4,569 research outputs found

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

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    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

    Digital adaptation of the Standing up for Myself intervention in young people and adults with intellectual disabilities: the STORM feasibility study

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    Background Stigma contributes to the negative social conditions persons with intellectual disabilities are exposed to, and it needs tackling at multiple levels. Standing Up for Myself is a psychosocial group intervention designed to enable individuals with intellectual disabilities to discuss stigmatising encounters in a safe and supportive setting and to increase their self-efficacy in managing and resisting stigma. Objectives To adapt Standing Up for Myself to make it suitable as a digital intervention; to evaluate the feasibility and acceptability of Digital Standing Up for Myself and online administration of outcome measures in a pilot; to describe usual practice in the context of the coronavirus disease 2019 pandemic to inform future evaluation. Design Adaptation work followed by a single-arm pilot of intervention delivery. Setting and participants Four third and education sector organisations. Individuals with mild-to-moderate intellectual disabilities, aged 16+, members of existing groups, with access to digital platforms. Intervention Digital Standing Up for Myself intervention. Adapted from face-to-face Standing Up for Myself intervention, delivered over four weekly sessions, plus a 1-month follow-up session. Outcomes Acceptability and feasibility of delivering Digital Standing Up for Myself and of collecting outcome and health economic measures at baseline and 3 months post baseline. Outcomes are mental well-being, self-esteem, self-efficacy in rejecting prejudice, reactions to discrimination and sense of social power. Results Adaptation to the intervention required changes to session duration, group size and number of videos; otherwise, the content remained largely the same. Guidance was aligned with digital delivery methods and a new group member booklet was produced. Twenty-two participants provided baseline data. The intervention was started by 21 participants (four groups), all of whom were retained at 3 months. Group facilitators reported delivering the intervention as feasible and suggested some refinements. Fidelity of the intervention was good, with over 90% of key components observed as implemented by facilitators. Both facilitators and group members reported the intervention to be acceptable. Group members reported subjective benefits, including increased confidence, pride and knowing how to deal with difficult situations. Digital collection of all outcome measures was feasible and acceptable, with data completeness ≥ 95% for all measures at both time points. Finally, a picture of usual practice has been developed as an intervention comparator for a future trial. Limitations The pilot sample was small. It remains unclear whether participants would be willing to be randomised to a treatment as usual arm or whether they could be retained for 12 months follow-up. Conclusions The target number of groups and participants were recruited, and retention was good. It is feasible and acceptable for group facilitators with some training and supervision to deliver Digital Standing Up for Myself. Further optimisation of the intervention is warranted. Future work To maximise the acceptability and reach of the intervention, a future trial could offer the adapted Digital Standing Up for Myself, potentially alongside the original face-to-face version of the intervention

    Configuration Management of Distributed Systems over Unreliable and Hostile Networks

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    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

    Displacement and the Humanities: Manifestos from the Ancient to the Present

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    This is the final version. Available on open access from MDPI via the DOI in this recordThis is a reprint of articles from the Special Issue published online in the open access journal Humanities (ISSN 2076-0787) (available at: https://www.mdpi.com/journal/humanities/special_issues/Manifestos Ancient Present)This volume brings together the work of practitioners, communities, artists and other researchers from multiple disciplines. Seeking to provoke a discourse around displacement within and beyond the field of Humanities, it positions historical cases and debates, some reaching into the ancient past, within diverse geo-chronological contexts and current world urgencies. In adopting an innovative dialogic structure, between practitioners on the ground - from architects and urban planners to artists - and academics working across subject areas, the volume is a proposition to: remap priorities for current research agendas; open up disciplines, critically analysing their approaches; address the socio-political responsibilities that we have as scholars and practitioners; and provide an alternative site of discourse for contemporary concerns about displacement. Ultimately, this volume aims to provoke future work and collaborations - hence, manifestos - not only in the historical and literary fields, but wider research concerned with human mobility and the challenges confronting people who are out of place of rights, protection and belonging

    Multidisciplinary perspectives on Artificial Intelligence and the law

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    This open access book presents an interdisciplinary, multi-authored, edited collection of chapters on Artificial Intelligence (‘AI’) and the Law. AI technology has come to play a central role in the modern data economy. Through a combination of increased computing power, the growing availability of data and the advancement of algorithms, AI has now become an umbrella term for some of the most transformational technological breakthroughs of this age. The importance of AI stems from both the opportunities that it offers and the challenges that it entails. While AI applications hold the promise of economic growth and efficiency gains, they also create significant risks and uncertainty. The potential and perils of AI have thus come to dominate modern discussions of technology and ethics – and although AI was initially allowed to largely develop without guidelines or rules, few would deny that the law is set to play a fundamental role in shaping the future of AI. As the debate over AI is far from over, the need for rigorous analysis has never been greater. This book thus brings together contributors from different fields and backgrounds to explore how the law might provide answers to some of the most pressing questions raised by AI. An outcome of the Católica Research Centre for the Future of Law and its interdisciplinary working group on Law and Artificial Intelligence, it includes contributions by leading scholars in the fields of technology, ethics and the law.info:eu-repo/semantics/publishedVersio

    Digitalization and Development

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    This book examines the diffusion of digitalization and Industry 4.0 technologies in Malaysia by focusing on the ecosystem critical for its expansion. The chapters examine the digital proliferation in major sectors of agriculture, manufacturing, e-commerce and services, as well as the intermediary organizations essential for the orderly performance of socioeconomic agents. The book incisively reviews policy instruments critical for the effective and orderly development of the embedding organizations, and the regulatory framework needed to quicken the appropriation of socioeconomic synergies from digitalization and Industry 4.0 technologies. It highlights the importance of collaboration between government, academic and industry partners, as well as makes key recommendations on how to encourage adoption of IR4.0 technologies in the short- and long-term. This book bridges the concepts and applications of digitalization and Industry 4.0 and will be a must-read for policy makers seeking to quicken the adoption of its technologies

    ARGUS: Context-Based Detection of Stealthy IoT Infiltration Attacks

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    IoT application domains, device diversity and connectivity are rapidly growing. IoT devices control various functions in smart homes and buildings, smart cities, and smart factories, making these devices an attractive target for attackers. On the other hand, the large variability of different application scenarios and inherent heterogeneity of devices make it very challenging to reliably detect abnormal IoT device behaviors and distinguish these from benign behaviors. Existing approaches for detecting attacks are mostly limited to attacks directly compromising individual IoT devices, or, require predefined detection policies. They cannot detect attacks that utilize the control plane of the IoT system to trigger actions in an unintended/malicious context, e.g., opening a smart lock while the smart home residents are absent. In this paper, we tackle this problem and propose ARGUS, the first self-learning intrusion detection system for detecting contextual attacks on IoT environments, in which the attacker maliciously invokes IoT device actions to reach its goals. ARGUS monitors the contextual setting based on the state and actions of IoT devices in the environment. An unsupervised Deep Neural Network (DNN) is used for modeling the typical contextual device behavior and detecting actions taking place in abnormal contextual settings. This unsupervised approach ensures that ARGUS is not restricted to detecting previously known attacks but is also able to detect new attacks. We evaluated ARGUS on heterogeneous real-world smart-home settings and achieve at least an F1-Score of 99.64% for each setup, with a false positive rate (FPR) of at most 0.03%.Comment: To appear in the 32nd USENIX Security Symposium, August 2022, Anaheim CA, US

    The Development of Microdosimetric Instrumentation for Quality Assurance in Heavy Ion Therapy, Boron Neutron Capture Therapy and Fast Neutron Therapy

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    This thesis presents research for the development of new microdosimetric instrumentation for use with solid-state microdosimeters in order to improve their portability for radioprotection purposes and for QA in various hadron therapy modalities. Monte Carlo simulation applications are developed and benchmarked, pertaining to the context of the relevant therapies considered. The simulation and experimental findings provide optimisation recommendations relating to microdosimeter performance and possible radioprotection risks by activated materials. The first part of this thesis is continuing research into the development of novel Silicon-on-Insulator (SOI) microdosimeters in the application of hadron therapy QA. This relates specifically to the optimisation of current microdosimeters, development of Monte Carlo applications for experimental validation, assessment of radioprotection risks during experiments and advanced Monte Carlo modelling of various accelerator beamlines. Geant4 and MCNP6 Monte Carlo codes are used extensively in this thesis, with rigorous benchmarking completed in the context of experimental verification, and evaluation of the similarities and differences when simulating relevant hadron therapy facilities. The second part of this thesis focuses on the development of a novel wireless microdosimetry system - the Radiodosimeter, to improve the operation efficiency and minimise any radioprotection risks. The successful implementation of the wireless Radiodosimeter is considered as an important milestone in the development of a microdosimetry system that can be operated by an end-user with no prior knowledge
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