9,540 research outputs found

    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

    Raising Critical Consciousness in Engineering Education: A Critical Exploration of Transformative Possibilities in Engineering Education and Research

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    This thesis represents a critical exploration of the opportunities, challenges, and barriers to enacting social justice via the engineering curriculum. Through an ethnographic case study of a British engineering for sustainable development course, I illuminate tensions and contradictions of attempts to “do good” while “doing engineering” in a higher education setting. This work is couched within critical and anti-colonial theoretical frames. Through critical and reflexive analysis, I illustrate attempts of participants to innovate in engineering education toward a counter-hegemonic engineering practice, and highlight transformative possibilities, as well as barriers. This case illustrates how the structures that formed modern engineering continue to shape engineering higher education, restraining attempts to transform engineering training for social good.A central question that has driven this work has been: Is it possible to cultivate a more socially just form of engineering practice through engineering higher education? The function of asking this question has been to interrogate a core assumption in engineering education research – that with the right blend of educational interventions, we can make strides towards social justice. My intent in interrogating this assumption is not to be nihilistic per se. I believe it is entirely possible that engineering could potentially be wielded for just cause and consequence. However, if we do not critically examine our core assumptions around this issue, we may also miss out on the possibility that socially just engineering is not achievable, at least in the way we are currently approaching it or in the current context within which it exists.An examination of this topic is already underway in the US context. However, it is under-explored in a British context. Given the different historical trajectories of engineering and engineering in higher education between these two contexts, a closer look at the British context is warranted

    Coworking through the Pandemic: Flexibly Yours

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    Coworking can be defined as a paid for service (usually) providing shared workspace and amenities to users. When the pandemic hit, owing to the business model’s in-person foundations of physical proximity and shared amenities, the coworking industry was expected to be seriously impacted. Yet fast forward, and as the pandemic has played out, coworking businesses are uniquely positioned in this uncertain and changing workscape. This dissertation presents one of the first academic explorations into how independent coworking businesses fared in the initial year of the pandemic. Specifically, the research explores the following questions: 1. How did independent coworking businesses manage and adapt to the pandemic? 2. What is virtual coworking and what are the experiences of workers in these virtual coworking spaces? 3. How does coworking flexibility affect social support and connection? Using a critically interpretive poststructural approach, this ethnography included virtual fieldwork and interviews. Sixty hours of virtual participant observation and 30 loosely structured interviews were conducted with coworking stakeholders (i.e., owner-operators, managers, and users) over videoconferencing platforms. Secondary data included written fieldnotes and coworking documents. Results capture the strategies used by coworking business owner-operators and managers to sustain their businesses and the attendant relationships with coworking users, irrespective of whether or not a physical location could be provided under pandemic lockdowns. Given the expansion of coworking businesses into virtual service offerings, a key contribution of my research is the finding that co-location in a physical coworking space is not necessary to cultivate vibes and a sense of community. By removing the physical infrastructure of coworking, the virtual coworking product in which I participated points to both a reinforcement of and an emphasis on the centrality of social connection, support, and community. By de-centering the priority of a physical co-location, I conceptualize coworking businesses as commodified support infrastructures—affective atmospheres produced through the entanglement of human bodies, other living things, objects, and technologies in a space. In viewing coworking businesses as fluid affective atmospheres of support, my research adds to the emerging coworking scholarship that attends to the atmospheric qualities of coworking, the role of affective labour, and the possibilities of encounters and interactions as bodies, objects, and technologies interconnect. My results reinforce the deep ambivalence of coworking, capturing tensions between productivity and sociality, and a blurring of boundaries between professional and private, and work and leisure. The analysis also suggests that the inherent flexibility, informality, turnover, and autonomy in coworking practices can make creating stable social connections and support difficult. Finally, the COVID-19 crisis brought to light how coworking lies primarily outside the scope of current employment legislation, which includes occupational health and safety, employment standards, and workers’ compensation. In the absence of well-defined policy directions, coworking business owner-operators and managers made individualized decisions, thereby ultimately downloading further risk and responsibility onto their coworking users

    Migrating Integration from SOAP to REST : Can the Advantages of Migration Justify the Project?

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    This thesis investigates the functional and conceptual differences between SOAP-based and RESTful web services and their implications in the context of a real-world migration project. The primary research questions addressed are: • What are the key functional and conceptual differences between SOAP-based and RESTful web services? • How can SOAP-based and RESTful service clients be implemented into a general client? • Can developing a client to work with REST and SOAP be justified based on differences in performance and maintainability? The thesis begins with a literature review of the core principles and features of SOAP and REST, highlighting their strengths, weaknesses, and suitability for different use cases. A detailed comparison table is provided to summarize the key differences between the two web services. The thesis presents a case study of a migration project from Lemonsoft's web team, which involved adapting an existing integration to support SOAP-based and RESTful services. The project utilized design patterns and a general client implementation to achieve a unified solution compatible with both protocols. In terms of performance, the evaluation showed that the general client led to faster execution times and reduced memory usage, enhancing the overall system efficiency. Additionally, improvements in maintainability were achieved by simplifying the codebase, using design patterns and object factories, adopting an interface-driven design, and promoting collaborative code reviews. These enhancements have not only resulted in a better user experience but also minimized future resource demands and maintenance costs. In conclusion, this thesis provides valuable insights into the functional and conceptual differences between SOAP-based and RESTful web services, the challenges and best practices for implementing a general client, and the justification for resource usage in such a solution based on performance and maintainability improvements

    Unified System on Chip RESTAPI Service (USOCRS)

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    Abstract. This thesis investigates the development of a Unified System on Chip RESTAPI Service (USOCRS) to enhance the efficiency and effectiveness of SOC verification reporting. The research aims to overcome the challenges associated with the transfer, utilization, and interpretation of SoC verification reports by creating a unified platform that integrates various tools and technologies. The research methodology used in this study follows a design science approach. A thorough literature review was conducted to explore existing approaches and technologies related to SOC verification reporting, automation, data visualization, and API development. The review revealed gaps in the current state of the field, providing a basis for further investigation. Using the insights gained from the literature review, a system design and implementation plan were developed. This plan makes use of cutting-edge technologies such as FASTAPI, SQL and NoSQL databases, Azure Active Directory for authentication, and Cloud services. The Verification Toolbox was employed to validate SoC reports based on the organization’s standards. The system went through manual testing, and user satisfaction was evaluated to ensure its functionality and usability. The results of this study demonstrate the successful design and implementation of the USOCRS, offering SOC engineers a unified and secure platform for uploading, validating, storing, and retrieving verification reports. The USOCRS facilitates seamless communication between users and the API, granting easy access to vital information including successes, failures, and test coverage derived from submitted SoC verification reports. By automating and standardizing the SOC verification reporting process, the USOCRS eliminates manual and repetitive tasks usually done by developers, thereby enhancing productivity, and establishing a robust and reliable framework for report storage and retrieval. Through the integration of diverse tools and technologies, the USOCRS presents a comprehensive solution that adheres to the required specifications of the SOC schema used within the organization. Furthermore, the USOCRS significantly improves the efficiency and effectiveness of SOC verification reporting. It facilitates the submission process, reduces latency through optimized data storage, and enables meaningful extraction and analysis of report data

    METROPOLITAN ENCHANTMENT AND DISENCHANTMENT. METROPOLITAN ANTHROPOLOGY FOR THE CONTEMPORARY LIVING MAP CONSTRUCTION

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    We can no longer interpret the contemporary metropolis as we did in the last century. The thought of civil economy regarding the contemporary Metropolis conflicts more or less radically with the merely acquisitive dimension of the behaviour of its citizens. What is needed is therefore a new capacity for imagining the economic-productive future of the city: hybrid social enterprises, economically sustainable, structured and capable of using technologies, could be a solution for producing value and distributing it fairly and inclusively. Metropolitan Urbanity is another issue to establish. Metropolis needs new spaces where inclusion can occur, and where a repository of the imagery can be recreated. What is the ontology behind the technique of metropolitan planning and management, its vision and its symbols? Competitiveness, speed, and meritocracy are political words, not technical ones. Metropolitan Urbanity is the characteristic of a polis that expresses itself in its public places. Today, however, public places are private ones that are destined for public use. The Common Good has always had a space of representation in the city, which was the public space. Today, the Green-Grey Infrastructure is the metropolitan city's monument that communicates a value for future generations and must therefore be recognised and imagined; it is the production of the metropolitan symbolic imagery, the new magic of the city

    New Approach for Market Intelligence Using Artificial and Computational Intelligence

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    Small and medium sized retailers are central to the private sector and a vital contributor to economic growth, but often they face enormous challenges in unleashing their full potential. Financial pitfalls, lack of adequate access to markets, and difficulties in exploiting technology have prevented them from achieving optimal productivity. Market Intelligence (MI) is the knowledge extracted from numerous internal and external data sources, aimed at providing a holistic view of the state of the market and influence marketing related decision-making processes in real-time. A related, burgeoning phenomenon and crucial topic in the field of marketing is Artificial Intelligence (AI) that entails fundamental changes to the skillssets marketers require. A vast amount of knowledge is stored in retailers’ point-of-sales databases. The format of this data often makes the knowledge they store hard to access and identify. As a powerful AI technique, Association Rules Mining helps to identify frequently associated patterns stored in large databases to predict customers’ shopping journeys. Consequently, the method has emerged as the key driver of cross-selling and upselling in the retail industry. At the core of this approach is the Market Basket Analysis that captures knowledge from heterogeneous customer shopping patterns and examines the effects of marketing initiatives. Apriori, that enumerates frequent itemsets purchased together (as market baskets), is the central algorithm in the analysis process. Problems occur, as Apriori lacks computational speed and has weaknesses in providing intelligent decision support. With the growth of simultaneous database scans, the computation cost increases and results in dramatically decreasing performance. Moreover, there are shortages in decision support, especially in the methods of finding rarely occurring events and identifying the brand trending popularity before it peaks. As the objective of this research is to find intelligent ways to assist small and medium sized retailers grow with MI strategy, we demonstrate the effects of AI, with algorithms in data preprocessing, market segmentation, and finding market trends. We show with a sales database of a small, local retailer how our Åbo algorithm increases mining performance and intelligence, as well as how it helps to extract valuable marketing insights to assess demand dynamics and product popularity trends. We also show how this results in commercial advantage and tangible return on investment. Additionally, an enhanced normal distribution method assists data pre-processing and helps to explore different types of potential anomalies.Små och medelstora detaljhandlare är centrala aktörer i den privata sektorn och bidrar starkt till den ekonomiska tillväxten, men de möter ofta enorma utmaningar i att uppnå sin fulla potential. Finansiella svårigheter, brist på marknadstillträde och svårigheter att utnyttja teknologi har ofta hindrat dem från att nå optimal produktivitet. Marknadsintelligens (MI) består av kunskap som samlats in från olika interna externa källor av data och som syftar till att erbjuda en helhetssyn av marknadsläget samt möjliggöra beslutsfattande i realtid. Ett relaterat och växande fenomen, samt ett viktigt tema inom marknadsföring är artificiell intelligens (AI) som ställer nya krav på marknadsförarnas färdigheter. Enorma mängder kunskap finns sparade i databaser av transaktioner samlade från detaljhandlarnas försäljningsplatser. Ändå är formatet på dessa data ofta sådant att det inte är lätt att tillgå och utnyttja kunskapen. Som AI-verktyg erbjuder affinitetsanalys en effektiv teknik för att identifiera upprepade mönster som statistiska associationer i data lagrade i stora försäljningsdatabaser. De hittade mönstren kan sedan utnyttjas som regler som förutser kundernas köpbeteende. I detaljhandel har affinitetsanalys blivit en nyckelfaktor bakom kors- och uppförsäljning. Som den centrala metoden i denna process fungerar marknadskorgsanalys som fångar upp kunskap från de heterogena köpbeteendena i data och hjälper till att utreda hur effektiva marknadsföringsplaner är. Apriori, som räknar upp de vanligt förekommande produktkombinationerna som köps tillsammans (marknadskorgen), är den centrala algoritmen i analysprocessen. Trots detta har Apriori brister som algoritm gällande låg beräkningshastighet och svag intelligens. När antalet parallella databassökningar stiger, ökar också beräkningskostnaden, vilket har negativa effekter på prestanda. Dessutom finns det brister i beslutstödet, speciellt gällande metoder att hitta sällan förekommande produktkombinationer, och i att identifiera ökande popularitet av varumärken från trenddata och utnyttja det innan det når sin höjdpunkt. Eftersom målet för denna forskning är att hjälpa små och medelstora detaljhandlare att växa med hjälp av MI-strategier, demonstreras effekter av AI med hjälp av algoritmer i förberedelsen av data, marknadssegmentering och trendanalys. Med hjälp av försäljningsdata från en liten, lokal detaljhandlare visar vi hur Åbo-algoritmen ökar prestanda och intelligens i datautvinningsprocessen och hjälper till att avslöja värdefulla insikter för marknadsföring, framför allt gällande dynamiken i efterfrågan och trender i populariteten av produkterna. Ytterligare visas hur detta resulterar i kommersiella fördelar och konkret avkastning på investering. Dessutom hjälper den utvidgade normalfördelningsmetoden i förberedelsen av data och med att hitta olika slags anomalier
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