1,126 research outputs found
Configuration Management of Distributed Systems over Unreliable and Hostile Networks
Economic incentives of large criminal profits and the threat of legal consequences have pushed criminals to continuously improve their malware, especially command and control channels. This thesis applied concepts from successful malware command and control to explore the survivability and resilience of benign configuration management systems.
This work expands on existing stage models of malware life cycle to contribute a new model for identifying malware concepts applicable to benign configuration management. The Hidden Master architecture is a contribution to master-agent network communication. In the Hidden Master architecture, communication between master and agent is asynchronous and can operate trough intermediate nodes. This protects the master secret key, which gives full control of all computers participating in configuration management. Multiple improvements to idempotent configuration were proposed, including the definition of the minimal base resource dependency model, simplified resource revalidation and the use of imperative general purpose language for defining idempotent configuration.
Following the constructive research approach, the improvements to configuration management were designed into two prototypes. This allowed validation in laboratory testing, in two case studies and in expert interviews. In laboratory testing, the Hidden Master prototype was more resilient than leading configuration management tools in high load and low memory conditions, and against packet loss and corruption. Only the research prototype was adaptable to a network without stable topology due to the asynchronous nature of the Hidden Master architecture.
The main case study used the research prototype in a complex environment to deploy a multi-room, authenticated audiovisual system for a client of an organization deploying the configuration. The case studies indicated that imperative general purpose language can be used for idempotent configuration in real life, for defining new configurations in unexpected situations using the base resources, and abstracting those using standard language features; and that such a system seems easy to learn.
Potential business benefits were identified and evaluated using individual semistructured expert interviews. Respondents agreed that the models and the Hidden Master architecture could reduce costs and risks, improve developer productivity and allow faster time-to-market. Protection of master secret keys and the reduced need for incident response were seen as key drivers for improved security. Low-cost geographic scaling and leveraging file serving capabilities of commodity servers were seen to improve scaling and resiliency. Respondents identified jurisdictional legal limitations to encryption and requirements for cloud operator auditing as factors potentially limiting the full use of some concepts
Mapping the Focal Points of WordPress: A Software and Critical Code Analysis
Programming languages or code can be examined through numerous analytical lenses. This project is a critical analysis of WordPress, a prevalent web content management system, applying four modes of inquiry. The project draws on theoretical perspectives and areas of study in media, software, platforms, code, language, and power structures. The applied research is based on Critical Code Studies, an interdisciplinary field of study that holds the potential as a theoretical lens and methodological toolkit to understand computational code beyond its function. The project begins with a critical code analysis of WordPress, examining its origins and source code and mapping selected vulnerabilities. An examination of the influence of digital and computational thinking follows this. The work also explores the intersection of code patching and vulnerability management and how code shapes our sense of control, trust, and empathy, ultimately arguing that a rhetorical-cultural lens can be used to better understand code\u27s controlling influence. Recurring themes throughout these analyses and observations are the connections to power and vulnerability in WordPress\u27 code and how cultural, processual, rhetorical, and ethical implications can be expressed through its code, creating a particular worldview. Code\u27s emergent properties help illustrate how human values and practices (e.g., empathy, aesthetics, language, and trust) become encoded in software design and how people perceive the software through its worldview. These connected analyses reveal cultural, processual, and vulnerability focal points and the influence these entanglements have concerning WordPress as code, software, and platform. WordPress is a complex sociotechnical platform worthy of further study, as is the interdisciplinary merging of theoretical perspectives and disciplines to critically examine code. Ultimately, this project helps further enrich the field by introducing focal points in code, examining sociocultural phenomena within the code, and offering techniques to apply critical code methods
Carbon Capture Storage Implemented On Flexible Power Plants And Their Grid Impacts
The energy grid is under a constant state of evolution from outside factors such as the rise ofrenewable energy in the form of solar and wind generation as well as competing with the changes in weather patterns from climate change leading to significant storms like the arctic event of 2022. Thermal power plants are greatly impacted by these changes. As a significant contributor of CO2 emissions, thermal power plants play an important role in emerging green technology policies to help the efforts of climate change. There is a significant cost associated with this change, however, as thermal plants are some of the cheapest to implement and have provided baseline power supply for decades for both first world countries and especially those still under development. An emerging technology that can bridge the gap between these two ideologies is carbon capture systems, which take the emissions normally emitted to the environment and allow them to be captured for storage later. Carbon Capture Storage (CCS) is not without its tradeoffs though. There is a significant change, of about 15%, in the power generation capability of the plant it is installed on, which can have drastic impacts on a grid already impacted by so many other changes. To combat these difficulties, flexible variations of thermal plants are being brought forth, but the capabilities of these options compared to the traditional is notional. This study used a simulation-based approach to quantify these impacts. The simulations evaluated traditional thermal plants, their flexible counterparts, renewable energy hosting, and the capabilities of both in regard to carbon capture installations. Using results from the developed model, the benefits of pairing flexible plants with dynamic CCS units show that additional renewable energy and load can be hosted, as well as show the limitations that those parameters exhibited
The influence of developmental experiences on the talent pathway in sport
It is well established that youth athletes are highly likely to encounter a range of experiences on the talent pathway that will accelerate and potentially derail their development. The aim of this thesis was to explore the influence of developmental experiences from both ex and current
talent pathway youth athletes to understand the influence of such experience both in and beyond the talent pathway. Chapter 4 explored the talent pathway experiences of ex-talent pathway athletes through semi-structured interviews. The findings of Chapter 4 highlight the
potential for talent pathways to facilitate positive and transferable developmental outcomes beyond the transition to professional sport. Chapter 5 explored the coaching philosophies of ex-talent pathway athletes, now coaching on a talent pathway. The findings highlighted the
potential influence of the participant’s own athlete experience on the talent pathway to support the development of the participant’s coaching philosophy relative to optimising the learning and development of their youth athletes. Chapter 6 explored the most difficult challenges of
eight young athletes on the talent pathway through a tracking approach. The findings emphasised the important role of coaches on the talent pathway to skilfully plan, prepare, and individualise challenging experiences to enhance the young athlete’s capability to navigate the
challenge. Chapter 7 explored how eight young athletes and their five talent pathway coaches experienced ‘most difficult’ challenges, as identified by the young athlete. Participants identified a range of psychobehavioural skills, the impact of the challenge environment and
social support to aid in the young athlete’s navigation of the experience. Chapter 8 provides specific implications for the research literature and coaching practice with a particular focus on the development, deployment, and transfer of skills and experiences on the talent pathway
and the impact of the bespoke nature of challenging experiences on the development of talent pathway youth athletes
Bayesian Forecasting in Economics and Finance: A Modern Review
The Bayesian statistical paradigm provides a principled and coherent approach
to probabilistic forecasting. Uncertainty about all unknowns that characterize
any forecasting problem -- model, parameters, latent states -- is able to be
quantified explicitly, and factored into the forecast distribution via the
process of integration or averaging. Allied with the elegance of the method,
Bayesian forecasting is now underpinned by the burgeoning field of Bayesian
computation, which enables Bayesian forecasts to be produced for virtually any
problem, no matter how large, or complex. The current state of play in Bayesian
forecasting in economics and finance is the subject of this review. The aim is
to provide the reader with an overview of modern approaches to the field, set
in some historical context; and with sufficient computational detail given to
assist the reader with implementation.Comment: The paper is now published online at:
https://doi.org/10.1016/j.ijforecast.2023.05.00
Enabling changeability with typescript and microservices architecture in web applications
Changeability is a non-functional property of software that affects the length of its lifecycle. In this work, the microservices architectural pattern and TypeScript are studied through a literature review, focusing on how they enable the changeability of a web application.
The modularity of software is a key factor in enabling changeability. The micro-services architectural pattern and the programming language TypeScript can impact the changeability of web applications with modularity. Microservices architecture is a well-suited architectural pattern for web applications, as it allows for the creation of modular service components that can be modified and added to the system individually. TypeScript is a programming language that adds a type system and class-based object-oriented programming to JavaScript offering an array of features that enable modularity.
Through discussion on relationships between the changeability of web applications and their three key characteristics, scalability, robustness, and security, this work demonstrates the importance of designing for change to ensure that web applications remain maintainable, extensible, restructurable, and portable over time. Combined, the micro-services architecture and TypeScript can enhance the modularity and thus changeability of web applications
FedFTN: Personalized Federated Learning with Deep Feature Transformation Network for Multi-institutional Low-count PET Denoising
Low-count PET is an efficient way to reduce radiation exposure and
acquisition time, but the reconstructed images often suffer from low
signal-to-noise ratio (SNR), thus affecting diagnosis and other downstream
tasks. Recent advances in deep learning have shown great potential in improving
low-count PET image quality, but acquiring a large, centralized, and diverse
dataset from multiple institutions for training a robust model is difficult due
to privacy and security concerns of patient data. Moreover, low-count PET data
at different institutions may have different data distribution, thus requiring
personalized models. While previous federated learning (FL) algorithms enable
multi-institution collaborative training without the need of aggregating local
data, addressing the large domain shift in the application of
multi-institutional low-count PET denoising remains a challenge and is still
highly under-explored. In this work, we propose FedFTN, a personalized
federated learning strategy that addresses these challenges. FedFTN uses a
local deep feature transformation network (FTN) to modulate the feature outputs
of a globally shared denoising network, enabling personalized low-count PET
denoising for each institution. During the federated learning process, only the
denoising network's weights are communicated and aggregated, while the FTN
remains at the local institutions for feature transformation. We evaluated our
method using a large-scale dataset of multi-institutional low-count PET imaging
data from three medical centers located across three continents, and showed
that FedFTN provides high-quality low-count PET images, outperforming previous
baseline FL reconstruction methods across all low-count levels at all three
institutions.Comment: 13 pages, 6 figures, Accepted at Medical Image Analysis Journal
(MedIA
The Role of a Microservice Architecture on cybersecurity and operational resilience in critical systems
Critical systems are characterized by their high degree of intolerance to threats, in other words,
their high level of resilience, because depending on the context in which the system is inserted,
the slightest failure could imply significant damage, whether in economic terms, or loss of
reputation, of information, of infrastructure, of the environment, or human life. The security of
such systems is traditionally associated with legacy infrastructures and data centers that are
monolithic, which translates into increasingly high evolution and protection challenges.
In the current context of rapid transformation where the variety of threats to systems has been
consistently increasing, this dissertation aims to carry out a compatibility study of the
microservice architecture, which is denoted by its characteristics such as resilience, scalability,
modifiability and technological heterogeneity, being flexible in structural adaptations, and in
rapidly evolving and highly complex settings, making it suited for agile environments. It also
explores what response artificial intelligence, more specifically machine learning, can provide
in a context of security and monitorability when combined with a simple banking system that
adopts the microservice architecture.Os sistemas críticos são caracterizados pelo seu elevado grau de intolerância às ameaças, por
outras palavras, o seu alto nível de resiliência, pois dependendo do contexto onde se insere o
sistema, a mínima falha poderá implicar danos significativos, seja em termos económicos, de
perda de reputação, de informação, de infraestrutura, de ambiente, ou de vida humana. A
segurança informática de tais sistemas está tradicionalmente associada a infraestruturas e data
centers legacy, ou seja, de natureza monolítica, o que se traduz em desafios de evolução e
proteção cada vez mais elevados.
No contexto atual de rápida transformação, onde as variedades de ameaças aos sistemas têm
vindo consistentemente a aumentar, esta dissertação visa realizar um estudo de
compatibilidade da arquitetura de microserviços, que se denota pelas suas caraterísticas tais
como a resiliência, escalabilidade, modificabilidade e heterogeneidade tecnológica, sendo
flexível em adaptações estruturais, e em cenários de rápida evolução e elevada complexidade,
tornando-a adequada a ambientes ágeis. Explora também a resposta que a inteligência artificial,
mais concretamente, machine learning, pode dar num contexto de segurança e
monitorabilidade quando combinado com um simples sistema bancário que adota uma
arquitetura de microserviços
Measuring the impact of COVID-19 on hospital care pathways
Care pathways in hospitals around the world reported significant disruption during the recent COVID-19 pandemic but measuring the actual impact is more problematic. Process mining can be useful for hospital management to measure the conformance of real-life care to what might be considered normal operations. In this study, we aim to demonstrate that process mining can be used to investigate process changes associated with complex disruptive events. We studied perturbations to accident and emergency (A &E) and maternity pathways in a UK public hospital during the COVID-19 pandemic. Co-incidentally the hospital had implemented a Command Centre approach for patient-flow management affording an opportunity to study both the planned improvement and the disruption due to the pandemic. Our study proposes and demonstrates a method for measuring and investigating the impact of such planned and unplanned disruptions affecting hospital care pathways. We found that during the pandemic, both A &E and maternity pathways had measurable reductions in the mean length of stay and a measurable drop in the percentage of pathways conforming to normative models. There were no distinctive patterns of monthly mean values of length of stay nor conformance throughout the phases of the installation of the hospital’s new Command Centre approach. Due to a deficit in the available A &E data, the findings for A &E pathways could not be interpreted
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Social Addictive Gameful Engineering (SAGE): A Game-based Learning and Assessment System for Computational Thinking
At an unrivaled and enduring pace, computing has transformed the world, resulting in demand for a universal fourth foundation beyond reading, writing, and arithmetic: computational thinking (CT). Despite increasingly widespread acceptance of CT as a crucial competency for all, transforming education systems accordingly has proven complex. The principal hypothesis of this thesis is that we can improve the efficiency and efficacy of teaching and learning CT by building gameful learning and assessment systems on top of block-based programming environments. Additionally, we believe this can be accomplished at scale and cost conducive to accelerating CT dissemination for all.
After introducing the requirements, approach, and architecture, we present a solution named Gameful Direct Instruction. This involves embedding Parsons Programming Puzzles (PPPs) in Scratch, which is a block-based programming environment currently used prevalently in grades 6-8. PPPs encourage students to practice CT by assembling into correct order sets of mixed-up blocks that comprise samples of well-written code which focus on individual concepts. The structure provided by PPPs enable instructors to design games that steer learner attention toward targeted learning goals through puzzle-solving play. Learners receive continuous automated feedback as they attempt to arrange programming constructs in correct order, leading to more efficient comprehension of core CT concepts than they might otherwise attain through less structured Scratch assignments. We measure this efficiency first via a pilot study conducted after the initial integration of PPPs with Scratch, and second after the addition of scaffolding enhancements in a study involving a larger adult general population.
We complement Gameful Direct Instruction with a solution named Gameful Constructionism. This involves integrating with Scratch implicit assessment functionality that facilitates constructionist video game (CVG) design and play. CVGs enable learner to explore CT using construction tools sufficiently expressive for personally meaningful gameplay. Instructors are enabled to guide learning by defining game objectives useful for implicit assessment, while affording learners the opportunity to take ownership of the experience and progress through the sequence of interest and motivation toward sustained engagement. When strategically arranged within a learning progression after PPP gameplay produces evidence of efficient comprehension, CVGs amplify the impact of direct instruction by providing the sculpted context in which learners can apply CT concepts more freely, thereby broadening and deepening understanding, and improving learning efficacy. We measure this efficacy in a study of the general adult population.
Since these approaches leverage low fidelity yet motivating gameful techniques, they facilitate the development of learning content at scale and cost supportive of widespread CT uptake. We conclude this thesis with a glance at future work that anticipates further progress in scalability via a solution named Gameful Intelligent Tutoring. This involves augmenting Scratch with Intelligent Tutoring System (ITS) functionality that offers across-activity next-game recommendations, and within-activity just-in-time and on-demand hints. Since these data-driven methods operate without requiring knowledge engineering for each game designed, the instructor can evolve her role from one focused on knowledge transfer to one centered on supporting learning through the design of educational experiences, and we can accelerate the dissemination of CT at scale and reasonable cost while also advancing toward continuously differentiated instruction for each learner
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