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Changemakers : Jeremey Love And Samantha Armstrong : Juris Doctorate : Defending Dreams In Challenging Times
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Law Review Symposium: Prisoners\u27 Rights: Protecting Civil Liberties Behind Bars & Beyond 11-7-2025
No full textLaw School News: Protecting LGBTQ+ Rights In Rhode Island: Insights From The Stonewall Lecture 11-18-2025
No full textInterwoven Architectural Skins: Biobased Material Fiber Construction Using Chuspata
No full textThis paper contributes to the growing body of research and application of biobased materials, an emerging technology in sustainable architecture, by specifically investigating potential architectural applications for the aquatic reed Typha domingensis. This invasive plant flourishes at the edges of lakes in the state of Michoacán, Mexico. Known locally as chuspata, the stalks are abundantly harvested for use by artisans in the region of Lake Pátzcuaro to produce domestic artcrafts and to clear the waterways for local fisherman. The chuspata artisans utilize the material through a weaving process that has deep cultural and pre-Hispanic origins and represents a circular process where environmental, economic, and cultural conditions intersect productively. Our research question asked whether chuspata could be employed at an architectural scale while building upon both the biological and cultural aspects of the raw material and its transformation through human processes. The pliability, cellular structure, linear rigidity, and sectional variability of the stalk were studied for their potential architectural performance along with the geometrical characteristics of common weaving patterns such as cadena, petate, and torcido. The study resulted in a collection of built prototypes and an exhibition pavilion developed in collaboration with artisans of Ihuatzio, along with architecture students and faculty from Mexico and the United States, featuring traditional and innovative weaving patterns to introduce porosity, rigidity, and three dimensionality, as a means to scale up the use of the material from small art craft objects to larger scale architectural components in horizontal and vertical configurations. Our outcomes point to the promise of employing rapidly renewable biobased materials to create light, aesthetically pleasing, and culturally resonant, temporary structures with low thermal mass to provide shade or as a screen in warm climates with significant urban heat islands. The low embodied energy and biodegradability of the material contribute to its sustainable use
Load Analysis and Material Optimization for an Underwater Autonomy Sensorized Task Platform
Get PDFWith developing technology, options for fabrication and material selection broaden. An example is 3D printable photopolymer resin used to create parts serving several applications. An application of this photopolymer resin is the ONR research project for the creation of the sensorized task platform for a robot to use underwater. The resin in this project was used to fabricate custom-made connecting brackets. These fabricated parts were hastily designed with no detailed analysis on stress distributions or material consumption. Using SolidWorks simulation analysis and Instron machines for experimentation, the goal of this project was to modify the original part with a reduced weight of 10% from the original design with no increased risk of failure. From this requirement, several parts were modified in SolidWorks from the original model that consumed unnecessary material. After several studies were conducted for the models, the final model achieved a 22% to 24% material reduction with no compromise to its strength
Optimizing Indoor Localization Using RSSI and IQ Data with Machine Learning
Get PDFThis paper explores implementing and evaluating a Bluetooth Low Energy (BLE)-based indoor localization system using Received Signal Strength Indicator (RSSI) and Angle of Arrival (AoA) data via machine learning. A survey of localization technologies (RFID, GPS, ZigBee, and BLE) provides context on capabilities and limitations in indoor positioning. IQ data and phase-based angle estimation show how BLE 5.1’s direction-finding features enable sub-meter accuracy. A multi-phase experiment in a three-story academic building examines model performance with different tag distributions, movement patterns, and environmental constraints. Machine learning models such as Support Vector Machines and Deep Neural Networks are trained and evaluated across six phases. The best models achieve 85–92% accuracy in room-level localization despite real-world signal interference. Limitations such as generalizability and signal obstruction are additionally discussed. The study demonstrates the viability of BLE-based machine learning forscalable, semi-precise indoor localization and identifies areas for optimization and future work
Climates’ Impact on Culture: Analyzing the Adaptive Capacity of Cultural Heritage Sites in the Global South Situated in the Scholarly and Public Spheres
Get PDFThis study used a qualitative case study analysis to answer the following research question: How are governments in the Global South tackling the challenge of preserving UNESCO World Heritage Sites in the face of climate change? This was done by investigating the adaptive capacity of the Chan Chan Archeological Site in Trujillo, Peru. The adaptive capacity of the site was evaluated using an adaptive capacity analytical framework that is composed of four determinants: learning capacity, room of autonomous change and access to information, access to resources, and leadership. These determinants were then sought out in State of Conservation Reports provided to UNESCO by the Republic of Peru.
The findings of this research were that the Chan Chan Archeological Site does not exhibit a high level of adaptive capacity and, therefore, will likely be unable to adapt to the environmental changes which will occur in the coming years. This is mainly due to insufficient access to resources, lack of a leadership body, and bureaucracy at the site which inhibits autonomous change