Dissertação(mestrado) - Universidade Federal do Rio Grande, Programa de Pós-Graduação em Oceanografia Física, Química e Geológica, Instituto de Oceanografia, 2011. / Submitted by Cristiane Silva (cristiane_gomides@hotmail.com) on 2013-03-12T12:42:52Z No. of bitstreams: 1 2011_lorena_collares.pdf: 4980623 bytes, checksum: fe164915b150fc2e5673516c2d5626b7 (MD5) / Approved for entry into archive by Bruna Vieira(bruninha_vieira@ibest.com.br) on 2013-07-15T17:50:41Z (GMT) No. of bitstreams: 1 2011_lorena_collares.pdf: 4980623 bytes, checksum: fe164915b150fc2e5673516c2d5626b7 (MD5) / Made available in DSpace on 2013-07-15T17:50:41Z (GMT). No. of bitstreams: 1 2011_lorena_collares.pdf: 4980623 bytes, checksum: fe164915b150fc2e5673516c2d5626b7 (MD5) Previous issue date: 2011 / Os icebergs representam uma distinta feição no Oceano Austral. As correntes oceânicas, o gelo marinho, a batimetria e os ventos são responsáveis por determinar a trajetória destes grandes blocos de gelo. Desta forma, informações sobre a distribuição e a concentração dos icebergs podem auxiliar no melhor entendimento da circulação oceânica e atmosférica nas regiões polares. Diferentes métodos de observação de icebergs têm sido utilizados ao longo do tempo para o entendimento desta componente da criosfera. Duas metodologias despontam para tal objetivo, plataformas de coleta de dados (PCDs) rastreadas via sistema satelital ARGOS e as imagens de radar. A fim de monitorar o deslocamento de icebergs, no noroeste do Mar de Weddell, foram utilizados dados de posição de PCDs fixadas em três icebergs (em 19 de fevereiro de 2009) nas proximidades da ilha James Ross. Imagens Advanced Synthetic Aperture Radar (ASAR) foram utilizadas como medida complementar no rastreamento de icebergs durante os anos de 2008 e 2009. A partir dos resultados foi possível associar a deriva dos icebergs monitorados aos principais sistemas de correntes e frentes desta região, como a Corrente Costeira Antártica, a Frente de Talude Antártico e a Frente de Weddell. Mais especificamente, pode-se observar aspectos da circulação regional, tal como a identificação de uma célula de circulação anticiclônica no entorno da ilha James Ross e a deriva de icebergs em direção ao Estreito de Bransfield. Um estudo de caso demonstrou a recirculação de um iceberg no interior do Estreito de Bransfield e sua desintegração associada. A estimativa média da taxa de desintegração dos icebergs monitorados foi de 19%, associadas com um fluxo de volume de água doce para o oceano de aproximadamente 0.57 m3 s-1 e 0.94 m3s-1, respectivamente durante o período de observações nos anos de 2008 e 2009. A velocidade média de deriva calculada através do monitoramento via PCDs e imagens ASAR foi de 3.04 ±1.9 cm s-1 e 5.97 ± 2.8cm s-1, respectivamente. / Icebergs represent a distinctive feature of the Southern Ocean. Ocean currents, sea ice, bathymetry and winds determine the icebergs trajectory and its drift. Thus, information about icebergs distribution and concentration help to better understand the ocean and atmospheric circulation in Polar Regions. Several methods to observe icebergs have been used to comprehend the behavior and the role of this component of the cryosphere. Two methodologies are emerging for this purpose recently, such as icebergs tagging (for satellite tracking) and orbital radar images. In order to monitor the displacement of icebergs in the northwestern Weddell Sea, we used data from three icebergs tagged with Data Collection Platforms - DCPs (19/02/2009) in the vicinity of the James Ross Island. Additionally, ASAR images were used as a complementary measure to track the icebergs during the years 2008 and 2009 in the same area. Observing the results, it was possible to associate the icebergs drift with the main currents and fronts systems found in this region, as the Antarctic Coastal Current, Antarctic Slope Front and Weddell Front. More specifically, one can observe the regional circulation, such as the identification of an anticyclonic circulation cell around the James Ross Island and icebergs drifting into the Bransfield Strait. A case study demonstrated the recirculation of iceberg within the Bransfield Strait and its corresponding loss of mass. The icebergs disintegration estimated was 19%, associated with a freshwater volume flow toward the ocean of approximately 0,57 m3 s-1 and 0,94 m3 s-1 , respectively during the observation period, for the years 2008 and 2009. The drift rates determined by monitoring icebergs via DCPs and ASAR images were, respectively, 3,04 ±1,9 cm s-1 and 5,97 ± 2,8cm s-1.

This dissertation studies economic issues in the digital economy with a specific focus on the economic aspects of how firms acquire and use consumer data. Chapter 1 empirically studies the drivers of digital attention in the space of social media applications. In order to do so I conduct an experiment where I comprehensively monitor how participants spend their time on digital services and use parental control software to shut off access to either their Instagram or YouTube. I characterize how participants substitute their time during and after the restrictions. I provide an interpretation of the substitution during the restriction period that allows me to conclude that relevant market definitions may be broader than those currently considered by regulatory authorities, but that the substantial diversion towards non-digital activities indicates significant market power from the perspective of consumers for Instagram and YouTube. I then use the results on substitution after the restriction period to motivate a discrete choice model of time usage with inertia and, using the estimates from this model, conduct merger assessments between social media applications. I find that the inertia channel is important for justifying blocking mergers, which I use to argue that currently debated policies aimed at curbing digital addiction are important not only just in their own right but also from an antitrust perspective and, in particular, as a potential policy tool for promoting competition in these markets. More broadly, my paper highlights the utility of product unavailability experiments for demand and merger analysis of digital goods. I thank Maayan Malter for working together with me on collecting the data for this paper. Chapter 2 then studies the next step in consumer data collection process – the extent to which a firm can collect a consumer’s data depends on privacy preferences and the set of available privacy tools. This chapter studies the impact of the General Data Protection Regulation on the ability of a data-intensive intermediary to collect and use consumer data. We find that the opt-in requirement of GDPR resulted in 12.5% drop in the intermediary-observed consumers, but the remaining consumers are trackable for a longer period of time. These findings are consistent with privacy-conscious consumers substituting away from less efficient privacy protection (e.g, cookie deletion) to explicit opt out—a process that would make opt-in consumers more predictable. Consistent with this hypothesis, the average value of the remaining consumers to advertisers has increased, offsetting some of the losses from consumer opt-outs. This chapter is jointly authored with Yeon-Koo Che and Tobias Salz. Chapter 3 and Chapter 4 make up the third portion of the dissertation that studies one of the most prominent uses of consumer data in the digital economy – recommendation systems. This chapter is a combination of several papers studying the economic impact of these systems. The first paper is a joint paper with Duarte Gonçalves which studies a model of strategic interaction between producers and a monopolist platform that employs a recommendation system. We characterize the consumer welfare implications of the platform’s entry into the production market. The platform’s entry induces the platform to bias recommendations to steer consumers towards its own goods, which leads to equilibrium investment adjustments by the producers and lower consumer welfare. Further, we find that a policy separating recommendation and production is not always welfare improving. Our results highlight the ability of integrated recommender systems to foreclose competition on online platforms. The second paper turns towards understanding how such systems impact consumer choices and is joint with Duarte Gonçalves and Shan Sikdar. In this paper we study a model of user decision-making in the context of recommender systems via numerical simulation. Our model provides an explanation for the findings of Nguyen et. al (2014), where, in environments where recommender systems are typically deployed, users consume increasingly similar items over time even without recommendation. We find that recommendation alleviates these natural filter-bubble effects, but that it also leads to an increase in homogeneity across users, resulting in a trade-off between homogenizing across-user consumption and diversifying within-user consumption. Finally, we discuss how our model highlights the importance of collecting data on user beliefs and their evolution over time both to design better recommendations and to further understand their impact.

Thesis: S.M., Joint Program in Applied Ocean Physics and Engineering (Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science; and the Woods Hole Oceanographic Institution), 2018. / This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections. / Cataloged from student-submitted PDF version of thesis. / Includes bibliographical references (pages 97-107). / Mobile robots and autonomous sensors have seen increasing use in scientific applications, from planetary rovers surveying for signs of life on Mars, to environmental buoys measuring and logging oceanographic conditions in coastal regions. This thesis makes contributions in both planning algorithms and model design for autonomous scientific information gathering, demonstrating how theory from machine learning, decision theory, theory of optimal experimental design, and statistical inference can be used to develop online algorithms for robotic information gathering that are robust to modeling errors, account for spatiotemporal structure in scientific data, and have probabilistic performance guarantees. This thesis first introduces a novel sample selection algorithm for online, irrevocable sampling in data streams that have spatiotemporal structure, such as those that commonly arise in robotics and environmental monitoring. Given a limited sampling capacity, the proposed periodic secretary algorithm uses an information-theoretic reward function to select samples in real-time that maximally reduce posterior uncertainty in a given scientific model. Additionally, we provide a lower bound on the quality of samples selected by the periodic secretary algorithm by leveraging the submodularity of the information-theoretic reward function. Finally, we demonstrate the robustness of the proposed approach by employing the periodic secretary algorithm to select samples irrevocably from a seven-year oceanographic data stream collected at the Martha's Vineyard Coastal Observatory off the coast of Cape Cod, USA. Secondly, we consider how scientific models can be specified in environments - such as the deep sea or deep space - where domain scientists may not have enough a priori knowledge to formulate a formal scientific model and hypothesis. These domains require scientific models that start with very little prior information and construct a model of the environment online as observations are gathered. We propose unsupervised machine learning as a technique for science model-learning in these environments. To this end, we introduce a hybrid Bayesian-deep learning model that learns a nonparametric topic model of a visual environment. We use this semantic visual model to identify observations that are poorly explained in the current model, and show experimentally that these highly perplexing observations often correspond to scientifically interesting phenomena. On a marine dataset collected by the SeaBED AUV on the Hannibal Sea Mount, images of high perplexity in the learned model corresponded, for example, to a scientifically novel crab congregation in the deep sea. The approaches presented in this thesis capture the depth and breadth of the problems facing the field of autonomous science. Developing robust autonomous systems that enhance our ability to perform exploratory science in environments such as the oceans, deep space, agricultural and disaster-relief zones will require insight and techniques from classical areas of robotics, such as motion and path planning, mapping, and localization, and from other domains, including machine learning, spatial statistics, optimization, and theory of experimental design. This thesis demonstrates how theory and practice from these diverse disciplines can be unified to address problems in autonomous scientific information gathering. / by Genevieve Elaine Flaspohler. / S.M.