3,991 research outputs found

    Mobile heritage practices. Implications for scholarly research, user experience design, and evaluation methods using mobile apps.

    Get PDF
    Mobile heritage apps have become one of the most popular means for audience engagement and curation of museum collections and heritage contexts. This raises practical and ethical questions for both researchers and practitioners, such as: what kind of audience engagement can be built using mobile apps? what are the current approaches? how can audience engagement with these experience be evaluated? how can those experiences be made more resilient, and in turn sustainable? In this thesis I explore experience design scholarships together with personal professional insights to analyse digital heritage practices with a view to accelerating thinking about and critique of mobile apps in particular. As a result, the chapters that follow here look at the evolution of digital heritage practices, examining the cultural, societal, and technological contexts in which mobile heritage apps are developed by the creative media industry, the academic institutions, and how these forces are shaping the user experience design methods. Drawing from studies in digital (critical) heritage, Human-Computer Interaction (HCI), and design thinking, this thesis provides a critical analysis of the development and use of mobile practices for the heritage. Furthermore, through an empirical and embedded approach to research, the thesis also presents auto-ethnographic case studies in order to show evidence that mobile experiences conceptualised by more organic design approaches, can result in more resilient and sustainable heritage practices. By doing so, this thesis encourages a renewed understanding of the pivotal role of these practices in the broader sociocultural, political and environmental changes.AHRC REAC

    Success Factors Facilitating Care During Escalation (the SUFFICE study)

    Get PDF
    Ede, J., Watkinson, P., Endacott, R., (2021) Protocol for a mixed methods exploratory study of success factors to escalation of care: the SUFFICE study. medRxiv 2021.11.01.21264875. Ede J, Petrinic T, Westgate V, Darbyshire J, Endacott R, Watkinson PJ. (2021) Human factors in escalating acute ward care: a qualitative evidence synthesis. BMJ Open Qual 10. Bedford, J. P., Ede, J. and Watkinson, P. J. (2021) ‘Triggers for new-onset atrial fibrillation in critically ill patients’, Intensive and Critical Care Nursing. Elsevier Ltd, 67, p. 103114. doi: 10.1016/j.iccn.2021.103114. Ede, J. et al. (2023) ‘Patient and public involvement and engagement (PPIE) in research: The Golden Thread’, Nursing in critical care, (April), pp. 16–19. doi: 10.1111/nicc.12921. Ede, J., Hutton, R., Watkinson, P., Kent, B. and Endacott, R. (2023) ‘Improving escalation of deteriorating patients through cognitive task analysis: Understanding differences between work-as-prescribed and work-as-done’, International Journal of Nursing Studies.BACKGROUND: In the United Kingdom, there continues to be preventable National Health Service (NHS) patient deaths. Contributory factors include inadequate recognition of deterioration, poor monitoring, or delayed escalation to a higher level of care. Strategies to improve care escalation, such as vital sign scoring systems and specialist teams who manage deterioration events, have shown variable impact on patient mortality. The need for greater care improvements has consistently been identified in NHS care reviews as well as patient stories. Furthermore, current research informing escalation improvements predominantly comes from examining failure to rescue events, neglecting what can be learned from rescue or successful escalation. AIM: The focus of this study was to address this knowledge gap by examining rescue and escalation events, and from this, to develop a Framework of Escalation Success Factors that can underpin a multi-faceted intervention to improve outcomes for deteriorating patients. METHODS: Escalation success factors, hospital and patient data were collected in a mixed methods, multi-site exploratory sequential study. Firstly, 151 ward care escalation events were observed to generate a theoretical understanding of the process. To identify escalation success factors, 390 care records were also reviewed from unwell ward patients in whom an Intensive Care Unit admission was avoided and compared to the records for patients who became unwell on the ward, admitted to an Intensive Care Unit, and died. Finally, thirty Applied Cognitive Task Analysis interviews were conducted with clinical experts (defined as greater than four years’ experience) including Ward Nurses (n= 7), Outreach Nurses (n= 5), Nurse Managers (n=5), Physiotherapists (n=4), Sepsis Nurses (n=3), Advanced Nurse Practitioners and Educators (n=2), Advance Clinical Practitioners (n=2), Nurse Consultant (n=1) and Doctor (n=1) to examine process of escalation in a Functional Resonance Analysis Model. RESULTS: In Phase 1, over half (n= 77, 51%) of the 151 escalation events observed were not initiated through an early warning score but other clinical concerns. The data demonstrated four escalation communication phenotypes (Informative, Outcome Focused, General Concern and Spontaneous Interaction) utilised by staff in different clinical contexts for different escalation purposes. In Phase 2, the 390 ward patient care record reviews (Survivors n=340, Non-survivors admitted to ICU n=50) identified that care and quality of escalation in the Non-survivor’s group was better overall than those that survived. Reviews also identified success factors present within deterioration events including Visibility, Monitoring, Adaptability, and Adjustments, not dissimilar to characteristics of high reliability organisations. Finally, Phase 3 interview data were dynamically modelled in a Functional Resonance Analysis Method. This illustrated differences in the number of escalation tasks contained in the early warning scoring system (n=8) compared to how escalation is successfully completed by clinical staff (n=24). Interview participants identified that 28% (9/32) of these tasks were cognitively difficult, also indicating how they overcome system complexity and challenges to successfully escalate. Interactions between escalation tasks were also examined, including Interdependence (how one affects another), Criticality (how many downstream tasks are initiated), Preconditions (what system factors need to be present), and Variability (factors which affect output reliability). This approach developed a system-focused understanding of escalation and signposted to process improvements. CONCLUSION: This research uniquely contributes to international evidence by presenting new elements to escalation of care processes. This includes indicating how frequently early warning scores trigger an escalation, the different ways in which escalation is communicated, that patient outcomes may inaccurately portray the quality of care delivered and examining the interaction between escalation tasks can identify areas of improvement. This is the first study to develop a preliminary Framework of Escalation Success Factors, which will be refined and used to underpin evidenced based care improvements. A key recommendation would be for organisations to use, when tested, the Framework of Escalation Success Factors to make system refinements that will promote successful escalation of care. PPI: This study has had Patient and Public Involvement and Engagement (PPIE) through a SUFFICE PPI Advisory Group

    Computer-Aided Drug Design and Drug Discovery: A Prospective Analysis

    Get PDF
    In the dynamic landscape of drug discovery, Computer-Aided Drug Design (CADD) emerges as a transformative force, bridging the realms of biology and technology. This paper overviews CADDs historical evolution, categorization into structure-based and ligand-based approaches, and its crucial role in rationalizing and expediting drug discovery. As CADD advances, incorporating diverse biological data and ensuring data privacy become paramount. Challenges persist, demanding the optimization of algorithms and robust ethical frameworks. Integrating Machine Learning and Artificial Intelligence amplifies CADDs predictive capabilities, yet ethical considerations and scalability challenges linger. Collaborative efforts and global initiatives, exemplified by platforms like Open-Source Malaria, underscore the democratization of drug discovery. The convergence of CADD with personalized medicine offers tailored therapeutic solutions, though ethical dilemmas and accessibility concerns must be navigated. Emerging technologies like quantum computing, immersive technologies, and green chemistry promise to redefine the future of CADD. The trajectory of CADD, marked by rapid advancements, anticipates challenges in ensuring accuracy, addressing biases in AI, and incorporating sustainability metrics. This paper concludes by highlighting the need for proactive measures in navigating the ethical, technological, and educational frontiers of CADD to shape a healthier, brighter future in drug discovery

    Recalibrating machine learning for social biases: demonstrating a new methodology through a case study classifying gender biases in archival documentation

    Get PDF
    This thesis proposes a recalibration of Machine Learning for social biases to minimize harms from existing approaches and practices in the field. Prioritizing quality over quantity, accuracy over efficiency, representativeness over convenience, and situated thinking over universal thinking, the thesis demonstrates an alternative approach to creating Machine Learning models. Drawing on GLAM, the Humanities, the Social Sciences, and Design, the thesis focuses on understanding and communicating biases in a specific use case. 11,888 metadata descriptions from the University of Edinburgh Heritage Collections' Archives catalog were manually annotated for gender biases and text classification models were then trained on the resulting dataset of 55,260 annotations. Evaluations of the models' performance demonstrates that annotating gender biases can be automated; however, the subjectivity of bias as a concept complicates the generalizability of any one approach. The contributions are: (1) an interdisciplinary and participatory Bias-Aware Methodology, (2) a Taxonomy of Gendered and Gender Biased Language, (3) data annotated for gender biased language, (4) gender biased text classification models, and (5) a human-centered approach to model evaluation. The contributions have implications for Machine Learning, demonstrating how bias is inherent to all data and models; more specifically for Natural Language Processing, providing an annotation taxonomy, annotated datasets and classification models for analyzing gender biased language at scale; for the Gallery, Library, Archives, and Museum sector, offering guidance to institutions seeking to reconcile with histories of marginalizing communities through their documentation practices; and for historians, who utilize cultural heritage documentation to study and interpret the past. Through a real-world application of the Bias-Aware Methodology in a case study, the thesis illustrates the need to shift away from removing social biases and towards acknowledging them, creating data and models that surface the uncertainty and multiplicity characteristic of human societies

    On the real world practice of Behaviour Driven Development

    Get PDF
    Surveys of industry practice over the last decade suggest that Behaviour Driven Development is a popular Agile practice. For example, 19% of respondents to the 14th State of Agile annual survey reported using BDD, placing it in the top 13 practices reported. As well as potential benefits, the adoption of BDD necessarily involves an additional cost of writing and maintaining Gherkin features and scenarios, and (if used for acceptance testing,) the associated step functions. Yet there is a lack of published literature exploring how BDD is used in practice and the challenges experienced by real world software development efforts. This gap is significant because without understanding current real world practice, it is hard to identify opportunities to address and mitigate challenges. In order to address this research gap concerning the challenges of using BDD, this thesis reports on a research project which explored: (a) the challenges of applying agile and undertaking requirements engineering in a real world context; (b) the challenges of applying BDD specifically and (c) the application of BDD in open-source projects to understand challenges in this different context. For this purpose, we progressively conducted two case studies, two series of interviews, four iterations of action research, and an empirical study. The first case study was conducted in an avionics company to discover the challenges of using an agile process in a large scale safety critical project environment. Since requirements management was found to be one of the biggest challenges during the case study, we decided to investigate BDD because of its reputation for requirements management. The second case study was conducted in the company with an aim to discover the challenges of using BDD in real life. The case study was complemented with an empirical study of the practice of BDD in open source projects, taking a study sample from the GitHub open source collaboration site. As a result of this Ph.D research, we were able to discover: (i) challenges of using an agile process in a large scale safety-critical organisation, (ii) current state of BDD in practice, (iii) technical limitations of Gherkin (i.e., the language for writing requirements in BDD), (iv) challenges of using BDD in a real project, (v) bad smells in the Gherkin specifications of open source projects on GitHub. We also presented a brief comparison between the theoretical description of BDD and BDD in practice. This research, therefore, presents the results of lessons learned from BDD in practice, and serves as a guide for software practitioners planning on using BDD in their projects

    Pristup specifikaciji i generisanju proizvodnih procesa zasnovan na inženjerstvu vođenom modelima

    Get PDF
    In this thesis, we present an approach to the production process specification and generation based on the model-driven paradigm, with the goal to increase the flexibility of factories and respond to the challenges that emerged in the era of Industry 4.0 more efficiently. To formally specify production processes and their variations in the Industry 4.0 environment, we created a novel domain-specific modeling language, whose models are machine-readable. The created language can be used to model production processes that can be independent of any production system, enabling process models to be used in different production systems, and process models used for the specific production system. To automatically transform production process models dependent on the specific production system into instructions that are to be executed by production system resources, we created an instruction generator. Also, we created generators for different manufacturing documentation, which automatically transform production process models into manufacturing documents of different types. The proposed approach, domain-specific modeling language, and software solution contribute to introducing factories into the digital transformation process. As factories must rapidly adapt to new products and their variations in the era of Industry 4.0, production must be dynamically led and instructions must be automatically sent to factory resources, depending on products that are to be created on the shop floor. The proposed approach contributes to the creation of such a dynamic environment in contemporary factories, as it allows to automatically generate instructions from process models and send them to resources for execution. Additionally, as there are numerous different products and their variations, keeping the required manufacturing documentation up to date becomes challenging, which can be done automatically by using the proposed approach and thus significantly lower process designers' time.У овој дисертацији представљен је приступ спецификацији и генерисању производних процеса заснован на инжењерству вођеном моделима, у циљу повећања флексибилности постројења у фабрикама и ефикаснијег разрешавања изазова који се појављују у ери Индустрије 4.0. За потребе формалне спецификације производних процеса и њихових варијација у амбијенту Индустрије 4.0, креиран је нови наменски језик, чије моделе рачунар може да обради на аутоматизован начин. Креирани језик има могућност моделовања производних процеса који могу бити независни од производних система и тиме употребљени у различитим постројењима или фабрикама, али и производних процеса који су специфични за одређени систем. Како би моделе производних процеса зависних од конкретног производног система било могуће на аутоматизован начин трансформисати у инструкције које ресурси производног система извршавају, креиран је генератор инструкција. Такође су креирани и генератори техничке документације, који на аутоматизован начин трансформишу моделе производних процеса у документе различитих типова. Употребом предложеног приступа, наменског језика и софтверског решења доприноси се увођењу фабрика у процес дигиталне трансформације. Како фабрике у ери Индустрије 4.0 морају брзо да се прилагоде новим производима и њиховим варијацијама, неопходно је динамички водити производњу и на аутоматизован начин слати инструкције ресурсима у фабрици, у зависности од производа који се креирају у конкретном постројењу. Тиме што је у предложеном приступу могуће из модела процеса аутоматизовано генерисати инструкције и послати их ресурсима, доприноси се креирању једног динамичког окружења у савременим фабрикама. Додатно, услед великог броја различитих производа и њихових варијација, постаје изазовно одржавати неопходну техничку документацију, што је у предложеном приступу могуће урадити на аутоматизован начин и тиме значајно уштедети време пројектаната процеса.U ovoj disertaciji predstavljen je pristup specifikaciji i generisanju proizvodnih procesa zasnovan na inženjerstvu vođenom modelima, u cilju povećanja fleksibilnosti postrojenja u fabrikama i efikasnijeg razrešavanja izazova koji se pojavljuju u eri Industrije 4.0. Za potrebe formalne specifikacije proizvodnih procesa i njihovih varijacija u ambijentu Industrije 4.0, kreiran je novi namenski jezik, čije modele računar može da obradi na automatizovan način. Kreirani jezik ima mogućnost modelovanja proizvodnih procesa koji mogu biti nezavisni od proizvodnih sistema i time upotrebljeni u različitim postrojenjima ili fabrikama, ali i proizvodnih procesa koji su specifični za određeni sistem. Kako bi modele proizvodnih procesa zavisnih od konkretnog proizvodnog sistema bilo moguće na automatizovan način transformisati u instrukcije koje resursi proizvodnog sistema izvršavaju, kreiran je generator instrukcija. Takođe su kreirani i generatori tehničke dokumentacije, koji na automatizovan način transformišu modele proizvodnih procesa u dokumente različitih tipova. Upotrebom predloženog pristupa, namenskog jezika i softverskog rešenja doprinosi se uvođenju fabrika u proces digitalne transformacije. Kako fabrike u eri Industrije 4.0 moraju brzo da se prilagode novim proizvodima i njihovim varijacijama, neophodno je dinamički voditi proizvodnju i na automatizovan način slati instrukcije resursima u fabrici, u zavisnosti od proizvoda koji se kreiraju u konkretnom postrojenju. Time što je u predloženom pristupu moguće iz modela procesa automatizovano generisati instrukcije i poslati ih resursima, doprinosi se kreiranju jednog dinamičkog okruženja u savremenim fabrikama. Dodatno, usled velikog broja različitih proizvoda i njihovih varijacija, postaje izazovno održavati neophodnu tehničku dokumentaciju, što je u predloženom pristupu moguće uraditi na automatizovan način i time značajno uštedeti vreme projektanata procesa

    Counterfactual sustainability screening - the definition and undertaking of a sustainability screening method for the assessment of defossilised supply chains

    Get PDF
    With the monumental shift in industrial interest towards sustainable, defossilised supply chains in response to the climate crisis, the understanding of alternative supply chain viability has never been more vital. As part of their Clean Future initiative, Unilever Home Care has committed to the phasing out of fossil carbon sources from their supply chains. To better assess the viability of these prospective supply chains within a quick timeframe, a counterfactual screening method has been developed which pits the performance of eleven selected sustainability indicators against a success baseline, returning a results array on the sustainability performance of these routes. This paper briefly introduces the initiatives laid out by Unilever Home Care, before undertaking a concise review on existing sustainability screening methods from the literature, with the key limitations of these methods outlined. In response to these limitations, a new methodology is then defined, with a case study of defossilised Linear Alkylbenzene Sulfonate (LAS)-appropriate olefins being applied. This study both illustrates the functionality of the methodology, as well as provides an insight into the viability of the assessed supply chains. Within the study, 18 technologies forming 18 routes were assessed, spanning green (“from plants”), grey (“from plastic waste”) and purple (“from CO2”) feedstocks (according to the Carbon Rainbow). General results trends suggest that green and grey routes hold much greater viability than the purple routes, given their relatively lower capital and operating costs, as well as their superior likelihood of being commercially viable by 2030. Plans for further research are also provided, with plans for results validation included

    Integrating art and AI: Evaluating the educational impact of AI tools in digital art history learning

    Get PDF
    This study delves into the burgeoning intersection of Artificial Intelligence (AI) and art history education, an area that has been relatively unexplored. The research focuses on how AI art generators impact learning outcomes in art history for both undergraduate and graduate students enrolled in Ancient Art courses, covering eras from ancient Mesopotamia to the fall of Rome. Utilizing a mixed-methods approach, the study analyzes AI-generated artworks, reflective essays, and survey responses to assess how these generative tools influence students’ comprehension, engagement, and creative interpretation of historical artworks. The study reveals that the use of AI tools in art history not only enhances students’ understanding of artistic concepts but also fosters a deeper, more nuanced appreciation of art from the periods studied. The findings indicate that engaging with AI tools promotes critical thinking and creativity, which are crucial competencies in the study of art history. Survey data further suggest that the integration of AI in art history positively influences students’ perceptions of the discipline, aligning well with contemporary digital trends. One of the significant outcomes of the study is the varied experiences of students with AI tools. While some faced challenges with the technology, particularly in accurately capturing complex artwork details and crafting effective prompts, others found success in using AI to generate detailed and creative interpretations of historical pieces. These experiences underscore the potential of AI as a valuable pedagogical tool in art history and humanities education, offering novel insights into teaching methodologies

    AI Lifecycle Zero-Touch Orchestration within the Edge-to-Cloud Continuum for Industry 5.0

    Get PDF
    The advancements in human-centered artificial intelligence (HCAI) systems for Industry 5.0 is a new phase of industrialization that places the worker at the center of the production process and uses new technologies to increase prosperity beyond jobs and growth. HCAI presents new objectives that were unreachable by either humans or machines alone, but this also comes with a new set of challenges. Our proposed method accomplishes this through the knowlEdge architecture, which enables human operators to implement AI solutions using a zero-touch framework. It relies on containerized AI model training and execution, supported by a robust data pipeline and rounded off with human feedback and evaluation interfaces. The result is a platform built from a number of components, spanning all major areas of the AI lifecycle. We outline both the architectural concepts and implementation guidelines and explain how they advance HCAI systems and Industry 5.0. In this article, we address the problems we encountered while implementing the ideas within the edge-to-cloud continuum. Further improvements to our approach may enhance the use of AI in Industry 5.0 and strengthen trust in AI systems
    corecore