Monotone Pieces Analysis for Qualitative Modeling

It is a crucial task to build qualitative models of industrial applications for model-based diagnosis. A Model Abstraction procedure is designed to automatically transform a quantitative model into qualitative model. If the data is monotone, the behavior can be easily abstracted using the corners of the bounding rectangle. Hence, many existing model abstraction approaches rely on monotonicity. But it is not a trivial problem to robustly detect monotone pieces from scattered data obtained by numerical simulation or experiments. This paper introduces an approach based on scale-dependent monotonicity: the notion that monotonicity can be defined relative to a scale. Real-valued functions defined on a finite set of reals e.g. simulation results, can be partitioned into quasi-monotone segments. The end points for the monotone segments are used as the initial set of landmarks for qualitative model abstraction. The qualitative model abstraction works as an iteratively refining process starting from the initial landmarks. The monotonicity analysis presented here can be used in constructing many other kinds of qualitative models; it is robust and computationally efficient

Quasi-monotonic segmentation of state variable behavior for reactive control

Real-world agents must react to changing conditions as they execute planned tasks. Conditions are typically monitored through time series representing state variables. While some predicates on these times series only consider one measure at a time, other predicates, sometimes called episodic predicates, consider sets of measures. We consider a special class of episodic predicates based on segmentation of the the measures into quasi-monotonic intervals where each interval is either quasi-increasing, quasi-decreasing, or quasi-flat. While being scale-based, this approach is also computational efficient and results can be computed exactly without need for approximation algorithms. Our approach is compared to linear spline and regression analysis

Scale-Based Monotonicity Analysis in Qualitative Modelling with Flat Segments

Qualitative models are often more suitable than classical quantitative models in tasks such as Model-based Diagnosis (MBD), explaining system behavior, and designing novel devices from first principles. Monotonicity is an important feature to leverage when constructing qualitative models. Detecting monotonic pieces robustly and efficiently from sensor or simulation data remains an open problem. This paper presents scale-based monotonicity: the notion that monotonicity can be defined relative to a scale. Real-valued functions defined on a finite set of reals e.g. sensor data or simulation results, can be partitioned into quasi-monotonic segments, i.e. segments monotonic with respect to a scale, in linear time. A novel segmentation algorithm is introduced along with a scale-based definition of "flatness"

Results of the 1986 NASA/FAA/DFVLR main rotor test entry in the German-Dutch wind tunnel (DNW)

An acoustics test of a 40%-scale MBB BO-105 helicopter main rotor was conducted in the Deutsch-Niederlandischer Windkanal (DNW). The research, directed by NASA Langley Research Center, concentrated on the generation and radiation of broadband noise and impulsive blade-vortex interaction (BVI) noise over ranges of pertinent rotor operational envelopes. Both the broadband and BVI experimental phases are reviewed, along with highlights of major technical results. For the broadband portion, significant advancement is the demonstration of the accuracy of prediction methods being developed for broadband self noise, due to boundary layer turbulence. Another key result is the discovery of rotor blade-wake interaction (BWI) as an important contributor to mid frequency noise. Also the DNW data are used to determine for full scale helicopters the relative importance of the different discrete and broadband noise sources. For the BVI test portion, a comprehensive data base documents the BVI impulsive noise character and directionality as functions of rotor flight conditions. The directional mapping of BVI noise emitted from the advancing side as well as the retreating side of the rotor constitutes a major advancement in the understanding of this dominant discrete mechanism

An inequality of Kostka numbers and Galois groups of Schubert problems

We show that the Galois group of any Schubert problem involving lines in projective space contains the alternating group. Using a criterion of Vakil and a special position argument due to Schubert, this follows from a particular inequality among Kostka numbers of two-rowed tableaux. In most cases, an easy combinatorial injection proves the inequality. For the remaining cases, we use that these Kostka numbers appear in tensor product decompositions of sl_2(C)-modules. Interpreting the tensor product as the action of certain commuting Toeplitz matrices and using a spectral analysis and Fourier series rewrites the inequality as the positivity of an integral. We establish the inequality by estimating this integral.Comment: Extended abstract for FPSAC 201

Beatniks and Politics, Nothing is New: Analyzing the Factors Surrounding Cal Poly’s Anti-War Movement during the Vietnam War

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ATTENTION AND SCHOOL SUCCESS: The Long-Term Implications of Attention for School Success among Low-Income Children

This study examined the longitudinal associations between sustained attention in preschool and children’s school success in later elementary school within a low-income sample (N = 2,403). Specifically, two facets of sustained attention (focused attention and lack of impulsivity) at age 5 were explored as independent predictors of children’s academic and behavioral competence across eight measures at age 9. Overall, the pattern of results indicates specificity between the facets of attention and school success, such that focused attention was primarily predictive of academic outcomes while impulsivity was mainly predictive of behavioral outcomes. Both facets of attention predicted teacher ratings of children’s academic skills and approaches to learning, which suggests that they jointly influence outcomes that span both domains of school success. Patterns of association were similar for children above and below the poverty line. Implications of these findings for interventions targeting school readiness and success among at-risk children are discussed.sustained attention, academic achievement, behavioral competence, low-income children