Like vs. Like: Strategy and Improvements in Supernova Cosmology Systematics

Control of systematic uncertainties in the use of Type Ia supernovae as standardized distance indicators can be achieved through contrasting subsets of observationally-characterized, like supernovae. Essentially, like supernovae at different redshifts reveal the cosmology, and differing supernovae at the same redshift reveal systematics, including evolution not already corrected for by the standardization. Here we examine the strategy for use of empirically defined subsets to minimize the cosmological parameter risk, the quadratic sum of the parameter uncertainty and systematic bias. We investigate the optimal recognition of subsets within the sample and discuss some issues of observational requirements on accurately measuring subset properties. Neglecting like vs. like comparison (i.e. creating only a single Hubble diagram) can cause cosmological constraints on dark energy to be biased by 1\sigma or degraded by a factor 1.6 for a total drift of 0.02 mag. Recognition of subsets at the 0.016 mag level (relative differences) erases bias and reduces the degradation to 2%.Comment: 11 pages, 6 figure

Containment experiments in vortex tubes with radial outflow and large superimposed axial flows

Containment tests of vortexes with radial outflow in basic vortex tube, and in axial-flow vortex tub

MintHint: Automated Synthesis of Repair Hints

Being able to automatically repair programs is an extremely challenging task. In this paper, we present MintHint, a novel technique for program repair that is a departure from most of today's approaches. Instead of trying to fully automate program repair, which is often an unachievable goal, MintHint performs statistical correlation analysis to identify expressions that are likely to occur in the repaired code and generates, using pattern-matching based synthesis, repair hints from these expressions. Intuitively, these hints suggest how to rectify a faulty statement and help developers find a complete, actual repair. MintHint can address a variety of common faults, including incorrect, spurious, and missing expressions. We present a user study that shows that developers' productivity can improve manyfold with the use of repair hints generated by MintHint -- compared to having only traditional fault localization information. We also apply MintHint to several faults of a widely used Unix utility program to further assess the effectiveness of the approach. Our results show that MintHint performs well even in situations where (1) the repair space searched does not contain the exact repair, and (2) the operational specification obtained from the test cases for repair is incomplete or even imprecise

A new method of measuring corrosion under water. Investigation of effect of velocity

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Bayesian segnet: Model uncertainty in deep convolutional encoder-decoder architectures for scene understanding

We present a deep learning framework for probabilistic pixel-wise semantic segmentation, which we term Bayesian SegNet. Semantic segmentation is an important tool for visual scene understanding and a meaningful measure of uncertainty is essential for decision making. Our contribution is a practical system which is able to predict pixel-wise class labels with a measure of model uncertainty. We achieve this by Monte Carlo sampling with dropout at test time to generate a posterior distribution of pixel class labels. In addition, we show that modelling uncertainty improves segmentation performance by 2-3% across a number of state of the art architectures such as SegNet, FCN and Dilation Network, with no additional parametrisation. We also observe a significant improvement in performance for smaller datasets where modelling uncertainty is more effective. We benchmark Bayesian SegNet on the indoor SUN Scene Understanding and outdoor CamVid driving scenes datasets.Toyota Corporatio

The K-band spectrum of the Cataclysmic Variable RXJ 0502.8+1624 (Tau 4)

We present the K-band spectrum of the cataclysmic variable RXJ 0502.8+1624 (Tau 4). The spectrum shows a broad, smooth hump, with no absorption lines from the secondary star visible. This result indicates that the infrared light of this system is dominated by cyclotron emission, and, in combination with the optical spectrum and X-ray properties, suggests that Tau 4 is a polar-type cataclysmic variable (CV). The system was chosen for study because the broadband JHK colours of Tau 4 are consistent with an L-type dwarf, suggesting that this system might harbour an elusive sub-stellar secondary star. The result presented here, along with the recent discovery of cyclotron emission in the cataclysmic variable EF Eri, suggests that care must be taken when using the broadband JHK colours of CVs when targeting searches for sub-stellar secondary starsComment: 4 pages, to appear as research note in A&