On the Feature Discovery for App Usage Prediction in Smartphones

With the increasing number of mobile Apps developed, they are now closely integrated into daily life. In this paper, we develop a framework to predict mobile Apps that are most likely to be used regarding the current device status of a smartphone. Such an Apps usage prediction framework is a crucial prerequisite for fast App launching, intelligent user experience, and power management of smartphones. By analyzing real App usage log data, we discover two kinds of features: The Explicit Feature (EF) from sensing readings of built-in sensors, and the Implicit Feature (IF) from App usage relations. The IF feature is derived by constructing the proposed App Usage Graph (abbreviated as AUG) that models App usage transitions. In light of AUG, we are able to discover usage relations among Apps. Since users may have different usage behaviors on their smartphones, we further propose one personalized feature selection algorithm. We explore minimum description length (MDL) from the training data and select those features which need less length to describe the training data. The personalized feature selection can successfully reduce the log size and the prediction time. Finally, we adopt the kNN classification model to predict Apps usage. Note that through the features selected by the proposed personalized feature selection algorithm, we only need to keep these features, which in turn reduces the prediction time and avoids the curse of dimensionality when using the kNN classifier. We conduct a comprehensive experimental study based on a real mobile App usage dataset. The results demonstrate the effectiveness of the proposed framework and show the predictive capability for App usage prediction.Comment: 10 pages, 17 figures, ICDM 2013 short pape

Shape restricted regression with random Bernstein polynomials

Shape restricted regressions, including isotonic regression and concave regression as special cases, are studied using priors on Bernstein polynomials and Markov chain Monte Carlo methods. These priors have large supports, select only smooth functions, can easily incorporate geometric information into the prior, and can be generated without computational difficulty. Algorithms generating priors and posteriors are proposed, and simulation studies are conducted to illustrate the performance of this approach. Comparisons with the density-regression method of Dette et al. (2006) are included.Comment: Published at http://dx.doi.org/10.1214/074921707000000157 in the IMS Lecture Notes Monograph Series (http://www.imstat.org/publications/lecnotes.htm) by the Institute of Mathematical Statistics (http://www.imstat.org

Profiling time course expression of virus genes---an illustration of Bayesian inference under shape restrictions

There have been several studies of the genome-wide temporal transcriptional program of viruses, based on microarray experiments, which are generally useful in the construction of gene regulation network. It seems that biological interpretations in these studies are directly based on the normalized data and some crude statistics, which provide rough estimates of limited features of the profile and may incur biases. This paper introduces a hierarchical Bayesian shape restricted regression method for making inference on the time course expression of virus genes. Estimates of many salient features of the expression profile like onset time, inflection point, maximum value, time to maximum value, area under curve, etc. can be obtained immediately by this method. Applying this method to a baculovirus microarray time course expression data set, we indicate that many biological questions can be formulated quantitatively and we are able to offer insights into the baculovirus biology.Comment: Published in at http://dx.doi.org/10.1214/09-AOAS258 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Tetra­kis(μ-2,4-difluoro­benzoato)bis­[(2,4-difluoro­benzoato)(1,10-phenanthroline)gadolinium(III)]

In the title compound, [Gd2(C7H3F2O2)6(C12H8N2)2], the asymmetric unit comprises one Gd3+ cation chelated by two 2,4-difluoro­benzoate and one 1,10-phenanthroline ligands. Two cations are linked into a centrosymmetric dimer via three bridging carboxyl­ate groups of 2,4-difluoro­benzoate ligands. Each Gd3+ ion is nine-coordinated by seven O atoms and two N atoms

Structural and Thermodynamic Factors of Suppressed Interdiffusion Kinetics in Multi-component High-entropy Materials

We report multi-component high-entropy materials as extraordinarily robust diffusion barriers and clarify the highly suppressed interdiffusion kinetics in the multi-component materials from structural and thermodynamic perspectives. The failures of six alloy barriers with different numbers of elements, from unitary Ti to senary TiTaCrZrAlRu, against the interdiffusion of Cu and Si were characterized, and experimental results indicated that, with more elements incorporated, the failure temperature of the barriers increased from 550 to 900°C. The activation energy of Cu diffusion through the alloy barriers was determined to increase from 110 to 163 kJ/mole. Mechanistic analyses suggest that, structurally, severe lattice distortion strains and a high packing density caused by different atom sizes, and, thermodynamically, a strengthened cohesion provide a total increase of 55 kJ/mole in the activation energy of substitutional Cu diffusion, and are believed to be the dominant factors of suppressed interdiffusion kinetics through the multi-component barrier materials

Tris[2-(propyl­imino­meth­yl)phenolato-κ2 N,O]cobalt(III)

The title compound, [Co(C10H12NO)3], was synthesized from cobalt(III) fluoride and 2-(propyl­imino­meth­yl)phenol in refluxing methanol. The CoIII ion is hexa­coordinated by three N and three O atoms from three bidentate Schiff base ligands in an octa­hedral geometry

Drastic population fluctuations explain the rapid extinction of the passenger pigeon

To assess the role of human disturbances in species' extinction requires an understanding of the species population history before human impact. The passenger pigeon was once the most abundant bird in the world, with a population size estimated at 3-5 billion in the 1800s; its abrupt extinction in 1914 raises the question of how such an abundant bird could have been driven to extinction in mere decades. Although human exploitation is often blamed, the role of natural population dynamics in the passenger pigeon's extinction remains unexplored. Applying high-throughput sequencing technologies to obtain sequences from most of the genome, we calculated that the passenger pigeon's effective population size throughout the last million years was persistently about 1/10,000 of the 1800's estimated number of individuals, a ratio 1,000-times lower than typically found. This result suggests that the passenger pigeon was not always super abundant but experienced dramatic population fluctuations, resembling those of an "outbreak" species. Ecological niche models supported inference of drastic changes in the extent of its breeding range over the last glacial-interglacial cycle. An estimate of acorn-based carrying capacity during the past 21,000 y showed great year-to-year variations. Based on our results, we hypothesize that ecological conditions that dramatically reduced population size under natural conditions could have interacted with human exploitation in causing the passenger pigeon's rapid demise. Our study illustrates that even species as abundant as the passenger pigeon can be vulnerable to human threats if they are subject to dramatic population fluctuations, and provides a new perspective on the greatest human-caused extinction in recorded history

SARS Exposure and Emergency Department Workers

Of 193 emergency department workers exposed to severe acute respiratory syndrome (SARS), 9 (4.7%) were infected. Pneumonia developed in six workers, and assays showed anti-SARS immunoglobulin (Ig) M and IgG. The other three workers were IgM-positive and had lower IgG titers; in two, mild illness developed, and one remained asymptomatic