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Articles 1 - 5 of 5
Full-Text Articles in Physical Sciences and Mathematics
School Policy Evaluated With Time-Reversible Markov Chain, Trajan Murphy, Iddo Ben-Ari
School Policy Evaluated With Time-Reversible Markov Chain, Trajan Murphy, Iddo Ben-Ari
Honors Scholar Theses
In this work we propose a reversible Markov chain scheme to model for the mobility of students affected by a grade school leveling policy. This model provides unified and mathematically tractable framework in which transition functions are sampled uniformly from the set of {\bf reversible} transition functions. The results from the study appear to confirm the disadvantageous effects of this school policy, on par with the of a previous model on the same policy.
Depressiongnn: Depression Prediction Using Graph Neural Network On Smartphone And Wearable Sensors, Param Bidja
Depressiongnn: Depression Prediction Using Graph Neural Network On Smartphone And Wearable Sensors, Param Bidja
Honors Scholar Theses
Depression prediction is a complicated classification problem because depression diagnosis involves many different social, physical, and mental signals. Traditional classification algorithms can only reach an accuracy of no more than 70% given the complexities of depression. However, a novel approach using Graph Neural Networks (GNN) can be used to reach over 80% accuracy, if a graph can represent the depression data set to capture differentiating features. Building such a graph requires 1) the definition of node features, which must be highly correlated with depression, and 2) the definition for edge metrics, which must also be highly correlated with depression. In …
Combinatorial Optimization: Introductory Problems And Methods, Erin Brownell
Combinatorial Optimization: Introductory Problems And Methods, Erin Brownell
Honors Scholar Theses
This paper will cover some topics of combinatorial optimization, the study of finding the best possible arrangement of a set of discrete objects. These topics include the shortest path problem and network flows, which can be extended to solve more complex problems. We will also briefly cover some basics of graph theory and solving linear programming problems to give context to the reader.
Analyzing The Mindsets And Behaviors Of Introductory Physics Students Through The Lens Of Intellectual Humility, Meagan Sundstrom
Analyzing The Mindsets And Behaviors Of Introductory Physics Students Through The Lens Of Intellectual Humility, Meagan Sundstrom
Honors Scholar Theses
Students often enter the physics classroom with intuitive conceptions drawn from real life experiences or former coursework, and may be hesitant or reluctant to re-evaluate these mindsets in favor of formally instructed knowledge. The goal of introductory physics courses is not only to teach and expose students to new content, but also to cultivate students’ ability to reason through and derive content knowledge through personal inquiry. This scientific process necessitates one’s abilities to be open-minded in terms of hearing evidence that contradicts his or her personal opinion, to be willing to discard any original misconceptions in the face of such …
Seeing Eye To Eye: A Machine Learning Approach To Automated Saccade Analysis, Maigh Attre
Seeing Eye To Eye: A Machine Learning Approach To Automated Saccade Analysis, Maigh Attre
Honors Scholar Theses
Abnormal ocular motility is a common manifestation of many underlying pathologies particularly those that are neurological. Dynamics of saccades, when the eye rapidly changes its point of fixation, have been characterized for many neurological disorders including concussions, traumatic brain injuries (TBI), and Parkinson’s disease. However, widespread saccade analysis for diagnostic and research purposes requires the recognition of certain eye movement parameters. Key information such as velocity and duration must be determined from data based on a wide set of patients’ characteristics that may range in eye shapes and iris, hair and skin pigmentation [36]. Previous work on saccade analysis has …