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Differential Pressure Sensor Analysis
Get PDFThe project goal is to fabricate a pressure sensor using p-type doped silicon. Doped silicon exhibits piezoresistive properties. The resistance of the material changes with mild deformation of the material. The sensor will then be implemented in a circuit design and evaluated. The stretch goal of the project is to build an air pressure sensor, but the baseline goal is to sense any pressure, be it from strain or weight. The material is sensitive to resistance changes across temperature, so a polyimide heater and sensing thermistor will be used to hold it at a stable temperature to stabilize that effect. The silicon wafer will be connected electrically into the circuit using an electrically conductive epoxy or adhesive. Plan A is to seal a piece of P-type silicon inside of a bulkhead wall to sense pressure between the inside of a sealed box and the outside. An idea from a classmate was to include insulative materials to help with the temperature challenge. Differential pressure sensors 2SMPP-03 and MP3V5050GP will be included on the board both to compare the built sensor to and as a backup plan to compare to one another in the event of sensor fabrication failure
Dual Axis Photovoltaic Solar Tracker VS Stationary Solar Panels
Get PDFThis paper explores the development and advantages of a dual-axis photovoltaic solar tracker, engineered to optimize solar energy capture by maintaining continuous alignment with the sun throughout the day. Solar panels operate based on the photovoltaic effect, where incident sunlight excites electrons in a semiconductor material, typically silicon - producing direct current electricity [1[. However, in stationary systems, this energy conversion peaks only when the panel’s orientation directly faces the sun, which happens briefly once per day. In contrast, a dual-axis tracker dynamically adjusts both azimuth and elevation angles to follow the sun’s path, significantly increasing daily energy output. In large-scale solar farms, industrial-grade actuators are commonly used to adjust the tilt angle of heavy solar arrays to follow the sun's elevation throughout the day [5[. However, these systems are typically mounted in a fixed horizontal position - usually facing east where the sun rises and only adjusts along a single axis. This half-stationary design limits their ability to track the sun's full trajectory, especially in locations where the sun’s path varies more dramatically with seasons or latitude. In contrast, our project offers a fully dynamic dual-axis tracking solution capable of adjusting both the horizontal (azimuth) and vertical (elevation) angles. This makes it effective in virtually any geographic location, especially useful for travelers using a solar energy system on vehicles such as RVs and Campers. For our design, we implemented a scaled-down version of this concept using servo motors and a compact gear system to mimic the functionality of industrial actuators. Despite its miniature size, the design follows the same control principles, utilizing sensor feedback to achieve real-time dual-axis sun tracking and maximizing solar exposure. The final system demonstrates that even at reduced scale, dynamic tracking dramatically improves solar efficiency compared to fixed panels. Our results confirm that dual-axis tracking is a practical and effective solution for maximizing solar output in both experimental and real-world applications
Confidence intervals for forced alignment with the Mason-Alberta Phonetic Segmenter
Get PDFForced alignment is a common tool in experimental phonetics to align audio with orthographic and phonetic transcriptions. Phonetic segmentation is not a straightforward process, however, and boundaries between phonetic segments cannot be easily determined. Most forced alignment tools provide a single estimate of a boundary based on conditional probabilities of segment categories given some acoustic data. The present project introduces a method of deriving confidence intervals for these boundaries using a neural network ensemble technique with the Mason-Alberta Phonetic Segmenter. Ten different segment classifier neural networks were previously trained, and the alignment process is repeated with each model. The alignment ensemble is then used to place the boundary at the median of the time points, and 97.85% confidence intervals are constructed using order statistics. On the Buckeye and TIMIT corpora, the ensemble boundaries show a slight improvement over using just a single model. The confidence intervals are incorporated into Praat TextGrids using a point tier, and they are also output as a table for researchers to analyze separately
Complete mitochondrial genomes of the Eastern lowland olingo (Bassaricyon alleni), ringtail (Bassariscus astutus), white-nosed coati (Nasua narica), and crab-eating raccoon (Procyon cancrivorus) elucidate the phylogeny of the Procyonidae
Get PDFBasque Txalaparta and Contemporary Percussion
Get PDFThe txalaparta was little-known around the time it underwent a revival within a Basque cultural reinvigoration in the 1960s, a politically complex time in the history of the Basque Country. Community and sharing are at the heart of txalaparta, both in its historical origins and performance practice. This dissertation aims to provide a point of access and interaction by contemporary percussionists and musicians through 1) developing a notation informed by the txalaparta practice, 2) applying that notation to comment on an observable pedagogy, 3) collaboration with contemporary classical composers to write original works inspired by txalaparta, all while 4) mindfully navigating the sociopolitical questions pertaining to these types of ethnomusicological and anthropological studies. It has developed into an experimental contemporary music practice that maintains those same values of community and sharing, as expressed through interviews with txalaparta performers, revivalists, and scholars in their readiness to share their ideas. A collaborative notation, along with original music towards this practice, will allow musicians of both cultures to share in this music-making practice and continue to complement each other in areas of performance, composition, and pedagogy
A TALE OF TWO LITERACIES: AN INTEGRATED COMPUTER SCIENCE CODING AND WRITING INSTRUCTION
Get PDFThe push to teach coding in schools continues to gain momentum. Coding helps students develop skills in problem-solving, critical thinking, and creativity, as well as improve overall academic performance. However, students with disabilities often face challenges in areas such as problem-solving, mathematics, and multistep reasoning when learning to code. Moreover, teachers may lack the time or proper training to effectively teach coding as a standalone subject to students with disabilities. To address these challenges, this study explores an integrated approach to teaching coding within the context of writing, due to the similarities between the two subjects. The purpose of this study is to examine whether a functional relation exists between integrated instructional coding/writing lessons, along with the use of a technology-based graphic organizer, and improvements in coding and writing skills for six upper elementary/middle school students with HID. The dependent variables included (a) speech blocks, (b) instances of sequencing, (c) central messaging, (d) the number of special effects, (e) the inclusion of a topic sentence, (f) the inclusion of supporting sentences, and (g) the inclusion of a summary sentence. This single-case multiple-baseline across participants study was conducted in a public charter school setting in the mid-Atlantic region of the United States. Results from this study show that upper elementary/middle school students with HID can greatly benefit from instructional lessons on coding/writing alongside a technology-based graphic organizer to improve coding/writing skills. Strong evidence of a functional relation between the independent and dependent variables was demonstrated for most measures, with the exception of moderate evidence of functional relation for central messaging and special effects measures. Implications and limitations are also discussed, along with where future research should be headed
Exceptional Mathematics Teachers' Beliefs about the Nature of Mathematics and Teaching and Learning
Get PDFTeachers' beliefs have been shown to play a fundamental role in their choices for instruction, task selection, and pedagogical decisions (Beswick, 2019; Cross Francis et al., 2014; Kertil et al., 2021; Šapkova, 2014). When asking teachers to align their practices with those envisioned by educational reformers (e.g., NCTM, 1989; NGA Center & CCSSO, 2010), teacher educators and professional developers must address teachers' underlying beliefs about the nature of mathematics (NOM) and teaching and learning. This qualitative explorative case study aimed to identify exceptional mathematics teachers' beliefs on the nature of mathematical knowledge teaching and learning. Exceptional middle school mathematics teachers in this study were recipients of the Presidential Award for Excellence in Mathematics and Science Teaching (PAEMST). PAEMST recipients are nationally recognized for using constructivist mathematics instruction that supports student learning through inquiry-based and student-centered instruction. A blended theoretical framework based on Earnest (1998) and Schommer-Aikins (2004) was employed to examine teachers’ beliefs and the relationship between their beliefs about NOM and teaching and learning, if and how their beliefs have evolved throughout their teaching career, and the contextual factors that were influential in the evolution of their beliefs. Teachers in this study were unfamiliar with the term but did provide a definition when asked about the source, structure, and stability of mathematical knowledge. Exceptional teachers' beliefs about the NOM evolved over their careers, from seeing mathematical knowledge as fixed and authoritative to seeing it as a dynamic discovery process involving nature and patterns. This shift in their beliefs about the NOM paralleled their teaching practices, emphasizing interconnectedness, independent problem-solving, and critical thinking, aligning with a Problem-Solving paradigm. Teachers identified the learning experiences that strongly influenced the change in their beliefs as those that fostered a deep understanding of mathematical concepts, often through targeted professional development. The implications for mathematics teacher education and professional development are discussed
DECISION SUPPORT FOR DESIGN SYNTHESIS MODELED AS A PARTIALLY OBSERVED MARKOV DECISION PROCESS
Get PDFThe purpose of this research is to improve the incorporation of risk management within the engineering design process. Current practices incorporate preliminary risk assessment but do not treat risk management holistically across system design and synthesis. Additionally, while most synthesis practices include pro forma verification activities, they do not provide guidance on the relative values of those activities, resulting in simultaneous generation of excess costs and false verification that the system meets requirements.The focus of this research is to demonstrate a proof-of-concept means of training decision support agents that will assist in optimally selecting design synthesis activities in a way that incorporates balanced risk avoidance, risk acceptance, and risk mitigation, including the costs (and value) of necessary verification activities. To that end, I have investigated the following hypotheses to test with this research: • Embedding the expected costs of system failures into a design’s state value function up-front will increase the likelihood of performing synthesis activities directed towards implementing risk mitigating features or of not performing synthesis activities directed towards implementing features that should be avoided. • Enforcing partial observability of the synthesis state when training decision support agents increases the relative value of performing verification activities. • Training a decision support agent against a design synthesis program will allow for one to determine, under various conditions, the relative preference of low-cost, low-accuracy testing to that of high-cost, high-accuracy testing. The proof-of-concept simulates synthesis of design specifications using a partially observed Markov decision process (POMDP). These simulations were then used to train decision support agents by means of reinforcement learning (RL) and approximate dynamic programming (ADP). After training, the agents were evaluated by recording their policy preferences given an observation of the design synthesis state. The results of the research demonstrated that agents trained in this way do decide to engage in risk avoidance activities as well as risk acceptance and mitigation, confirming the first hypothesis. However, there is not currently strong evidence to support the second or third hypotheses as the agents trained thus far rarely select to perform validation activities. The contributions of the research are as follows. This research provides a means to advance our understanding of the relative value of performing different verification activities at various points in the implementation of a feature in relation to sensitivity, specificity, and cost. And finally, this research advances the practice of risk management in design synthesis by demonstrating a method for optimally choosing between risk acceptance, mitigation, and avoidance during the design synthesis decision-making process
Us Against When: Futures and Complexity-Informed Conflict Transformation in the United States
Get PDFPeacebuilding practitioners in the United States comprise a sensemaking community that is grappling with multiple approaches to making positive change in the United States. Each organization and practitioner brings a set of methods to address that problem and an ideal audience that they believe should be the locus of change. The Us Against When project partnered with the Horizons Project and Common Ground USA to develop an image of a more peaceful United States and test how a peacebuilding scenario resonated with these organizations’ audiences. The research addressed the following question: How can a complexity-informed sensemaking approach help United States-based peace organizations align their image of the desired future with their constituents and improve practice by utilizing sensemaking data to inform decision-making in their programming? Sensemaking activities included interpretation of the scenario in the SenseMaker tool, participatory sensemaking process, and early feedback from the organizations about the ways the resulting insights informed their decision making. The peacebuilding scenario was interpreted by over 800 respondents in five states at higher risk for political violence (Arizona, Texas, Georgia, Pennsylvania, and Ohio). The research’s experimental approach demonstrated how techniques from futures studies and complexity science could contribute to the ability of peacebuilders to construct sensemaking feedback loops and better orient their practice in complex conflicts
BIM-Enabled Facility Management Framework and Simulation
Get PDFThis research offers a comprehensive investigation into developing and validating a standardized Building Information Modeling for Facility Management (BIM-FM) framework and simulation, supported by an empirical case study of the Long and Kimmy Nguyen Engineering Building. The primary objective of this study is to bridge the gap between theoretical BIM-FM frameworks and their practical application within the Architecture, Engineering, and Construction (AEC) industry to facilitate a more integrated and efficient approach to facility operation. The study adopts a mixed-methods research methodology that combines a qualitative literature review with a quantitative computational simulation. The qualitative phase focuses on a systematic review of existing BIM-FM frameworks and their implementation within the AEC sector. This serves to identify key performance indicators (KPIs) and industry requirements critical for BIM-FM framework development and integration, such as the Facility Condition Index (FCI), Maintenance Efficiency Index (MEI), and Replacement Efficiency Index (REI). The quantitative phase focuses on developing a computational simulation as a primary tool for empirically validating the proposed framework using the KPIs applied to a specific real-world context through a case study. This is to offer a robust platform for assessing BIM-FM strategies and providing quantifiable evidence of their utility and relevance. The proposed framework developed in the study is driven by insights from the literature review. It encompasses three main phases: (1) identifying best practices and gaps, (2) analyzing and comparing existing frameworks, and (3) formulating the framework's logic and workflow. This structured approach attempts to tackle the identified industry needs and challenges within the AEC industry. Furthermore, the research simulation development chapter details using Unity as a platform for operating the proposed simulation logic. The simulation integrates several core components to facilitate realistic presentations of facility operations and deepen the understanding of BIM-FM integration and predictive performance in long-term facility operation strategies. A core aspect of the research is the case study, focusing on the Long and Kimmy Nguyen Engineering Building at George Mason University. The case study selection adheres to criteria that ensure alignment with industry standards and contains diverse assets. This study also develops a BIM model of the facility and integrates it into the Unity simulation for accurate operation and performance assessment. The simulation results show that the proposed BIM-FM framework outperformed traditional FM and BIM-FM systems across key performance metrics. It maintained superior facility conditions, with a mean FCI of 0.794, and showed a lower FCI decrease over time than its counterparts, emphasizing its effectiveness in facility upkeep. Its mean MEI of 0.160 and REI of 6.03 were also notably higher, which shows greater maintenance and replacement efficacy. The framework's strategic approach also resulted in more consistent deferred maintenance work orders and higher average facility conditions, showcasing effective maintenance scheduling. Financially, the system demonstrated improved operational efficiency, saving an average of approximately \$91,424.94 annually, translating into over \$3.75 million in net savings over its lifecycle. Sensitivity analysis underscored its financial robustness and adaptability to economic changes, highlighting its long-term viability for FM operations. This application of a real-world facility provides critical insights into the framework's effectiveness and challenges encountered compared to other traditional systems, offering a comprehensive evaluation of its adaptability and versatility across a broad spectrum of FM requirements. In conclusion, this study contributes to the body of knowledge by offering a standardized BIM-FM framework that integrates qualitative insights with quantitative validations using a proposed novel FM simulation. This, coupled with a detailed real-world case study, highlights the potential of standardized BIM-FM systems to improve the facility operation process and provide a more integrated and efficient approach aligned with the current industry needs and standards