1. Under the Guise of Safety, EdTech Software Surveils [2019] Online
An investigation into the privacy concerns with popular edtech "safety management" software.
An investigation into the privacy concerns with popular edtech "safety management" software.
2. A Break in the Cloud: Finding the Local in the Global Internet [2018] Online
The Internet has radically changed every mode of production, distribution, and consumption in modern life, granting global access to information transcending time and space. However, the physical infrastructure that enables the Internet is often overlooked, due to the virtual and intangible nature of Internet connection. This disconnect between the digital and the physical is captured by the popular buzzword - “the cloud” - a metaphor that abstracts away the vast, energy-guzzling tracts of data server farms kept hidden in corporate secrecy. This thesis seeks to make “the cloud” visible and concrete, and in doing so, zooms in from the Internet’s “global village”1 back to the physical realities of Internet infrastructure embedded within local communities. Through an analysis and synthesis of technical papers, corporate marketing, policy reports, and maps, it situates the “global” nature of the cloud within national and local politics and communities. In addition, through a case study of Google’s first data center in The Dalles, Oregon, and its intimate relationship with a community-piloted municipal fiber network - QLife Network - this thesis brings local community needs and negotiations in conversation with the global corporate order of digital technologies. The discussion concludes with a proposed framework for a community-oriented approach to accessing the global Internet, urging for visibility through new media art and community-based Internet infrastructure investment. Recognizing the realities of local within a global Internet makes the first necessary step in bringing the cloud out of its technological black box, and in short, finding the break in the cloud.
The Internet has radically changed every mode of production, distribution, and consumption in modern life, granting global access to information transcending time and space. However, the physical infrastructure that enables the Internet is often overlooked, due to the virtual and intangible nature of Internet connection. This disconnect between the digital and the physical is captured by the popular buzzword - “the cloud” - a metaphor that abstracts away the vast, energy-guzzling tracts of data server farms kept hidden in corporate secrecy. This thesis seeks to make “the cloud” visible and concrete, and in doing so, zooms in from the Internet’s “global village”1 back to the physical realities of Internet infrastructure embedded within local communities. Through an analysis and synthesis of technical papers, corporate marketing, policy reports, and maps, it situates the “global” nature of the cloud within national and local politics and communities. In addition, through a case study of Google’s first data center in The Dalles, Oregon, and its intimate relationship with a community-piloted municipal fiber network - QLife Network - this thesis brings local community needs and negotiations in conversation with the global corporate order of digital technologies. The discussion concludes with a proposed framework for a community-oriented approach to accessing the global Internet, urging for visibility through new media art and community-based Internet infrastructure investment. Recognizing the realities of local within a global Internet makes the first necessary step in bringing the cloud out of its technological black box, and in short, finding the break in the cloud.
3. A forward genetic screen identifies new host factors influencing bacteriophage lambda's lysis-lysogeny decision [2018] Online
- Collection
- Undergraduate Theses, School of Engineering
In order to survive, organisms must integrate internal and external signals via complex signaling pathways to intelligently navigate their environment. Bacteriophage lambda has long been a classic model for understanding such pathways, and how they allow cells to effect changes in physiology in order to adapt to varying circumstances. When infecting its host Escherichia coli, phage lambda may either make more viruses (lysis), or integrate itself into the host genome (lysogeny). To better understand the extent to which host physiology influences the lysis-lysogeny decision, I performed a forward genetic screen to identify genes whose deletions bias the infected cell towards lysis or lysogeny. This screen revealed numerous host-encoded genes linked to the lysis-lysogeny decision, including transcription factors and genes in metabolic pathways. These results demonstrate previously unknown links between host physiology and viral decision-making, shedding new light on this classic model system.
In order to survive, organisms must integrate internal and external signals via complex signaling pathways to intelligently navigate their environment. Bacteriophage lambda has long been a classic model for understanding such pathways, and how they allow cells to effect changes in physiology in order to adapt to varying circumstances. When infecting its host Escherichia coli, phage lambda may either make more viruses (lysis), or integrate itself into the host genome (lysogeny). To better understand the extent to which host physiology influences the lysis-lysogeny decision, I performed a forward genetic screen to identify genes whose deletions bias the infected cell towards lysis or lysogeny. This screen revealed numerous host-encoded genes linked to the lysis-lysogeny decision, including transcription factors and genes in metabolic pathways. These results demonstrate previously unknown links between host physiology and viral decision-making, shedding new light on this classic model system.
4. A la protección de la salud: Indigenous status, insurance affiliation, and prenatal care quality in Oaxaca, Mexico [2018] Online
- Collection
- Stanford University, Fisher Family Honors Program in Democracy, Development, and the Rule of Law
Despite the introduction of Seguro Popular, a universal form of health insurance, in the early 2000s, indigenous women in Mexico continue to exhibit disparately poor maternal health outcomes relative to non-indigenous women. This difference has typically been attributed to factors including poverty, rurality, and lack of care adherence, but little work has addressed the role of prenatal care quality in explaining this trend. Similarly, though Seguro Popular has assisted in equalizing the proportion of indigenous and non-indigenous women who receive prenatal care, few studies have compared the substantive quality of care provided to these two groups. Using data from ENADID 2014, this study characterizes the relationship between indigenous status, insurance affiliation, and prenatal care quality, focusing specifically on the state of Oaxaca. After developing an index of prenatal care quality consistent with both international norms and local patient care preferences, I demonstrate significantly worse prenatal care quality among indigenous women across every measure of quality. Even after controls for socioeconomic marginalization, linear and logistic regression models of prenatal care demonstrate that indigenous women received 0.642 fewer prenatal visits (p < 0.05), exhibited reduced odds of receiving prenatal care in the first trimester (OR 0.5929, p < 0.05), received 0.3515 fewer interventions over the course of pregnancy (out of a checklist of 11 essential procedures, p < 0.05), had reduced odds of receiving prenatal care from a doctor (OR 0.3969, p < 0.01), received poorer information quality of care (0.2284 points fewer on a 3-point scale, p < 0.05), and received poorer interpersonal quality of care (0.3791 points fewer on a 3-point scale, p < 0.01). Regression models stratified by indigenous status suggest that these indigenous status- based inequalities are concentrated among Seguro Popular affiliates. The signifiant correlation between indigenous status and poor care quality, independent of socioeconomic marginalization, suggests insufficient cross-cultural communication and implicit discrimination as potential sources of this quality difference. In addition to demonstrating continued indigenous care access inequality in Oaxaca even after the implementation of Seguro Popular, these results suggest discrepancies in access to quality prenatal care as a possible explanation of Mexico’s indigenous maternal health disparities.
Despite the introduction of Seguro Popular, a universal form of health insurance, in the early 2000s, indigenous women in Mexico continue to exhibit disparately poor maternal health outcomes relative to non-indigenous women. This difference has typically been attributed to factors including poverty, rurality, and lack of care adherence, but little work has addressed the role of prenatal care quality in explaining this trend. Similarly, though Seguro Popular has assisted in equalizing the proportion of indigenous and non-indigenous women who receive prenatal care, few studies have compared the substantive quality of care provided to these two groups. Using data from ENADID 2014, this study characterizes the relationship between indigenous status, insurance affiliation, and prenatal care quality, focusing specifically on the state of Oaxaca. After developing an index of prenatal care quality consistent with both international norms and local patient care preferences, I demonstrate significantly worse prenatal care quality among indigenous women across every measure of quality. Even after controls for socioeconomic marginalization, linear and logistic regression models of prenatal care demonstrate that indigenous women received 0.642 fewer prenatal visits (p < 0.05), exhibited reduced odds of receiving prenatal care in the first trimester (OR 0.5929, p < 0.05), received 0.3515 fewer interventions over the course of pregnancy (out of a checklist of 11 essential procedures, p < 0.05), had reduced odds of receiving prenatal care from a doctor (OR 0.3969, p < 0.01), received poorer information quality of care (0.2284 points fewer on a 3-point scale, p < 0.05), and received poorer interpersonal quality of care (0.3791 points fewer on a 3-point scale, p < 0.01). Regression models stratified by indigenous status suggest that these indigenous status- based inequalities are concentrated among Seguro Popular affiliates. The signifiant correlation between indigenous status and poor care quality, independent of socioeconomic marginalization, suggests insufficient cross-cultural communication and implicit discrimination as potential sources of this quality difference. In addition to demonstrating continued indigenous care access inequality in Oaxaca even after the implementation of Seguro Popular, these results suggest discrepancies in access to quality prenatal care as a possible explanation of Mexico’s indigenous maternal health disparities.
5. A Life-cycle Assessment of Canadian-produced Liquefied Natural Gas for Consumption in China [2018] Online
- Collection
- Master's Theses, Stanford Earth
Natural gas consumption has increased in recent decades due to low prices and emissions benefits over coal. The greenhouse gas (GHG) benefits of natural gas over coal require a low upstream emissions profile, in particular with low fugitive emissions of methane. Furthermore, natural gas is unlike oil in that it is highly transport-constrained. Liquefied natural gas (LNG) allows for overseas shipping but comes at significant economic and energetic costs. We worked with a Canadian liquids-rich gas producer to better understand upstream fugitive emissions and assess their efficacy of leak detection and repair (LDAR) programs. We model emissions from their operations and perform life-cycle assessment (LCA) of a hypothetical scenario where they produce 1 billion cubic feet per day of LNG in coastal British Columbia, for consumption in Shenzhen, China. We determine the life- cycle GHG and criteria air pollutant emissions associated with such a project.
We find that the LDAR surveys have resulted in decreased number of emissions points and decreased site-wide emissions. Leaks that were fixed from LDAR surveys tended to remain fixed and did not reappear. Likewise, leaks that were not fixed tended to persist and did not go away on their own, indicating that leak persistence is very high. Consequently, LDAR surveys are resulting in emissions reductions, as long as detected leaks are fixed. Repeat LDAR surveys regularly found new emission sources, even without significant site changes occurring, supporting the idea that LDAR surveys must be done regularly to find and fix new emission sources that arise from equipment failure or breakdown.
We find that Canada-to-China LNG will result in fewer life-cycle GHG emissions than the same power generated using coal in Asian markets. Studies have estimated Chinese coal power emissions to be anywhere from 868 to 975 g CO2e/kWh, nearly double our results of 408.2 to 547.9 g CO2e/kWh. Our results are lower than prior studies due to low upstream emissions and more efficient LNG production assumptions. LCA studies of LNG have focused on upstream and liquefaction stages, but our work makes it clear that total emissions are dominated by end-use emissions. When considering the climate benefits and drawbacks of LNG, it is critical to understand how the gas will be used.
Natural gas consumption has increased in recent decades due to low prices and emissions benefits over coal. The greenhouse gas (GHG) benefits of natural gas over coal require a low upstream emissions profile, in particular with low fugitive emissions of methane. Furthermore, natural gas is unlike oil in that it is highly transport-constrained. Liquefied natural gas (LNG) allows for overseas shipping but comes at significant economic and energetic costs. We worked with a Canadian liquids-rich gas producer to better understand upstream fugitive emissions and assess their efficacy of leak detection and repair (LDAR) programs. We model emissions from their operations and perform life-cycle assessment (LCA) of a hypothetical scenario where they produce 1 billion cubic feet per day of LNG in coastal British Columbia, for consumption in Shenzhen, China. We determine the life- cycle GHG and criteria air pollutant emissions associated with such a project.
We find that the LDAR surveys have resulted in decreased number of emissions points and decreased site-wide emissions. Leaks that were fixed from LDAR surveys tended to remain fixed and did not reappear. Likewise, leaks that were not fixed tended to persist and did not go away on their own, indicating that leak persistence is very high. Consequently, LDAR surveys are resulting in emissions reductions, as long as detected leaks are fixed. Repeat LDAR surveys regularly found new emission sources, even without significant site changes occurring, supporting the idea that LDAR surveys must be done regularly to find and fix new emission sources that arise from equipment failure or breakdown.
We find that Canada-to-China LNG will result in fewer life-cycle GHG emissions than the same power generated using coal in Asian markets. Studies have estimated Chinese coal power emissions to be anywhere from 868 to 975 g CO2e/kWh, nearly double our results of 408.2 to 547.9 g CO2e/kWh. Our results are lower than prior studies due to low upstream emissions and more efficient LNG production assumptions. LCA studies of LNG have focused on upstream and liquefaction stages, but our work makes it clear that total emissions are dominated by end-use emissions. When considering the climate benefits and drawbacks of LNG, it is critical to understand how the gas will be used.
6. A Literature Review Promoting Counterinsurgency Cultural Training in Virtual Reality [2018] Online
Counterinsurgency cultural training (COIN-CT) could be augmented by adapting existing 3D desktop educational modules to virtual reality (VR). The following literature review synthesizes research on VR as a medium for training, VR as a medium for perspective taking, and current COIN-CT offerings to promote future empirical studies on VR COIN-CT solutions. This paper examines how VR features such as social presence, body transfer, and embodied cognition can lead to improved learning transfer. This paper also reviews current COIN-CT offerings in depth, identifies how VR could enhance existing options, and addresses potential challenges facing widespread adoption of VR COIN-CT.
Counterinsurgency cultural training (COIN-CT) could be augmented by adapting existing 3D desktop educational modules to virtual reality (VR). The following literature review synthesizes research on VR as a medium for training, VR as a medium for perspective taking, and current COIN-CT offerings to promote future empirical studies on VR COIN-CT solutions. This paper examines how VR features such as social presence, body transfer, and embodied cognition can lead to improved learning transfer. This paper also reviews current COIN-CT offerings in depth, identifies how VR could enhance existing options, and addresses potential challenges facing widespread adoption of VR COIN-CT.
7. A New Era of Personalized Politics: The 2016 Twitter Campaign [2018] Online
This study looked at personalization during the 2016 presidential election. The ubiquity of social media and the unique features of Twitter enable new forms of personalization to emerge during political campaigns. This research added to the growing body of literature in political communication by taking a multifaceted approach to personalized politics in assessing content, interactivity, and language. The findings in this study confirmed trends from previous research in that politicians are posting more content relating to traditional campaign strategies (agenda setting, mobilization, and criticism) rather than revealing personal information about themselves. However, findings also suggest that personalized communicative practices are indeed emerging on Twitter through use of interactive features and language. This multifaceted analysis allows one to draw inferences to how personalization takes form, to give insights on how political campaigning will continue to evolve on Twitter, and to discuss its implications on the democratic process.
This study looked at personalization during the 2016 presidential election. The ubiquity of social media and the unique features of Twitter enable new forms of personalization to emerge during political campaigns. This research added to the growing body of literature in political communication by taking a multifaceted approach to personalized politics in assessing content, interactivity, and language. The findings in this study confirmed trends from previous research in that politicians are posting more content relating to traditional campaign strategies (agenda setting, mobilization, and criticism) rather than revealing personal information about themselves. However, findings also suggest that personalized communicative practices are indeed emerging on Twitter through use of interactive features and language. This multifaceted analysis allows one to draw inferences to how personalization takes form, to give insights on how political campaigning will continue to evolve on Twitter, and to discuss its implications on the democratic process.
8. A sequence-to-sequence regression of genome-wide chromatin data through adversarial training [2018] Online
- Collection
- Undergraduate Theses, School of Engineering
An Assay for Transposase-Accessible Chromatin using sequencing (ATAC-seq) reveals information about open chromatin regions, individual nucleosomes, and chromatin compaction at nucleotide resolution using only 500 to 50,000 cells. In contrast, Chromatin Immunoprecipitation sequencing (ChIP-seq) requires much more biological samples, typically millions of cells, to detect DNA regions with histone modifications. In this sense, regressing histone ChIP-seq data from less costly ATAC-seq data will help us map missing histone marks and understand epigenomic activity in a more efficient way. This paper investigates how our modified deep adversarial training approach can be used to predict ChIP-seq signal based on ATAC-seq signal. We begin by setting the performance of convolutional neural network (CNN) model as a baseline. We then introduce three modifications to the widely used adversarial network architecture. First, we modify the generator component of the adversarial network so that it takes ATAC-seq signal as input instead of random noise and generates ChIP-seq signal from the ATAC-seq signal. Second, we suggest composite objective function based on two different losses - mean squared error and adversarial loss. Third, we apply one-sided label smoothing, which is essential in stabilizing the adversarial training. The generator trained through our new adversarial training approach reports Pearson correlation of 0.562 with respect to the actual ChIP-seq signal, outperforming the CNN baseline. We also conduct qualitative analysis on how the adversarial training based on the composite objective function helps the model predict ChIP-seq peaks using ATAC-seq signal. To the best of our knowledge, this is the first attempt to tackle epigenomic signal imputation task using deep adversarial training.
An Assay for Transposase-Accessible Chromatin using sequencing (ATAC-seq) reveals information about open chromatin regions, individual nucleosomes, and chromatin compaction at nucleotide resolution using only 500 to 50,000 cells. In contrast, Chromatin Immunoprecipitation sequencing (ChIP-seq) requires much more biological samples, typically millions of cells, to detect DNA regions with histone modifications. In this sense, regressing histone ChIP-seq data from less costly ATAC-seq data will help us map missing histone marks and understand epigenomic activity in a more efficient way. This paper investigates how our modified deep adversarial training approach can be used to predict ChIP-seq signal based on ATAC-seq signal. We begin by setting the performance of convolutional neural network (CNN) model as a baseline. We then introduce three modifications to the widely used adversarial network architecture. First, we modify the generator component of the adversarial network so that it takes ATAC-seq signal as input instead of random noise and generates ChIP-seq signal from the ATAC-seq signal. Second, we suggest composite objective function based on two different losses - mean squared error and adversarial loss. Third, we apply one-sided label smoothing, which is essential in stabilizing the adversarial training. The generator trained through our new adversarial training approach reports Pearson correlation of 0.562 with respect to the actual ChIP-seq signal, outperforming the CNN baseline. We also conduct qualitative analysis on how the adversarial training based on the composite objective function helps the model predict ChIP-seq peaks using ATAC-seq signal. To the best of our knowledge, this is the first attempt to tackle epigenomic signal imputation task using deep adversarial training.
9. A Smoke Removing DC-DC Converter Composed of a Seven Stage Class DE Rectifier and a Class Phi 2 Inverter [2018] Online
- Collection
- Undergraduate Theses, School of Engineering
This thesis presents the design methodology of a miniaturized, portable, and low power electrostatic precipitator (ESP) to reduce indoor air pollution (IAP) from rural cook-stoves. Decreasing the concentration of aerosol particles helps reduce the incidence of respiratory tract infections that can lead to disease and even death. We trace existing technologies and standards to combat IAP in cookstoves, design an ESP that allows precipitation at lower voltages via an electrode design that utilizes sub 5 kV voltages, and explore how rapidly pulsed converters decrease the power consumption of the circuit and increase smoke collection.
This thesis presents the design methodology of a miniaturized, portable, and low power electrostatic precipitator (ESP) to reduce indoor air pollution (IAP) from rural cook-stoves. Decreasing the concentration of aerosol particles helps reduce the incidence of respiratory tract infections that can lead to disease and even death. We trace existing technologies and standards to combat IAP in cookstoves, design an ESP that allows precipitation at lower voltages via an electrode design that utilizes sub 5 kV voltages, and explore how rapidly pulsed converters decrease the power consumption of the circuit and increase smoke collection.
10. A Spectral View of Adversarially Robust Features [2018] Online
- Collection
- Undergraduate Theses, School of Engineering
While great progress has been made in image classification using machine learning, often achieving near-human or even superhuman accuracy on image classification tasks, recent studies have found that image classification models are vulnerable to adversarial attacks: special images crafted to fool the models into mislabeling the picture. In this work, we investigate the problem of creating an adversarially robust feature: a feature f whose value at any point x cannot be changed much by perturbing x slightly. We establish strong connections between adversarially robust features and a natural spectral property of the geometry of the dataset and metric of interest. This connection can be leveraged both to provide robust features and to provide a lower bound on the robustness of any function that has significant variance across the dataset. Finally, we provide empirical evidence that the adversarially robust features yielded via this spectral approach can be fruitfully leveraged to learn a robust (and accurate) model.
While great progress has been made in image classification using machine learning, often achieving near-human or even superhuman accuracy on image classification tasks, recent studies have found that image classification models are vulnerable to adversarial attacks: special images crafted to fool the models into mislabeling the picture. In this work, we investigate the problem of creating an adversarially robust feature: a feature f whose value at any point x cannot be changed much by perturbing x slightly. We establish strong connections between adversarially robust features and a natural spectral property of the geometry of the dataset and metric of interest. This connection can be leveraged both to provide robust features and to provide a lower bound on the robustness of any function that has significant variance across the dataset. Finally, we provide empirical evidence that the adversarially robust features yielded via this spectral approach can be fruitfully leveraged to learn a robust (and accurate) model.
11. "A Stain on Our Souls:" The Darfur Genocide During the Obama Presidency [2018] Online
Since 2003, the Sudanese government and its Arab militia proxies have conducted a genocide against Africans in Darfur, killing roughly 500,000 people and displacing 2.7 million. Public outcry compelled President George W. Bush to take diplomatic measures to end the atrocities, though they achieved little success. In 2007, then-Senator Barack Obama included Darfur on his presidential platform and denounced the genocide as a “stain on our souls.” Nevertheless, during his presidency, Obama not only failed to address the genocide, but also lifted sanctions that had been imposed on Khartoum for its criminal activities in Darfur. This thesis examines why the Obama Administration’s foreign policies in relation to Darfur were so weak. In particular, I focus on four main factors that constrained U.S. action in the region: lack of political salience, South Sudan's creation and subsequent implosion, humanitarian crises elsewhere, and China's and Russia's economic interests in Sudan. By understanding these policy constraints, we might learn how to end this long and violent genocide, as well as other humanitarian conflicts in areas with little national strategic import.
Since 2003, the Sudanese government and its Arab militia proxies have conducted a genocide against Africans in Darfur, killing roughly 500,000 people and displacing 2.7 million. Public outcry compelled President George W. Bush to take diplomatic measures to end the atrocities, though they achieved little success. In 2007, then-Senator Barack Obama included Darfur on his presidential platform and denounced the genocide as a “stain on our souls.” Nevertheless, during his presidency, Obama not only failed to address the genocide, but also lifted sanctions that had been imposed on Khartoum for its criminal activities in Darfur. This thesis examines why the Obama Administration’s foreign policies in relation to Darfur were so weak. In particular, I focus on four main factors that constrained U.S. action in the region: lack of political salience, South Sudan's creation and subsequent implosion, humanitarian crises elsewhere, and China's and Russia's economic interests in Sudan. By understanding these policy constraints, we might learn how to end this long and violent genocide, as well as other humanitarian conflicts in areas with little national strategic import.
12. Absorbing optical antennas [electronic resource] : applications in nanophotonics and combustion [2018] Online
- Book
- 1 online resource.
The promise of optical antennas is the ability to tame the light to behave in ways not achievable using traditional optical components. For example, our results here demonstrate that a careful engineering of optical antennas allow the strong, even perfect, absorption of light in ultra-thin geometries, i.e., geometries much thinner than the wavelength of light. Enabled by geometry-sensitive antenna resonances, this absorption behavior can also be realized for a broad selection of colors. A detailed theoretical analysis of the observed perfect absorption phenomenon reveals the role of incoherently interacting degenerate electric and magnetic resonances in overcoming the well-known absorption limit for infinitesimally thin films. With another set of experiments, we show that strongly absorbed optical energy in aluminum nanoantennas can be used to heat them efficiently above their melting temperature and stimulate an explosive exothermic oxidation reaction called melt-dispersion mechanism. Importantly, we see that engineering the specific geometry of the constituent particles allows an unprecedented control of aluminum ignition, both spectrally and spatially, through the fine tuning of the optical antenna resonances.
The promise of optical antennas is the ability to tame the light to behave in ways not achievable using traditional optical components. For example, our results here demonstrate that a careful engineering of optical antennas allow the strong, even perfect, absorption of light in ultra-thin geometries, i.e., geometries much thinner than the wavelength of light. Enabled by geometry-sensitive antenna resonances, this absorption behavior can also be realized for a broad selection of colors. A detailed theoretical analysis of the observed perfect absorption phenomenon reveals the role of incoherently interacting degenerate electric and magnetic resonances in overcoming the well-known absorption limit for infinitesimally thin films. With another set of experiments, we show that strongly absorbed optical energy in aluminum nanoantennas can be used to heat them efficiently above their melting temperature and stimulate an explosive exothermic oxidation reaction called melt-dispersion mechanism. Importantly, we see that engineering the specific geometry of the constituent particles allows an unprecedented control of aluminum ignition, both spectrally and spatially, through the fine tuning of the optical antenna resonances.
- Book
- 453 pages : illustrations (partly color) ; 23 cm.
14. Activist Responsibility and Social Platforms: Analyzing Billie Jean King's Furtherance of Women's Athletics Through Liberal Feminism [2018] Online
This thesis addresses whether members of disadvantaged social groups who have access to an influential platform bear an activist responsibly for their respective community. In answering this overarching question, this thesis focuses on athletics as the platform in discussion and feminism as the mode of advocacy. Through analysis of hegemonic gender ideology in the American public sphere, brief history of women's athletics to the 1970s, and contention between second-wave feminism and women's athletics in the early years of Title IX, research supports the need for prominent female athletes to further feminist causes. Billie Jean King's relationship with both movements sheds light on the struggles faced by each, and an interview conducted for this thesis reaffirms athletes' unique social affordances and consequent social responsibility.
This thesis addresses whether members of disadvantaged social groups who have access to an influential platform bear an activist responsibly for their respective community. In answering this overarching question, this thesis focuses on athletics as the platform in discussion and feminism as the mode of advocacy. Through analysis of hegemonic gender ideology in the American public sphere, brief history of women's athletics to the 1970s, and contention between second-wave feminism and women's athletics in the early years of Title IX, research supports the need for prominent female athletes to further feminist causes. Billie Jean King's relationship with both movements sheds light on the struggles faced by each, and an interview conducted for this thesis reaffirms athletes' unique social affordances and consequent social responsibility.
15. Adsorption of multifunctional molecules on the Ge(100)-2x1 surface [electronic resource] [2018] Online
- Book
- 1 online resource.
The technological revolution that started with digital electronics more than 50 years ago has pushed the limits of scalability in device fabrication. Device features are currently at the nanometer scale, which requires structures to be built with atomic level accuracy. Advances in nanotechnology have opened up an exciting area of research that allows for molecular level control of device surfaces. Organic molecules can provide the tailorability required to continue the progress of semiconductor technologies. Organic functionalization provides a pathway to control the surface at the molecular level. Fundamental understanding of the adsorption phenomena between organic molecules and the surface is critical to achieve a stable inorganic/organic interface for the creation of hybrid nanostructures. This thesis aims to expand our current toolkit on functionalization to molecules that have multiple functionalities that can react with the surface. The reaction mechanism of these molecules is complex as there are several driving forces that can play a role during adsorption and influence the final reaction products. This thesis covers the adsorption of multifunctional molecules on the Ge(100)-2×1 surface using a combination of experimental and theoretical techniques: Fourier transform infrared spectroscopy, X-ray photoelectron spectroscopy, and density functional theory calculations. We explored the adsorption of four different molecules: 1,2,3-benzenetriol (C6H6O3); 1,3,5-benzenetriol (C6H6O3); 2-hydroxymethyl-1,3-propanediol (C4H10O3); pyrazine (C4H6N2). These are the first reported studies of these molecules on the Ge(100) surface. In order to understand the extent to which molecular geometry affects surface coverage, a detailed comparison of the adsorption of two triol molecules was carried out: 1,3,5-benzenetriol which has a rigid phenyl backbone and 2-hydroxymethyl-1,3-propanediol with a flexible alkyl backbone. DFT results showed that the rigid backbone exhibits a higher degree of strain, which translates to a loss of exothermicity in the reaction coordinate. Experiments showed that the flexibility of the alkyl backbone provides higher rotational degrees of freedom and an enhancement in surface coverage. In order to understand the effect of intermolecular interactions, the adsorption of 1,2,3-benzenetriol was explored. Interestingly, we found that at high coverage, intramolecular hydrogen bonding in singly and dually adsorbate products breaks to form intermolecular hydrogen bonding with a nearby adsorbate, which provides enhanced stabilization of the surface adduct. This additional stabilization may lower the reactivity of unreacted functional groups even if an empty nearby Ge site is available for reaction. The distribution of products resulted in primarily bidentate adsorbates, leaving an unreacted moiety at the surface. We also found evidence of coverage and temperature effects on adsorbed pyrazine molecules on the Ge surface. It was observed that this molecule adsorbs on Ge through both carbon and nitrogen moieties and the product distribution changes as a function of coverage and temperature. At low coverage, incoming molecules react primarily through C-cycloaddition reactions and N dative bonds. However, as the density of adsorbates increases, new incoming molecules adsorbed primarily through the nitrogen moiety. Furthermore, as the temperature increases, the product distribution changed from primarily non-activated dative bond to activated cycloaddition products. Overall, the studies in this thesis provide new insight into competition and selectivity in adsorption of multifunctional molecules on the Ge(100)-2×1 surface.
The technological revolution that started with digital electronics more than 50 years ago has pushed the limits of scalability in device fabrication. Device features are currently at the nanometer scale, which requires structures to be built with atomic level accuracy. Advances in nanotechnology have opened up an exciting area of research that allows for molecular level control of device surfaces. Organic molecules can provide the tailorability required to continue the progress of semiconductor technologies. Organic functionalization provides a pathway to control the surface at the molecular level. Fundamental understanding of the adsorption phenomena between organic molecules and the surface is critical to achieve a stable inorganic/organic interface for the creation of hybrid nanostructures. This thesis aims to expand our current toolkit on functionalization to molecules that have multiple functionalities that can react with the surface. The reaction mechanism of these molecules is complex as there are several driving forces that can play a role during adsorption and influence the final reaction products. This thesis covers the adsorption of multifunctional molecules on the Ge(100)-2×1 surface using a combination of experimental and theoretical techniques: Fourier transform infrared spectroscopy, X-ray photoelectron spectroscopy, and density functional theory calculations. We explored the adsorption of four different molecules: 1,2,3-benzenetriol (C6H6O3); 1,3,5-benzenetriol (C6H6O3); 2-hydroxymethyl-1,3-propanediol (C4H10O3); pyrazine (C4H6N2). These are the first reported studies of these molecules on the Ge(100) surface. In order to understand the extent to which molecular geometry affects surface coverage, a detailed comparison of the adsorption of two triol molecules was carried out: 1,3,5-benzenetriol which has a rigid phenyl backbone and 2-hydroxymethyl-1,3-propanediol with a flexible alkyl backbone. DFT results showed that the rigid backbone exhibits a higher degree of strain, which translates to a loss of exothermicity in the reaction coordinate. Experiments showed that the flexibility of the alkyl backbone provides higher rotational degrees of freedom and an enhancement in surface coverage. In order to understand the effect of intermolecular interactions, the adsorption of 1,2,3-benzenetriol was explored. Interestingly, we found that at high coverage, intramolecular hydrogen bonding in singly and dually adsorbate products breaks to form intermolecular hydrogen bonding with a nearby adsorbate, which provides enhanced stabilization of the surface adduct. This additional stabilization may lower the reactivity of unreacted functional groups even if an empty nearby Ge site is available for reaction. The distribution of products resulted in primarily bidentate adsorbates, leaving an unreacted moiety at the surface. We also found evidence of coverage and temperature effects on adsorbed pyrazine molecules on the Ge surface. It was observed that this molecule adsorbs on Ge through both carbon and nitrogen moieties and the product distribution changes as a function of coverage and temperature. At low coverage, incoming molecules react primarily through C-cycloaddition reactions and N dative bonds. However, as the density of adsorbates increases, new incoming molecules adsorbed primarily through the nitrogen moiety. Furthermore, as the temperature increases, the product distribution changed from primarily non-activated dative bond to activated cycloaddition products. Overall, the studies in this thesis provide new insight into competition and selectivity in adsorption of multifunctional molecules on the Ge(100)-2×1 surface.
16. Advancing ab initio electronic structure theory and computational methods for excited state molecular dynamics [2018] Online
- Book
- 1 online resource.
Photochemistry studies chemical reactions caused by absorption of light. Developing theoretical and computational tools for photochemistry will not only help better understand photochemical processes such as photosynthesis and vision, but can also provide guidelines about how molecular photodevices can be better designed. Therefore, the goal of my graduate research is to develop a set of computational tools for studying photochemical processes. Physical systems have a hierarchical structure, i.e. basic particles like nuclei and electrons interact leading to the formation of molecules, and molecules interact and change conformations giving rise to chemical reactions. Naturally, the corresponding theoretical methods should also follow this hierarchy. At the bottom level, we need molecular integrals to describe different types of interactions between basic particles. I introduced the automated code engine (ACE) that generates optimized codes for computing integrals on the graphical processing units, and developed several variants of tensor hyper-contraction (THC) approximations. ACE reduces the computational prefactor of integral evaluations whereas THC reduces the formal scaling. On top of the integrals, we then need electronic structure methods to describe the energies and forces for a molecule at any given nuclear configuration; including electron correlation is the key to having an accurate description. Here, I first developed single reference THC-MP2 to capture the dynamic correlations, and then developed multi-reference THC-CASPT2 method to incorporate static correlations simultaneously. These methods were later generalized to THC-MSPT2 to enable descriptions for excited states and conical intersections, both are critical for photochemistry. Finally, given the electronic structure methods, we then need methods to explore the potential energy surfaces. In particular, critical point search methods locate the important configurations (e.g. Franck-Condon point, conical intersections), while molecular dynamics methods generate trajectories describing how the molecules move and interact with each other. By interfacing the electronic structure methods that I developed with the geomeTRIC geometry optimizer and G-AIMS non-adiabatic dynamics framework, a complete toolbox for understanding photochemistry is provided.
Photochemistry studies chemical reactions caused by absorption of light. Developing theoretical and computational tools for photochemistry will not only help better understand photochemical processes such as photosynthesis and vision, but can also provide guidelines about how molecular photodevices can be better designed. Therefore, the goal of my graduate research is to develop a set of computational tools for studying photochemical processes. Physical systems have a hierarchical structure, i.e. basic particles like nuclei and electrons interact leading to the formation of molecules, and molecules interact and change conformations giving rise to chemical reactions. Naturally, the corresponding theoretical methods should also follow this hierarchy. At the bottom level, we need molecular integrals to describe different types of interactions between basic particles. I introduced the automated code engine (ACE) that generates optimized codes for computing integrals on the graphical processing units, and developed several variants of tensor hyper-contraction (THC) approximations. ACE reduces the computational prefactor of integral evaluations whereas THC reduces the formal scaling. On top of the integrals, we then need electronic structure methods to describe the energies and forces for a molecule at any given nuclear configuration; including electron correlation is the key to having an accurate description. Here, I first developed single reference THC-MP2 to capture the dynamic correlations, and then developed multi-reference THC-CASPT2 method to incorporate static correlations simultaneously. These methods were later generalized to THC-MSPT2 to enable descriptions for excited states and conical intersections, both are critical for photochemistry. Finally, given the electronic structure methods, we then need methods to explore the potential energy surfaces. In particular, critical point search methods locate the important configurations (e.g. Franck-Condon point, conical intersections), while molecular dynamics methods generate trajectories describing how the molecules move and interact with each other. By interfacing the electronic structure methods that I developed with the geomeTRIC geometry optimizer and G-AIMS non-adiabatic dynamics framework, a complete toolbox for understanding photochemistry is provided.
- Book
- 1 online resource.
Silicon Photonics is considered to be essential for the sustained growth of semiconductor industry moving forward. The ubiquitous mobile devices and Internet of Things (IoT) are driving the data needs of the end user exponentially which has led to numerous data centers and perilously large power consumption in each of them. More than 3.4 billion people in the world have access to internet today and this number is increasing steadily day by day. Together, we generate more than 50 Terabytes (50,000 Gigabytes) of internet traffic per second at any given point of time. This number was just 100 Gigabytes per second in 2002 and it is expected to grow much faster going into the future. As for the power consumption, US data centers alone consumed about 70 billion kilowatt-hours of electricity in 2014, representing 2 percent of the country's total energy consumption, according to a study. That's equivalent to the amount consumed by about 6.4 million average American homes that year. This is a 4 percent increase in total data center energy consumption from 2010 to 2014, and a huge change from the preceding five years, during which total US data center energy consumption grew by 24 percent, and an even bigger change from the first half of last decade, when their energy consumption grew nearly 90 percent. It is well established that the copper cables which transfer data from one end of the data-center to the other are the bottlenecks reducing the overall bandwidth of the system and skyrocketing the power consumption on the whole. This bottleneck is getting worse day by day owing to the ever-increasing data needs. Silicon Photonics based 'optical interconnects' are the best solution to remove this bottleneck. Optical interconnects use photons instead of electrons for communication and therefore have the potential to offer very large bandwidths at minimal power consumption. In the very near future all the copper wires in the data-center ecosystem will have to be replaced by these optical interconnects if we must meet the data needs within the prescribed power budget. In order to build such a platform where conventional machines in the data center work in tandem with novel interconnects based on photon-devices, all the optical components need to be integrated seamlessly on a silicon chip. Modulators are the most important optical component of such a platform since they act as optical switches which control the flow of photons. In the first part of the dissertation, a silicon compatible germanium (Ge) electro-absorption modulator with the best reported energy-delay product is demonstrated. The figure-of-merits along with the design principles are discussed in detail while the fabrication methodology is briefly touched upon. Experimentally measured characteristics are then shown to be the best-in-class and ones that match the data requirements of the data-centers with minimal energy consumption. In the second part of the dissertation, we focus on developing an efficient silicon-compatible light emitter based on strained Ge technology. Detailed theoretical calculations lay down a roadmap for room-temperature lasing from Ge. These calculations also prove that the loss mechanisms involved in the light emission process from Ge have been inadequately modeled until now and shows that a particular loss mechanism known as the inter-valence-band absorption is a major barrier in the realization of a strained Ge laser. CMOS compatible fabrication techniques to introduce large uniaxial strain in Ge are then discussed. Finally, a low-threshold Ge laser at a temperature of 83 K is demonstrated. In the final part of the dissertation, the first demonstration of a 'truly' silicon compatible three-dimensional (3D) photonic crystals is discussed. Using the methodology developed, a broadband omnidirectional reflector is also demonstrated on silicon. This methodology is also shown to be particulary well suited for 3D waveguides and optical cavities.
Silicon Photonics is considered to be essential for the sustained growth of semiconductor industry moving forward. The ubiquitous mobile devices and Internet of Things (IoT) are driving the data needs of the end user exponentially which has led to numerous data centers and perilously large power consumption in each of them. More than 3.4 billion people in the world have access to internet today and this number is increasing steadily day by day. Together, we generate more than 50 Terabytes (50,000 Gigabytes) of internet traffic per second at any given point of time. This number was just 100 Gigabytes per second in 2002 and it is expected to grow much faster going into the future. As for the power consumption, US data centers alone consumed about 70 billion kilowatt-hours of electricity in 2014, representing 2 percent of the country's total energy consumption, according to a study. That's equivalent to the amount consumed by about 6.4 million average American homes that year. This is a 4 percent increase in total data center energy consumption from 2010 to 2014, and a huge change from the preceding five years, during which total US data center energy consumption grew by 24 percent, and an even bigger change from the first half of last decade, when their energy consumption grew nearly 90 percent. It is well established that the copper cables which transfer data from one end of the data-center to the other are the bottlenecks reducing the overall bandwidth of the system and skyrocketing the power consumption on the whole. This bottleneck is getting worse day by day owing to the ever-increasing data needs. Silicon Photonics based 'optical interconnects' are the best solution to remove this bottleneck. Optical interconnects use photons instead of electrons for communication and therefore have the potential to offer very large bandwidths at minimal power consumption. In the very near future all the copper wires in the data-center ecosystem will have to be replaced by these optical interconnects if we must meet the data needs within the prescribed power budget. In order to build such a platform where conventional machines in the data center work in tandem with novel interconnects based on photon-devices, all the optical components need to be integrated seamlessly on a silicon chip. Modulators are the most important optical component of such a platform since they act as optical switches which control the flow of photons. In the first part of the dissertation, a silicon compatible germanium (Ge) electro-absorption modulator with the best reported energy-delay product is demonstrated. The figure-of-merits along with the design principles are discussed in detail while the fabrication methodology is briefly touched upon. Experimentally measured characteristics are then shown to be the best-in-class and ones that match the data requirements of the data-centers with minimal energy consumption. In the second part of the dissertation, we focus on developing an efficient silicon-compatible light emitter based on strained Ge technology. Detailed theoretical calculations lay down a roadmap for room-temperature lasing from Ge. These calculations also prove that the loss mechanisms involved in the light emission process from Ge have been inadequately modeled until now and shows that a particular loss mechanism known as the inter-valence-band absorption is a major barrier in the realization of a strained Ge laser. CMOS compatible fabrication techniques to introduce large uniaxial strain in Ge are then discussed. Finally, a low-threshold Ge laser at a temperature of 83 K is demonstrated. In the final part of the dissertation, the first demonstration of a 'truly' silicon compatible three-dimensional (3D) photonic crystals is discussed. Using the methodology developed, a broadband omnidirectional reflector is also demonstrated on silicon. This methodology is also shown to be particulary well suited for 3D waveguides and optical cavities.
18. Aerodynamic interactions in arrays of vertical-axis wind turbines [2018] Online
- Book
- 1 online resource.
Understanding the aerodynamic interactions between turbines in a wind farm is essential for maximizing power generation. In contrast to horizontal-axis wind turbines (HAWTs), for which wake interactions between turbines in arrays must be minimized to prevent performance losses, vertical-axis wind turbines (VAWTs) in arrays have demonstrated beneficial interactions that can result in net power output greater than that of turbines in isolation. These synergistic interactions have been observed in previous numerical simulations, laboratory experiments, and field work. This dissertation builds on previous work by identifying the aerodynamic mechanisms that result in beneficial turbine-turbine interactions and providing insights into potential wind farm optimization. The experimental data presented indicates increased power production of downstream VAWTs when positioned offset from the wake of upstream turbines. Comparison with three-dimensional, three-component flow measurements demonstrates that this enhancement is due to flow acceleration adjacent to the upstream turbine, which increase the incident freestream velocity on appropriately positioned downstream turbines. A low-order model combining potential flow and actuator disk theory accurately captures this effect. Laboratory and field experiments were used to validate the model's predictive capabilities, and an evolutionary algorithm was deployed to investigate array optimization. Furthermore, changes in upstream turbine performance are related to variations in the surrounding flow field due to the presence of the downstream rotor. Finally, three-dimensional vortex interactions behind pairs of VAWTs are observed to replenish momentum in the array's wake. These effects are described along with their implications for wind farm design.
Understanding the aerodynamic interactions between turbines in a wind farm is essential for maximizing power generation. In contrast to horizontal-axis wind turbines (HAWTs), for which wake interactions between turbines in arrays must be minimized to prevent performance losses, vertical-axis wind turbines (VAWTs) in arrays have demonstrated beneficial interactions that can result in net power output greater than that of turbines in isolation. These synergistic interactions have been observed in previous numerical simulations, laboratory experiments, and field work. This dissertation builds on previous work by identifying the aerodynamic mechanisms that result in beneficial turbine-turbine interactions and providing insights into potential wind farm optimization. The experimental data presented indicates increased power production of downstream VAWTs when positioned offset from the wake of upstream turbines. Comparison with three-dimensional, three-component flow measurements demonstrates that this enhancement is due to flow acceleration adjacent to the upstream turbine, which increase the incident freestream velocity on appropriately positioned downstream turbines. A low-order model combining potential flow and actuator disk theory accurately captures this effect. Laboratory and field experiments were used to validate the model's predictive capabilities, and an evolutionary algorithm was deployed to investigate array optimization. Furthermore, changes in upstream turbine performance are related to variations in the surrounding flow field due to the presence of the downstream rotor. Finally, three-dimensional vortex interactions behind pairs of VAWTs are observed to replenish momentum in the array's wake. These effects are described along with their implications for wind farm design.
19. Aggregated Model Spaces [2018] Online
- Collection
- Undergraduate Theses, School of Engineering
In many practical applications, machine learning is divided over multiple agents, where each agent learns a different task and/or learns from a different dataset. We present Aggregated Model Spaces (AMS), a framework for learning a global model by aggregating local learnings performed by each agent. Our approach forgoes sharing of data between agents, makes no assumptions on the distribution of data across agents, and requires minimal communication between agents. We empirically validate our techniques on MNIST experiments and discuss how AMS can generalize to a wide range of problem settings, including federated averaging and catastrophic forgetting. We believe our framework to be among the first to lay out a general methodology for “combining” distinct models.
In many practical applications, machine learning is divided over multiple agents, where each agent learns a different task and/or learns from a different dataset. We present Aggregated Model Spaces (AMS), a framework for learning a global model by aggregating local learnings performed by each agent. Our approach forgoes sharing of data between agents, makes no assumptions on the distribution of data across agents, and requires minimal communication between agents. We empirically validate our techniques on MNIST experiments and discuss how AMS can generalize to a wide range of problem settings, including federated averaging and catastrophic forgetting. We believe our framework to be among the first to lay out a general methodology for “combining” distinct models.
- Book
- 350 pages : illustrations ; 25 cm
SAL3 (off-campus storage)
| SAL3 (off-campus storage) | Status |
|---|---|
| Stacks | Request |
| DS119.7 .T36 2018 | Available |
