Sabbatical leave report: Spring 2014 - Brin, Leon (2014)
Wrote the online, open source numerical analysis textbook "Tea Time Numerical Analysis" hosted at github.com. Report describes the process of writing, publishing the text. Includes information about review process and statement of success towards goals.
Keywords: dept.mat; faculty_collection; sabbatical_report

Sabbatical leave follow-up reports - Hong, Jooyoun (Production: Spring 2014 ; Mathematics., 2014)
The sabbatical leave was spent on research on Hibbert coefficients of ideals and integral closures of ideals, resulting in submission for publication, as co-author, of articles, Specialization and integral closure, to the Journal of the London Mathematical Society, and Hilbert polynomials of j-transforms, to the Mathematical Proceedings of the Cambridge Philosophical Society. Two research visits, to Purdue University and to Maiji University in Japan, facilitated work on these publications and laid foundation for new projects, already in progress, on normality of ideals and reduction numbers of ideals.
Keywords: dept.mat; faculty_collection; sabbatical_report

Truck versus human: Mathematics under pressure - Field, E.; Ivison, R.; Reyher, A.; Warner, S. (College Mathematics Journal, 2014)
If you are ever faced with an oncoming truck, this paper could save your life. We investigate the optimal path that you should take from the middle of the road to the curb in order to avoid being hit by an oncoming truck. Although your instincts may tell you to run directly toward the curb, it turns out that this path, although the shortest, is not generally the safest.
1 citations (Crossref) [2023-10-31]
Keywords: dept.mat

Parameters governing deviations from the beer-lambert-bouger law for direct transmission - Clark, Aaron S (14th Conference on Cloud Physics/14th Conference on Atmospheric Radiation/Anthony Slingo Symposium, 2014)
Citation Key Alias: lens.org/054-763-221-479-911
Keywords: dept.mat; ⛔ No DOI found

On the link between particle size and deviations from the Beer–Lambert–Bouguer law for direct transmission - Larsen, Michael L; Clark, Aaron S (Journal of Quantitative Spectroscopy & Radiative Transfer, 2014)
Ballistic photon models of radiative transfer in discrete absorbing random media have demonstrated deviations from the Beer-Lambert-Bouguer law of exponential attenuation. A number of theoretical constructs to quantify the deviation from the Beer-Lambert-Bouguer law have appeared in the literature, several of which rely principally on a statistical measure related to the statistics of the absorber spatial positions alone. Here, we utilize a simple computational model to explore the interplay between the geometric size of the absorbing obstacles and the statistics governing the placement of the absorbers in the volume. We find that a description of the volume that depends on particle size and the spatial statistics of absorbers is not sufficient to fully characterize deviations from the Beer-Lambert-Bouguer law. Implications for future further theoretical and computational explorations of the problem are explored. © 2013 Elsevier Ltd.
27 citations (Crossref) [2023-10-31] Citation Key Alias: lens.org/106-914-218-360-135 tex.type: [object Object]
Keywords: Beer; Beer-Lambert-Bouguer law; Light transmission; Non-exponential transmission laws; Optical depth; Particle size; Poisson process; Poisson ratio; Stochastic media; Transmission law; dept.mat; numerical model; optical depth; particle size; radiative transfer; stochasticity

A clustering-based grouping model for enhancing collaborative learning - Pang, Yulei; Xiao, Feiya; Wang, Huaying; Xue, Xiaozhen (International Conference on Machine Learning and Applications, 2014)
Group work is widely used in tertiary institutions due to the considerable advantages of collaborative learning. Previous studies indicated that the group diversity had positive influence on the group work achievement. Therefore, how to achieve diversity within a group effectively and automatically is an interesting question. In this paper we propose a novel clustering-based grouping model. The proposed technique first employs balanced K-means algorithm to divide the students into several size-balanced clusters, such that the students within the same cluster are more similar (in some sense) to each other than to those in other clusters, then adopts one-sample-each-cluster strategy to construct the groups. We evaluated the proposed technique based on two small-scale case studies. The result observed may indicate that the clustering-based grouping model is feasible and effective. © 2014 IEEE.
9 citations (Crossref) [2023-10-31] tex.type: Proceedings paper
Keywords: Artificial intelligence; Case-studies; Collaborative learning; Group diversity; Grouping model; K-means; Learning systems; Novel clustering; Tertiary institutions; balanced K-means; collaborative learning; dept.mat; group diversity; k-Means algorithm

Feature selections for effectively localizing faulty events in GUI applications - Xue, Xiaozhen; Pang, Yulei; Namin, Akbar Siami (International Conference on Machine Learning and Applications, 2014)
Due to the complex causality of failure and the special characteristics of test cases, the faults in GUI (Graphic User Interface) applications are difficult to localize. This paper adapts feature selection algorithms to localize GUI-related faults in a given program. Features are defined as the subsequences of events executed. By employing statistical feature ranking techniques, the events can be ranked by the suspiciousness of events being responsible to exhibit faulty behavior. The features defined in a given source code implementing (event handle) the underlying event are then ranked in suspiciousness order. The evaluation of the proposed technique based on some open source Java projects verified the effectiveness of this feature selection based fault localization technique for GUI applications. © 2014 IEEE.
10 citations (Crossref) [2023-10-31] tex.type: Proceedings paper
Keywords: Artificial intelligence; Fault localization; Feature extraction; Feature selection algorithm; GUI; GUI applications; Graphic user interface; Graphical user interfaces; Java programming language; Learning systems; Open source software; Open sources; Source codes; Statistical features; Test case; User interfaces; dept.mat; faults localization; feature selection