Showing papers by "University of Central Florida published in 2008"

Intrinsic and extrinsic performance limits of graphene devices on SiO2.

Abstract: The linear dispersion relation in graphene gives rise to a surprising prediction: the resistivity due to isotropic scatterers, such as white-noise disorder or phonons, is independent of carrier density, n. Here we show that electron-acoustic phonon scattering is indeed independent of n, and contributes only 30 Omega to graphene's room-temperature resistivity. At a technologically relevant carrier density of 1 x1012 cm-2, we infer a mean free path for electron-acoustic phonon scattering of >2 microm and an intrinsic mobility limit of 2 x 105 cm2 V-1 s-1. If realized, this mobility would exceed that of InSb, the inorganic semiconductor with the highest known mobility ( approximately 7.7 x 104 cm2 V-1 s-1; ref. 9) and that of semiconducting carbon nanotubes ( approximately 1 x 105 cm2 V-1 s-1; ref. 10). A strongly temperature-dependent resistivity contribution is observed above approximately 200 K (ref. 8); its magnitude, temperature dependence and carrier-density dependence are consistent with extrinsic scattering by surface phonons at the SiO2 substrate and limit the room-temperature mobility to approximately 4 x 104 cm2 V-1 s-1, indicating the importance of substrate choice for graphene devices.

Beam dynamics in PT symmetric optical lattices.

Abstract: The possibility of parity-time (PT) symmetric periodic potentials is investigated within the context of optics. Beam dynamics in this new type of optical structures is examined in detail for both one- and two-dimensional lattice geometries. It is shown that PT periodic structures can exhibit unique characteristics stemming from the nonorthogonality of the associated Floquet-Bloch modes. Some of these features include double refraction, power oscillations, and eigenfunction unfolding as well as nonreciprocal diffraction patterns.

Action MACH a spatio-temporal Maximum Average Correlation Height filter for action recognition

Abstract: In this paper we introduce a template-based method for recognizing human actions called action MACH. Our approach is based on a maximum average correlation height (MACH) filter. A common limitation of template-based methods is their inability to generate a single template using a collection of examples. MACH is capable of capturing intra-class variability by synthesizing a single Action MACH filter for a given action class. We generalize the traditional MACH filter to video (3D spatiotemporal volume), and vector valued data. By analyzing the response of the filter in the frequency domain, we avoid the high computational cost commonly incurred in template-based approaches. Vector valued data is analyzed using the Clifford Fourier transform, a generalization of the Fourier transform intended for both scalar and vector-valued data. Finally, we perform an extensive set of experiments and compare our method with some of the most recent approaches in the field by using publicly available datasets, and two new annotated human action datasets which include actions performed in classic feature films and sports broadcast television.

Charged-impurity scattering in graphene

Abstract: Valuable insight into the influence of scattering from impurities on the peculiar electronic properties of graphene are gained by a systematic study of how its conductivity changes with increasing concentration of potassium ions deposited on its surface. Since the initial demonstration of the ability to experimentally isolate a single graphene sheet1, a great deal of theoretical work has focused on explaining graphene’s unusual carrier-density-dependent conductivity σ(n), and its minimum value (σmin) of nearly twice the quantum unit of conductance (4e2/h) (refs 1, 2, 3, 4, 5, 6). Potential explanations for such behaviour include short-range disorder7,8,9,10, ‘ripples’ in graphene’s atomic structure11,12 and the presence of charged impurities7,8,13,14,15,16,17,18. Here, we conduct a systematic study of the last of these mechanisms, by monitoring changes in electronic characteristics of initially clean graphene19 as the density of charged impurities (nimp) is increased by depositing potassium atoms onto its surface in ultrahigh vacuum. At non-zero carrier density, charged-impurity scattering produces the widely observed linear dependence1,2,3,4,5,6 of σ(n). More significantly, we find that σmin occurs not at the carrier density that neutralizes nimp, but rather the carrier density at which the average impurity potential is zero15. As nimp increases, σmin initially falls to a minimum value near 4e2/h. This indicates that σmin in the present experimental samples1,2,3,4,5,6 is governed not by the physics of the Dirac point singularity20,21, but rather by carrier-density inhomogeneities induced by the potential of charged impurities6,8,14,15.

Eliciting risk and time preferences.

Abstract: We design experiments to jointly elicit risk and time preferences for the adult Danish population. Since subjects are generally risk averse, we find that joint elicitation provides estimates of discount rates that are significantly lower than those found in previous studies and more in line with what would be considered as a priori reasonable rates. The statistical specification relies on a theoretical framework that involves a latent trade-off between long-run optimization and short-run temptation. Estimation of this specification is undertaken using structural, maximum likelihood methods. Our main results based on exponential discounting are robust to alternative specifications such as hyperbolic discounting. These results have direct implications for attempts to elicit time preferences, as well as debates over the appropriate domain of the utility function when characterizing risk aversion and time consistency.

A Comparative Study of Energy Minimization Methods for Markov Random Fields with Smoothness-Based Priors

Abstract: Among the most exciting advances in early vision has been the development of efficient energy minimization algorithms for pixel-labeling tasks such as depth or texture computation. It has been known for decades that such problems can be elegantly expressed as Markov random fields, yet the resulting energy minimization problems have been widely viewed as intractable. Algorithms such as graph cuts and loopy belief propagation (LBP) have proven to be very powerful: For example, such methods form the basis for almost all the top-performing stereo methods. However, the trade-offs among different energy minimization algorithms are still not well understood. In this paper, we describe a set of energy minimization benchmarks and use them to compare the solution quality and runtime of several common energy minimization algorithms. We investigate three promising methods-graph cuts, LBP, and tree-reweighted message passing-in addition to the well-known older iterated conditional mode (ICM) algorithm. Our benchmark problems are drawn from published energy functions used for stereo, image stitching, interactive segmentation, and denoising. We also provide a general-purpose software interface that allows vision researchers to easily switch between optimization methods. The benchmarks, code, images, and results are available at http://vision.middlebury.edu/MRF/.

Optical solitons in PT periodic potentials

Abstract: We investigate the effect of nonlinearity on beam dynamics in parity-time (PT) symmetric potentials. We show that a novel class of one- and two-dimensional nonlinear self-trapped modes can exist in optical PT synthetic lattices. These solitons are shown to be stable over a wide range of potential parameters. The transverse power flow within these complex solitons is also examined.

On Teams, Teamwork, and Team Performance: Discoveries and Developments

Abstract: Objective: We highlight some of the key discoveries and developments in the area of team performance over the past 50 years, especially as reflected in the pages of Human Factors.Background: Teams ...

Mitochondrial fragmentation in neurodegeneration

Abstract: Mitochondria are remarkably dynamic organelles that migrate, divide and fuse. Cycles of mitochondrial fission and fusion ensure metabolite and mitochondrial DNA mixing and dictate organelle shape, number and bioenergetic functionality. There is mounting evidence that mitochondrial dysfunction is an early and causal event in neurodegeneration. Mutations in the mitochondrial fusion GTPases mitofusin 2 and optic atrophy 1, neurotoxins and oxidative stress all disrupt the cable-like morphology of functional mitochondria. This results in impaired bioenergetics and mitochondrial migration, and can trigger neurodegeneration. These findings suggest potential new treatment avenues for neurodegenerative diseases.

Self-healing properties of optical Airy beams

Abstract: We investigate both theoretically and experimentally the self-healing properties of accelerating Airy beams. We show that this class of waves tends to reform during propagation in spite of the severity of the imposed perturbations. In all occasions the reconstruction of these beams is interpreted through their internal transverse power flow. The robustness of these optical beams in scattering and turbulent environments is also studied experimentally. Our observations are in excellent agreement with numerical simulations.

Anderson localization and nonlinearity in one-dimensional disordered photonic lattices.

Abstract: We experimentally investigate the evolution of linear and nonlinear waves in a realization of the Anderson model using disordered one-dimensional waveguide lattices. Two types of localized eigenmodes, flat-phased and staggered, are directly measured. Nonlinear perturbations enhance localization in one type and induce delocalization in the other. In a complementary approach, we study the evolution on short time scales of delta-like wave packets in the presence of disorder. A transition from ballistic wave packet expansion to exponential (Anderson) localization is observed. We also find an intermediate regime in which the ballistic and localized components coexist while diffusive dynamics is absent. Evidence is found for a faster transition into localization under nonlinear conditions.

A meta‐analysis of teamwork processes: tests of a multidimensional model and relationships with team effectiveness criteria

Abstract: Drawing from Marks, Mathieu, and Zaccaro (2001), we proposed that narrowly focused teamwork processes load onto 3 higher-order teamwork process dimensions, which in turn load onto a general teamwork process factor. Results of model testing using meta-analyses of relationships among narrow teamwork processes provided support for the structure of this multidimensional theory of teamwork process. Meta-analytic results also indicated that teamwork processes have positive relationships with team performance and member satisfaction, and that the relationships are similar across the teamwork dimensions and levels of process specificity. Supplemental analyses revealed that the 3 intermediate-level teamwork processes are positively and strongly related to cohesion and potency. Results of moderator analyses suggested that relationships among teamwork processes and team performance are somewhat dependent on task interdependence and team size.

A One-Step Homogeneous Immunoassay for Cancer Biomarker Detection Using Gold Nanoparticle Probes Coupled with Dynamic Light Scattering

Abstract: A one-step homogeneous immunoassay for the detection of a prostate cancer biomarker, free-PSA (prostate specific antigen), was developed using gold nanoparticle probes coupled with dynamic light scattering (DLS) measurements. A spherical gold nanoparticle with a core diameter around 37 nm and a gold nanorod with a dimension of 40 by 10 nm were first conjugated with two different primary anti-PSA antibodies and then used as optical probes for the immunoassay. In the presence of antigen f-PSA in solution, the nanoparticles and nanorods aggregate together into pairs and oligomers through the formation of a sandwich type antibody−antigen−antibody linkage. The relative ratio of nanoparticle-nanorod pairs and oligomers versus individual nanoparticles was quantitatively monitored by DLS measurement. A correlation can be established between this relative ratio and the amount of antigen in solution. The light scattering intensity of nanoparticles and nanoparticle oligomers is several orders of magnitude higher tha...

The organisation of denial: Conservative think tanks and environmental scepticism

Abstract: Environmental scepticism denies the seriousness of environmental problems, and self-professed ‘sceptics’ claim to be unbiased analysts combating ‘junk science’. This study quantitatively analyses 141 English-language environmentally sceptical books published between 1972 and 2005. We find that over 92 per cent of these books, most published in the US since 1992, are linked to conservative think tanks (CTTs). Further, we analyse CTTs involved with environmental issues and find that 90 per cent of them espouse environmental scepticism. We conclude that scepticism is a tactic of an elite-driven counter-movement designed to combat environmentalism, and that the successful use of this tactic has contributed to the weakening of US commitment to environmental protection.

Does Team Training Improve Team Performance? A Meta-Analysis

Abstract: Objective: This research effort leveraged the science of training to guide a taxonomic integration and a series of meta-analyses to gauge the effectiveness and boundary conditions of team training ...

Exploiting Open-Endedness to Solve Problems Through the Search for Novelty

Abstract: This paper establishes a link between the challenge of solving highly ambitious problems in machine learning and the goal of reproducing the dynamics of open-ended evolution in artificial life. A major problem with the objective function in machine learning is that through deception it may actually prevent the objective from being reached. In a similar way, selection in evolution may sometimes act to discourage increasing complexity. This paper proposes a single idea that both overcomes the obstacle of deception and suggests a simple new approach to open-ended evolution: Instead of either explicitly seeking an objective or modeling a domain to capture the open-endedness of natural evolution, the idea is to simply search for novelty. Even in an objective-based problem, such novelty search ignores the objective and searches for behavioral novelty. Yet because many points in the search space collapse to the same point in behavior space, it turns out that the search for novelty is computationally feasible. Furthermore, because there are only so many simple behaviors, the search for novelty leads to increasing complexity. In fact, on the way up the ladder of complexity, the search is likely to encounter at least one solution. In this way, by decoupling the idea of open-ended search from only artificial life worlds, the raw search for novelty can be applied to real world problems. Counterintuitively, in the deceptive maze navigation task in this paper, novelty search significantly outperforms objective-based search, suggesting a surprising new approach to machine learning.

Learning human actions via information maximization

Abstract: In this paper, we present a novel approach for automatically learning a compact and yet discriminative appearance-based human action model. A video sequence is represented by a bag of spatiotemporal features called video-words by quantizing the extracted 3D interest points (cuboids) from the videos. Our proposed approach is able to automatically discover the optimal number of video-word clusters by utilizing maximization of mutual information(MMI). Unlike the k-means algorithm, which is typically used to cluster spatiotemporal cuboids into video words based on their appearance similarity, MMI clustering further groups the video-words, which are highly correlated to some group of actions. To capture the structural information of the learnt optimal video-word clusters, we explore the correlation of the compact video-word clusters. We use the modified correlogram, which is not only translation and rotation invariant, but also somewhat scale invariant. We extensively test our proposed approach on two publicly available challenging datasets: the KTH dataset and IXMAS multiview dataset. To the best of our knowledge, we are the first to try the bag of video-words related approach on the multiview dataset. We have obtained very impressive results on both datasets.

Dark-field microscopy studies of single metal nanoparticles: understanding the factors that influence the linewidth of the localized surface plasmon resonance

Abstract: This article provides a review of our recent Rayleigh scattering measurements on single metal nanoparticles. Two different systems will be discussed in detail: gold nanorods with lengths between 30 and 80 nm, and widths between 8 and 30 nm; and hollow gold-silver nanocubes (termed nanoboxes or nanocages depending on their exact morphology) with edge lengths between 100 and 160 nm, and wall thicknesses of the order of 10 nm. The goal of this work is to understand how the linewidth of the localized surface plasmon resonance depends on the size, shape, and environment of the nanoparticles. Specifically, the relative contributions from bulk dephasing, electron-surface scattering, and radiation damping (energy loss via coupling to the radiation field) have been determined by examining particles with different dimensions. This separation is possible because the magnitude of the radiation damping effect is proportional to the particle volume, whereas, the electron-surface scattering contribution is inversely proportional to the dimensions. For the nanorods, radiation damping is the dominant effect for thick rods (widths greater than 20 nm), while electron-surface scattering is dominant for thin rods (widths less than 10 nm). Rods with widths in between these limits have narrow resonances-approaching the value determined by the bulk contribution. For nanoboxes and nanocages, both radiation damping and electron-surface scattering are significant at all sizes. This is because these materials have thin walls, but large edge lengths and, therefore, relatively large volumes. The effect of the environment on the localized surface plasmon resonance has also been studied for nanoboxes. Increasing the dielectric constant of the surroundings causes a red-shift and an increase in the linewidth of the plasmon band. The increase in linewidth is attributed to enhanced radiation damping.

Ballistic dynamics of Airy beams

Abstract: We demonstrate both theoretically and experimentally that optical Airy beams propagating in free space can perform ballistic dynamics akin to those of projectiles moving under the action of gravity. The parabolic trajectories of these beams as well as the motion of their center of gravity were observed in good agreement with theory. The possibility of circumventing an obstacle placed in the path of the Airy beam is discussed.

Floor Fields for Tracking in High Density Crowd Scenes

Abstract: This paper presents an algorithm for tracking individual targets in high density crowd scenes containing hundreds of people. Tracking in such a scene is extremely challenging due to the small number of pixels on the target, appearance ambiguity resulting from the dense packing, and severe inter-object occlusions. The novel tracking algorithm, which is outlined in this paper, will overcome these challenges using a scene structure based force model. In this force model an individual, when moving in a particular scene, is subjected to global and local forces that are functions of the layout of that scene and the locomotive behavior of other individuals in the scene. The key ingredients of the force model are three floor fields, which are inspired by the research in the field of evacuation dynamics, namely Static Floor Field (SFF), Dynamic Floor Field (DFF), and Boundary Floor Field (BFF). These fields determine the probability of move from one location to another by converting the long-range forces into local ones. The SFF specifies regions of the scene which are attractive in nature (e.g. an exit location). The DFF specifies the immediate behavior of the crowd in the vicinity of the individual being tracked. The BFF specifies influences exhibited by the barriers in the scene (e.g. walls, no-go areas). By combining cues from all three fields with the available appearance information, we track individual targets in high density crowds.

STAT3 as a target for inducing apoptosis in solid and hematological tumors.

Abstract: Studies in the past few years have provided compelling evidence for the critical role of aberrant Signal Transducer and Activator of Transcription 3 (STAT3) in malignant transformation and tumorigenesis. Thus, it is now generally accepted that STAT3 is one of the critical players in human cancer formation and represents a valid target for novel anticancer drug design. This review focuses on aberrant STAT3 and its role in promoting tumor cell survival and supporting the malignant phenotype. A brief evaluation of the current strategies targeting STAT3 for the development of novel anticancer agents against human tumors harboring constitutively active STAT3 will also be presented.

Examining the pedagogical foundations of modern educational computer games

Abstract: This study examines the pedagogical foundations of modern educational (computer video) games. Specifically, Cooper's [Cooper, H. (1985, Mar 31-April 4). A taxonomy of literature reviews. In Paper presented at the American Educational Research Association, Chicago, IL] literature review framework was used to locate and examine relevant literature and games (published between the years 2000 and 2007) and to organize and report findings. A total of 50 articles and 55 educational games met specified selection criteria. The pedagogical foundations of the games were further investigated by contacting the authors of the games. Twenty-two games were based on established learning theories or instructional strategies and two games included basic instructional events that were not associated with any particular theory or strategy. No information regarding the pedagogical foundations of the 31 games was found or received. Analysis of the games and supporting literature revealed several patterns of practice that may be used to guide future research and development of educational games.

Learning object motion patterns for anomaly detection and improved object detection

Abstract: We present a novel framework for learning patterns of motion and sizes of objects in static camera surveillance. The proposed method provides a new higher-level layer to the traditional surveillance pipeline for anomalous event detection and scene model feedback. Pixel level probability density functions (pdfs) of appearance have been used for background modelling in the past, but modelling pixel level pdfs of object speed and size from the tracks is novel. Each pdf is modelled as a multivariate Gaussian mixture model (GMM) of the motion (destination location & transition time) and the size (width & height) parameters of the objects at that location. Output of the tracking module is used to perform unsupervised EM-based learning of every GMM. We have successfully used the proposed scene model to detect local as well as global anomalies in object tracks. We also show the use of this scene model to improve object detection through pixel-level parameter feedback of the minimum object size and background learning rate. Most object path modelling approaches first cluster the tracks into major paths in the scene, which can be a source of error. We avoid this by building local pdfs that capture a variety of tracks which are passing through them. Qualitative and quantitative analysis of actual surveillance videos proved the effectiveness of the proposed approach.

An empirical examination of factors contributing to the creation of successful e-learning environments

Abstract: Although existing models of e-learning effectiveness in information systems (IS) have increased our understanding of how technology can support and enhance learning, most of our models do not take into account the importance of social presence. Thus, this study extends previous research by developing a model of e-learning effectiveness which adds social presence to other oft studied variables including application-specific computer self-efficacy (AS-CSE), perceived usefulness, course interaction, and e-learning effectiveness. Using data from 345 individuals, this model was validated through a field study in an introductory IS survey course. Results indicate that AS-CSE and perceived usefulness were related to course performance, course satisfaction, and course instrumentality. In addition, course interaction was related to course performance and satisfaction. Finally, social presence was related to course satisfaction and course instrumentality. Implications for research and practice are discussed.

Effect of synthesis conditions on the growth of ZnO nanorods via hydrothermal method

Abstract: ZnO nanorods with hexagonal structures were synthesized by a hydrothermal method under different conditions. The effect of synthesis conditions on ZnO nanorod growth was systematically studied by scanning electron microscopy. All samples were characterized by X-ray diffraction, energy-dispersive X-ray spectroscopy and micro-Raman spectroscopy. The results demonstrate that the morphology and ordering of ZnO nanorods are determined by the growth temperature, the overall concentration of the precursors and deposition time. ZnO nanorod morphology and surface-to-volume ratio are most sensitive to temperature. The width of ZnO nanorods can be controlled by the overall concentration of the reactants and by temperature. The influence of the chemical reactions, the nucleation and growth process on the morphology of ZnO nanorods is discussed.