the design, management, maintenance, and use of pedestrian plazas. The five case study plazas are located in neighborhoods without sufficient public space, as determined by the Department of Transportation, which runs the program. The following data collection strategies were used: site observations, user surveys, and interviews with government officials and sponsor partners. This research demonstrates that although pedestrian plazas are relatively small and are located immediately adjacent to roadways, they fulfill an important role in urban neighborhoods that otherwise lack sufficient public space for recreation. The type and diversity of activities vary between the plazas, depending on features of their design, maintenance, and management. The findings suggest that partnerships between the City and community organizations in the New York City Plaza Program play a prominent role in shaping design, maintenance, and management strategies, which affect their use. Neighborhood residents use the case study pedestrian plazas in a variety of ways, including for gathering with friends and family, people-watching, chatting, eating and drinking, and attending programmed events. Some plazas are typically frequented by the same people on a daily basis and become popular gathering places whereas other plazas are more often used for shorter periods of time for eating lunch, meeting someone, and taking a brief rest.