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Full-Text Articles in Physical Sciences and Mathematics
Exploring The Impact Of Knowledge And Social Environment On Influenza Prevention And Transmission In Midwestern United States High School Students, William L. Romine, Tanvi Banerjee, William S. Barrow, William R. Folk
Exploring The Impact Of Knowledge And Social Environment On Influenza Prevention And Transmission In Midwestern United States High School Students, William L. Romine, Tanvi Banerjee, William S. Barrow, William R. Folk
Kno.e.sis Publications
We used data from a convenience sample of 410 Midwestern United States students from six secondary schools to develop parsimonious models for explaining and predicting precautions and illness related to influenza. Scores for knowledge and perceptions were obtained using two-parameter Item Response Theory (IRT) models. Relationships between outcome variables and predictors were verified using Pearson and Spearman correlations, and nested [student within school] fixed effects multinomial logistic regression models were specified from these using Akaike’s Information Criterion (AIC). Neural network models were then formulated as classifiers using 10-fold cross validation to predict precautions and illness. Perceived barriers against taking precautions …
Demographic Prediction Of Mobile User From Phone Usage, Shahram Mohrehkesh, Shuiwang Ji, Tamer Nadeem, Michele C. Weigle
Demographic Prediction Of Mobile User From Phone Usage, Shahram Mohrehkesh, Shuiwang Ji, Tamer Nadeem, Michele C. Weigle
Computer Science Faculty Publications
In this paper, we describe how we use the mobile phone usage of users to predict their demographic attributes. Using call log, visited GSM cells information, visited Bluetooth devices, visited Wireless LAN devices, accelerometer data, and so on, we predict the gender, age, marital status, job and number of people in household of users. The accuracy of developed classifiers for these classification problems ranges from 45-87% depending upon the particular classification problem.