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Frost Protection from Small Protective Coverings
Full text linkThe purpose of this study was to determine the frost protection value of covering your plants in spring with polyethylene terephthalate (plastic) milk jugs or polyurethane rose cones. These coverings were placed in a field southeast of Kalamazoo, Michigan. Nocturnal temperatures were measured from May 7- 24, 1995 on clear and cloudy nights. Spring nocturnal temperatures inside one U.S. gallon milk jugs were slightly lower and those inside rose cones slightly higher than ambient air temperatures. Placing holes near the bases of these covers to provide additional circulation resulted in slightly lower nocturnal temperatures under the rose cones but no variation in temperatures within the milk jugs
A Home for the Homeless? Residents\u27 Perceptions of the Armitage Homeless Camp.
Full text linkResponding to a shortage in local shelter space and a preference for alternative forms of shelter, homeless people in Lane County, Oregon, took shelter unlawfully at the Armitage Homeless Camp (AHC). This paper examines the residents\u27 sense of place, concepts of home, and perceptions of the camp in an attempt to gauge the meaning and value of AHC from the perspective of urban campers. Data were collected from November to May, 1993, through participant observation, interviews, and surveys in the forms of questionnaires, cognitive mapping, and selfdirected photography. The data suggest that the campers identified with the environment and community at AHC and made attempts to create a home-like environment on site. The paper concludes that AHC offered a temporary sense of home and community to its residents
Place and Cultural Identity Among Guatemalan Indians: The Fragility of Goodness
Full text linkPlace experience may be more important to culture groups in war-torn and impoverished countries than to those in stable, developed regions. There is evidence from diverse sources that place experiences are directly relevant to the distinct Indian identities found within Guatemala\u27s western highlands. Individual municipios often are distinct in their clothing, language and attachment to the land. A rereading of ethnographies gathered during the last few decades, along with new survey data, suggest that place and identity are strongly linked, possibly in part as a response to a history of violence and oppression in the region
UC-1244 Agentic AI For Intelligent Customer Communication
No full textE-commerce web shoppers need fast, reliable responses to a variety of requests: account modifications, order tracking, or policy inquiries. Businesses must address user queries in a fast and efficient manner, or else lose customers. Multi-agent AI models boast the ability to answer customer questions and act upon consumer queries without outside intervention. However, research is sparse as to how agentic models can transfer benefit to large commercial software stacks under realistic commercial load. We sought to ask whether a multi-agent AI architecture can effectively handle commercial-scale e-commerce customer service tasks. Moreover, we investigated how a multi-agent AI architecture compares to traditional single-agent customer service solutions in handling complex e-commerce tasks. Our team developed a multi-agent AI architecture using specialized Claude Haiku agents coordinated through LangGraph, with a React frontend and PostgreSQL DB-Kafka backend. Testing will compare our multi-agent system against a single-agent baseline to evaluate effectiveness in handling complex customer service requests. Preliminary results have shown that an agentic AI architecture significantly increases query-response correctness for customer requests
UC-1226 iKnowIT: Multilingual Smartphone Tutorial Platform
No full textDigital literacy challenges affect millions of adults who struggle with basic smartphone use due to rapidly changing technology and limited support. iKnowIT is a dynamic, web-based learning platform designed to provide clear, visual, and multilingual tutorials that guide users through essential device functions. The goal of iKnowIT is to bridge the digital divide and empower users to engage confidently with modern technolog
UC-1168 Shepherd\u27s Sin - A Visual Novel Hybrid Game Made with Unity
No full textBy day, the grand old house shifts and shudders as if though alive. The six other residents gather in its lounges and parlors, sipping tea, squabbling over rooms, and faking civility. They laugh, they bicker, and they carry on as though nothing festers within these walls. When night falls, their facades rot away. They twist into monstrous embodiments of malice, each one a reflection of the seven deadly sins. By morning, they forget. You do not. Armed with a worn-out Monster Hunter’s Guidebook, you must reclaim its missing pages to learn who these people truly are, what they truly are. You must uncover their weaknesses and gather the weapons needed to destroy them before the storm clears
UC-0253 Stock Price Predictions Using LSTM & Technical Indicators
No full textStock price predictions using traditional statistical methods remains challenging due to market volatility and nonlinear dynamics. Long Short-Term Memory (LTSM) networks may model temporal dependencies in stock data more effectively than traditional statistical methods. Historical data for several companies’ stocks was obtained from Yahoo Finance, where it was then enriched with various technical indicators such as momentum and volatility. Preliminary analysis through Scala programming language suggests that incorporating these technical indicators can enhance short-term price prediction accuracy. Future works may seek to integrate additional trend and volume based indications in another, more robust, programming language like Python
UR-0227 Compilation of Binary Neurons to OBDDs
No full textA neuron with binary inputs & outputs corresponds to a Boolean function. To explain and verify the behavior a neuron (and by extension, a neural network), we can explain and verify its Boolean function. There has been recent interest in representing the Boolean function of such a neuron as an Ordered Binary Decision Diagram (OBDD), which facilitates such analyses. We propose an algorithm for compiling a binary neuron into an OBDD using a compiler that decomposes a Boolean function into a decision graph. We augment this compiler so that it outputs an OBDD instead. Our augmented compiler produces intermediate OBDDs that represent inner- and outer-bounds of the original neuron, tightening compilation progresses. Theoretically, decision graphs of binary neurons are more succinct than their decision trees. Empirically, compilation to decision graphs can scale to neurons with over a thousand features, compared to dozens of features using other compilers
UR-0199 Blood Flow Simulation From Coronary Computed Tomography Angiography Using Vnet
No full textCoronary artery disease (CAD) is one of the leading causes of death worldwide, making the assessment of blood flow and pressure distribution within coronary vessels essential for diagnosis and treatment planning. Fractional Flow Reserve (FFR) is a key measure used to determine the severity of arterial blockages, but traditional methods, such as invasive measurements or computational fluid dynamics (CFD) simulations, are not only time-consuming and costly but also invasive. This project explores the use of deep learning to predict blood pressure distribution in coronary arteries using a 3D convolutional neural network. The dataset consists of Coronary Computed Tomography Angiography (CCTA) scans paired with blood pressure obtained from CFD simulations. After preprocessing and voxelizing the CCTA scans, the VNet model learns to map the vessel’s geometry to its internal pressure distribution. Our model achieved a Pearson correlation of 0.93 and an R² score of 0.84 between the predicted and simulated pressures. These results indicate that VNet delivers accurate, spatially consistent pressure predictions that closely match CFD outputs while substantially reducing computation time. This approach underscores the potential of deep learning to accelerate non-invasive FFR estimation and enhance patient-specific cardiovascular analysis