5,600 research outputs found

    A Political Theory of Engineered Systems and A Study of Engineering and Justice Workshops

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    Since there are good reasons to think that some engineered systems are socially undesirable—for example, internal combustion engines that cause climate change, algorithms that are racist, and nuclear weapons that can destroy all life—there is a well-established literature that attempts to identify best practices for designing and regulating engineered systems in order to prevent harm and promote justice. Most of this literature, especially the design theory and engineering justice literature meant to help guide engineers, focuses on environmental, physical, social, and mental harms such as ecosystem and bodily poisoning, racial and gender discrimination, and urban alienation. However, the literature that focuses on how engineered systems can produce political harms—harms to how we shape the way we live in community together—is not well established. The first part of this thesis contributes to identifying how particular types of engineered systems can harm a democratic politics. Building on democratic theory, philosophy of collective harms, and design theory, it argues that engineered systems that extend in space and time beyond a certain threshold subvert the knowledge and empowerment necessary for a democratic politics. For example, the systems of global shipping and the internet that fundamentally shape our lives are so large that people cannot attain the knowledge necessary to regulate them well nor the empowerment necessary to shape them. The second part of this thesis is an empirical study of a workshop designed to encourage engineering undergraduates to understand how engineered systems can subvert a democratic politics, with the ultimate goal of supporting students in incorporating that understanding into their work. 32 Dartmouth undergraduate engineering students participated in the study. Half were assigned to participate in a workshop group, half to a control group. The workshop group participants took a pretest; then participated in a 3-hour, semi-structured workshop with 4 participants per session (as well as a discussion leader and note-taker) over lunch or dinner; and then took a posttest. The control group participants took the same pre- and post- tests, but had no suggested activity in the intervening 3 hours. We find that the students who participated in workshops had a statistically significant test-score improvement as compared to the control group (Brunner-Munzel test, p \u3c .001). Using thematic analysis methods, we show the data is consistent with the hypothesis that workshops produced a score improvement because of certain structure (small size, long duration, discussion-based, over homemade food) and content (theoretically rich, challenging). Thematic analysis also reveals workshop failures and areas for improvement (too much content for the duration, not well enough organized). The thesis concludes with a discussion of limitations and suggestions for future theoretical, empirical, and pedagogical research

    Distributed Ledger Technology (DLT) Applications in Payment, Clearing, and Settlement Systems:A Study of Blockchain-Based Payment Barriers and Potential Solutions, and DLT Application in Central Bank Payment System Functions

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    Payment, clearing, and settlement systems are essential components of the financial markets and exert considerable influence on the overall economy. While there have been considerable technological advancements in payment systems, the conventional systems still depend on centralized architecture, with inherent limitations and risks. The emergence of Distributed ledger technology (DLT) is being regarded as a potential solution to transform payment and settlement processes and address certain challenges posed by the centralized architecture of traditional payment systems (Bank for International Settlements, 2017). While proof-of-concept projects have demonstrated the technical feasibility of DLT, significant barriers still hinder its adoption and implementation. The overarching objective of this thesis is to contribute to the developing area of DLT application in payment, clearing and settlement systems, which is still in its initial stages of applications development and lacks a substantial body of scholarly literature and empirical research. This is achieved by identifying the socio-technical barriers to adoption and diffusion of blockchain-based payment systems and the solutions proposed to address them. Furthermore, the thesis examines and classifies various applications of DLT in central bank payment system functions, offering valuable insights into the motivations, DLT platforms used, and consensus algorithms for applicable use cases. To achieve these objectives, the methodology employed involved a systematic literature review (SLR) of academic literature on blockchain-based payment systems. Furthermore, we utilized a thematic analysis approach to examine data collected from various sources regarding the use of DLT applications in central bank payment system functions, such as central bank white papers, industry reports, and policy documents. The study's findings on blockchain-based payment systems barriers and proposed solutions; challenge the prevailing emphasis on technological and regulatory barriers in the literature and industry discourse regarding the adoption and implementation of blockchain-based payment systems. It highlights the importance of considering the broader socio-technical context and identifying barriers across all five dimensions of the social technical framework, including technological, infrastructural, user practices/market, regulatory, and cultural dimensions. Furthermore, the research identified seven DLT applications in central bank payment system functions. These are grouped into three overarching themes: central banks' operational responsibilities in payment and settlement systems, issuance of central bank digital money, and regulatory oversight/supervisory functions, along with other ancillary functions. Each of these applications has unique motivations or value proposition, which is the underlying reason for utilizing in that particular use case

    Structuring the State’s Voice of Contention in Harmonious Society: How Party Newspapers Cover Social Protests in China

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    During the Chinese Communist Party’s (CCP) campaign of building a ‘harmonious society’, how do the official newspapers cover the instances of social contention on the ground? Answering this question will shed light not only on how the party press works but also on how the state and the society interact in today’s China. This thesis conceptualises this phenomenon with a multi-faceted and multi-levelled notion of ‘state-initiated contentious public sphere’ to capture the complexity of mediated relations between the state and social contention in the party press. Adopting a relational approach, this thesis analyses 1758 news reports of ‘mass incident’ in the People’s Daily and the Guangming Daily between 2004 and 2020, employing cluster analysis, qualitative comparative analysis, and social network analysis. The thesis finds significant differences in the patterns of contentious coverage in the party press at the level of event and province and an uneven distribution of attention to social contention across incidents and regions. For ‘reported regions’, the thesis distinguishes four types of coverage and presents how party press responds differently to social contention in different scenarios at the provincial level. For ‘identified incidents’, the thesis distinguishes a cumulative type of visibility based on the quantity of coverage from a relational visibility based on the structure emerging from coverage and explains how different news-making rationales determine whether instances receive similar amounts of coverage or occupy similar positions within coverage. Eventually, by demonstrating how the Chinese state strategically uses party press to respond to social contention and how social contention is journalistically placed in different positions in the state’s eyes, this thesis argues that what social contention leads to is the establishment of complex state-contention relations channelled through the party press

    UMSL Bulletin 2023-2024

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    The 2023-2024 Bulletin and Course Catalog for the University of Missouri St. Louis.https://irl.umsl.edu/bulletin/1088/thumbnail.jp

    Natural and Technological Hazards in Urban Areas

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    Natural hazard events and technological accidents are separate causes of environmental impacts. Natural hazards are physical phenomena active in geological times, whereas technological hazards result from actions or facilities created by humans. In our time, combined natural and man-made hazards have been induced. Overpopulation and urban development in areas prone to natural hazards increase the impact of natural disasters worldwide. Additionally, urban areas are frequently characterized by intense industrial activity and rapid, poorly planned growth that threatens the environment and degrades the quality of life. Therefore, proper urban planning is crucial to minimize fatalities and reduce the environmental and economic impacts that accompany both natural and technological hazardous events

    LIPIcs, Volume 251, ITCS 2023, Complete Volume

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    LIPIcs, Volume 251, ITCS 2023, Complete Volum

    UMSL Bulletin 2022-2023

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    The 2022-2023 Bulletin and Course Catalog for the University of Missouri St. Louis.https://irl.umsl.edu/bulletin/1087/thumbnail.jp

    Synthetic Aperture Radar (SAR) Meets Deep Learning

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    This reprint focuses on the application of the combination of synthetic aperture radars and depth learning technology. It aims to further promote the development of SAR image intelligent interpretation technology. A synthetic aperture radar (SAR) is an important active microwave imaging sensor, whose all-day and all-weather working capacity give it an important place in the remote sensing community. Since the United States launched the first SAR satellite, SAR has received much attention in the remote sensing community, e.g., in geological exploration, topographic mapping, disaster forecast, and traffic monitoring. It is valuable and meaningful, therefore, to study SAR-based remote sensing applications. In recent years, deep learning represented by convolution neural networks has promoted significant progress in the computer vision community, e.g., in face recognition, the driverless field and Internet of things (IoT). Deep learning can enable computational models with multiple processing layers to learn data representations with multiple-level abstractions. This can greatly improve the performance of various applications. This reprint provides a platform for researchers to handle the above significant challenges and present their innovative and cutting-edge research results when applying deep learning to SAR in various manuscript types, e.g., articles, letters, reviews and technical reports

    Query optimization by using derivability in a data warehouse environment

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    Materialized summary tables and cached query results are frequently used for the optimization of aggregate queries in a data warehouse. Query rewriting techniques are incorporated into database systems to use those materialized views and thus avoid the access of the possibly huge raw data. A rewriting is only possible if the query is derivable from these views. Several approaches can be found in the literature to check the derivability and find query rewritings. The specific application scenario of a data warehouse with its multidimensional perspective allows the consideration of much more semantic information, e.g. structural dependencies within the dimension hierarchies and different characteristics of measures. The motivation of this article is to use this information to present conditions for derivability in a large number of relevant cases which go beyond previous approaches
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