10,348 research outputs found
Communicating Actor Automata -- Modelling Erlang Processes as Communicating Machines
Brand and Zafiropulo's notion of Communicating Finite-State Machines (CFSMs)
provides a succinct and powerful model of message-passing concurrency, based
around channels. However, a major variant of message-passing concurrency is not
readily captured by CFSMs: the actor model. In this work, we define a variant
of CFSMs, called Communicating Actor Automata, to capture the actor model of
concurrency as provided by Erlang: with mailboxes, from which messages are
received according to repeated application of pattern matching. Furthermore,
this variant of CFSMs supports dynamic process topologies, capturing common
programming idioms in the context of actor-based message-passing concurrency.
This gives a new basis for modelling, specifying, and verifying Erlang
programs. We also consider a class of CAAs that give rise to freedom from race
conditions.Comment: In Proceedings PLACES 2023, arXiv:2304.0543
The temporality of rhetoric: the spatialization of time in modern criticism
Every conception of criticism conceals a notion of time which informs the manner in which the critic conceives of history, representation and criticism itself. This thesis reveals the philosophies of time inherent in certain key modern critical concepts: allegory, irony and the sublime. Each concept opens a breach in time, a disruption of chronology. In each case this gap or aporia is emphatically closed, elided or denied. Taking the philosophy of time elaborated by Giorgio Agamben as an introductory proposition, my argument turns in Chapter One to the allegorical temporality which Walter Benjamin sees as the time of photography. The second chapter examines the aesthetics of the sublime as melancholic or mournful untimeliness. In Chapter Three, Paul de Man's conception of irony provides an exemplary instance of the denial of this troubling temporal predicament. In opposition to the foreclosure of the disturbing temporalities of criticism, history and representation, the thesis proposes a fundamental rethinking of the philosophy of time as it relates to these categories of reflection. In a reading of an inaugural meditation on the nature of time, and in examining certain key contemporary philosophical and critical texts, I argue for a critical attendance to that which eludes those modes of thought that attempt to map time as a recognizable and essentially spatial field. The Confessions of Augustine provide, in the fourth chapter, a model for thinking through the problems set up earlier: Augustine affords us, precisely, a means of conceiving of the gap or the interim. In the final chapter, this concept is developed with reference to the criticism of Arnold and Eliot, the fiction of Virginia Woolf and the philosophy of cinema derived from Deleuze and Lyotard. In conclusion, the philosophical implications of the thesis are placed in relation to a conception of the untimeliness of death
Recommended from our members
Co-design As Healing: Exploring The Experiences Of Participants Facing Mental Health Problems
This thesis is an exploration of the healing role of co-design in mental health. Although co-design projects conducted within mental health settings are rising, existing literature tends to focus on the object of design and its outcomes while the experiences of participants per se remain largely unexplored. The guiding research question of this study is not how we design things that improve mental health, but how co-designing, as an act, might do so.
The thesis presents two projects that were organized in collaboration with the mental health charity Islington Mind and the Psychosis Therapy Project (PTP) in London.
The project at Islington Mind used a structured design process inviting participants to design for wellbeing. A case study analysis provides insights on how participants were impacted, summarizing key challenges and opportunities.
The design at PTP worked towards creating a collective brief in an emergent fashion, finally culminating in a board game. The experiences of participants were explored through Interpretative Phenomenological Analysis (IPA), using semi-structured interview data. The analysis served to identify key themes characterising the experience of co-design such as contributing, connecting, thinking and intentioning. In addition, a mixed-methods analysis of questionnaires and interview data exploring participants' wellbeing, showed that all participants who engaged fairly consistently in the project improved after the project ended, although some participants' scores returned to baseline six months later.
Reflecting on both projects, an approach to facilitation within mental health is outlined, detailing how the dimensions of weaving and layered participation, nurturing mattering and facilitating attitudes interlace. This contribution raises awareness of tacit dimensions in the practice of facilitation, articulating the nuances of how to encourage and sustain meaningful and ethical engagement and offering insights into a range of tools. It highlights the importance of remaining reflexive in relation to attitudes and emotions and discusses practical methodological and ethical challenges and ways to resolve them which can be of benefit to researchers embarking on a similar journey.
The thesis also offers detailed insights on how methodologies from different fields were integrated into a whole, arguing for transparency and reflexivity about epistemological assumptions, and how underlying paradigms shift in an interdisciplinary context.
Based on the overall findings, the thesis makes a case for considering design as healing (or a designerly way of healing), highlighting implications at a systems, social and individual level. It makes an original contribution to our understanding of design, highlighting its healing character, and proposes a new way to support mental health. The participants in this study not only had increased their own wellbeing through co-designing, but were also empowered and contributed towards healing the world. Hence, the thesis argues for a unique, holistic perspective of design and mental health, recognizing the interconnectedness of the individual, social and systemic dimensions of the healing processes that are ignited
TOWARDS AN UNDERSTANDING OF EFFORTFUL FUNDRAISING EXPERIENCES: USING INTERPRETATIVE PHENOMENOLOGICAL ANALYSIS IN FUNDRAISING RESEARCH
Physical-activity oriented community fundraising has experienced an exponential growth in popularity over the past 15 years. The aim of this study was to explore the value of effortful fundraising experiences, from the point of view of participants, and explore the impact that these experiences have on peopleâs lives. This study used an IPA approach to interview 23 individuals, recognising the role of participants as proxy (nonprofessional) fundraisers for charitable organisations, and the unique organisation donor dynamic that this creates. It also bought together relevant psychological theory related to physical activity fundraising experiences (through a narrative literature review) and used primary interview data to substantiate these. Effortful fundraising experiences are examined in detail to understand their significance to participants, and how such experiences influence their connection with a charity or cause. This was done with an idiographic focus at first, before examining convergences and divergences across the sample. This study found that effortful fundraising experiences can have a profound positive impact upon community fundraisers in both the short and the long term. Additionally, it found that these experiences can be opportunities for charitable organisations to create lasting meaningful relationships with participants, and foster mutually beneficial lifetime relationships with them. Further research is needed to test specific psychological theory in this context, including self-esteem theory, self determination theory, and the martyrdom effect (among others)
'Exarcheia doesn't exist': Authenticity, Resistance and Archival Politics in Athens
My thesis investigates the ways people, materialities and urban spaces interact to form affective ecologies and produce historicity. It focuses on the neighbourhood of Exarcheia, Athensâ contested political topography par excellence, known for its production of radical politics of discontent and resistance to state oppression and eoliberal capitalism. Embracing Exarcheiaâs controversial status within Greek vernacular, media and state discourses, this thesis aims to unpick the neighbourhoodsâ socio-spatial assemblage imbued with affect and formed through the numerous (mis)understandings and (mis)interpretations rooted in its turbulent political history. Drawing on theory on urban spaces, affect, hauntology and archival politics, I argue for Exarcheia as an unwavering archival space composed of affective chronotopes â (in)tangible loci that defy space and temporality. I posit that the interwoven narratives and materialities emerging in my fieldwork are persistently â and perhaps obsessively â reiterating themselves and remaining imprinted on the neighbourhoodâs landscape as an incessant reminder of violent histories that the state often seeks to erase and forget. Through this analysis, I contribute to understandings of place as a primary ethnographic âobjectâ and the ways in which place forms complex interactions and relationships with social actors, shapes their subjectivities, retains and bestows their memories and senses of historicity
From wallet to mobile: exploring how mobile payments create customer value in the service experience
This study explores how mobile proximity payments (MPP) (e.g., Apple Pay) create customer value in the service experience compared to traditional payment methods (e.g. cash and card). The main objectives were firstly to understand how customer value manifests as an outcome in the MPP service experience, and secondly to understand how the customer activities in the process of using MPP create customer value. To achieve these objectives a conceptual framework is built upon the Grönroos-Voima Value Model (Grönroos and Voima, 2013), and uses the Theory of Consumption Value (Sheth et al., 1991) to determine the customer value constructs for MPP, which is complimented with Script theory (Abelson, 1981) to determine the value creating activities the consumer does in the process of paying with MPP.
The study uses a sequential exploratory mixed methods design, wherein the first qualitative stage uses two methods, self-observations (n=200) and semi-structured interviews (n=18). The subsequent second quantitative stage uses an online survey (n=441) and Structural Equation Modelling analysis to further examine the relationships and effect between the value creating activities and customer value constructs identified in stage one. The academic contributions include the development of a model of mobile payment services value creation in the service experience, introducing the concept of in-use barriers which occur after adoption and constrains the consumers existing use of MPP, and revealing the importance of the mobile in-hand momentary condition as an antecedent state. Additionally, the customer value perspective of this thesis demonstrates an alternative to the dominant Information Technology approaches to researching mobile payments and broadens the view of technology from purely an object a user interacts with to an object that is immersed in consumersâ daily life
The Adirondack Chronology
The Adirondack Chronology is intended to be a useful resource for researchers and others interested in the Adirondacks and Adirondack history.https://digitalworks.union.edu/arlpublications/1000/thumbnail.jp
Foundations for programming and implementing effect handlers
First-class control operators provide programmers with an expressive and efficient
means for manipulating control through reification of the current control state as a first-class object, enabling programmers to implement their own computational effects and
control idioms as shareable libraries. Effect handlers provide a particularly structured
approach to programming with first-class control by naming control reifying operations
and separating from their handling.
This thesis is composed of three strands of work in which I develop operational
foundations for programming and implementing effect handlers as well as exploring
the expressive power of effect handlers.
The first strand develops a fine-grain call-by-value core calculus of a statically
typed programming language with a structural notion of effect types, as opposed to the
nominal notion of effect types that dominates the literature. With the structural approach,
effects need not be declared before use. The usual safety properties of statically typed
programming are retained by making crucial use of row polymorphism to build and
track effect signatures. The calculus features three forms of handlers: deep, shallow,
and parameterised. They each offer a different approach to manipulate the control state
of programs. Traditional deep handlers are defined by folds over computation trees,
and are the original con-struct proposed by Plotkin and Pretnar. Shallow handlers are
defined by case splits (rather than folds) over computation trees. Parameterised handlers
are deep handlers extended with a state value that is threaded through the folds over
computation trees. To demonstrate the usefulness of effects and handlers as a practical
programming abstraction I implement the essence of a small UNIX-style operating
system complete with multi-user environment, time-sharing, and file I/O.
The second strand studies continuation passing style (CPS) and abstract machine
semantics, which are foundational techniques that admit a unified basis for implementing deep, shallow, and parameterised effect handlers in the same environment. The
CPS translation is obtained through a series of refinements of a basic first-order CPS
translation for a fine-grain call-by-value language into an untyped language. Each refinement moves toward a more intensional representation of continuations eventually
arriving at the notion of generalised continuation, which admit simultaneous support for
deep, shallow, and parameterised handlers. The initial refinement adds support for deep
handlers by representing stacks of continuations and handlers as a curried sequence of
arguments. The image of the resulting translation is not properly tail-recursive, meaning some function application terms do not appear in tail position. To rectify this the
CPS translation is refined once more to obtain an uncurried representation of stacks
of continuations and handlers. Finally, the translation is made higher-order in order to
contract administrative redexes at translation time. The generalised continuation representation is used to construct an abstract machine that provide simultaneous support for
deep, shallow, and parameterised effect handlers. kinds of effect handlers.
The third strand explores the expressiveness of effect handlers. First, I show that
deep, shallow, and parameterised notions of handlers are interdefinable by way of typed
macro-expressiveness, which provides a syntactic notion of expressiveness that affirms
the existence of encodings between handlers, but it provides no information about the
computational content of the encodings. Second, using the semantic notion of expressiveness I show that for a class of programs a programming language with first-class
control (e.g. effect handlers) admits asymptotically faster implementations than possible in a language without first-class control
Socio-endocrinology revisited: New tools to tackle old questions
Animalsâ social environments impact their health and survival, but the proximate links between sociality and fitness are still not fully understood. In this thesis, I develop and apply new approaches to address an outstanding question within this sociality-fitness link: does grooming (a widely studied, positive social interaction) directly affect glucocorticoid concentrations (GCs; a group of steroid hormones indicating physiological stress) in a wild primate? To date, negative, long-term correlations between grooming and GCs have been found, but the logistical difficulties of studying proximate mechanisms in the wild leave knowledge gaps regarding the short-term, causal mechanisms that underpin this relationship. New technologies, such as collar-mounted tri-axial accelerometers, can provide the continuous behavioural data required to match grooming to non-invasive GC measures (Chapter 1). Using Chacma baboons (Papio ursinus) living on the Cape Peninsula, South Africa as a model system, I identify giving and receiving grooming using tri-axial accelerometers and supervised machine learning methods, with high overall accuracy (~80%) (Chapter 2). I then test what socio-ecological variables predict variation in faecal and urinary GCs (fGCs and uGCs) (Chapter 3). Shorter and rainy days are associated with higher fGCs and uGCs, respectively, suggesting that environmental conditions may impose stressors in the form of temporal bottlenecks. Indeed, I find that short days and days with more rain-hours are associated with reduced giving grooming (Chapter 4), and that this reduction is characterised by fewer and shorter grooming bouts. Finally, I test whether grooming predicts GCs, and find that while there is a long-term negative correlation between grooming and GCs, grooming in the short-term, in particular giving grooming, is associated with higher fGCs and uGCs (Chapter 5). I end with a discussion on how the new tools I applied have enabled me to advance our understanding of sociality and stress in primate social systems (Chapter 6)
Machine learning for managing structured and semi-structured data
As the digitalization of private, commercial, and public sectors advances rapidly, an increasing amount of data is becoming available. In order to gain insights or knowledge from these enormous amounts of raw data, a deep analysis is essential. The immense volume requires highly automated processes with minimal manual interaction. In recent years, machine learning methods have taken on a central role in this task. In addition to the individual data points, their interrelationships often play a decisive role, e.g. whether two patients are related to each other or whether they are treated by the same physician. Hence, relational learning is an important branch of research, which studies how to harness this explicitly available structural information between different data points. Recently, graph neural networks have gained importance. These can be considered an extension of convolutional neural networks from regular grids to general (irregular) graphs.
Knowledge graphs play an essential role in representing facts about entities in a machine-readable way. While great efforts are made to store as many facts as possible in these graphs, they often remain incomplete, i.e., true facts are missing. Manual verification and expansion of the graphs is becoming increasingly difficult due to the large volume of data and must therefore be assisted or substituted by automated procedures which predict missing facts. The field of knowledge graph completion can be roughly divided into two categories: Link Prediction and Entity Alignment. In Link Prediction, machine learning models are trained to predict unknown facts between entities based on the known facts. Entity Alignment aims at identifying shared entities between graphs in order to link several such knowledge graphs based on some provided seed alignment pairs.
In this thesis, we present important advances in the field of knowledge graph completion. For Entity Alignment, we show how to reduce the number of required seed alignments while maintaining performance by novel active learning techniques. We also discuss the power of textual features and show that graph-neural-network-based methods have difficulties with noisy alignment data. For Link Prediction, we demonstrate how to improve the prediction for unknown entities at training time by exploiting additional metadata on individual statements, often available in modern graphs. Supported with results from a large-scale experimental study, we present an analysis of the effect of individual components of machine learning models, e.g., the interaction function or loss criterion, on the task of link prediction. We also introduce a software library that simplifies the implementation and study of such components and makes them accessible to a wide research community, ranging from relational learning researchers to applied fields, such as life sciences. Finally, we propose a novel metric for evaluating ranking results, as used for both completion tasks. It allows for easier interpretation and comparison, especially in cases with different numbers of ranking candidates, as encountered in the de-facto standard evaluation protocols for both tasks.Mit der rasant fortschreitenden Digitalisierung des privaten, kommerziellen und öffentlichen Sektors werden immer gröĂere Datenmengen verfĂŒgbar. Um aus diesen enormen Mengen an Rohdaten Erkenntnisse oder Wissen zu gewinnen, ist eine tiefgehende Analyse unerlĂ€sslich. Das immense Volumen erfordert hochautomatisierte Prozesse mit minimaler manueller Interaktion. In den letzten Jahren haben Methoden des maschinellen Lernens eine zentrale Rolle bei dieser Aufgabe eingenommen. Neben den einzelnen Datenpunkten spielen oft auch deren ZusammenhĂ€nge eine entscheidende Rolle, z.B. ob zwei Patienten miteinander verwandt sind oder ob sie vom selben Arzt behandelt werden. Daher ist das relationale Lernen ein wichtiger Forschungszweig, der untersucht, wie diese explizit verfĂŒgbaren strukturellen Informationen zwischen verschiedenen Datenpunkten nutzbar gemacht werden können. In letzter Zeit haben Graph Neural Networks an Bedeutung gewonnen. Diese können als eine Erweiterung von CNNs von regelmĂ€Ăigen Gittern auf allgemeine (unregelmĂ€Ăige) Graphen betrachtet werden.
Wissensgraphen spielen eine wesentliche Rolle bei der Darstellung von Fakten ĂŒber EntitĂ€ten in maschinenlesbaren Form. Obwohl groĂe Anstrengungen unternommen werden, so viele Fakten wie möglich in diesen Graphen zu speichern, bleiben sie oft unvollstĂ€ndig, d. h. es fehlen Fakten. Die manuelle ĂberprĂŒfung und Erweiterung der Graphen wird aufgrund der groĂen Datenmengen immer schwieriger und muss daher durch automatisierte Verfahren unterstĂŒtzt oder ersetzt werden, die fehlende Fakten vorhersagen. Das Gebiet der WissensgraphenvervollstĂ€ndigung lĂ€sst sich grob in zwei Kategorien einteilen: Link Prediction und Entity Alignment. Bei der Link Prediction werden maschinelle Lernmodelle trainiert, um unbekannte Fakten zwischen EntitĂ€ten auf der Grundlage der bekannten Fakten vorherzusagen. Entity Alignment zielt darauf ab, gemeinsame EntitĂ€ten zwischen Graphen zu identifizieren, um mehrere solcher Wissensgraphen auf der Grundlage einiger vorgegebener Paare zu verknĂŒpfen.
In dieser Arbeit stellen wir wichtige Fortschritte auf dem Gebiet der VervollstĂ€ndigung von Wissensgraphen vor. FĂŒr das Entity Alignment zeigen wir, wie die Anzahl der benötigten Paare reduziert werden kann, wĂ€hrend die Leistung durch neuartige aktive Lerntechniken erhalten bleibt. Wir erörtern auch die LeistungsfĂ€higkeit von Textmerkmalen und zeigen, dass auf Graph-Neural-Networks basierende Methoden Schwierigkeiten mit verrauschten Paar-Daten haben. FĂŒr die Link Prediction demonstrieren wir, wie die Vorhersage fĂŒr unbekannte EntitĂ€ten zur Trainingszeit verbessert werden kann, indem zusĂ€tzliche Metadaten zu einzelnen Aussagen genutzt werden, die oft in modernen Graphen verfĂŒgbar sind. GestĂŒtzt auf Ergebnisse einer groĂ angelegten experimentellen Studie prĂ€sentieren wir eine Analyse der Auswirkungen einzelner Komponenten von Modellen des maschinellen Lernens, z. B. der Interaktionsfunktion oder des Verlustkriteriums, auf die Aufgabe der Link Prediction. AuĂerdem stellen wir eine Softwarebibliothek vor, die die Implementierung und Untersuchung solcher Komponenten vereinfacht und sie einer breiten Forschungsgemeinschaft zugĂ€nglich macht, die von Forschern im Bereich des relationalen Lernens bis hin zu angewandten Bereichen wie den Biowissenschaften reicht. SchlieĂlich schlagen wir eine neuartige Metrik fĂŒr die Bewertung von Ranking-Ergebnissen vor, wie sie fĂŒr beide Aufgaben verwendet wird. Sie ermöglicht eine einfachere Interpretation und einen leichteren Vergleich, insbesondere in FĂ€llen mit einer unterschiedlichen Anzahl von Kandidaten, wie sie in den de-facto Standardbewertungsprotokollen fĂŒr beide Aufgaben vorkommen
- âŠ