3,150 research outputs found
ENHANCING CLOUD SYSTEM RUNTIME TO ADDRESS COMPLEX FAILURES
As the reliance on cloud systems intensifies in our progressively digital world, understanding and reinforcing their reliability becomes more crucial than ever. Despite impressive advancements in augmenting the resilience of cloud systems, the growing incidence of complex failures now poses a substantial challenge to the availability of these systems. With cloud systems continuing to scale and increase in complexity, failures not only become more elusive to detect but can also lead to more catastrophic consequences. Such failures question the foundational premises of conventional fault-tolerance designs, necessitating the creation of novel system designs to counteract them.
This dissertation aims to enhance distributed systems’ capabilities to detect, localize, and react to complex failures at runtime. To this end, this dissertation makes contributions to address three emerging categories of failures in cloud systems. The first part delves into the investigation of partial failures, introducing OmegaGen, a tool adept at generating tailored checkers for detecting and localizing such failures. The second part grapples with silent semantic failures prevalent in cloud systems, showcasing our study findings, and introducing Oathkeeper, a tool that leverages past failures to infer rules and expose these silent issues. The third part explores solutions to slow failures via RESIN, a framework specifically designed to detect, diagnose, and mitigate memory leaks in cloud-scale infrastructures, developed in collaboration with Microsoft Azure. The dissertation concludes by offering insights into future directions for the construction of reliable cloud systems
Patterns and Variation in English Language Discourse
The publication is reviewed post-conference proceedings from the international 9th Brno Conference on Linguistics Studies in English, held on 16–17 September 2021 and organised by the Faculty of Education, Masaryk University in Brno. The papers revolve around the themes of patterns and variation in specialised discourses (namely the media, academic, business, tourism, educational and learner discourses), effective interaction between the addressor and addressees and the current trends and development in specialised discourses. The principal methodological perspectives are the comparative approach involving discourses in English and another language, critical and corpus analysis, as well as identification of pragmatic strategies and appropriate rhetorical means. The authors of papers are researchers from the Czech Republic, Italy, Luxembourg, Serbia and Georgia
Towards a centralized multicore automotive system
Today’s automotive systems are inundated with embedded electronics to host chassis, powertrain, infotainment, advanced driver assistance systems, and other modern vehicle functions. As many as 100 embedded microcontrollers execute hundreds of millions of lines of code in a single vehicle. To control the increasing complexity in vehicle electronics and services, automakers are planning to consolidate different on-board automotive functions as software tasks on centralized multicore hardware platforms. However, these vehicle software services have different and contrasting timing, safety, and security requirements. Existing vehicle operating systems are ill-equipped to provide all the required service guarantees on a single machine. A centralized automotive system aims to tackle this by assigning software tasks to multiple criticality domains or levels according to their consequences of failures, or international safety standards like ISO 26262. This research investigates several emerging challenges in time-critical systems for a centralized multicore automotive platform and proposes a novel vehicle operating system framework to address them.
This thesis first introduces an integrated vehicle management system (VMS), called DriveOS™, for a PC-class multicore hardware platform. Its separation kernel design enables temporal and spatial isolation among critical and non-critical vehicle services in different domains on the same machine. Time- and safety-critical vehicle functions are implemented in a sandboxed Real-time Operating System (OS) domain, and non-critical software is developed in a sandboxed general-purpose OS (e.g., Linux, Android) domain. To leverage the advantages of model-driven vehicle function development, DriveOS provides a multi-domain application framework in Simulink. This thesis also presents a real-time task pipeline scheduling algorithm in multiprocessors for communication between connected vehicle services with end-to-end guarantees. The benefits and performance of the overall automotive system framework are demonstrated with hardware-in-the-loop testing using real-world applications, car datasets and simulated benchmarks, and with an early-stage deployment in a production-grade luxury electric vehicle
2023-2024 Catalog
The 2023-2024 Governors State University Undergraduate and Graduate Catalog is a comprehensive listing of current information regarding:Degree RequirementsCourse OfferingsUndergraduate and Graduate Rules and Regulation
NEMISA Digital Skills Conference (Colloquium) 2023
The purpose of the colloquium and events centred around the central role that data plays
today as a desirable commodity that must become an important part of massifying digital
skilling efforts. Governments amass even more critical data that, if leveraged, could
change the way public services are delivered, and even change the social and economic
fortunes of any country. Therefore, smart governments and organisations increasingly
require data skills to gain insights and foresight, to secure themselves, and for improved
decision making and efficiency. However, data skills are scarce, and even more
challenging is the inconsistency of the associated training programs with most curated for
the Science, Technology, Engineering, and Mathematics (STEM) disciplines.
Nonetheless, the interdisciplinary yet agnostic nature of data means that there is
opportunity to expand data skills into the non-STEM disciplines as well.College of Engineering, Science and Technolog
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
Spatial Interaction Models in a Big Data Grocery Retailing Environment
Grocery expenditure is responsible for around 10% of total household spend in the UK, making the grocery retail market worth over ÂŁ200bn a year in 2021. The size of this market and the nature of retailing competition makes it important for retailers to make the right decisions. One such decision is the location of their stores for which there have been a number of changes in the location, format and channel of consumer interaction along with the methods that have been employed to determine new store location. In recent years it has been suggested that the spatial interaction model is the most appropriate method for estimating new store revenue and hence location. However, previous attempts to explore the performance of the spatial interaction model in grocery retailing have been limited by access to loyalty card data. In this thesis we show that these models are unable to account for the heterogeneity in store conditions and consumer behaviour to model total store revenue. Notably, we find that at the regional scale the size of the errors are such that these models are unlikely to be used consistently in practice for estimating store revenue or locating new stores. Furthermore, that the performance achieved in previous applications are unlikely to be consistently replicated. Thus our results demonstrate that the spatial interaction model in its current form is no longer appropriate for modelling grocery store revenue. It is anticipated that these results may become a starting point for the development and application of alternative forms of models and methods for predicting grocery retailing store revenue. Notably, such new methods must be able to account for recent changes in consumer behaviour such as convenience store shopping, multi-purpose trips and the growing influence of e-commerce, alongside changes in retailers interaction strategies
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