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Full-Text Articles in Physical Sciences and Mathematics
Interview Of Margaret Mccoey, M.S., Margaret M. Mccoey, Matthew Riffe
Interview Of Margaret Mccoey, M.S., Margaret M. Mccoey, Matthew Riffe
All Oral Histories
Margaret “Peggy” McCoey is the Director of Graduate Programs in Computer Information Science, Information Technology, and Economic Crime Forensics at La Salle University. Born in the Oxford Circle section of Philadelphia in 1957, Peggy grew up in St. Martin of Tours parish attending their grade school before going to Little Flower High School. After graduation in 1975, Peggy entered La Salle University an undergraduate where she received a bachelor’s degree in Computer Science. Peggy received a master’s degree from Villanova in 1984. Beginning in 1982, Peggy McCoey has taught at La Salle University in some capacity. Throughout the 1990’s, Peggy …
Modeling Heterogeneous User Churn And Local Resilience Of Unstructured P2p Networks, Zhongmei Yao, Derek Leonard, Dmitri Loguinov, Xiaoming Wang
Modeling Heterogeneous User Churn And Local Resilience Of Unstructured P2p Networks, Zhongmei Yao, Derek Leonard, Dmitri Loguinov, Xiaoming Wang
Zhongmei Yao
Previous analytical results on the resilience of unstructured P2P systems have not explicitly modeled heterogeneity of user churn (i.e., difference in online behavior) or the impact of in-degree on system resilience. To overcome these limitations, we introduce a generic model of heterogeneous user churn, derive the distribution of the various metrics observed in prior experimental studies (e.g., lifetime distribution of joining users, joint distribution of session time of alive peers, and residual lifetime of a randomly selected user), derive several closed-form results on the transient behavior of in-degree, and eventually obtain the joint in/out degree isolation probability as a simple …
A Predictive Modeling System: Early Identification Of Students At-Risk Enrolled In Online Learning Programs, Mary L. Fonti
A Predictive Modeling System: Early Identification Of Students At-Risk Enrolled In Online Learning Programs, Mary L. Fonti
CCE Theses and Dissertations
Predictive statistical modeling shows promise in accurately predicting academic performance for students enrolled in online programs. This approach has proven effective in accurately identifying students who are at-risk enabling instructors to provide instructional intervention. While the potential benefits of statistical modeling is significant, implementations have proven to be complex, costly, and difficult to maintain. To address these issues, the purpose of this study is to develop a fully integrated, automated predictive modeling system (PMS) that is flexible, easy to use, and portable to identify students who are potentially at-risk for not succeeding in a course they are currently enrolled in. …
Math In The Dark: Tools For Expressing Mathematical Content By Visually Impaired Students, Patricia M. Mcdermott-Wells
Math In The Dark: Tools For Expressing Mathematical Content By Visually Impaired Students, Patricia M. Mcdermott-Wells
CCE Theses and Dissertations
Blind and visually impaired students are under-represented in the science, technology, engineering, and mathematics disciplines of higher education and the workforce. This is due primarily to the difficulties they encounter in trying to succeed in mathematics courses. While there are sufficient tools available to create Braille content, including the special Nemeth Braille used in the U.S. for mathematics constructs, there are very few tools to allow a blind or visually impaired student to create his/her own mathematical content in a manner that sighted individuals can use. The software tools that are available are isolated, do not interface well with other …