8,152 research outputs found
Colour technologies for content production and distribution of broadcast content
The requirement of colour reproduction has long been a priority driving the development of new colour imaging systems that maximise human perceptual plausibility. This thesis explores machine learning algorithms for colour processing to assist both content production and distribution. First, this research studies colourisation technologies with practical use cases in restoration and processing of archived content. The research targets practical deployable solutions, developing a cost-effective pipeline which integrates the activity of the producer into the processing workflow. In particular, a fully automatic image colourisation paradigm using Conditional GANs is proposed to improve content generalisation and colourfulness of existing baselines. Moreover, a more conservative solution is considered by providing references to guide the system towards more accurate colour predictions. A fast-end-to-end architecture is proposed to improve existing exemplar-based image colourisation methods while decreasing the complexity and runtime. Finally, the proposed image-based methods are integrated into a video colourisation pipeline. A general framework is proposed to reduce the generation of temporal flickering or propagation of errors when such methods are applied frame-to-frame. The proposed model is jointly trained to stabilise the input video and to cluster their frames with the aim of learning scene-specific modes. Second, this research explored colour processing technologies for content distribution with the aim to effectively deliver the processed content to the broad audience. In particular, video compression is tackled by introducing a novel methodology for chroma intra prediction based on attention models. Although the proposed architecture helped to gain control over the reference samples and better understand the prediction process, the complexity of the underlying neural network significantly increased the encoding and decoding time. Therefore, aiming at efficient deployment within the latest video coding standards, this work also focused on the simplification of the proposed architecture to obtain a more compact and explainable model
High-throughput Tools and Techniques to Investigate Environmental Effects on Aging Behaviors in Caenorhabditis elegans
Aging is modulated by genetic and environmental cues; however, it is difficult to study how these perturbations modulate the aging process in a robust, high-throughput manner. Methods to gather large-scale behavioral data for aging studies are labor-intensive, lack individual-level resolution, or lack precise spatiotemporal environmental control. In addition, tools to analyze large-scale behavioral data sets are difficult to scale, unable to be broadly applied across complex environments, or fail to detect subtle behavioral changes.
In this thesis I develop tools to enable robust, microfluidic culture and behavioral analysis of C. elegans to examine how environmental cues, such as dietary restriction, influence longevity and behavior with age. In Aim 1, I engineer a robust pipeline for the long-term longitudinal culture and behavioral monitoring of C. elegans in aging studies with precise spatiotemporal environmental control. In Aim 2, I develop a flexible deep learning based pipeline for detecting and extracting postural information from large-scale behavioral datasets across heterogeneous environments. In Aim 3, I characterize how the full behavioral repertoire of individuals change with age, along with examining how these age-related behavioral changes are modulated by different dietary restriction regimes. The completion of this thesis provides 1) a new toolset to robustly explore how genetic or environmental effects influence longevity and healthspan, 2) a flexible pipeline for analyzing large-scale behavioral data in C. elegans, and 3) insight into how environmental perturbations influence health through age-related changes in behavior.Ph.D
The Viability and Potential Consequences of IoT-Based Ransomware
With the increased threat of ransomware and the substantial growth of the Internet of Things (IoT) market, there is significant motivation for attackers to carry out IoT-based ransomware campaigns. In this thesis, the viability of such malware is tested.
As part of this work, various techniques that could be used by ransomware developers to attack commercial IoT devices were explored. First, methods that attackers could use to communicate with the victim were examined, such that a ransom note was able to be reliably sent to a victim. Next, the viability of using "bricking" as a method of ransom was evaluated, such that devices could be remotely disabled unless the victim makes a payment to the attacker. Research was then performed to ascertain whether it was possible to remotely gain persistence on IoT devices, which would improve the efficacy of existing ransomware methods, and provide opportunities for more advanced ransomware to be created. Finally, after successfully identifying a number of persistence techniques, the viability of privacy-invasion based ransomware was analysed.
For each assessed technique, proofs of concept were developed. A range of devices -- with various intended purposes, such as routers, cameras and phones -- were used to test the viability of these proofs of concept. To test communication hijacking, devices' "channels of communication" -- such as web services and embedded screens -- were identified, then hijacked to display custom ransom notes. During the analysis of bricking-based ransomware, a working proof of concept was created, which was then able to remotely brick five IoT devices. After analysing the storage design of an assortment of IoT devices, six different persistence techniques were identified, which were then successfully tested on four devices, such that malicious filesystem modifications would be retained after the device was rebooted. When researching privacy-invasion based ransomware, several methods were created to extract information from data sources that can be commonly found on IoT devices, such as nearby WiFi signals, images from cameras, or audio from microphones. These were successfully implemented in a test environment such that ransomable data could be extracted, processed, and stored for later use to blackmail the victim.
Overall, IoT-based ransomware has not only been shown to be viable but also highly damaging to both IoT devices and their users. While the use of IoT-ransomware is still very uncommon "in the wild", the techniques demonstrated within this work highlight an urgent need to improve the security of IoT devices to avoid the risk of IoT-based ransomware causing havoc in our society. Finally, during the development of these proofs of concept, a number of potential countermeasures were identified, which can be used to limit the effectiveness of the attacking techniques discovered in this PhD research
Anuário científico da Escola Superior de Tecnologia da Saúde de Lisboa - 2021
É com grande prazer que apresentamos a mais recente edição (a 11.ª) do Anuário Científico da Escola Superior de Tecnologia da Saúde de Lisboa. Como instituição de ensino superior, temos o compromisso de promover e incentivar a pesquisa científica em todas as áreas do conhecimento que contemplam a nossa missão. Esta publicação tem como objetivo divulgar toda a produção científica desenvolvida pelos Professores, Investigadores, Estudantes e Pessoal não Docente da ESTeSL durante 2021. Este Anuário é, assim, o reflexo do trabalho árduo e dedicado da nossa comunidade, que se empenhou na produção de conteúdo científico de elevada qualidade e partilhada com a Sociedade na forma de livros, capítulos de livros, artigos publicados em revistas nacionais e internacionais, resumos de comunicações orais e pósteres, bem como resultado dos trabalhos de 1º e 2º ciclo. Com isto, o conteúdo desta publicação abrange uma ampla variedade de tópicos, desde temas mais fundamentais até estudos de aplicação prática em contextos específicos de Saúde, refletindo desta forma a pluralidade e diversidade de áreas que definem, e tornam única, a ESTeSL. Acreditamos que a investigação e pesquisa científica é um eixo fundamental para o desenvolvimento da sociedade e é por isso que incentivamos os nossos estudantes a envolverem-se em atividades de pesquisa e prática baseada na evidência desde o início dos seus estudos na ESTeSL. Esta publicação é um exemplo do sucesso desses esforços, sendo a maior de sempre, o que faz com que estejamos muito orgulhosos em partilhar os resultados e descobertas dos nossos investigadores com a comunidade científica e o público em geral. Esperamos que este Anuário inspire e motive outros estudantes, profissionais de saúde, professores e outros colaboradores a continuarem a explorar novas ideias e contribuir para o avanço da ciência e da tecnologia no corpo de conhecimento próprio das áreas que compõe a ESTeSL. Agradecemos a todos os envolvidos na produção deste anuário e desejamos uma leitura inspiradora e agradável.info:eu-repo/semantics/publishedVersio
Dynamic Subspace Estimation with Grassmannian Geodesics
Dynamic subspace estimation, or subspace tracking, is a fundamental problem
in statistical signal processing and machine learning. This paper considers a
geodesic model for time-varying subspaces. The natural objective function for
this model is non-convex. We propose a novel algorithm for minimizing this
objective and estimating the parameters of the model from data with
Grassmannian-constrained optimization. We show that with this algorithm, the
objective is monotonically non-increasing. We demonstrate the performance of
this model and our algorithm on synthetic data, video data, and dynamic fMRI
data
A Decision Support System for Economic Viability and Environmental Impact Assessment of Vertical Farms
Vertical farming (VF) is the practice of growing crops or animals using the vertical dimension via multi-tier racks or vertically inclined surfaces. In this thesis, I focus on the emerging industry of plant-specific VF. Vertical plant farming (VPF) is a promising and relatively novel practice that can be conducted in buildings with environmental control and artificial lighting. However, the nascent sector has experienced challenges in economic viability, standardisation, and environmental sustainability. Practitioners and academics call for a comprehensive financial analysis of VPF, but efforts are stifled by a lack of valid and available data.
A review of economic estimation and horticultural software identifies a need for a decision support system (DSS) that facilitates risk-empowered business planning for vertical farmers. This thesis proposes an open-source DSS framework to evaluate business sustainability through financial risk and environmental impact assessments. Data from the literature, alongside lessons learned from industry practitioners, would be centralised in the proposed DSS using imprecise data techniques. These techniques have been applied in engineering but are seldom used in financial forecasting. This could benefit complex sectors which only have scarce data to predict business viability.
To begin the execution of the DSS framework, VPF practitioners were interviewed using a mixed-methods approach. Learnings from over 19 shuttered and operational VPF projects provide insights into the barriers inhibiting scalability and identifying risks to form a risk taxonomy. Labour was the most commonly reported top challenge. Therefore, research was conducted to explore lean principles to improve productivity.
A probabilistic model representing a spectrum of variables and their associated uncertainty was built according to the DSS framework to evaluate the financial risk for VF projects. This enabled flexible computation without precise production or financial data to improve economic estimation accuracy. The model assessed two VPF cases (one in the UK and another in Japan), demonstrating the first risk and uncertainty quantification of VPF business models in the literature. The results highlighted measures to improve economic viability and the viability of the UK and Japan case.
The environmental impact assessment model was developed, allowing VPF operators to evaluate their carbon footprint compared to traditional agriculture using life-cycle assessment. I explore strategies for net-zero carbon production through sensitivity analysis. Renewable energies, especially solar, geothermal, and tidal power, show promise for reducing the carbon emissions of indoor VPF. Results show that renewably-powered VPF can reduce carbon emissions compared to field-based agriculture when considering the land-use change.
The drivers for DSS adoption have been researched, showing a pathway of compliance and design thinking to overcome the ‘problem of implementation’ and enable commercialisation. Further work is suggested to standardise VF equipment, collect benchmarking data, and characterise risks. This work will reduce risk and uncertainty and accelerate the sector’s emergence
Influence of local PO₂ on skeletal muscle microvascular blood flow during hyperinsulinemia
The goal of this thesis was to test the hypothesis that insulin mediated hyperemia is partially dependent on local muscle oxygen concentration. To do so, microvascular blood flow was measured in response to varying imposed concentrations of oxygen in rat skeletal muscle. Sprague-Dawley rats were anesthetized, and the extensor digitorum longus (EDL) was reflected onto an inverted microscope. Intravital video microscopy sequences were recorded during baseline and hyperinsulinemic euglycemia. The muscle was reflected over a glass stage insert (Experiment 1a and 1b), or over a gas exchange chamber (Experiment 2), and microvascular capillary blood flow was recorded during sequential changes (7%-12%-2%-7%) of oxygen (O₂) concentration. Blood flow was measured by the red blood cell supply rate (SR) in number of cells per second. In Experiment 1a, supply rate (SR) increased from 8.0 to 14 cells/s at baseline to euglycemia (p = 0.01), while no significant SR variation was detected after performing a sham hyperinsulinemic euglycemic clamp (Experiment 1b). In Experiment 2, SR decreased at 12% O₂ and increased at 2% O₂, compared to 7% O₂, under both experimental conditions. SR responses to oxygen square wave oscillations during euglycemia were not different to those at baseline at each O₂ concentration (p > 0.9). Our results suggest the increase in blood flow observed in response to insulin is eliminated if tissue oxygen microenvironment is clamped at given oxygen concentrations.
All animal protocols were approved by Memorial University’s Institutional Animal Care Committee
Translating erasure: Proposing auto-theory as a practice for artistic enquiry and analysis while comprehending personal grief
Erasure as an artistic technique has developed in my moving image work after my father's passing. I export videos into sequences of thousands of images and erase outlines of the targeted objects in each frame. The repetitive and low conscious labour is a way to ease the agony and to grieve my father. Hours compressed into thousands of frames, turning into a glimpse of illusion and leaving a ghostly emptiness on the images. Both its visual presentation and making reflect the life events and encounters I've experienced in the UK and Taiwan in the past years.
I consider an artwork embodies interconnected relationships between one's personal impulses and artistic training. As an art student, I have found it challenging to describe such a creative process with conventional academic writing. Within a construct that inclines to present thoughts as reasonable and rational arguments, my personal experiences and the intensity of feeling seem out of place. Within an academic framework, how can I make an argument out of how I have developed the erasure in my artwork to perform the grief, fading memories of a loved one, existential crisis and what's in-between?
Through auto-theoretical approaches to writing and making of moving image work, this research aims to build a structure that can express both the intimate and intellectual aspects of an art practice. This writing up process interweaves my personal stories that motivate my artistic expression into art theories. The memories about my late father, my relationship with languages, and my lives between the UK and Taiwan meet with different artists' uses of erasure.
As the conversations between the introspections and theoretical analysis accumulate, my writing and moving image work unravel an art journey that encompasses the nuances and struggles I've experienced as an international student. Within the search for an ideal model to illustrate an art practice, this research further generates profound understandings of memory, grief, loss, language, conflicted identities and cultural belonging
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
Socio-endocrinology revisited: New tools to tackle old questions
Animals’ 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)
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