A New American’s Perspective: Improving Public Engagement by Rededicating Our Society to Democratic Ideals

Paul Stewart's "Rebels All" workshop. On stage, L-R: Jeff Corfield, Mushroom, Peter Bate, Paul Lawler, SmokeyHoward, Dianne J.Date:1980-0

PRICE FORECASTING WITH TIME-SERIES METHODS AND NONSTATIONARY DATA: AN APPLICATION TO MONTHLY U.S. CATTLE PRICES

The forecasting performance of various multivariate as well as univariate ARIMA models is evaluated in the presence of nonstationarity. The results indicate the importance of identifying the characteristics of the time series by testing for types of nonstationarity. Procedures that permit model specifications consistent with the systemÂ’s dynamics provide the most accurate forecasts.Demand and Price Analysis, Livestock Production/Industries,

Interactive Data Exploration with Smart Drill-Down

We present {\em smart drill-down}, an operator for interactively exploring a relational table to discover and summarize "interesting" groups of tuples. Each group of tuples is described by a {\em rule}. For instance, the rule $(a, b, \star, 1000)$ tells us that there are a thousand tuples with value $a$ in the first column and $b$ in the second column (and any value in the third column). Smart drill-down presents an analyst with a list of rules that together describe interesting aspects of the table. The analyst can tailor the definition of interesting, and can interactively apply smart drill-down on an existing rule to explore that part of the table. We demonstrate that the underlying optimization problems are {\sc NP-Hard}, and describe an algorithm for finding the approximately optimal list of rules to display when the user uses a smart drill-down, and a dynamic sampling scheme for efficiently interacting with large tables. Finally, we perform experiments on real datasets on our experimental prototype to demonstrate the usefulness of smart drill-down and study the performance of our algorithms

An Improved Statistic for the Pooled Triangle Test against PRNU-Copy Attack

We propose a new statistic to improve the pooled version of the triangle test used to combat the fingerprint-copy counter-forensic attack against PRNU-based camera identification [1]. As opposed to the original version of the test, the new statistic exploits the one-tail nature of the test, weighting differently positive and negative deviations from the expected value of the correlation between the image under analysis and the candidate images, i.e., those image suspected to have been used during the attack. The experimental results confirm the superior performance of the new test, especially when the conditions of the test are challenging ones, that is when the number of images used for the fingerprint-copy attack is large and the size of the image under test is small.Comment: submitted to IEEE Signal Processing Letter