3,055 research outputs found

    Towards Neuromorphic Gradient Descent: Exact Gradients and Low-Variance Online Estimates for Spiking Neural Networks

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    Spiking Neural Networks (SNNs) are biologically-plausible models that can run on low-powered non-Von Neumann neuromorphic hardware, positioning them as promising alternatives to conventional Deep Neural Networks (DNNs) for energy-efficient edge computing and robotics. Over the past few years, the Gradient Descent (GD) and Error Backpropagation (BP) algorithms used in DNNs have inspired various training methods for SNNs. However, the non-local and the reverse nature of BP, combined with the inherent non-differentiability of spikes, represent fundamental obstacles to computing gradients with SNNs directly on neuromorphic hardware. Therefore, novel approaches are required to overcome the limitations of GD and BP and enable online gradient computation on neuromorphic hardware. In this thesis, I address the limitations of GD and BP with SNNs by proposing three algorithms. First, I extend a recent method that computes exact gradients with temporally-coded SNNs by relaxing the firing constraint of temporal coding and allowing multiple spikes per neuron. My proposed method generalizes the computation of exact gradients with SNNs and enhances the tradeoffs between performance and various other aspects of spiking neurons. Next, I introduce a novel alternative to BP that computes low-variance gradient estimates in a local and online manner. Compared to other alternatives to BP, the proposed method demonstrates an improved convergence rate and increased performance with DNNs. Finally, I combine these two methods and propose an algorithm that estimates gradients with SNNs in a manner that is compatible with the constraints of neuromorphic hardware. My empirical results demonstrate the effectiveness of the resulting algorithm in training SNNs without performing BP

    Climate Change and Critical Agrarian Studies

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    Climate change is perhaps the greatest threat to humanity today and plays out as a cruel engine of myriad forms of injustice, violence and destruction. The effects of climate change from human-made emissions of greenhouse gases are devastating and accelerating; yet are uncertain and uneven both in terms of geography and socio-economic impacts. Emerging from the dynamics of capitalism since the industrial revolution — as well as industrialisation under state-led socialism — the consequences of climate change are especially profound for the countryside and its inhabitants. The book interrogates the narratives and strategies that frame climate change and examines the institutionalised responses in agrarian settings, highlighting what exclusions and inclusions result. It explores how different people — in relation to class and other co-constituted axes of social difference such as gender, race, ethnicity, age and occupation — are affected by climate change, as well as the climate adaptation and mitigation responses being implemented in rural areas. The book in turn explores how climate change – and the responses to it - affect processes of social differentiation, trajectories of accumulation and in turn agrarian politics. Finally, the book examines what strategies are required to confront climate change, and the underlying political-economic dynamics that cause it, reflecting on what this means for agrarian struggles across the world. The 26 chapters in this volume explore how the relationship between capitalism and climate change plays out in the rural world and, in particular, the way agrarian struggles connect with the huge challenge of climate change. Through a huge variety of case studies alongside more conceptual chapters, the book makes the often-missing connection between climate change and critical agrarian studies. The book argues that making the connection between climate and agrarian justice is crucial

    Deteção de intrusões de rede baseada em anomalias

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    Dissertação de mestrado integrado em Eletrónica Industrial e ComputadoresAo longo dos últimos anos, a segurança de hardware e software tornou-se uma grande preocupação. À medida que a complexidade dos sistemas aumenta, as suas vulnerabilidades a sofisticadas técnicas de ataque têm proporcionalmente escalado. Frequentemente o problema reside na heterogenidade de dispositivos conectados ao veículo, tornando difícil a convergência da monitorização de todos os protocolos num único produto de segurança. Por esse motivo, o mercado requer ferramentas mais avançadas para a monitorizar ambientes críticos à vida humana, tais como os nossos automóveis. Considerando que existem várias formas de interagir com os sistemas de entretenimento do automóvel como o Bluetooth, o Wi-fi ou CDs multimédia, a necessidade de auditar as suas interfaces tornou-se uma prioridade, uma vez que elas representam um sério meio de aceeso à rede interna do carro. Atualmente, os mecanismos de segurança de um carro focam-se na monitotização da rede CAN, deixando para trás as tecnologias referidas e não contemplando os sistemas não críticos. Como exemplo disso, o Bluetooth traz desafios diferentes da rede CAN, uma vez que interage diretamente com o utilizador e está exposto a ataques externos. Uma abordagem alternativa para tornar o automóvel num sistema mais robusto é manter sob supervisão as comunicações que com este são estabelecidas. Ao implementar uma detecção de intrusão baseada em anomalias, esta dissertação visa analisar o protocolo Bluetooth no sentido de identificar interações anormais que possam alertar para uma situação fora dos padrões de utilização. Em última análise, este produto de software embebido incorpora uma grande margem de auto-aprendizagem, que é vital para enfrentar quaisquer ameaças desconhecidas e aumentar os níveis de segurança globais. Ao longo deste documento, apresentamos o estudo do problema seguido de uma metodologia alternativa que implementa um algoritmo baseado numa LSTM para prever a sequência de comandos HCI correspondentes a tráfego Bluetooth normal. Os resultados mostram a forma como esta abordagem pode impactar a deteção de intrusões nestes ambientes ao demonstrar uma grande capacidade para identificar padrões anómalos no conjunto de dados considerado.In the last few years, hardware and software security have become a major concern. As the systems’ complexity increases, its vulnerabilities to several sophisticated attack techniques have escalated likewise. Quite often, the problem lies in the heterogeneity of the devices connected to the vehicle, making it difficult to converge the monitoring systems of all existing protocols into one security product. Thereby, the market requires more refined tools to monitor life-risky environments such as personal vehicles. Considering that there are several ways to interact with the car’s infotainment system, such as Wi-fi, Bluetooth, or CD player, the need to audit these interfaces has become a priority as they represent a serious channel to reach the internal car network. Nowadays, security in car networks focuses on CAN bus monitoring, leaving behind the aforementioned technologies and not contemplating other non-critical systems. As an example of these concerns, Bluetooth brings different challenges compared to CAN as it interacts directly with the user, being exposed to external attacks. An alternative approach to converting modern vehicles and their set of computers into more robust systems is to keep track of established communications with them. By enforcing anomaly-based intrusion detection this dissertation aims to analyze the Bluetooth protocol to identify abnormal user interactions that may alert for a non conforming pattern. Ultimately, such embedded software product incorporates a self-learning edge, which is vital to face newly developed threats and increasing global security levels. Throughout this document, we present the study case followed by an alternative methodology that implements an LSTM based algorithm to predict a sequence of HCI commands corresponding to normal Bluetooth traffic. The results show how this approach can impact intrusion detection in such environments by expressing a high capability of identifying abnormal patterns in the considered data

    Second-Person Surveillance: Politics of User Implication in Digital Documentaries

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    This dissertation analyzes digital documentaries that utilize second-person address and roleplay to make users feel implicated in contemporary refugee crises, mass incarceration in the U.S., and state and corporate surveillances. Digital documentaries are seemingly more interactive and participatory than linear film and video documentary as they are comprised of a variety of auditory, visual, and written media, utilize networked technologies, and turn the documentary audience into a documentary user. I draw on scholarship from documentary, game, new media, and surveillance studies to analyze how second-person address in digital documentaries is configured through user positioning and direct address within the works themselves, in how organizations and creators frame their productions, and in how users and players respond in reviews, discussion forums, and Let’s Plays. I build on Michael Rothberg’s theorization of the implicated subject to explore how these digital documentaries bring the user into complicated relationality with national and international crises. Visually and experientially implying that users bear responsibility to the subjects and subject matter, these works can, on the one hand, replicate modes of liberal empathy for suffering, distant “others” and, on the other, simulate one’s own surveillant modes of observation or behavior to mirror it back to users and open up one’s offline thoughts and actions as a site of critique. This dissertation charts how second-person address shapes and limits the political potentialities of documentary projects and connects them to a lineage of direct address from educational and propaganda films, museum exhibits, and serious games. By centralizing the user’s individual experience, the interventions that second-person digital documentaries can make into social discourse change from public, institution-based education to more privatized forms of sentimental education geared toward personal edification and self-realization. Unless tied to larger initiatives or movements, I argue that digital documentaries reaffirm a neoliberal politics of individual self-regulation and governance instead of public education or collective, social intervention. Chapter one focuses on 360-degree virtual reality (VR) documentaries that utilize the feeling of presence to position users as if among refugees and as witnesses to refugee experiences in camps outside of Europe and various dwellings in European cities. My analysis of Clouds Over Sidra (Gabo Arora and Chris Milk 2015) and The Displaced (Imraan Ismail and Ben C. Solomon 2015) shows how these VR documentaries utilize observational realism to make believable and immersive their representations of already empathetic refugees. The empathetic refugee is often young, vulnerable, depoliticized and dehistoricized and is a well-known trope in other forms of humanitarian media that continues into VR documentaries. Forced to Flee (Zahra Rasool 2017), I am Rohingya (Zahra Rasool 2017), So Leben Flüchtlinge in Berlin (Berliner Morgenpost 2017), and Limbo: A Virtual Experience of Waiting for Asylum (Shehani Fernando 2017) disrupt easy immersions into realistic-looking VR experiences of stereotyped representations and user identifications and, instead, can reflect back the user’s political inaction and surveillant modes of looking. Chapter two analyzes web- and social media messenger-based documentaries that position users as outsiders to U.S. mass incarceration. Users are noir-style co-investigators into the crime of the prison-industrial complex in Fremont County, Colorado in Prison Valley: The Prison Industry (David Dufresne and Philippe Brault 2009) and co-riders on a bus transporting prison inmates’ loved ones for visitations to correctional facilities in Upstate New York in A Temporary Contact (Nirit Peled and Sara Kolster 2017). Both projects construct an experience of carceral constraint for users to reinscribe seeming “outside” places, people, and experiences as within the continuation of the racialized and classed politics of state control through mass incarceration. These projects utilize interfaces that create a tension between replicating an exploitative hierarchy between non-incarcerated users and those subject to mass incarceration while also de-immersing users in these experiences to mirror back the user’s supposed distance from this mode of state regulation. Chapter three investigates a type of digital game I term dataveillance simulation games, which position users as surveillance agents in ambiguously dystopian nation-states and force users to use their own critical thinking and judgment to construct the criminality of state-sanctioned surveillance targets. Project Perfect Citizen (Bad Cop Studios 2016), Orwell: Keeping an Eye on You (Osmotic Studios 2016), and Papers, Please (Lucas Pope 2013) all create a dual empathy: players empathize with bureaucratic surveillance agents while empathizing with surveillance targets whose emails, text messages, documents, and social media profiles reveal them to be “normal” people. I argue that while these games show criminality to be a construct, they also utilize a racialized fear of the loss of one’s individual privacy to make players feel like they too could be surveillance targets. Chapter four examines personalized digital documentaries that turn users and their data into the subject matter. Do Not Track (Brett Gaylor 2015), A Week with Wanda (Joe Derry Hall 2019), Stealing Ur Feelings (Noah Levenson 2019), Alfred Premium (Joël Ronez, Pierre Corbinais, and Émilie F. Grenier 2019), How They Watch You (Nick Briz 2021), and Fairly Intelligent™ (A.M. Darke 2021) track, monitor, and confront users with their own online behavior to reflect back a corporate surveillance that collects, analyzes, and exploits user data for profit. These digital documentaries utilize emotional fear- and humor-based appeals to persuade users that these technologies are controlling them, shaping their desires and needs, and dehumanizing them through algorithmic surveillance

    Automated and foundational verification of low-level programs

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    Formal verification is a promising technique to ensure the reliability of low-level programs like operating systems and hypervisors, since it can show the absence of whole classes of bugs and prevent critical vulnerabilities. However, to realize the full potential of formal verification for real-world low-level programs one has to overcome several challenges, including: (1) dealing with the complexities of realistic models of real-world programming languages; (2) ensuring the trustworthiness of the verification, ideally by providing foundational proofs (i.e., proofs that can be checked by a general-purpose proof assistant); and (3) minimizing the manual effort required for verification by providing a high degree of automation. This dissertation presents multiple projects that advance formal verification along these three axes: RefinedC provides the first approach for verifying C code that combines foundational proofs with a high degree of automation via a novel refinement and ownership type system. Islaris shows how to scale verification of assembly code to realistic models of modern instruction set architectures-in particular, Armv8-A and RISC-V. DimSum develops a decentralized approach for reasoning about programs that consist of components written in multiple different languages (e.g., assembly and C), as is common for low-level programs. RefinedC and Islaris rest on Lithium, a novel proof engine for separation logic that combines automation with foundational proofs.Formale Verifikation ist eine vielversprechende Technik, um die Verlässlichkeit von grundlegenden Programmen wie Betriebssystemen sicherzustellen. Um das volle Potenzial formaler Verifikation zu realisieren, müssen jedoch mehrere Herausforderungen gemeistert werden: Erstens muss die Komplexität von realistischen Modellen von Programmiersprachen wie C oder Assembler gehandhabt werden. Zweitens muss die Vertrauenswürdigkeit der Verifikation sichergestellt werden, idealerweise durch maschinenüberprüfbare Beweise. Drittens muss die Verifikation automatisiert werden, um den manuellen Aufwand zu minimieren. Diese Dissertation präsentiert mehrere Projekte, die formale Verifikation entlang dieser Achsen weiterentwickeln: RefinedC ist der erste Ansatz für die Verifikation von C Code, der maschinenüberprüfbare Beweise mit einem hohen Grad an Automatisierung vereint. Islaris zeigt, wie die Verifikation von Assembler zu realistischen Modellen von modernen Befehlssatzarchitekturen wie Armv8-A oder RISC-V skaliert werden kann. DimSum entwickelt einen neuen Ansatz für die Verifizierung von Programmen, die aus Komponenten in mehreren Programmiersprachen bestehen (z.B., C und Assembler), wie es oft bei grundlegenden Programmen wie Betriebssystemen der Fall ist. RefinedC und Islaris basieren auf Lithium, eine neue Automatisierungstechnik für Separationslogik, die maschinenüberprüfbare Beweise und Automatisierung verbindet.This research was supported in part by a Google PhD Fellowship, in part by awards from Android Security's ASPIRE program and from Google Research, and in part by a European Research Council (ERC) Consolidator Grant for the project "RustBelt", funded under the European Union’s Horizon 2020 Framework Programme (grant agreement no. 683289)

    The Politics of Platformization: Amsterdam Dialogues on Platform Theory

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    What is platformization and why is it a relevant category in the contemporary political landscape? How is it related to cybernetics and the history of computation? This book tries to answer such questions by engaging in multidisciplinary dialogues about the first ten years of the emerging fields of platform studies and platform theory. It deploys a narrative and playful approach that makes use of anecdotes, personal histories, etymologies, and futurable speculations to investigate both the fragmented genealogy that led to platformization and the organizational and economic trends that guide nowadays platform sociotechnical imaginaries

    Post-Global Aesthetics

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    Phenomena such as the Covid-19 pandemic, climate change, or the surge of political populism show that the current phase of accelerated globalization is over. New concepts are needed in order to respond to this exhaustion of the global project: the volume scrutinizes these responses in the aesthetic realm and under a "post-global" banner, while incorporating alternative, non-Western epistemologies and literatures of the post-colonial Global South

    (b2023 to 2014) The UNBELIEVABLE similarities between the ideas of some people (2006-2016) and my ideas (2002-2008) in physics (quantum mechanics, cosmology), cognitive neuroscience, philosophy of mind, and philosophy (this manuscript would require a REVOLUTION in international academy environment!)

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    (b2023 to 2014) The UNBELIEVABLE similarities between the ideas of some people (2006-2016) and my ideas (2002-2008) in physics (quantum mechanics, cosmology), cognitive neuroscience, philosophy of mind, and philosophy (this manuscript would require a REVOLUTION in international academy environment!

    University of Windsor Graduate Calendar 2023 Spring

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    https://scholar.uwindsor.ca/universitywindsorgraduatecalendars/1027/thumbnail.jp

    Forested Watersheds and Water Supply: Exploring Effects of Wildfires, Silviculture, and Climate Change on Downstream Waters

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    Drinking water supplies for much of society originate in forests. To preserve the capability of these forests to produce clean and easily treatable water, source water supply and protection strategies focus in particular on potential disturbances to the landscape, which include prescribed forest harvesting and wildfires of varying intensity. While decades of work have revealed relationships between forest harvesting and stream flow response, there is a considerable lack of synthesis disentangling the interactions of climate, wildfires, stream flow, and water quality. Revealing the mechanisms for impacts on downstream waters after disturbances of harvesting and wildfire will greatly improve land and water management. In this dissertation, I combined synthesis of previously published or available data, novel mathematical analyses, and deterministic modeling to disentangle various disturbance effects and further our understanding of processes in forested watersheds. I broadly sought to explore how streamflow and water quality change after forest disturbances, and how new methods and analyses can provide insight into the biogeochemical and ecohydrologic processes changing during disturbances. First, I examined the effect of wildfire on hydrology, and developed a novel Budyko decomposition method to separate climatic and disturbance effects on streamflow. Using a set of 17 watersheds in southern California, I showed that while traditional metrics like changes in flow or runoff ratio might not detect a disturbance effect from wildfire due to confounding climate signals, the Budyko framework can be used successfully for statistical change detection. The method was used to estimate hydrologic recovery timescales that varied between 5 and 45 years, with an increase of about 4 years of recovery time per 10% of the watershed burned. Next, in Chapter 3 I used a meta-analysis approach to examine the effect of wildfire on water quality, using data from 121 catchments around the world. Analyzing the changes in concentrations of stream water nutrients, including carbon, nitrogen, and phosphorus, I showed that concentrations generally increased after fire. While a large amount of variability existed in the data, we found concurrent increases in the constituents after fire highlighting tight coupling of the biogeochemical cycles. Most interestingly, we found fire to increase the concentrations of biologically active nutrients like nitrate and phosphate at a greater rate than total nitrogen and phosphorus, with median increases of 40-60% in the nitrate to TN, and SRP to TP ratios. Next, I conducted an analysis of both water quality and hydrology together after fire in Chapter 4, using a set of 29 wildfire-impacted watersheds in the United States. Concentration-discharge relationships can be used to reveal pathways and sources of elements exported from watersheds, and my overall hypothesis was that these relationships change in post-fire landscapes. I developed a new methodology, using k-means clustering, to classify watersheds as chemostatic, dilution, mobilization and chemodynamic, and explored how their position within the cluster changed in post-fire landscapes. I found that the behavior of nitrate and ammonium was increasingly chemostatic after fire, while behavior of total nitrogen, phosphorus, and organic phosphorus was increasingly mobilizing after fire. Finally, I developed a coupled hydrology-vegetation-biogeochemistry model to simulate and elucidate processes controlling the impact of harvesting on downstream waters. I focused on the Turkey Lakes watershed where a significant amount of data has been collected on vegetation and soil nutrient dynamics, in addition to traditional streamflow and water quality metrics, and developed a novel multi-part calibration process that used measured data on stream, forest, and soil characteristics and dynamics. Future work would involve using the model to explore the data driven relationships that have been developed in the earlier chapters of the paper. The work presented in this dissertation highlights new small and large-scale relationships between disturbances in forested watersheds and effects on downstream waters. With more threats predicted to escalate and overlap in the coming years, the novel results and methodologies that I have presented here should contribute to improving land and water management
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