1,102 research outputs found
LIPIcs, Volume 251, ITCS 2023, Complete Volume
LIPIcs, Volume 251, ITCS 2023, Complete Volum
Advances and Applications of DSmT for Information Fusion. Collected Works, Volume 5
This ïŹfth volume on Advances and Applications of DSmT for Information Fusion collects theoretical and applied contributions of researchers working in different ïŹelds of applications and in mathematics, and is available in open-access. The collected contributions of this volume have either been published or presented after disseminating the fourth volume in 2015 in international conferences, seminars, workshops and journals, or they are new. The contributions of each part of this volume are chronologically ordered.
First Part of this book presents some theoretical advances on DSmT, dealing mainly with modiïŹed Proportional ConïŹict Redistribution Rules (PCR) of combination with degree of intersection, coarsening techniques, interval calculus for PCR thanks to set inversion via interval analysis (SIVIA), rough set classiïŹers, canonical decomposition of dichotomous belief functions, fast PCR fusion, fast inter-criteria analysis with PCR, and improved PCR5 and PCR6 rules preserving the (quasi-)neutrality of (quasi-)vacuous belief assignment in the fusion of sources of evidence with their Matlab codes.
Because more applications of DSmT have emerged in the past years since the apparition of the fourth book of DSmT in 2015, the second part of this volume is about selected applications of DSmT mainly in building change detection, object recognition, quality of data association in tracking, perception in robotics, risk assessment for torrent protection and multi-criteria decision-making, multi-modal image fusion, coarsening techniques, recommender system, levee characterization and assessment, human heading perception, trust assessment, robotics, biometrics, failure detection, GPS systems, inter-criteria analysis, group decision, human activity recognition, storm prediction, data association for autonomous vehicles, identiïŹcation of maritime vessels, fusion of support vector machines (SVM), Silx-Furtif RUST code library for information fusion including PCR rules, and network for ship classiïŹcation.
Finally, the third part presents interesting contributions related to belief functions in general published or presented along the years since 2015. These contributions are related with decision-making under uncertainty, belief approximations, probability transformations, new distances between belief functions, non-classical multi-criteria decision-making problems with belief functions, generalization of Bayes theorem, image processing, data association, entropy and cross-entropy measures, fuzzy evidence numbers, negator of belief mass, human activity recognition, information fusion for breast cancer therapy, imbalanced data classiïŹcation, and hybrid techniques mixing deep learning with belief functions as well
Second-Person Surveillance: Politics of User Implication in Digital Documentaries
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 Letâs Plays. I build on Michael Rothbergâs 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 âothersâ and, on the other, simulate oneâs own surveillant modes of observation or behavior to mirror it back to users and open up oneâs 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 userâs 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 FlĂŒchtlinge 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 userâs 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 inmatesâ 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 âoutsideâ 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 userâs 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 ânormalâ people. I argue that while these games show criminality to be a construct, they also utilize a racialized fear of the loss of oneâs 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 (JoĂ«l Ronez, Pierre Corbinais, and Ămilie F. Grenier 2019), How They Watch You (Nick Briz 2021), and Fairly Intelligentâą (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
WL meet VC
Recently, many works studied the expressive power of graph neural networks
(GNNs) by linking it to the -dimensional Weisfeiler--Leman algorithm
(). Here, the is a well-studied
heuristic for the graph isomorphism problem, which iteratively colors or
partitions a graph's vertex set. While this connection has led to significant
advances in understanding and enhancing GNNs' expressive power, it does not
provide insights into their generalization performance, i.e., their ability to
make meaningful predictions beyond the training set. In this paper, we study
GNNs' generalization ability through the lens of Vapnik--Chervonenkis (VC)
dimension theory in two settings, focusing on graph-level predictions. First,
when no upper bound on the graphs' order is known, we show that the bitlength
of GNNs' weights tightly bounds their VC dimension. Further, we derive an upper
bound for GNNs' VC dimension using the number of colors produced by the
. Secondly, when an upper bound on the graphs' order is
known, we show a tight connection between the number of graphs distinguishable
by the and GNNs' VC dimension. Our empirical study
confirms the validity of our theoretical findings.Comment: arXiv admin note: text overlap with arXiv:2206.1116
(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!)
(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!
Uncertainty in runtime verification : a survey
Runtime Verification can be defined as a collection of formal methods for studying the dynamic evaluation of execution traces against formal specifications. Aside from creating a monitor from specifications and building algorithms for the evaluation of the trace, the process of gathering events and making them available for the monitor and the communication between the system under analysis and the monitor are critical and important steps in the runtime verification process. In many situations and for a variety of reasons, the event trace could be incomplete or could contain imprecise events. When a missing or ambiguous event is detected, the monitor may be unable to deliver a sound verdict. In this survey, we review the literature dealing with the problem of monitoring with incomplete traces. We list the different causes of uncertainty that have been identified, and analyze their effect on the monitoring process. We identify and compare the different methods that have been proposed to perform monitoring on such traces, highlighting the advantages and drawbacks of each method
- âŠ