An intelligent assistant for exploratory data analysis

In this paper we present an account of the main features of SNOUT, an intelligent assistant for exploratory data analysis (EDA) of social science survey data that incorporates a range of data mining techniques. EDA has much in common with existing data mining techniques: its main objective is to help an investigator reach an understanding of the important relationships ina data set rather than simply develop predictive models for selectd variables. Brief descriptions of a number of novel techniques developed for use in SNOUT are presented. These include heuristic variable level inference and classification, automatic category formation, the use of similarity trees to identify groups of related variables, interactive decision tree construction and model selection using a genetic algorithm

A Hybrid N-body--Coagulation Code for Planet Formation

We describe a hybrid algorithm to calculate the formation of planets from an initial ensemble of planetesimals. The algorithm uses a coagulation code to treat the growth of planetesimals into oligarchs and explicit N-body calculations to follow the evolution of oligarchs into planets. To validate the N-body portion of the algorithm, we use a battery of tests in planetary dynamics. Several complete calculations of terrestrial planet formation with the hybrid code yield good agreement with previously published calculations. These results demonstrate that the hybrid code provides an accurate treatment of the evolution of planetesimals into planets.Comment: Astronomical Journal, accepted; 33 pages + 11 figure

Using an Ant Colony Optimization Algorithm for Monotonic Regression Rule Discovery

Many data mining algorithms do not make use of existing domain knowledge when constructing their models. This can lead to model rejection as users may not trust models that behave contrary to their expectations. Semantic constraints provide a way to encapsulate this knowledge which can then be used to guide the construction of models. One of the most studied semantic constraints in the literature is monotonicity, however current monotonically-aware algorithms have focused on ordinal classification problems. This paper proposes an extension to an ACO-based regression algorithm in order to extract a list of monotonic regression rules. We compared the proposed algorithm against a greedy regression rule induction algorithm that preserves monotonic constraints and the well-known M5’ Rules. Our experiments using eight publicly available data sets show that the proposed algorithm successfully creates monotonic rules while maintaining predictive accuracy

Service differentiated drop code unit for metro ring optical networks

The authors demonstrate using both simulation and experiment, a drop code unit for metro ring optical networks with service differentiation capability. This is achieved by means of a spectral amplitude coding technique whereby the code weight in a particular channel is varied to provide different signal quality levels. Transmission of three channels with different weights operating at 10 Gbps per channel was simulated over a 68 km unamplified and 185 km amplified links of dispersion compensated fibre. Services are perfectly dropped at bit error rates from 10−9 to 10−3, leaving the through service free from accumulated noise. The authors also present a 2.5 Gbps per channel proof-of-concept experiment over 40 km of single-mode fibre (SMF)

Dynamical Evolution of Elliptical Galaxies with Central Singularities

We study the effect of a massive central singularity on the structure of a triaxial galaxy using N-body simulations. Starting from a single initial model, we grow black holes with various final masses Mh and at various rates, ranging from impulsive to adiabatic. In all cases, the galaxy achieves a final shape that is nearly spherical at the center and close to axisymmetric throughout. However, the rate of change of the galaxy's shape depends strongly on the ratio Mh/Mg of black hole mass to galaxy mass. When Mh/Mg < 0.3%, the galaxy evolves in shape on a timescale that exceeds 100 orbital periods, or roughly a galaxy lifetime. When Mh/Mg > 2%, the galaxy becomes axisymmetric in little more than a crossing time. We propose that the rapid evolution toward axisymmetric shapes that occurs when Mh/Mg > 2% provides a negative feedback mechanism which limits the mass of central black holes by cutting off their supply of fuel.Comment: 27 Latex pages, 9 Postscript figures, uses aastex.sty. Accepted for Publication in The Astrophysical Journal, Nov. 26, 199

Far-Term Exploration of Advanced Single-Aisle Subsonic Transport Aircraft Concepts

Far-term single-aisle class aircraft concepts for potential entry-into-service of 2045 were investigated using an Interactive Reconfigurable Matrix of Alternatives (IRMA) approach. The configurations identified through this design space exploration were then distilled into three advanced aircraft concepts best characterizing the prominent features identified through the IRMA exploration. These three aircraft concepts were then configured and sized for a 150-passenger capacity and a 3,500 nautical mile design mission. Mission block fuel burn was estimated and compared to a far-term conventional configuration baseline concept and a 2005 l. These comparisons suggest considerable potential improvements in fuel efficiency from the investigated advanced concepts

Modular Unmanned Aerial System with Multi-Mode Propulsion

A modular Unmanned Aerial System (UAS) includes an Unmanned Aerial Vehicle (UAV) parent module and UAV child modules. A main wing extends from a respective fuselage of the modules. The UAS includes docking mechanisms coupled to wingtips of the main wings. The child modules dock with the wingtips of the parent or an adjacent child module. Docking forms a linked-flight configuration, with undocking and separation from the parent or adjacent child module achieving an independent-flight configuration. The modules have booms arranged transverse to the main wings and parallel to the longitudinal axis, as well as front and rear rotors/propellers. The front and rear propellers have axes of rotation that are normal to a plane of the longitudinal axis in a vertical takeoff and landing (VTOL) configuration, with the axis of rotation of the rear propellers parallel to the longitudinal axis in a forward-flight configuration

Collisional Dark Matter and the Origin of Massive Black Holes

If the cosmological dark matter is primarily in the form of an elementary particle which has cross section and mass for self-interaction having a ratio similar to that of ordinary nuclear matter, then seed black holes (formed in stellar collapse) will grow in a Hubble time, due to accretion of the dark matter, to a mass range 10^6 - 10^9 solar masses. Furthermore, the dependence of the final black hole mass on the galaxy velocity dispersion will be approximately as observed and the growth rate will show a time dependence consistent with observations. Other astrophysical consequences of collisional dark matter and tests of the idea are noted.Comment: 7 pages, no figures, LaTeX2e, Accepted for publication in Phys. Rev. Lett. Changed conten

Robust Machine Learning Applied to Astronomical Datasets I: Star-Galaxy Classification of the SDSS DR3 Using Decision Trees

We provide classifications for all 143 million non-repeat photometric objects in the Third Data Release of the Sloan Digital Sky Survey (SDSS) using decision trees trained on 477,068 objects with SDSS spectroscopic data. We demonstrate that these star/galaxy classifications are expected to be reliable for approximately 22 million objects with r < ~20. The general machine learning environment Data-to-Knowledge and supercomputing resources enabled extensive investigation of the decision tree parameter space. This work presents the first public release of objects classified in this way for an entire SDSS data release. The objects are classified as either galaxy, star or nsng (neither star nor galaxy), with an associated probability for each class. To demonstrate how to effectively make use of these classifications, we perform several important tests. First, we detail selection criteria within the probability space defined by the three classes to extract samples of stars and galaxies to a given completeness and efficiency. Second, we investigate the efficacy of the classifications and the effect of extrapolating from the spectroscopic regime by performing blind tests on objects in the SDSS, 2dF Galaxy Redshift and 2dF QSO Redshift (2QZ) surveys. Given the photometric limits of our spectroscopic training data, we effectively begin to extrapolate past our star-galaxy training set at r ~ 18. By comparing the number counts of our training sample with the classified sources, however, we find that our efficiencies appear to remain robust to r ~ 20. As a result, we expect our classifications to be accurate for 900,000 galaxies and 6.7 million stars, and remain robust via extrapolation for a total of 8.0 million galaxies and 13.9 million stars. [Abridged]Comment: 27 pages, 12 figures, to be published in ApJ, uses emulateapj.cl