Solutions without singularities in gauge theory of gravitation

A de-Sitter gauge theory of the gravitational field is developed using a spherical symmetric Minkowski space-time as base manifold. The gravitational field is described by gauge potentials and the mathematical structure of the underlying space-time is not affected by physical events. The field equations are written and their solutions without singularities are obtained by imposing some constraints on the invariants of the model. An example of such a solution is given and its dependence on the cosmological constant is studied. A comparison with results obtained in General Relativity theory is also presented. Keywords: gauge theory, gravitation, singularity, computer algebraComment: 9 pages, no figure

How to Find More Supernovae with Less Work: Object Classification Techniques for Difference Imaging

We present the results of applying new object classification techniques to difference images in the context of the Nearby Supernova Factory supernova search. Most current supernova searches subtract reference images from new images, identify objects in these difference images, and apply simple threshold cuts on parameters such as statistical significance, shape, and motion to reject objects such as cosmic rays, asteroids, and subtraction artifacts. Although most static objects subtract cleanly, even a very low false positive detection rate can lead to hundreds of non-supernova candidates which must be vetted by human inspection before triggering additional followup. In comparison to simple threshold cuts, more sophisticated methods such as Boosted Decision Trees, Random Forests, and Support Vector Machines provide dramatically better object discrimination. At the Nearby Supernova Factory, we reduced the number of non-supernova candidates by a factor of 10 while increasing our supernova identification efficiency. Methods such as these will be crucial for maintaining a reasonable false positive rate in the automated transient alert pipelines of upcoming projects such as PanSTARRS and LSST.Comment: 25 pages; 6 figures; submitted to Ap

Self-Interaction and Gauge Invariance

A simple unified closed form derivation of the non-linearities of the Einstein, Yang-Mills and spinless (e.g., chiral) meson systems is given. For the first two, the non-linearities are required by locality and consistency; in all cases, they are determined by the conserved currents associated with the initial (linear) gauge invariance of the first kind. Use of first-order formalism leads uniformly to a simple cubic self-interaction.Comment: Missing last reference added. 9 pages, This article, the first paper in Gen. Rel. Grav. [1 (1970) 9], is now somewhat inaccessible; the present posting is the original version, with a few subsequent references included. Updates update

A Non-Sequential Representation of Sequential Data for Churn Prediction

We investigate the length of event sequence giving best predictions when using a continuous HMM approach to churn prediction from sequential data. Motivated by observations that predictions based on only the few most recent events seem to be the most accurate, a non-sequential dataset is constructed from customer event histories by averaging features of the last few events. A simple K-nearest neighbor algorithm on this dataset is found to give significantly improved performance. It is quite intuitive to think that most people will react only to events in the fairly recent past. Events related to telecommunications occurring months or years ago are unlikely to have a large impact on a customer’s future behaviour, and these results bear this out. Methods that deal with sequential data also tend to be much more complex than those dealing with simple nontemporal data, giving an added benefit to expressing the recent information in a non-sequential manner

Vapor Detection, Classification, and Quantification Performance Using Arrays of Conducting Polymer Composite Chemically Sensitive Resistors

We describe a method for generating a variety of chemically diverse, broadly responsive, low power vapor sensors. A key to our ability to fabricate chemically diverse sensing elements is the preparation of processable, air stable films of electrically conducting organic polymers. An array of such sensing elements produces a chemically reversible, diagnostic pattern of electrical resistance changes upon exposure to different odorants. Such conducting polymer elements are simply prepared and are readily modified chemically to respond to a broad range of analytes. In addition, these sensors yield a fairly rapid, low power, de electrical signal in response to the vapor of interest, and their signals are readily integrated with software or hardware-based neural networks for purposes of analyte identification. Principle component analysis has demonstrated that such sensors can identify and quantify different airborne organic solvents, and can yield information on the components of gas mixtures

Array-based carbon black-polymer composite vapor detectors for detection of DNT in environments containing complex analyte mixtures

Thin films of carbon black-organic polymer composites have been deposited across two metallic leads, with sorption of vapors producing swelling-induced resistance changes of the detector films. To identify and classify vapors, arrays of such vapor sensing elements have been constructed in which each element of the array contains a different polymer as the insulating phase and a common conductor, carbon black, as the conducting phase. The differing gas-solid partition coefficients for the various polymers of the detector array produce a pattern of differential resistance changes that is used to classify vapors and vapor mixtures. The performance of this detector array system towards 2,4-dinitrotoluene, the predominant signature in the vapor phase above land mines, in the presence high concentrations of water or of acetone has been evaluated