2,840 research outputs found
A tool for subjective and interactive visual data exploration
We present SIDE, a tool for Subjective and Interactive Visual Data Exploration, which lets users explore high dimensional data via subjectively informative 2D data visualizations. Many existing visual analytics tools are either restricted to specific problems and domains or they aim to find visualizations that align with user’s belief about the data. In contrast, our generic tool computes data visualizations that are surprising given a user’s current understanding of the data. The user’s belief state is represented as a set of projection tiles. Hence, this user-awareness offers users an efficient way to interactively explore yet-unknown features of complex high dimensional datasets
E-cigarette use among women of reproductive age: Impulsivity, cigarette smoking status, and other risk factors.
INTRODUCTION: The study aim was to examine impulsivity and other risk factors for e-cigarette use among women of reproductive age comparing current daily cigarette smokers to never cigarette smokers. Women of reproductive age are of special interest because of the additional risk that tobacco and nicotine use represents should they become pregnant.
METHOD: Survey data were collected anonymously online using Amazon Mechanical Turk in 2014. Participants were 800 women ages 24-44years from the US. Half (n=400) reported current, daily smoking and half (n=400) reported smokingsociodemographics, tobacco/nicotine use, and impulsivity (i.e., delay discounting & Barratt Impulsiveness Scale). Predictors of smoking and e-cigarette use were examined using logistic regression.
RESULTS: Daily cigarette smoking was associated with greater impulsivity, lower education, past illegal drug use, and White race/ethnicity. E-cigarette use in the overall sample was associated with being a cigarette smoker and greater education. E-cigarette use among current smokers was associated with increased nicotine dependence and quitting smoking; among never smokers it was associated with greater impulsivity and illegal drug use. E-cigarette use was associated with hookah use, and for never smokers only with use of cigars and other nicotine products.
CONCLUSIONS: E-cigarette use among women of reproductive age varies by smoking status, with use among current smokers reflecting attempts to quit smoking whereas among non-smokers use may be a marker of a more impulsive repertoire that includes greater use of alternative tobacco products and illegal drugs
Simulation-assisted control in building energy management systems
Technological advances in real-time data collection, data transfer and ever-increasing computational power are bringing simulation-assisted control and on-line fault detection and diagnosis (FDD) closer to reality than was imagined when building energy management systems (BEMSs) were introduced in the 1970s. This paper describes the development and testing of a prototype simulation-assisted controller, in which a detailed simulation program is embedded in real-time control decision making. Results from an experiment in a full-scale environmental test facility demonstrate the feasibility of predictive control using a physically-based thermal simulation program
Measuring classifier performance: a coherent alternative to the area under the ROC curve
Investigation of the Gravitational Potential Dependence of the Fine-Structure Constant Using Atomic Dysprosium
Radio-frequency E1 transitions between nearly degenerate, opposite parity
levels of atomic dysprosium were monitored over an eight month period to search
for a variation in the fine-structure constant. During this time period, data
were taken at different points in the gravitational potential of the Sun. The
data are fitted to the variation in the gravitational potential yielding a
value of for the fit parameter . This
value gives the current best laboratory limit. In addition, our value of
combined with other experimental constraints is used to extract
the first limits on k_e and k_q. These coefficients characterize the variation
of m_e/m_p and m_q/m_p in a changing gravitational potential, where m_e, m_p,
and m_q are electron, proton, and quark masses. The results are and .Comment: 6 pages, 3 figure
Unicor: A Species Connectivity And Corridor Network Simulator
Maintenance of species and landscape connectivity has emerged as an urgent need in the field of conservation biology. Current gaps include quantitative and spatially-explicit predictions of current and potential future patterns of fragmentation under a range of climate change scenarios. To address this need, we introduce UNIversal CORridor network simulator (UNICOR), a species connectivity and corridor identification tool. UNICOR applies Dijkstra’s shortest path algorithm to individual-based simulations and outputs can be used to designate movement corridors, identify isolated populations, and characterize zones for species persistence. The program's key features include a driver-module framework, connectivity maps with thresholding and buffering, and graph theory metrics. Through parallel-processing computational efficiency is greatly improved, allowing for larger ranges (grid dimensions of thousands) and larger populations (individuals in the thousands), whereas previous approaches are limited by prolonged computational times and poor algorithmic efficiency; restricting problem-size (range and populations), and requiring artificially subsampling of target populations
On the combination of omics data for prediction of binary outcomes
Enrichment of predictive models with new biomolecular markers is an important
task in high-dimensional omic applications. Increasingly, clinical studies
include several sets of such omics markers available for each patient,
measuring different levels of biological variation. As a result, one of the
main challenges in predictive research is the integration of different sources
of omic biomarkers for the prediction of health traits. We review several
approaches for the combination of omic markers in the context of binary outcome
prediction, all based on double cross-validation and regularized regression
models. We evaluate their performance in terms of calibration and
discrimination and we compare their performance with respect to single-omic
source predictions. We illustrate the methods through the analysis of two real
datasets. On the one hand, we consider the combination of two fractions of
proteomic mass spectrometry for the calibration of a diagnostic rule for the
detection of early-stage breast cancer. On the other hand, we consider
transcriptomics and metabolomics as predictors of obesity using data from the
Dietary, Lifestyle, and Genetic determinants of Obesity and Metabolic syndrome
(DILGOM) study, a population-based cohort, from Finland
Turning down the lamp: Software specialisation for the cloud
© USENIX Workshop on Hot Topics in Cloud Computing, HotCloud 2010.All right reserved. The wide availability of cloud computing offers an unprecedented opportunity to rethink how we construct applications. The cloud is currently mostly used to package up existing software stacks and operating systems (e.g. LAMP) for scaling out websites. We instead view the cloud as a stable hardware platform, and present a programming framework which permits applications to be constructed to run directly on top of it without intervening software layers. Our prototype (dubbed Mirage) is unashamedly academic; it extends the Objective Caml language with storage extensions and a custom run-time to emit binaries that execute as a guest operating system under Xen. Mirage applications exhibit significant performance speedups for I/O and memory handling versus the same code running under Linux/Xen. Our results can be generalised to offer insight into improving more commonly used languages such as PHP, Python and Ruby, and we discuss lessons learnt and future directions
Working group written presentation: Trapped radiation effects
The results of the Trapped Radiation Effects Panel for the Space Environmental Effects on Materials Workshop are presented. The needs of the space community for new data regarding effects of the space environment on materials, including electronics are listed. A series of questions asked of each of the panels at the workshop are addressed. Areas of research which should be pursued to satisfy the requirements for better knowledge of the environment and better understanding of the effects of the energetic charged particle environment on new materials and advanced electronics technology are suggested
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