3,532 research outputs found
Mobile heritage practices. Implications for scholarly research, user experience design, and evaluation methods using mobile apps.
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
Southern Adventist University Undergraduate Catalog 2023-2024
Southern Adventist University\u27s undergraduate catalog for the academic year 2023-2024.https://knowledge.e.southern.edu/undergrad_catalog/1123/thumbnail.jp
UMSL Bulletin 2023-2024
The 2023-2024 Bulletin and Course Catalog for the University of Missouri St. Louis.https://irl.umsl.edu/bulletin/1088/thumbnail.jp
UMSL Bulletin 2022-2023
The 2022-2023 Bulletin and Course Catalog for the University of Missouri St. Louis.https://irl.umsl.edu/bulletin/1087/thumbnail.jp
The Application of Data Analytics Technologies for the Predictive Maintenance of Industrial Facilities in Internet of Things (IoT) Environments
In industrial production environments, the maintenance of equipment has a decisive influence on costs and on the plannability of production capacities. In particular, unplanned failures during production times cause high costs, unplanned downtimes and possibly additional collateral damage. Predictive Maintenance starts here and tries to predict a possible failure and its cause so early that its prevention can be prepared and carried out in time. In order to be able to predict malfunctions and failures, the industrial plant with its characteristics, as well as wear and ageing processes, must be modelled. Such modelling can be done by replicating its physical properties. However, this is very complex and requires enormous expert knowledge about the plant and about wear and ageing processes of each individual component. Neural networks and machine learning make it possible to train such models using data and offer an alternative, especially when very complex and non-linear behaviour is evident.
In order for models to make predictions, as much data as possible about the condition of a plant and its environment and production planning data is needed. In Industrial Internet of Things (IIoT) environments, the amount of available data is constantly increasing. Intelligent sensors and highly interconnected production facilities produce a steady stream of data. The sheer volume of data, but also the steady stream in which data is transmitted, place high demands on the data processing systems. If a participating system wants to perform live analyses on the incoming data streams, it must be able to process the incoming data at least as fast as the continuous data stream delivers it. If this is not the case, the system falls further and further behind in processing and thus in its analyses. This also applies to Predictive Maintenance systems, especially if they use complex and computationally intensive machine learning models. If sufficiently scalable hardware resources are available, this may not be a problem at first. However, if this is not the case or if the processing takes place on decentralised units with limited hardware resources (e.g. edge devices), the runtime behaviour and resource requirements of the type of neural network used can become an important criterion.
This thesis addresses Predictive Maintenance systems in IIoT environments using neural networks and Deep Learning, where the runtime behaviour and the resource requirements are relevant. The question is whether it is possible to achieve better runtimes with similarly result quality using a new type of neural network. The focus is on reducing the complexity of the network and improving its parallelisability. Inspired by projects in which complexity was distributed to less complex neural subnetworks by upstream measures, two hypotheses presented in this thesis emerged: a) the distribution of complexity into simpler subnetworks leads to faster processing overall, despite the overhead this creates, and b) if a neural cell has a deeper internal structure, this leads to a less complex network. Within the framework of a qualitative study, an overall impression of Predictive Maintenance applications in IIoT environments using neural networks was developed. Based on the findings, a novel model layout was developed named Sliced Long Short-Term Memory Neural Network (SlicedLSTM). The SlicedLSTM implements the assumptions made in the aforementioned hypotheses in its inner model architecture.
Within the framework of a quantitative study, the runtime behaviour of the SlicedLSTM was compared with that of a reference model in the form of laboratory tests. The study uses synthetically generated data from a NASA project to predict failures of modules of aircraft gas turbines. The dataset contains 1,414 multivariate time series with 104,897 samples of test data and 160,360 samples of training data.
As a result, it could be proven for the specific application and the data used that the SlicedLSTM delivers faster processing times with similar result accuracy and thus clearly outperforms the reference model in this respect. The hypotheses about the influence of complexity in the internal structure of the neuronal cells were confirmed by the study carried out in the context of this thesis
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
To make the dominoes fall: A relational-processual approach to societal accountability in the Italian and Spanish anti-corruption arenas
In che modo le organizzazioni della società civile (OSC) contribuiscono alla lotta contro la corruzione? Come possono responsabilizzare i rappresentanti politici? La presente tesi si propone di rispondere a queste a queste domande di ricerca, unendo gli studi sulla lotta alla corruzione a quelli sui movimenti sociali e concentrandosi sul concetto di societal accountability, cioè sui meccanismi di controllo e di sanzione dei rappresentanti pubblici. Negli ultimi anni, gli studiosi della corruzione hanno enfatizzato sempre più il ruolo della società civile come antidoto contro la corruzione, a complemento dei meccanismi di accountability statali ed elettorali. Tuttavia, gli studi empirici sugli effetti anticorruzione degli interventi civici non hanno ancora prodotto risultati coerenti. Questo non dovrebbe sorprendere. Se misurare la corruzione è un compito arduo, valutare se e quanto gli scambi corruttivi vengano impediti grazie alle iniziative della società civile sembra virtualmente impossibile. Per questo motivo, il presente lavoro fa un passo indietro e problematizza lo studio della societal accountability, affrontandola non come un insieme predefinito di meccanismi o pratiche messe in atto da attori civici anticorruzione, ma come il risultato di interazioni sostenute e conflittuali tra più attori, civici e non. Per fare ciò, lo studio si ispira alle teorie dei movimenti sociali e concettualizza la societal accountability come un insieme di conseguenze dell’azione collettiva. Pertanto, questo lavoro mira a capire come e in quali condizioni le iniziative anticorruzione dal basso raggiungano risultati di accountability, quali il passaggio di nuove norme, il miglioramento dell’answerability istituzionale e potenziale sanzionatorio. Con questo obiettivo, la tesi si basa sulle evidenze esistenti negli studi sulla corruzione e sull'accountability e contribuisce ai dibattiti in corso sulle conseguenze dell'azione collettiva. Il quadro teorico si concentra sul concetto di influenza, aderendo a un approccio processuale-relazionale. L'influenza è intesa come un'istanza di causalità relazionale, una forma di potere posizionale che consente a più attori di esercitare un controllo sulle conseguenze dell’azione collettiva. Facendo da ponte tra l'approccio strategico-interazionale e i modelli di mediazione, l'analisi chiarisce le strategie seguite dalle OSC nella ricerca di posizioni di influenza, così come i meccanismi attraverso i quali i modelli relazionali producono cambiamento sociale. Il quadro analitico è applicato alle arene anticorruzione in Italia e in Spagna e si restringe a tre specifiche aree di intervento: l'introduzione di leggi sulla trasparenza, l'approvazione di leggi per la protezione dei whistleblower e lo sviluppo di progetti di monitoraggio civico. Il materiale empirico comprende 37 interviste qualitative semi-strutturate, documenti e dati network. Nel complesso, le evidenze raccolte contribuiscono alla letteratura sulla lotta alla corruzione, dimostrando che le OSC contribuiscono, direttamente e indirettamente, alla lotta contro la corruzione ottenendo cambiamenti nelle politiche, aumentando l’answerability del sistema e innescando sanzioni formali e informali quando necessario. Tuttavia, l’analisi comparata dei casi italiano e spagnolo evidenziano differenze rilevanti. In particolare, l'indagine empirica contribuisce agli attuali dibattiti sullo studio della società della social accountability, dimostrando che l'integrazione con le élite politiche può aumentare la probabilità di ottenere di ottenere un cambiamento delle politiche, mentre l'integrazione orizzontale tra gli attori civici può aumentare il loro potenziale sanzionatorio. In definitiva, questo lavoro dimostra come gli approcci processuali-relazionali possano integrare modelli strategici e di mediazione per comprendere meglio il modo in cui gli attori collettivi influenzano il cambiamento politico e sociale. Le osservazioni conclusive sostengono che le interazioni e le relazioni costruite dagli attori nel corso del tempo e in diverse arene fungono da canali di mediazione a livello micro, meso e macro. Complessivamente, ciò dimostra che i singoli attori, i modelli di relazione nelle e tra le arene e le idee sulle relazioni mediano tra le strategie dei attori collettivi, aumentando o limitando così la loro influenza sulla lotta alla corruzione.How do civil society organizations (CSOs) contribute to the struggle against public corruption? How can they hold their political representatives accountable? This thesis aims to answer these wide-ranging research questions, bridging anti-corruption and social movement studies by focusing on societal accountability, i.e., grassroots mechanisms for controlling and sanctioning powerholders. Over the last few years, corruption scholars have increasingly emphasized the role of civil society as an antidote against corruption, complementing state and electoral accountability mechanisms. However, empirical studies on the anti-corruption effects of civic interventions have yet to yield consistent results. This should hardly come as a surprise. If measuring corruption is a challenging task, assessing the extent to which corrupt deals are prevented due to civil society initiatives appears virtually impossible. Hence, this work takes a step back and problematizes the study of societal accountability, approaching it not as a pre-given set of mechanisms or practices deployed by anti-corruption civic actors but as the result of sustained and contentious interactions between multiple players. To do so, the study draws on social movement theories and conceptualizes societal accountability as a set of consequences of collective action efforts. Therefore, this work aims to understand how and under what conditions bottom-up anti-corruption initiatives achieve accountability results such as legal claim attainments, answerability, and sanctioning potential. With this goal in mind, the thesis builds upon existing evidence from corruption and accountability studies and contributes to ongoing debates on the consequences of collective action. The theoretical framework focuses on the concept of influence, subscribing to a processual-relational approach. It understands influence as a relationally emergent instance of causality, a form of positional power that enables multiple players to exert control over the consequences of collective struggles. By bridging the strategic-interaction approach and mediation models; the analysis elucidates the strategies followed by CSOs in seeking positions of influence, as well as the mechanisms through which relational patterns produce social change. The analytical framework is applied to the anti-corruption arenas in Italy and Spain and is narrowed down by focusing on three specific campaigns in each country: introducing transparency laws, passing whistleblowers' protection acts, and developing civic monitoring projects. The empirical material comprises 37 semi-structured qualitative interviews, documents, and network data retrieved through Action Organization Analysis. The corpus of data is analyzed by combining thematic analysis, frame analysis, and a theory-building process tracing through a qualitative network approach. Overall, the evidence collected contributes to the literature on anti-corruption, demonstrating that CSOs, directly and indirectly, contribute to the anti-corruption struggle by achieving policy change, increasing the system's answerability, and triggering formal and informal sanctions when necessary. However, the Italian and Spanish cases' comparative accounts highlight relevant differences. In particular, the empirical investigation contributes to current debates on the study of societal accountability, showing that integration with political elites may increase the likelihood of obtaining policy change, whereas horizontal integration among civic actors may enhance their sanctioning potential. Ultimately, this work shows how processual-relational approaches can help integrate strategic and mediation models to understand better how change-oriented collective actors influence political and social change. The concluding remarks maintain that the interactions and relations built by players over time and across different arenas serve as mediation channels at the micro-, meso-, and macro-levels. Overall, this demonstrates that individual players, patterns of relations in and across arenas, and ideas about relationships mediate between players' strategies, resources, or frames and their contextual conditions, thereby increasing or constraining their influence over the anti-corruption struggl
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