186 research outputs found
Spaces in-between: a transitional inquiry into transitionality
Working between the philosophy of Deleuze and Guattari and the psychoanalysis of
Winnicott, through stories and creative writing, I create new concepts and understandings of
the notion of assemblages. This thesis is a playful exploration of experiences, thinking with
theory, making a creative-relational inquiry.
Moving between the refrain and the transitional object, I work with the idea of a transitional
inquiry: between the internal and external, between the conscious and unconscious,
producing something-in-the-world. Even though it is personal, this type of inquiry de-centres
the notion of the subject to include objects, machines, and the creation of territories as
fundamental aspects to understand human processes.
One of the main contributions of working with Deleuze, Guattari, and Winnicott is to think
the transitional object together with the refrain and propose a holding-machine to help other
machines develop and process assemblages. This concept emerges while working with stories
of trauma, understanding them as moments where the subject cannot process events and
affects.
This exploration is about spaces in-between, spaces that are not entirely what they are, as
they move between the created and the discovered, between the intensities and extensions,
fantasy, and reality
INNOVATIVE DIGITAL START-UPS AND THEIR VENTURE CREATION PROCESS WITH ENABLING DIGITAL PLATFORMS
Start-ups have gained media attention since Google, Facebook and Amazon were launched in the 1990s. The book Lean Start-up, published in 2011, was another important milestone for digital start-up literature. As unicorn companies emerge around the world, topics highlighted in the news include the vast amount of capital that digital start-ups are raising, the ways in which these digital ventures are disrupting industries, and their global impact on digital economy. However, digital start-ups, digital venture ideas, and their venture creation process lack a unified venture creation model, as there is a gap in the re-search on entrepreneurial processes in a digital context. This research is an explorative study of the venture creation process of innovative digital start-ups that examines what is missing from entrepreneurial process models in a digital technology context and investi-gates how early stage digital start-ups conduct the venture creation process, starting with the pre-phase of antecedents and ending with the launch and scaling of the venture.
The research proposes a novel process model of innovative digital start-up venture crea-tion and describes the nature and patterns of the process. A conceptual model was devel-oped based on the entrepreneurship, information systems, and digital innovation litera-ture and empirically assessed with a multi-method qualitative research design. The data collected from semi-structured interviews, internet sources, and observation field notes covered 34 innovative digital start-ups and their founders. Interviews were conducted in-ternationally in high-ranking start-up ecosystems, and the data were analysed with the-matic analysis and fact-checked by triangulating internet data sources. The contribution to entrepreneurship theory is a new illustrative model of the venture creation process of innovative digital start-ups, including the emergent outcome of the process having a digi-tal artefact at its core (e.g., mobile apps, web-based solutions, digital platforms, software solutions, and digital ecosystems). Digital platforms and their multiple roles in the process are presented, as well as the role of critical events as moderators of the process which trigger new development cycles. During the venture creation process, the recombining of digital technologies, modules, and components enabled by digital infrastructures, plat-forms, and ecosystem partners represent digital technology affordances. This recombina-tion provides opportunities for asset-free development of digital venture ideas
Distributed Control and State Estimation of DC Microgrids Based on Constrained Communication Networks.
PhD ThesesThe intermittent nature of renewable energy sources (RES) such as wind turbines
and photovoltaic panels, requires advanced control systems to provide the
balance between energy supply and demand in any power system. For better
management of power quality and security issues, energy storage systems (ESSs)
are deployed to compensate for the temporary mismatch of supply and demand.
Furthermore, in rural areas with no connection to the main grid, ESSs such as
batteries are deployed in large quantities as a solution for temporary power stabilization
during RES unavailability. However, the control complexity of the
power system increases as more ESSs are getting installed due to the need for
coordination of the power transfer among them.
This thesis undertakes a thorough analysis of distributed control and state
estimation designs for direct current (DC) microgrids with ESSs based on constrained
communication networks. The developed distributed control and estimation
strategies are designed for operation over constrained communication
networks. They don't require a central coordinator for synchronization of the
control tasks between the ESSs. This forms a multi-agent environment where
the controllers cooperatively achieve the DC microgrid objectives, i.e. voltage
stabilization, proportional power-sharing, and balancing of ESSs' energy level.
To overcome the communication network constraints, event-based controllers
and estimators are designed, which e ectively reduce the network tra c and as
a result, provide higher throughput with reduced delays for the real-time control
loops of the DC microgrids. The controllers are designed to be distributed,
leading to use cases such as autonomous islanded microgrids, smart villages,
and plug-and-play mobile microgrids. The feasibility and performance of the
proposed control and estimation strategies are con rmed in several experimental
test benches by showing the higher reliability and robustness in the delivered
power quality. The results have shown considerable reduction in the network
tra c, meanwhile the control system provided high performance in terms of
stability, robustness, power quality and endurabilit
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Quantum Cognitively Motivated Context-Aware Multimodal Representation Learning for Human Language Analysis
A long-standing goal in the field of Artificial Intelligence (AI) is to develop systems that can perceive and understand human multimodal language. This requires both the consideration of context in the form of surrounding utterances in a conversation, i.e., context modelling, as well as the impact of different modalities (e.g., linguistic, visual acoustic), i.e., multimodal fusion. In the last few years, significant strides have been made towards the interpretation of human language due to simultaneous advancement in deep learning, data gathering and computing infrastructure. AI models have been investigated to either model interactions across distinct modalities, i.e., linguistic, visual and acoustic, or model interactions across parties in a conversation, achieving unprecedented levels of performance. However, AI models are often designed with only performance as their design target, leaving aside other essential factors such as transparency, interpretability, and how humans understand and reason about cognitive states.
In line with this observation, in this dissertation, we develop quantum probabilistic neural models and techniques that allow us to capture rational and irrational cognitive biases, without requiring a priori understanding and identification of them. First, we present a comprehensive empirical comparison of state-of-the-art (SOTA) modality fusion strategies for video sentiment analysis. The findings provide us helpful insights into the development of more effective modality fusion models incorporating quantum-inspired components. Second, we introduce an end-to-end complex-valued neural model for video sentiment analysis, simulating quantum procedural steps, outside of physics, into the neural network modelling paradigm. Third, we investigate non-classical correlations across different modalities. In particular, we describe a methodology to model interactions between image and text for an information retrieval scenario. The results provide us with theoretical and empirical insights to develop a transparent end-to-end probabilistic neural model for video emotion detection in conversations, capturing non-classical correlations across distinct modalities. Fourth, we introduce a theoretical framework to model user's cognitive states underlying their multimodal decision perspectives, and propose a methodology to capture interference of modalities in decision making.
Overall, we show that our models advance the SOTA on various affective analysis tasks, achieve high transparency due to the mapping to quantum physics meanings, and improve post-hoc interpretability, unearthing useful and explainable knowledge about cross-modal interactions
THE MANY WAYS OF WAKING UP FROM SLEEP - MOVING FORWARD THE ANALYSIS OF SLEEP MICROARCHITECTURE
One of the defining characteristics of sleep is that it is readily reversible towards wakefulness. This is exemplified in the common daily experience of waking up in the morning. My thesis studies sleep-wake transitions that are equally common and frequent, yet often not consciously perceived and neglected as random sleep perturbations of minor significance. Using mice as an experimental species, I find that healthy non-rapid-eye-movement sleep (NREMS), also named deep restorative sleep, is a dynamic brain state showing defined, periodically recurring moments of fragility. During these, diverse types of brief arousal-like events with various combinations of physiological correlates appear, including global or local cortical activation, muscle activity, and heart rate changes. Using a mice model of chronic neuropathic pain, I find that the rules I have identified in healthy sleep serve to identify previously unrecognized sleep disruptions that could contribute to sleep complaints of chronic pain patients. The experimental and analytical methods I have developed in these studies also helped in the identification of the neuronal basis of the fragility periods of NREM sleep. Together, my studies offer novel insights and analytical tools for the study of sleep-wake transitions and their perturbance in pathological conditions linked to sensory discomfort.
More specifically, my work departed from recent findings that NREMS in mice is divided in recurring periods of sleep fragility at frequencies ~0.02 Hz, characterized by heightened arousability. Through analyzing the temporal distribution of brief arousal events termed microarousals, I hypothesized that these fragility periods could serve a time raster for the probing of spontaneous sleep perturbations. Motivated by the question of how sensory discomfort caused by pain affects sleep, I have used the spared nerve injury (SNI) model, which consists in the injury of two of the 3 branches of the sciatic nerve. I found that the role of fragility periods in timing spontaneous arousals is highly useful to identify sleep disruptions not commonly detected with standard polysomnographic measures. Thus, by scrutinizing the fragility periods of NREMS in the SNI mice, I discovered an overrepresentation of a novel form of local perturbation within the hindlimb primary somatosensory cortex (S1HL), accompanied by heart rate increases. In addition, I showed that SNI animals woke up more frequently facing external stimuli, using closed-loop methods targeting specifically the fragility or continuity periods. These findings led me to propose that chronic pain-related sleep complaints may arise primarily from a perturbed arousability. The closed-loop techniques to probe arousability could be transferred to interrogate neuronal mechanisms underlying NREMS fragility, leading to the recognition that intrusion of wake-related activity into NREMS is a previously underappreciated mechanism controlling sleep fragility and architecture.
Overall, I present my thesis to advance the view on NREMS as a dynamic heterogeneous state of which insights into its neuronal mechanisms, and its physio- and pathophysiological manifestations in animal models should be key to formulate testable hypotheses aimed to cure the suffering of sleep disorder in human.
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Une des caractĂ©ristiques qui dĂ©finit le sommeil, est que lâon peut rapidement retourner Ă un Ă©tat dâĂ©veil. De fait, nous lâexpĂ©rimentons chaque matin au rĂ©veil. Ma thĂšse Ă©tudie les transitions sommeil-Ă©veil qui, bien que frĂ©quentes, sont souvent non consciemment perçues et traitĂ©es comme des perturbations sans importance et alĂ©atoires du sommeil. En utilisant la souris comme modĂšle expĂ©rimental, je montre que le sommeil sans mouvements rapides des yeux (NREMS), Ă©galement appelĂ© le sommeil profond et rĂ©parateur, est un Ă©tat cĂ©rĂ©bral dynamique composĂ© de pĂ©riodes discrĂštes et rĂ©currentes de fragilitĂ© face Ă des stimuli externe. Pendant celles-ci, plusieurs types dâĂ©vĂšnements associĂ©s Ă des Ă©veils brefs apparaissent, combinant activation corticale, activitĂ© musculaire et/ou une hausse des battements cardiaques. Je dĂ©montre que la comprĂ©hension des transitions sommeil-Ă©veil physiologiques sâavĂšre utile pour Ă©tudier le sommeil de souris souffrant de douleurs neuropathiques chroniques. Ces souris prĂ©sentent un nouveau type de perturbations locales lors du sommeil, qui pourraient possiblement expliquer une partie des plaintes de mauvais sommeil exprimĂ©es par les patients souffrant de douleurs chroniques. Les mĂ©thodes analytiques et expĂ©rimentales que jâai dĂ©veloppĂ©es dans ces Ă©tudes ont aussi aidĂ© Ă lâidentification des bases neuronales de la genĂšse des pĂ©riodes de fragilitĂ©s du sommeil NREM. En somme, mes Ă©tudes offrent des connaissances inĂ©dites et des mĂ©thodes dâanalyses pour lâĂ©tude des transitions sommeil-Ă©veil et de leurs perturbations en conditions pathologiques.
Une Ă©tude rĂ©cente du laboratoire a montrĂ© que le sommeil NREM est divisĂ© en pĂ©riodes de fragilitĂ© alternant avec des pĂ©riodes de non-fragilitĂ© (continuitĂ©), environ toutes les 50 secondes ce qui donne une frĂ©quence de 0.02 Hz. Les pĂ©riodes de fragilitĂ© sont caractĂ©risĂ©es par une hausse de « lâĂ©veillabilitĂ© » ou propension Ă sâĂ©veiller. Ma premiĂšre observation est que les Ă©veils brefs, couramment appelĂ©s micro-rĂ©veils, prĂ©sentent une distribution temporelle hautement restreinte aux pĂ©riodes de fragilitĂ©. Ainsi, jâai Ă©mis lâhypothĂšse que ces pĂ©riodes pourraient servir de moments spĂ©cialement choisis par le cerveau pour la mesure de potentielles perturbations spontanĂ©es. MotivĂ© par la question de comment les douleurs chroniques perturbent le sommeil, je lâai analysĂ© chez un modĂšle de souris de douleurs neuropathique, le modĂšle de dâĂ©pargne du nerf sural (SNI). Le rĂŽle des pĂ©riodes de fragilitĂ© Ă restreindre les micro- rĂ©veils sâest avĂ©rĂ© trĂšs utile pour dĂ©tecter de nouvelles formes de rĂ©action Ă des perturbations qui ne sont pas Ă©videntes par des analyses classiques du sommeil. En effet, spĂ©cifiquement pendant ces pĂ©riodes de fragilitĂ©, jâai dĂ©couvert une sur-reprĂ©sentation dâun nouveau type dâĂ©veil local confinĂ© au cortex somatosensoriel primaire et accompagnĂ© dâune hausse du rythme cardiaque. De plus, en utilisant de nouvelles mĂ©thodes basĂ©es sur des boucles-fermĂ©es, jâai dĂ©montrĂ© que les souris SNI se rĂ©veillaient plus frĂ©quemment que leurs contrĂŽles en faisant face Ă des stimuli externes. Sur la base de ces dĂ©couvertes, je propose que les plaintes de mauvais sommeil chez les patients souffrant de douleurs chroniques puissent prendre leur source dans une Ă©veillabilitĂ© perturbĂ©e. Les mĂ©thodes de boucles-fermĂ©es pour analyser lâĂ©veillabilitĂ© a aussi pu ĂȘtre transfĂ©rĂ©e pour lâĂ©tude optogĂ©nĂ©tique des mĂ©canismes neuronaux Ă la base de la fragilitĂ©
du sommeil NREM. Cela a menĂ© Ă la reconnaissance que lâintrusion dâactivitĂ© normalement associĂ©e Ă lâĂ©veil dans le sommeil est un mĂ©canisme de contrĂŽle de sa fragilitĂ© et de son architecture souvent ignorĂ© dans le domaine.
En somme, ma thĂšse permet une avancĂ©e de notre vision du sommeil NREM comme Ă©tant un Ă©tat dynamique et hĂ©tĂ©rogĂšne dont les mĂ©canismes neuronaux sous-jacent, en conditions normales et pathogĂ©niques, sont clefs pour la formulation dâhypothĂšses testables visant Ă la guĂ©rison des patients souffrant de troubles du sommeil
Recent Development of Hybrid Renewable Energy Systems
Abstract: The use of renewable energies continues to increase. However, the energy obtained from renewable resources is variable over time. The amount of energy produced from the renewable energy sources (RES) over time depends on the meteorological conditions of the region chosen, the season, the relief, etc. So, variable power and nonguaranteed energy produced by renewable sources implies intermittence of the grid. The key lies in supply sources integrated to a hybrid system (HS)
Leveraging Machine Learning Techniques towards Intelligent Networking Automation
In this thesis, we address some of the challenges that the Intelligent Networking Automation (INA) paradigm poses. Our goal is to design schemes leveraging Machine Learning (ML) techniques to cope with situations that involve hard decision-making actions. The proposed solutions are data-driven and consist of an agent that operates at network elements such as routers, switches, or network servers. The data are gathered from realistic scenarios, either actual network deployments or emulated environments. To evaluate the enhancements that the designed schemes provide, we compare our solutions to non-intelligent ones. Additionally, we assess the trade-off between the obtained improvements and the computational costs of implementing the proposed mechanisms.
Accordingly, this thesis tackles the challenges that four specific research problems present. The first topic addresses the problem of balancing traffic in dense Internet of Things (IoT) network scenarios where the end devices and the Base Stations (BSs) form complex networks. By applying ML techniques to discover patterns in the association between the end devices and the BSs, the proposed scheme can balance the traffic load in a IoT network to increase the packet delivery ratio and reduce the energy cost of data delivery. The second research topic proposes an intelligent congestion control for internet connections at edge network elements. The design includes a congestion predictor based on an Artificial Neural Network (ANN) and an Active Queue Management (AQM) parameter tuner. Similarly, the third research topic includes an intelligent solution to the inter-domain congestion. Different from second topic, this problem considers the preservation of the private network data by means of Federated Learning (FL), since network elements of several organizations participate in the intelligent process. Finally, the fourth research topic refers to a framework to efficiently gathering network telemetry (NT) data. The proposed solution considers a traffic-aware approach so that the NT is intelligently collected and transmitted by the network elements.
All the proposed schemes are evaluated through use cases considering standardized networking mechanisms. Therefore, we envision that the solutions of these specific problems encompass a set of methods that can be utilized in real-world scenarios towards the realization of the INA paradigm
Contributing to the development of social pedagogy in the UK: a case study at 'Santiago 1' residential care home in Spain
In recent years there has been a growing interest in social pedagogy in the UK,
much of which has focused on residential care for looked after children, a system
that has been under scrutiny over recent decades. Research carried out in other
European countries where social pedagogy is an established academic discipline
and profession, alongside pilot programmes, training courses and practical
initiatives in the UK, have shed light on what not that long ago was an unknown
field in this country. These European studies suggest that social pedagogical
approaches might potentially help to improve residential care in the UK.
This research aims to contribute to the development of social pedagogy in the UK
through the study of its practice in Spain, where there is a significant tradition in this
field. In order to do it, I have carried out a case study in a residential care institution
working to a social pedagogic approach named âSantiago 1â. In a time when the
tendency is to provide small family-like homes for children in care, Santiago 1 offers
an example of a big institution (around 100 residents in total) where education, both
in its more formal and informal versions, is at the core of their intervention. Through
this case study, I have sought to find how its practice can inform a
conceptualisation of social pedagogy and the possible implications of this for the
current residential care situation in the UK. I designed an inductive study, using
qualitative ethnographic methods (participant observation and semi-structured
interviews) for data collection, followed by a thematic data analysis. The findings
arguably make such desired contribution.
The findings confirm some of the notions and principles already existing in the
academic body of knowledge in the field of social pedagogy. However, they also
give insight into aspects that are frequently overlooked, such as creating an
educative intervention that goes beyond the target group to have an impact on the
community, and making use of group work and living as a cornerstone for the social
pedagogic intervention. These perspectives lead to a discussion in which I point out
the implications of trying to implement these social pedagogic ideas and practices
in the UK and argue for the need for several changes in the current residential care
system and the regulations that frame it that would be required in order to do so
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