50107 research outputs found
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Universalizing Dark Heritage: Edward Berger’s All Quiet on the Western Front (2022)
No full textIn this study, I analyze Edward Berger’s 2022 film All Quiet on the Western Front as a “heritage film.” Scholars use this analytical lens to uncover the ways in which national cinemas portray history and thus partake in the construction of a national heritage. I argue that All Quiet on the Western Front is a special case of the heritage film, for two reasons. First, the film constructs heritage by depicting a history of trauma, thus creating what scholars have termed “dark heritage.” Second, the film does not construct a strictly national heritage; instead, it de-emphasizes the national perspective and universalizes the heritage of WWI. The film depicts the events of the Western Front as a traumatic part of history that concerns all of humanity, thus constructing a universal human heritage. In my study, I first define the terms “heritage,” “dark heritage,” and “heritage film.” Then, I analyze key scenes to show how All Quiet on the Front uses narrative and audiovisual tools to universalize the heritage of WWI.Master of Arts (M.A.
Leveraging AI in OER Creation
No full textDiscover how generative AI can revolutionize the creation of Open Educational Resources (OER) in this beginner-friendly session, Leveraging AI for OER Creation. Designed for those new to the world of AI, this session will guide you step-by-step through using AI tools to develop diverse and engaging educational content. Learn how to create images, infographics, assignments, quizzes, process guides, videos, and even interactive chatbots efficiently and creatively. Gain practical tips for integrating AI into your workflow to save time, enhance learner engagement, and make OER development more accessible. Whether you're an educator or content creator, this session will provide you with the foundational skills and confidence to harness the power of AI for impactful teaching and learning materials
Student Overboard: Rescuing One Discipline at a Time
No full textTake a behind-the-scenes look at this Louisiana team's innovative approach to developing an Introduction to Practical Nursing course. By collaboratively adapting an open licensed textbook, the team is working to enhance LPN education and training in the state. With federal grant support from LOUIS: The Library Network, eighteen cohorts are working to create courses for high-demand CTE programs. The Practical Nursing cohort stands out by incorporating recorded interviews with nursing students and practitioners into both the textbook and Moodle course. Discover how they’re making it happen and learn more about the Building a Competitive Workforce: Career and Technical Education (CTE) OER with Embedded Digital Skills grant
TOWARDS PRIVACY-SENSITIVE EDGE-BASED CROWD AND SYNDROMIC SIGNAL MONITORING CONTACTLESS SYSTEMS
No full textWith the advancement of mobile computing paradigms, smart contactless monitoring is increasingly finding its place in our daily lives. As mass-produced, power-efficient, and inexpensive hardware becomes more commonplace, coupled with recent advancements in real-time AI-based systems, the paradigms in contactless monitoring are rapidly evolving. However, despite these advancements, there remains a significant gap in building end-to-end innovative pipelines that demonstrate the practical applications and usefulness of such systems in solving real-world problems. Building practical applications in the real world while maintaining privacy, security, and accuracy remains a challenge to this day. Additionally, building syndromic signal monitoring platforms is an unexplored area of research. To address these issues, we have developed multiple novel, first-of-their-kind approaches using edge-AI for crowd and syndromic signal monitoring.
This thesis presents various applications of contactless monitoring in real-world settings, focusing on public health and crowd monitoring. We begin by discussing our work on FluSense, a first-of-its kind edge AI-based system that directly captures syndromic signals from hospital waiting areas to predict the number of flu patient visits, demonstrating how contactless monitoring can be utilized for public health surveillance.
Next, we explore how such a system can estimate occupancy in an area using only non-speech audio, ensuring participant privacy while maintaining high levels of accuracy compared to other modalities which are more privacy invasive and location dependant.
Additionally, we will discuss our follow-up work on FluSense for COVID-19 outbreak monitoring, highlighting why intelligently capturing audio-based syndromic signals can provide more informative data about COVID-19 outbreaks compared to other public health monitoring methods such as thermal body temperature scanning.
Finally, we address enhancing the privacy of contactless monitoring through Homomorphic Encryption (HE). Since standard neural network activations are often incompatible with HE, we investigate the use of PNNs. However, training high-degree PNNs, necessary for strong performance, faces significant hurdles like numerical instability and exploding gradients . To overcome this, we introduce and validate a novel training framework featuring Boundary Loss and Selective Gradient Clipping . This framework enables stable training of high-degree PNNs across diverse tasks, achieving accuracy comparable to standard networks while ensuring HE compatibility. This advancement facilitates the development of practical, privacy-preserving syndromic surveillance systems.
Through this research, we aim to advance the current state of intelligent real-time contactless monitoring systems that are cost-effective, accurate, and privacy-preserving, bridging the gap between technological capabilities and practical applications in public health and crowd monitoring.Doctor of Philosophy (Ph.D.
The 1960s Free Speech Movement: A Roadmap to Modern Student Activism and Campus Policing
No full textThe Convergence Between a Just Energy Transition and Community-Based Participatory Research: A Community's Input on Demand Response Programs
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Carjack Consecutive Interpreting Scenario (English-French)
No full textOverview: This is a consecutive interpreting scenario for interpreter practice purposes. In the recording, a male prosecutor examines a female witness in a carjack case.
Instructions for use: Use the recording to practice consecutive interpreting in the legal setting. Record your performance and compare it to the text after you finish. It is recommended to repeat the exercise as many times as needed