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A Computational Framework to Optimize Piezoelectric Power Harvesting from a UAV Wing
Get PDFThis paper proposes a computational framework to optimize the ambient power harvesting from an unmanned air vehicle wing by means of piezoelectricity. First, the wing shape and material are selected based on specific design factors. The wing is then subjected to a vibrational analysis in order to predict the first torsional frequency required to calculate an optimum charging speed. The harvester module is then selected so that the vibration frequency of the charging speed fails within the resonance frequency of the harvester. A finite element modeling is conducted to predict the harvester output voltage during the chagrining speed. Finally, a power management circuit is designed to boost the harvester output voltage to 5V. The proposed framework was validated experimentally using the car-top rig method (error 2.18%). Twenty minutes of flight time were enough to recharge a 600mAh lithium-ion battery used to energize a 5V servomotor that controls the wing flap
Midwest Entrepreneurship Case Competition Website (2023-2024)
Get PDFArchived Midwest Entrepreneurship Case Competition Website (November 2023 - October 2024
New Paths in Jewish and Religious Studies: Essays in Honor of Professor Elliot R. Wolfson
Get PDFThe work of Elliot R. Wolfson has profoundly influenced the fields of Jewish studies as well as philosophy and religion more broadly. His radically new approaches have created pioneering ways of analyzing texts and thinking about religion through the lens of gender, sexuality, and feminist theory. The contributors to New Paths in Jewish and Religious Studies: Essays in Honor of Professor Elliot R. Wolfson, many of whom are internationally renowned scholars, hearken from diverse fields. Each has learned from and collaborated with Wolfson as student or colleague, and each has expanded the new scholarly directions initiated by Wolfson’s groundbreaking work. Wolfson’s scholarship gives us innovative ways to think about Judaism and a fresh understanding of religion. Not only a scholar, Wolfson is one of the most important Jewish thinkers of our day. Chapters are grouped according to the categories of religion, Jewish thought and philosophy, and a focused section on Kabbalah, Wolfson’s primary specialization. The volume concludes with a bibliography of Wolfson’s published work and a selection of his poetry.https://docs.lib.purdue.edu/purduepress_ebooks/1074/thumbnail.jp
A Comprehensive Analysis of How Pet Ownership Impacts the Experiences and Well-Being of Homeless Individuals
Get PDFThis paper conducts a thorough examination of the relationship between pet ownership and homelessness. In a context where homelessness in the United States is a growing concern, we delve into an aspect that has received little attention: how homeless individuals and their pets interact. Through an extensive review of existing research, this paper aims to uncover the demographic characteristics of homeless pet owners and understand the significant effects of this bond. Our findings reveal that homeless individuals with pets come from diverse backgrounds, including various ages, genders, and racial backgrounds. Their pets provide not only companionship but also emotional support, improved physical health, and a deterrent against criminal behavior. Homeless pet owners often prioritize their pets’ well-being, showing the depth of their attachment. However, pet ownership among the homeless comes with challenges. These individuals face barriers to accessing necessary medical care, encounter difficulties finding shelters that allow pets, and sometimes choose to stay on the streets to remain with their pets. They also face discrimination from their communities, which compounds their existing difficulties. This research identifies gaps in the existing literature and suggests areas for further investigation. Future studies should examine the well-being of homeless-owned pets, the impact of the COVID-19 pandemic on homelessness and pet ownership, and the effectiveness of shelters that accommodate pets and mobile health care services. Addressing these gaps will enhance our understanding of the complex relationship between pet ownership and homelessness and improve support services and policies for this vulnerable population
Integrated Virtual Reality for a Motivating and Effectual Language-Learning Experience
Get PDFThe increased globalization of STEM fields and the resulting needed multilingualism provide ample reason to infuse language classrooms with responsive and immersive technologies. Furthermore, technology has proven to be a powerful resource to motivate students, regardless of the field. Early results show that the use of immersive technology positively affects both motivation and retention, and that students desire these types of technology and resources in more of their courses
The Impact of Geospatial Contexts and Out-of-School Experiences on Students\u27 STEM Identity Formation
Get PDFSTEM teaching faces challenges in varied geospatial contexts (Mulvey et al., 2023), where place and space factors play a significant role. This research brief explores the influence of place and space in shaping students\u27 STEM identities throughout their educational journey, with a specific emphasis on the role of out-of-school experiences in fostering student learning and interest in STEM careers, particularly among middle school students
Extreme Image Transformations Improve Latent Representations in Machines
Get PDFShuffling pixels in an image helps machines to learn a more robust object representation. To probe the strategies used by humans and machines for object recognition, we introduce Extreme Image Transformations (EITs). Machines rely heavily on exploiting low-level features like color and texture, so their performance degrades on out-of-distribution and adversarial inputs. Humans depend on high-level features like shapes and contours, making them relatively robust to image distortions. EITs systematically shuffle the pixels in an image, parameterized by the size of grids, probability of shuffle and binary block movement, distorting the structure of objects at both local and global levels. We found that humans maintain high accuracy on globally transformed images while machines perform well on locally transformed images, as shown in our prior work. Adversarial attacks further demonstrate the inability of machines to learn robust representations with popular vision datasets and train- ing paradigms. To close this performance gap, we tested EITs fine-tuned networks on images distorted with common corruptions (weather, gaussian, etc.) We found that EIT fine-tuned networks learn robust object representations, demonstrating improved performance on adversarial attacks, with strong activations in object regions. Fine-tuning with EITs forces networks to focus on essential object features rather than superficial cues, improving generalization. Our work quantifies differences in strategies used in human and artificial vision, highlighting neuro-inspired techniques to enhance neural networks. Understanding differences between biological and artificial vision can enable more human-like computer vision techniques