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Articles 1 - 4 of 4
Full-Text Articles in Probability
Risk-Based Machine Learning Approaches For Probabilistic Transient Stability, Umair Shahzad
Risk-Based Machine Learning Approaches For Probabilistic Transient Stability, Umair Shahzad
Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research
Power systems are getting more complex than ever and are consequently operating close to their limit of stability. Moreover, with the increasing demand of renewable wind generation, and the requirement to maintain a secure power system, the importance of transient stability cannot be overestimated. Considering its significance in power system security, it is important to propose a different approach for enhancing the transient stability, considering uncertainties. Current deterministic industry practices of transient stability assessment ignore the probabilistic nature of variables (fault type, fault location, fault clearing time, etc.). These approaches typically provide a conservative criterion and can result in expensive …
Improving Bayesian Graph Convolutional Networks Using Markov Chain Monte Carlo Graph Sampling, Aneesh Komanduri
Improving Bayesian Graph Convolutional Networks Using Markov Chain Monte Carlo Graph Sampling, Aneesh Komanduri
Computer Science and Computer Engineering Undergraduate Honors Theses
In the modern age of social media and networks, graph representations of real-world phenomena have become incredibly crucial. Often, we are interested in understanding how entities in a graph are interconnected. Graph Neural Networks (GNNs) have proven to be a very useful tool in a variety of graph learning tasks including node classification, link prediction, and edge classification. However, in most of these tasks, the graph data we are working with may be noisy and may contain spurious edges. That is, there is a lot of uncertainty associated with the underlying graph structure. Recent approaches to modeling uncertainty have been …
Modified Firearm Discharge Residue Analysis Utilizing Advanced Analytical Techniques, Complexing Agents, And Quantum Chemical Calculations, William J. Feeney
Modified Firearm Discharge Residue Analysis Utilizing Advanced Analytical Techniques, Complexing Agents, And Quantum Chemical Calculations, William J. Feeney
Graduate Theses, Dissertations, and Problem Reports
The use of gunshot residue (GSR) or firearm discharge residue (FDR) evidence faces some challenges because of instrumental and analytical limitations and the difficulties in evaluating and communicating evidentiary value. For instance, the categorization of GSR based only on elemental analysis of single, spherical particles is becoming insufficient because newer ammunition formulations produce residues with varying particle morphology and composition. Also, one common criticism about GSR practitioners is that their reports focus on the presence or absence of GSR in an item without providing an assessment of the weight of the evidence. Such reports leave the end-used with unanswered questions, …
Design Project: Smart Headband, John Michel, Jack Durkin, Noah Lewis
Design Project: Smart Headband, John Michel, Jack Durkin, Noah Lewis
Williams Honors College, Honors Research Projects
Concussion in sports is a prevalent medical issue. It can be difficult for medical professionals to diagnose concussions. With the fast pace nature of many sports, and the damaging effects of concussions, it is important that any concussion risks are assessed immediately. There is a growing trend of wearable technology that collects data such as steps and provides the wearer with in-depth information regarding their performance. The Smart Headband project created a wearable that can record impact data and provide the wearer with a detailed analysis on their risk of sustaining a concussion. The Smart Headband uses accelerometers and gyroscopes …