6,942 research outputs found

    Examples of works to practice staccato technique in clarinet instrument

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    Klarnetin staccato tekniğini güçlendirme aşamaları eser çalışmalarıyla uygulanmıştır. Staccato geçişlerini hızlandıracak ritim ve nüans çalışmalarına yer verilmiştir. Çalışmanın en önemli amacı sadece staccato çalışması değil parmak-dilin eş zamanlı uyumunun hassasiyeti üzerinde de durulmasıdır. Staccato çalışmalarını daha verimli hale getirmek için eser çalışmasının içinde etüt çalışmasına da yer verilmiştir. Çalışmaların üzerinde titizlikle durulması staccato çalışmasının ilham verici etkisi ile müzikal kimliğe yeni bir boyut kazandırmıştır. Sekiz özgün eser çalışmasının her aşaması anlatılmıştır. Her aşamanın bir sonraki performans ve tekniği güçlendirmesi esas alınmıştır. Bu çalışmada staccato tekniğinin hangi alanlarda kullanıldığı, nasıl sonuçlar elde edildiği bilgisine yer verilmiştir. Notaların parmak ve dil uyumu ile nasıl şekilleneceği ve nasıl bir çalışma disiplini içinde gerçekleşeceği planlanmıştır. Kamış-nota-diyafram-parmak-dil-nüans ve disiplin kavramlarının staccato tekniğinde ayrılmaz bir bütün olduğu saptanmıştır. Araştırmada literatür taraması yapılarak staccato ile ilgili çalışmalar taranmıştır. Tarama sonucunda klarnet tekniğin de kullanılan staccato eser çalışmasının az olduğu tespit edilmiştir. Metot taramasında da etüt çalışmasının daha çok olduğu saptanmıştır. Böylelikle klarnetin staccato tekniğini hızlandırma ve güçlendirme çalışmaları sunulmuştur. Staccato etüt çalışmaları yapılırken, araya eser çalışmasının girmesi beyni rahatlattığı ve istekliliği daha arttırdığı gözlemlenmiştir. Staccato çalışmasını yaparken doğru bir kamış seçimi üzerinde de durulmuştur. Staccato tekniğini doğru çalışmak için doğru bir kamışın dil hızını arttırdığı saptanmıştır. Doğru bir kamış seçimi kamıştan rahat ses çıkmasına bağlıdır. Kamış, dil atma gücünü vermiyorsa daha doğru bir kamış seçiminin yapılması gerekliliği vurgulanmıştır. Staccato çalışmalarında baştan sona bir eseri yorumlamak zor olabilir. Bu açıdan çalışma, verilen müzikal nüanslara uymanın, dil atış performansını rahatlattığını ortaya koymuştur. Gelecek nesillere edinilen bilgi ve birikimlerin aktarılması ve geliştirici olması teşvik edilmiştir. Çıkacak eserlerin nasıl çözüleceği, staccato tekniğinin nasıl üstesinden gelinebileceği anlatılmıştır. Staccato tekniğinin daha kısa sürede çözüme kavuşturulması amaç edinilmiştir. Parmakların yerlerini öğrettiğimiz kadar belleğimize de çalışmaların kaydedilmesi önemlidir. Gösterilen azmin ve sabrın sonucu olarak ortaya çıkan yapıt başarıyı daha da yukarı seviyelere çıkaracaktır

    Linguistic- and Acoustic-based Automatic Dementia Detection using Deep Learning Methods

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    Dementia can affect a person's speech and language abilities, even in the early stages. Dementia is incurable, but early detection can enable treatment that can slow down and maintain mental function. Therefore, early diagnosis of dementia is of great importance. However, current dementia detection procedures in clinical practice are expensive, invasive, and sometimes inaccurate. In comparison, computational tools based on the automatic analysis of spoken language have the potential to be applied as a cheap, easy-to-use, and objective clinical assistance tool for dementia detection. In recent years, several studies have shown promise in this area. However, most studies focus heavily on the machine learning aspects and, as a consequence, often lack sufficient incorporation of clinical knowledge. Many studies also concentrate on clinically less relevant tasks such as the distinction between HC and people with AD which is relatively easy and therefore less interesting both in terms of the machine learning and the clinical application. The studies in this thesis concentrate on automatically identifying signs of neurodegenerative dementia in the early stages and distinguishing them from other clinical, diagnostic categories related to memory problems: (FMD, MCI, and HC). A key focus, when designing the proposed systems has been to better consider (and incorporate) currently used clinical knowledge and also to bear in mind how these machine-learning based systems could be translated for use in real clinical settings. Firstly, a state-of-the-art end-to-end system is constructed for extracting linguistic information from automatically transcribed spontaneous speech. The system's architecture is based on hierarchical principles thereby mimicking those used in clinical practice where information at both word-, sentence- and paragraph-level is used when extracting information to be used for diagnosis. Secondly, hand-crafted features are designed that are based on clinical knowledge of the importance of pausing and rhythm. These are successfully joined with features extracted from the end-to-end system. Thirdly, different classification tasks are explored, each set up so as to represent the types of diagnostic decision-making that is relevant in clinical practice. Finally, experiments are conducted to explore how to better deal with the known problem of confounding and overlapping symptoms on speech and language from age and cognitive decline. A multi-task system is constructed that takes age into account while predicting cognitive decline. The studies use the publicly available DementiaBank dataset as well as the IVA dataset, which has been collected by our collaborators at the Royal Hallamshire Hospital, UK. In conclusion, this thesis proposes multiple methods of using speech and language information for dementia detection with state-of-the-art deep learning technologies, confirming the automatic system's potential for dementia detection

    Chinese Benteng Women’s Participation in Local Development Affairs in Indonesia: Appropriate means for struggle and a pathway to claim citizen’ right?

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    It had been more than two decades passing by aftermath the devastating Asia’s Financial Crisis in 1997, subsequently followed by Suharto’s step down from his presidential throne which he occupied for more than three decades. The financial turmoil turned to a political disaster furthermore has led to massive looting that severely impacted Indonesians of Chinese descendant, including unresolved mystery of the most atrocious sexual violation against women and covert killings of students and democracy activists in this country. Since then, precisely aftermath May 1998, which publicly known as “Reformasi”1, Indonesia underwent political reform that eventually corresponded positively to its macroeconomic growth. Twenty years later, in 2018, Indonesia captured worldwide attention because it has successfully hosted two internationally renowned events, namely the Asian Games 2018 – the most prestigious sport events in Asia – conducted in Jakarta and Palembang; and the IMF/World Bank Annual Meeting 2018 in Bali. Particularly in the IMF/World Bank Annual Meeting, this event has significantly elevated Indonesia’s credibility and international prestige in the global economic powerplay as one of the nations with promising growth and openness. However, the narrative about poverty and inequality, including increasing racial tension, religious conservatism, and sexual violation against women are superseded by friendly climate for foreign investment and eventually excessive glorification of the nation’s economic growth. By portraying the image of promising new economic power, as rhetorically promised by President Joko Widodo during his presidential terms, Indonesia has swept the growing inequality in this highly stratified society that historically compounded with religious and racial tension under the carpet of digital economy.Arte y Humanidade

    Buddhist Poetics, Beat “Cosmo-Politics,” and the Maker Ethos: Asian Americanist Critiques of Whiteness in Midcentury American Beat Writing

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    Buddhist Poetics, Beat “Cosmo-Politics,” and the Maker Ethos: Asian Americanist Critiques of Whiteness in Midcentury American Beat Writing employs Walter Benjamin’s notion of the “ruin”—which is not just a noun or notion, but also a verb, a mode of criticism—to intervene in the ostensibly well-trodden ground of what is known as “Beat literature.” The project broadly argues for the “ruination” of Beat literature, where ruination means not destruction or annihilation, but a return to an unkempt state (as in the image of a ruined building) that more accurately reflects this literature’s many layers of cultural, interpersonal, and transpacific exchange and extraction. Though many have rightly suggested that Beat literature is broadly Orientalist and transpacific in nature, I reveal the specific cultural appropriations, adaptations, and translations that occurred in this period and in these literary texts: the broadly East Asian cultural materials (like Zen Buddhism) so valued in Beat literature and its social communities were derived not solely from “the East” nor from translated Chinese and Japanese texts, but also from the Asians in America with whom Euro Americans were friends and worked alongside. My chapters on Asian diasporic poetry, letters, and autobiographical writing highlight Beat literature’s connections to ethnic studies, settler colonial studies, gender studies, and critical race theory, applying an interdisciplinary approach to text and culture and bringing forward the cultural productions and expertise of Asian/Americans during this midcentury period. Because I am suggesting the work of Asian/Americans be read alongside other canonical Beat texts, their work destabilizes or “ruins” Beat literature, which has been seen as a body of texts that articulate a political, anticapitalist critique of post-WWII and Cold War-era America, but which I show to be reflective of a specific, European American identity grounded in a politics that does not accommodate the effects of settler colonialism and imperialism. The seeming stability and coherence of the category of “Beat” has only been possible because the work of Asian/Americans in this period was erased, unacknowledged. My project’s major intervention may be found in its combination of critique—where I show how whiteness influenced Euro Americans’ artistic choices and cultural appropriations—and recovery, where I reveal from whom and how these appropriations occurred. Further, I suggest that we begin to analyze American Buddhist writing beyond the limited rubrics formerly available to us in “Beat” and avant-garde literatures and in their communities of reception

    Recent Hong Kong cinema and the generic role of film noir in relation to the politics of identity and difference

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    This thesis identifies a connection in Hong Kong cinema with classical Hollywood film noir and examines what it will call a 'reinvestment' in film noir in recent films. It will show that this reinvestment is a discursive strategy that both engages the spectator-subject in the cinematic practice and disengages him or her from the hegemony of the discourse by decentring the narrative. The thesis argues that a cinematic practice has occurred in the recent reinvestment of film noir in Hong Kong, which restages the intertextual relay of the historical genre that gives rise to an expectation of ideas about social instability. The noir vision that is seen as related to the fixed categories of film narratives, characterizations and visual styles is reassessed in the course of the thesis using Derridian theory. The focus of analysis is the way in which the constitution of meanings is dependent on generic characteristics that are different. Key to the phenomenon is a film strategy that destabilizes, differs and defers the interpretation of crises-personal, social, political and/or cultural-by soliciting self-conscious re-reading of suffering, evil, fate, chance and fortune. It will be argued that such a strategy evokes the genre expectation as the film invokes a network of ideas regarding a world perceived by the audience in association with the noirish moods of claustrophobia, paranoia, despair and nihilism. The noir vision is thus mutated and transformed when the film device differs and defers the conception of the crises as tragic in nature by exposing the workings of the genre amalgamation and the ideological function of the cinematic discourse. Thus, noirishness becomes both an affect and an agent that contrives a self-reflexive re-reading of the tragic vision and of the conventional comprehension of reality within the discursive practice. The film strategy, as an agent that problematizes the film form and narrative, gives rise to what I call a politics of difference, which may also be understood as the Lyotardian 'language game' or a practice of 'pastiche' in Jameson's terminology. Under the influence of the film strategy, the spectator is enabled to negotiate his or her understanding of recent Hong Kong cinema diegetically and extra-diegetically by traversing different positions of cinematic identification. When the practice of genre amalgamation adopts the visual impact of the noirish film form, the film turns itself into a playing field of 'fatal' misrecognition or a site of question. Through cinematic identification and alienation from the identification, the spectator-subject is enabled to experience the misrecognition as the film slowly foregrounds the way in which the viewer's presence is implicated in the narrative. This thesis demonstrates that certain contemporary Hong Kong films introduce this selfconscious mode of explication and interpretation, which solicits the spectator to negotiate his or her subject-position in the course of viewing. The notions of identity and subjectivity under scrutiny will thus be reread. With reference to The Private Eye Blue, Swordsman II, City a/Glass and Happy Together, the thesis shall explore the ways in which the Hong Kong films enable and facilitate a negotiation of cultural identity

    Scalable software and models for large-scale extracellular recordings

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    The brain represents information about the world through the electrical activity of populations of neurons. By placing an electrode near a neuron that is firing (spiking), it is possible to detect the resulting extracellular action potential (EAP) that is transmitted down an axon to other neurons. In this way, it is possible to monitor the communication of a group of neurons to uncover how they encode and transmit information. As the number of recorded neurons continues to increase, however, so do the data processing and analysis challenges. It is crucial that scalable software and analysis tools are developed and made available to the neuroscience community to keep up with the large amounts of data that are already being gathered. This thesis is composed of three pieces of work which I develop in order to better process and analyze large-scale extracellular recordings. My work spans all stages of extracellular analysis from the processing of raw electrical recordings to the development of statistical models to reveal underlying structure in neural population activity. In the first work, I focus on developing software to improve the comparison and adoption of different computational approaches for spike sorting. When analyzing neural recordings, most researchers are interested in the spiking activity of individual neurons, which must be extracted from the raw electrical traces through a process called spike sorting. Much development has been directed towards improving the performance and automation of spike sorting. This continuous development, while essential, has contributed to an over-saturation of new, incompatible tools that hinders rigorous benchmarking and complicates reproducible analysis. To address these limitations, I develop SpikeInterface, an open-source, Python framework designed to unify preexisting spike sorting technologies into a single toolkit and to facilitate straightforward benchmarking of different approaches. With this framework, I demonstrate that modern, automated spike sorters have low agreement when analyzing the same dataset, i.e. they find different numbers of neurons with different activity profiles; This result holds true for a variety of simulated and real datasets. Also, I demonstrate that utilizing a consensus-based approach to spike sorting, where the outputs of multiple spike sorters are combined, can dramatically reduce the number of falsely detected neurons. In the second work, I focus on developing an unsupervised machine learning approach for determining the source location of individually detected spikes that are recorded by high-density, microelectrode arrays. By localizing the source of individual spikes, my method is able to determine the approximate position of the recorded neuriii ons in relation to the microelectrode array. To allow my model to work with large-scale datasets, I utilize deep neural networks, a family of machine learning algorithms that can be trained to approximate complicated functions in a scalable fashion. I evaluate my method on both simulated and real extracellular datasets, demonstrating that it is more accurate than other commonly used methods. Also, I show that location estimates for individual spikes can be utilized to improve the efficiency and accuracy of spike sorting. After training, my method allows for localization of one million spikes in approximately 37 seconds on a TITAN X GPU, enabling real-time analysis of massive extracellular datasets. In my third and final presented work, I focus on developing an unsupervised machine learning model that can uncover patterns of activity from neural populations associated with a behaviour being performed. Specifically, I introduce Targeted Neural Dynamical Modelling (TNDM), a statistical model that jointly models the neural activity and any external behavioural variables. TNDM decomposes neural dynamics (i.e. temporal activity patterns) into behaviourally relevant and behaviourally irrelevant dynamics; the behaviourally relevant dynamics constitute all activity patterns required to generate the behaviour of interest while behaviourally irrelevant dynamics may be completely unrelated (e.g. other behavioural or brain states), or even related to behaviour execution (e.g. dynamics that are associated with behaviour generally but are not task specific). Again, I implement TNDM using a deep neural network to improve its scalability and expressivity. On synthetic data and on real recordings from the premotor (PMd) and primary motor cortex (M1) of a monkey performing a center-out reaching task, I show that TNDM is able to extract low-dimensional neural dynamics that are highly predictive of behaviour without sacrificing its fit to the neural data

    Optimización del rendimiento y la eficiencia energética en sistemas masivamente paralelos

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    RESUMEN Los sistemas heterogéneos son cada vez más relevantes, debido a sus capacidades de rendimiento y eficiencia energética, estando presentes en todo tipo de plataformas de cómputo, desde dispositivos embebidos y servidores, hasta nodos HPC de grandes centros de datos. Su complejidad hace que sean habitualmente usados bajo el paradigma de tareas y el modelo de programación host-device. Esto penaliza fuertemente el aprovechamiento de los aceleradores y el consumo energético del sistema, además de dificultar la adaptación de las aplicaciones. La co-ejecución permite que todos los dispositivos cooperen para computar el mismo problema, consumiendo menos tiempo y energía. No obstante, los programadores deben encargarse de toda la gestión de los dispositivos, la distribución de la carga y la portabilidad del código entre sistemas, complicando notablemente su programación. Esta tesis ofrece contribuciones para mejorar el rendimiento y la eficiencia energética en estos sistemas masivamente paralelos. Se realizan propuestas que abordan objetivos generalmente contrapuestos: se mejora la usabilidad y la programabilidad, a la vez que se garantiza una mayor abstracción y extensibilidad del sistema, y al mismo tiempo se aumenta el rendimiento, la escalabilidad y la eficiencia energética. Para ello, se proponen dos motores de ejecución con enfoques completamente distintos. EngineCL, centrado en OpenCL y con una API de alto nivel, favorece la máxima compatibilidad entre todo tipo de dispositivos y proporciona un sistema modular extensible. Su versatilidad permite adaptarlo a entornos para los que no fue concebido, como aplicaciones con ejecuciones restringidas por tiempo o simuladores HPC de dinámica molecular, como el utilizado en un centro de investigación internacional. Considerando las tendencias industriales y enfatizando la aplicabilidad profesional, CoexecutorRuntime proporciona un sistema flexible centrado en C++/SYCL que dota de soporte a la co-ejecución a la tecnología oneAPI. Este runtime acerca a los programadores al dominio del problema, posibilitando la explotación de estrategias dinámicas adaptativas que mejoran la eficiencia en todo tipo de aplicaciones.ABSTRACT Heterogeneous systems are becoming increasingly relevant, due to their performance and energy efficiency capabilities, being present in all types of computing platforms, from embedded devices and servers to HPC nodes in large data centers. Their complexity implies that they are usually used under the task paradigm and the host-device programming model. This strongly penalizes accelerator utilization and system energy consumption, as well as making it difficult to adapt applications. Co-execution allows all devices to simultaneously compute the same problem, cooperating to consume less time and energy. However, programmers must handle all device management, workload distribution and code portability between systems, significantly complicating their programming. This thesis offers contributions to improve performance and energy efficiency in these massively parallel systems. The proposals address the following generally conflicting objectives: usability and programmability are improved, while ensuring enhanced system abstraction and extensibility, and at the same time performance, scalability and energy efficiency are increased. To achieve this, two runtime systems with completely different approaches are proposed. EngineCL, focused on OpenCL and with a high-level API, provides an extensible modular system and favors maximum compatibility between all types of devices. Its versatility allows it to be adapted to environments for which it was not originally designed, including applications with time-constrained executions or molecular dynamics HPC simulators, such as the one used in an international research center. Considering industrial trends and emphasizing professional applicability, CoexecutorRuntime provides a flexible C++/SYCL-based system that provides co-execution support for oneAPI technology. This runtime brings programmers closer to the problem domain, enabling the exploitation of dynamic adaptive strategies that improve efficiency in all types of applications.Funding: This PhD has been supported by the Spanish Ministry of Education (FPU16/03299 grant), the Spanish Science and Technology Commission under contracts TIN2016-76635-C2-2-R and PID2019-105660RB-C22. This work has also been partially supported by the Mont-Blanc 3: European Scalable and Power Efficient HPC Platform based on Low-Power Embedded Technology project (G.A. No. 671697) from the European Union’s Horizon 2020 Research and Innovation Programme (H2020 Programme). Some activities have also been funded by the Spanish Science and Technology Commission under contract TIN2016-81840-REDT (CAPAP-H6 network). The Integration II: Hybrid programming models of Chapter 4 has been partially performed under the Project HPC-EUROPA3 (INFRAIA-2016-1-730897), with the support of the EC Research Innovation Action under the H2020 Programme. In particular, the author gratefully acknowledges the support of the SPMT Department of the High Performance Computing Center Stuttgart (HLRS)

    Remote sensing of wetlands in the Lake Whangape catchment, Waikato, New Zealand.

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    Wetlands are among the world's most valuable ecosystems. They provide numerous ecological and socio-economic benefits. However, wetlands continue to disappear due to the increasing demand for wetland resources. In New Zealand, more than 90% of the original extent of wetlands has been lost since the mid-eighteenth century. Therefore, legislation has been identified for the protection of wetlands as a matter of national importance. Geographic Information System (GIS) and Remote Sensing (RS) techniques have proven helpful for mapping and monitoring wetland resources. This study aims to understand how RStechniques can classify wetlands in the Lake Whangape catchment, Waikato. The parameters that can be extracted from available data and their effectiveness in the classification process are also studied. Four types of input data are collectively employed in the study. The data types are optical RS data, Synthetic Aperture Radar (SAR) data, a Digital Elevation Model (DEM), and wetland polygons provided by the Waikato Regional Council (WRC). All the steps including, accessing satellite scenes and data processing were performed within Google Earth Engine (GEE) computing platform using JavaScript language. The classification process for this study includes feature extraction, feature selection, model training, classification, and validation. Finally, the accuracy of the classification results is checked visually and statistically. The classification was carried out in two stages. In Stage one, open water, wetland, and non-wetland areas are classified (simple classification). The combined wetlands class is separated into marsh and swamp in the second stage (detailed classification). Based on the results, the Topographic Position Index (TPI) is the most influential parameter in identifying wetlands, while the Modified Normalized Water Index (MNDWI) successfully identifies open water. The overall accuracy reached 91% at the simple classification stage. However, the detailed classification results received comparatively low classification accuracies (the overall accuracy is 76%)

    The Rhetoric of Citizenship, Slavery, and Immigration: Fashioning a Language for Belonging in English Literature

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    With the rise of transnational migration, political factions ration the status of citizen against global diasporas, positioning citizenship as the primary space to assert opposition to hybrid forms of identity and multiculturalism. Simultaneously, however, contradictory ideals of inclusion compete using the same language, leading to confusions of citizenship rhetoric. This rhetoric—the vocabulary used to talk about citizenship, including in government legislation, in print and digital channels, and in everyday public life—obscures citizenship's deep normative divides, while exaggerating the nationalistic character of political membership. Located at the intersection of literary and citizenship studies, my dissertation constellates the literary text with issues of state governmentality and rhetorics of belonging in order to examine citizenship rhetoric from a literary perspective that is attentive to its affective and imaginary registers. Instead of citizenship as a form of rootedness, I foster a methodological approach that centres the role of movement—and in particular, the drive for authority over movement—in the imagining and practice of citizenship, in turn revealing the migratory and diasporic threads that underwrite modernity. While postcolonial and ethnicity studies have unravelled the complexity of national and ethnic belonging, my dissertation complements this existing scholarship by converging on citizenship rhetoric as a discursive formation shaped and altered by literature. I trace literature's role in configuring citizenship with sustained focus on Olaudah Equiano's The Interesting Narrative, Frances Burney's The Wanderer, Mary Shelley's travelogues and Frankenstein, Herman Melville's Benito Cereno, and Brian Friel's Translations. While historically rooted, this project is forward looking and considers how eighteenth and nineteenth century imaginings of the citizen still inform contemporary political practices

    A Genealogy of Consumer Surveillance: From the First Public Market to Eatons Department Store to Amazon

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    Consumer surveillance has intensified over time and across differing forms of consumption space and spatial arrangement, which in turn raises the question of what explains the historical changes in the modalities of consumer surveillance. Contemporary surveillance literatures focus primarily on the current phenomenon with little consideration of the historical processes upon which the changes in the scope and intensity of the modalities of consumer surveillance were made possible. My study employs Foucauldian genealogical methodology as a system of inquiry to map the historical transformation in the modalities of consumer surveillance, by utilizing archival records, across three different consumption spaces in key stages of retail development: the first regulatory public market in the Town of York during the pre-industrial period, Eatons department store in the industrial economy, and Amazon that coincided with the rise of information economy. Conversely, contemporary theories of surveillance generally approach the intensification question by focusing on the surveillance-space axis or surveillance-consumption axis, and the spatiality of consumer surveillance is reduced to Foucauldian disciplinary panopticon. Utilizing Foucaults theories of power and governmentality and his intriguing account of the role of space in the exercise of power, my genealogical project examines the intersection of surveillance-space-consumption to understand the intensification of consumer surveillance over time across the three spaces under study. In my genealogical project, I identify five key moments pertaining to differing modalities of consumer surveillance: marketization of space, standardization of consuming bodies, statistification of consumers, virtualization of consumption, and AI inhabitation in consumer spaces. My genealogical project demonstrates that spatiality and spatialization are a recurring issue in differing modalities of consumer surveillance over time. Yet, the spatial techniques have changed and become more complex to augment the scope and intensity of monitoring and gaining of new knowledge about consumers and consumption, as part of long-standing efforts to manage the unpredictable dynamics of consumer behaviour by attaining control over all aspects of consumers life
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