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Articles 1 - 12 of 12
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Educators’ Perspectives Of Using (Or Not Using) Online Exam Proctoring., David Balash, Elena Korkes, Miles Grant, Adam J. Aviv, Rahel A. Fainchtein, Micah Sherr
Educators’ Perspectives Of Using (Or Not Using) Online Exam Proctoring., David Balash, Elena Korkes, Miles Grant, Adam J. Aviv, Rahel A. Fainchtein, Micah Sherr
Department of Math & Statistics Faculty Publications
The onset of the COVID-19 pandemic changed the land- scape of education and led to increased usage of remote proc- toring tools that are designed to monitor students when they take assessments outside the classroom. While prior work has explored students’ privacy and security concerns regard- ing online proctoring tools, the perspective of educators is under explored. Notably, educators are the decision makers in the classrooms and choose which remote proctoring ser- vices and the level of observations they deem appropriate. To explore how educators balance the security and privacy of their students with the requirements of remote exams, we …
Topology-Guided Roadmap Construction With Dynamic Region Sampling, Read Sandström, Diane Uwacu, Jory Denny, Nancy M. Amato
Topology-Guided Roadmap Construction With Dynamic Region Sampling, Read Sandström, Diane Uwacu, Jory Denny, Nancy M. Amato
Department of Math & Statistics Faculty Publications
Many types of planning problems require discovery of multiple pathways through the environment, such as multi-robot coordination or protein ligand binding. The Probabilistic Roadmap (PRM) algorithm is a powerful tool for this case, but often cannot efficiently connect the roadmap in the presence of narrow passages. In this letter, we present a guidance mechanism that encourages the rapid construction of well-connected roadmaps with PRM methods. We leverage a topological skeleton of the workspace to track the algorithm's progress in both covering and connecting distinct neighborhoods, and employ this information to focus computation on the uncovered and unconnected regions. We demonstrate …
Asymptotically-Optimal Topological Nearest-Neighbor Filtering, Read Sandström, Jory Denny, Nancy M. Amato
Asymptotically-Optimal Topological Nearest-Neighbor Filtering, Read Sandström, Jory Denny, Nancy M. Amato
Department of Math & Statistics Faculty Publications
Nearest-neighbor finding is a major bottleneck for sampling-based motion planning algorithms. The cost of finding nearest neighbors grows with the size of the roadmap, leading to a significant computational bottleneck for problems which require many configurations to find a solution. In this work, we develop a method of mapping configurations of a jointed robot to neighborhoods in the workspace that supports fast search for configurations in nearby neighborhoods. This expedites nearest-neighbor search by locating a small set of the most likely candidates for connecting to the query with a local plan. We show that this filtering technique can preserve asymptotically-optimal …
Score Following With Hidden Tempo Using A Switching State-Space Model, Yucong Jiang, Chris Raphael
Score Following With Hidden Tempo Using A Switching State-Space Model, Yucong Jiang, Chris Raphael
Department of Math & Statistics Faculty Publications
A score-following program traces the notes in a musical score during a performance. This capability is essential to many meaningful applications that synchronize audio with a score in an on-line fashion. Existing algorithms often stumble on certain difficult cases, one of which is piano music. This paper presents a new method to tackle such cases. The method treats tempo as a variable rather than a constant (with constraints), allowing the program to adapt to live performance variations. This is first expressed by a Kalman filter model at the note level, and then by an almost equivalent switching state-space model at …
A Tidy Data Model For Natural Language Processing Using Cleannlp, Taylor B. Arnold
A Tidy Data Model For Natural Language Processing Using Cleannlp, Taylor B. Arnold
Department of Math & Statistics Faculty Publications
Recent advances in natural language processing have produced libraries that extract low level features from a collection of raw texts. These features, known as annotations, are usually stored internally in hierarchical, tree-based data structures. This paper proposes a data model to represent annotations as a collection of normalized relational data tables optimized for exploratory data analysis and predictive modeling. The R package cleanNLP, which calls one of two state of the art NLP libraries (CoreNLP or spaCy), is presented as an implementation of this data model. It takes raw text as an input and returns a list of normalized tables. …
Introducing Computer Science In An Integrated Science Course, Barry Lawson, Doug Szajda, Lewis Barnett Iii
Introducing Computer Science In An Integrated Science Course, Barry Lawson, Doug Szajda, Lewis Barnett Iii
Department of Math & Statistics Faculty Publications
This paper describes our implementation and experience of incorporating computer science concepts into a team-taught, first-year interdisciplinary course for prospective science majors at the University of Richmond. The course integrates essential concepts from each of five STEM disciplines: biology, chemistry, computer science, mathematics, and physics. Including computer science in this course faces three primary challenges: few of the students have any CS background; the time devoted to CS instruction is reduced compared to a traditional introductory CS course; and the spirit of the course requires the CS material to be highly integrated with the other disciplines. Here we discuss our …
Challenging Disciplinary Boundaries In The First Year: A New Introductory Integrated Science Course For Stem Majors, Lisa Gentile, Lester Caudill, Mirela Fetea, April L. Hill, Kathy Hoke, Barry Lawson, Ovidiu Z. Lipan, Michael Kerckhove, Carol A. Parish, Krista J. Stenger, Doug Szajda
Challenging Disciplinary Boundaries In The First Year: A New Introductory Integrated Science Course For Stem Majors, Lisa Gentile, Lester Caudill, Mirela Fetea, April L. Hill, Kathy Hoke, Barry Lawson, Ovidiu Z. Lipan, Michael Kerckhove, Carol A. Parish, Krista J. Stenger, Doug Szajda
Department of Math & Statistics Faculty Publications
To help undergraduates make connections among disciplines so they are able to approach, evaluate, and contribute to the solutions of important global problems, our campus has been focused on interdisciplinary research and education opportunities across the science, technology, engineering, and mathematics (STEM) disciplines. This paper describes the mobilization, planning, and implementation of a first-year interdisciplinary course for STEM majors that integrates key concepts found in traditional first-semester biology, chemistry, computer science, mathematics, and physics courses. This team-taught course, Integrated Quantitative Science (IQS), is half of a first-year student’s schedule in both semesters and is composed of a double lecture and …
Impact Of Interdisciplinary Undergraduate Research In Mathematics And Biology On The Development Of A New Course Integrating Five Stem Disciplines, Lester Caudill, April L. Hill, Kathy Hoke, Ovidiu Z. Lipan
Impact Of Interdisciplinary Undergraduate Research In Mathematics And Biology On The Development Of A New Course Integrating Five Stem Disciplines, Lester Caudill, April L. Hill, Kathy Hoke, Ovidiu Z. Lipan
Department of Math & Statistics Faculty Publications
Funded by innovative programs at the National Science Foundation and the Howard Hughes Medical Institute, University of Richmond faculty in biology, chemistry, mathematics, physics, and computer science teamed up to offer first- and second-year students the opportunity to contribute to vibrant, interdisciplinary research projects. The result was not only good science but also good science that motivated and informed course development. Here, we describe four recent undergraduate research projects involving students and faculty in biology, physics, mathematics, and computer science and how each contributed in significant ways to the conception and implementation of our new Integrated Quantitative Science course, a …
Design And Implementation Of Interactive Tutorials For Data Structures, Lewis Barnett Iii
Design And Implementation Of Interactive Tutorials For Data Structures, Lewis Barnett Iii
Department of Math & Statistics Faculty Publications
The Tutorial Generation Toolkit (TGT) is a set of Java classes that supports authoring interactive tutorial applications. This paper describes extensions to the capabilities of the TGT to support styles of interaction identified as effective in recent research. Several new tutorials aimed at the data structures course built using the enhanced toolkit are also described.
Use Of Pen-Based Technology In Calculus Courses, John R. Hubbard
Use Of Pen-Based Technology In Calculus Courses, John R. Hubbard
Department of Math & Statistics Faculty Publications
The author and his students used Tablet computers in Calculus I and Calculus II classes, providing students with dynamic digital transcripts that they could replay at their convenience. He and his students agreed that these graphic replays provide an effective alternative to the static explanations found in textbooks and in traditional course notes. Two specific examples are given in this paper.
Codes, Correlations And Power Control In Ofdm, James A. Davis, Jonathan Jedwab, Kenneth G. Paterson
Codes, Correlations And Power Control In Ofdm, James A. Davis, Jonathan Jedwab, Kenneth G. Paterson
Department of Math & Statistics Faculty Publications
Practical communications engineering is continually producing problems of interest to the coding theory community. A recent example is the power-control problem in Orthogonal Frequency Division Multiplexing (OFDM). We report recent work which gives a mathematical framework for generating solutions to this notorious problem that are suited to low-cost wireless applications. The key result is a connection between Golay complementary sequences and Reed-Muller codes. The former are almost ideal for OFDM transmissions because they have a very low peak-to-mean envelope power ratio (PMEPR), while the latter have efficient encoding and decoding algorithms and good error correction capability. This result is then …
Peak-To-Mean Power Control And Error Correction For Ofdm Transmission Using Golay Sequences And Reed-Muller Codes, James A. Davis, J Jedwab
Peak-To-Mean Power Control And Error Correction For Ofdm Transmission Using Golay Sequences And Reed-Muller Codes, James A. Davis, J Jedwab
Department of Math & Statistics Faculty Publications
A coding scheme for OFDM transmission is proposed, exploiting a previously unrecognised connection between pairs of Golay complementary sequences and second-order Reed-Muller codes. The scheme solves the notorious problem of power control in OFDM systems by maintaining a peak-to-mean envelope power ratio of at most 3dB while allowing simple encoding and decoding at high code rates for binary, quaternary or higher-phase signalling together with good error correction.