1,165 research outputs found

    Undergraduate Catalog of Studies, 2023-2024

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    Graduate Catalog of Studies, 2023-2024

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    Undergraduate Catalog of Studies, 2023-2024

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    Graduate Catalog of Studies, 2023-2024

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    Microcredentials to support PBL

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    Undergraduate Catalog of Studies, 2022-2023

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    Control and Archaism

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    The presentation will delve into the relationship between control society and archaism. Deleuze’s conceptualization of control implies the reconfiguration of former spaces of discipline. While the Foucauldian model of discipline was characterized by enclosed spaces (such as prisons, armies, and churches), Deleuze’s notion of control highlights a continuous network where individuals are no longer molded but modulated. This prompts us to ponder the shift in the temporal structure that occurs during the transition from a disciplinary society to one governed by control. Specifically, this presentation aims to explore the disparities in our historical perspectives when viewed from disciplinary and control paradigms. In this context, I will explore Deleuze and Guattari's concept of ‘archaism’. According to Deleuze and Guattari, archaism is an inherent aspect of capitalism, its continual endeavor to reconstruct territoriality and replicate antiquated coding patterns. Capitalism necessitates archaism due to its lack of inherent belief structures. In essence, the system, which the duo name the ‘age of cynicism’, requires the revival of old codes to sustain its systems of subjugation and dominance. As my presentation will demonstrate, one can discern a transformation in the evolution of archaism as society shifts from discipline to control. By comparing the fascist archaism of the thirties in Germany and the archaism of contemporary alt-right movements, I will show that a disciplinary society presupposes a more centralized form of archaism, which is highly susceptible to state control and deeply ingrained in the institutional fabric of social life. Conversely, a control society implies a diversification and creativity in archaic attitudes, hinting at its potential for emancipation—a viewpoint emphasized by Deleuze and Guattari themselves in ’Anti-Oedipus’

    Artificial Intelligence for the Edge Computing Paradigm.

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    With modern technologies moving towards the internet of things where seemingly every financial, private, commercial and medical transaction being carried out by portable and intelligent devices; Machine Learning has found its way into every smart device and application possible. However, Machine Learning cannot be used on the edge directly due to the limited capabilities of small and battery-powered modules. Therefore, this thesis aims to provide light-weight automated Machine Learning models which are applied on a standard edge device, the Raspberry Pi, where one framework aims to limit parameter tuning while automating feature extraction and a second which can perform Machine Learning classification on the edge traditionally, and can be used additionally for image-based explainable Artificial Intelligence. Also, a commercial Artificial Intelligence software have been ported to work in a client/server setups on the Raspberry Pi board where it was incorporated in all of the Machine Learning frameworks which will be presented in this thesis. This dissertation also introduces multiple algorithms that can convert images into Time-series for classification and explainability but also introduces novel Time-series feature extraction algorithms that are applied to biomedical data while introducing the concept of the Activation Engine, which is a post-processing block that tunes Neural Networks without the need of particular experience in Machine Leaning. Also, a tree-based method for multiclass classification has been introduced which outperforms the One-to-Many approach while being less complex that the One-to-One method.\par The results presented in this thesis exhibit high accuracy when compared with the literature, while remaining efficient in terms of power consumption and the time of inference. Additionally the concepts, methods or algorithms that were introduced are particularly novel technically, where they include: • Feature extraction of professionally annotated, and poorly annotated time-series. • The introduction of the Activation Engine post-processing block. • A model for global image explainability with inference on the edge. • A tree-based algorithm for multiclass classification

    (b2023 to 2014) The UNBELIEVABLE similarities between the ideas of some people (2006-2016) and my ideas (2002-2008) in physics (quantum mechanics, cosmology), cognitive neuroscience, philosophy of mind, and philosophy (this manuscript would require a REVOLUTION in international academy environment!)

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    (b2023 to 2014) The UNBELIEVABLE similarities between the ideas of some people (2006-2016) and my ideas (2002-2008) in physics (quantum mechanics, cosmology), cognitive neuroscience, philosophy of mind, and philosophy (this manuscript would require a REVOLUTION in international academy environment!

    Experiences of African American Students in a STEM-Focused Community Program

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    The United States has invested millions of dollars in STEM program initiatives; however, African Americans in STEM career fields are underrepresented. The purpose of this qualitative hermeneutic phenomenological study aimed to explore the lived experiences of African-American first-year college students from rural communities in a STEM program and whether their experiences influenced their decision to pursue a STEM major in college. Spencer’s phenomenological variant of ecological systems theory (PVEST) was used to frame the study. Data were collected from semistructured interviews with eight African American first-year college students from rural communities. Coding analysis involved identifying meaning units and situated narratives to identify seven themes: experiential learning projects, sources of support, early exposure, networking opportunities, lack of diversity, self-perception, and disconnect between college expectations and student preparedness. Findings revealed that although students found STEM programs valuable and engaging, they lacked information about college expectations and diversity. PVEST highlighted the importance of understanding people’s processes when they perceive the world. This study provides implications for stakeholders to consider the experiences of African American students when designing pipeline STEM programs that address the underrepresentation of African Americans in STEM career fields
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