12 research outputs found

    Law in the present future : approaching the legal imaginary of smart cities with science (and) fiction

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    This doctoral research concerns smart cities, describing digital solutions and social issues related to their innovative technologies, adopted models, and major projects around the world. The many perspectives mentioned in it were identified by online tools used for the textual analysis of two databases that were built from relevant publications on the main subject by authors coming from media and academia. Expected legal elements emerged from the applied process, such as privacy, security, transparency, participation, accountability, and governance. A general review was produced on the information available about the public policies of Big Data in the two municipal cases of Rio de Janeiro and Montréal, and their regulation in the Brazilian and Canadian contexts. The combined approaches from science and literature were explored to reflect on the normative concerns represented by the global challenges and local risks brought by urban surveillance, climate change, and other neoliberal conditions. Cyberpunk Science Fiction reveals itself useful for engaging with the shared problems that need to be faced in the present time, all involving democracy. The results achieved reveal that this work was, in fact, about the complex network of practices and senses between (post)modern law and the imaginary of the future.Cette recherche doctorale centrée sur les villes intelligentes met en évidence les solutions numériques et les questionnements sociétaux qui ont trait aux technologies innovantes, ainsi qu’aux principaux modèles et projets développés autour d’elles à travers le monde. Des perspectives multiples en lien avec ces développements ont été identifiées à l’aide d’outils en ligne qui ont permis l’analyse textuelle de deux bases de données comprenant des publications scientifiques et des écrits médiatiques. De ce processus analytique ont émergé des éléments juridiques relatifs aux questions de vie privée, de sécurité, de transparence, de participation, d’imputabilité et de gouvernance. De plus, à partir de ces informations a été réalisée une revue des politiques publiques relatives aux mégadonnées dans les villes de Rio de Janeiro et de Montréal, ainsi que des réglementations nationales du Canada et du Brésil en lien avec ce sujet. Finalement, à travers l’exploration d’écrits scientifiques et fictionnels de la littérature, les principaux enjeux normatifs soulevés localement et mondialement par la surveillance urbaine, les changements climatiques et les politiques néolibérales ont pu être mis à jour. Le courant cyberpunk de la science-fiction s’est avéré particulièrement utile pour révéler les principaux problèmes politiques, en lien avec la préservation de la démocratie, auxquelles sont confrontées nos sociétés présentement. Les résultats de la recherche démontrent finalement la présence d’un réseau de pratiques et de significations entre le droit (post)moderne et les représentations imaginaires du futur

    Event detection in high throughput social media

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    Helping academics manage students with “invisible disabilities”

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    Seeing affect: knowledge infrastructures in facial expression recognition systems

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    Efforts to process and simulate human affect have come to occupy a prominent role in Human-Computer Interaction as well as developments in machine learning systems. Affective computing applications promise to decode human affective experience and provide objective insights into usersʼ affective behaviors, ranging from frustration and boredom to states of clinical relevance such as depression and anxiety. While these projects are often grounded in psychological theories that have been contested both within scholarly and public domains, practitioners have remained largely agnostic to this debate, focusing instead on the development of either applicable technical systems or advancements of the fieldʼs state of the art. I take this controversy as an entry point to investigate the tensions related to the classification of affective behaviors and how practitioners validate these classification choices. This work offers an empirical examination of the discursive and material repertoires ‒ the infrastructures of knowledge ‒ that affective computing practitioners mobilize to legitimize and validate their practice. I build on feminist studies of science and technology to interrogate and challenge the claims of objectivity on which affective computing applications rest. By looking at research practices and commercial developments of Facial Expression Recognition (FER) systems, the findings unpack the interplay of knowledge, vision, and power underpinning the development of machine learning applications of affective computing. The thesis begins with an analysis of historical efforts to quantify affective behaviors and how these are reflected in modern affective computing practice. Here, three main themes emerge that will guide and orient the empirical findings: 1) the role that framings of science and scientific practice play in constructing affective behaviors as “objective” scientific facts, 2) the role of human interpretation and mediation required to make sense of affective data, and 3) the prescriptive and performative dimensions of these quantification efforts. This analysis forms the historical backdrop for the empirical core of the thesis: semi-structured interviews with affective computing practitioners across the academic and industry sectors, including the data annotators labelling the modelsʼ training datasets. My findings reveal the discursive and material strategies that participants adopt to validate affective classification, including forms of boundary work to establish credibility as well as the local and contingent work of human interpretation and standardization involved in the process of making sense of affective data. Here, I show how, despite their professed agnosticism, practitioners must make normative choices in order to ʻseeʼ (and teach machines how to see) affect. I apply the notion of knowledge infrastructures to conceptualize the scaffolding of data practices, norms and routines, psychological theories, and historical and epistemological assumptions that shape practitionersʼ vision and inform FER design. Finally, I return to the problem of agnosticism and its socio-ethical relevance to the broader field of machine learning. Here, I argue that agnosticism can make it difficult to locate the technologyʼs historical and epistemological lineages and, therefore, obscure accountability. I conclude by arguing that both policy and practice would benefit from a nuanced examination of the plurality of visions and forms of knowledge involved in the automation of affect

    Collaborative Help for Individualized Problems: Learning from the MythTV User Community and Diabetes Patient Support Groups.

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    As information technology increasingly becomes part of everyday life, new opportunities arise for aggregating people’s experiences and knowledge. Collaborative help can utilize collective experience and knowledge to benefit everyday problem solving activities. However, current help systems often limit their focus to common and active problems (e.g., Frequently Asked Questions), making it difficult for users to find answers to the problems that are uncommon and individualized. In my dissertation, I address how individualized problems can be better supported through collaborative help. My dissertation contributes to existing conversations around collaborative help, especially challenges in information reuse and contextualization. I further expand discussions around the role of temporal information during expertise sharing for finding solutions to individualized problems. In order to study this, I examined two research sites using an interpretivist approach (Strauss & Corbin, 1990): the MythTV user community and diabetes patient support groups. Because problems are often individualized for members of both communities, these sites serve as excellent places to examine the research problem. I discuss three key findings that are critical for understanding how individualized problems are solved in community-based collaborative help systems. First, operationalizing experiences is critical for sharing executable solutions and context. Operationalized experiences are not only about the objectification and easy transfer of tacit knowledge (Ambrosini & Bowman, 2002), but generate knowledge that can be directly re-used. Second, operationalization process inevitably fails to capture practices “simultaneously embedded in various processes” (Ackerman & Halverson, 2000) during maintenance activities, be it maintaining MythTV or diabetes. However, the breakdown of operationalization process helps each community member learn how to manage individualized situations as they occur. Lastly, operationalization process needs to take place within the larger context of sharing trajectories. By comparing, aligning, and collaging pieces of individual trajectories, community members collectively expand their knowledge about managing MythTV or diabetes over time. Through continual sharing of maintenance trajectories, members reduce uncertainty about the future, take preventative actions, and reflect on the past to revise their practices.Ph.D.InformationUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/89774/1/jinah_1.pd

    Variation of Soil Structure in the Foot and Toe Slopes of Mt. Vukan, East-central Serbia

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    This paper presents the variation of soil structure along the foot and toe slopes of Mt. Vukan, East-Central Serbia. The analysis of aggregate size distribution and structure indices were conducted by means of soil units, characteristic soil horizons and elevation differences along the study area. Soils of Great Field located at different elevations were found to have significant variation in ASD and soil structure indices. Topsoil horizon of Eutric Cambisols have higher MWD after dry sieving, but at the same time it has the highest variation in MWD after wet sieving, indicating low water stability, which is opposite to the coefficient of aggregability. We share an opinion that change in MWD better depicts soils structure stability to water. The results of correlation analysis indicated that clay content is correlated more to structure indices compared with SOM content. SOM is significantly correlated with ASD and soil structure indices only in Calcomelansols, whereas the significant correlation of clay content and soil structure is more evident in Eutric Cambisols and Non-calcaric Chernozems, compared with other soil units. Soil structure variation along the lowest chain of Catena might be strong, and that it has to be analyzed from the point of view of soil unit and their corresponding soil horizons
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