VictorJuiz/thesis huggingface dataset:
Fast Algorithms for Transmission Switching with High Performance Computing

There has been multiple national directives to enhance the economic operations of the power transmission system and promote the eﬃcient use of the current grid conﬁguration and resources. Transmission switching has been proposed as a new control method for various beneﬁts, including improving the economic eﬃciency and meeting the reliability requirements. Optimal Transmission Switching model has been introduced to ﬁnd an optimal generation dispatch and network topology to minimize the dispatch cost. Binary decision variables are used to denote the control of the transmission lines, which makes the model a nonlinear program. It suﬀers from curse of dimensionality and faces serious computational challenges./nTo tackle the computational challenge of the Optimal Transmission Switching model, we propose three greedy algorithms in which only one line is switched at an iteration. In each iteration we solve a series of linear programs or smaller MIP programs, which can be implemented in parallel with the aid of high performance computing. The ﬁrst algorithm enumerates all the possible line switching actions. The second algorithm produces a priority list ranking lines by a sensitivity factor based on dual criterion, and evaluate lines starting from the top of the list. The last one divides lines into small groups and consider each group at one time. We test the algorithms on the IEEE 118-Bus network and the FERC 13,867-Bus network which is representative of PJM Regional Transmission Organization. The results show that all three proposed algorithms result in cost reduction close to the best known optimal within a reasonable timeframe for IEEE network. For the FERC network which can not be solved directly by the OTS, the ﬁrst two greedy algorithms are able to produce switching sequences which result in considerable cost reduction./nFurthermore we propose three machine learning based methods to produce priority lists for ranking possible line switching actions to facilitate faster searching. The algorithms take in the parameters from network status and network conﬁguration to produce a standardized score representing the possible cost reduction of the line switching action. The numerical results on IEEE network and FERC network are presented. We evaluate the eﬀectiveness of the priority lists based on dual criterion and machine learning methods by both regression analysis and comparison with random lists./nBased on the algorithms in literature and those we develop, we propose an algorithm selection method which selects the algorithm to optimize the cost improvement at each iteration. They show improvement in the cost reduction compared to the individual algorithms, especially for the FERC network.

Advisor: Oren, Shmuel S
How does learning shape us? Exploring mechanisms of plasticity in cognition

How do learning experiences shape our brain and cognitive skills? While there has been extensive evidence showing that learning experiences do have an impact on cognitive performance across the lifespan, we are still understanding how those changes take place. My dissertation work has sought to characterize the mechanisms that underlie improved performance resulting from different learning experiences. In Chapter 1, the general introduction, I present relevant background literature to provide a context for the rest of the chapters in my dissertation. In Chapter 2, I provide an overview of the type of changes to the functional connectivity of brain networks that result from sensory, motor, and cognitive learning experiences. The evidence from that body of work leads us to conclude that learning changes the way brain networks interact, such that BOLD fluctuations within the network engaged in the learning experience become more tightly synchronized at rest. Having established evidence for experience-dependent brain plasticity, we turn our attention to Chapter 3, where I examine the cognitive impact of broad learning experiences across five decades of life. I present findings suggesting that education has a greater influence on performance on assessments that measure more complex skills, like reasoning. Educational attainment also modulates ages of peak cognitive functioning, while it has little bearing on novel learning. Given that Chapter 2 and 3 provide evidence of the impact of learning on the brain and behavior, we then probe mechanisms of change. In Chapter 4, we present unified findings from a broad literature to explain how various eyetracking measures provide a relatively simple method to characterize cognitive mechanisms that support change as a result of maturation, which can be applied to study changes that occur as a result of learning. Using this eyetracking methodology, in Chapter 5 and 6, I provide empirical evidence about the mechanisms that support improvements in reasoning performance resulting from a real-world learning experience. We find that the young adults became more proficient at encoding, maintaining, and integrating visual relations after only a relatively short learning experience that emphasized reasoning about verbal relations and rules. Collectively, my dissertation work provides mechanistic insights about how learning experiences shape higher-level cognition.

Advisor: Bunge, Silvia A
Essays in Development Economics and Political Economy

In the first chapter, I discuss a study that uses experimental variation in a door-to-door information campaign to test for polarization in policy choice across the electorate in Turkey. The campaign took place before a landmark referendum that was initiated by the incumbent party in Turkey after the chaotic coup attempt in July 2016. The referendum was on institutional changes to weaken constraints on the executive branch in Turkey. I designed the implementation of the door-to-door campaign as a randomized experiment. In this campaign, the opposition party gave uniform information on poor economic performance and increased terrorist activity under the incumbent's leadership to more than 130,000 voters. I show that voters, despite being exposed to the same campaign, diverged further in their vote choice on aggregate, leading to a significant increase in political polarization. This is a unique result where polarization in vote choice at the aggregate level is driven by differences in reaction to the same door-to-door campaign./nIn the second chapter, I investigate electoral competition in an illiberal democracy. To promote their electoral and policy goals, elected officials make investments in a ``home style" -- a strategy to learn about their voters and select their public platform accordingly. I consider a framework of home style grounded in perception: politicians better able to accurately assess voter preferences will more closely tailor their communications to those preferences. I conducted interviews with Members of Parliament establishing that the majority party regularly conducts polls to assess voter preferences while the opposition party does not. I then analyze nearly a million MPs’ tweets and find that the majority party is more likely to communicate on the issues of most importance to their constituents than the opposition. Finally, I conduct a quasi-experiment and find that providing opposition MPs with polling increases their likelihood to communicate about their constituents’ most important issues while there is no effect among majority MPs. This result supports the qualitative evidence that the incumbent invests more in learning about voters than the opposition./nThe third chapter, co-authored with Marshall Burke, Felipe Gonzalez, Solomon Hsiang, and Edward Miguel, studies whether economic or non-economic factors better explain the well-established relationship between temperature and violence in a unique context where intergroup killings by drug-trafficking organizations (DTOs) and “normal” interpersonal homicides are separately documented. A constellation of evidence, including the limited influence of a cash transfer program as well as comparison with both non-violent DTO crime and suicides, indicate that economic factors only partially explain the observed relationship between temperature and violence. We argue that noneconomic psychological and physiological factors that are affected by temperature, modeled here as a “taste for violence,” likely play an important role in causing both interpersonal and intergroup violence.

Advisor: Sadoulet, Elisabeth
Resolving Soft Material Crystallinity through Scanning Transmission Electron Nanodiffraction

A method for imaging the semi-crystalline structure of organic, electrically conduct- ing molecular thin films using scanning nanodiffraction transmission electron microscopy (4D-STEM) is developed, with a maximum achieved resolution of 5-10 nm, depending on the material analyzed. The changes in local nanocrystalline structure of the polymer thin films under study - regioregular Poly(3-hexyl-thiophene-2,5-diyl), the small molecule 7,7’- (4,4 - bis(2 - ethylhexyl) - 4H - silolo[3,2-b:4, 5-b’] dithiophene - 2,6 - diyl) bis(6 - flu- oro - 4 - (5’- hexyl[2,2’-bithiophen] - 5 - yl)benzo[c][1,2,5] - thiadiazole), abbreviated as p- DTS(FBTTh2 )2 or T1, and Poly[2,5-bis(3-tetradecylthiophen-2-yl)thieno[3,2-b ]thiophene], abbreviated as PBTTT - with processing conditions, such as solvent addition and annealing, are characterized and visualized. The methods presented show spatially resolved features such as overlapping grains and nematic liquid crystal character that have not been directly imaged before, and help remove ambiguities in X-ray and other techniques that have been thus far used to characterize these materials./nThe method is first applied to polyethylene and P3HT samples to demonstrate the via- bility of the electron transmission technique on soft materials and determine its limitations. A resolution of 5 nm is achieved on P3HT. The method is subsequently used to visualize the changes in crystal structure of T1 when treated with 1,8-diiodooctane (DIO), and then on PBTTT to characterize morphological changes upon annealing. It is found that for T1, while the untreated samples exhibited a liquid-crystal-like structure with crystalline orientations varying smoothly over all possible rotations, the addition of a co-solvent induces partial segmentation of the structure characterized by the emergence of sharp grain boundaries and overlapping domains with unrelated orientations. In the case of PBTTT, the crystalline character of the nematic liquid crystal phase increases upon annealing. These results demon- strate how scanning electron nanobeam diffraction can provide a new level of insight into the structure of functional organic solids, and show how structure-property relationships can be visualized in organic systems using nanoscale electron microscopy techniques previously only available for hard materials such as metals and ceramics.

Advisor: Minor, Andrew
Emerging Power Multilateralism: A New Generation of Intergovernmental Organizations and Implications for the Global Sustainable Development Regime

The purpose of this dissertation research is twofold: to explain why and how emerging great and middle power countries established new intergovernmental organizations (IGOs) and to consider implications for changing global norms and practices of sustainable development. Rather than focusing on either the international context or domestic motivations, this study explains the phenomena of IGO establishments by incorporating factors and strategies at both levels. This study offers two arguments: that emerging great and middle power countries created IGOs as a response to a combination of different international and domestic factors, and that, contrary to initial speculations, this array of new IGOs poses little threat to the existing norms and practices of pre-existing institutions. In this study, three detailed case studies on the Asian Infrastructure Development Bank, the New Development Bank, and the Global Green Growth Institute and their comparative assessment are presented. The findings from this research point to the broader debate on international relations theory investigating the utility and impacts of international cooperation and institutions, international environmental governance, and the effectiveness of international regime complexity and fragmentation. The urgency of developmental and climate challenges, as well as the lasting impact of development projects and policy implementation, makes this research project ever more relevant.

Advisor: O'Neill, Katherine
Statistics meets Optimization: Computational guarantees for statistical learning algorithms

Modern technological advances have prompted massive scale data collection in many/nmodern fields such as artificial intelligence, and traditional sciences alike. This has led to/nan increasing need for scalable machine learning algorithms and statistical methods to draw/nconclusions about the world. In all data-driven procedures, the data scientist faces the/nfollowing fundamental questions: How should I design the learning algorithm and how long/nshould I run it? Which samples should I collect for training and how many are sufficient to/ngeneralize conclusions to unseen data? These questions relate to statistical and computational properties of both the data and the algorithm. This thesis explores their role in the areas of non-convex optimization, non-parametric estimation, active learning and multiple testing./nIn the first part, we provide insights of different flavor concerning the/ninterplay between statistical and computational properties of first-order type methods on/ncommon estimation procedures. The expectation-maximization (EM) algorithm estimates/nparameters of a latent variable model by running a first-order type method on a non-convex/nlandscape. We identify and characterize a general class of Hidden Markov Models for which/nlinear convergence of EM to a statistically optimal point is provable for a large initialization/nradius. For non-parametric estimation problems, functional gradient descent type (also/ncalled boosting) algorithms are used to estimate the best fit in infinite dimensional function/nspaces. We develop a new proof technique showing that early stopping the algorithm instead/nmay also yield an optimal estimator without explicit regularization. In fact, the same/nkey quantities (localized complexities) are underlying both traditional penalty-based and/nalgorithmic regularization./nIn the second part of the thesis, we explore how data collected adaptively with a constantly/nupdated estimation can lead to signifcant reduction in sample complexity for multiple/nhypothesis testing problems. In particular, we show how adaptive strategies can be used/nto simultaneously control the false discovery rate over multiple tests and return the best/nalternative (among many) for each test with optimal sample complexity in an online manner.

Advisor: Wainwright, Martin J
Land Use in Renewable Energy Planning

All forms of energy generation can have intensive or extensive land use requirements, causing habitat and biodiversity loss in sensitive and diverse ecosystems globally. With the rapid transformation and growth of the energy sector in countries worldwide, understanding the impacts of past practices and charting the trajectory of future development projects is imperative for preventing negative environmental consequences. This dissertation contributes modeling strategies for integrating environmental impacts in renewable energy planning processes and spatially-explicit empirical methods for identifying and quantifying land use and land cover impacts related to renewable energy development./nTo explore land use and energy conflicts in a jurisdiction that is in the midst of a large-scale low-carbon energy transition, I ask the following: (1) is it possible to meet California's ambitious renewable energy targets without using high conservation-value land? (2) what are the system costs of low-impact renewable energy development? I find that while trade-offs between conservation value and renewable resource quality exist, restricting development to low-impact land is not only possible, but incurs only negligible economic cost increases. Given this possibility, I use California as a case study to identify decision-making opportunities in energy planning processes for integrating conservation and land use values and avoiding conservation-climate conflicts./nExtending the spatial methods developed for California to countries in Africa that are planning renewable energy expansion, I ask, what is the potential for low-environmental-impact, socially-responsible, and cost-effective development of wind and solar energy in emerging economies in Africa? Using a multi-criteria analysis approach, I find that "no-regrets'' options---specifically areas that are low-cost, low-environmental impact, and highly accessible--exist such that significant fractions of demand can be quickly served with low-impact resources without large additional cost./nDespite the magnitude and pace of hydropower expansion in highly biodiverse aquatic and terrestrial ecosystems in Southeast Asia, Africa, and Latin America, the potential indirect land use and land cover change resulting from hydropower development is poorly understood. To fill this gap, I ask, what are the indirect deforestation and land use impacts of utility-scale hydropower development in the Brazilian Amazon? Do siting choices and pre-existing land use and land cover affect the extent of the impact? Using scalable remote sensing and spatial econometric methods for causal inference, I find a 11-59% increase in indirect deforestation due to hydropower development. These findings can contribute to estimates of potential future terrestrial impacts from the hundreds of hydropower plants planned and proposed in relatively intact areas of the Brazilian Amazon.

Advisor: Torn, Margaret
Advancing comfort technology and analytics to personalize thermal experience in the built environment

Nearly 60% of global energy consumption in buildings is used for space heating and cooling to provide occupant comfort. Yet, a large portion of occupants are dissatisfied with the buildings’ thermal environment. There are many reasons for thermal dissatisfaction in buildings, but a fundamental cause is the current practice of delivering uniform thermal conditions based on universal rules, without accounting for individual differences in comfort requirements. To address these issues, a growing body of research has emerged to better reflect individual’ comfort requirements. This dissertation contributes to this research by providing the following primary innovations: 1) Internet-connected personal comfort system (PCS) and 2) personal comfort models that can help to deliver personalized comfort experiences in occupied spaces. In particular, I developed and field-tested the new capabilities of PCS (data reporting, wireless connectivity) that could support individualized learning and coordinated controls with other building systems. I also proposed a new framework for thermal comfort modeling – personal comfort models that can predict individuals’ thermal comfort, instead of the average response of a large population, using Internet of Things and machine learning. As a practical use case, I developed a set of personal comfort models using the PCS field study data to demonstrate how the proposed framework can be implemented. The results showed that personal comfort models produced superior accuracy over conventional comfort models (PMV, adaptive) and that PCS heating and cooling control behavior was a strong predictor of individuals’ thermal preference and could be used as an individualized comfort feedback for HVAC controls. The results of this dissertation showed a synergistic effect between PCS and personal comfort models that could enable occupant-centric comfort management in buildings.

Advisor: Brager, Gail
Making Modern American Citizenship: Citizens, Aliens, and Rights, 1865-1965

American citizenship and the rights of U.S. citizenship became modern from the time of the Civil War until the Civil Rights era. Voting became the quintessential right of American citizenship as marginalized citizens won suffrage rights and noncitizen men lost the franchise in nearly two dozen states and territories. Conversely, nativist-inspired policies that counted only citizens as part of the population for redistricting purposes were gradually rescinded in states where they had long operated. At the same time, many forms of publicly funded blue-collar work and access to professional licenses were increasingly restricted to U.S. citizens. And the liminal legal status of hundreds of thousands of marital expatriates (U.S.-born women who had lost citizenship upon marrying noncitizen men) forced judges and immigration officers to interpret and administer the boundaries and meaning of increasingly exclusive citizenship rights./nThis dissertation explores how U.S. citizenship and restrictive “rights of citizenship” were claimed, debated, learned, and experienced by citizens and noncitizens alike from 1865 to 1965. Part I, “Consolidating the Political Rights of Citizenship,” examines state constitutional and legislative debates over alien suffrage and the inclusion of noncitizens in apportionment policies. It demonstrates the growing power of “citizen only” arguments and documents how these debates transformed the rules governing membership and participation in the polity. Part II, “Claiming, Administering, and Experiencing Employment as a Right of Citizenship,” examines state legislative and licensing records to identify patterns in laws restricting noncitizens’ access to work. These policies, which disproportionately harmed and targeted women and nonwhite immigrants, led to heightened identification requirements and made exclusive economic “rights of citizenship” more powerful, recognizable, and tangible in American life./nPart III, “The Ascendance of the Rights of Citizenship,” analyzes how marital expatriates experienced and contested their alienage from the 1920s to the 1950s. It also explores how they were declared to be “citizens without the rights of citizenship” by federal immigration authorities in 1940. The courts increasingly struck this interpretation down, reasoning that citizenship status could not be separated from citizenship rights. While these rulings did not ensure that citizens possessed equal de facto or even de jure rights, they did represent a crucial transformation integral to the modern era of American citizenship: a belief that “rights of citizenship” exist, matter, and are – or at the very least ought to be – definable.

Advisor: Einhorn, Robin