Showing papers by "Rensselaer Polytechnic Institute published in 2009"

The Seventh Data Release of the Sloan Digital Sky Survey

Abstract: This paper describes the Seventh Data Release of the Sloan Digital Sky Survey (SDSS), marking the completion of the original goals of the SDSS and the end of the phase known as SDSS-II. It includes 11,663 deg^2 of imaging data, with most of the ~2000 deg^2 increment over the previous data release lying in regions of low Galactic latitude. The catalog contains five-band photometry for 357 million distinct objects. The survey also includes repeat photometry on a 120° long, 2°.5 wide stripe along the celestial equator in the Southern Galactic Cap, with some regions covered by as many as 90 individual imaging runs. We include a co-addition of the best of these data, going roughly 2 mag fainter than the main survey over 250 deg^2. The survey has completed spectroscopy over 9380 deg^2; the spectroscopy is now complete over a large contiguous area of the Northern Galactic Cap, closing the gap that was present in previous data releases. There are over 1.6 million spectra in total, including 930,000 galaxies, 120,000 quasars, and 460,000 stars. The data release includes improved stellar photometry at low Galactic latitude. The astrometry has all been recalibrated with the second version of the USNO CCD Astrograph Catalog, reducing the rms statistical errors at the bright end to 45 milliarcseconds per coordinate. We further quantify a systematic error in bright galaxy photometry due to poor sky determination; this problem is less severe than previously reported for the majority of galaxies. Finally, we describe a series of improvements to the spectroscopic reductions, including better flat fielding and improved wavelength calibration at the blue end, better processing of objects with extremely strong narrow emission lines, and an improved determination of stellar metallicities.

JADE: Adaptive Differential Evolution With Optional External Archive

Abstract: A new differential evolution (DE) algorithm, JADE, is proposed to improve optimization performance by implementing a new mutation strategy ldquoDE/current-to-p bestrdquo with optional external archive and updating control parameters in an adaptive manner. The DE/current-to-pbest is a generalization of the classic ldquoDE/current-to-best,rdquo while the optional archive operation utilizes historical data to provide information of progress direction. Both operations diversify the population and improve the convergence performance. The parameter adaptation automatically updates the control parameters to appropriate values and avoids a user's prior knowledge of the relationship between the parameter settings and the characteristics of optimization problems. It is thus helpful to improve the robustness of the algorithm. Simulation results show that JADE is better than, or at least comparable to, other classic or adaptive DE algorithms, the canonical particle swarm optimization, and other evolutionary algorithms from the literature in terms of convergence performance for a set of 20 benchmark problems. JADE with an external archive shows promising results for relatively high dimensional problems. In addition, it clearly shows that there is no fixed control parameter setting suitable for various problems or even at different optimization stages of a single problem.

Enhanced mechanical properties of nanocomposites at low graphene content.

Abstract: In this study, the mechanical properties of epoxy nanocomposites with graphene platelets, single-walled carbon nanotubes, and multi-walled carbon nanotube additives were compared at a nanofiller weight fraction of 0.1 ± 0.002%. The mechanical properties measured were the Young’s modulus, ultimate tensile strength, fracture toughness, fracture energy, and the material’s resistance to fatigue crack propagation. The results indicate that graphene platelets significantly out-perform carbon nanotube additives. The Young’s modulus of the graphene nanocomposite was ∼31% greater than the pristine epoxy as compared to ∼3% increase for single-walled carbon nanotubes. The tensile strength of the baseline epoxy was enhanced by ∼40% with graphene platelets compared to ∼14% improvement for multi-walled carbon nanotubes. The mode I fracture toughness of the nanocomposite with graphene platelets showed ∼53% increase over the epoxy compared to ∼20% improvement for multi-walled carbon nanotubes. The fatigue resistance resu...

Histopathological Image Analysis: A Review

Abstract: Over the past decade, dramatic increases in computational power and improvement in image analysis algorithms have allowed the development of powerful computer-assisted analytical approaches to radiological data. With the recent advent of whole slide digital scanners, tissue histopathology slides can now be digitized and stored in digital image form. Consequently, digitized tissue histopathology has now become amenable to the application of computerized image analysis and machine learning techniques. Analogous to the role of computer-assisted diagnosis (CAD) algorithms in medical imaging to complement the opinion of a radiologist, CAD algorithms have begun to be developed for disease detection, diagnosis, and prognosis prediction to complement the opinion of the pathologist. In this paper, we review the recent state of the art CAD technology for digitized histopathology. This paper also briefly describes the development and application of novel image analysis technology for a few specific histopathology related problems being pursued in the United States and Europe.

SEGUE: A SPECTROSCOPIC SURVEY OF 240,000 STARS WITH g = 14-20

Abstract: The Sloan Extension for Galactic Understanding and Exploration (SEGUE) Survey obtained {approx}240,000 moderate-resolution (R {approx} 1800) spectra from 3900 {angstrom} to 9000 {angstrom} of fainter Milky Way stars (14.0 10 per resolution element, stellar atmospheric parameters are estimated, including metallicity, surface gravity, and effective temperature. SEGUE obtained 3500 deg{sup 2} of additional ugriz imaging (primarily at low Galactic latitudes) providing precise multicolor photometry ({sigma}(g, r, i) {approx} 2%), ({sigma}(u, z) {approx} 3%) and astrometry ({approx}0.1) for spectroscopic target selection. The stellar spectra, imaging data, and derived parameter catalogs for this survey are publicly available as part of Sloan Digital Sky Survey Data Release 7.

A benchmark study on the thermal conductivity of nanofluids

Abstract: This article reports on the International Nanofluid Property Benchmark Exercise, or INPBE, in which the thermal conductivity of identical samples of colloidally stable dispersions of nanoparticles or “nanofluids,” was measured by over 30 organizations worldwide, using a variety of experimental approaches, including the transient hot wire method, steady-state methods, and optical methods. The nanofluids tested in the exercise were comprised of aqueous and nonaqueous basefluids, metal and metal oxide particles, near-spherical and elongated particles, at low and high particle concentrations. The data analysis reveals that the data from most organizations lie within a relatively narrow band (±10% or less) about the sample average with only few outliers. The thermal conductivity of the nanofluids was found to increase with particle concentration and aspect ratio, as expected from classical theory. There are (small) systematic differences in the absolute values of the nanofluid thermal conductivity among the various experimental approaches; however, such differences tend to disappear when the data are normalized to the measured thermal conductivity of the basefluid. The effective medium theory developed for dispersed particles by Maxwell in 1881 and recently generalized by Nan et al. [J. Appl. Phys. 81, 6692 (1997)], was found to be in good agreement with the experimental data, suggesting that no anomalous enhancement of thermal conductivity was achieved in the nanofluids tested in this exercise.

Anisotropic self-assembly of spherical polymer-grafted nanoparticles

Abstract: It is easy to understand the self-assembly of particles with anisotropic shapes or interactions (for example, cobalt nanoparticles or proteins) into highly extended structures. However, there is no experimentally established strategy for creating a range of anisotropic structures from common spherical nanoparticles. We demonstrate that spherical nanoparticles uniformly grafted with macromolecules ('nanoparticle amphiphiles') robustly self-assemble into a variety of anisotropic superstructures when they are dispersed in the corresponding homopolymer matrix. Theory and simulations suggest that this self-assembly reflects a balance between the energy gain when particle cores approach and the entropy of distorting the grafted polymers. The effectively directional nature of the particle interactions is thus a many-body emergent property. Our experiments demonstrate that this approach to nanoparticle self-assembly enables considerable control for the creation of polymer nanocomposites with enhanced mechanical properties. Grafted nanoparticles are thus versatile building blocks for creating tunable and functional particle superstructures with significant practical applications.

Ionic liquid-mediated selective extraction of lignin from wood leading to enhanced enzymatic cellulose hydrolysis

Abstract: Lignocellulose represents a key sustainable source of biomass for transformation into biofuels and bio-based products. Unfortunately, lignocellulosic biomass is highly recalcitrant to biotransformation, both microbial and enzymatic, which limits its use and prevents economically viable conversion into value-added products. As a result, effective pretreatment strategies are necessary, which invariably involves high energy processing or results in the degradation of key components of lignocellulose. In this work, the ionic liquid, 1-ethyl-3-methylimidazolium acetate ([Emim][CH3COO]), was used as a pretreatment solvent to extract lignin from wood flour. The cellulose in the pretreated wood flour becomes far less crystalline without undergoing solubilization. When 40% of the lignin was removed, the cellulose crystallinity index dropped below 45, resulting in > 90% of the cellulose in wood flour to be hydrolyzed by Trichoderma viride cellulase. [Emim] [CH3COO] was easily reused, thereby resulting in a highly concentrated solution of chemically unmodified lignin, which may serve as a valuable source of a polyaromatic material as a value-added product.

CUR matrix decompositions for improved data analysis

Abstract: Principal components analysis and, more generally, the Singular Value Decomposition are fundamental data analysis tools that express a data matrix in terms of a sequence of orthogonal or uncorrelated vectors of decreasing importance. Unfortunately, being linear combinations of up to all the data points, these vectors are notoriously difficult to interpret in terms of the data and processes generating the data. In this article, we develop CUR matrix decompositions for improved data analysis. CUR decompositions are low-rank matrix decompositions that are explicitly expressed in terms of a small number of actual columns and/or actual rows of the data matrix. Because they are constructed from actual data elements, CUR decompositions are interpretable by practitioners of the field from which the data are drawn (to the extent that the original data are). We present an algorithm that preferentially chooses columns and rows that exhibit high “statistical leverage” and, thus, in a very precise statistical sense, exert a disproportionately large “influence” on the best low-rank fit of the data matrix. By selecting columns and rows in this manner, we obtain improved relative-error and constant-factor approximation guarantees in worst-case analysis, as opposed to the much coarser additive-error guarantees of prior work. In addition, since the construction involves computing quantities with a natural and widely studied statistical interpretation, we can leverage ideas from diagnostic regression analysis to employ these matrix decompositions for exploratory data analysis.

Entrepreneurs' Optimism And New Venture Performance: A Social Cognitive Perspective

Abstract: Previous research indicates that entrepreneurs are generally high in dispositional optimism—the tendency to expect positive outcomes even when such expectations are not rationally justified. Findings of the current study demonstrate a negative relationship between entrepreneurs' optimism and the performance (revenue and employment growth) of their new ventures. Past experience creating ventures and industry dynamism moderated these effects, strengthening the negative relationship between entrepreneurs' optimism and venture performance. These findings illustrate the benefits of applying a social cognitive perspective toward efforts to understand key aspects of the new venture creation and development process.

Bank ownership and efficiency in China: What will happen in the world’s largest nation? ☆

Abstract: China is reforming its banking system, partially privatizing and taking on minority foreign ownership of three of its dominant “Big Four” state-owned banks. This paper helps predict the effects by analyzing the efficiency of Chinese banks over 1994–2003. Findings suggest that Big Four banks are by far the least efficient; foreign banks are most efficient; and minority foreign ownership is associated with significantly improved efficiency. We present corroborating robustness checks and offer several credible mechanisms through which minority foreign owners may increase Chinese bank efficiency. These findings suggest that minority foreign ownership of the Big Four will likely improve performance significantly.

Small-Signal Methods for AC Distributed Power Systems–A Review

Abstract: AC distributed power systems (DPS) can be found in several new and emerging applications. Similar to dc distributed power systems, an ac DPS relies on power electronics and control to realize its functions and achieve the required performance. System stability and power quality are important issues in both types of systems due to the complex system behavior resulted from active control at both the source and the load side. Traditional small-signal analysis methods cannot be directly applied to an ac DPS because of the periodically time-varying system operation trajectory. Possible solutions to this problem include transformation into a rotating (dq) reference frame, modeling using dynamic phasors, reduced-order modeling, and harmonic linearization. This paper reviews these small-signal methods and discusses their utilities as well as limitations. Compatibility of each type of models with state-space and impedance-based system analysis approaches will also be discussed. Problems related to the linearization of phasor-based models and their use in impedance-based system analysis are highlighted in particular.

Ocean overturning since the Late Cretaceous: Inferences from a new benthic foraminiferal isotope compilation

Abstract: [1] Benthic foraminiferal oxygen isotopic (d 18 O) and carbon isotopic (d 13 C) trends, constructed from compilations of data series from multiple ocean sites, provide one of the primary means of reconstructing changes in the ocean interior. These records are also widely used as a general climate indicator for comparison with local and more specific marine and terrestrial climate proxy records. We present new benthic foraminiferal d 18 O and d 13 C compilations for individual ocean basins that provide a robust estimate of benthic foraminiferal stable isotopic variations to � 80Ma andtentatively to � 110Ma. First-order variations ininterbasinal isotopicgradients delineate transitions from interior ocean heterogeneity during the Late Cretaceous (>� 65 Ma) to early Paleogene (35– 65 Ma) homogeneity and a return to heterogeneity in the late Paleogene–early Neogene (35–0 Ma). We propose that these transitions reflect alterations in a first-order characteristic of ocean circulation: the ability of winds to make water in the deep ocean circulate. We document the initiation of large interbasinal d 18 O gradients in the early Oligocene and link the variations in interbasinal d 18 O gradients from the middle Eocene to Oligocene with the increasing influence of wind-driven mixing due to the gradual tectonic opening of Southern Ocean passages and initiation and strengthening of the Antarctic Circumpolar Current. The role of wind-driven upwelling, possibly associated with a Tethyan Circumequatorial Current, in controlling Late Cretaceous interior ocean heterogeneity should be the subject of further research.

Information, affordances, and the control of action in sport.

Abstract: The theory of affordances, a conceptual pillar of the ecological approach to perception and action, has the potential to become a guiding principle for research on perception and action in sport. Affordances are opportunities for action. They describe the environment in terms of behaviors that are possible at a given moment under a given set of conditions. Affordances capture the tight coupling between perception and action, and allow for the prospective and moment-to-moment control of activity that is characteristic of fluent, fast-paced behavior on the playing field. We begin with an overview of the ecological approach and the principle of direct perception, using past research on interceptive action to illustrate how this principle has been put to work to capture information-movement relations in perceptualmotor skill. We then review theory and research on body-scaled, action-scaled, and social affordances, highlighting outstanding questions that provide opportunities for new research on affordances in the context of sport. We conclude with consideration of affordances as providing a functional semantics for sports.

How do feelings influence effort? An empirical study of entrepreneurs' affect and venture effort.

Abstract: How do feelings influence the effort of entrepreneurs? To obtain data on this issue, the authors implemented experience sampling methodology in which 46 entrepreneurs used cell phones to provide reports on their affect, future temporal focus, and venture effort twice daily for 24 days. Drawing on the affect-as-information theory, the study found that entrepreneurs' negative affect directly predicts entrepreneurs' effort toward tasks that are required immediately. Results were consistent for within-day and next-day time lags. Extending the theory, the study found that positive affect predicts venture effort beyond what is immediately required and that this relationship is mediated by future temporal focus. The mediating effects were significant only for next-day outcomes. Implications of findings on the nature of the affect-effort relationship for different time lags are discussed.

Unsupervised Multiway Data Analysis: A Literature Survey

Abstract: Two-way arrays or matrices are often not enough to represent all the information in the data and standard two-way analysis techniques commonly applied on matrices may fail to find the underlying structures in multi-modal datasets. Multiway data analysis has recently become popular as an exploratory analysis tool in discovering the structures in higher-order datasets, where data have more than two modes. We provide a review of significant contributions in the literature on multiway models, algorithms as well as their applications in diverse disciplines including chemometrics, neuroscience, social network analysis, text mining and computer vision.

Nanostructured Silicon Anodes for Lithium Ion Rechargeable Batteries

Abstract: Rechargeable lithium ion batteries are integral to today's information-rich, mobile society. Currently they are one of the most popular types of battery used in portable electronics because of their high energy density and flexible design. Despite their increasing use at the present time, there is great continued commercial interest in developing new and improved electrode materials for lithium ion batteries that would lead to dramatically higher energy capacity and longer cycle life. Silicon is one of the most promising anode materials because it has the highest known theoretical charge capacity and is the second most abundant element on earth. However, silicon anodes have limited applications because of the huge volume change associated with the insertion and extraction of lithium. This causes cracking and pulverization of the anode, which leads to a loss of electrical contact and eventual fading of capacity. Nanostructured silicon anodes, as compared to the previously tested silicon film anodes, can help overcome the above issues. As arrays of silicon nanowires or nanorods, which help accommodate the volume changes, or as nanoscale compliant layers, which increase the stress resilience of silicon films, nanoengineered silicon anodes show potential to enable a new generation of lithium ion batteries with significantly higher reversible charge capacity and longer cycle life.

An improved approximation algorithm for the column subset selection problem

Abstract: We consider the problem of selecting the "best" subset of exactly k columns from an m x n matrix A. In particular, we present and analyze a novel two-stage algorithm that runs in O(min{mn2, m2n}) time and returns as output an m x k matrix C consisting of exactly k columns of A. In the first stage (the randomized stage), the algorithm randomly selects O(k log k) columns according to a judiciously-chosen probability distribution that depends on information in the top-k right singular subspace of A. In the second stage (the deterministic stage), the algorithm applies a deterministic column-selection procedure to select and return exactly k columns from the set of columns selected in the first stage. Let C be the m x k matrix containing those k columns, let PC denote the projection matrix onto the span of those columns, and let Ak denote the "best" rank-k approximation to the matrix A as computed with the singular value decomposition. Then, we prove that[EQUATION]with probability at least 0.7. This spectral norm bound improves upon the best previously-existing result (of Gu and Eisenstat [21]) for the spectral norm version of this Column Subset Selection Problem. We also prove that[EQUATION]with the same probability. This Frobenius norm bound is only a factor of √k log k worse than the best previously existing existential result and is roughly O(√k!) better than the best previous algorithmic result (both of Deshpande et al. [11]) for the Frobenius norm version of this Column Subset Selection Problem.

Graphene oxide as an ideal substrate for hydrogen storage.

Abstract: Organometallic nanomaterials hold the promise for molecular hydrogen (H(2)) storage by providing nearly ideal binding strength to H(2) for room-temperature applications Synthesizing such materials, however, faces severe setbacks due to the problem of metal clustering Inspired by a recent experimental breakthrough ( J Am Chem Soc 2008 , 130 , 6992 ), which demonstrates enhanced H(2) binding in Ti-grafted mesoporous silica, we propose combining the graphene oxide (GO) technique with Ti anchoring to overcome the current synthesis bottleneck for practical storage materials Similar to silica, GO contains ample hydroxyl groups, which are the active sites for anchoring Ti atoms GO can be routinely synthesized and is much lighter than silica Hence, higher gravimetric storage capacity can be readily achieved Our first-principles computations suggest that GO is primarily made of low-energy oxygen-containing structural motifs on the graphene sheet The Ti atoms bind strongly to the oxygen sites with binding energies as high as 450 kJ/mol This is comparable to that of silica and is indeed enough to prevent the Ti atoms from clustering Each Ti can bind multiple H(2) with the desired binding energies (14-41 kJ/mol-H(2)) The estimated theoretical gravimetric and volumetric densities are 49 wt % and 64 g/L, respectively

Ripple-Based Control of Switching Regulators—An Overview

Abstract: Switching regulators with ripple-based control (ie, ?ripple regulators?) are conceptually simple, have fast transient responses to both line and load perturbations, and some versions operate with a switching frequency that is proportional to the load current under the discontinuous conduction mode These characteristics make the ripple regulators well-suited, especially for power management applications in computers and portable electronic devices Ripple regulators also have some drawbacks, including (in some versions) a poorly defined switching frequency, noise-induced jitter, inadequate dc regulation, and a tendency for fast-scale instability This paper presents an overview of the various ripple-based control techniques, discusses their merits and limitations, and introduces techniques for reducing the noise sensitivity and the sensitivity to capacitor parameters, improving the frequency stability and the dc regulation, and avoiding fast-scale instability

3-D Hyperintegration and Packaging Technologies for Micro-Nano Systems

Abstract: Three-dimensional (3-D) hyperintegration is an emerging technology, which vertically stacks and interconnects multiple materials, technologies, and functional components to form highly integrated micro-nano systems. This 3-D hyperintegration is expected to lead to an industry paradigm shift due to its tremendous benefits. Worldwide academic and industrial research activities currently focus on technology innovations, simulation and design, and product prototypes. Anticipated applications start with memory, handheld devices, and high-performance computers and extend to high-density multifunctional heterogeneous integration of InfoTech-NanoTech-BioTech systems. This paper overviews the 3-D hyperintegration and packaging technologies, including motivations, key technology platforms, status, and perspectives towards commercialization. The challenges associated with the 3-D technologies are addressed, including integration architectures and design tools, yield and cost, thermal and mechanical constraints, and manufacturing infrastructure.

On the Use of the Adjusted Rand Index as a Metric for Evaluating Supervised Classification

Abstract: The Adjusted Rand Index (ARI) is frequently used in cluster validation since it is a measure of agreement between two partitions: one given by the clustering process and the other defined by external criteria. In this paper we investigate the usability of this clustering validation measure in supervised classification problems by two different approaches: as a performance measure and in feature selection. Since ARI measures the relation between pairs of dataset elements not using information from classes (labels) it can be used to detect problems with the classification algorithm specially when combined with conventional performance measures. Instead, if we use the class information, we can apply ARI also to perform feature selection. We present the results of several experiments where we have applied ARI both as a performance measure and for feature selection showing the validity of this index for the given tasks.

Characterizing hydrophobicity of interfaces by using cavity formation, solute binding, and water correlations

Abstract: Hydrophobicity is often characterized macroscopically by the droplet contact angle. Molecular signatures of hydrophobicity have, however, remained elusive. Successful theories predict a drying transition leading to a vapor-like region near large hard-sphere solutes and interfaces. Adding attractions wets the interface with local density increasing with attractions. Here we present extensive molecular simulation studies of hydration of realistic surfaces with a wide range of chemistries from hydrophobic (−CF3, −CH3) to hydrophilic (−OH, −CONH2). We show that the water density near weakly attractive hydrophobic surfaces (e.g., −CF3) can be bulk-like or larger, and provides a poor quantification of surface hydrophobicity. In contrast, the probability of cavity formation or the free energy of binding of hydrophobic solutes to interfaces correlates quantitatively with the macroscopic wetting properties and serves as an excellent signature of hydrophobicity. Specifically, the probability of cavity formation is enhanced in the vicinity of hydrophobic surfaces, and water–water correlations correspondingly display characteristics similar to those near a vapor–liquid interface. Hydrophilic surfaces suppress cavity formation and reduce the water–water correlation length. Our results suggest a potentially robust approach for characterizing hydrophobicity of more complex and heterogeneous surfaces of proteins and biomolecules, and other nanoscopic objects.

Institutional development, financial deepening and economic growth: Evidence from China

Abstract: Ilmestynyt myos New York University . Leonard N. Stern School of Business . Economics department working papers 7/2007

Coherent Polarization Control of Terahertz Waves Generated from Two-Color Laser-Induced Gas Plasma

Abstract: Electrons ionized from an atom or molecule by circularly or elliptically polarized femtosecond omega and 2omega pulses exhibit different trajectory orientations as the relative phase between the two pulses changes. Macroscopically, the polarization of the terahertz wave emitted during the ionization process was found to be coherently controllable through the optical phase. This new finding can be completely reproduced by numerical simulation and may enable fast terahertz wave modulation and coherent control of nonlinear responses excited by intense terahertz waves with controllable polarization.

Turning carbon nanotubes from exceptional heat conductors into insulators.

Abstract: Thermal conductivity ($\ensuremath{\kappa}$) of isolated carbon nanotubes (CNTs) is higher than the $\ensuremath{\kappa}$ of diamond; however, in this Letter we show that the $\ensuremath{\kappa}$ of a packed bed of three-dimensional random networks of single and multiwall CNTs is smaller than that of thermally insulating amorphous polymers. The thermoelectric power ($\ensuremath{\Sigma}$) of the random network of CNTs was also measured. The $\ensuremath{\Sigma}$ of a single wall nanotube network is very similar to that of isolated nanotubes and, in contrast with $\ensuremath{\kappa}$, $\ensuremath{\Sigma}$ shows a strong dependence on the tube diameter.