On Using Active Learning and Self-Training when Mining Performance Discussions on Stack Overflow

Abundant data is the key to successful machine learning. However, supervised learning requires annotated data that are often hard to obtain. In a classification task with limited resources, Active Learning (AL) promises to guide annotators to examples that bring the most value for a classifier. AL can be successfully combined with self-training, i.e., extending a training set with the unlabelled examples for which a classifier is the most certain. We report our experiences on using AL in a systematic manner to train an SVM classifier for Stack Overflow posts discussing performance of software components. We show that the training examples deemed as the most valuable to the classifier are also the most difficult for humans to annotate. Despite carefully evolved annotation criteria, we report low inter-rater agreement, but we also propose mitigation strategies. Finally, based on one annotator's work, we show that self-training can improve the classification accuracy. We conclude the paper by discussing implication for future text miners aspiring to use AL and self-training.Comment: Preprint of paper accepted for the Proc. of the 21st International Conference on Evaluation and Assessment in Software Engineering, 201

Compressible turbulent boundary layer interaction experiments

Four phases of research results are reported: (1) experiments on the compressible turbulent boundary layer flow in a streamwise corner; (2) the two dimensional (2D) interaction of incident shock waves with a compressible turbulent boundary layer; (3) three dimensional (3D) shock/boundary layer interactions; and (4) cooperative experiments at Princeton and numerical computations at NASA-Ames

The Perfect Lion: The Life and Death of Confederate Artillerist John Pelham

Fresh Biographical Sketch of Confederate Artillerist Four books have now been written on Confederate artillerist John Pelham who, at the time of his death on March 18,1863, following the battle of Kelly’s Ford, Virginia, was but a major—a twenty-four year old major. Thousands of Civil W...

Opportunities and challenges grow from Arabidopsis genome sequencing

A recent Cold Spring Harbor Laboratory meeting in December 1997 provided the first meeting on the Arabidopsisgenome featuring a unique combination of functional studies and sequencing efforts; it included a broad range of talks covering genome sequencing and analysis efforts, mapping and defining genes, and gene expression patterns and function. Significant points to come out of the meeting were that a number of international consortiums have completed substantial portions of sequence on all five chromosomes with 17 Mb of sequence currently available through various web pages and 8 Mb of annotated sequence available through GenBank. Although physical maps of three of the five chromosomes have not yet been completed, David Bouchez (INRA, Versailles, France) reported that >90% of the clones in the CIC (CNRS, INRA, CEPH) Arabidopsis YAC library have been anchored via hybridization to genetically mapped markers. This should greatly facilitate the construction of physical maps. Michael Mindrinos from the Ausubel laboratory (Massachusetts General Hospital, Boston, MA) reported the development of a new class of PCR-based marker, the SNAPs (single nucleotideamplified polymorphisms), which should greatly assist positional cloning efforts. Daphne Preuss (University of Chicago, IL) reported the use of tetrad analysis to place the centromeres on the genetic map (Fig. 1), taking advantage of the pollen mutant quartet1 (Preuss et al. 1994; Copenhaver et al. 1998). Interestingly, this analysis placed the centromeres very close to, but not necessarily within, the centromeric repeat blocks mapped recently by Round et al. (1997)

Substance Abuse via Legally Prescribed Drugs: The Case of Vicodin in the United States

Vicodin is the most commonly prescribed pain reliever in the United States. Research indicates that there are two million people who are currently abusing Vicodin, and the majority of those who abuse Vicodin were initially exposed to it via prescription. Our goal is to determine the most effective strategies for reducing the overall population of Vicodin abusers. More specifically, we focus on whether prevention methods aimed at educating doctors and patients on the potential for drug abuse or treatment methods implemented after a person abuses Vicodin will have a greater overall impact. We consider one linear and two non-linear compartmental models in which medical users of Vicodin can transition into the abuser compartment or leave the population by no longer taking the drug. Once Vicodin abusers, people can transition into a treatment compartment, with the possibility of leaving the population through successful completion of treatment or of relapsing and re-entering the abusive compartment. The linear model assumes no social interaction, while both non-linear models consider interaction. One considers interaction with abusers affecting the relapse rate, while the other assumes both this and an additional interaction between the number of abusers and the number of new prescriptions. Sensitivity analyses are conducted varying the rates of success of these intervention methods measured by the parameters to determine which strategy has the greatest impact on controlling the population of Vicodin abusers. From these models and analyses, we determine that manipulating parameters tied to prevention measures has a greater impact on reducing the population of abusers than manipulating parameters associated with treatment. We also note that increasing the rate at which abusers seek treatment affects the population of abusers more than the success rate of treatment itself

Non-exponential kinetic behavior of confined water

We present the results of molecular dynamics simulations of SPC/E water confined in a realistic model of a silica pore. The single-particle dynamics have been studied at ambient temperature for different hydration levels. The confinement near the hydrophilic surface makes the dynamic behaviour of the liquid strongly dependent on the hydration level. Upon decrease of the number of water molecules in the pore we observe the onset of a slow dynamics due to the ``cage effect''. The conventional picture of a stochastic single-particle diffusion process thus looses its validity

Draft genome sequence of Pseudomonas moraviensis R28-S

We report the draft genome sequence of Pseudomonas moraviensis R28-S, isolated from the municipal wastewater treatment plant of Moscow, ID. The strain carries a native mercury resistance plasmid, poorly maintains introduced IncP-1 antibiotic resistance plasmids, and has been useful for studying the evolution of plasmid host range and stability

Active Sampling-based Binary Verification of Dynamical Systems

Nonlinear, adaptive, or otherwise complex control techniques are increasingly relied upon to ensure the safety of systems operating in uncertain environments. However, the nonlinearity of the resulting closed-loop system complicates verification that the system does in fact satisfy those requirements at all possible operating conditions. While analytical proof-based techniques and finite abstractions can be used to provably verify the closed-loop system's response at different operating conditions, they often produce conservative approximations due to restrictive assumptions and are difficult to construct in many applications. In contrast, popular statistical verification techniques relax the restrictions and instead rely upon simulations to construct statistical or probabilistic guarantees. This work presents a data-driven statistical verification procedure that instead constructs statistical learning models from simulated training data to separate the set of possible perturbations into "safe" and "unsafe" subsets. Binary evaluations of closed-loop system requirement satisfaction at various realizations of the uncertainties are obtained through temporal logic robustness metrics, which are then used to construct predictive models of requirement satisfaction over the full set of possible uncertainties. As the accuracy of these predictive statistical models is inherently coupled to the quality of the training data, an active learning algorithm selects additional sample points in order to maximize the expected change in the data-driven model and thus, indirectly, minimize the prediction error. Various case studies demonstrate the closed-loop verification procedure and highlight improvements in prediction error over both existing analytical and statistical verification techniques.Comment: 23 page

A Probe of New Physics in Top Quark Pair Production at e−e+e^-e^+ Colliders

We describe how to probe new physics through examination of the form factors describing the Ztt couplings via the scattering process e^-e^+->t+tbar. We focus on experimental methods on how the top quark momentum can be determined and show how this can be applied to select polarized samples of $t\bar{t}$ pairs through the angular correlations in the final state leptons. We also study the dependence on the energy and luminosity of an \ee\ collider to probe a CP violating asymmetry at the $10^{-2}$ level.}Comment: 24 pages in TeXsis (figures available upon request) (revised July 1993

Multiple-scattering effects on incoherent neutron scattering in glasses and viscous liquids

Incoherent neutron scattering experiments are simulated for simple dynamic models: a glass (with a smooth distribution of harmonic vibrations) and a viscous liquid (described by schematic mode-coupling equations). In most situations multiple scattering has little influence upon spectral distributions, but it completely distorts the wavenumber-dependent amplitudes. This explains an anomaly observed in recent experiments