Detecting lamb waves with broadband acousto-ultrasonic signals in composite structures

Lamb waves can be produced and detected in ceramic matrix composites (CMC) and metal matrix composites (MMC) plates using the acousto-ultrasonic configuration employing broadband transducers. Experimental dispersion curves of lowest symmetric and lowest antisymmetric modes behave in a manner analogous to the graphite/polymer theoretical curves. In this study a basis has been established for analyzing Lamb wave velocities for characterizing composite plates. Lamb wave dispersion curves and group velocities were correlated with variations in axial stiffness and shear stiffness in MMC and CMC. For CMCs, interfacial shear strength was also correlated with the first antisymmetric Lamb mode.     

Effect of superconducting fluctuations on the nmr relaxation rate of high-T c superconductors

The effect of superconducting order parameter fluctuations on the nuclear-spin relaxation rate, 1/T ₁, is studied for clean two-dimensional systems by calculating the three Maki-Thomson-type diagrams which represent the lowest-order fluctuation contributions to the transverse susceptibility. For Gaussian fluctuations and for temperatures near the mean field transition temperature,T _c0, we employ a weak-coupling theory in which the pair-fluctuation propagator can also include pair-breaking effects. We also go beyond the Gaussian theory and take into account the interactions between Cooper-pair fluctuations corresponding to the fourth-order Ginzburg-Landau fluctuation terms. We compare our results with previous results in the dirty limit and in 3D. We obtain a pronounced peak in 1/T₁ atT _c and briefly discuss possible reasons why this peak is not observed.     

Efficient Reflectance and Visibility Approximations for Environment Map Rendering

We present a technique for approximating isotropic BRDFs and precomputed self-occlusion that enables accurate and efficient prefiltered environment map rendering. Our approach uses a nonlinear approximation of the BRDF as a weighted sum of isotropic Gaussian functions. Our representation requires a minimal amount of storage, can accurately represent BRDFs of arbitrary sharpness, and is above all, efficient to render. We precompute visibility due to self-occlusion and store a low-frequency approximation suitable for glossy reflections. We demonstrate our method by fitting our representation to measured BRDF data, yielding high visual quality at real-time frame rates.     

Synthesis and characterization of soluble (porphyrinato)iron(II) polymers

The use of (tetrakis(4-hexylphenyl)porphyrinato)Fe(II) in polymerization reactions with bidentate ligands such as 9,10-diisocyanoanthracene and 1,4-diisocyanobenzene led to well-defined stacked polymers1 and2 which are still soluble in common organic solvents such as chloroform, dichloromethane, and tetrahydrofurane. They have been completely characterized by¹H-NMR and UV/vis spectropscopy in solution, even allowing end-group analysis for determination of the average degree of polymerization, yieldingn=10 andn=5 for1 and2, respectively. Mößbauer and IR spectroscopy further established the strong Fe-CN bonding reflected by very small isomer shifts and quadrupole splittings (E _Q0.2 mm s^–1) and a large decrease in the IR stretching frequency (v _CN60 cm^–1). The axially stacked polymers exhibit semiconducting properties only upon doping.Presented at the 5th International Symposium on Macromolecule-Metal Complexes (MMV), Summer 1993 in Bremen, Germany.     

Characterization for High Dynamic Range Imaging

In this paper we present a new practical camera characterization technique to improve color accuracy in high dynamic range (HDR) imaging. Camera characterization refers to the process of mapping device‐dependent signals, such as digital camera RAW images, into a well‐defined color space. This is a well‐understood process for low dynamic range (LDR) imaging and is part of most digital cameras — usually mapping from the raw camera signal to the sRGB or Adobe RGB color space. This paper presents an efficient and accurate characterization method for high dynamic range imaging that extends previous methods originally designed for LDR imaging. We demonstrate that our characterization method is very accurate even in unknown illumination conditions, effectively turning a digital camera into a measurement device that measures physically accurate radiance values — both in terms of luminance and color — rivaling more expensive measurement instruments.     

Home location inference from sparse and noisy data: models and applications

Accurate home location is increasingly important for urban computing. Existing methods either rely on continuous (and expensive) Global Positioning System (GPS) data or suffer from poor accuracy. In particular, the sparse and noisy nature of social media data poses serious challenges in pinpointing where people live at scale. We revisit this research topic and infer home location within 100 m×100 m squares at 70% accuracy for 76% and 71% of active users in New York City and the Bay Area, respectively. To the best of our knowledge, this is the first time home location has been detected at such a fine granularity using sparse and noisy data. Since people spend a large portion of their time at home, our model enables novel applications. As an example, we focus on modeling people’s health at scale by linking their home locations with publicly available statistics, such as education disparity. Results in multiple geographic regions demonstrate both the effectiveness and added value of our home localization method and reveal insights that eluded earlier studies. In addition, we are able to discover the real buzz in the communities where people live.     

Constraints and AI planning

Tackling real-world planning problems often requires considering various types of constraints, which can range from simple numerical comparators to complex resources. This article provides an overview of techniques to deal with such constraints by expressing planning within general constraint-solving frameworks. Our goal here is to explore the interplay of constraints and planning, highlighting the differences between propositional satisfiability (SAT), integer programming (IP), and constraint programming (CP), and discuss their potential in expressing and solving AI planning problems.     

Color affects perceived odor intensity.

In Experiment 1, some odorous solutions (e.g., strawberry) were rated as smelling stronger when colored (e.g., red) than when colorless. Experiment 2 showed this effect to be due to a perceptual change rather than a response to experimental demand characteristics. Experiment 3 showed that the color-induced increase in odor intensity is not due to subjects' preexperimental experience with particular color–odor combinations, because the increase occurred with novel ones. We conclude that color induces a weak olfactory percept that combines with odorant-induced percepts. The effect may be due to conditioning or may be the result of residual intersensory neural connections left over from infancy. (PsycINFO Database Record (c) 2010 APA, all rights reserved)