Convenience Voting Legislation

The popularity of "convenience voting" measures -- vote-by-mail (VBM), liberal absentee voting and Early Vote -- has grown in recent years. A majority of states now permit voting by mail upon request, early voting, or both. This trend towards convenience voting has been propelled by its popularity among voters and a perception among policymakers and advocates that such measures decrease costs, increase turnout, and are generally more advantageous than casting a ballot in person on the second Tuesday in November.While legislation introduced in 2008 by state lawmakers indicates that this trends continues, few states saw passage of significant laws that alter the traditional way America votes. Furthermore, research suggests convenience voting may do little to expand the electorate, let alone increase voter turnout. In this memorandum, we provide information on the status of convenience voting legislation in states for 2008, the current parameters of convenience voting laws in the states, and note some of the limitations of convenience voting measures

Youth Voting Legislation

Although youth voter participation is on the rise, young people are still underrepresented in the electorate. In 2006, voters between the ages of 18 and 29 comprised about 20 percent of the eligible voting population, but only half actually voted. Among young minority citizens, voter registration and turnout is even lower, lagging behind White rates by ten and five percent, respectively.The stratification in the youth electorate is reinforced by current methods of voter mobilization efforts, which concentrate on college campuses where the student body is overwhelmingly White. This legislative session saw multiple approaches toward increasing youth participation in the electoral process, including voter registration and voter education measures and more ambitious efforts to extend voting rights to citizens younger than 18. The majority of these measures failed to pass, resulting in few improvements in the ways in which American youths interact in the election system.In this memorandum, we provide information on the status of youth voting state legislation in 2008, related current election law, and issues involved in youth voter mobilization and participation

Multi-label Ferns for Efficient Recognition of Musical Instruments in Recordings

In this paper we introduce multi-label ferns, and apply this technique for automatic classification of musical instruments in audio recordings. We compare the performance of our proposed method to a set of binary random ferns, using jazz recordings as input data. Our main result is obtaining much faster classification and higher F-score. We also achieve substantial reduction of the model size

Boosted Random ferns for object detection

© 20xx IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.In this paper we introduce the Boosted Random Ferns (BRFs) to rapidly build discriminative classifiers for learning and detecting object categories. At the core of our approach we use standard random ferns, but we introduce four main innovations that let us bring ferns from an instance to a category level, and still retain efficiency. First, we define binary features on the histogram of oriented gradients-domain (as opposed to intensity-), allowing for a better representation of intra-class variability. Second, both the positions where ferns are evaluated within the sliding window, and the location of the binary features for each fern are not chosen completely at random, but instead we use a boosting strategy to pick the most discriminative combination of them. This is further enhanced by our third contribution, that is to adapt the boosting strategy to enable sharing of binary features among different ferns, yielding high recognition rates at a low computational cost. And finally, we show that training can be performed online, for sequentially arriving images. Overall, the resulting classifier can be very efficiently trained, densely evaluated for all image locations in about 0.1 seconds, and provides detection rates similar to competing approaches that require expensive and significantly slower processing times. We demonstrate the effectiveness of our approach by thorough experimentation in publicly available datasets in which we compare against state-of-the-art, and for tasks of both 2D detection and 3D multi-view estimation.Peer ReviewedPostprint (author's final draft

Registration and Voting Among Americans Ages 18-29

Young Americans ages 18-29 appear to be registering and voting at significantly higher rates than in recent elections. If further research bears this it out, it will be a welcome development given that young Americans are underrepresented in the electorate compared to their voting eligible population. This research memorandum provides registration and voting information on voting-eligible Americans ages 18-24 and 25-29 by age and college experience.The data raises one cautionary note: to the extent programs to engage young Americans in the democratic process focus primarily on college campuses, they will not only miss half of voting-eligible Americans ages 18-24 but also overlook a majority of Blacks and Latinos in this age group

Circular 102

In 1989, a systematic evaluation of woody and herbaceous perennial landscape plants was begun at the University of Alaska Fairbanks Georgeson Botanical Garden (64°51’N, 147°52’W). These evaluations were expanded to include annual flowers in 1992 and ferns in 1993. The purpose of this research is to identify hardy perennials capable of surviving in subarctic environments; to evaluate the ornamental potential of perennials and annuals; and to fulfill a growing demand for information on landscape plant materials by homeowners, commercial growers, and landscapers.Introduction -- Explanation of Plant Evaluation Tables -- Table 1. Weather records for the test years -- Table 2. All plant materials evaluated in 1994: Herbaceous perennials; Ferns; Ornamental grasses; Woody perennials -- Table 4. Plantings from 1994 that have not yet been evaluated for winter survival: Herbaceous perennials; Ferns; Woody perennials -- Table 5. Annual flowers evaluated in 1994 -- Appendix 1. Commercial Sources and Organizations -- Map of GB

Evolutionary conservation of ABA signaling for stomatal closure in ferns

ABA-driven stomatal regulation reportedly evolved after the divergence of ferns, during the early evolution of seed plants approximately 360 Mya. This hypothesis is based on the observation that the stomata of certain fern species are unresponsive to ABA, but exhibit passive hydraulic control. However, ABA-induced stomatal closure was detected in some mosses and lycophytes. Here, we observed that a number of ABA signaling and membrane transporter protein families diversified over the evolutionary history of land plants. The aquatic ferns Azolla filiculoides and Salvinia cucullata have representatives of 23 families of proteins orthologous to those of Arabidopsis thaliana and all other land plant species studied. Phylogenetic analysis of the key ABA signaling proteins indicates an evolutionarily conserved stomatal response to ABA. Moreover, comparative transcriptomic analysis has identified a suite of ABA responsive genes that differentially expressed in a terrestrial fern species, Polystichum proliferum. These genes encode proteins associated with ABA biosynthesis, transport, reception, transcription, signaling, and ion and sugar transport, which fit the general ABA signaling pathway constructed from Arabidopsis thaliana and Hordeum vulgare. The retention of these key ABA-responsive genes could have had a profound effect on the adaptation of ferns to dry conditions. Furthermore, stomatal assays have shown the primary evidence for ABA-induced closure of stomata in two terrestrial fern species P. proliferum and Nephrolepis exaltata. In summary, we report new molecular and physiological evidence for the presence of active stomatal control in ferns

rFerns: An Implementation of the Random Ferns Method for General-Purpose Machine Learning

In this paper I present an extended implementation of the Random ferns algorithm contained in the R package rFerns. It differs from the original by the ability of consuming categorical and numerical attributes instead of only binary ones. Also, instead of using simple attribute subspace ensemble it employs bagging and thus produce error approximation and variable importance measure modelled after Random forest algorithm. I also present benchmarks' results which show that although Random ferns' accuracy is mostly smaller than achieved by Random forest, its speed and good quality of importance measure it provides make rFerns a reasonable choice for a specific applications