Multiscale wavelet representations for mammographic feature analysis
NASA Astrophysics Data System (ADS)
Laine, Andrew F.; Song, Shuwu
1992-12-01
This paper introduces a novel approach for accomplishing mammographic feature analysis through multiresolution representations. We show that efficient (nonredundant) representations may be identified from digital mammography and used to enhance specific mammographic features within a continuum of scale space. The multiresolution decomposition of wavelet transforms provides a natural hierarchy in which to embed an interactive paradigm for accomplishing scale space feature analysis. Choosing wavelets (or analyzing functions) that are simultaneously localized in both space and frequency, results in a powerful methodology for image analysis. Multiresolution and orientation selectivity, known biological mechanisms in primate vision, are ingrained in wavelet representations and inspire the techniques presented in this paper. Our approach includes local analysis of complete multiscale representations. Mammograms are reconstructed from wavelet coefficients, enhanced by linear, exponential and constant weight functions localized in scale space. By improving the visualization of breast pathology we can improve the changes of early detection of breast cancers (improve quality) while requiring less time to evaluate mammograms for most patients (lower costs).
Wavelet processing techniques for digital mammography
NASA Astrophysics Data System (ADS)
Laine, Andrew F.; Song, Shuwu
1992-09-01
This paper introduces a novel approach for accomplishing mammographic feature analysis through multiresolution representations. We show that efficient (nonredundant) representations may be identified from digital mammography and used to enhance specific mammographic features within a continuum of scale space. The multiresolution decomposition of wavelet transforms provides a natural hierarchy in which to embed an interactive paradigm for accomplishing scale space feature analysis. Similar to traditional coarse to fine matching strategies, the radiologist may first choose to look for coarse features (e.g., dominant mass) within low frequency levels of a wavelet transform and later examine finer features (e.g., microcalcifications) at higher frequency levels. In addition, features may be extracted by applying geometric constraints within each level of the transform. Choosing wavelets (or analyzing functions) that are simultaneously localized in both space and frequency, results in a powerful methodology for image analysis. Multiresolution and orientation selectivity, known biological mechanisms in primate vision, are ingrained in wavelet representations and inspire the techniques presented in this paper. Our approach includes local analysis of complete multiscale representations. Mammograms are reconstructed from wavelet representations, enhanced by linear, exponential and constant weight functions through scale space. By improving the visualization of breast pathology we can improve the chances of early detection of breast cancers (improve quality) while requiring less time to evaluate mammograms for most patients (lower costs).
Adaptive multiscale processing for contrast enhancement
NASA Astrophysics Data System (ADS)
Laine, Andrew F.; Song, Shuwu; Fan, Jian; Huda, Walter; Honeyman, Janice C.; Steinbach, Barbara G.
1993-07-01
This paper introduces a novel approach for accomplishing mammographic feature analysis through overcomplete multiresolution representations. We show that efficient representations may be identified from digital mammograms within a continuum of scale space and used to enhance features of importance to mammography. Choosing analyzing functions that are well localized in both space and frequency, results in a powerful methodology for image analysis. We describe methods of contrast enhancement based on two overcomplete (redundant) multiscale representations: (1) Dyadic wavelet transform (2) (phi) -transform. Mammograms are reconstructed from transform coefficients modified at one or more levels by non-linear, logarithmic and constant scale-space weight functions. Multiscale edges identified within distinct levels of transform space provide a local support for enhancement throughout each decomposition. We demonstrate that features extracted from wavelet spaces can provide an adaptive mechanism for accomplishing local contrast enhancement. We suggest that multiscale detection and local enhancement of singularities may be effectively employed for the visualization of breast pathology without excessive noise amplification.
ERIC Educational Resources Information Center
Nishimura, Mayu; Maurer, Daphne; Gao, Xiaoqing
2009-01-01
We explored differences in the mental representation of facial identity between 8-year-olds and adults. The 8-year-olds and adults made similarity judgments of a homogeneous set of faces (individual hair cues removed) using an "odd-man-out" paradigm. Multidimensional scaling (MDS) analyses were performed to represent perceived similarity of faces…
Sereno, Anne B.; Lehky, Sidney R.
2011-01-01
Although the representation of space is as fundamental to visual processing as the representation of shape, it has received relatively little attention from neurophysiological investigations. In this study we characterize representations of space within visual cortex, and examine how they differ in a first direct comparison between dorsal and ventral subdivisions of the visual pathways. Neural activities were recorded in anterior inferotemporal cortex (AIT) and lateral intraparietal cortex (LIP) of awake behaving monkeys, structures associated with the ventral and dorsal visual pathways respectively, as a stimulus was presented at different locations within the visual field. In spatially selective cells, we find greater modulation of cell responses in LIP with changes in stimulus position. Further, using a novel population-based statistical approach (namely, multidimensional scaling), we recover the spatial map implicit within activities of neural populations, allowing us to quantitatively compare the geometry of neural space with physical space. We show that a population of spatially selective LIP neurons, despite having large receptive fields, is able to almost perfectly reconstruct stimulus locations within a low-dimensional representation. In contrast, a population of AIT neurons, despite each cell being spatially selective, provide less accurate low-dimensional reconstructions of stimulus locations. They produce instead only a topologically (categorically) correct rendition of space, which nevertheless might be critical for object and scene recognition. Furthermore, we found that the spatial representation recovered from population activity shows greater translation invariance in LIP than in AIT. We suggest that LIP spatial representations may be dimensionally isomorphic with 3D physical space, while in AIT spatial representations may reflect a more categorical representation of space (e.g., “next to” or “above”). PMID:21344010
Modelling of Space-Time Soil Moisture in Savannas and its Relation to Vegetation Patterns
NASA Astrophysics Data System (ADS)
Rodriguez-Iturbe, I.; Mohanty, B.; Chen, Z.
2017-12-01
A physically derived space-time representation of the soil moisture field is presented. It includes the incorporation of a "jitter" process acting over the space-time soil moisture field and accounting for the short distance heterogeneities in topography, soil, and vegetation characteristics. The modelling scheme allows for the representation of spatial random fluctuations of soil moisture at small spatial scales and reproduces quite well the space-time correlation structure of soil moisture from a field study in Oklahoma. It is shown that the islands of soil moisture above different thresholds have sizes which follow power distributions over an extended range of scales. A discussion is provided about the possible links of this feature with the observed power law distributions of the clusters of trees in savannas.
Universal sequence map (USM) of arbitrary discrete sequences
2002-01-01
Background For over a decade the idea of representing biological sequences in a continuous coordinate space has maintained its appeal but not been fully realized. The basic idea is that any sequence of symbols may define trajectories in the continuous space conserving all its statistical properties. Ideally, such a representation would allow scale independent sequence analysis – without the context of fixed memory length. A simple example would consist on being able to infer the homology between two sequences solely by comparing the coordinates of any two homologous units. Results We have successfully identified such an iterative function for bijective mappingψ of discrete sequences into objects of continuous state space that enable scale-independent sequence analysis. The technique, named Universal Sequence Mapping (USM), is applicable to sequences with an arbitrary length and arbitrary number of unique units and generates a representation where map distance estimates sequence similarity. The novel USM procedure is based on earlier work by these and other authors on the properties of Chaos Game Representation (CGR). The latter enables the representation of 4 unit type sequences (like DNA) as an order free Markov Chain transition table. The properties of USM are illustrated with test data and can be verified for other data by using the accompanying web-based tool:http://bioinformatics.musc.edu/~jonas/usm/. Conclusions USM is shown to enable a statistical mechanics approach to sequence analysis. The scale independent representation frees sequence analysis from the need to assume a memory length in the investigation of syntactic rules. PMID:11895567
Population Coding of Visual Space: Modeling
Lehky, Sidney R.; Sereno, Anne B.
2011-01-01
We examine how the representation of space is affected by receptive field (RF) characteristics of the encoding population. Spatial responses were defined by overlapping Gaussian RFs. These responses were analyzed using multidimensional scaling to extract the representation of global space implicit in population activity. Spatial representations were based purely on firing rates, which were not labeled with RF characteristics (tuning curve peak location, for example), differentiating this approach from many other population coding models. Because responses were unlabeled, this model represents space using intrinsic coding, extracting relative positions amongst stimuli, rather than extrinsic coding where known RF characteristics provide a reference frame for extracting absolute positions. Two parameters were particularly important: RF diameter and RF dispersion, where dispersion indicates how broadly RF centers are spread out from the fovea. For large RFs, the model was able to form metrically accurate representations of physical space on low-dimensional manifolds embedded within the high-dimensional neural population response space, suggesting that in some cases the neural representation of space may be dimensionally isomorphic with 3D physical space. Smaller RF sizes degraded and distorted the spatial representation, with the smallest RF sizes (present in early visual areas) being unable to recover even a topologically consistent rendition of space on low-dimensional manifolds. Finally, although positional invariance of stimulus responses has long been associated with large RFs in object recognition models, we found RF dispersion rather than RF diameter to be the critical parameter. In fact, at a population level, the modeling suggests that higher ventral stream areas with highly restricted RF dispersion would be unable to achieve positionally-invariant representations beyond this narrow region around fixation. PMID:21344012
The Structure of Integral Dimensions: Contrasting Topological and Cartesian Representations
ERIC Educational Resources Information Center
Jones, Matt; Goldstone, Robert L.
2013-01-01
Diverse evidence shows that perceptually integral dimensions, such as those composing color, are represented holistically. However, the nature of these holistic representations is poorly understood. Extant theories, such as those founded on multidimensional scaling or general recognition theory, model integral stimulus spaces using a Cartesian…
Development of the Hippocampal Cognitive Map in Pre-weanling Rats
Wills, Tom; Cacucci, Francesca; Burgess, Neil; O’Keefe, John
2011-01-01
Orienting in large-scale space depends on the interaction of environmental experience and pre-configured, possibly innate, constructs. Place, head-direction and grid cells in the hippocampal formation provide allocentric representations of space. Here we show how these cognitive representations emerge and develop as rat pups first begin to explore their environment. Directional, locational and rhythmic organization of firing are present during initial exploration, including adult-like directional firing. The stability and precision of place cell firing continues to develop throughout juvenility. Stable grid cell firing appears later but matures rapidly to adult levels. Our results demonstrate the presence of three neuronal representations of space prior to extensive experience, and show how they develop with age. PMID:20558720
URBAN MORPHOLOGY FOR HOUSTON TO DRIVE MODELS-3/CMAQ AT NEIGHBORHOOD SCALES
Air quality simulation models applied at various horizontal scales require different degrees of treatment in the specifications of the underlying surfaces. As we model neighborhood scales ( 1 km horizontal grid spacing), the representation of urban morphological structures (e....
A study of complex scaling transformation using the Wigner representation of wavefunctions.
Kaprálová-Ždánská, Petra Ruth
2011-05-28
The complex scaling operator exp(-θ ̂x̂p/ℏ), being a foundation of the complex scaling method for resonances, is studied in the Wigner phase-space representation. It is shown that the complex scaling operator behaves similarly to the squeezing operator, rotating and amplifying Wigner quasi-probability distributions of the respective wavefunctions. It is disclosed that the distorting effect of the complex scaling transformation is correlated with increased numerical errors of computed resonance energies and widths. The behavior of the numerical error is demonstrated for a computation of CO(2+) vibronic resonances. © 2011 American Institute of Physics
Nishimura, Mayu; Maurer, Daphne; Gao, Xiaoqing
2009-07-01
We explored differences in the mental representation of facial identity between 8-year-olds and adults. The 8-year-olds and adults made similarity judgments of a homogeneous set of faces (individual hair cues removed) using an "odd-man-out" paradigm. Multidimensional scaling (MDS) analyses were performed to represent perceived similarity of faces in a multidimensional space. Five dimensions accounted optimally for the judgments of both children and adults, with similar local clustering of faces. However, the fit of the MDS solutions was better for adults, in part because children's responses were more variable. More children relied predominantly on a single dimension, namely eye color, whereas adults appeared to use multiple dimensions for each judgment. The pattern of findings suggests that children's mental representation of faces has a structure similar to that of adults but that children's judgments are influenced less consistently by that overall structure.
Bounds on the polymer scale from gamma ray bursts
NASA Astrophysics Data System (ADS)
Bonder, Yuri; Garcia-Chung, Angel; Rastgoo, Saeed
2017-11-01
The polymer representations, which are partially motivated by loop quantum gravity, have been suggested as alternative schemes to quantize the matter fields. Here we apply a version of the polymer representations to the free electromagnetic field, in a reduced phase space setting, and derive the corresponding effective (i.e., semiclassical) Hamiltonian. We study the propagation of an electromagnetic pulse, and we confront our theoretical results with gamma ray burst observations. This comparison reveals that the dimensionless polymer scale must be smaller than 4 ×10-35 , casting doubts on the possibility that the matter fields are quantized with the polymer representation we employed.
Hexagonal wavelet processing of digital mammography
NASA Astrophysics Data System (ADS)
Laine, Andrew F.; Schuler, Sergio; Huda, Walter; Honeyman-Buck, Janice C.; Steinbach, Barbara G.
1993-09-01
This paper introduces a novel approach for accomplishing mammographic feature analysis through overcomplete multiresolution representations. We show that efficient representations may be identified from digital mammograms and used to enhance features of importance to mammography within a continuum of scale-space. We present a method of contrast enhancement based on an overcomplete, non-separable multiscale representation: the hexagonal wavelet transform. Mammograms are reconstructed from transform coefficients modified at one or more levels by local and global non-linear operators. Multiscale edges identified within distinct levels of transform space provide local support for enhancement. We demonstrate that features extracted from multiresolution representations can provide an adaptive mechanism for accomplishing local contrast enhancement. We suggest that multiscale detection and local enhancement of singularities may be effectively employed for the visualization of breast pathology without excessive noise amplification.
Embedded Data Representations.
Willett, Wesley; Jansen, Yvonne; Dragicevic, Pierre
2017-01-01
We introduce embedded data representations, the use of visual and physical representations of data that are deeply integrated with the physical spaces, objects, and entities to which the data refers. Technologies like lightweight wireless displays, mixed reality hardware, and autonomous vehicles are making it increasingly easier to display data in-context. While researchers and artists have already begun to create embedded data representations, the benefits, trade-offs, and even the language necessary to describe and compare these approaches remain unexplored. In this paper, we formalize the notion of physical data referents - the real-world entities and spaces to which data corresponds - and examine the relationship between referents and the visual and physical representations of their data. We differentiate situated representations, which display data in proximity to data referents, and embedded representations, which display data so that it spatially coincides with data referents. Drawing on examples from visualization, ubiquitous computing, and art, we explore the role of spatial indirection, scale, and interaction for embedded representations. We also examine the tradeoffs between non-situated, situated, and embedded data displays, including both visualizations and physicalizations. Based on our observations, we identify a variety of design challenges for embedded data representation, and suggest opportunities for future research and applications.
Time drawings: Spatial representation of temporal concepts.
Leone, María Juliana; Salles, Alejo; Pulver, Alejandro; Golombek, Diego Andrés; Sigman, Mariano
2018-03-01
Time representation is a fundamental property of human cognition. Ample evidence shows that time (and numbers) are represented in space. However, how the conceptual mapping varies across individuals, scales, and temporal structures remains largely unknown. To investigate this issue, we conducted a large online study consisting in five experiments that addressed different time scales and topology: Zones of time, Seasons, Days of the week, Parts of the day and Timeline. Participants were asked to map different kinds of time events to a location in space and to determine their size and color. Results showed that time is organized in space in a hierarchical progression: some features appear to be universal (i.e. selection order), others are shaped by how time is organized in distinct cultures (i.e. location order) and, finally, some aspects vary depending on individual features such as age, gender, and chronotype (i.e. size and color). Copyright © 2018 Elsevier Inc. All rights reserved.
An event map of memory space in the hippocampus
Deuker, Lorena; Bellmund, Jacob LS; Navarro Schröder, Tobias; Doeller, Christian F
2016-01-01
The hippocampus has long been implicated in both episodic and spatial memory, however these mnemonic functions have been traditionally investigated in separate research strands. Theoretical accounts and rodent data suggest a common mechanism for spatial and episodic memory in the hippocampus by providing an abstract and flexible representation of the external world. Here, we monitor the de novo formation of such a representation of space and time in humans using fMRI. After learning spatio-temporal trajectories in a large-scale virtual city, subject-specific neural similarity in the hippocampus scaled with the remembered proximity of events in space and time. Crucially, the structure of the entire spatio-temporal network was reflected in neural patterns. Our results provide evidence for a common coding mechanism underlying spatial and temporal aspects of episodic memory in the hippocampus and shed new light on its role in interleaving multiple episodes in a neural event map of memory space. DOI: http://dx.doi.org/10.7554/eLife.16534.001 PMID:27710766
A CPT for Improving Turbulence and Cloud Processes in the NCEP Global Models
NASA Astrophysics Data System (ADS)
Krueger, S. K.; Moorthi, S.; Randall, D. A.; Pincus, R.; Bogenschutz, P.; Belochitski, A.; Chikira, M.; Dazlich, D. A.; Swales, D. J.; Thakur, P. K.; Yang, F.; Cheng, A.
2016-12-01
Our Climate Process Team (CPT) is based on the premise that the NCEP (National Centers for Environmental Prediction) global models can be improved by installing an integrated, self-consistent description of turbulence, clouds, deep convection, and the interactions between clouds and radiative and microphysical processes. The goal of our CPT is to unify the representation of turbulence and subgrid-scale (SGS) cloud processes and to unify the representation of SGS deep convective precipitation and grid-scale precipitation as the horizontal resolution decreases. We aim to improve the representation of small-scale phenomena by implementing a PDF-based SGS turbulence and cloudiness scheme that replaces the boundary layer turbulence scheme, the shallow convection scheme, and the cloud fraction schemes in the GFS (Global Forecast System) and CFS (Climate Forecast System) global models. We intend to improve the treatment of deep convection by introducing a unified parameterization that scales continuously between the simulation of individual clouds when and where the grid spacing is sufficiently fine and the behavior of a conventional parameterization of deep convection when and where the grid spacing is coarse. We will endeavor to improve the representation of the interactions of clouds, radiation, and microphysics in the GFS/CFS by using the additional information provided by the PDF-based SGS cloud scheme. The team is evaluating the impacts of the model upgrades with metrics used by the NCEP short-range and seasonal forecast operations.
Familiarity expands space and contracts time.
Jafarpour, Anna; Spiers, Hugo
2017-01-01
When humans draw maps, or make judgments about travel-time, their responses are rarely accurate and are often systematically distorted. Distortion effects on estimating time to arrival and the scale of sketch-maps reveal the nature of mental representation of time and space. Inspired by data from rodent entorhinal grid cells, we predicted that familiarity to an environment would distort representations of the space by expanding the size of it. We also hypothesized that travel-time estimation would be distorted in the same direction as space-size, if time and space rely on the same cognitive map. We asked international students, who had lived at a college in London for 9 months, to sketch a south-up map of their college district, estimate travel-time to destinations within the area, and mark their everyday walking routes. We found that while estimates for sketched space were expanded with familiarity, estimates of the time to travel through the space were contracted with familiarity. Thus, we found dissociable responses to familiarity in representations of time and space. © 2016 The Authors Hippocampus Published by Wiley Periodicals, Inc. © 2016 The Authors Hippocampus Published by Wiley Periodicals, Inc.
2014-01-01
Background Due to rapid sequencing of genomes, there are now millions of deposited protein sequences with no known function. Fast sequence-based comparisons allow detecting close homologs for a protein of interest to transfer functional information from the homologs to the given protein. Sequence-based comparison cannot detect remote homologs, in which evolution has adjusted the sequence while largely preserving structure. Structure-based comparisons can detect remote homologs but most methods for doing so are too expensive to apply at a large scale over structural databases of proteins. Recently, fragment-based structural representations have been proposed that allow fast detection of remote homologs with reasonable accuracy. These representations have also been used to obtain linearly-reducible maps of protein structure space. It has been shown, as additionally supported from analysis in this paper that such maps preserve functional co-localization of the protein structure space. Methods Inspired by a recent application of the Latent Dirichlet Allocation (LDA) model for conducting structural comparisons of proteins, we propose higher-order LDA-obtained topic-based representations of protein structures to provide an alternative route for remote homology detection and organization of the protein structure space in few dimensions. Various techniques based on natural language processing are proposed and employed to aid the analysis of topics in the protein structure domain. Results We show that a topic-based representation is just as effective as a fragment-based one at automated detection of remote homologs and organization of protein structure space. We conduct a detailed analysis of the information content in the topic-based representation, showing that topics have semantic meaning. The fragment-based and topic-based representations are also shown to allow prediction of superfamily membership. Conclusions This work opens exciting venues in designing novel representations to extract information about protein structures, as well as organizing and mining protein structure space with mature text mining tools. PMID:25080993
Matching shapes with self-intersections: application to leaf classification.
Mokhtarian, Farzin; Abbasi, Sadegh
2004-05-01
We address the problem of two-dimensional (2-D) shape representation and matching in presence of self-intersection for large image databases. This may occur when part of an object is hidden behind another part and results in a darker section in the gray level image of the object. The boundary contour of the object must include the boundary of this part which is entirely inside the outline of the object. The Curvature Scale Space (CSS) image of a shape is a multiscale organization of its inflection points as it is smoothed. The CSS-based shape representation method has been selected for MPEG-7 standardization. We study the effects of contour self-intersection on the Curvature Scale Space image. When there is no self-intersection, the CSS image contains several arch shape contours, each related to a concavity or a convexity of the shape. Self intersections create contours with minima as well as maxima in the CSS image. An efficient shape representation method has been introduced in this paper which describes a shape using the maxima as well as the minima of its CSS contours. This is a natural generalization of the conventional method which only includes the maxima of the CSS image contours. The conventional matching algorithm has also been modified to accommodate the new information about the minima. The method has been successfully used in a real world application to find, for an unknown leaf, similar classes from a database of classified leaf images representing different varieties of chrysanthemum. For many classes of leaves, self-intersection is inevitable during the scanning of the image. Therefore the original contributions of this paper is the generalization of the Curvature Scale Space representation to the class of 2-D contours with self-intersection, and its application to the classification of Chrysanthemum leaves.
Imagining Cosmopolitan Space: Spectacle, Rice and Global Citizenship
ERIC Educational Resources Information Center
Parry, Simon
2010-01-01
How do you stage the world? This article reviews how a series of performance installations by the theatre company Stan's Cafe have approached global space. It examines the way "Plague Nation" and "Of All the People in All the World" tackle national and global scale through the representation of populations. Drawing on a…
Goal-oriented robot navigation learning using a multi-scale space representation.
Llofriu, M; Tejera, G; Contreras, M; Pelc, T; Fellous, J M; Weitzenfeld, A
2015-12-01
There has been extensive research in recent years on the multi-scale nature of hippocampal place cells and entorhinal grid cells encoding which led to many speculations on their role in spatial cognition. In this paper we focus on the multi-scale nature of place cells and how they contribute to faster learning during goal-oriented navigation when compared to a spatial cognition system composed of single scale place cells. The task consists of a circular arena with a fixed goal location, in which a robot is trained to find the shortest path to the goal after a number of learning trials. Synaptic connections are modified using a reinforcement learning paradigm adapted to the place cells multi-scale architecture. The model is evaluated in both simulation and physical robots. We find that larger scale and combined multi-scale representations favor goal-oriented navigation task learning. Copyright © 2015 Elsevier Ltd. All rights reserved.
Listening to music primes space: pianists, but not novices, simulate heard actions.
Taylor, J Eric T; Witt, Jessica K
2015-03-01
Musicians sometimes report twitching in their fingers or hands while listening to music. This anecdote could be indicative of a tendency for auditory-motor co-representation in musicians. Here, we describe two studies showing that pianists (Experiment 1), but not novices (Experiment 2) automatically generate spatial representations that correspond to learned musical actions while listening to music. Participants made one-handed movements to the left or right from a central location in response to visual stimuli while listening to task-irrelevant auditory stimuli, which were scales played on a piano. These task-irrelevant scales were either ascending (compatible with rightward movements) or descending (compatible with leftward movements). Pianists were faster to respond when the scale direction was compatible with the direction of response movement, whereas novices' movements were unaffected by the scale. These results are in agreement with existing research on action-effect coupling in musicians, which draw heavily on common coding theory. In addition, these results show how intricate auditory stimuli (ascending or descending scales) evoke coarse, domain-general spatial representations.
Bohon, Kaitlin S.; Hermann, Katherine L.; Hansen, Thorsten
2016-01-01
Abstract The lateral geniculate nucleus is thought to represent color using two populations of cone-opponent neurons [L vs M; S vs (L + M)], which establish the cardinal directions in color space (reddish vs cyan; lavender vs lime). How is this representation transformed to bring about color perception? Prior work implicates populations of glob cells in posterior inferior temporal cortex (PIT; the V4 complex), but the correspondence between the neural representation of color in PIT/V4 complex and the organization of perceptual color space is unclear. We compared color-tuning data for populations of glob cells and interglob cells to predictions obtained using models that varied in the color-tuning narrowness of the cells, and the color preference distribution across the populations. Glob cells were best accounted for by simulated neurons that have nonlinear (narrow) tuning and, as a population, represent a color space designed to be perceptually uniform (CIELUV). Multidimensional scaling and representational similarity analyses showed that the color space representations in both glob and interglob populations were correlated with the organization of CIELUV space, but glob cells showed a stronger correlation. Hue could be classified invariant to luminance with high accuracy given glob responses and above-chance accuracy given interglob responses. Luminance could be read out invariant to changes in hue in both populations, but interglob cells tended to prefer stimuli having luminance contrast, regardless of hue, whereas glob cells typically retained hue tuning as luminance contrast was modulated. The combined luminance/hue sensitivity of glob cells is predicted for neurons that can distinguish two colors of the same hue at different luminance levels (orange/brown). PMID:27595132
Discriminative graph embedding for label propagation.
Nguyen, Canh Hao; Mamitsuka, Hiroshi
2011-09-01
In many applications, the available information is encoded in graph structures. This is a common problem in biological networks, social networks, web communities and document citations. We investigate the problem of classifying nodes' labels on a similarity graph given only a graph structure on the nodes. Conventional machine learning methods usually require data to reside in some Euclidean spaces or to have a kernel representation. Applying these methods to nodes on graphs would require embedding the graphs into these spaces. By embedding and then learning the nodes on graphs, most methods are either flexible with different learning objectives or efficient enough for large scale applications. We propose a method to embed a graph into a feature space for a discriminative purpose. Our idea is to include label information into the embedding process, making the space representation tailored to the task. We design embedding objective functions that the following learning formulations become spectral transforms. We then reformulate these spectral transforms into multiple kernel learning problems. Our method, while being tailored to the discriminative tasks, is efficient and can scale to massive data sets. We show the need of discriminative embedding on some simulations. Applying to biological network problems, our method is shown to outperform baselines.
Tcheang, Lili; Bülthoff, Heinrich H.; Burgess, Neil
2011-01-01
Our ability to return to the start of a route recently performed in darkness is thought to reflect path integration of motion-related information. Here we provide evidence that motion-related interoceptive representations (proprioceptive, vestibular, and motor efference copy) combine with visual representations to form a single multimodal representation guiding navigation. We used immersive virtual reality to decouple visual input from motion-related interoception by manipulating the rotation or translation gain of the visual projection. First, participants walked an outbound path with both visual and interoceptive input, and returned to the start in darkness, demonstrating the influences of both visual and interoceptive information in a virtual reality environment. Next, participants adapted to visual rotation gains in the virtual environment, and then performed the path integration task entirely in darkness. Our findings were accurately predicted by a quantitative model in which visual and interoceptive inputs combine into a single multimodal representation guiding navigation, and are incompatible with a model of separate visual and interoceptive influences on action (in which path integration in darkness must rely solely on interoceptive representations). Overall, our findings suggest that a combined multimodal representation guides large-scale navigation, consistent with a role for visual imagery or a cognitive map. PMID:21199934
Haberman, Jason; Brady, Timothy F; Alvarez, George A
2015-04-01
Ensemble perception, including the ability to "see the average" from a group of items, operates in numerous feature domains (size, orientation, speed, facial expression, etc.). Although the ubiquity of ensemble representations is well established, the large-scale cognitive architecture of this process remains poorly defined. We address this using an individual differences approach. In a series of experiments, observers saw groups of objects and reported either a single item from the group or the average of the entire group. High-level ensemble representations (e.g., average facial expression) showed complete independence from low-level ensemble representations (e.g., average orientation). In contrast, low-level ensemble representations (e.g., orientation and color) were correlated with each other, but not with high-level ensemble representations (e.g., facial expression and person identity). These results suggest that there is not a single domain-general ensemble mechanism, and that the relationship among various ensemble representations depends on how proximal they are in representational space. (c) 2015 APA, all rights reserved).
Suppression of Phase Mixing in Drift-Kinetic Plasma Turbulence
NASA Astrophysics Data System (ADS)
Parker, J. T.; Dellar, P. J.; Schekochihin, A. A.; Highcock, E. G.
2017-12-01
The solar wind and interstellar medium are examples of strongly magnetised, weakly collisional, astrophysical plasmas. Their turbulent fluctuations are strongly anisotropic, with small amplitudes, and frequencies much lower than the Larmor frequency. This regime is described by gyrokinetic theory, a reduced five-dimensional kinetic system describing averages over Larmor orbits. A turbulent plasma may transfer free energy, a measure of fluctuation amplitudes, from injection at large scales, typically by an instability, to dissipation at small physical scales like a turbulent fluid. Alternatively, a turbulent plasma may form fine scale structures in velocity space via phase-mixing, the mechanism that leads to Landau damping in linear plasma theory. Macroscopic plasma properties like heat and momentum transport are affected by both mechanisms. While each is understood in isolation, their interaction is not. We study this interaction using a Hankel-Hermite velocity space representation of gyrokinetic theory. The Hankel transform interacts neatly with the Bessel functions that arise from averaging over Larmor orbits, so the perpendicular velocity space is decoupled for linearized problems. The Hermite transform expresses phase mixing as nearest-neighbor coupling between parallel velocity space scales represented by Hermite mode numbers. We use this representation to study transfer mechanisms in drift-kinetic plasma turbulence, the long wavelength limit of gyrokinetic theory. We show that phase space is divided into two regions, with one transfer mechanism dominating in each. Most energy is contained in the region where the fluid-like nonlinear cascade dominates. Moreover, in that region the nonlinear cascade interferes with phase mixing by exciting an "anti phase mixing" transfer of free energy from small to large velocity space scales. This cancels out the usual phase mixing, and renders the overall behavior fluid-like. These results profoundly change our understanding of free energy flow in drift-kinetic turbulence, and, moreover, explain previously observed spectra.
SPARK: A Framework for Multi-Scale Agent-Based Biomedical Modeling.
Solovyev, Alexey; Mikheev, Maxim; Zhou, Leming; Dutta-Moscato, Joyeeta; Ziraldo, Cordelia; An, Gary; Vodovotz, Yoram; Mi, Qi
2010-01-01
Multi-scale modeling of complex biological systems remains a central challenge in the systems biology community. A method of dynamic knowledge representation known as agent-based modeling enables the study of higher level behavior emerging from discrete events performed by individual components. With the advancement of computer technology, agent-based modeling has emerged as an innovative technique to model the complexities of systems biology. In this work, the authors describe SPARK (Simple Platform for Agent-based Representation of Knowledge), a framework for agent-based modeling specifically designed for systems-level biomedical model development. SPARK is a stand-alone application written in Java. It provides a user-friendly interface, and a simple programming language for developing Agent-Based Models (ABMs). SPARK has the following features specialized for modeling biomedical systems: 1) continuous space that can simulate real physical space; 2) flexible agent size and shape that can represent the relative proportions of various cell types; 3) multiple spaces that can concurrently simulate and visualize multiple scales in biomedical models; 4) a convenient graphical user interface. Existing ABMs of diabetic foot ulcers and acute inflammation were implemented in SPARK. Models of identical complexity were run in both NetLogo and SPARK; the SPARK-based models ran two to three times faster.
Costs and benefits of tool-use on the perception of reachable space.
Bourgeois, Jérémy; Farnè, Alessandro; Coello, Yann
2014-05-01
Previous studies have shown that using a tool modifies in a short time-scale both near-body space perception and arm-length representation in the body schema. However, to date no research has specifically investigated the effect of tool-use on an action-related perceptual task. We report here a study assessing the effect of tool-use on the perception of reachable space for perceptual estimates made in reference to either the tool or the hand. Using the tool on distal objects resulted in an extension of perceived reachable space with the tool and reduced the variability of reachability estimates. Tool use also extended perceived reachable space with the hand, but with a concomitant increase of the variability of reachability estimates. These findings suggest that tool incorporation into the represented arm following tool-use improves the anticipation of action possibilities with the tool, while hand representation becomes less accurate. Copyright © 2014 Elsevier B.V. All rights reserved.
Fractal analysis of urban environment: land use and sewer system
NASA Astrophysics Data System (ADS)
Gires, A.; Ochoa Rodriguez, S.; Van Assel, J.; Bruni, G.; Murla Tulys, D.; Wang, L.; Pina, R.; Richard, J.; Ichiba, A.; Willems, P.; Tchiguirinskaia, I.; ten Veldhuis, M. C.; Schertzer, D. J. M.
2014-12-01
Land use distribution are usually obtained by automatic processing of satellite and airborne pictures. The complexity of the obtained patterns which are furthermore scale dependent is enhanced in urban environment. This scale dependency is even more visible in a rasterized representation where only a unique class is affected to each pixel. A parameter commonly analysed in urban hydrology is the coefficient of imperviousness, which reflects the proportion of rainfall that will be immediately active in the catchment response. This coefficient is strongly scale dependent with a rasterized representation. This complex behaviour is well grasped with the help of the scale invariant notion of fractal dimension which enables to quantify the space occupied by a geometrical set (here the impervious areas) not only at a single scale but across all scales. This fractal dimension is also compared to the ones computed on the representation of the catchments with the help of operational semi-distributed models. Fractal dimensions of the corresponding sewer systems are also computed and compared with values found in the literature for natural river networks. This methodology is tested on 7 pilot sites of the European NWE Interreg IV RainGain project located in France, Belgium, Netherlands, United-Kingdom and Portugal. Results are compared between all the case study which exhibit different physical features (slope, level of urbanisation, population density...).
The finite scaling for S = 1 XXZ chains with uniaxial single-ion-type anisotropy
NASA Astrophysics Data System (ADS)
Wang, Honglei; Xiong, Xingliang
2014-03-01
The scaling behavior of criticality for spin-1 XXZ chains with uniaxial single-ion-type anisotropy is investigated by employing the infinite matrix product state representation with the infinite time evolving block decimation method. At criticality, the accuracy of the ground state of a system is limited by the truncation dimension χ of the local Hilbert space. We present four evidences for the scaling of the entanglement entropy, the largest eigenvalue of the Schmidt decomposition, the correlation length, and the connection between the actual correlation length ξ and the energy. The result shows that the finite scalings are governed by the central charge of the critical system. Also, it demonstrates that the infinite time evolving block decimation algorithm by the infinite matrix product state representation can be a quite accurate method to simulate the critical properties at criticality.
Multiresolution forecasting for futures trading using wavelet decompositions.
Zhang, B L; Coggins, R; Jabri, M A; Dersch, D; Flower, B
2001-01-01
We investigate the effectiveness of a financial time-series forecasting strategy which exploits the multiresolution property of the wavelet transform. A financial series is decomposed into an over complete, shift invariant scale-related representation. In transform space, each individual wavelet series is modeled by a separate multilayer perceptron (MLP). We apply the Bayesian method of automatic relevance determination to choose short past windows (short-term history) for the inputs to the MLPs at lower scales and long past windows (long-term history) at higher scales. To form the overall forecast, the individual forecasts are then recombined by the linear reconstruction property of the inverse transform with the chosen autocorrelation shell representation, or by another perceptron which learns the weight of each scale in the prediction of the original time series. The forecast results are then passed to a money management system to generate trades.
Lee, S; Pan, J J
1996-01-01
This paper presents a new approach to representation and recognition of handwritten numerals. The approach first transforms a two-dimensional (2-D) spatial representation of a numeral into a three-dimensional (3-D) spatio-temporal representation by identifying the tracing sequence based on a set of heuristic rules acting as transformation operators. A multiresolution critical-point segmentation method is then proposed to extract local feature points, at varying degrees of scale and coarseness. A new neural network architecture, referred to as radial-basis competitive and cooperative network (RCCN), is presented especially for handwritten numeral recognition. RCCN is a globally competitive and locally cooperative network with the capability of self-organizing hidden units to progressively achieve desired network performance, and functions as a universal approximator of arbitrary input-output mappings. Three types of RCCNs are explored: input-space RCCN (IRCCN), output-space RCCN (ORCCN), and bidirectional RCCN (BRCCN). Experiments against handwritten zip code numerals acquired by the U.S. Postal Service indicated that the proposed method is robust in terms of variations, deformations, transformations, and corruption, achieving about 97% recognition rate.
HD Hydrological modelling at catchment scale using rainfall radar observations
NASA Astrophysics Data System (ADS)
Ciampalini
2017-04-01
Hydrological simulations at catchment scale repose on the quality and data availability both for soil and rainfall data. Soil data are quite easy to be collected, although their quality depends on the resources devoted to this task, rainfall data observations, instead, need further effort because of their spatiotemporal variability. Rainfalls are normally recorded with rain gauges located in the catchment, they can provide detailed temporal data, but, the representativeness is limited to the point where the data are collected. Combining different gauges in space can provide a better representation of the rainfall event but the spatialization is often the main obstacle to obtain data close to the reality. Since several years, radar observations overcome this gap providing continuous data registration, that, when properly calibrated, can offer an adequate, continuous, cover in space and time for medium-wide catchments. Here, we use radar records for the south of the France on the La Peyne catchment with the protocol there adopted by the national meteo agency, with resolution of 1 km space and 5' time scale observations. We present here the realisation of a model able to perform from rainfall radar observations, continuous hydrological and soil erosion simulations. The model is semi-theoretically based, once it simulates water fluxes (infiltration-excess overland flow, saturation overland flow, infiltration and channel routing) with a cinematic wave using the St. Venant equation on a simplified "bucket" conceptual model for ground water, and, an empirical representation of sediment load as adopted in models such as STREAM-LANDSOIL (Cerdan et al., 2002, Ciampalini et al., 2012). The advantage of this approach is to furnish a dynamic representation - simulation of the rainfall-runoff events more easily than using spatialized rainfalls from meteo stations and to offer a new look on the spatial component of the events.
[The fragmentation of representational space in schizophrenia].
Plagnol, A; Oïta, M; Montreuil, M; Granger, B; Lubart, T
2003-01-01
Existent neurocognitive models of schizophrenia converge towards a core of impairments involving working memory, context processing, action planning, controlled and intentional processing. However, the emergence of this core remains itself difficult to explain and more specific hypotheses do not explain the heterogeneity of schizophrenia. To overcome these limits, we propose a new paradigm based on representational theory from cognitive science. Some recent developments of this theory enable us to describe a subjective universe as a representational space which is displayed from memory. We outline a conceptual framework to construct such a representational space from analogical -representations that can be activated in working memory and are connected to a network of symbolic structures. These connections are notably made through an analytic process of the analogical fragments, which involves the attentional focus. This framework allows us to define rigorously some defense processes in response to traumatic tensions that are expressed on the representational space. The fragmentation of representational space is a consequence of a defensive denial based on an impairment of the analytic process. The fragmentation forms some parasitic areas in memory which are excluded from the main part of the representational space and disturb information processing. The key clinical concepts of paranoid syndromes can be defined in this conceptual framework: mental automatism, delusional intuition, acute destructuration, psychotic dissociation, and autistic withdrawal. We show that these syndromes imply each other, which in return increases the fragmentation of the representational space. Some new concepts emerge naturally in this framework, such as the concept of "suture" which is defined as a link between a parasitic area and the main representational space. Schizophrenia appears as a borderline case of fragmentation of the representational space. This conceptual framework is compatible with numerous etiological factors. Multiple clinical forms can be differentiated in accordance with the persistence of parasitic areas, the degree of fragmentation, and the formation of sutures. We use this approach to account for an empirical study concerning the analysis of analogical representations in schizophrenia. We used the Parallel Visual Information Processing Test (PVIPT) which assesses the analysis of interfering visual information. Subjects were asked to connect several small geometric figures printed on a transparency. The transparency was displayed above four photographs which were the interfering material. Then, subjects completed three tasks concerning the photographs: a recognition task, a recall task, and an affective qualification task. Using a case-by-case study, this test allows us to access the defense processes of the subjects, which is not possible with the usual methods in cognitive psychopathology. Twelve clinically-stable schizophrenic subjects participated in the study which also included a self-assessment of alexithymia by the Toronto Alexithymia Scale. We obtained 2 main results: (a) creation of items in recall or false recognition by 8 subjects, and (b) lack of the usual -negative correlations between the alexithymia score and the recall, recognition and affective qualification scores in the PVIPT. These 2 results contrast with what has been previously observed for alexithymia using the same methodology. The result (a) confirms an interfering activation in schizophrenic memory, which can be interpreted in our framework as indicative of parasitic areas. The creation of items suggests the formation of sutures between the semantic content of photographs and some delusional fragments. The result (b) suggests that the apparent alexithymia in schizophrenia is a defense against interfering activation in parasitic areas. We underline the interest of individual protocols to exhibit the dynamic interplay between an interfering activity in memory and a defensive flattening of affects.
A simple and fast representation space for classifying complex time series
NASA Astrophysics Data System (ADS)
Zunino, Luciano; Olivares, Felipe; Bariviera, Aurelio F.; Rosso, Osvaldo A.
2017-03-01
In the context of time series analysis considerable effort has been directed towards the implementation of efficient discriminating statistical quantifiers. Very recently, a simple and fast representation space has been introduced, namely the number of turning points versus the Abbe value. It is able to separate time series from stationary and non-stationary processes with long-range dependences. In this work we show that this bidimensional approach is useful for distinguishing complex time series: different sets of financial and physiological data are efficiently discriminated. Additionally, a multiscale generalization that takes into account the multiple time scales often involved in complex systems has been also proposed. This multiscale analysis is essential to reach a higher discriminative power between physiological time series in health and disease.
Influence of Immersive Human Scale Architectural Representation on Design Judgment
NASA Astrophysics Data System (ADS)
Elder, Rebecca L.
Unrealistic visual representation of architecture within our existing environments have lost all reference to the human senses. As a design tool, visual and auditory stimuli can be utilized to determine human's perception of design. This experiment renders varying building inputs within different sites, simulated with corresponding immersive visual and audio sensory cues. Introducing audio has been proven to influence the way a person perceives a space, yet most inhabitants rely strictly on their sense of vision to make design judgments. Though not as apparent, users prefer spaces that have a better quality of sound and comfort. Through a series of questions, we can begin to analyze whether a design is fit for both an acoustic and visual environment.
Subjective time in near and far representational space.
Zäch, Peter; Brugger, Peter
2008-03-01
We set out to measure healthy subjects' estimates of temporal duration during the imagination of left and right sides of an object located in either near or far representational space. Duration estimates during the observation of small-scale scenes are shorter than those during the observation of the same scenes presented in a larger scale. It is not known whether a similar space-time relationship also exists for objects merely imagined and whether subjective time varies with a forced focus on either the left or the right side of a mental image. Eyes closed, 40 healthy, right-handed subjects (20 women) had to imagine a standard Swiss railway clock either at a distance of 30 cm or 6 m. They were required to focus on the imagined movement of the second hand and provide estimates of elapsed durations of 15 and 30 seconds. Separate estimates for the left and right side of the clockface were obtained. The magnitude of implicit line bisection error was assessed in a separate task. Irrespective of side of the clockface, duration estimates were shorter for the clockface imagined in far space than for the one imagined immediately in front of the inner eye. For men, but not women, duration judgments (left relative to right side of the clockface) correlated with relative lengths of left and right line segments in the bisection task. Subjective time seems to run faster during the inspection of a small-size compared with a larger-size mental image. This finding underlines the equivalence of the laws that guide both exploration and representation of space. Together with the observed correlation between spatial and temporal measures of lateral asymmetries, the result also illustrates the conceptual similarities in the processing of space and time. The normative data presented here may be useful for clinical applications of the paradigm in patients with hemispatial neglect or a distorted perception of time.
Grid cells form a global representation of connected environments.
Carpenter, Francis; Manson, Daniel; Jeffery, Kate; Burgess, Neil; Barry, Caswell
2015-05-04
The firing patterns of grid cells in medial entorhinal cortex (mEC) and associated brain areas form triangular arrays that tessellate the environment [1, 2] and maintain constant spatial offsets to each other between environments [3, 4]. These cells are thought to provide an efficient metric for navigation in large-scale space [5-8]. However, an accurate and universal metric requires grid cell firing patterns to uniformly cover the space to be navigated, in contrast to recent demonstrations that environmental features such as boundaries can distort [9-11] and fragment [12] grid patterns. To establish whether grid firing is determined by local environmental cues, or provides a coherent global representation, we recorded mEC grid cells in rats foraging in an environment containing two perceptually identical compartments connected via a corridor. During initial exposures to the multicompartment environment, grid firing patterns were dominated by local environmental cues, replicating between the two compartments. However, with prolonged experience, grid cell firing patterns formed a single, continuous representation that spanned both compartments. Thus, we provide the first evidence that in a complex environment, grid cell firing can form the coherent global pattern necessary for them to act as a metric capable of supporting large-scale spatial navigation. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.
Grid Cells Form a Global Representation of Connected Environments
Carpenter, Francis; Manson, Daniel; Jeffery, Kate; Burgess, Neil; Barry, Caswell
2015-01-01
Summary The firing patterns of grid cells in medial entorhinal cortex (mEC) and associated brain areas form triangular arrays that tessellate the environment [1, 2] and maintain constant spatial offsets to each other between environments [3, 4]. These cells are thought to provide an efficient metric for navigation in large-scale space [5–8]. However, an accurate and universal metric requires grid cell firing patterns to uniformly cover the space to be navigated, in contrast to recent demonstrations that environmental features such as boundaries can distort [9–11] and fragment [12] grid patterns. To establish whether grid firing is determined by local environmental cues, or provides a coherent global representation, we recorded mEC grid cells in rats foraging in an environment containing two perceptually identical compartments connected via a corridor. During initial exposures to the multicompartment environment, grid firing patterns were dominated by local environmental cues, replicating between the two compartments. However, with prolonged experience, grid cell firing patterns formed a single, continuous representation that spanned both compartments. Thus, we provide the first evidence that in a complex environment, grid cell firing can form the coherent global pattern necessary for them to act as a metric capable of supporting large-scale spatial navigation. PMID:25913404
Data fusion of multi-scale representations for structural damage detection
NASA Astrophysics Data System (ADS)
Guo, Tian; Xu, Zili
2018-01-01
Despite extensive researches into structural health monitoring (SHM) in the past decades, there are few methods that can detect multiple slight damage in noisy environments. Here, we introduce a new hybrid method that utilizes multi-scale space theory and data fusion approach for multiple damage detection in beams and plates. A cascade filtering approach provides multi-scale space for noisy mode shapes and filters the fluctuations caused by measurement noise. In multi-scale space, a series of amplification and data fusion algorithms are utilized to search the damage features across all possible scales. We verify the effectiveness of the method by numerical simulation using damaged beams and plates with various types of boundary conditions. Monte Carlo simulations are conducted to illustrate the effectiveness and noise immunity of the proposed method. The applicability is further validated via laboratory cases studies focusing on different damage scenarios. Both results demonstrate that the proposed method has a superior noise tolerant ability, as well as damage sensitivity, without knowing material properties or boundary conditions.
Space and Place: Recognizing Ties that Bind.
ERIC Educational Resources Information Center
Whiteford, Gary T.
1980-01-01
Suggests methods to test whether students have acquired a sense of place or spatial understanding. Knowledge of the concepts of map representation, the region, man/land notations, spatial relations, location, and scale are vital to geographic understanding. Concludes that geographic ideas should relate to particular maps. (Author/KC)
Design of chemical space networks on the basis of Tversky similarity
NASA Astrophysics Data System (ADS)
Wu, Mengjun; Vogt, Martin; Maggiora, Gerald M.; Bajorath, Jürgen
2016-01-01
Chemical space networks (CSNs) have been introduced as a coordinate-free representation of chemical space. In CSNs, nodes represent compounds and edges pairwise similarity relationships. These network representations are mostly used to navigate sections of biologically relevant chemical space. Different types of CSNs have been designed on the basis of alternative similarity measures including continuous numerical similarity values or substructure-based similarity criteria. CSNs can be characterized and compared on the basis of statistical concepts from network science. Herein, a new CSN design is introduced that is based upon asymmetric similarity assessment using the Tversky coefficient and termed TV-CSN. Compared to other CSNs, TV-CSNs have unique features. While CSNs typically contain separate compound communities and exhibit small world character, many TV-CSNs are also scale-free in nature and contain hubs, i.e., extensively connected central compounds. Compared to other CSNs, these hubs are a characteristic of TV-CSN topology. Hub-containing compound communities are of particular interest for the exploration of structure-activity relationships.
Log-polar mapping-based scale space tracking with adaptive target response
NASA Astrophysics Data System (ADS)
Li, Dongdong; Wen, Gongjian; Kuai, Yangliu; Zhang, Ximing
2017-05-01
Correlation filter-based tracking has exhibited impressive robustness and accuracy in recent years. Standard correlation filter-based trackers are restricted to translation estimation and equipped with fixed target response. These trackers produce an inferior performance when encountered with a significant scale variation or appearance change. We propose a log-polar mapping-based scale space tracker with an adaptive target response. This tracker transforms the scale variation of the target in the Cartesian space into a shift along the logarithmic axis in the log-polar space. A one-dimensional scale correlation filter is learned online to estimate the shift along the logarithmic axis. With the log-polar representation, scale estimation is achieved accurately without a multiresolution pyramid. To achieve an adaptive target response, a variance of the Gaussian function is computed from the response map and updated online with a learning rate parameter. Our log-polar mapping-based scale correlation filter and adaptive target response can be combined with any correlation filter-based trackers. In addition, the scale correlation filter can be extended to a two-dimensional correlation filter to achieve joint estimation of the scale variation and in-plane rotation. Experiments performed on an OTB50 benchmark demonstrate that our tracker achieves superior performance against state-of-the-art trackers.
Do Monkeys Think in Metaphors? Representations of Space and Time in Monkeys and Humans
ERIC Educational Resources Information Center
Merritt, Dustin J.; Casasanto, Daniel; Brannon, Elizabeth M.
2010-01-01
Research on the relationship between the representation of space and time has produced two contrasting proposals. ATOM posits that space and time are represented via a common magnitude system, suggesting a symmetrical relationship between space and time. According to metaphor theory, however, representations of time depend on representations of…
NASA Technical Reports Server (NTRS)
Klumpar, D. M. (Principal Investigator)
1981-01-01
Progress is reported in reading MAGSAT tapes in modeling procedure developed to compute the magnetic fields at satellite orbit due to current distributions in the ionosphere. The modeling technique utilizes a linear current element representation of the large-scale space-current system.
Insight and search in Katona's five-square problem.
Ollinger, Michael; Jones, Gary; Knoblich, Günther
2014-01-01
Insights are often productive outcomes of human thinking. We provide a cognitive model that explains insight problem solving by the interplay of problem space search and representational change, whereby the problem space is constrained or relaxed based on the problem representation. By introducing different experimental conditions that either constrained the initial search space or helped solvers to initiate a representational change, we investigated the interplay of problem space search and representational change in Katona's five-square problem. Testing 168 participants, we demonstrated that independent hints relating to the initial search space and to representational change had little effect on solution rates. However, providing both hints caused a significant increase in solution rates. Our results show the interplay between problem space search and representational change in insight problem solving: The initial problem space can be so large that people fail to encounter impasse, but even when representational change is achieved the resulting problem space can still provide a major obstacle to finding the solution.
Servidio, S; Chasapis, A; Matthaeus, W H; Perrone, D; Valentini, F; Parashar, T N; Veltri, P; Gershman, D; Russell, C T; Giles, B; Fuselier, S A; Phan, T D; Burch, J
2017-11-17
Plasma turbulence is investigated using unprecedented high-resolution ion velocity distribution measurements by the Magnetospheric Multiscale mission (MMS) in the Earth's magnetosheath. This novel observation of a highly structured particle distribution suggests a cascadelike process in velocity space. Complex velocity space structure is investigated using a three-dimensional Hermite transform, revealing, for the first time in observational data, a power-law distribution of moments. In analogy to hydrodynamics, a Kolmogorov approach leads directly to a range of predictions for this phase-space transport. The scaling theory is found to be in agreement with observations. The combined use of state-of-the-art MMS data sets, novel implementation of a Hermite transform method, and scaling theory of the velocity cascade opens new pathways to the understanding of plasma turbulence and the crucial velocity space features that lead to dissipation in plasmas.
Multi-scale Material Appearance
NASA Astrophysics Data System (ADS)
Wu, Hongzhi
Modeling and rendering the appearance of materials is important for a diverse range of applications of computer graphics - from automobile design to movies and cultural heritage. The appearance of materials varies considerably at different scales, posing significant challenges due to the sheer complexity of the data, as well the need to maintain inter-scale consistency constraints. This thesis presents a series of studies around the modeling, rendering and editing of multi-scale material appearance. To efficiently render material appearance at multiple scales, we develop an object-space precomputed adaptive sampling method, which precomputes a hierarchy of view-independent points that preserve multi-level appearance. To support bi-scale material appearance design, we propose a novel reflectance filtering algorithm, which rapidly computes the large-scale appearance from small-scale details, by exploiting the low-rank structures of Bidirectional Visible Normal Distribution Functions and pre-rotated Bidirectional Reflectance Distribution Functions in the matrix formulation of the rendering algorithm. This approach can guide the physical realization of appearance, as well as the modeling of real-world materials using very sparse measurements. Finally, we present a bi-scale-inspired high-quality general representation for material appearance described by Bidirectional Texture Functions. Our representation is at once compact, easily editable, and amenable to efficient rendering.
An evaluation of space time cube representation of spatiotemporal patterns.
Kristensson, Per Ola; Dahlbäck, Nils; Anundi, Daniel; Björnstad, Marius; Gillberg, Hanna; Haraldsson, Jonas; Mårtensson, Ingrid; Nordvall, Mathias; Ståhl, Josefine
2009-01-01
Space time cube representation is an information visualization technique where spatiotemporal data points are mapped into a cube. Information visualization researchers have previously argued that space time cube representation is beneficial in revealing complex spatiotemporal patterns in a data set to users. The argument is based on the fact that both time and spatial information are displayed simultaneously to users, an effect difficult to achieve in other representations. However, to our knowledge the actual usefulness of space time cube representation in conveying complex spatiotemporal patterns to users has not been empirically validated. To fill this gap, we report on a between-subjects experiment comparing novice users' error rates and response times when answering a set of questions using either space time cube or a baseline 2D representation. For some simple questions, the error rates were lower when using the baseline representation. For complex questions where the participants needed an overall understanding of the spatiotemporal structure of the data set, the space time cube representation resulted in on average twice as fast response times with no difference in error rates compared to the baseline. These results provide an empirical foundation for the hypothesis that space time cube representation benefits users analyzing complex spatiotemporal patterns.
The curious case of large-N expansions on a (pseudo)sphere
DOE Office of Scientific and Technical Information (OSTI.GOV)
Polyakov, Alexander M.; Saleem, Zain H.; Stokes, James
We elucidate the large-N dynamics of one-dimensional sigma models with spherical and hyperbolic target spaces and find a duality between the Lagrange multiplier and the angular momentum. In the hyperbolic model we propose a new class of operators based on the irreducible representations of hyperbolic space. We also uncover unexpected zero modes which lead to the double scaling of the 1/N expansion and explore these modes using Gelfand-Dikiy equations.
The curious case of large-N expansions on a (pseudo)sphere
Polyakov, Alexander M.; Saleem, Zain H.; Stokes, James
2015-02-03
We elucidate the large-N dynamics of one-dimensional sigma models with spherical and hyperbolic target spaces and find a duality between the Lagrange multiplier and the angular momentum. In the hyperbolic model we propose a new class of operators based on the irreducible representations of hyperbolic space. We also uncover unexpected zero modes which lead to the double scaling of the 1/N expansion and explore these modes using Gelfand-Dikiy equations.
Shape in Picture: Mathematical Description of Shape in Grey-Level Images
1992-09-11
representation is scale-space, derived frrr- the linear isotropic diffusion equation; recently other types of equations have been considered. Multiscale...recognition of dimensions in the general case of an arbitrary denominator is similar to that just explained. 3 Linear Inequalities in the Two-Dimensional...solid region containing all pixels of the space, whose coordinates satisfy a linear inequality. A Um C scspt fr Digital Geometry 41 s a a v--’ -0 7 O
NASA Technical Reports Server (NTRS)
Klumpar, D. M. (Principal Investigator)
1982-01-01
The status of the initial testing of the modeling procedure developed to compute the magnetic fields at satellite orbit due to current distributions in the ionosphere and magnetosphere is reported. The modeling technique utilizes a linear current element representation of the large scale space-current system.
ERIC Educational Resources Information Center
Bodzin, Alec M.; Fu, Qiong; Bressler, Denise; Vallera, Farah L.
2015-01-01
Geospatially enabled learning technologies may enhance Earth science learning by placing emphasis on geographic space, visualization, scale, representation, and geospatial thinking and reasoning (GTR) skills. This study examined if and how a series of Web geographic information system investigations that the researchers developed improved urban…
Visual Working Memory Is Independent of the Cortical Spacing Between Memoranda.
Harrison, William J; Bays, Paul M
2018-03-21
The sensory recruitment hypothesis states that visual short-term memory is maintained in the same visual cortical areas that initially encode a stimulus' features. Although it is well established that the distance between features in visual cortex determines their visibility, a limitation known as crowding, it is unknown whether short-term memory is similarly constrained by the cortical spacing of memory items. Here, we investigated whether the cortical spacing between sequentially presented memoranda affects the fidelity of memory in humans (of both sexes). In a first experiment, we varied cortical spacing by taking advantage of the log-scaling of visual cortex with eccentricity, presenting memoranda in peripheral vision sequentially along either the radial or tangential visual axis with respect to the fovea. In a second experiment, we presented memoranda sequentially either within or beyond the critical spacing of visual crowding, a distance within which visual features cannot be perceptually distinguished due to their nearby cortical representations. In both experiments and across multiple measures, we found strong evidence that the ability to maintain visual features in memory is unaffected by cortical spacing. These results indicate that the neural architecture underpinning working memory has properties inconsistent with the known behavior of sensory neurons in visual cortex. Instead, the dissociation between perceptual and memory representations supports a role of higher cortical areas such as posterior parietal or prefrontal regions or may involve an as yet unspecified mechanism in visual cortex in which stimulus features are bound to their temporal order. SIGNIFICANCE STATEMENT Although much is known about the resolution with which we can remember visual objects, the cortical representation of items held in short-term memory remains contentious. A popular hypothesis suggests that memory of visual features is maintained via the recruitment of the same neural architecture in sensory cortex that encodes stimuli. We investigated this claim by manipulating the spacing in visual cortex between sequentially presented memoranda such that some items shared cortical representations more than others while preventing perceptual interference between stimuli. We found clear evidence that short-term memory is independent of the intracortical spacing of memoranda, revealing a dissociation between perceptual and memory representations. Our data indicate that working memory relies on different neural mechanisms from sensory perception. Copyright © 2018 Harrison and Bays.
2018-01-01
Abstract We examined how attention causes neural population representations of shape and location to change in ventral stream (AIT) and dorsal stream (LIP). Monkeys performed two identical delayed-match-to-sample (DMTS) tasks, attending either to shape or location. In AIT, shapes were more discriminable when directing attention to shape rather than location, measured by an increase in mean distance between population response vectors. In LIP, attending to location rather than shape did not increase the discriminability of different stimulus locations. Even when factoring out the change in mean vector response distance, multidimensional scaling (MDS) still showed a significant task difference in AIT, but not LIP, indicating that beyond increasing discriminability, attention also causes a nonlinear warping of representation space in AIT. Despite single-cell attentional modulations in both areas, our data show that attentional modulations of population representations are weaker in LIP, likely due to a need to maintain veridical representations for visuomotor control. PMID:29876521
Neural encoding of large-scale three-dimensional space-properties and constraints.
Jeffery, Kate J; Wilson, Jonathan J; Casali, Giulio; Hayman, Robin M
2015-01-01
How the brain represents represent large-scale, navigable space has been the topic of intensive investigation for several decades, resulting in the discovery that neurons in a complex network of cortical and subcortical brain regions co-operatively encode distance, direction, place, movement etc. using a variety of different sensory inputs. However, such studies have mainly been conducted in simple laboratory settings in which animals explore small, two-dimensional (i.e., flat) arenas. The real world, by contrast, is complex and three dimensional with hills, valleys, tunnels, branches, and-for species that can swim or fly-large volumetric spaces. Adding an additional dimension to space adds coding challenges, a primary reason for which is that several basic geometric properties are different in three dimensions. This article will explore the consequences of these challenges for the establishment of a functional three-dimensional metric map of space, one of which is that the brains of some species might have evolved to reduce the dimensionality of the representational space and thus sidestep some of these problems.
Decorrelation scales for Arctic Ocean hydrography - Part I: Amerasian Basin
NASA Astrophysics Data System (ADS)
Sumata, Hiroshi; Kauker, Frank; Karcher, Michael; Rabe, Benjamin; Timmermans, Mary-Louise; Behrendt, Axel; Gerdes, Rüdiger; Schauer, Ursula; Shimada, Koji; Cho, Kyoung-Ho; Kikuchi, Takashi
2018-03-01
Any use of observational data for data assimilation requires adequate information of their representativeness in space and time. This is particularly important for sparse, non-synoptic data, which comprise the bulk of oceanic in situ observations in the Arctic. To quantify spatial and temporal scales of temperature and salinity variations, we estimate the autocorrelation function and associated decorrelation scales for the Amerasian Basin of the Arctic Ocean. For this purpose, we compile historical measurements from 1980 to 2015. Assuming spatial and temporal homogeneity of the decorrelation scale in the basin interior (abyssal plain area), we calculate autocorrelations as a function of spatial distance and temporal lag. The examination of the functional form of autocorrelation in each depth range reveals that the autocorrelation is well described by a Gaussian function in space and time. We derive decorrelation scales of 150-200 km in space and 100-300 days in time. These scales are directly applicable to quantify the representation error, which is essential for use of ocean in situ measurements in data assimilation. We also describe how the estimated autocorrelation function and decorrelation scale should be applied for cost function calculation in a data assimilation system.
Multiscale vector fields for image pattern recognition
NASA Technical Reports Server (NTRS)
Low, Kah-Chan; Coggins, James M.
1990-01-01
A uniform processing framework for low-level vision computing in which a bank of spatial filters maps the image intensity structure at each pixel into an abstract feature space is proposed. Some properties of the filters and the feature space are described. Local orientation is measured by a vector sum in the feature space as follows: each filter's preferred orientation along with the strength of the filter's output determine the orientation and the length of a vector in the feature space; the vectors for all filters are summed to yield a resultant vector for a particular pixel and scale. The orientation of the resultant vector indicates the local orientation, and the magnitude of the vector indicates the strength of the local orientation preference. Limitations of the vector sum method are discussed. Investigations show that the processing framework provides a useful, redundant representation of image structure across orientation and scale.
Scaling a Convection-Resolving RCM to Near-Global Scales
NASA Astrophysics Data System (ADS)
Leutwyler, D.; Fuhrer, O.; Chadha, T.; Kwasniewski, G.; Hoefler, T.; Lapillonne, X.; Lüthi, D.; Osuna, C.; Schar, C.; Schulthess, T. C.; Vogt, H.
2017-12-01
In the recent years, first decade-long kilometer-scale resolution RCM simulations have been performed on continental-scale computational domains. However, the size of the planet Earth is still an order of magnitude larger and thus the computational implications of performing global climate simulations at this resolution are challenging. We explore the gap between the currently established RCM simulations and global simulations by scaling the GPU accelerated version of the COSMO model to a near-global computational domain. To this end, the evolution of an idealized moist baroclinic wave has been simulated over the course of 10 days with a grid spacing of up to 930 m. The computational mesh employs 36'000 x 16'001 x 60 grid points and covers 98.4% of the planet's surface. The code shows perfect weak scaling up to 4'888 Nodes of the Piz Daint supercomputer and yields 0.043 simulated years per day (SYPD) which is approximately one seventh of the 0.2-0.3 SYPD required to conduct AMIP-type simulations. However, at half the resolution (1.9 km) we've observed 0.23 SYPD. Besides formation of frontal precipitating systems containing embedded explicitly-resolved convective motions, the simulations reveal a secondary instability that leads to cut-off warm-core cyclonic vortices in the cyclone's core, once the grid spacing is refined to the kilometer scale. The explicit representation of embedded moist convection and the representation of the previously unresolved instabilities exhibit a physically different behavior in comparison to coarser-resolution simulations. The study demonstrates that global climate simulations using kilometer-scale resolution are imminent and serves as a baseline benchmark for global climate model applications and future exascale supercomputing systems.
Generative Representations for Automated Design of Robots
NASA Technical Reports Server (NTRS)
Homby, Gregory S.; Lipson, Hod; Pollack, Jordan B.
2007-01-01
A method of automated design of complex, modular robots involves an evolutionary process in which generative representations of designs are used. The term generative representations as used here signifies, loosely, representations that consist of or include algorithms, computer programs, and the like, wherein encoded designs can reuse elements of their encoding and thereby evolve toward greater complexity. Automated design of robots through synthetic evolutionary processes has already been demonstrated, but it is not clear whether genetically inspired search algorithms can yield designs that are sufficiently complex for practical engineering. The ultimate success of such algorithms as tools for automation of design depends on the scaling properties of representations of designs. A nongenerative representation (one in which each element of the encoded design is used at most once in translating to the design) scales linearly with the number of elements. Search algorithms that use nongenerative representations quickly become intractable (search times vary approximately exponentially with numbers of design elements), and thus are not amenable to scaling to complex designs. Generative representations are compact representations and were devised as means to circumvent the above-mentioned fundamental restriction on scalability. In the present method, a robot is defined by a compact programmatic form (its generative representation) and the evolutionary variation takes place on this form. The evolutionary process is an iterative one, wherein each cycle consists of the following steps: 1. Generative representations are generated in an evolutionary subprocess. 2. Each generative representation is a program that, when compiled, produces an assembly procedure. 3. In a computational simulation, a constructor executes an assembly procedure to generate a robot. 4. A physical-simulation program tests the performance of a simulated constructed robot, evaluating the performance according to a fitness criterion to yield a figure of merit that is fed back into the evolutionary subprocess of the next iteration. In comparison with prior approaches to automated evolutionary design of robots, the use of generative representations offers two advantages: First, a generative representation enables the reuse of components in regular and hierarchical ways and thereby serves a systematic means of creating more complex modules out of simpler ones. Second, the evolved generative representation may capture intrinsic properties of the design problem, so that variations in the representations move through the design space more effectively than do equivalent variations in a nongenerative representation. This method has been demonstrated by using it to design some robots that move, variously, by walking, rolling, or sliding. Some of the robots were built (see figure). Although these robots are very simple, in comparison with robots designed by humans, their structures are more regular, modular, hierarchical, and complex than are those of evolved designs of comparable functionality synthesized by use of nongenerative representations.
A Decade-long Continental-Scale Convection-Resolving Climate Simulation on GPUs
NASA Astrophysics Data System (ADS)
Leutwyler, David; Fuhrer, Oliver; Lapillonne, Xavier; Lüthi, Daniel; Schär, Christoph
2016-04-01
The representation of moist convection in climate models represents a major challenge, due to the small scales involved. Convection-resolving models have proven to be very useful tools in numerical weather prediction and in climate research. Using horizontal grid spacings of O(1km), they allow to explicitly resolve deep convection leading to an improved representation of the water cycle. However, due to their extremely demanding computational requirements, they have so far been limited to short simulations and/or small computational domains. Innovations in the supercomputing domain have led to new supercomputer-designs that involve conventional multicore CPUs and accelerators such as graphics processing units (GPUs). One of the first atmospheric models that has been fully ported to GPUs is the Consortium for Small-Scale Modeling weather and climate model COSMO. This new version allows us to expand the size of the simulation domain to areas spanning continents and the time period up to one decade. We present results from a decade-long, convection-resolving climate simulation using the GPU-enabled COSMO version. The simulation is driven by the ERA-interim reanalysis. The results illustrate how the approach allows for the representation of interactions between synoptic-scale and meso-scale atmospheric circulations at scales ranging from 1000 to 10 km. We discuss the performance of the convection-resolving modeling approach on the European scale. Specifically we focus on the annual cycle of convection in Europe, on the organization of convective clouds and on the verification of hourly rainfall with various high resolution datasets.
The organization of conspecific face space in nonhuman primates
Parr, Lisa A.; Taubert, Jessica; Little, Anthony C.; Hancock, Peter J. B.
2013-01-01
Humans and chimpanzees demonstrate numerous cognitive specializations for processing faces, but comparative studies with monkeys suggest that these may be the result of recent evolutionary adaptations. The present study utilized the novel approach of face space, a powerful theoretical framework used to understand the representation of face identity in humans, to further explore species differences in face processing. According to the theory, faces are represented by vectors in a multidimensional space, the centre of which is defined by an average face. Each dimension codes features important for describing a face’s identity, and vector length codes the feature’s distinctiveness. Chimpanzees and rhesus monkeys discriminated male and female conspecifics’ faces, rated by humans for their distinctiveness, using a computerized task. Multidimensional scaling analyses showed that the organization of face space was similar between humans and chimpanzees. Distinctive faces had the longest vectors and were the easiest for chimpanzees to discriminate. In contrast, distinctiveness did not correlate with the performance of rhesus monkeys. The feature dimensions for each species’ face space were visualized and described using morphing techniques. These results confirm species differences in the perceptual representation of conspecific faces, which are discussed within an evolutionary framework. PMID:22670823
Recollection-Dependent Memory for Event Duration in Large-Scale Spatial Navigation
ERIC Educational Resources Information Center
Brunec, Iva K.; Ozubko, Jason D.; Barense, Morgan D.; Moscovitch, Morris
2017-01-01
Time and space represent two key aspects of episodic memories, forming the spatiotemporal context of events in a sequence. Little is known, however, about how temporal information, such as the duration and the order of particular events, are encoded into memory, and if it matters whether the memory representation is based on recollection or…
Scaling and efficiency of PRISM in adaptive simulations of turbulent premixed flames
DOE Office of Scientific and Technical Information (OSTI.GOV)
Tonse, Shaheen R.; Bell, J.B.; Brown, N.J.
1999-12-01
The dominant computational cost in modeling turbulent combustion phenomena numerically with high fidelity chemical mechanisms is the time required to solve the ordinary differential equations associated with chemical kinetics. One approach to reducing that computational cost is to develop an inexpensive surrogate model that accurately represents evolution of chemical kinetics. One such approach, PRISM, develops a polynomial representation of the chemistry evolution in a local region of chemical composition space. This representation is then stored for later use. As the computation proceeds, the chemistry evolution for other points within the same region are computed by evaluating these polynomials instead ofmore » calling an ordinary differential equation solver. If initial data for advancing the chemistry is encountered that is not in any region for which a polynomial is defined, the methodology dynamically samples that region and constructs a new representation for that region. The utility of this approach is determined by the size of the regions over which the representation provides a good approximation to the kinetics and the number of these regions that are necessary to model the subset of composition space that is active during a simulation. In this paper, we assess the PRISM methodology in the context of a turbulent premixed flame in two dimensions. We consider a range of turbulent intensities ranging from weak turbulence that has little effect on the flame to strong turbulence that tears pockets of burning fluid from the main flame. For each case, we explore a range of sizes for the local regions and determine the scaling behavior as a function of region size and turbulent intensity.« less
THEORETICAL REVIEW The Hippocampus, Time, and Memory Across Scales
Howard, Marc W.; Eichenbaum, Howard
2014-01-01
A wealth of experimental studies with animals have offered insights about how neural networks within the hippocampus support the temporal organization of memories. These studies have revealed the existence of “time cells” that encode moments in time, much as the well-known “place cells” map locations in space. Another line of work inspired by human behavioral studies suggests that episodic memories are mediated by a state of temporal context that changes gradually over long time scales, up to at least a few thousand seconds. In this view, the “mental time travel” hypothesized to support the experience of episodic memory corresponds to a “jump back in time” in which a previous state of temporal context is recovered. We suggest that these 2 sets of findings could be different facets of a representation of temporal history that maintains a record at the last few thousand seconds of experience. The ability to represent long time scales comes at the cost of discarding precise information about when a stimulus was experienced—this uncertainty becomes greater for events further in the past. We review recent computational work that describes a mechanism that could construct such a scale-invariant representation. Taken as a whole, this suggests the hippocampus plays its role in multiple aspects of cognition by representing events embedded in a general spatiotemporal context. The representation of internal time can be useful across nonhippocampal memory systems. PMID:23915126
Precision of working memory for speech sounds.
Joseph, Sabine; Iverson, Paul; Manohar, Sanjay; Fox, Zoe; Scott, Sophie K; Husain, Masud
2015-01-01
Memory for speech sounds is a key component of models of verbal working memory (WM). But how good is verbal WM? Most investigations assess this using binary report measures to derive a fixed number of items that can be stored. However, recent findings in visual WM have challenged such "quantized" views by employing measures of recall precision with an analogue response scale. WM for speech sounds might rely on both continuous and categorical storage mechanisms. Using a novel speech matching paradigm, we measured WM recall precision for phonemes. Vowel qualities were sampled from a formant space continuum. A probe vowel had to be adjusted to match the vowel quality of a target on a continuous, analogue response scale. Crucially, this provided an index of the variability of a memory representation around its true value and thus allowed us to estimate how memories were distorted from the original sounds. Memory load affected the quality of speech sound recall in two ways. First, there was a gradual decline in recall precision with increasing number of items, consistent with the view that WM representations of speech sounds become noisier with an increase in the number of items held in memory, just as for vision. Based on multidimensional scaling (MDS), the level of noise appeared to be reflected in distortions of the formant space. Second, as memory load increased, there was evidence of greater clustering of participants' responses around particular vowels. A mixture model captured both continuous and categorical responses, demonstrating a shift from continuous to categorical memory with increasing WM load. This suggests that direct acoustic storage can be used for single items, but when more items must be stored, categorical representations must be used.
Qiao, Yu; Wang, Wei; Minematsu, Nobuaki; Liu, Jianzhuang; Takeda, Mitsuo; Tang, Xiaoou
2009-10-01
This paper studies phase singularities (PSs) for image representation. We show that PSs calculated with Laguerre-Gauss filters contain important information and provide a useful tool for image analysis. PSs are invariant to image translation and rotation. We introduce several invariant features to characterize the core structures around PSs and analyze the stability of PSs to noise addition and scale change. We also study the characteristics of PSs in a scale space, which lead to a method to select key scales along phase singularity curves. We demonstrate two applications of PSs: object tracking and image matching. In object tracking, we use the iterative closest point algorithm to determine the correspondences of PSs between two adjacent frames. The use of PSs allows us to precisely determine the motions of tracked objects. In image matching, we combine PSs and scale-invariant feature transform (SIFT) descriptor to deal with the variations between two images and examine the proposed method on a benchmark database. The results indicate that our method can find more correct matching pairs with higher repeatability rates than some well-known methods.
Multiple Scales of Representation along the Hippocampal Anteroposterior Axis in Humans.
Brunec, Iva K; Bellana, Buddhika; Ozubko, Jason D; Man, Vincent; Robin, Jessica; Liu, Zhong-Xu; Grady, Cheryl; Rosenbaum, R Shayna; Winocur, Gordon; Barense, Morgan D; Moscovitch, Morris
2018-06-13
The ability to represent the world accurately relies on simultaneous coarse and fine-grained neural information coding, capturing both gist and detail of an experience. The longitudinal axis of the hippocampus may provide a gradient of representational granularity in spatial and episodic memory in rodents and humans [1-8]. Rodent place cells in the ventral hippocampus exhibit significantly larger place fields and greater autocorrelation than those in the dorsal hippocampus [1, 9-11], which may underlie a coarser and slower changing representation of space [10, 12]. Recent evidence suggests that properties of cellular dynamics in rodents can be captured with fMRI in humans during spatial navigation [13] and conceptual learning [14]. Similarly, mechanisms supporting granularity along the long axis may also be extrapolated to the scale of fMRI signal. Here, we provide the first evidence for separable scales of representation along the human hippocampal anteroposterior axis during navigation and rest by showing (1) greater similarity among voxel time courses and (2) higher temporal autocorrelation in anterior hippocampus (aHPC), relative to posterior hippocampus (pHPC), the human homologs of ventral and dorsal rodent hippocampus. aHPC voxels exhibited more similar activity at each time point and slower signal change over time than voxels in pHPC, consistent with place field organization in rodents. Importantly, similarity between voxels was related to navigational strategy and episodic memory. These findings provide evidence that the human hippocampus supports an anterior-to-posterior gradient of coarse-to-fine spatiotemporal representations, suggesting the existence of a cross-species mechanism, whereby lower neural similarity supports more complex coding of experience. Copyright © 2018 Elsevier Ltd. All rights reserved.
Sequence analysis by iterated maps, a review.
Almeida, Jonas S
2014-05-01
Among alignment-free methods, Iterated Maps (IMs) are on a particular extreme: they are also scale free (order free). The use of IMs for sequence analysis is also distinct from other alignment-free methodologies in being rooted in statistical mechanics instead of computational linguistics. Both of these roots go back over two decades to the use of fractal geometry in the characterization of phase-space representations. The time series analysis origin of the field is betrayed by the title of the manuscript that started this alignment-free subdomain in 1990, 'Chaos Game Representation'. The clash between the analysis of sequences as continuous series and the better established use of Markovian approaches to discrete series was almost immediate, with a defining critique published in same journal 2 years later. The rest of that decade would go by before the scale-free nature of the IM space was uncovered. The ensuing decade saw this scalability generalized for non-genomic alphabets as well as an interest in its use for graphic representation of biological sequences. Finally, in the past couple of years, in step with the emergence of BigData and MapReduce as a new computational paradigm, there is a surprising third act in the IM story. Multiple reports have described gains in computational efficiency of multiple orders of magnitude over more conventional sequence analysis methodologies. The stage appears to be now set for a recasting of IMs with a central role in processing nextgen sequencing results.
In (or outside of) your neck of the woods: laterality in spatial body representation
Hach, Sylvia; Schütz-Bosbach, Simone
2014-01-01
Beside language, space is to date the most widely recognized lateralized systems. For example, it has been shown that even mental representations of space and the spatial representation of abstract concepts display lateralized characteristics. For the most part, this body of literature describes space as distal or something outside of the observer or actor. What has been strangely absent in the literature on the whole and specifically in the spatial literature until recently is the most proximal space imaginable – the body. In this review, we will summarize three strands of literature showing laterality in body representations. First, evidence of hemispheric asymmetries in body space in health and, second in body space in disease will be examined. Third, studies pointing to differential contributions of the right and left hemisphere to illusory body (space) will be summarized. Together these studies show hemispheric asymmetries to be evident in body representations at the level of simple somatosensory and proprioceptive representations. We propose a novel working hypothesis, whereby neural systems dedicated to processing action-oriented information about one’s own body space may ontogenetically serve as a template for the perception of the external world. PMID:24600421
Alternative transitions between existing representations in multi-scale maps
NASA Astrophysics Data System (ADS)
Dumont, Marion; Touya, Guillaume; Duchêne, Cécile
2018-05-01
Map users may have issues to achieve multi-scale navigation tasks, as cartographic objects may have various representations across scales. We assume that adding intermediate representations could be one way to reduce the differences between existing representations, and to ease the transitions across scales. We consider an existing multiscale map on the scale range from 1 : 25k to 1 : 100k scales. Based on hypotheses about intermediate representations design, we build custom multi-scale maps with alternative transitions. We will conduct in a next future a user evaluation to compare the efficiency of these alternative maps for multi-scale navigation. This paper discusses the hypotheses and production process of these alternative maps.
Linearized self-consistent quasiparticle GW method: Application to semiconductors and simple metals
NASA Astrophysics Data System (ADS)
Kutepov, A. L.; Oudovenko, V. S.; Kotliar, G.
2017-10-01
We present a code implementing the linearized quasiparticle self-consistent GW method (LQSGW) in the LAPW basis. Our approach is based on the linearization of the self-energy around zero frequency which differs it from the existing implementations of the QSGW method. The linearization allows us to use Matsubara frequencies instead of working on the real axis. This results in efficiency gains by switching to the imaginary time representation in the same way as in the space time method. The all electron LAPW basis set eliminates the need for pseudopotentials. We discuss the advantages of our approach, such as its N3 scaling with the system size N, as well as its shortcomings. We apply our approach to study the electronic properties of selected semiconductors, insulators, and simple metals and show that our code produces the results very close to the previously published QSGW data. Our implementation is a good platform for further many body diagrammatic resummations such as the vertex-corrected GW approach and the GW+DMFT method. Program Files doi:http://dx.doi.org/10.17632/cpchkfty4w.1 Licensing provisions: GNU General Public License Programming language: Fortran 90 External routines/libraries: BLAS, LAPACK, MPI (optional) Nature of problem: Direct implementation of the GW method scales as N4 with the system size, which quickly becomes prohibitively time consuming even in the modern computers. Solution method: We implemented the GW approach using a method that switches between real space and momentum space representations. Some operations are faster in real space, whereas others are more computationally efficient in the reciprocal space. This makes our approach scale as N3. Restrictions: The limiting factor is usually the memory available in a computer. Using 10 GB/core of memory allows us to study the systems up to 15 atoms per unit cell.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Seyedhosseini, Mojtaba; Kumar, Ritwik; Jurrus, Elizabeth R.
2011-10-01
Automated neural circuit reconstruction through electron microscopy (EM) images is a challenging problem. In this paper, we present a novel method that exploits multi-scale contextual information together with Radon-like features (RLF) to learn a series of discriminative models. The main idea is to build a framework which is capable of extracting information about cell membranes from a large contextual area of an EM image in a computationally efficient way. Toward this goal, we extract RLF that can be computed efficiently from the input image and generate a scale-space representation of the context images that are obtained at the output ofmore » each discriminative model in the series. Compared to a single-scale model, the use of a multi-scale representation of the context image gives the subsequent classifiers access to a larger contextual area in an effective way. Our strategy is general and independent of the classifier and has the potential to be used in any context based framework. We demonstrate that our method outperforms the state-of-the-art algorithms in detection of neuron membranes in EM images.« less
NASA Technical Reports Server (NTRS)
Mennell, R. C.
1973-01-01
Experimental aerodynamic investigations were conducted in a low speed wind tunnel on an 0.0405 scale representation of the 89A light weight Space Shuttle Orbiter to obtain pressure loads data in the presence of the ground for orbiter structural strength analysis. The model and the facility are described, and data reduction is outlined. Tables are included for data set/run number collation, data set/component collation, model component description, and pressure tap locations by series number. Tabulated force and pressure source data are presented.
Zambrano, Eduardo; Šulc, Miroslav; Vaníček, Jiří
2013-08-07
Time-resolved electronic spectra can be obtained as the Fourier transform of a special type of time correlation function known as fidelity amplitude, which, in turn, can be evaluated approximately and efficiently with the dephasing representation. Here we improve both the accuracy of this approximation-with an amplitude correction derived from the phase-space propagator-and its efficiency-with an improved cellular scheme employing inverse Weierstrass transform and optimal scaling of the cell size. We demonstrate the advantages of the new methodology by computing dispersed time-resolved stimulated emission spectra in the harmonic potential, pyrazine, and the NCO molecule. In contrast, we show that in strongly chaotic systems such as the quartic oscillator the original dephasing representation is more appropriate than either the cellular or prefactor-corrected methods.
A Scalable Approach to Probabilistic Latent Space Inference of Large-Scale Networks
Yin, Junming; Ho, Qirong; Xing, Eric P.
2014-01-01
We propose a scalable approach for making inference about latent spaces of large networks. With a succinct representation of networks as a bag of triangular motifs, a parsimonious statistical model, and an efficient stochastic variational inference algorithm, we are able to analyze real networks with over a million vertices and hundreds of latent roles on a single machine in a matter of hours, a setting that is out of reach for many existing methods. When compared to the state-of-the-art probabilistic approaches, our method is several orders of magnitude faster, with competitive or improved accuracy for latent space recovery and link prediction. PMID:25400487
NASA Technical Reports Server (NTRS)
Houlihan, S. R.
1975-01-01
Experimental aerodynamic investigations were conducted on a dual-strut mounted 0.0405-scale representation of the 140A/B outer mold line space shuttle orbiter vehicle. The tests, conducted from 11 Oct., 1974 through 22 Oct., 1974, were primarily to investigate aerodynamic stability and control characteristics of the space shuttle orbiter ferry configuration. Four afterbody fairing configurations and various additions to them in the form of horizontal and ventral fins strakes and other aerodynamic protuberances were tested. Base line data on the basic orbiter with MPS nozzles and bodyflap were recorded. The drag of the optimum ferry configuration was increased to the level of the basic orbiter for possible flight test configurations by the addition of two sizes of perforated speed brakes on the tail cone surface.
NASTRAN analysis of the 1/8-scale space shuttle dynamic model
NASA Technical Reports Server (NTRS)
Bernstein, M.; Mason, P. W.; Zalesak, J.; Gregory, D. J.; Levy, A.
1973-01-01
The space shuttle configuration has more complex structural dynamic characteristics than previous launch vehicles primarily because of the high model density at low frequencies and the high degree of coupling between the lateral and longitudinal motions. An accurate analytical representation of these characteristics is a primary means for treating structural dynamics problems during the design phase of the shuttle program. The 1/8-scale model program was developed to explore the adequacy of available analytical modeling technology and to provide the means for investigating problems which are more readily treated experimentally. The basic objectives of the 1/8-scale model program are: (1) to provide early verification of analytical modeling procedures on a shuttle-like structure, (2) to demonstrate important vehicle dynamic characteristics of a typical shuttle design, (3) to disclose any previously unanticipated structural dynamic characteristics, and (4) to provide for development and demonstration of cost effective prototype testing procedures.
A Generalized Simple Formulation of Convective Adjustment ...
Convective adjustment timescale (τ) for cumulus clouds is one of the most influential parameters controlling parameterized convective precipitation in climate and weather simulation models at global and regional scales. Due to the complex nature of deep convection, a prescribed value or ad hoc representation of τ is used in most global and regional climate/weather models making it a tunable parameter and yet still resulting in uncertainties in convective precipitation simulations. In this work, a generalized simple formulation of τ for use in any convection parameterization for shallow and deep clouds is developed to reduce convective precipitation biases at different grid spacing. Unlike existing other methods, our new formulation can be used with field campaign measurements to estimate τ as demonstrated by using data from two different special field campaigns. Then, we implemented our formulation into a regional model (WRF) for testing and evaluation. Results indicate that our simple τ formulation can give realistic temporal and spatial variations of τ across continental U.S. as well as grid-scale and subgrid scale precipitation. We also found that as the grid spacing decreases (e.g., from 36 to 4-km grid spacing), grid-scale precipitation dominants over subgrid-scale precipitation. The generalized τ formulation works for various types of atmospheric conditions (e.g., continental clouds due to heating and large-scale forcing over la
From phase space to integrable representations and level-rank duality
NASA Astrophysics Data System (ADS)
Chattopadhyay, Arghya; Dutta, Parikshit; Dutta, Suvankar
2018-05-01
We explicitly find representations for different large N phases of Chern-Simons matter theory on S 2 × S 1. These representations are characterised by Young diagrams. We show that no-gap and lower-gap phase of Chern-Simons-matter theory correspond to integrable representations of SU( N) k affine Lie algebra, where as upper-cap phase corresponds to integrable representations of SU( k - N) k affine Lie algebra. We use phase space description of [1] to obtain these representations and argue how putting a cap on eigenvalue distribution forces corresponding representations to be integrable. We also prove that the Young diagrams corresponding to lower-gap and upper-cap representations are related to each other by transposition under level-rank duality. Finally we draw phase space droplets for these phases and show how information about eigenvalue and Young diagram descriptions can be captured in topologies of these droplets in a unified way.
ERIC Educational Resources Information Center
Kuhlmeier, Valerie
2005-01-01
Many recent studies have explored young children's ability to use information from physical representations of space to guide search within the real world. In one commonly used procedure, children are asked to find a hidden toy in a room after observing a smaller toy being hidden in the analogous location in a scale model of the room.…
Five challenges for spatial epidemic models
Riley, Steven; Eames, Ken; Isham, Valerie; Mollison, Denis; Trapman, Pieter
2015-01-01
Infectious disease incidence data are increasingly available at the level of the individual and include high-resolution spatial components. Therefore, we are now better able to challenge models that explicitly represent space. Here, we consider five topics within spatial disease dynamics: the construction of network models; characterising threshold behaviour; modelling long-distance interactions; the appropriate scale for interventions; and the representation of population heterogeneity. PMID:25843387
ERIC Educational Resources Information Center
Gazeley, Louise; Dunne, Máiréad
2013-01-01
Exclusion from school is a disciplinary sanction used in English schools to manage behaviour by limiting a young person's attendance at school and the over-representation of Black pupils in national exclusions statistics has been a long-standing cause of concern. This paper reports on the findings of a small-scale, qualitative study that explored…
NASA Astrophysics Data System (ADS)
Carey, C. L.
2011-06-01
The following paper undertakes an iconographic analysis of Robert Rauschenberg's large scale print, Autobiography (1967). The artist's interest in astronomy and astrology, visual metaphors aligning the body with the cosmos, and the cartographic representation of self are discussed. Autobiography is placed in cultural and historical context with other works by the artist, elaborated as a personal narrative-an alternative to traditional self portraiture.
NASA Astrophysics Data System (ADS)
Wang, Xianmin; Li, Bo; Xu, Qizhi
2016-07-01
The anisotropic scale space (ASS) is often used to enhance the performance of a scale-invariant feature transform (SIFT) algorithm in the registration of synthetic aperture radar (SAR) images. The existing ASS-based methods usually suffer from unstable keypoints and false matches, since the anisotropic diffusion filtering has limitations in reducing the speckle noise from SAR images while building the ASS image representation. We proposed a speckle reducing SIFT match method to obtain stable keypoints and acquire precise matches for the SAR image registration. First, the keypoints are detected in a speckle reducing anisotropic scale space constructed by the speckle reducing anisotropic diffusion, so that speckle noise is greatly reduced and prominent structures of the images are preserved, consequently the stable keypoints can be derived. Next, the probabilistic relaxation labeling approach is employed to establish the matches of the keypoints then the correct match rate of the keypoints is significantly increased. Experiments conducted on simulated speckled images and real SAR images demonstrate the effectiveness of the proposed method.
Properties of heuristic search strategies
NASA Technical Reports Server (NTRS)
Vanderbrug, G. J.
1973-01-01
A directed graph is used to model the search space of a state space representation with single input operators, an AND/OR is used for problem reduction representations, and a theorem proving graph is used for state space representations with multiple input operators. These three graph models and heuristic strategies for searching them are surveyed. The completeness, admissibility, and optimality properties of search strategies which use the evaluation function f = (1 - omega)g = omega(h) are presented and interpreted using a representation of the search process in the plane. The use of multiple output operators to imply dependent successors, and thus obtain a formalism which includes all three types of representations, is discussed.
Space-time modeling of soil moisture
NASA Astrophysics Data System (ADS)
Chen, Zijuan; Mohanty, Binayak P.; Rodriguez-Iturbe, Ignacio
2017-11-01
A physically derived space-time mathematical representation of the soil moisture field is carried out via the soil moisture balance equation driven by stochastic rainfall forcing. The model incorporates spatial diffusion and in its original version, it is shown to be unable to reproduce the relative fast decay in the spatial correlation functions observed in empirical data. This decay resulting from variations in local topography as well as in local soil and vegetation conditions is well reproduced via a jitter process acting multiplicatively over the space-time soil moisture field. The jitter is a multiplicative noise acting on the soil moisture dynamics with the objective to deflate its correlation structure at small spatial scales which are not embedded in the probabilistic structure of the rainfall process that drives the dynamics. These scales of order of several meters to several hundred meters are of great importance in ecohydrologic dynamics. Properties of space-time correlation functions and spectral densities of the model with jitter are explored analytically, and the influence of the jitter parameters, reflecting variabilities of soil moisture at different spatial and temporal scales, is investigated. A case study fitting the derived model to a soil moisture dataset is presented in detail.
NASA Astrophysics Data System (ADS)
Pesaresi, Martino; Ouzounis, Georgios K.; Gueguen, Lionel
2012-06-01
A new compact representation of dierential morphological prole (DMP) vector elds is presented. It is referred to as the CSL model and is conceived to radically reduce the dimensionality of the DMP descriptors. The model maps three characteristic parameters, namely scale, saliency and level, into the RGB space through a HSV transform. The result is a a medium abstraction semantic layer used for visual exploration, image information mining and pattern classication. Fused with the PANTEX built-up presence index, the CSL model converges to an approximate building footprint representation layer in which color represents building class labels. This process is demonstrated on the rst high resolution (HR) global human settlement layer (GHSL) computed from multi-modal HR and VHR satellite images. Results of the rst massive processing exercise involving several thousands of scenes around the globe are reported along with validation gures.
On the mapping associated with the complex representation of functions and processes.
NASA Technical Reports Server (NTRS)
Harger, R. O.
1972-01-01
The mapping between function spaces that is implied by the representation of a real 'bandpass' function by a complex 'low-pass' function is explicitly accepted. The discussion is extended to the representation of stationary random processes where the mapping is between spaces of random processes. This approach clarifies the nature of the complex representation, especially in the case of random processes and, in addition, derives the properties of the complex representation.-
NASA Technical Reports Server (NTRS)
Mellenthin, J. A.; Cleary, J. W.; Nichols, M. E.; Milam, M. D.
1974-01-01
The results of a wind tunnel test to determine the force, moment, and hinge-moment characteristics of the Configuration 2A Space Shuttle Vehicle Orbiter at Mach numbers 5, 7 and 10 are presented. The model was an 0.015-scale representation of the Orbiter Configuration 2A used in test 0A11A and later tests. Six-component aerodynamic force and moment data were recorded from a 1.50-inch internal strain-gage balance, and base pressures were taken for axial and drag force corrections. Hinge-moment data were obtained for the rudder and the inboard and outboard elevon panels of the starboard wing.
Classical Wave Model of Quantum-Like Processing in Brain
NASA Astrophysics Data System (ADS)
Khrennikov, A.
2011-01-01
We discuss the conjecture on quantum-like (QL) processing of information in the brain. It is not based on the physical quantum brain (e.g., Penrose) - quantum physical carriers of information. In our approach the brain created the QL representation (QLR) of information in Hilbert space. It uses quantum information rules in decision making. The existence of such QLR was (at least preliminary) confirmed by experimental data from cognitive psychology. The violation of the law of total probability in these experiments is an important sign of nonclassicality of data. In so called "constructive wave function approach" such data can be represented by complex amplitudes. We presented 1,2 the QL model of decision making. In this paper we speculate on a possible physical realization of QLR in the brain: a classical wave model producing QLR . It is based on variety of time scales in the brain. Each pair of scales (fine - the background fluctuations of electromagnetic field and rough - the cognitive image scale) induces the QL representation. The background field plays the crucial role in creation of "superstrong QL correlations" in the brain.
Singlet particles as cold dark matter in a noncommutative space-time
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ettefaghi, M. M.
2009-03-15
We extend the noncommutative (NC) standard model to incorporate singlet particles as cold dark matter. In the NC space-time, the singlet particles can be coupled to the U(1) gauge field in the adjoint representation. We study the relic density of the singlet particles due to the NC induced interaction. Demanding either the singlet fermion or the singlet scalar to serve as cold dark matter and the NC induced interactions to be relevant to the dark matter production, we obtain the corresponding relations between the NC scale and the dark matter masses, which are consistent with some existing bounds.
Vertex Space Analysis for Model-Based Target Recognition.
1996-08-01
performed in our unique invariant representation, Vertex Space, that reduces both the dimensionality and size of the required search space. Vertex Space ... mapping results in a reduced representation that serves as a characteristic target signature which is invariant to four of the six viewing geometry
Representations of body and space: theoretical concepts and controversies.
Trojan, Jörg
2015-09-01
Recent years have seen a revived interest in how body and space are represented perceptually and how they affect human cognition and behaviour. Various conceptualisations of body and space have been proposed, alternately stressing neurophysiological, cognitive, or social aspects, but unified approaches are scarce. This short paper will give an overview of different views on body and space. At least three relevant dimensions can be identified in which concepts of body and space may differ: (1) perspective: while we conceptually differentiate between body and space perception, they imply each other and the underlying mechanisms overlap. (2) Level: representations of body and space may emerge at different processing levels, from spinal mechanisms guiding reflex movements to those we construct in our imagination. (3) Affect: representations of body and space are closely linked to affect, but this relationship has not received enough attention yet. Despite many empirical findings, our current views on body and space representations remain ambiguous. One problem may lie in the implicit diversity of "bodies" and "spaces" examined in different studies. Specifications of these concepts may help understand existing results better and are important for guiding future research.
A scale-invariant internal representation of time.
Shankar, Karthik H; Howard, Marc W
2012-01-01
We propose a principled way to construct an internal representation of the temporal stimulus history leading up to the present moment. A set of leaky integrators performs a Laplace transform on the stimulus function, and a linear operator approximates the inversion of the Laplace transform. The result is a representation of stimulus history that retains information about the temporal sequence of stimuli. This procedure naturally represents more recent stimuli more accurately than less recent stimuli; the decrement in accuracy is precisely scale invariant. This procedure also yields time cells that fire at specific latencies following the stimulus with a scale-invariant temporal spread. Combined with a simple associative memory, this representation gives rise to a moment-to-moment prediction that is also scale invariant in time. We propose that this scale-invariant representation of temporal stimulus history could serve as an underlying representation accessible to higher-level behavioral and cognitive mechanisms. In order to illustrate the potential utility of this scale-invariant representation in a variety of fields, we sketch applications using minimal performance functions to problems in classical conditioning, interval timing, scale-invariant learning in autoshaping, and the persistence of the recency effect in episodic memory across timescales.
Interactive Machine Learning at Scale with CHISSL
DOE Office of Scientific and Technical Information (OSTI.GOV)
Arendt, Dustin L.; Grace, Emily A.; Volkova, Svitlana
We demonstrate CHISSL, a scalable client-server system for real-time interactive machine learning. Our system is capa- ble of incorporating user feedback incrementally and imme- diately without a structured or pre-defined prediction task. Computation is partitioned between a lightweight web-client and a heavyweight server. The server relies on representation learning and agglomerative clustering to learn a dendrogram, a hierarchical approximation of a representation space. The client uses only this dendrogram to incorporate user feedback into the model via transduction. Distances and predictions for each unlabeled instance are updated incrementally and deter- ministically, with O(n) space and time complexity. Our al- gorithmmore » is implemented in a functional prototype, designed to be easy to use by non-experts. The prototype organizes the large amounts of data into recommendations. This allows the user to interact with actual instances by dragging and drop- ping to provide feedback in an intuitive manner. We applied CHISSL to several domains including cyber, social media, and geo-temporal analysis.« less
NASA Astrophysics Data System (ADS)
Jakubczyk, Dorota; Jakubczyk, Paweł
2018-02-01
We propose combinatorial approach to the representation of Schur-Weyl duality in physical systems on the example of one-dimensional spin chains. Exploiting the Robinson-Schensted-Knuth algorithm, we perform decomposition of the dual group representations into irreducible representations in a fully combinatorial way. As representation space, we choose the Hilbert space of the spin chains, but this approach can be easily generalized to an arbitrary physical system where the Schur-Weyl duality works.
Audio Motor Training at the Foot Level Improves Space Representation.
Aggius-Vella, Elena; Campus, Claudio; Finocchietti, Sara; Gori, Monica
2017-01-01
Spatial representation is developed thanks to the integration of visual signals with the other senses. It has been shown that the lack of vision compromises the development of some spatial representations. In this study we tested the effect of a new rehabilitation device called ABBI (Audio Bracelet for Blind Interaction) to improve space representation. ABBI produces an audio feedback linked to body movement. Previous studies from our group showed that this device improves the spatial representation of space in early blind adults around the upper part of the body. Here we evaluate whether the audio motor feedback produced by ABBI can also improve audio spatial representation of sighted individuals in the space around the legs. Forty five blindfolded sighted subjects participated in the study, subdivided into three experimental groups. An audio space localization (front-back discrimination) task was performed twice by all groups of subjects before and after different kind of training conditions. A group (experimental) performed an audio-motor training with the ABBI device placed on their foot. Another group (control) performed a free motor activity without audio feedback associated with body movement. The other group (control) passively listened to the ABBI sound moved at foot level by the experimenter without producing any body movement. Results showed that only the experimental group, which performed the training with the audio-motor feedback, showed an improvement in accuracy for sound discrimination. No improvement was observed for the two control groups. These findings suggest that the audio-motor training with ABBI improves audio space perception also in the space around the legs in sighted individuals. This result provides important inputs for the rehabilitation of the space representations in the lower part of the body.
Audio Motor Training at the Foot Level Improves Space Representation
Aggius-Vella, Elena; Campus, Claudio; Finocchietti, Sara; Gori, Monica
2017-01-01
Spatial representation is developed thanks to the integration of visual signals with the other senses. It has been shown that the lack of vision compromises the development of some spatial representations. In this study we tested the effect of a new rehabilitation device called ABBI (Audio Bracelet for Blind Interaction) to improve space representation. ABBI produces an audio feedback linked to body movement. Previous studies from our group showed that this device improves the spatial representation of space in early blind adults around the upper part of the body. Here we evaluate whether the audio motor feedback produced by ABBI can also improve audio spatial representation of sighted individuals in the space around the legs. Forty five blindfolded sighted subjects participated in the study, subdivided into three experimental groups. An audio space localization (front-back discrimination) task was performed twice by all groups of subjects before and after different kind of training conditions. A group (experimental) performed an audio-motor training with the ABBI device placed on their foot. Another group (control) performed a free motor activity without audio feedback associated with body movement. The other group (control) passively listened to the ABBI sound moved at foot level by the experimenter without producing any body movement. Results showed that only the experimental group, which performed the training with the audio-motor feedback, showed an improvement in accuracy for sound discrimination. No improvement was observed for the two control groups. These findings suggest that the audio-motor training with ABBI improves audio space perception also in the space around the legs in sighted individuals. This result provides important inputs for the rehabilitation of the space representations in the lower part of the body. PMID:29326564
Multi-scale kinetic description of granular clusters: invariance, balance, and temperature
NASA Astrophysics Data System (ADS)
Capriz, Gianfranco; Mariano, Paolo Maria
2017-12-01
We discuss a multi-scale continuum representation of bodies made of several mass particles flowing independently each other. From an invariance procedure and a nonstandard balance of inertial actions, we derive the balance equations introduced in earlier work directly in pointwise form, essentially on the basis of physical plausibility. In this way, we analyze their foundations. Then, we propose a Boltzmann-type equation for the distribution of kinetic energies within control volumes in space and indicate how such a distribution allows us to propose a definition of (granular) temperature along processes far from equilibrium.
NASA Astrophysics Data System (ADS)
Gires, Auguste; Tchiguirinskaia, Ioulia; Schertzer, Daniel; Ochoa-Rodriguez, Susana; Willems, Patrick; Ichiba, Abdellah; Wang, Lipen; Pina, Rui; Van Assel, Johan; Bruni, Guendalina; Murla Tuyls, Damian; ten Veldhuis, Marie-Claire
2017-04-01
Land use distribution and sewer system geometry exhibit complex scale dependent patterns in urban environment. This scale dependency is even more visible in a rasterized representation where only a unique class is affected to each pixel. Such features are well grasped with fractal tools, which are based scale invariance and intrinsically designed to characterise and quantify the space filled by a geometrical set exhibiting complex and tortuous patterns. Fractal tools have been widely used in hydrology but seldom in the specific context of urban hydrology. In this paper, they are used to analyse surface and sewer data from 10 urban or peri-urban catchments located in 5 European countries in the framework of the NWE Interreg RainGain project (www.raingain.eu). The aim was to characterise urban catchment properties accounting for the complexity and inhomogeneity typical of urban water systems. Sewer system density and imperviousness (roads or buildings), represented in rasterized maps of 2 m x 2 m pixels, were analysed to quantify their fractal dimension, characteristic of scaling invariance. It appears that both sewer density and imperviousness exhibit scale invariant features that can be characterized with the help of fractal dimensions ranging from 1.6 to 2, depending on the catchment. In a given area, consistent results were found for the two geometrical features, yielding a robust and innovative way of quantifying the level of urbanization. The representation of imperviousness in operational semi-distributed hydrological models for these catchments was also investigated by computing fractal dimensions of the geometrical sets made up of the sub-catchments with coefficients of imperviousness greater than a range of thresholds. It enables to quantify how well spatial structures of imperviousness are represented in the urban hydrological models.
Towards integrated modelling of soil organic carbon cycling at landscape scale
NASA Astrophysics Data System (ADS)
Viaud, V.
2009-04-01
Soil organic carbon (SOC) is recognized as a key factor of the chemical, biological and physical quality of soil. Numerous models of soil organic matter turnover have been developed since the 1930ies, most of them dedicated to plot scale applications. More recently, they have been applied to national scales to establish the inventories of carbon stocks directed by the Kyoto protocol. However, only few studies consider the intermediate landscape scale, where the spatio-temporal pattern of land management practices, its interactions with the physical environment and its impacts on SOC dynamics can be investigated to provide guidelines for sustainable management of soils in agricultural areas. Modelling SOC cycling at this scale requires accessing accurate spatially explicit input data on soils (SOC content, bulk density, depth, texture) and land use (land cover, farm practices), and combining both data in a relevant integrated landscape representation. The purpose of this paper is to present a first approach to modelling SOC evolution in a small catchment. The impact of the way landscape is represented on SOC stocks in the catchment was more specifically addressed. This study was based on the field map, the soil survey, the crop rotations and land management practices of an actual 10-km² agricultural catchment located in Brittany (France). RothC model was used to drive soil organic matter dynamics. Landscape representation in the form of a systematic regular grid, where driving properties vary continuously in space, was compared to a representation where landscape is subdivided into a set of homogeneous geographical units. This preliminary work enabled to identify future needs to improve integrated soil-landscape modelling in agricultural areas.
Automation Activities that Support C2 Agility to Mitigate Type 7 Risks
2014-06-01
on business trip • Space ship runs into space junk What are the probabilities for these events in a 45-year career time frame? Event that...representation that information system understands State- Space Diagram Common Agility Space (CAS) A simple C2 organization representation
The effects of mental representation on performance in a navigation task
NASA Technical Reports Server (NTRS)
Barshi, Immanuel; Healy, Alice F.
2002-01-01
In three experiments, we investigated the mental representations employed when instructions were followed that involved navigation in a space displayed as a grid on a computer screen. Performance was affected much more by the number of instructional units than by the number of words per unit. Performance in a three-dimensional space was independent of the number of dimensions along which participants navigated. However, memory for and accuracy in following the instructions were reduced when the task required mentally representing a three-dimensional space, as compared with representing a two-dimensional space, although the words used in the instructions were identical in the two cases. These results demonstrate the interdependence of verbal and spatial memory representations, because individuals' immediate memory for verbal navigation instructions is affected by their mental representation of the space referred to by the instructions.
Khaligh-Razavi, Seyed-Mahdi; Henriksson, Linda; Kay, Kendrick; Kriegeskorte, Nikolaus
2017-02-01
Studies of the primate visual system have begun to test a wide range of complex computational object-vision models. Realistic models have many parameters, which in practice cannot be fitted using the limited amounts of brain-activity data typically available. Task performance optimization (e.g. using backpropagation to train neural networks) provides major constraints for fitting parameters and discovering nonlinear representational features appropriate for the task (e.g. object classification). Model representations can be compared to brain representations in terms of the representational dissimilarities they predict for an image set. This method, called representational similarity analysis (RSA), enables us to test the representational feature space as is (fixed RSA) or to fit a linear transformation that mixes the nonlinear model features so as to best explain a cortical area's representational space (mixed RSA). Like voxel/population-receptive-field modelling, mixed RSA uses a training set (different stimuli) to fit one weight per model feature and response channel (voxels here), so as to best predict the response profile across images for each response channel. We analysed response patterns elicited by natural images, which were measured with functional magnetic resonance imaging (fMRI). We found that early visual areas were best accounted for by shallow models, such as a Gabor wavelet pyramid (GWP). The GWP model performed similarly with and without mixing, suggesting that the original features already approximated the representational space, obviating the need for mixing. However, a higher ventral-stream visual representation (lateral occipital region) was best explained by the higher layers of a deep convolutional network and mixing of its feature set was essential for this model to explain the representation. We suspect that mixing was essential because the convolutional network had been trained to discriminate a set of 1000 categories, whose frequencies in the training set did not match their frequencies in natural experience or their behavioural importance. The latter factors might determine the representational prominence of semantic dimensions in higher-level ventral-stream areas. Our results demonstrate the benefits of testing both the specific representational hypothesis expressed by a model's original feature space and the hypothesis space generated by linear transformations of that feature space.
a Voxel-Based Metadata Structure for Change Detection in Point Clouds of Large-Scale Urban Areas
NASA Astrophysics Data System (ADS)
Gehrung, J.; Hebel, M.; Arens, M.; Stilla, U.
2018-05-01
Mobile laser scanning has not only the potential to create detailed representations of urban environments, but also to determine changes up to a very detailed level. An environment representation for change detection in large scale urban environments based on point clouds has drawbacks in terms of memory scalability. Volumes, however, are a promising building block for memory efficient change detection methods. The challenge of working with 3D occupancy grids is that the usual raycasting-based methods applied for their generation lead to artifacts caused by the traversal of unfavorable discretized space. These artifacts have the potential to distort the state of voxels in close proximity to planar structures. In this work we propose a raycasting approach that utilizes knowledge about planar surfaces to completely prevent this kind of artifacts. To demonstrate the capabilities of our approach, a method for the iterative volumetric approximation of point clouds that allows to speed up the raycasting by 36 percent is proposed.
Palm vein recognition based on directional empirical mode decomposition
NASA Astrophysics Data System (ADS)
Lee, Jen-Chun; Chang, Chien-Ping; Chen, Wei-Kuei
2014-04-01
Directional empirical mode decomposition (DEMD) has recently been proposed to make empirical mode decomposition suitable for the processing of texture analysis. Using DEMD, samples are decomposed into a series of images, referred to as two-dimensional intrinsic mode functions (2-D IMFs), from finer to large scale. A DEMD-based 2 linear discriminant analysis (LDA) for palm vein recognition is proposed. The proposed method progresses through three steps: (i) a set of 2-D IMF features of various scale and orientation are extracted using DEMD, (ii) the 2LDA method is then applied to reduce the dimensionality of the feature space in both the row and column directions, and (iii) the nearest neighbor classifier is used for classification. We also propose two strategies for using the set of 2-D IMF features: ensemble DEMD vein representation (EDVR) and multichannel DEMD vein representation (MDVR). In experiments using palm vein databases, the proposed MDVR-based 2LDA method achieved recognition accuracy of 99.73%, thereby demonstrating its feasibility for palm vein recognition.
Exploring the Structure of Spatial Representations
Madl, Tamas; Franklin, Stan; Chen, Ke; Trappl, Robert; Montaldi, Daniela
2016-01-01
It has been suggested that the map-like representations that support human spatial memory are fragmented into sub-maps with local reference frames, rather than being unitary and global. However, the principles underlying the structure of these ‘cognitive maps’ are not well understood. We propose that the structure of the representations of navigation space arises from clustering within individual psychological spaces, i.e. from a process that groups together objects that are close in these spaces. Building on the ideas of representational geometry and similarity-based representations in cognitive science, we formulate methods for learning dissimilarity functions (metrics) characterizing participants’ psychological spaces. We show that these learned metrics, together with a probabilistic model of clustering based on the Bayesian cognition paradigm, allow prediction of participants’ cognitive map structures in advance. Apart from insights into spatial representation learning in human cognition, these methods could facilitate novel computational tools capable of using human-like spatial concepts. We also compare several features influencing spatial memory structure, including spatial distance, visual similarity and functional similarity, and report strong correlations between these dimensions and the grouping probability in participants’ spatial representations, providing further support for clustering in spatial memory. PMID:27347681
Tensor scale: An analytic approach with efficient computation and applications☆
Xu, Ziyue; Saha, Punam K.; Dasgupta, Soura
2015-01-01
Scale is a widely used notion in computer vision and image understanding that evolved in the form of scale-space theory where the key idea is to represent and analyze an image at various resolutions. Recently, we introduced a notion of local morphometric scale referred to as “tensor scale” using an ellipsoidal model that yields a unified representation of structure size, orientation and anisotropy. In the previous work, tensor scale was described using a 2-D algorithmic approach and a precise analytic definition was missing. Also, the application of tensor scale in 3-D using the previous framework is not practical due to high computational complexity. In this paper, an analytic definition of tensor scale is formulated for n-dimensional (n-D) images that captures local structure size, orientation and anisotropy. Also, an efficient computational solution in 2- and 3-D using several novel differential geometric approaches is presented and the accuracy of results is experimentally examined. Also, a matrix representation of tensor scale is derived facilitating several operations including tensor field smoothing to capture larger contextual knowledge. Finally, the applications of tensor scale in image filtering and n-linear interpolation are presented and the performance of their results is examined in comparison with respective state-of-art methods. Specifically, the performance of tensor scale based image filtering is compared with gradient and Weickert’s structure tensor based diffusive filtering algorithms. Also, the performance of tensor scale based n-linear interpolation is evaluated in comparison with standard n-linear and windowed-sinc interpolation methods. PMID:26236148
NASA Technical Reports Server (NTRS)
Dye, W. H.
1976-01-01
Results of aerodynamic heating tests conducted in October 1974 on a space shuttle orbiter model using the phase change paint technique are presented. The model was a 0.040 scale representation of the forward 50 percent of the orbiter. Surface roughness effects on boundary layer transition were investigated. Roughness was simulated by using steel balls varying in diameter from 0 (no balls) to 0.039 inch with 0.040 inch wide by 0.080 inch deep gaps. A nominal Mach number of 8 was tested with Reynolds number varying from 0.75 through 3.5 million per foot. Angle of attack was varied from 20 deg to 40 deg.
Towards a large-scale scalable adaptive heart model using shallow tree meshes
NASA Astrophysics Data System (ADS)
Krause, Dorian; Dickopf, Thomas; Potse, Mark; Krause, Rolf
2015-10-01
Electrophysiological heart models are sophisticated computational tools that place high demands on the computing hardware due to the high spatial resolution required to capture the steep depolarization front. To address this challenge, we present a novel adaptive scheme for resolving the deporalization front accurately using adaptivity in space. Our adaptive scheme is based on locally structured meshes. These tensor meshes in space are organized in a parallel forest of trees, which allows us to resolve complicated geometries and to realize high variations in the local mesh sizes with a minimal memory footprint in the adaptive scheme. We discuss both a non-conforming mortar element approximation and a conforming finite element space and present an efficient technique for the assembly of the respective stiffness matrices using matrix representations of the inclusion operators into the product space on the so-called shallow tree meshes. We analyzed the parallel performance and scalability for a two-dimensional ventricle slice as well as for a full large-scale heart model. Our results demonstrate that the method has good performance and high accuracy.
Multiscale unfolding of real networks by geometric renormalization
NASA Astrophysics Data System (ADS)
García-Pérez, Guillermo; Boguñá, Marián; Serrano, M. Ángeles
2018-06-01
Symmetries in physical theories denote invariance under some transformation, such as self-similarity under a change of scale. The renormalization group provides a powerful framework to study these symmetries, leading to a better understanding of the universal properties of phase transitions. However, the small-world property of complex networks complicates application of the renormalization group by introducing correlations between coexisting scales. Here, we provide a framework for the investigation of complex networks at different resolutions. The approach is based on geometric representations, which have been shown to sustain network navigability and to reveal the mechanisms that govern network structure and evolution. We define a geometric renormalization group for networks by embedding them into an underlying hidden metric space. We find that real scale-free networks show geometric scaling under this renormalization group transformation. We unfold the networks in a self-similar multilayer shell that distinguishes the coexisting scales and their interactions. This in turn offers a basis for exploring critical phenomena and universality in complex networks. It also affords us immediate practical applications, including high-fidelity smaller-scale replicas of large networks and a multiscale navigation protocol in hyperbolic space, which betters those on single layers.
ERIC Educational Resources Information Center
English, Michael C.; Maybery, Murray T.; Visser, Troy A.
2017-01-01
Neurotypical individuals display a leftward attentional bias, called pseudoneglect, for physical space (e.g. landmark task) and mental representations of space (e.g. mental number line bisection). However, leftward bias is reduced in autistic individuals viewing faces, and neurotypical individuals with autistic traits viewing "greyscale"…
Towards European-scale convection-resolving climate simulations with GPUs: a study with COSMO 4.19
NASA Astrophysics Data System (ADS)
Leutwyler, David; Fuhrer, Oliver; Lapillonne, Xavier; Lüthi, Daniel; Schär, Christoph
2016-09-01
The representation of moist convection in climate models represents a major challenge, due to the small scales involved. Using horizontal grid spacings of O(1km), convection-resolving weather and climate models allows one to explicitly resolve deep convection. However, due to their extremely demanding computational requirements, they have so far been limited to short simulations and/or small computational domains. Innovations in supercomputing have led to new hybrid node designs, mixing conventional multi-core hardware and accelerators such as graphics processing units (GPUs). One of the first atmospheric models that has been fully ported to these architectures is the COSMO (Consortium for Small-scale Modeling) model.Here we present the convection-resolving COSMO model on continental scales using a version of the model capable of using GPU accelerators. The verification of a week-long simulation containing winter storm Kyrill shows that, for this case, convection-parameterizing simulations and convection-resolving simulations agree well. Furthermore, we demonstrate the applicability of the approach to longer simulations by conducting a 3-month-long simulation of the summer season 2006. Its results corroborate the findings found on smaller domains such as more credible representation of the diurnal cycle of precipitation in convection-resolving models and a tendency to produce more intensive hourly precipitation events. Both simulations also show how the approach allows for the representation of interactions between synoptic-scale and meso-scale atmospheric circulations at scales ranging from 1000 to 10 km. This includes the formation of sharp cold frontal structures, convection embedded in fronts and small eddies, or the formation and organization of propagating cold pools. Finally, we assess the performance gain from using heterogeneous hardware equipped with GPUs relative to multi-core hardware. With the COSMO model, we now use a weather and climate model that has all the necessary modules required for real-case convection-resolving regional climate simulations on GPUs.
Five challenges for spatial epidemic models.
Riley, Steven; Eames, Ken; Isham, Valerie; Mollison, Denis; Trapman, Pieter
2015-03-01
Infectious disease incidence data are increasingly available at the level of the individual and include high-resolution spatial components. Therefore, we are now better able to challenge models that explicitly represent space. Here, we consider five topics within spatial disease dynamics: the construction of network models; characterising threshold behaviour; modelling long-distance interactions; the appropriate scale for interventions; and the representation of population heterogeneity. Copyright © 2014 The Authors. Published by Elsevier B.V. All rights reserved.
ERIC Educational Resources Information Center
Braswell, Gregory S.
2015-01-01
This exploratory study examined children's experiences with producing and comprehending external representations in a preschool classroom. Data collection and analyses focused on how artifacts, spaces, adult-guided routines, and social conventions shape young children's representational development. Participants included 4- and…
A k-space method for large-scale models of wave propagation in tissue.
Mast, T D; Souriau, L P; Liu, D L; Tabei, M; Nachman, A I; Waag, R C
2001-03-01
Large-scale simulation of ultrasonic pulse propagation in inhomogeneous tissue is important for the study of ultrasound-tissue interaction as well as for development of new imaging methods. Typical scales of interest span hundreds of wavelengths; most current two-dimensional methods, such as finite-difference and finite-element methods, are unable to compute propagation on this scale with the efficiency needed for imaging studies. Furthermore, for most available methods of simulating ultrasonic propagation, large-scale, three-dimensional computations of ultrasonic scattering are infeasible. Some of these difficulties have been overcome by previous pseudospectral and k-space methods, which allow substantial portions of the necessary computations to be executed using fast Fourier transforms. This paper presents a simplified derivation of the k-space method for a medium of variable sound speed and density; the derivation clearly shows the relationship of this k-space method to both past k-space methods and pseudospectral methods. In the present method, the spatial differential equations are solved by a simple Fourier transform method, and temporal iteration is performed using a k-t space propagator. The temporal iteration procedure is shown to be exact for homogeneous media, unconditionally stable for "slow" (c(x) < or = c0) media, and highly accurate for general weakly scattering media. The applicability of the k-space method to large-scale soft tissue modeling is shown by simulating two-dimensional propagation of an incident plane wave through several tissue-mimicking cylinders as well as a model chest wall cross section. A three-dimensional implementation of the k-space method is also employed for the example problem of propagation through a tissue-mimicking sphere. Numerical results indicate that the k-space method is accurate for large-scale soft tissue computations with much greater efficiency than that of an analogous leapfrog pseudospectral method or a 2-4 finite difference time-domain method. However, numerical results also indicate that the k-space method is less accurate than the finite-difference method for a high contrast scatterer with bone-like properties, although qualitative results can still be obtained by the k-space method with high efficiency. Possible extensions to the method, including representation of absorption effects, absorbing boundary conditions, elastic-wave propagation, and acoustic nonlinearity, are discussed.
Is the Classroom Obsolete in the Twenty-First Century?
ERIC Educational Resources Information Center
Benade, Leon
2017-01-01
Lefebvre's triadic conception of "spatial practice, representations of space and representational spaces" provides the theoretical framework of this article, which recognises a productive relationship between space and social relations. Its writing stems from a current and ongoing qualitative study of innovative teaching and learning…
Mapping Children--Mapping Space.
ERIC Educational Resources Information Center
Pick, Herbert L., Jr.
Research is underway concerning the way the perception, conception, and representation of spatial layout develops. Three concepts are important here--space itself, frame of reference, and cognitive map. Cognitive map refers to a form of representation of the behavioral space, not paired associate or serial response learning. Other criteria…
NASA Technical Reports Server (NTRS)
Rogge, R. L.
1974-01-01
Strut support interference investigations were conducted on an 0.004-(-) scale representation of the space shuttle launch vehicle in order to determine transonic and supersonic model support interference effects for use in a future exhaust plume effects study. Strut configurations were also tested. Orbiter, external tank, and solid rocket booster pressures were recorded at Mach numbers 0.9, 1.2, 1.5, and 2.0. Angle of attack and angle of sideslip were varied between plus or minus 4 degrees in 2 degree increments. Parametric variations consisted only of the strut configurations.
NASA Technical Reports Server (NTRS)
Hughes, T.
1974-01-01
Experimental aerodynamic investigations were conducted on a string-mounted 0.030 scale representation of the 140A/B space shuttle orbiter in the 7.75- by 11-foot low speed wind tunnel. The primary test objectives were to establish basic longitudinal and lateral directional stability and control characteristics for the basic configuration plus control surface hinge moments. Aerodynamic force and moment data were measured in the body axis system by an internally mounted, six-component strain gage balance. Additional configurations investigated were sealed rudder hingeline gaps, sealed elevon gaps and compartmentized speedbrakes.
Arrows as anchors: An analysis of the material features of electric field vector arrows
NASA Astrophysics Data System (ADS)
Gire, Elizabeth; Price, Edward
2014-12-01
Representations in physics possess both physical and conceptual aspects that are fundamentally intertwined and can interact to support or hinder sense making and computation. We use distributed cognition and the theory of conceptual blending with material anchors to interpret the roles of conceptual and material features of representations in students' use of representations for computation. We focus on the vector-arrows representation of electric fields and describe this representation as a conceptual blend of electric field concepts, physical space, and the material features of the representation (i.e., the physical writing and the surface upon which it is drawn). In this representation, spatial extent (e.g., distance on paper) is used to represent both distances in coordinate space and magnitudes of electric field vectors. In conceptual blending theory, this conflation is described as a clash between the input spaces in the blend. We explore the benefits and drawbacks of this clash, as well as other features of this representation. This analysis is illustrated with examples from clinical problem-solving interviews with upper-division physics majors. We see that while these intermediate physics students make a variety of errors using this representation, they also use the geometric features of the representation to add electric field contributions and to organize the problem situation productively.
Matsumoto, Yuji; Takaki, Yasuhiro
2014-06-15
Horizontally scanning holography can enlarge both screen size and viewing zone angle. A microelectromechanical-system spatial light modulator, which can generate only binary images, is used to generate hologram patterns. Thus, techniques to improve gray-scale representation in reconstructed images should be developed. In this study, the error diffusion technique was used for the binarization of holograms. When the Floyd-Steinberg error diffusion coefficients were used, gray-scale representation was improved. However, the linearity in the gray-scale representation was not satisfactory. We proposed the use of a correction table and showed that the linearity was greatly improved.
Greene, Samuel M; Batista, Victor S
2017-09-12
We introduce the "tensor-train split-operator Fourier transform" (TT-SOFT) method for simulations of multidimensional nonadiabatic quantum dynamics. TT-SOFT is essentially the grid-based SOFT method implemented in dynamically adaptive tensor-train representations. In the same spirit of all matrix product states, the tensor-train format enables the representation, propagation, and computation of observables of multidimensional wave functions in terms of the grid-based wavepacket tensor components, bypassing the need of actually computing the wave function in its full-rank tensor product grid space. We demonstrate the accuracy and efficiency of the TT-SOFT method as applied to propagation of 24-dimensional wave packets, describing the S 1 /S 2 interconversion dynamics of pyrazine after UV photoexcitation to the S 2 state. Our results show that the TT-SOFT method is a powerful computational approach for simulations of quantum dynamics of polyatomic systems since it avoids the exponential scaling problem of full-rank grid-based representations.
NASA Astrophysics Data System (ADS)
Cruz-Roa, Angel; Arevalo, John; Basavanhally, Ajay; Madabhushi, Anant; González, Fabio
2015-01-01
Learning data representations directly from the data itself is an approach that has shown great success in different pattern recognition problems, outperforming state-of-the-art feature extraction schemes for different tasks in computer vision, speech recognition and natural language processing. Representation learning applies unsupervised and supervised machine learning methods to large amounts of data to find building-blocks that better represent the information in it. Digitized histopathology images represents a very good testbed for representation learning since it involves large amounts of high complex, visual data. This paper presents a comparative evaluation of different supervised and unsupervised representation learning architectures to specifically address open questions on what type of learning architectures (deep or shallow), type of learning (unsupervised or supervised) is optimal. In this paper we limit ourselves to addressing these questions in the context of distinguishing between anaplastic and non-anaplastic medulloblastomas from routine haematoxylin and eosin stained images. The unsupervised approaches evaluated were sparse autoencoders and topographic reconstruct independent component analysis, and the supervised approach was convolutional neural networks. Experimental results show that shallow architectures with more neurons are better than deeper architectures without taking into account local space invariances and that topographic constraints provide useful invariant features in scale and rotations for efficient tumor differentiation.
The Koslowski-Sahlmann representation: quantum configuration space
NASA Astrophysics Data System (ADS)
Campiglia, Miguel; Varadarajan, Madhavan
2014-09-01
The Koslowski-Sahlmann (KS) representation is a generalization of the representation underlying the discrete spatial geometry of loop quantum gravity (LQG), to accommodate states labelled by smooth spatial geometries. As shown recently, the KS representation supports, in addition to the action of the holonomy and flux operators, the action of operators which are the quantum counterparts of certain connection dependent functions known as ‘background exponentials’. Here we show that the KS representation displays the following properties which are the exact counterparts of LQG ones: (i) the abelian * algebra of SU(2) holonomies and ‘U(1)’ background exponentials can be completed to a C* algebra, (ii) the space of semianalytic SU(2) connections is topologically dense in the spectrum of this algebra, (iii) there exists a measure on this spectrum for which the KS Hilbert space is realized as the space of square integrable functions on the spectrum, (iv) the spectrum admits a characterization as a projective limit of finite numbers of copies of SU(2) and U(1), (v) the algebra underlying the KS representation is constructed from cylindrical functions and their derivations in exactly the same way as the LQG (holonomy-flux) algebra except that the KS cylindrical functions depend on the holonomies and the background exponentials, this extra dependence being responsible for the differences between the KS and LQG algebras. While these results are obtained for compact spaces, they are expected to be of use for the construction of the KS representation in the asymptotically flat case.
Body frame close coupling wave packet approach to gas phase atom-rigid rotor inelastic collisions
NASA Technical Reports Server (NTRS)
Sun, Y.; Judson, R. S.; Kouri, D. J.
1989-01-01
The close coupling wave packet (CCWP) method is formulated in a body-fixed representation for atom-rigid rotor inelastic scattering. For J greater than j-max (where J is the total angular momentum and j is the rotational quantum number), the computational cost of propagating the coupled channel wave packets in the body frame is shown to scale approximately as N exp 3/2, where N is the total number of channels. For large numbers of channels, this will be much more efficient than the space frame CCWP method previously developed which scales approximately as N-squared under the same conditions.
DD-HDS: A method for visualization and exploration of high-dimensional data.
Lespinats, Sylvain; Verleysen, Michel; Giron, Alain; Fertil, Bernard
2007-09-01
Mapping high-dimensional data in a low-dimensional space, for example, for visualization, is a problem of increasingly major concern in data analysis. This paper presents data-driven high-dimensional scaling (DD-HDS), a nonlinear mapping method that follows the line of multidimensional scaling (MDS) approach, based on the preservation of distances between pairs of data. It improves the performance of existing competitors with respect to the representation of high-dimensional data, in two ways. It introduces (1) a specific weighting of distances between data taking into account the concentration of measure phenomenon and (2) a symmetric handling of short distances in the original and output spaces, avoiding false neighbor representations while still allowing some necessary tears in the original distribution. More precisely, the weighting is set according to the effective distribution of distances in the data set, with the exception of a single user-defined parameter setting the tradeoff between local neighborhood preservation and global mapping. The optimization of the stress criterion designed for the mapping is realized by "force-directed placement" (FDP). The mappings of low- and high-dimensional data sets are presented as illustrations of the features and advantages of the proposed algorithm. The weighting function specific to high-dimensional data and the symmetric handling of short distances can be easily incorporated in most distance preservation-based nonlinear dimensionality reduction methods.
NASA Astrophysics Data System (ADS)
Matthes, J. H.; Dietze, M.; Fox, A. M.; Goring, S. J.; McLachlan, J. S.; Moore, D. J.; Poulter, B.; Quaife, T. L.; Schaefer, K. M.; Steinkamp, J.; Williams, J. W.
2014-12-01
Interactions between ecological systems and the atmosphere are the result of dynamic processes with system memories that persist from seconds to centuries. Adequately capturing long-term biosphere-atmosphere exchange within earth system models (ESMs) requires an accurate representation of changes in plant functional types (PFTs) through time and space, particularly at timescales associated with ecological succession. However, most model parameterization and development has occurred using datasets than span less than a decade. We tested the ability of ESMs to capture the ecological dynamics observed in paleoecological and historical data spanning the last millennium. Focusing on an area from the Upper Midwest to New England, we examined differences in the magnitude and spatial pattern of PFT distributions and ecotones between historic datasets and the CMIP5 inter-comparison project's large-scale ESMs. We then conducted a 1000-year model inter-comparison using six state-of-the-art biosphere models at sites that bridged regional temperature and precipitation gradients. The distribution of ecosystem characteristics in modeled climate space reveals widely disparate relationships between modeled climate and vegetation that led to large differences in long-term biosphere-atmosphere fluxes for this region. Model simulations revealed that both the interaction between climate and vegetation and the representation of ecosystem dynamics within models were important controls on biosphere-atmosphere exchange.
Multiphase flow predictions from carbonate pore space images using extracted network models
NASA Astrophysics Data System (ADS)
Al-Kharusi, Anwar S.; Blunt, Martin J.
2008-06-01
A methodology to extract networks from pore space images is used to make predictions of multiphase transport properties for subsurface carbonate samples. The extraction of the network model is based on the computation of the location and sizes of pores and throats to create a topological representation of the void space of three-dimensional (3-D) rock images, using the concept of maximal balls. In this work, we follow a multistaged workflow. We start with a 2-D thin-section image; convert it statistically into a 3-D representation of the pore space; extract a network model from this image; and finally, simulate primary drainage, waterflooding, and secondary drainage flow processes using a pore-scale simulator. We test this workflow for a reservoir carbonate rock. The network-predicted absolute permeability is similar to the core plug measured value and the value computed on the 3-D void space image using the lattice Boltzmann method. The predicted capillary pressure during primary drainage agrees well with a mercury-air experiment on a core sample, indicating that we have an adequate representation of the rock's pore structure. We adjust the contact angles in the network to match the measured waterflood and secondary drainage capillary pressures. We infer a significant degree of contact angle hysteresis. We then predict relative permeabilities for primary drainage, waterflooding, and secondary drainage that agree well with laboratory measured values. This approach can be used to predict multiphase transport properties when wettability and pore structure vary in a reservoir, where experimental data is scant or missing. There are shortfalls to this approach, however. We compare results from three networks, one of which was derived from a section of the rock containing vugs. Our method fails to predict properties reliably when an unrepresentative image is processed to construct the 3-D network model. This occurs when the image volume is not sufficient to represent the geological variations observed in a core plug sample.
Improving left spatial neglect through music scale playing.
Bernardi, Nicolò Francesco; Cioffi, Maria Cristina; Ronchi, Roberta; Maravita, Angelo; Bricolo, Emanuela; Zigiotto, Luca; Perucca, Laura; Vallar, Giuseppe
2017-03-01
The study assessed whether the auditory reference provided by a music scale could improve spatial exploration of a standard musical instrument keyboard in right-brain-damaged patients with left spatial neglect. As performing music scales involves the production of predictable successive pitches, the expectation of the subsequent note may facilitate patients to explore a larger extension of space in the left affected side, during the production of music scales from right to left. Eleven right-brain-damaged stroke patients with left spatial neglect, 12 patients without neglect, and 12 age-matched healthy participants played descending scales on a music keyboard. In a counterbalanced design, the participants' exploratory performance was assessed while producing scales in three feedback conditions: With congruent sound, no-sound, or random sound feedback provided by the keyboard. The number of keys played and the timing of key press were recorded. Spatial exploration by patients with left neglect was superior with congruent sound feedback, compared to both Silence and Random sound conditions. Both the congruent and incongruent sound conditions were associated with a greater deceleration in all groups. The frame provided by the music scale improves exploration of the left side of space, contralateral to the right hemisphere, damaged in patients with left neglect. Performing a scale with congruent sounds may trigger at some extent preserved auditory and spatial multisensory representations of successive sounds, thus influencing the time course of space scanning, and ultimately resulting in a more extensive spatial exploration. These findings offer new perspectives also for the rehabilitation of the disorder. © 2015 The British Psychological Society.
Representational Distance Learning for Deep Neural Networks
McClure, Patrick; Kriegeskorte, Nikolaus
2016-01-01
Deep neural networks (DNNs) provide useful models of visual representational transformations. We present a method that enables a DNN (student) to learn from the internal representational spaces of a reference model (teacher), which could be another DNN or, in the future, a biological brain. Representational spaces of the student and the teacher are characterized by representational distance matrices (RDMs). We propose representational distance learning (RDL), a stochastic gradient descent method that drives the RDMs of the student to approximate the RDMs of the teacher. We demonstrate that RDL is competitive with other transfer learning techniques for two publicly available benchmark computer vision datasets (MNIST and CIFAR-100), while allowing for architectural differences between student and teacher. By pulling the student's RDMs toward those of the teacher, RDL significantly improved visual classification performance when compared to baseline networks that did not use transfer learning. In the future, RDL may enable combined supervised training of deep neural networks using task constraints (e.g., images and category labels) and constraints from brain-activity measurements, so as to build models that replicate the internal representational spaces of biological brains. PMID:28082889
Representational Distance Learning for Deep Neural Networks.
McClure, Patrick; Kriegeskorte, Nikolaus
2016-01-01
Deep neural networks (DNNs) provide useful models of visual representational transformations. We present a method that enables a DNN (student) to learn from the internal representational spaces of a reference model (teacher), which could be another DNN or, in the future, a biological brain. Representational spaces of the student and the teacher are characterized by representational distance matrices (RDMs). We propose representational distance learning (RDL), a stochastic gradient descent method that drives the RDMs of the student to approximate the RDMs of the teacher. We demonstrate that RDL is competitive with other transfer learning techniques for two publicly available benchmark computer vision datasets (MNIST and CIFAR-100), while allowing for architectural differences between student and teacher. By pulling the student's RDMs toward those of the teacher, RDL significantly improved visual classification performance when compared to baseline networks that did not use transfer learning. In the future, RDL may enable combined supervised training of deep neural networks using task constraints (e.g., images and category labels) and constraints from brain-activity measurements, so as to build models that replicate the internal representational spaces of biological brains.
Using Grid Cells for Navigation
Bush, Daniel; Barry, Caswell; Manson, Daniel; Burgess, Neil
2015-01-01
Summary Mammals are able to navigate to hidden goal locations by direct routes that may traverse previously unvisited terrain. Empirical evidence suggests that this “vector navigation” relies on an internal representation of space provided by the hippocampal formation. The periodic spatial firing patterns of grid cells in the hippocampal formation offer a compact combinatorial code for location within large-scale space. Here, we consider the computational problem of how to determine the vector between start and goal locations encoded by the firing of grid cells when this vector may be much longer than the largest grid scale. First, we present an algorithmic solution to the problem, inspired by the Fourier shift theorem. Second, we describe several potential neural network implementations of this solution that combine efficiency of search and biological plausibility. Finally, we discuss the empirical predictions of these implementations and their relationship to the anatomy and electrophysiology of the hippocampal formation. PMID:26247860
General tensor discriminant analysis and gabor features for gait recognition.
Tao, Dacheng; Li, Xuelong; Wu, Xindong; Maybank, Stephen J
2007-10-01
The traditional image representations are not suited to conventional classification methods, such as the linear discriminant analysis (LDA), because of the under sample problem (USP): the dimensionality of the feature space is much higher than the number of training samples. Motivated by the successes of the two dimensional LDA (2DLDA) for face recognition, we develop a general tensor discriminant analysis (GTDA) as a preprocessing step for LDA. The benefits of GTDA compared with existing preprocessing methods, e.g., principal component analysis (PCA) and 2DLDA, include 1) the USP is reduced in subsequent classification by, for example, LDA; 2) the discriminative information in the training tensors is preserved; and 3) GTDA provides stable recognition rates because the alternating projection optimization algorithm to obtain a solution of GTDA converges, while that of 2DLDA does not. We use human gait recognition to validate the proposed GTDA. The averaged gait images are utilized for gait representation. Given the popularity of Gabor function based image decompositions for image understanding and object recognition, we develop three different Gabor function based image representations: 1) the GaborD representation is the sum of Gabor filter responses over directions, 2) GaborS is the sum of Gabor filter responses over scales, and 3) GaborSD is the sum of Gabor filter responses over scales and directions. The GaborD, GaborS and GaborSD representations are applied to the problem of recognizing people from their averaged gait images.A large number of experiments were carried out to evaluate the effectiveness (recognition rate) of gait recognition based on first obtaining a Gabor, GaborD, GaborS or GaborSD image representation, then using GDTA to extract features and finally using LDA for classification. The proposed methods achieved good performance for gait recognition based on image sequences from the USF HumanID Database. Experimental comparisons are made with nine state of the art classification methods in gait recognition.
Representations of time coordinates in FITS. Time and relative dimension in space
NASA Astrophysics Data System (ADS)
Rots, Arnold H.; Bunclark, Peter S.; Calabretta, Mark R.; Allen, Steven L.; Manchester, Richard N.; Thompson, William T.
2015-02-01
Context. In a series of three previous papers, formulation and specifics of the representation of world coordinate transformations in FITS data have been presented. This fourth paper deals with encoding time. Aims: Time on all scales and precisions known in astronomical datasets is to be described in an unambiguous, complete, and self-consistent manner. Methods: Employing the well-established World Coordinate System (WCS) framework, and maintaining compatibility with the FITS conventions that are currently in use to specify time, the standard is extended to describe rigorously the time coordinate. Results: World coordinate functions are defined for temporal axes sampled linearly and as specified by a lookup table. The resulting standard is consistent with the existing FITS WCS standards and specifies a metadata set that achieves the aims enunciated above.
Space-Time Error Representation and Estimation in Navier-Stokes Calculations
NASA Technical Reports Server (NTRS)
Barth, Timothy J.
2006-01-01
The mathematical framework for a-posteriori error estimation of functionals elucidated by Eriksson et al. [7] and Becker and Rannacher [3] is revisited in a space-time context. Using these theories, a hierarchy of exact and approximate error representation formulas are presented for use in error estimation and mesh adaptivity. Numerical space-time results for simple model problems as well as compressible Navier-Stokes flow at Re = 300 over a 2D circular cylinder are then presented to demonstrate elements of the error representation theory for time-dependent problems.
Quesque, François; Gigliotti, Maria-Francesca; Ott, Laurent; Bruyelle, Jean-Luc
2018-01-01
Peripersonal space is a multisensory representation of the environment around the body in relation to the motor system, underlying the interactions with the physical and social world. Although changing body properties and social context have been shown to alter the functional processing of space, little is known about how changing the value of objects influences the representation of peripersonal space. In two experiments, we tested the effect of modifying the spatial distribution of reward-yielding targets on manual reaching actions and peripersonal space representation. Before and after performing a target-selection task consisting of manually selecting a set of targets on a touch-screen table, participants performed a two-alternative forced-choice reachability-judgment task. In the target-selection task, half of the targets were associated with a reward (change of colour from grey to green, providing 1 point), the other half being associated with no reward (change of colour from grey to red, providing no point). In Experiment 1, the target-selection task was performed individually with the aim of maximizing the point count, and the distribution of the reward-yielding targets was either 50%, 25% or 75% in the proximal and distal spaces. In Experiment 2, the target-selection task was performed in a social context involving cooperation between two participants to maximize the point count, and the distribution of the reward-yielding targets was 50% in the proximal and distal spaces. Results showed that changing the distribution of the reward-yielding targets or introducing the social context modified concurrently the amplitude of self-generated manual reaching actions and the representation of peripersonal space. Moreover, a decrease of the amplitude of manual reaching actions caused a reduction of peripersonal space when resulting from the distribution of reward-yielding targets, while this effect was not observed in a social interaction context. In that case, the decreased amplitude of manual reaching actions was accompanied by an increase of peripersonal space representation, which was not due to the mere presence of a confederate (control experiment). We conclude that reward-dependent modulation of objects values in the environment modifies the representation of peripersonal space, when resulting from either self-generated motor actions or observation of motor actions performed by a confederate. PMID:29771982
Coello, Yann; Quesque, François; Gigliotti, Maria-Francesca; Ott, Laurent; Bruyelle, Jean-Luc
2018-01-01
Peripersonal space is a multisensory representation of the environment around the body in relation to the motor system, underlying the interactions with the physical and social world. Although changing body properties and social context have been shown to alter the functional processing of space, little is known about how changing the value of objects influences the representation of peripersonal space. In two experiments, we tested the effect of modifying the spatial distribution of reward-yielding targets on manual reaching actions and peripersonal space representation. Before and after performing a target-selection task consisting of manually selecting a set of targets on a touch-screen table, participants performed a two-alternative forced-choice reachability-judgment task. In the target-selection task, half of the targets were associated with a reward (change of colour from grey to green, providing 1 point), the other half being associated with no reward (change of colour from grey to red, providing no point). In Experiment 1, the target-selection task was performed individually with the aim of maximizing the point count, and the distribution of the reward-yielding targets was either 50%, 25% or 75% in the proximal and distal spaces. In Experiment 2, the target-selection task was performed in a social context involving cooperation between two participants to maximize the point count, and the distribution of the reward-yielding targets was 50% in the proximal and distal spaces. Results showed that changing the distribution of the reward-yielding targets or introducing the social context modified concurrently the amplitude of self-generated manual reaching actions and the representation of peripersonal space. Moreover, a decrease of the amplitude of manual reaching actions caused a reduction of peripersonal space when resulting from the distribution of reward-yielding targets, while this effect was not observed in a social interaction context. In that case, the decreased amplitude of manual reaching actions was accompanied by an increase of peripersonal space representation, which was not due to the mere presence of a confederate (control experiment). We conclude that reward-dependent modulation of objects values in the environment modifies the representation of peripersonal space, when resulting from either self-generated motor actions or observation of motor actions performed by a confederate.
Cohomologie des Groupes Localement Compacts et Produits Tensoriels Continus de Representations
ERIC Educational Resources Information Center
Guichardet, A.
1976-01-01
Contains few and sometimes incomplete proofs on continuous tensor products of Hilbert spaces and of group representations, and on the irreducibility of the latter. Theory of continuous tensor products of Hilbert Spaces is closely related to that of conditionally positive definite functions; it relies on the technique of symmetric Hilbert spaces,…
Multiview alignment hashing for efficient image search.
Liu, Li; Yu, Mengyang; Shao, Ling
2015-03-01
Hashing is a popular and efficient method for nearest neighbor search in large-scale data spaces by embedding high-dimensional feature descriptors into a similarity preserving Hamming space with a low dimension. For most hashing methods, the performance of retrieval heavily depends on the choice of the high-dimensional feature descriptor. Furthermore, a single type of feature cannot be descriptive enough for different images when it is used for hashing. Thus, how to combine multiple representations for learning effective hashing functions is an imminent task. In this paper, we present a novel unsupervised multiview alignment hashing approach based on regularized kernel nonnegative matrix factorization, which can find a compact representation uncovering the hidden semantics and simultaneously respecting the joint probability distribution of data. In particular, we aim to seek a matrix factorization to effectively fuse the multiple information sources meanwhile discarding the feature redundancy. Since the raised problem is regarded as nonconvex and discrete, our objective function is then optimized via an alternate way with relaxation and converges to a locally optimal solution. After finding the low-dimensional representation, the hashing functions are finally obtained through multivariable logistic regression. The proposed method is systematically evaluated on three data sets: 1) Caltech-256; 2) CIFAR-10; and 3) CIFAR-20, and the results show that our method significantly outperforms the state-of-the-art multiview hashing techniques.
Andersen, Lau M
2018-01-01
An important aim of an analysis pipeline for magnetoencephalographic (MEG) data is that it allows for the researcher spending maximal effort on making the statistical comparisons that will answer his or her questions. The example question being answered here is whether the so-called beta rebound differs between novel and repeated stimulations. Two analyses are presented: going from individual sensor space representations to, respectively, an across-group sensor space representation and an across-group source space representation. The data analyzed are neural responses to tactile stimulations of the right index finger in a group of 20 healthy participants acquired from an Elekta Neuromag System. The processing steps covered for the first analysis are MaxFiltering the raw data, defining, preprocessing and epoching the data, cleaning the data, finding and removing independent components related to eye blinks, eye movements and heart beats, calculating participants' individual evoked responses by averaging over epoched data and subsequently removing the average response from single epochs, calculating a time-frequency representation and baselining it with non-stimulation trials and finally calculating a grand average, an across-group sensor space representation. The second analysis starts from the grand average sensor space representation and after identification of the beta rebound the neural origin is imaged using beamformer source reconstruction. This analysis covers reading in co-registered magnetic resonance images, segmenting the data, creating a volume conductor, creating a forward model, cutting out MEG data of interest in the time and frequency domains, getting Fourier transforms and estimating source activity with a beamformer model where power is expressed relative to MEG data measured during periods of non-stimulation. Finally, morphing the source estimates onto a common template and performing group-level statistics on the data are covered. Functions for saving relevant figures in an automated and structured manner are also included. The protocol presented here can be applied to any research protocol where the emphasis is on source reconstruction of induced responses where the underlying sources are not coherent.
Knowledge representation in space flight operations
NASA Technical Reports Server (NTRS)
Busse, Carl
1989-01-01
In space flight operations rapid understanding of the state of the space vehicle is essential. Representation of knowledge depicting space vehicle status in a dynamic environment presents a difficult challenge. The NASA Jet Propulsion Laboratory has pursued areas of technology associated with the advancement of spacecraft operations environment. This has led to the development of several advanced mission systems which incorporate enhanced graphics capabilities. These systems include: (1) Spacecraft Health Automated Reasoning Prototype (SHARP); (2) Spacecraft Monitoring Environment (SME); (3) Electrical Power Data Monitor (EPDM); (4) Generic Payload Operations Control Center (GPOCC); and (5) Telemetry System Monitor Prototype (TSM). Knowledge representation in these systems provides a direct representation of the intrinsic images associated with the instrument and satellite telemetry and telecommunications systems. The man-machine interface includes easily interpreted contextual graphic displays. These interactive video displays contain multiple display screens with pop-up windows and intelligent, high resolution graphics linked through context and mouse-sensitive icons and text.
1993-10-01
Designed by the mission crew members, the STS-61 crew insignia depicts the astronaut symbol superimposed against the sky with the Earth underneath. Also seen are two circles representing the optical configuration of the Hubble Space Telescope (HST). Light is focused by reflections from a large primary mirror and a smaller secondary mirror. The light is analyzed by various instruments and, according to the crew members, brings to us on Earth knowledge about planets, stars, galaxies and other celestial objects, allowing us to better understand the complex physical processes at work in the universe. The Space Shuttle Endeavour is also represented as the fundamental tool that allows the crew to perform the first servicing of the Hubble Space Telescope so its scientific deep space mission may be extended for several years to come. The overall design of the emblem, with lines converging to a high point, is also a symbolic representation of the large-scale Earth-based effort which involves space agencies, industry, and the universities to reach goals of knowledge and perfection.
[Time perceptions and representations].
Tordjman, S
2015-09-01
Representations of time and time measurements depend on subjective constructs that vary according to changes in our concepts, beliefs, societal needs and technical advances. Similarly, the past, the future and the present are subjective representations that depend on each individual's psychic time and biological time. Therefore, there is no single, one-size-fits-all time for everyone, but rather a different, subjective time for each individual. We need to acknowledge the existence of different inter-individual times but also intra-individual times, to which different functions and different rhythms are attached, depending on the system of reference. However, the construction of these time perceptions and representations is influenced by objective factors (physiological, physical and cognitive) related to neuroscience which will be presented and discussed in this article. Thus, studying representation and perception of time lies at the crossroads between neuroscience, human sciences and philosophy. Furthermore, it is possible to identify several constants among the many and various representations of time and their corresponding measures, regardless of the system of time reference. These include the notion of movements repeated in a stable rhythmic pattern involving the recurrence of the same interval of time, which enables us to define units of time of equal and invariable duration. This rhythmicity is also found at a physiological level and contributes through circadian rhythms, in particular the melatonin rhythm, to the existence of a biological time. Alterations of temporality in mental disorders will be also discussed in this article illustrated by certain developmental disorders such as autism spectrum disorders. In particular, the hypothesis will be developed that children with autism would need to create discontinuity out of continuity through stereotyped behaviors and/or interests. This discontinuity repeated at regular intervals could have been fundamentally lacking in their physiological development due to possibly altered circadian rhythms, including arhythmy and asynchrony. Time measurement, based on the repetition of discontinuity at regular intervals, involves also a spatial representation. It is our own trajectory through space-time, and thus our own motion, including the physiological process of aging, that affords us a representation of the passing of time, just as the countryside seems to be moving past us when we travel in a vehicle. Chinese and Indian societies actually have circular representations of time, and linear representations of time and its trajectory through space-time are currently a feature of Western societies. Circular time is collective time, and its metaphysical representations go beyond the life of a single individual, referring to the cyclical, or at least nonlinear, nature of time. Linear time is individual time, in that it refers to the scale of a person's lifetime, and it is physically represented by an arrow flying ineluctably from the past to the future. An intermediate concept can be proposed that acknowledges the existence of linear time involving various arrows of time corresponding to different lifespans (human, animal, plant, planet lifespans, etc.). In fact, the very notion of time would depend on the trajectory of each arrow of time, like shooting stars in the sky with different trajectory lengths which would define different time scales. The time scale of these various lifespans are very different (for example, a few decades for humans and a few days or hours for insects). It would not make sense to try to understand the passage of time experienced by an insect which may live only a few hours based on a human time scale. One hour in an insect's life cannot be compared to one experienced by a human. Yet again, it appears that there is a coexistence of different clocks based here on different lifespans. Finally, the evolution of our society focused on the present moment and choosing the cesium atom as the international reference unit of time measurement (cesium has a transition frequency of 9.192.631.77000 oscillations per second), will be questioned. We can consider that focusing on the present moment, in particular on instantaneity rather than infinity, prevents us from facing our own finitude. In conclusion, the question is raised that the current representation of time might be a means of managing our fear of death, giving us the illusion of controlling the uncontrollable, in particular the passage of time, and a means of avoiding to represent what many regard as non-representable, namely our own demise. Copyright © 2015 L’Encéphale. Published by Elsevier Masson SAS.. All rights reserved.
Topological Schemas of Memory Spaces.
Babichev, Andrey; Dabaghian, Yuri A
2018-01-01
Hippocampal cognitive map-a neuronal representation of the spatial environment-is widely discussed in the computational neuroscience literature for decades. However, more recent studies point out that hippocampus plays a major role in producing yet another cognitive framework-the memory space-that incorporates not only spatial, but also non-spatial memories. Unlike the cognitive maps, the memory spaces, broadly understood as "networks of interconnections among the representations of events," have not yet been studied from a theoretical perspective. Here we propose a mathematical approach that allows modeling memory spaces constructively, as epiphenomena of neuronal spiking activity and thus to interlink several important notions of cognitive neurophysiology. First, we suggest that memory spaces have a topological nature-a hypothesis that allows treating both spatial and non-spatial aspects of hippocampal function on equal footing. We then model the hippocampal memory spaces in different environments and demonstrate that the resulting constructions naturally incorporate the corresponding cognitive maps and provide a wider context for interpreting spatial information. Lastly, we propose a formal description of the memory consolidation process that connects memory spaces to the Morris' cognitive schemas-heuristic representations of the acquired memories, used to explain the dynamics of learning and memory consolidation in a given environment. The proposed approach allows evaluating these constructs as the most compact representations of the memory space's structure.
Holographic representation of space-variant systems: system theory.
Marks Ii, R J; Krile, T F
1976-09-01
System theory for holographic representation of linear space-variant systems is derived. The utility of the resulting piecewise isoplanatic approximation (PIA) is illustrated by example application to the invariant system, ideal magnifier, and Fourier transformer. A method previously employed to holographically represent a space-variant system, the discrete approximation, is shown to be a special case of the PIA.
Yu, Yinan; Diamantaras, Konstantinos I; McKelvey, Tomas; Kung, Sun-Yuan
2018-02-01
In kernel-based classification models, given limited computational power and storage capacity, operations over the full kernel matrix becomes prohibitive. In this paper, we propose a new supervised learning framework using kernel models for sequential data processing. The framework is based on two components that both aim at enhancing the classification capability with a subset selection scheme. The first part is a subspace projection technique in the reproducing kernel Hilbert space using a CLAss-specific Subspace Kernel representation for kernel approximation. In the second part, we propose a novel structural risk minimization algorithm called the adaptive margin slack minimization to iteratively improve the classification accuracy by an adaptive data selection. We motivate each part separately, and then integrate them into learning frameworks for large scale data. We propose two such frameworks: the memory efficient sequential processing for sequential data processing and the parallelized sequential processing for distributed computing with sequential data acquisition. We test our methods on several benchmark data sets and compared with the state-of-the-art techniques to verify the validity of the proposed techniques.
Marcus, Lars
2018-01-01
The world is witnessing unprecedented urbanization, bringing extreme challenges to contemporary practices in urban planning and design. This calls for improved urban models that can generate new knowledge and enhance practical skill. Importantly, any urban model embodies a conception of the relation between humans and the physical environment. In urban modeling this is typically conceived of as a relation between human subjects and an environmental object, thereby reproducing a humans-environment dichotomy. Alternative modeling traditions, such as space syntax that originates in architecture rather than geography, have tried to overcome this dichotomy. Central in this effort is the development of new representations of urban space, such as in the case of space syntax, the axial map. This form of representation aims to integrate both human behavior and the physical environment into one and the same description. Interestingly, models based on these representations have proved to better capture pedestrian movement than regular models. Pedestrian movement, as well as other kinds of human flows in urban space, is essential for urban modeling, since increasingly flows of this kind are understood as the driver in urban processes. Critical for a full understanding of space syntax modeling is the ontology of its' representations, such as the axial map. Space syntax theory here often refers to James Gibson's "Theory of affordances," where the concept of affordances, in a manner similar to axial maps, aims to bridge the subject-object dichotomy by neither constituting physical properties of the environment or human behavior, but rather what emerges in the meeting between the two. In extension of this, the axial map can be interpreted as a representation of how the physical form of the environment affords human accessibility and visibility in urban space. This paper presents a close examination of the form of representations developed in space syntax methodology, in particular in the light of Gibson's "theory of affordances." The overarching aim is to contribute to a theoretical framework for urban models based on affordances, which may support the overcoming of the subject-object dichotomy in such models, here deemed essential for a greater social-ecological sustainability of cities.
Medendorp, W. P.
2015-01-01
It is known that the brain uses multiple reference frames to code spatial information, including eye-centered and body-centered frames. When we move our body in space, these internal representations are no longer in register with external space, unless they are actively updated. Whether the brain updates multiple spatial representations in parallel, or whether it restricts its updating mechanisms to a single reference frame from which other representations are constructed, remains an open question. We developed an optimal integration model to simulate the updating of visual space across body motion in multiple or single reference frames. To test this model, we designed an experiment in which participants had to remember the location of a briefly presented target while being translated sideways. The behavioral responses were in agreement with a model that uses a combination of eye- and body-centered representations, weighted according to the reliability in which the target location is stored and updated in each reference frame. Our findings suggest that the brain simultaneously updates multiple spatial representations across body motion. Because both representations are kept in sync, they can be optimally combined to provide a more precise estimate of visual locations in space than based on single-frame updating mechanisms. PMID:26490289
A real-space stochastic density matrix approach for density functional electronic structure.
Beck, Thomas L
2015-12-21
The recent development of real-space grid methods has led to more efficient, accurate, and adaptable approaches for large-scale electrostatics and density functional electronic structure modeling. With the incorporation of multiscale techniques, linear-scaling real-space solvers are possible for density functional problems if localized orbitals are used to represent the Kohn-Sham energy functional. These methods still suffer from high computational and storage overheads, however, due to extensive matrix operations related to the underlying wave function grid representation. In this paper, an alternative stochastic method is outlined that aims to solve directly for the one-electron density matrix in real space. In order to illustrate aspects of the method, model calculations are performed for simple one-dimensional problems that display some features of the more general problem, such as spatial nodes in the density matrix. This orbital-free approach may prove helpful considering a future involving increasingly parallel computing architectures. Its primary advantage is the near-locality of the random walks, allowing for simultaneous updates of the density matrix in different regions of space partitioned across the processors. In addition, it allows for testing and enforcement of the particle number and idempotency constraints through stabilization of a Feynman-Kac functional integral as opposed to the extensive matrix operations in traditional approaches.
Audio Spatial Representation Around the Body
Aggius-Vella, Elena; Campus, Claudio; Finocchietti, Sara; Gori, Monica
2017-01-01
Studies have found that portions of space around our body are differently coded by our brain. Numerous works have investigated visual and auditory spatial representation, focusing mostly on the spatial representation of stimuli presented at head level, especially in the frontal space. Only few studies have investigated spatial representation around the entire body and its relationship with motor activity. Moreover, it is still not clear whether the space surrounding us is represented as a unitary dimension or whether it is split up into different portions, differently shaped by our senses and motor activity. To clarify these points, we investigated audio localization of dynamic and static sounds at different body levels. In order to understand the role of a motor action in auditory space representation, we asked subjects to localize sounds by pointing with the hand or the foot, or by giving a verbal answer. We found that the audio sound localization was different depending on the body part considered. Moreover, a different pattern of response was observed when subjects were asked to make actions with respect to the verbal responses. These results suggest that the audio space around our body is split in various spatial portions, which are perceived differently: front, back, around chest, and around foot, suggesting that these four areas could be differently modulated by our senses and our actions. PMID:29249999
Reflection Positive Stochastic Processes Indexed by Lie Groups
NASA Astrophysics Data System (ADS)
Jorgensen, Palle E. T.; Neeb, Karl-Hermann; Ólafsson, Gestur
2016-06-01
Reflection positivity originates from one of the Osterwalder-Schrader axioms for constructive quantum field theory. It serves as a bridge between euclidean and relativistic quantum field theory. In mathematics, more specifically, in representation theory, it is related to the Cartan duality of symmetric Lie groups (Lie groups with an involution) and results in a transformation of a unitary representation of a symmetric Lie group to a unitary representation of its Cartan dual. In this article we continue our investigation of representation theoretic aspects of reflection positivity by discussing reflection positive Markov processes indexed by Lie groups, measures on path spaces, and invariant gaussian measures in spaces of distribution vectors. This provides new constructions of reflection positive unitary representations.
NASA Astrophysics Data System (ADS)
Leutwyler, D.; Fuhrer, O.; Ban, N.; Lapillonne, X.; Lüthi, D.; Schar, C.
2017-12-01
The representation of moist convection in climate models represents a major challenge, due to the small scales involved. Regional climate simulations using horizontal resolutions of O(1km) allow to explicitly resolve deep convection leading to an improved representation of the water cycle. However, due to their extremely demanding computational requirements, they have so far been limited to short simulations and/or small computational domains. A new version of the Consortium for Small-Scale Modeling weather and climate model (COSMO) is capable of exploiting new supercomputer architectures employing GPU accelerators, and allows convection-resolving climate simulations on computational domains spanning continents and time periods up to one decade. We present results from a decade-long, convection-resolving climate simulation on a European-scale computational domain. The simulation has a grid spacing of 2.2 km, 1536x1536x60 grid points, covers the period 1999-2008, and is driven by the ERA-Interim reanalysis. Specifically we present an evaluation of hourly rainfall using a wide range of data sets, including several rain-gauge networks and a remotely-sensed lightning data set. Substantial improvements are found in terms of the diurnal cycles of precipitation amount, wet-hour frequency and all-hour 99th percentile. However the results also reveal substantial differences between regions with and without strong orographic forcing. Furthermore we present an index for deep-convective activity based on the statistics of vertical motion. Comparison of the index with lightning data shows that the convection-resolving climate simulations are able to reproduce important features of the annual cycle of deep convection in Europe. Leutwyler D., D. Lüthi, N. Ban, O. Fuhrer, and C. Schär (2017): Evaluation of the Convection-Resolving Climate Modeling Approach on Continental Scales , J. Geophys. Res. Atmos., 122, doi:10.1002/2016JD026013.
NASA Astrophysics Data System (ADS)
Benioff, Paul
2015-05-01
The purpose of this paper is to put the description of number scaling and its effects on physics and geometry on a firmer foundation, and to make it more understandable. A main point is that two different concepts, number and number value are combined in the usual representations of number structures. This is valid as long as just one structure of each number type is being considered. It is not valid when different structures of each number type are being considered. Elements of base sets of number structures, considered by themselves, have no meaning. They acquire meaning or value as elements of a number structure. Fiber bundles over a space or space time manifold, M, are described. The fiber consists of a collection of many real or complex number structures and vector space structures. The structures are parameterized by a real or complex scaling factor, s. A vector space at a fiber level, s, has, as scalars, real or complex number structures at the same level. Connections are described that relate scalar and vector space structures at both neighbor M locations and at neighbor scaling levels. Scalar and vector structure valued fields are described and covariant derivatives of these fields are obtained. Two complex vector fields, each with one real and one imaginary field, appear, with one complex field associated with positions in M and the other with position dependent scaling factors. A derivation of the covariant derivative for scalar and vector valued fields gives the same vector fields. The derivation shows that the complex vector field associated with scaling fiber levels is the gradient of a complex scalar field. Use of these results in gauge theory shows that the imaginary part of the vector field associated with M positions acts like the electromagnetic field. The physical relevance of the other three fields, if any, is not known.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Choo, Jaegul; Kim, Hannah; Clarkson, Edward
In this paper, we present an interactive visual information retrieval and recommendation system, called VisIRR, for large-scale document discovery. VisIRR effectively combines the paradigms of (1) a passive pull through query processes for retrieval and (2) an active push that recommends items of potential interest to users based on their preferences. Equipped with an efficient dynamic query interface against a large-scale corpus, VisIRR organizes the retrieved documents into high-level topics and visualizes them in a 2D space, representing the relationships among the topics along with their keyword summary. In addition, based on interactive personalized preference feedback with regard to documents,more » VisIRR provides document recommendations from the entire corpus, which are beyond the retrieved sets. Such recommended documents are visualized in the same space as the retrieved documents, so that users can seamlessly analyze both existing and newly recommended ones. This article presents novel computational methods, which make these integrated representations and fast interactions possible for a large-scale document corpus. We illustrate how the system works by providing detailed usage scenarios. Finally, we present preliminary user study results for evaluating the effectiveness of the system.« less
Choo, Jaegul; Kim, Hannah; Clarkson, Edward; ...
2018-01-31
In this paper, we present an interactive visual information retrieval and recommendation system, called VisIRR, for large-scale document discovery. VisIRR effectively combines the paradigms of (1) a passive pull through query processes for retrieval and (2) an active push that recommends items of potential interest to users based on their preferences. Equipped with an efficient dynamic query interface against a large-scale corpus, VisIRR organizes the retrieved documents into high-level topics and visualizes them in a 2D space, representing the relationships among the topics along with their keyword summary. In addition, based on interactive personalized preference feedback with regard to documents,more » VisIRR provides document recommendations from the entire corpus, which are beyond the retrieved sets. Such recommended documents are visualized in the same space as the retrieved documents, so that users can seamlessly analyze both existing and newly recommended ones. This article presents novel computational methods, which make these integrated representations and fast interactions possible for a large-scale document corpus. We illustrate how the system works by providing detailed usage scenarios. Finally, we present preliminary user study results for evaluating the effectiveness of the system.« less
Adinkra (in)equivalence from Coxeter group representations: A case study
NASA Astrophysics Data System (ADS)
Chappell, Isaac; Gates, S. James; Hübsch, T.
2014-02-01
Using a MathematicaTM code, we present a straightforward numerical analysis of the 384-dimensional solution space of signed permutation 4×4 matrices, which in sets of four, provide representations of the 𝒢ℛ(4, 4) algebra, closely related to the 𝒩 = 1 (simple) supersymmetry algebra in four-dimensional space-time. Following after ideas discussed in previous papers about automorphisms and classification of adinkras and corresponding supermultiplets, we make a new and alternative proposal to use equivalence classes of the (unsigned) permutation group S4 to define distinct representations of higher-dimensional spin bundles within the context of adinkras. For this purpose, the definition of a dual operator akin to the well-known Hodge star is found to partition the space of these 𝒢ℛ(4, 4) representations into three suggestive classes.
NASA Technical Reports Server (NTRS)
Mennell, R. C.; Cameron, B. W.
1974-01-01
Experimental aerodynamic investigations were conducted on a .0405 scale representation of the space shuttle orbiter in a 7.75 x 11 foot low speed wind tunnel during the time period March 21, to April 17, 1973. The primary test objectives were to investigate both the aerodynamic and propulsion effects of various air breathing engine systems in free air and in the presence of the ground. The free air portion of this test investigated the aerodynamic effects of engine nacelle number, nacelle grouping, and nacelle location. For this testing the model was sting mounted on a six component internal strain gage balance entering through the model base. The ground plane portion of the aerodynamic test investigated the same nacelle effects at ground plane locations of full scale W.P. = 239.9, 209.3, 158.9, 108.5, and 7.78 in. At the conclusion of the aerodynamic test period the propulsion effects of various nacelle locations and freestream orientations in the presence of the ground were investigated.
NASA Astrophysics Data System (ADS)
Guo, Tian; Xu, Zili
2018-03-01
Measurement noise is inevitable in practice; thus, it is difficult to identify defects, cracks or damage in a structure while suppressing noise simultaneously. In this work, a novel method is introduced to detect multiple damage in noisy environments. Based on multi-scale space analysis for discrete signals, a method for extracting damage characteristics from the measured displacement mode shape is illustrated. Moreover, the proposed method incorporates a data fusion algorithm to further eliminate measurement noise-based interference. The effectiveness of the method is verified by numerical and experimental methods applied to different structural types. The results demonstrate that there are two advantages to the proposed method. First, damage features are extracted by the difference of the multi-scale representation; this step is taken such that the interference of noise amplification can be avoided. Second, a data fusion technique applied to the proposed method provides a global decision, which retains the damage features while maximally eliminating the uncertainty. Monte Carlo simulations are utilized to validate that the proposed method has a higher accuracy in damage detection.
Prose Representation: A Multidimensional Scaling Approach.
ERIC Educational Resources Information Center
LaPorte, Ronald E.; Voss, James F.
1979-01-01
Multidimensional scaling was used to study the comprehension of prose. Undergraduates rated the similarity of twenty nouns before and after reading passages containing those nouns. Results indicated that the scaling analysis provided an effective valid indicator of prose representation. (Author/JKS)
Kellis, Spencer; Sorensen, Larry; Darvas, Felix; Sayres, Conor; O'Neill, Kevin; Brown, Richard B; House, Paul; Ojemann, Jeff; Greger, Bradley
2016-01-01
Electrocorticography grids have been used to study and diagnose neural pathophysiology for over 50 years, and recently have been used for various neural prosthetic applications. Here we provide evidence that micro-scale electrodes are better suited for studying cortical pathology and function, and for implementing neural prostheses. This work compares dynamics in space, time, and frequency of cortical field potentials recorded by three types of electrodes: electrocorticographic (ECoG) electrodes, non-penetrating micro-ECoG (μECoG) electrodes that use microelectrodes and have tighter interelectrode spacing; and penetrating microelectrodes (MEA) that penetrate the cortex to record single- or multiunit activity (SUA or MUA) and local field potentials (LFP). While the finest spatial scales are found in LFPs recorded intracortically, we found that LFP recorded from μECoG electrodes demonstrate scales of linear similarity (i.e., correlation, coherence, and phase) closer to the intracortical electrodes than the clinical ECoG electrodes. We conclude that LFPs can be recorded intracortically and epicortically at finer scales than clinical ECoG electrodes are capable of capturing. Recorded with appropriately scaled electrodes and grids, field potentials expose a more detailed representation of cortical network activity, enabling advanced analyses of cortical pathology and demanding applications such as brain-computer interfaces. Copyright © 2015 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.
Topological Schemas of Memory Spaces
Babichev, Andrey; Dabaghian, Yuri A.
2018-01-01
Hippocampal cognitive map—a neuronal representation of the spatial environment—is widely discussed in the computational neuroscience literature for decades. However, more recent studies point out that hippocampus plays a major role in producing yet another cognitive framework—the memory space—that incorporates not only spatial, but also non-spatial memories. Unlike the cognitive maps, the memory spaces, broadly understood as “networks of interconnections among the representations of events,” have not yet been studied from a theoretical perspective. Here we propose a mathematical approach that allows modeling memory spaces constructively, as epiphenomena of neuronal spiking activity and thus to interlink several important notions of cognitive neurophysiology. First, we suggest that memory spaces have a topological nature—a hypothesis that allows treating both spatial and non-spatial aspects of hippocampal function on equal footing. We then model the hippocampal memory spaces in different environments and demonstrate that the resulting constructions naturally incorporate the corresponding cognitive maps and provide a wider context for interpreting spatial information. Lastly, we propose a formal description of the memory consolidation process that connects memory spaces to the Morris' cognitive schemas-heuristic representations of the acquired memories, used to explain the dynamics of learning and memory consolidation in a given environment. The proposed approach allows evaluating these constructs as the most compact representations of the memory space's structure. PMID:29740306
The scale invariant generator technique for quantifying anisotropic scale invariance
NASA Astrophysics Data System (ADS)
Lewis, G. M.; Lovejoy, S.; Schertzer, D.; Pecknold, S.
1999-11-01
Scale invariance is rapidly becoming a new paradigm for geophysics. However, little attention has been paid to the anisotropy that is invariably present in geophysical fields in the form of differential stratification and rotation, texture and morphology. In order to account for scaling anisotropy, the formalism of generalized scale invariance (GSI) was developed. Until now there has existed only a single fairly ad hoc GSI analysis technique valid for studying differential rotation. In this paper, we use a two-dimensional representation of the linear approximation to generalized scale invariance, to obtain a much improved technique for quantifying anisotropic scale invariance called the scale invariant generator technique (SIG). The accuracy of the technique is tested using anisotropic multifractal simulations and error estimates are provided for the geophysically relevant range of parameters. It is found that the technique yields reasonable estimates for simulations with a diversity of anisotropic and statistical characteristics. The scale invariant generator technique can profitably be applied to the scale invariant study of vertical/horizontal and space/time cross-sections of geophysical fields as well as to the study of the texture/morphology of fields.
Electron tomography and 3D molecular simulations of platinum nanocrystals
NASA Astrophysics Data System (ADS)
Florea, Ileana; Demortière, Arnaud; Petit, Christophe; Bulou, Hervé; Hirlimann, Charles; Ersen, Ovidiu
2012-07-01
This work reports on the morphology of individual platinum nanocrystals with sizes of about 5 nm. By using the electron tomography technique that gives 3D spatial selectivity, access to quantitative information in the real space was obtained. The morphology of individual nanoparticles was characterized using HAADF-STEM tomography and it was shown to be close to a truncated octahedron. Using molecular dynamics simulations, this geometrical shape was found to be the one minimizing the nanocrystal energy. Starting from the tomographic reconstruction, 3D crystallographic representations of the studied Pt nanocrystals were obtained at the nanometer scale, allowing the quantification of the relative amount of the crystallographic facets present on the particle surface.This work reports on the morphology of individual platinum nanocrystals with sizes of about 5 nm. By using the electron tomography technique that gives 3D spatial selectivity, access to quantitative information in the real space was obtained. The morphology of individual nanoparticles was characterized using HAADF-STEM tomography and it was shown to be close to a truncated octahedron. Using molecular dynamics simulations, this geometrical shape was found to be the one minimizing the nanocrystal energy. Starting from the tomographic reconstruction, 3D crystallographic representations of the studied Pt nanocrystals were obtained at the nanometer scale, allowing the quantification of the relative amount of the crystallographic facets present on the particle surface. Electronic supplementary information (ESI) available. See DOI: 10.1039/c2nr30990d
A computational theory of visual receptive fields.
Lindeberg, Tony
2013-12-01
A receptive field constitutes a region in the visual field where a visual cell or a visual operator responds to visual stimuli. This paper presents a theory for what types of receptive field profiles can be regarded as natural for an idealized vision system, given a set of structural requirements on the first stages of visual processing that reflect symmetry properties of the surrounding world. These symmetry properties include (i) covariance properties under scale changes, affine image deformations, and Galilean transformations of space-time as occur for real-world image data as well as specific requirements of (ii) temporal causality implying that the future cannot be accessed and (iii) a time-recursive updating mechanism of a limited temporal buffer of the past as is necessary for a genuine real-time system. Fundamental structural requirements are also imposed to ensure (iv) mutual consistency and a proper handling of internal representations at different spatial and temporal scales. It is shown how a set of families of idealized receptive field profiles can be derived by necessity regarding spatial, spatio-chromatic, and spatio-temporal receptive fields in terms of Gaussian kernels, Gaussian derivatives, or closely related operators. Such image filters have been successfully used as a basis for expressing a large number of visual operations in computer vision, regarding feature detection, feature classification, motion estimation, object recognition, spatio-temporal recognition, and shape estimation. Hence, the associated so-called scale-space theory constitutes a both theoretically well-founded and general framework for expressing visual operations. There are very close similarities between receptive field profiles predicted from this scale-space theory and receptive field profiles found by cell recordings in biological vision. Among the family of receptive field profiles derived by necessity from the assumptions, idealized models with very good qualitative agreement are obtained for (i) spatial on-center/off-surround and off-center/on-surround receptive fields in the fovea and the LGN, (ii) simple cells with spatial directional preference in V1, (iii) spatio-chromatic double-opponent neurons in V1, (iv) space-time separable spatio-temporal receptive fields in the LGN and V1, and (v) non-separable space-time tilted receptive fields in V1, all within the same unified theory. In addition, the paper presents a more general framework for relating and interpreting these receptive fields conceptually and possibly predicting new receptive field profiles as well as for pre-wiring covariance under scaling, affine, and Galilean transformations into the representations of visual stimuli. This paper describes the basic structure of the necessity results concerning receptive field profiles regarding the mathematical foundation of the theory and outlines how the proposed theory could be used in further studies and modelling of biological vision. It is also shown how receptive field responses can be interpreted physically, as the superposition of relative variations of surface structure and illumination variations, given a logarithmic brightness scale, and how receptive field measurements will be invariant under multiplicative illumination variations and exposure control mechanisms.
Web-based Visual Analytics for Extreme Scale Climate Science
DOE Office of Scientific and Technical Information (OSTI.GOV)
Steed, Chad A; Evans, Katherine J; Harney, John F
In this paper, we introduce a Web-based visual analytics framework for democratizing advanced visualization and analysis capabilities pertinent to large-scale earth system simulations. We address significant limitations of present climate data analysis tools such as tightly coupled dependencies, ineffi- cient data movements, complex user interfaces, and static visualizations. Our Web-based visual analytics framework removes critical barriers to the widespread accessibility and adoption of advanced scientific techniques. Using distributed connections to back-end diagnostics, we minimize data movements and leverage HPC platforms. We also mitigate system dependency issues by employing a RESTful interface. Our framework embraces the visual analytics paradigm via newmore » visual navigation techniques for hierarchical parameter spaces, multi-scale representations, and interactive spatio-temporal data mining methods that retain details. Although generalizable to other science domains, the current work focuses on improving exploratory analysis of large-scale Community Land Model (CLM) and Community Atmosphere Model (CAM) simulations.« less
Squeezing, Striking, and Vocalizing: Is Number Representation Fundamentally Spatial?
ERIC Educational Resources Information Center
Nunez, Rafael; Doan, D.; Nikoulina, Anastasia
2011-01-01
Numbers are fundamental entities in mathematics, but their cognitive bases are unclear. Abundant research points to linear space as a natural grounding for number representation. But, is number representation fundamentally spatial? We disentangle number representation from standard number-to-line reporting methods, and compare numerical…
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ceccato, Alessandro; Frezzato, Diego, E-mail: diego.frezzato@unipd.it; Nicolini, Paolo
In this work, we deal with general reactive systems involving N species and M elementary reactions under applicability of the mass-action law. Starting from the dynamic variables introduced in two previous works [P. Nicolini and D. Frezzato, J. Chem. Phys. 138(23), 234101 (2013); 138(23), 234102 (2013)], we turn to a new representation in which the system state is specified in a (N × M){sup 2}-dimensional space by a point whose coordinates have physical dimension of inverse-of-time. By adopting hyper-spherical coordinates (a set of dimensionless “angular” variables and a single “radial” one with physical dimension of inverse-of-time) and by examining themore » properties of their evolution law both formally and numerically on model kinetic schemes, we show that the system evolves towards the equilibrium as being attracted by a sequence of fixed subspaces (one at a time) each associated with a compact domain of the concentration space. Thus, we point out that also for general non-linear kinetics there exist fixed “objects” on the global scale, although they are conceived in such an abstract and extended space. Moreover, we propose a link between the persistence of the belonging of a trajectory to such subspaces and the closeness to the slow manifold which would be perceived by looking at the bundling of the trajectories in the concentration space.« less
Emerging Object Representations in the Visual System Predict Reaction Times for Categorization
Ritchie, J. Brendan; Tovar, David A.; Carlson, Thomas A.
2015-01-01
Recognizing an object takes just a fraction of a second, less than the blink of an eye. Applying multivariate pattern analysis, or “brain decoding”, methods to magnetoencephalography (MEG) data has allowed researchers to characterize, in high temporal resolution, the emerging representation of object categories that underlie our capacity for rapid recognition. Shortly after stimulus onset, object exemplars cluster by category in a high-dimensional activation space in the brain. In this emerging activation space, the decodability of exemplar category varies over time, reflecting the brain’s transformation of visual inputs into coherent category representations. How do these emerging representations relate to categorization behavior? Recently it has been proposed that the distance of an exemplar representation from a categorical boundary in an activation space is critical for perceptual decision-making, and that reaction times should therefore correlate with distance from the boundary. The predictions of this distance hypothesis have been born out in human inferior temporal cortex (IT), an area of the brain crucial for the representation of object categories. When viewed in the context of a time varying neural signal, the optimal time to “read out” category information is when category representations in the brain are most decodable. Here, we show that the distance from a decision boundary through activation space, as measured using MEG decoding methods, correlates with reaction times for visual categorization during the period of peak decodability. Our results suggest that the brain begins to read out information about exemplar category at the optimal time for use in choice behaviour, and support the hypothesis that the structure of the representation for objects in the visual system is partially constitutive of the decision process in recognition. PMID:26107634
Veloz, Tomas; Desjardins, Sylvie
2015-01-01
Quantum models of concept combinations have been successful in representing various experimental situations that cannot be accommodated by traditional models based on classical probability or fuzzy set theory. In many cases, the focus has been on producing a representation that fits experimental results to validate quantum models. However, these representations are not always consistent with the cognitive modeling principles. Moreover, some important issues related to the representation of concepts such as the dimensionality of the realization space, the uniqueness of solutions, and the compatibility of measurements, have been overlooked. In this paper, we provide a dimensional analysis of the realization space for the two-sector Fock space model for conjunction of concepts focusing on the first and second sectors separately. We then introduce various representation of concepts that arise from the use of unitary operators in the realization space. In these concrete representations, a pair of concepts and their combination are modeled by a single conceptual state, and by a collection of exemplar-dependent operators. Therefore, they are consistent with cognitive modeling principles. This framework not only provides a uniform approach to model an entire data set, but, because all measurement operators are expressed in the same basis, allows us to address the question of compatibility of measurements. In particular, we present evidence that it may be possible to predict non-commutative effects from partial measurements of conceptual combinations. PMID:26617556
Veloz, Tomas; Desjardins, Sylvie
2015-01-01
Quantum models of concept combinations have been successful in representing various experimental situations that cannot be accommodated by traditional models based on classical probability or fuzzy set theory. In many cases, the focus has been on producing a representation that fits experimental results to validate quantum models. However, these representations are not always consistent with the cognitive modeling principles. Moreover, some important issues related to the representation of concepts such as the dimensionality of the realization space, the uniqueness of solutions, and the compatibility of measurements, have been overlooked. In this paper, we provide a dimensional analysis of the realization space for the two-sector Fock space model for conjunction of concepts focusing on the first and second sectors separately. We then introduce various representation of concepts that arise from the use of unitary operators in the realization space. In these concrete representations, a pair of concepts and their combination are modeled by a single conceptual state, and by a collection of exemplar-dependent operators. Therefore, they are consistent with cognitive modeling principles. This framework not only provides a uniform approach to model an entire data set, but, because all measurement operators are expressed in the same basis, allows us to address the question of compatibility of measurements. In particular, we present evidence that it may be possible to predict non-commutative effects from partial measurements of conceptual combinations.
Alpha-canonical form representation of the open loop dynamics of the Space Shuttle main engine
NASA Technical Reports Server (NTRS)
Duyar, Almet; Eldem, Vasfi; Merrill, Walter C.; Guo, Ten-Huei
1991-01-01
A parameter and structure estimation technique for multivariable systems is used to obtain a state space representation of open loop dynamics of the space shuttle main engine in alpha-canonical form. The parameterization being used is both minimal and unique. The simplified linear model may be used for fault detection studies and control system design and development.
Maximum entropy perception-action space: a Bayesian model of eye movement selection
NASA Astrophysics Data System (ADS)
Colas, Francis; Bessière, Pierre; Girard, Benoît
2011-03-01
In this article, we investigate the issue of the selection of eye movements in a free-eye Multiple Object Tracking task. We propose a Bayesian model of retinotopic maps with a complex logarithmic mapping. This model is structured in two parts: a representation of the visual scene, and a decision model based on the representation. We compare different decision models based on different features of the representation and we show that taking into account uncertainty helps predict the eye movements of subjects recorded in a psychophysics experiment. Finally, based on experimental data, we postulate that the complex logarithmic mapping has a functional relevance, as the density of objects in this space in more uniform than expected. This may indicate that the representation space and control strategies are such that the object density is of maximum entropy.
NASA Technical Reports Server (NTRS)
Helly, J. J., Jr.; Bates, W. V.; Cutler, M.; Kelem, S.
1984-01-01
A new representation of malfunction procedure logic which permits the automation of these procedures using Boolean normal forms is presented. This representation is discussed in the context of the development of an expert system for space shuttle flight control including software and hardware implementation modes, and a distributed architecture. The roles and responsibility of the flight control team as well as previous work toward the development of expert systems for flight control support at Johnson Space Center are discussed. The notion of malfunction procedures as graphs is introduced as well as the concept of hardware-equivalence.
Spatial Hyperschematia without Spatial Neglect after Insulo-Thalamic Disconnection
Saj, Arnaud; Wilcke, Juliane C.; Gschwind, Markus; Emond, Héloïse; Assal, Frédéric
2013-01-01
Different spatial representations are not stored as a single multipurpose map in the brain. Right brain-damaged patients can show a distortion, a compression of peripersonal and extrapersonal space. Here we report the case of a patient with a right insulo-thalamic disconnection without spatial neglect. The patient, compared with 10 healthy control subjects, showed a constant and reliable increase of her peripersonal and extrapersonal egocentric space representations - that we named spatial hyperschematia - yet left her allocentric space representations intact. This striking dissociation shows that our interactions with the surrounding world are represented and processed modularly in the human brain, depending on their frame of reference. PMID:24302992
de la Vega de León, Antonio; Bajorath, Jürgen
2016-09-01
The concept of chemical space is of fundamental relevance for medicinal chemistry and chemical informatics. Multidimensional chemical space representations are coordinate-based. Chemical space networks (CSNs) have been introduced as a coordinate-free representation. A computational approach is presented for the transformation of multidimensional chemical space into CSNs. The design of transformation CSNs (TRANS-CSNs) is based upon a similarity function that directly reflects distance relationships in original multidimensional space. TRANS-CSNs provide an immediate visualization of coordinate-based chemical space and do not require the use of dimensionality reduction techniques. At low network density, TRANS-CSNs are readily interpretable and make it possible to evaluate structure-activity relationship information originating from multidimensional chemical space.
Vector-based navigation using grid-like representations in artificial agents.
Banino, Andrea; Barry, Caswell; Uria, Benigno; Blundell, Charles; Lillicrap, Timothy; Mirowski, Piotr; Pritzel, Alexander; Chadwick, Martin J; Degris, Thomas; Modayil, Joseph; Wayne, Greg; Soyer, Hubert; Viola, Fabio; Zhang, Brian; Goroshin, Ross; Rabinowitz, Neil; Pascanu, Razvan; Beattie, Charlie; Petersen, Stig; Sadik, Amir; Gaffney, Stephen; King, Helen; Kavukcuoglu, Koray; Hassabis, Demis; Hadsell, Raia; Kumaran, Dharshan
2018-05-01
Deep neural networks have achieved impressive successes in fields ranging from object recognition to complex games such as Go 1,2 . Navigation, however, remains a substantial challenge for artificial agents, with deep neural networks trained by reinforcement learning 3-5 failing to rival the proficiency of mammalian spatial behaviour, which is underpinned by grid cells in the entorhinal cortex 6 . Grid cells are thought to provide a multi-scale periodic representation that functions as a metric for coding space 7,8 and is critical for integrating self-motion (path integration) 6,7,9 and planning direct trajectories to goals (vector-based navigation) 7,10,11 . Here we set out to leverage the computational functions of grid cells to develop a deep reinforcement learning agent with mammal-like navigational abilities. We first trained a recurrent network to perform path integration, leading to the emergence of representations resembling grid cells, as well as other entorhinal cell types 12 . We then showed that this representation provided an effective basis for an agent to locate goals in challenging, unfamiliar, and changeable environments-optimizing the primary objective of navigation through deep reinforcement learning. The performance of agents endowed with grid-like representations surpassed that of an expert human and comparison agents, with the metric quantities necessary for vector-based navigation derived from grid-like units within the network. Furthermore, grid-like representations enabled agents to conduct shortcut behaviours reminiscent of those performed by mammals. Our findings show that emergent grid-like representations furnish agents with a Euclidean spatial metric and associated vector operations, providing a foundation for proficient navigation. As such, our results support neuroscientific theories that see grid cells as critical for vector-based navigation 7,10,11 , demonstrating that the latter can be combined with path-based strategies to support navigation in challenging environments.
Marcus, Lars
2018-01-01
The world is witnessing unprecedented urbanization, bringing extreme challenges to contemporary practices in urban planning and design. This calls for improved urban models that can generate new knowledge and enhance practical skill. Importantly, any urban model embodies a conception of the relation between humans and the physical environment. In urban modeling this is typically conceived of as a relation between human subjects and an environmental object, thereby reproducing a humans-environment dichotomy. Alternative modeling traditions, such as space syntax that originates in architecture rather than geography, have tried to overcome this dichotomy. Central in this effort is the development of new representations of urban space, such as in the case of space syntax, the axial map. This form of representation aims to integrate both human behavior and the physical environment into one and the same description. Interestingly, models based on these representations have proved to better capture pedestrian movement than regular models. Pedestrian movement, as well as other kinds of human flows in urban space, is essential for urban modeling, since increasingly flows of this kind are understood as the driver in urban processes. Critical for a full understanding of space syntax modeling is the ontology of its' representations, such as the axial map. Space syntax theory here often refers to James Gibson's “Theory of affordances,” where the concept of affordances, in a manner similar to axial maps, aims to bridge the subject-object dichotomy by neither constituting physical properties of the environment or human behavior, but rather what emerges in the meeting between the two. In extension of this, the axial map can be interpreted as a representation of how the physical form of the environment affords human accessibility and visibility in urban space. This paper presents a close examination of the form of representations developed in space syntax methodology, in particular in the light of Gibson's “theory of affordances.“ The overarching aim is to contribute to a theoretical framework for urban models based on affordances, which may support the overcoming of the subject-object dichotomy in such models, here deemed essential for a greater social-ecological sustainability of cities. PMID:29731726
Expression-invariant representations of faces.
Bronstein, Alexander M; Bronstein, Michael M; Kimmel, Ron
2007-01-01
Addressed here is the problem of constructing and analyzing expression-invariant representations of human faces. We demonstrate and justify experimentally a simple geometric model that allows to describe facial expressions as isometric deformations of the facial surface. The main step in the construction of expression-invariant representation of a face involves embedding of the facial intrinsic geometric structure into some low-dimensional space. We study the influence of the embedding space geometry and dimensionality choice on the representation accuracy and argue that compared to its Euclidean counterpart, spherical embedding leads to notably smaller metric distortions. We experimentally support our claim showing that a smaller embedding error leads to better recognition.
Güçlü, Umut; van Gerven, Marcel A J
2017-01-15
Recently, deep neural networks (DNNs) have been shown to provide accurate predictions of neural responses across the ventral visual pathway. We here explore whether they also provide accurate predictions of neural responses across the dorsal visual pathway, which is thought to be devoted to motion processing and action recognition. This is achieved by training deep neural networks to recognize actions in videos and subsequently using them to predict neural responses while subjects are watching natural movies. Moreover, we explore whether dorsal stream representations are shared between subjects. In order to address this question, we examine if individual subject predictions can be made in a common representational space estimated via hyperalignment. Results show that a DNN trained for action recognition can be used to accurately predict how dorsal stream responds to natural movies, revealing a correspondence in representations of DNN layers and dorsal stream areas. It is also demonstrated that models operating in a common representational space can generalize to responses of multiple or even unseen individual subjects to novel spatio-temporal stimuli in both encoding and decoding settings, suggesting that a common representational space underlies dorsal stream responses across multiple subjects. Copyright © 2015 Elsevier Inc. All rights reserved.
14 CFR 77.69 - Limitations on appearance and representation.
Code of Federal Regulations, 2010 CFR
2010-01-01
... 14 Aeronautics and Space 2 2010-01-01 2010-01-01 false Limitations on appearance and representation. 77.69 Section 77.69 Aeronautics and Space FEDERAL AVIATION ADMINISTRATION, DEPARTMENT OF... personally consider the matter concerned or gain particular knowledge of it while he was an officer or...
14 CFR 77.69 - Limitations on appearance and representation.
Code of Federal Regulations, 2011 CFR
2011-01-01
... 14 Aeronautics and Space 2 2011-01-01 2011-01-01 false Limitations on appearance and representation. 77.69 Section 77.69 Aeronautics and Space FEDERAL AVIATION ADMINISTRATION, DEPARTMENT OF... showing that he did not personally consider the matter concerned or gain particular knowledge of it while...
Representation of magnetic fields in space
NASA Technical Reports Server (NTRS)
Stern, D. P.
1975-01-01
Several methods by which a magnetic field in space can be represented are reviewed with particular attention to problems of the observed geomagnetic field. Time dependence is assumed to be negligible, and five main classes of representation are described by vector potential, scalar potential, orthogonal vectors, Euler potentials, and expanded magnetic field.
Using Grid Cells for Navigation.
Bush, Daniel; Barry, Caswell; Manson, Daniel; Burgess, Neil
2015-08-05
Mammals are able to navigate to hidden goal locations by direct routes that may traverse previously unvisited terrain. Empirical evidence suggests that this "vector navigation" relies on an internal representation of space provided by the hippocampal formation. The periodic spatial firing patterns of grid cells in the hippocampal formation offer a compact combinatorial code for location within large-scale space. Here, we consider the computational problem of how to determine the vector between start and goal locations encoded by the firing of grid cells when this vector may be much longer than the largest grid scale. First, we present an algorithmic solution to the problem, inspired by the Fourier shift theorem. Second, we describe several potential neural network implementations of this solution that combine efficiency of search and biological plausibility. Finally, we discuss the empirical predictions of these implementations and their relationship to the anatomy and electrophysiology of the hippocampal formation. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.
NASA Technical Reports Server (NTRS)
Mennell, R. C.
1976-01-01
Experimental aerodynamic investigations were conducted on a sting mounted scale representation of the 140C outer mold line space shuttle orbiter configuration in the low speed wind tunnel. The primary test objectives were to define the orbiter landing gear system pressure loading and to record landing gear door and strut hingemoment levels. Secondary objectives included recording the aerodynamic influence of various landing gear configurations on orbiter force data as well as investigating 40 x 80 ft. Ames Wind Tunnel strut simulation effects on both orbiter landing gear loads and aerodynamic characteristics. Testing was conducted at a Mach number of 0.17, free stream dynamic pressure of 42.5 PSF, and Reynolds number per unit length of 1.2 million per foot. Angle of attack variation was 0 to 20 while yaw angles ranged from -10 to 10 deg.
Optical linear algebra processors - Architectures and algorithms
NASA Technical Reports Server (NTRS)
Casasent, David
1986-01-01
Attention is given to the component design and optical configuration features of a generic optical linear algebra processor (OLAP) architecture, as well as the large number of OLAP architectures, number representations, algorithms and applications encountered in current literature. Number-representation issues associated with bipolar and complex-valued data representations, high-accuracy (including floating point) performance, and the base or radix to be employed, are discussed, together with case studies on a space-integrating frequency-multiplexed architecture and a hybrid space-integrating and time-integrating multichannel architecture.
NASA Astrophysics Data System (ADS)
Tuller, Markus; Or, Dani
2001-05-01
Many models for hydraulic conductivity of partially saturated porous media rely on oversimplified representation of the pore space as a bundle of cylindrical capillaries and disregard flow in liquid films. Recent progress in modeling liquid behavior in angular pores of partially saturated porous media offers an alternative framework. We assume that equilibrium liquid-vapor interfaces provide well-defined and stable boundaries for slow laminar film and corner flow regimes in pore space comprised of angular pores connected to slit-shaped spaces. Knowledge of liquid configuration in the assumed geometry facilitates calculation of average liquid velocities in films and corners and enables derivation of pore-scale hydraulic conductivity as a function of matric potential. The pore-scale model is statistically upscaled to represent hydraulic conductivity for a sample of porous medium. Model parameters for the analytical sample-scale expressions are estimated from measured liquid retention data and other measurable medium properties. Model calculations illustrate the important role of film flow, whose contribution dominates capillary flow (in full pores and corners) at relatively high matric potentials (approximately -100 to -300 J kg-1, or -1 to 3 bars). The crossover region between film and capillary flow is marked by a significant change in the slope of the hydraulic conductivity function as often observed in measurements. Model predictions are compared with the widely applied van Genuchten-Mualem model and yield reasonable agreement with measured retention and hydraulic conductivity data over a wide range of soil textural classes.
Comparison of variational real-space representations of the kinetic energy operator
NASA Astrophysics Data System (ADS)
Skylaris, Chris-Kriton; Diéguez, Oswaldo; Haynes, Peter D.; Payne, Mike C.
2002-08-01
We present a comparison of real-space methods based on regular grids for electronic structure calculations that are designed to have basis set variational properties, using as a reference the conventional method of finite differences (a real-space method that is not variational) and the reciprocal-space plane-wave method which is fully variational. We find that a definition of the finite-difference method [P. Maragakis, J. Soler, and E. Kaxiras, Phys. Rev. B 64, 193101 (2001)] satisfies one of the two properties of variational behavior at the cost of larger errors than the conventional finite-difference method. On the other hand, a technique which represents functions in a number of plane waves which is independent of system size closely follows the plane-wave method and therefore also the criteria for variational behavior. Its application is only limited by the requirement of having functions strictly localized in regions of real space, but this is a characteristic of an increasing number of modern real-space methods, as they are designed to have a computational cost that scales linearly with system size.
Neurolinguistic approach to natural language processing with applications to medical text analysis.
Duch, Włodzisław; Matykiewicz, Paweł; Pestian, John
2008-12-01
Understanding written or spoken language presumably involves spreading neural activation in the brain. This process may be approximated by spreading activation in semantic networks, providing enhanced representations that involve concepts not found directly in the text. The approximation of this process is of great practical and theoretical interest. Although activations of neural circuits involved in representation of words rapidly change in time snapshots of these activations spreading through associative networks may be captured in a vector model. Concepts of similar type activate larger clusters of neurons, priming areas in the left and right hemisphere. Analysis of recent brain imaging experiments shows the importance of the right hemisphere non-verbal clusterization. Medical ontologies enable development of a large-scale practical algorithm to re-create pathways of spreading neural activations. First concepts of specific semantic type are identified in the text, and then all related concepts of the same type are added to the text, providing expanded representations. To avoid rapid growth of the extended feature space after each step only the most useful features that increase document clusterization are retained. Short hospital discharge summaries are used to illustrate how this process works on a real, very noisy data. Expanded texts show significantly improved clustering and may be classified with much higher accuracy. Although better approximations to the spreading of neural activations may be devised a practical approach presented in this paper helps to discover pathways used by the brain to process specific concepts, and may be used in large-scale applications.
TEXSYS. [a knowledge based system for the Space Station Freedom thermal control system test-bed
NASA Technical Reports Server (NTRS)
Bull, John
1990-01-01
The Systems Autonomy Demonstration Project has recently completed a major test and evaluation of TEXSYS, a knowledge-based system (KBS) which demonstrates real-time control and FDIR for the Space Station Freedom thermal control system test-bed. TEXSYS is the largest KBS ever developed by NASA and offers a unique opportunity for the study of technical issues associated with the use of advanced KBS concepts including: model-based reasoning and diagnosis, quantitative and qualitative reasoning, integrated use of model-based and rule-based representations, temporal reasoning, and scale-up performance issues. TEXSYS represents a major achievement in advanced automation that has the potential to significantly influence Space Station Freedom's design for the thermal control system. An overview of the Systems Autonomy Demonstration Project, the thermal control system test-bed, the TEXSYS architecture, preliminary test results, and thermal domain expert feedback are presented.
Benitez, P; Losada, J C; Benito, R M; Borondo, F
2015-10-01
A study of the dynamical characteristics of the phase space corresponding to the vibrations of the LiNC-LiCN molecule using an analysis based on the small alignment index (SALI) is presented. SALI is a good indicator of chaos that can easily determine whether a given trajectory is regular or chaotic regardless of the dimensionality of the system, and can also provide a wealth of dynamical information when conveniently implemented. In two-dimensional (2D) systems SALI maps are computed as 2D phase space representations, where the SALI asymptotic values are represented in color scale. We show here how these maps provide full information on the dynamical phase space structure of the LiNC-LiCN system, even quantifying numerically the volume of the different zones of chaos and regularity as a function of the molecule excitation energy.
Transductive multi-view zero-shot learning.
Fu, Yanwei; Hospedales, Timothy M; Xiang, Tao; Gong, Shaogang
2015-11-01
Most existing zero-shot learning approaches exploit transfer learning via an intermediate semantic representation shared between an annotated auxiliary dataset and a target dataset with different classes and no annotation. A projection from a low-level feature space to the semantic representation space is learned from the auxiliary dataset and applied without adaptation to the target dataset. In this paper we identify two inherent limitations with these approaches. First, due to having disjoint and potentially unrelated classes, the projection functions learned from the auxiliary dataset/domain are biased when applied directly to the target dataset/domain. We call this problem the projection domain shift problem and propose a novel framework, transductive multi-view embedding, to solve it. The second limitation is the prototype sparsity problem which refers to the fact that for each target class, only a single prototype is available for zero-shot learning given a semantic representation. To overcome this problem, a novel heterogeneous multi-view hypergraph label propagation method is formulated for zero-shot learning in the transductive embedding space. It effectively exploits the complementary information offered by different semantic representations and takes advantage of the manifold structures of multiple representation spaces in a coherent manner. We demonstrate through extensive experiments that the proposed approach (1) rectifies the projection shift between the auxiliary and target domains, (2) exploits the complementarity of multiple semantic representations, (3) significantly outperforms existing methods for both zero-shot and N-shot recognition on three image and video benchmark datasets, and (4) enables novel cross-view annotation tasks.
Project M: Scale Model of Lunar Landing Site of Apollo 17: Focus on Lighting Conditions and Analysis
NASA Technical Reports Server (NTRS)
Vanik, Christopher S.; Crain, Timothy P.
2010-01-01
This document captures the research and development of a scale model representation of the Apollo 17 landing site on the moon as part of the NASA INSPIRE program. Several key elements in this model were surface slope characteristics, crater sizes and locations, prominent rocks, and lighting conditions. This model supports development of Autonomous Landing and Hazard Avoidance Technology (ALHAT) and Project M for the GN&C Autonomous Flight Systems Branch. It will help project engineers visualize the landing site, and is housed in the building 16 Navigation Systems Technology Lab. The lead mentor was Dr. Timothy P. Crain. The purpose of this project was to develop an accurate scale representation of the Apollo 17 landing site on the moon. This was done on an 8'2.5"X10'1.375" reduced friction granite table, which can be restored to its previous condition if needed. The first step in this project was to research the best way to model and recreate the Apollo 17 landing site for the mockup. The project required a thorough plan, budget, and schedule, which was presented to the EG6 Branch for build approval. The final phase was to build the model. The project also required thorough research on the Apollo 17 landing site and the topography of the moon. This research was done on the internet and in person with Dean Eppler, a space scientist, from JSC KX. This data was used to analyze and calculate the scale of the mockup and the ratio of the sizes of the craters, ridges, etc. The final goal was to effectively communicate project status and demonstrate the multiple advantages of using our model. The conclusion of this project was that the mockup was completed as accurately as possible, and it successfully enables the Project M specialists to visualize and plan their goal on an accurate three dimensional surface representation.
Learning of Multimodal Representations With Random Walks on the Click Graph.
Wu, Fei; Lu, Xinyan; Song, Jun; Yan, Shuicheng; Zhang, Zhongfei Mark; Rui, Yong; Zhuang, Yueting
2016-02-01
In multimedia information retrieval, most classic approaches tend to represent different modalities of media in the same feature space. With the click data collected from the users' searching behavior, existing approaches take either one-to-one paired data (text-image pairs) or ranking examples (text-query-image and/or image-query-text ranking lists) as training examples, which do not make full use of the click data, particularly the implicit connections among the data objects. In this paper, we treat the click data as a large click graph, in which vertices are images/text queries and edges indicate the clicks between an image and a query. We consider learning a multimodal representation from the perspective of encoding the explicit/implicit relevance relationship between the vertices in the click graph. By minimizing both the truncated random walk loss as well as the distance between the learned representation of vertices and their corresponding deep neural network output, the proposed model which is named multimodal random walk neural network (MRW-NN) can be applied to not only learn robust representation of the existing multimodal data in the click graph, but also deal with the unseen queries and images to support cross-modal retrieval. We evaluate the latent representation learned by MRW-NN on a public large-scale click log data set Clickture and further show that MRW-NN achieves much better cross-modal retrieval performance on the unseen queries/images than the other state-of-the-art methods.
NASA Astrophysics Data System (ADS)
Santos, Léonard; Thirel, Guillaume; Perrin, Charles
2018-04-01
In many conceptual rainfall-runoff models, the water balance differential equations are not explicitly formulated. These differential equations are solved sequentially by splitting the equations into terms that can be solved analytically with a technique called operator splitting
. As a result, only the solutions of the split equations are used to present the different models. This article provides a methodology to make the governing water balance equations of a bucket-type rainfall-runoff model explicit and to solve them continuously. This is done by setting up a comprehensive state-space representation of the model. By representing it in this way, the operator splitting, which makes the structural analysis of the model more complex, could be removed. In this state-space representation, the lag functions (unit hydrographs), which are frequent in rainfall-runoff models and make the resolution of the representation difficult, are first replaced by a so-called Nash cascade
and then solved with a robust numerical integration technique. To illustrate this methodology, the GR4J model is taken as an example. The substitution of the unit hydrographs with a Nash cascade, even if it modifies the model behaviour when solved using operator splitting, does not modify it when the state-space representation is solved using an implicit integration technique. Indeed, the flow time series simulated by the new representation of the model are very similar to those simulated by the classic model. The use of a robust numerical technique that approximates a continuous-time model also improves the lag parameter consistency across time steps and provides a more time-consistent model with time-independent parameters.
Metropolitan natural area protection to maximize public access and species representation
Jane A. Ruliffson; Robert G. Haight; Paul H. Gobster; Frances R. Homans
2003-01-01
In response to widespread urban development, local governments in metropolitan areas in the United States acquire and protect privately-owned open space. We addressed the planner's problem of allocating a fixed budget for open space protection among eligible natural areas with the twin objectives of maximizing public access and species representation. Both...
NASA Technical Reports Server (NTRS)
Hwang, Chyi; Guo, Tong-Yi; Shieh, Leang-San
1991-01-01
A canonical state-space realization based on the multipoint Jordan continued-fraction expansion (CFE) is presented for single-input-single-output (SISO) systems. The similarity transformation matrix which relates the new canonical form to the phase-variable canonical form is also derived. The presented canonical state-space representation is particularly attractive for the application of SISO system theory in which a reduced-dimensional time-domain model is necessary.
Challenges of Representing Sub-Grid Physics in an Adaptive Mesh Refinement Atmospheric Model
NASA Astrophysics Data System (ADS)
O'Brien, T. A.; Johansen, H.; Johnson, J. N.; Rosa, D.; Benedict, J. J.; Keen, N. D.; Collins, W.; Goodfriend, E.
2015-12-01
Some of the greatest potential impacts from future climate change are tied to extreme atmospheric phenomena that are inherently multiscale, including tropical cyclones and atmospheric rivers. Extremes are challenging to simulate in conventional climate models due to existing models' coarse resolutions relative to the native length-scales of these phenomena. Studying the weather systems of interest requires an atmospheric model with sufficient local resolution, and sufficient performance for long-duration climate-change simulations. To this end, we have developed a new global climate code with adaptive spatial and temporal resolution. The dynamics are formulated using a block-structured conservative finite volume approach suitable for moist non-hydrostatic atmospheric dynamics. By using both space- and time-adaptive mesh refinement, the solver focuses computational resources only where greater accuracy is needed to resolve critical phenomena. We explore different methods for parameterizing sub-grid physics, such as microphysics, macrophysics, turbulence, and radiative transfer. In particular, we contrast the simplified physics representation of Reed and Jablonowski (2012) with the more complex physics representation used in the System for Atmospheric Modeling of Khairoutdinov and Randall (2003). We also explore the use of a novel macrophysics parameterization that is designed to be explicitly scale-aware.
Transformations and representations supporting spatial perspective taking
Yu, Alfred B.; Zacks, Jeffrey M.
2018-01-01
Spatial perspective taking is the ability to reason about spatial relations relative to another’s viewpoint. Here, we propose a mechanistic hypothesis that relates mental representations of one’s viewpoint to the transformations used for spatial perspective taking. We test this hypothesis using a novel behavioral paradigm that assays patterns of response time and variation in those patterns across people. The results support the hypothesis that people maintain a schematic representation of the space around their body, update that representation to take another’s perspective, and thereby to reason about the space around their body. This is a powerful computational mechanism that can support imitation, coordination of behavior, and observational learning. PMID:29545731
ERIC Educational Resources Information Center
Luxford, Cynthia J.; Bretz, Stacey Lowery
2014-01-01
Teachers use multiple representations to communicate the concepts of bonding, including Lewis structures, formulas, space-filling models, and 3D manipulatives. As students learn to interpret these multiple representations, they may develop misconceptions that can create problems in further learning of chemistry. Interviews were conducted with 28…
NASA Astrophysics Data System (ADS)
Kawamura, Katsunori
2009-03-01
We completely classify type III factor representations of Cuntz-Krieger algebras associated with quasi-free states up to unitary equivalence. Furthermore, we realize these representations on concrete Hilbert spaces without using GNS construction. Free groups and their type II1 factor representations are used in these realizations.
Incorporating linguistic knowledge for learning distributed word representations.
Wang, Yan; Liu, Zhiyuan; Sun, Maosong
2015-01-01
Combined with neural language models, distributed word representations achieve significant advantages in computational linguistics and text mining. Most existing models estimate distributed word vectors from large-scale data in an unsupervised fashion, which, however, do not take rich linguistic knowledge into consideration. Linguistic knowledge can be represented as either link-based knowledge or preference-based knowledge, and we propose knowledge regularized word representation models (KRWR) to incorporate these prior knowledge for learning distributed word representations. Experiment results demonstrate that our estimated word representation achieves better performance in task of semantic relatedness ranking. This indicates that our methods can efficiently encode both prior knowledge from knowledge bases and statistical knowledge from large-scale text corpora into a unified word representation model, which will benefit many tasks in text mining.
Incorporating Linguistic Knowledge for Learning Distributed Word Representations
Wang, Yan; Liu, Zhiyuan; Sun, Maosong
2015-01-01
Combined with neural language models, distributed word representations achieve significant advantages in computational linguistics and text mining. Most existing models estimate distributed word vectors from large-scale data in an unsupervised fashion, which, however, do not take rich linguistic knowledge into consideration. Linguistic knowledge can be represented as either link-based knowledge or preference-based knowledge, and we propose knowledge regularized word representation models (KRWR) to incorporate these prior knowledge for learning distributed word representations. Experiment results demonstrate that our estimated word representation achieves better performance in task of semantic relatedness ranking. This indicates that our methods can efficiently encode both prior knowledge from knowledge bases and statistical knowledge from large-scale text corpora into a unified word representation model, which will benefit many tasks in text mining. PMID:25874581
NASA Astrophysics Data System (ADS)
Riley, W. J.; Dwivedi, D.; Ghimire, B.; Hoffman, F. M.; Pau, G. S. H.; Randerson, J. T.; Shen, C.; Tang, J.; Zhu, Q.
2015-12-01
Numerical model representations of decadal- to centennial-scale soil-carbon dynamics are a dominant cause of uncertainty in climate change predictions. Recent attempts by some Earth System Model (ESM) teams to integrate previously unrepresented soil processes (e.g., explicit microbial processes, abiotic interactions with mineral surfaces, vertical transport), poor performance of many ESM land models against large-scale and experimental manipulation observations, and complexities associated with spatial heterogeneity highlight the nascent nature of our community's ability to accurately predict future soil carbon dynamics. I will present recent work from our group to develop a modeling framework to integrate pore-, column-, watershed-, and global-scale soil process representations into an ESM (ACME), and apply the International Land Model Benchmarking (ILAMB) package for evaluation. At the column scale and across a wide range of sites, observed depth-resolved carbon stocks and their 14C derived turnover times can be explained by a model with explicit representation of two microbial populations, a simple representation of mineralogy, and vertical transport. Integrating soil and plant dynamics requires a 'process-scaling' approach, since all aspects of the multi-nutrient system cannot be explicitly resolved at ESM scales. I will show that one approach, the Equilibrium Chemistry Approximation, improves predictions of forest nitrogen and phosphorus experimental manipulations and leads to very different global soil carbon predictions. Translating model representations from the site- to ESM-scale requires a spatial scaling approach that either explicitly resolves the relevant processes, or more practically, accounts for fine-resolution dynamics at coarser scales. To that end, I will present recent watershed-scale modeling work that applies reduced order model methods to accurately scale fine-resolution soil carbon dynamics to coarse-resolution simulations. Finally, we contend that creating believable soil carbon predictions requires a robust, transparent, and community-available benchmarking framework. I will present an ILAMB evaluation of several of the above-mentioned approaches in ACME, and attempt to motivate community adoption of this evaluation approach.
Role of Dentate Gyrus in Aligning Internal Spatial Map to External Landmark
ERIC Educational Resources Information Center
Lee, Jong Won; Kim, Woon Ryoung; Sun, Woong; Jung, Min Whan
2009-01-01
Humans and animals form internal representations of external space based on their own body movement (dead reckoning) as well as external landmarks. It is poorly understood, however, how different types of information are integrated to form a unified representation of external space. To examine the role of dentate gyrus (DG) in this process, we…
Time in the Mind: Using Space to Think about Time
ERIC Educational Resources Information Center
Casasanto, Daniel; Boroditsky, Lera
2008-01-01
How do we construct abstract ideas like justice, mathematics, or time-travel? In this paper we investigate whether mental representations that result from physical experience underlie people's more abstract mental representations, using the domains of space and time as a testbed. People often talk about time using spatial language (e.g., a "long"…
ERIC Educational Resources Information Center
Abrahamson, Dor
2006-01-01
This snapshot introduces a computer-based representation and activity that enables students to simultaneously "see" the combinatorial space of a stochastic device (e.g., dice, spinner, coins) and its outcome distribution. The author argues that the "ambiguous" representation fosters student insight into probability. [Snapshots are subject to peer…
ERIC Educational Resources Information Center
Aminu, Abdulhadi
2010-01-01
By rhotrix we understand an object that lies in some way between (n x n)-dimensional matrices and (2n - 1) x (2n - 1)-dimensional matrices. Representation of vectors in rhotrices is different from the representation of vectors in matrices. A number of vector spaces in matrices and their properties are known. On the other hand, little seems to be…
Using the Logarithm of Odds to Define a Vector Space on Probabilistic Atlases
Pohl, Kilian M.; Fisher, John; Bouix, Sylvain; Shenton, Martha; McCarley, Robert W.; Grimson, W. Eric L.; Kikinis, Ron; Wells, William M.
2007-01-01
The Logarithm of the Odds ratio (LogOdds) is frequently used in areas such as artificial neural networks, economics, and biology, as an alternative representation of probabilities. Here, we use LogOdds to place probabilistic atlases in a linear vector space. This representation has several useful properties for medical imaging. For example, it not only encodes the shape of multiple anatomical structures but also captures some information concerning uncertainty. We demonstrate that the resulting vector space operations of addition and scalar multiplication have natural probabilistic interpretations. We discuss several examples for placing label maps into the space of LogOdds. First, we relate signed distance maps, a widely used implicit shape representation, to LogOdds and compare it to an alternative that is based on smoothing by spatial Gaussians. We find that the LogOdds approach better preserves shapes in a complex multiple object setting. In the second example, we capture the uncertainty of boundary locations by mapping multiple label maps of the same object into the LogOdds space. Third, we define a framework for non-convex interpolations among atlases that capture different time points in the aging process of a population. We evaluate the accuracy of our representation by generating a deformable shape atlas that captures the variations of anatomical shapes across a population. The deformable atlas is the result of a principal component analysis within the LogOdds space. This atlas is integrated into an existing segmentation approach for MR images. We compare the performance of the resulting implementation in segmenting 20 test cases to a similar approach that uses a more standard shape model that is based on signed distance maps. On this data set, the Bayesian classification model with our new representation outperformed the other approaches in segmenting subcortical structures. PMID:17698403
Hoffmann, Susanne; Vega-Zuniga, Tomas; Greiter, Wolfgang; Krabichler, Quirin; Bley, Alexandra; Matthes, Mariana; Zimmer, Christiane; Firzlaff, Uwe; Luksch, Harald
2016-11-01
The midbrain superior colliculus (SC) commonly features a retinotopic representation of visual space in its superficial layers, which is congruent with maps formed by multisensory neurons and motor neurons in its deep layers. Information flow between layers is suggested to enable the SC to mediate goal-directed orienting movements. While most mammals strongly rely on vision for orienting, some species such as echolocating bats have developed alternative strategies, which raises the question how sensory maps are organized in these animals. We probed the visual system of the echolocating bat Phyllostomus discolor and found that binocular high acuity vision is frontally oriented and thus aligned with the biosonar system, whereas monocular visual fields cover a large area of peripheral space. For the first time in echolocating bats, we could show that in contrast with other mammals, visual processing is restricted to the superficial layers of the SC. The topographic representation of visual space, however, followed the general mammalian pattern. In addition, we found a clear topographic representation of sound azimuth in the deeper collicular layers, which was congruent with the superficial visual space map and with a previously documented map of orienting movements. Especially for bats navigating at high speed in densely structured environments, it is vitally important to transfer and coordinate spatial information between sensors and motor systems. Here, we demonstrate first evidence for the existence of congruent maps of sensory space in the bat SC that might serve to generate a unified representation of the environment to guide motor actions. © 2016 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.
The DTW-based representation space for seismic pattern classification
NASA Astrophysics Data System (ADS)
Orozco-Alzate, Mauricio; Castro-Cabrera, Paola Alexandra; Bicego, Manuele; Londoño-Bonilla, John Makario
2015-12-01
Distinguishing among the different seismic volcanic patterns is still one of the most important and labor-intensive tasks for volcano monitoring. This task could be lightened and made free from subjective bias by using automatic classification techniques. In this context, a core but often overlooked issue is the choice of an appropriate representation of the data to be classified. Recently, it has been suggested that using a relative representation (i.e. proximities, namely dissimilarities on pairs of objects) instead of an absolute one (i.e. features, namely measurements on single objects) is advantageous to exploit the relational information contained in the dissimilarities to derive highly discriminant vector spaces, where any classifier can be used. According to that motivation, this paper investigates the suitability of a dynamic time warping (DTW) dissimilarity-based vector representation for the classification of seismic patterns. Results show the usefulness of such a representation in the seismic pattern classification scenario, including analyses of potential benefits from recent advances in the dissimilarity-based paradigm such as the proper selection of representation sets and the combination of different dissimilarity representations that might be available for the same data.
The Deleuzian Concept of Structure and Quantum Mechanics
NASA Astrophysics Data System (ADS)
Christiaens, Wim A.
2014-03-01
Gilles Deleuze wanted a philosophy of nature in a pre-kantian almost archaic sense. A central concept in his philosophy is `multiplicity'. Although the concept is philosophical through and through, it has roots in the mathematical notion of manifold, specifically the state spaces for dynamical systems exhibiting non-linear behaviour. Deleuze was attracted to such mathematical structures because he believed they indicated a break with the dogmatic image of thought (the kind of thought that constrains itself into producing representations of reality conceived as particular things with strict borders, behaving and interacting according to invariant covering laws within space). However, even though it is true that a phase space representation of a physical entity is not a typical materialist picture of reality, it derives from a normal Euclidean representation, and can in principle be reduced to it. We want to argue that the real break happens with the quantum state space, and that Deleuze's typical description of a multiplicity fits even better with the quantum state space.
Free-energy landscape for cage breaking of three hard disks.
Hunter, Gary L; Weeks, Eric R
2012-03-01
We investigate cage breaking in dense hard-disk systems using a model of three Brownian disks confined within a circular corral. This system has a six-dimensional configuration space, but can be equivalently thought to explore a symmetric one-dimensional free-energy landscape containing two energy minima separated by an energy barrier. The exact free-energy landscape can be calculated as a function of system size by a direct enumeration of states. Results of simulations show the average time between cage breaking events follows an Arrhenius scaling when the energy barrier is large. We also discuss some of the consequences of using a one-dimensional representation to understand dynamics through a multidimensional space, such as diffusion acquiring spatial dependence and discontinuities in spatial derivatives of free energy.
NASA Technical Reports Server (NTRS)
Hughes, T.; Mennell, R.
1974-01-01
Experimental aerodynamic investigations were conducted on a stingmounted 0.0405-scale representation of the 140A/B space shuttle orbiter in a 7.75 by 11-Foot low speed wind tunnel from April 24 to April 26, 1974. Differential inboard/outboard elevon panel deflections with the 6-inch gap were investigated to determine outboard panel aileron effectiveness. The elevons were deflected from +20 degrees to -40 degrees in various combinations. Aerodynamic force and moment data for the orbiter were measured in the body axis system by an internally mounted, six-component strain gage balance. The model was sting mounted with the center of rotation located at F.S. 60.172. The angle of attack range was from -10 degrees to +24 degrees.
Orbital Debris Assesment Tesing in the AEDC Range G
NASA Technical Reports Server (NTRS)
Polk, Marshall; Woods, David; Roebuck, Brian; Opiela, John; Sheaffer, Patti; Liou, J.-C.
2015-01-01
The space environment presents many hazards for satellites and spacecraft. One of the major hazards is hypervelocity impacts from uncontrolled man-made space debris. Arnold Engineering Development Complex (AEDC), The National Aeronautics and Space Administration (NASA), The United States Air Force Space and Missile Systems Center (SMC), the University of Florida, and The Aerospace Corporation configured a large ballistic range to perform a series of hypervelocity destructive impact tests in order to better understand the effects of space collisions. The test utilized AEDC's Range G light gas launcher, which is capable of firing projectiles up to 7 km/s. A non-functional full-scale representation of a modern satellite called the DebriSat was destroyed in the enclosed range enviroment. Several modifications to the range facility were made to ensure quality data was obtained from the impact events. The facility modifcations were intended to provide a high impact energy to target mass ratio (>200 J/g), a non-damaging method of debris collection, and an instrumentation suite capable of providing information on the physics of the entire imapct event.
Spatial versus Tree Representations of Proximity Data.
ERIC Educational Resources Information Center
Pruzansky, Sandra; And Others
1982-01-01
Two-dimensional euclidean planes and additive trees are two of the most common representations of proximity data for multidimensional scaling. Guidelines for comparing these representations and discovering properties that could help identify which representation is more appropriate for a given data set are presented. (Author/JKS)
Linguistic and Perceptual Mapping in Spatial Representations: An Attentional Account.
Valdés-Conroy, Berenice; Hinojosa, José A; Román, Francisco J; Romero-Ferreiro, Verónica
2018-03-01
Building on evidence for embodied representations, we investigated whether Spanish spatial terms map onto the NEAR/FAR perceptual division of space. Using a long horizontal display, we measured congruency effects during the processing of spatial terms presented in NEAR or FAR space. Across three experiments, we manipulated the task demands in order to investigate the role of endogenous attention in linguistic and perceptual space mapping. We predicted congruency effects only when spatial properties were relevant for the task (reaching estimation task, Experiment 1) but not when attention was allocated to other features (lexical decision, Experiment 2; and color, Experiment 3). Results showed faster responses for words presented in Near-space in all experiments. Consistent with our hypothesis, congruency effects were observed only when a reaching estimate was requested. Our results add important evidence for the role of top-down processing in congruency effects from embodied representations of spatial terms. Copyright © 2017 Cognitive Science Society, Inc.
Analysis of genomic sequences by Chaos Game Representation.
Almeida, J S; Carriço, J A; Maretzek, A; Noble, P A; Fletcher, M
2001-05-01
Chaos Game Representation (CGR) is an iterative mapping technique that processes sequences of units, such as nucleotides in a DNA sequence or amino acids in a protein, in order to find the coordinates for their position in a continuous space. This distribution of positions has two properties: it is unique, and the source sequence can be recovered from the coordinates such that distance between positions measures similarity between the corresponding sequences. The possibility of using the latter property to identify succession schemes have been entirely overlooked in previous studies which raises the possibility that CGR may be upgraded from a mere representation technique to a sequence modeling tool. The distribution of positions in the CGR plane were shown to be a generalization of Markov chain probability tables that accommodates non-integer orders. Therefore, Markov models are particular cases of CGR models rather than the reverse, as currently accepted. In addition, the CGR generalization has both practical (computational efficiency) and fundamental (scale independence) advantages. These results are illustrated by using Escherichia coli K-12 as a test data-set, in particular, the genes thrA, thrB and thrC of the threonine operon.
Development of Multi-slice Analytical Tool to Support BIM-based Design Process
NASA Astrophysics Data System (ADS)
Atmodiwirjo, P.; Johanes, M.; Yatmo, Y. A.
2017-03-01
This paper describes the on-going development of computational tool to analyse architecture and interior space based on multi-slice representation approach that is integrated with Building Information Modelling (BIM). Architecture and interior space is experienced as a dynamic entity, which have the spatial properties that might be variable from one part of space to another, therefore the representation of space through standard architectural drawings is sometimes not sufficient. The representation of space as a series of slices with certain properties in each slice becomes important, so that the different characteristics in each part of space could inform the design process. The analytical tool is developed for use as a stand-alone application that utilises the data exported from generic BIM modelling tool. The tool would be useful to assist design development process that applies BIM, particularly for the design of architecture and interior spaces that are experienced as continuous spaces. The tool allows the identification of how the spatial properties change dynamically throughout the space and allows the prediction of the potential design problems. Integrating the multi-slice analytical tool in BIM-based design process thereby could assist the architects to generate better design and to avoid unnecessary costs that are often caused by failure to identify problems during design development stages.
The Information Is In the Maps: Representations & Algorithms for Mapping among Geometric Data
2015-09-30
space of all maps is a huge space and an important part of the project has addressed the problem of finding compact representations and encodings...understanding the relationships among its parts, or its connections to other data sets that may share the same or similar structure. Towards this end, we have...for the much smaller spaces of interesting maps within a specific application. The machinery developed here has proven of use across a broad spectrum
Cinematic representations of medical technologies in the Spanish official newsreel, 1943-1970.
Medina-Doménech, Rosa M; Menéndez-Navarro, Alfredo
2005-10-01
NO-DO, the Spanish official newsreel produced by Franco's dictatorship (1939-1975), held a 30-year monopoly over audio-visual information in Spain from 1943 to 1975. This paper reports on an analysis of coverage of medical technologies by the Spanish Cinematic Newsreel Service, NO-DO, from 1943 to 1970. The study focuses on the changing roles played by cultural representations of medical technologies deployed in NO-DO. Our analysis shows how these representations offered a new space for the legitimization of the regime, and, more importantly, played a key role in the attempts to construct and enforce a hegemonic national identity after the Spanish Civil War (1936-1939). During the period of isolationist autocracy that ended in the mid-1950s, the images of medical technologies reinforced the idea of a self-sufficient "national space" and deepened the break with the historical past. Once the international isolation of the regime was overcome in the late 1950s and the 1960s, the representation of medical technologies contributed to establishing a Spanish national identity that mirrored the outside world, the foreign space. Finally, gender representations in NO-DO are also explored.
NASA Astrophysics Data System (ADS)
Field, F.; Goodbun, J.; Watson, V.
Architects have a role to play in interplanetary space that has barely yet been explored. The architectural community is largely unaware of this new territory, for which there is still no agreed method of practice. There is moreover a general confusion, in scientific and related fields, over what architects might actually do there today. Current extra-planetary designs generally fail to explore the dynamic and relational nature of space-time, and often reduce human habitation to a purely functional problem. This is compounded by a crisis over the representation (drawing) of space-time. The present work returns to first principles of architecture in order to realign them with current socio-economic and technological trends surrounding the space industry. What emerges is simultaneously the basis for an ecological space architecture, and the representational strategies necessary to draw it. We explore this approach through a work of design-based research that describes the construction of Ocean; a huge body of water formed by the collision of two asteroids at the Translunar Lagrange Point (L2), that would serve as a site for colonisation, and as a resource to fuel future missions. Ocean is an experimental model for extra-planetary space design and its representation, within the autonomous discipline of architecture.
Beyond the Mental Number Line: A Neural Network Model of Number-Space Interactions
ERIC Educational Resources Information Center
Chen, Qi; Verguts, Tom
2010-01-01
It is commonly assumed that there is an interaction between the representations of number and space (e.g., [Dehaene et al., 1993] and [Walsh, 2003]), typically ascribed to a mental number line. The exact nature of this interaction has remained elusive, however. Here we propose that spatial aspects are not inherent to number representations, but…
Boccia, M; Piccardi, L; Palermo, L; Nemmi, F; Sulpizio, V; Galati, G; Guariglia, C
2014-09-05
Visual mental imagery is a process that draws on different cognitive abilities and is affected by the contents of mental images. Several studies have demonstrated that different brain areas subtend the mental imagery of navigational and non-navigational contents. Here, we set out to determine whether there are distinct representations for navigational and geographical images. Specifically, we used a Spatial Compatibility Task (SCT) to assess the mental representation of a familiar navigational space (the campus), a familiar geographical space (the map of Italy) and familiar objects (the clock). Twenty-one participants judged whether the vertical or the horizontal arrangement of items was correct. We found that distinct representational strategies were preferred to solve different categories on the SCT, namely, the horizontal perspective for the campus and the vertical perspective for the clock and the map of Italy. Furthermore, we found significant effects due to individual differences in the vividness of mental images and in preferences for verbal versus visual strategies, which selectively affect the contents of mental images. Our results suggest that imagining a familiar navigational space is somewhat different from imagining a familiar geographical space. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.
A study of kindergarten children's spatial representation in a mapping project
NASA Astrophysics Data System (ADS)
Davis, Genevieve A.; Hyun, Eunsook
2005-02-01
This phenomenological study examined kindergarten children's development of spatial representation in a year long mapping project. Findings and discussion relative to how children conceptualised and represented physical space are presented in light of theoretical notions advanced by Piaget, van Hiele, and cognitive science researchers Battista and Clements. Analyses of the processes the children used and their finished products indicate that children can negotiate meaning for complex systems of geometric concepts when given opportunities to debate, negotiate, reflect, evaluate and seek meaning for representing space. The complexity and "holistic" nature of spatial representation of young children emerged in this study.
Squeezed states: A geometric framework
NASA Technical Reports Server (NTRS)
Ali, S. T.; Brooke, J. A.; Gazeau, J.-P.
1992-01-01
A general definition of squeezed states is proposed and its main features are illustrated through a discussion of the standard optical coherent states represented by 'Gaussian pure states'. The set-up involves representations of groups on Hilbert spaces over homogeneous spaces of the group, and relies on the construction of a square integrable (coherent state) group representation modulo a subgroup. This construction depends upon a choice of a Borel section which has a certain permissible arbitrariness in its selection; this freedom is attributable to a squeezing of the defining coherent states of the representation, and corresponds in this way to a sort of gauging.
Noisy bases in Hilbert space: A new class of thermal coherent states and their properties
NASA Technical Reports Server (NTRS)
Vourdas, A.; Bishop, R. F.
1995-01-01
Coherent mixed states (or thermal coherent states) associated with the displaced harmonic oscillator at finite temperature, are introduced as a 'random' (or 'thermal' or 'noisy') basis in Hilbert space. A resolution of the identity for these states is proved and used to generalize the usual coherent state formalism for the finite temperature case. The Bargmann representation of an operator is introduced and its relation to the P and Q representations is studied. Generalized P and Q representations for the finite temperature case are also considered and several interesting relations among them are derived.
Multiscale skeletal representation of images via Voronoi diagrams
NASA Astrophysics Data System (ADS)
Marston, R. E.; Shih, Jian C.
1995-08-01
Polygonal approximations to skeletal or stroke-based representations of 2D objects may consume less storage and be sufficient to describe their shape for many applications. Multi- scale descriptions of object outlines are well established but corresponding methods for skeletal descriptions have been slower to develop. In this paper we offer a method of generating scale-based skeletal representation via the Voronoi diagram. The method has the advantages of less time complexity, a closer relationship between the skeletons at each scale and better control over simplification of the skeleton at lower scales. This is because the algorithm starts by generating the skeleton at the coarsest scale first, then it produces each finer scale, in an iterative manner, directly from the level below. The skeletal approximations produced by the algorithm also benefit from a strong relationship with the object outline, due to the structure of the Voronoi diagram.
Exploring the Phase Space of a System of Differential Equations: Different Mathematical Registers
ERIC Educational Resources Information Center
Dana-Picard, Thierry; Kidron, Ivy
2008-01-01
We describe and analyze a situation involving symbolic representation and graphical visualization of the solution of a system of two linear differential equations, using a computer algebra system. Symbolic solution and graphical representation complement each other. Graphical representation helps to understand the behavior of the symbolic…
NASA Technical Reports Server (NTRS)
Klumpar, D. M. (Principal Investigator)
1982-01-01
Progress made in reducing MAGSAT data and displaying magnetic field perturbations caused primarily by external currents is reported. A periodic and repeatable perturbation pattern is described that arises from external current effects but appears as unique signatures associated with upper middle latitudes on the Earth's surface. Initial testing of the modeling procedure that was developed to compute the magnetic fields at satellite orbit due to current distributions in the ionosphere and magnetosphere is also discussed. The modeling technique utilizes a linear current element representation of the large scale space current system.
Independent Component Analysis of Textures
NASA Technical Reports Server (NTRS)
Manduchi, Roberto; Portilla, Javier
2000-01-01
A common method for texture representation is to use the marginal probability densities over the outputs of a set of multi-orientation, multi-scale filters as a description of the texture. We propose a technique, based on Independent Components Analysis, for choosing the set of filters that yield the most informative marginals, meaning that the product over the marginals most closely approximates the joint probability density function of the filter outputs. The algorithm is implemented using a steerable filter space. Experiments involving both texture classification and synthesis show that compared to Principal Components Analysis, ICA provides superior performance for modeling of natural and synthetic textures.
Stereo-tomography in triangulated models
NASA Astrophysics Data System (ADS)
Yang, Kai; Shao, Wei-Dong; Xing, Feng-yuan; Xiong, Kai
2018-04-01
Stereo-tomography is a distinctive tomographic method. It is capable of estimating the scatterer position, the local dip of scatterer and the background velocity simultaneously. Building a geologically consistent velocity model is always appealing for applied and earthquake seismologists. Differing from the previous work to incorporate various regularization techniques into the cost function of stereo-tomography, we think extending stereo-tomography to the triangulated model will be the most straightforward way to achieve this goal. In this paper, we provided all the Fréchet derivatives of stereo-tomographic data components with respect to model components for slowness-squared triangulated model (or sloth model) in 2D Cartesian coordinate based on the ray perturbation theory for interfaces. A sloth model representation means a sparser model representation when compared with conventional B-spline model representation. A sparser model representation leads to a smaller scale of stereo-tomographic (Fréchet) matrix, a higher-accuracy solution when solving linear equations, a faster convergence rate and a lower requirement for quantity of data space. Moreover, a quantitative representation of interface strengthens the relationships among different model components, which makes the cross regularizations among these model components, such as node coordinates, scatterer coordinates and scattering angles, etc., more straightforward and easier to be implemented. The sensitivity analysis, the model resolution matrix analysis and a series of synthetic data examples demonstrate the correctness of the Fréchet derivatives, the applicability of the regularization terms and the robustness of the stereo-tomography in triangulated model. It provides a solid theoretical foundation for the real applications in the future.
Crottaz-Herbette, Sonia; Fornari, Eleonora; Notter, Michael P; Bindschaedler, Claire; Manzoni, Laura; Clarke, Stephanie
2017-09-01
Prismatic adaptation has been repeatedly reported to alleviate neglect symptoms; in normal subjects, it was shown to enhance the representation of the left visual space within the left inferior parietal cortex. Our study aimed to determine in humans whether similar compensatory mechanisms underlie the beneficial effect of prismatic adaptation in neglect. Fifteen patients with right hemispheric lesions and 11 age-matched controls underwent a prismatic adaptation session which was preceded and followed by fMRI using a visual detection task. In patients, the prismatic adaptation session improved the accuracy of target detection in the left and central space and enhanced the representation of this visual space within the left hemisphere in parts of the temporal convexity, inferior parietal lobule and prefrontal cortex. Across patients, the increase in neuronal activation within the temporal regions correlated with performance improvements in this visual space. In control subjects, prismatic adaptation enhanced the representation of the left visual space within the left inferior parietal lobule and decreased it within the left temporal cortex. Thus, a brief exposure to prismatic adaptation enhances, both in patients and in control subjects, the competence of the left hemisphere for the left space, but the regions extended beyond the inferior parietal lobule to the temporal convexity in patients. These results suggest that the left hemisphere provides compensatory mechanisms in neglect by assuming the representation of the whole space within the ventral attentional system. The rapidity of the change suggests that the underlying mechanism relies on uncovering pre-existing synaptic connections. Copyright © 2017 Elsevier Ltd. All rights reserved.
Neurolinguistic Approach to Natural Language Processing with Applications to Medical Text Analysis
Matykiewicz, Paweł; Pestian, John
2008-01-01
Understanding written or spoken language presumably involves spreading neural activation in the brain. This process may be approximated by spreading activation in semantic networks, providing enhanced representations that involve concepts that are not found directly in the text. Approximation of this process is of great practical and theoretical interest. Although activations of neural circuits involved in representation of words rapidly change in time snapshots of these activations spreading through associative networks may be captured in a vector model. Concepts of similar type activate larger clusters of neurons, priming areas in the left and right hemisphere. Analysis of recent brain imaging experiments shows the importance of the right hemisphere non-verbal clusterization. Medical ontologies enable development of a large-scale practical algorithm to re-create pathways of spreading neural activations. First concepts of specific semantic type are identified in the text, and then all related concepts of the same type are added to the text, providing expanded representations. To avoid rapid growth of the extended feature space after each step only the most useful features that increase document clusterization are retained. Short hospital discharge summaries are used to illustrate how this process works on a real, very noisy data. Expanded texts show significantly improved clustering and may be classified with much higher accuracy. Although better approximations to the spreading of neural activations may be devised a practical approach presented in this paper helps to discover pathways used by the brain to process specific concepts, and may be used in large-scale applications. PMID:18614334
Quantum groups, roots of unity and particles on quantized Anti-de Sitter space
DOE Office of Scientific and Technical Information (OSTI.GOV)
Steinacker, Harold
1997-05-23
Quantum groups in general and the quantum Anti-de Sitter group U q(so(2,3)) in particular are studied from the point of view of quantum field theory. The author shows that if q is a suitable root of unity, there exist finite-dimensional, unitary representations corresponding to essentially all the classical one-particle representations with (half) integer spin, with the same structure at low energies as in the classical case. In the massless case for spin ≥ 1, "naive" representations are unitarizable only after factoring out a subspace of "pure gauges", as classically. Unitary many-particle representations are defined, with the correct classical limit. Furthermore,more » the author identifies a remarkable element Q in the center of U q(g), which plays the role of a BRST operator in the case of U q(so(2,3)) at roots of unity, for any spin ≥ 1. The associated ghosts are an intrinsic part of the indecomposable representations. The author shows how to define an involution on algebras of creation and anihilation operators at roots of unity, in an example corresponding to non-identical particles. It is shown how nonabelian gauge fields appear naturally in this framework, without having to define connections on fiber bundles. Integration on Quantum Euclidean space and sphere and on Anti-de Sitter space is studied as well. The author gives a conjecture how Q can be used in general to analyze the structure of indecomposable representations, and to define a new, completely reducible associative (tensor) product of representations at roots of unity, which generalizes the standard "truncated" tensor product as well as many-particle representations.« less
Symbolic, Nonsymbolic and Conceptual: An Across-Notation Study on the Space Mapping of Numerals.
Zhang, Yu; You, Xuqun; Zhu, Rongjuan
2016-07-01
Previous studies suggested that there are interconnections between two numeral modalities of symbolic notation and nonsymbolic notation (array of dots), differences and similarities of the processing, and representation of the two modalities have both been found in previous research. However, whether there are differences between the spatial representation and numeral-space mapping of the two numeral modalities of symbolic notation and nonsymbolic notation is still uninvestigated. The present study aims to examine whether there are differences between the spatial representation and numeral-space mapping of the two numeral modalities of symbolic notation and nonsymbolic notation; especially how zero, as both a symbolic magnitude numeral and a nonsymbolic conceptual numeral, mapping onto space; and if the mapping happens automatically at an early stage of the numeral information processing. Results of the two experiments demonstrate that the low-level processing of symbolic numerals including zero and nonsymbolic numerals except zero can mapping onto space, whereas the low-level processing of nonsymbolic zero as a semantic conceptual numeral cannot mapping onto space, which indicating the specialty of zero in the numeral domain. The present study indicates that the processing of non-semantic numerals can mapping onto space, whereas semantic conceptual numerals cannot mapping onto space. © The Author(s) 2016.
Serino, Andrea; Canzoneri, Elisa; Marzolla, Marilena; di Pellegrino, Giuseppe; Magosso, Elisa
2015-01-01
Stimuli from different sensory modalities occurring on or close to the body are integrated in a multisensory representation of the space surrounding the body, i.e., peripersonal space (PPS). PPS dynamically modifies depending on experience, e.g., it extends after using a tool to reach far objects. However, the neural mechanism underlying PPS plasticity after tool use is largely unknown. Here we use a combined computational-behavioral approach to propose and test a possible mechanism accounting for PPS extension. We first present a neural network model simulating audio-tactile representation in the PPS around one hand. Simulation experiments showed that our model reproduced the main property of PPS neurons, i.e., selective multisensory response for stimuli occurring close to the hand. We used the neural network model to simulate the effects of a tool-use training. In terms of sensory inputs, tool use was conceptualized as a concurrent tactile stimulation from the hand, due to holding the tool, and an auditory stimulation from the far space, due to tool-mediated action. Results showed that after exposure to those inputs, PPS neurons responded also to multisensory stimuli far from the hand. The model thus suggests that synchronous pairing of tactile hand stimulation and auditory stimulation from the far space is sufficient to extend PPS, such as after tool-use. Such prediction was confirmed by a behavioral experiment, where we used an audio-tactile interaction paradigm to measure the boundaries of PPS representation. We found that PPS extended after synchronous tactile-hand stimulation and auditory-far stimulation in a group of healthy volunteers. Control experiments both in simulation and behavioral settings showed that the same amount of tactile and auditory inputs administered out of synchrony did not change PPS representation. We conclude by proposing a simple, biological-plausible model to explain plasticity in PPS representation after tool-use, which is supported by computational and behavioral data. PMID:25698947
Serino, Andrea; Canzoneri, Elisa; Marzolla, Marilena; di Pellegrino, Giuseppe; Magosso, Elisa
2015-01-01
Stimuli from different sensory modalities occurring on or close to the body are integrated in a multisensory representation of the space surrounding the body, i.e., peripersonal space (PPS). PPS dynamically modifies depending on experience, e.g., it extends after using a tool to reach far objects. However, the neural mechanism underlying PPS plasticity after tool use is largely unknown. Here we use a combined computational-behavioral approach to propose and test a possible mechanism accounting for PPS extension. We first present a neural network model simulating audio-tactile representation in the PPS around one hand. Simulation experiments showed that our model reproduced the main property of PPS neurons, i.e., selective multisensory response for stimuli occurring close to the hand. We used the neural network model to simulate the effects of a tool-use training. In terms of sensory inputs, tool use was conceptualized as a concurrent tactile stimulation from the hand, due to holding the tool, and an auditory stimulation from the far space, due to tool-mediated action. Results showed that after exposure to those inputs, PPS neurons responded also to multisensory stimuli far from the hand. The model thus suggests that synchronous pairing of tactile hand stimulation and auditory stimulation from the far space is sufficient to extend PPS, such as after tool-use. Such prediction was confirmed by a behavioral experiment, where we used an audio-tactile interaction paradigm to measure the boundaries of PPS representation. We found that PPS extended after synchronous tactile-hand stimulation and auditory-far stimulation in a group of healthy volunteers. Control experiments both in simulation and behavioral settings showed that the same amount of tactile and auditory inputs administered out of synchrony did not change PPS representation. We conclude by proposing a simple, biological-plausible model to explain plasticity in PPS representation after tool-use, which is supported by computational and behavioral data.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Liu, Yi-Chin; Fan, Jiwen; Zhang, Guang J.
2015-04-27
Following Part I, in which 3-D cloud-resolving model (CRM) simulations of a squall line and mesoscale convective complex in the mid-latitude continental and the tropical regions are conducted and evaluated, we examine the scale-dependence of eddy transport of water vapor, evaluate different eddy transport formulations, and improve the representation of convective transport across all scales by proposing a new formulation that more accurately represents the CRM-calculated eddy flux. CRM results show that there are strong grid-spacing dependencies of updraft and downdraft fractions regardless of altitudes, cloud life stage, and geographical location. As for the eddy transport of water vapor, updraftmore » eddy flux is a major contributor to total eddy flux in the lower and middle troposphere. However, downdraft eddy transport can be as large as updraft eddy transport in the lower atmosphere especially at the mature stage of 38 mid-latitude continental convection. We show that the single updraft approach significantly underestimates updraft eddy transport of water vapor because it fails to account for the large internal variability of updrafts, while a single downdraft represents the downdraft eddy transport of water vapor well. We find that using as few as 3 updrafts can account for the internal variability of updrafts well. Based on evaluation with the CRM simulated data, we recommend a simplified eddy transport formulation that considers three updrafts and one downdraft. Such formulation is similar to the conventional one but much more accurately represents CRM-simulated eddy flux across all grid scales.« less
Towards a multilevel cognitive probabilistic representation of space
NASA Astrophysics Data System (ADS)
Tapus, Adriana; Vasudevan, Shrihari; Siegwart, Roland
2005-03-01
This paper addresses the problem of perception and representation of space for a mobile agent. A probabilistic hierarchical framework is suggested as a solution to this problem. The method proposed is a combination of probabilistic belief with "Object Graph Models" (OGM). The world is viewed from a topological optic, in terms of objects and relationships between them. The hierarchical representation that we propose permits an efficient and reliable modeling of the information that the mobile agent would perceive from its environment. The integration of both navigational and interactional capabilities through efficient representation is also addressed. Experiments on a set of images taken from the real world that validate the approach are reported. This framework draws on the general understanding of human cognition and perception and contributes towards the overall efforts to build cognitive robot companions.
NASA Technical Reports Server (NTRS)
Hughes, M. T.; Mennell, R. C.
1974-01-01
Experimental aerodynamic investigations were conducted on an 0.015-scale representation of the integrated space shuttle launch vehicle in the trisonic wind tunnel. The primary test objective was to obtain subsonic and transonic elevon and bodyflap hinge moments and wing bending-torsion moments in the presence of the launch vehicle. Wing pressures were also recorded for the upper and lower right wing surfaces at two spanwise stations. The hinge moment, wing bending/torsion moments and wing pressure data were recorded over an angle-of-attack (alpha) range from -8 deg to +8 deg, and angle-of-sideslip (beta) range from -8 deg to +8 deg and at Mach numbers of 0.90, 1.12, 1.24 and 1.50. Tests were also conducted to determine the effects of the orbiter rear attach cross beam and the forward attach wedge and strut diameter. The orbiter alone was tested at 0.90 and 1.24 Mach number only.
Satellite Map of Port-au-Prince, Haiti-2010-Natural Color
Cole, Christopher J.; Sloan, Jeff
2010-01-01
The U.S. Geological Survey produced 1:24,000-scale post-earthquake image base maps incorporating high- and medium-resolution remotely sensed imagery following the 7.0 magnitude earthquake near the capital city of Port au Prince, Haiti, on January 12, 2010. Commercial 2.4-meter multispectral QuickBird imagery was acquired by DigitalGlobe on January 15, 2010, following the initial earthquake. Ten-meter multispectral ALOS AVNIR-2 imagery was collected by the Japanese Space Agency (JAXA) on January 12, 2010. These data were acquired under the Remote Sensing International Charter, a global team of space and satellite agencies that provide timely imagery in support of emergency response efforts worldwide. The images shown on this map were employed to support earthquake response efforts, specifically for use in determining ground deformation, damage assessment, and emergency management decisions. The raw, unprocessed imagery was geo-corrected, mosaicked, and reproduced onto a cartographic 1:24,000-scale base map. These maps are intended to provide a temporally current representation of post-earthquake ground conditions, which may be of use to decision makers and to the general public.
Satellite Map of Port-au-Prince, Haiti-2010-Infrared
Cole, Christopher J.; Sloan, Jeff
2010-01-01
The U.S. Geological Survey produced 1:24,000-scale post-earthquake image base maps incorporating high- and medium-resolution remotely sensed imagery following the 7.0 magnitude earthquake near the capital city of Port au Prince, Haiti, on January 12, 2010. Commercial 2.4-meter multispectral QuickBird imagery was acquired by DigitalGlobe on January 15, 2010, following the initial earthquake. Ten-meter multispectral ALOS AVNIR-2 imagery was collected by the Japanese Space Agency (JAXA) on January 12, 2010. These data were acquired under the Remote Sensing International Charter, a global team of space and satellite agencies that provide timely imagery in support of emergency response efforts worldwide. The images shown on this map were employed to support earthquake response efforts, specifically for use in determining ground deformation, damage assessment, and emergency management decisions. The raw, unprocessed imagery was geo-corrected, mosaicked, and reproduced onto a cartographic 1:24,000-scale base map. These maps are intended to provide a temporally current representation of post-earthquake ground conditions, which may be of use to decision makers and to the general public.
NASA Astrophysics Data System (ADS)
Orimo, Yuki; Sato, Takeshi; Scrinzi, Armin; Ishikawa, Kenichi L.
2018-02-01
We present a numerical implementation of the infinite-range exterior complex scaling [Scrinzi, Phys. Rev. A 81, 053845 (2010), 10.1103/PhysRevA.81.053845] as an efficient absorbing boundary to the time-dependent complete-active-space self-consistent field method [Sato, Ishikawa, Březinová, Lackner, Nagele, and Burgdörfer, Phys. Rev. A 94, 023405 (2016), 10.1103/PhysRevA.94.023405] for multielectron atoms subject to an intense laser pulse. We introduce Gauss-Laguerre-Radau quadrature points to construct discrete variable representation basis functions in the last radial finite element extending to infinity. This implementation is applied to strong-field ionization and high-harmonic generation in He, Be, and Ne atoms. It efficiently prevents unphysical reflection of photoelectron wave packets at the simulation boundary, enabling accurate simulations with substantially reduced computational cost, even under significant (≈50 % ) double ionization. For the case of a simulation of high-harmonic generation from Ne, for example, 80% cost reduction is achieved, compared to a mask-function absorption boundary.
Using Generative Representations to Evolve Robots. Chapter 1
NASA Technical Reports Server (NTRS)
Hornby, Gregory S.
2004-01-01
Recent research has demonstrated the ability of evolutionary algorithms to automatically design both the physical structure and software controller of real physical robots. One of the challenges for these automated design systems is to improve their ability to scale to the high complexities found in real-world problems. Here we claim that for automated design systems to scale in complexity they must use a representation which allows for the hierarchical creation and reuse of modules, which we call a generative representation. Not only is the ability to reuse modules necessary for functional scalability, but it is also valuable for improving efficiency in testing and construction. We then describe an evolutionary design system with a generative representation capable of hierarchical modularity and demonstrate it for the design of locomoting robots in simulation. Finally, results from our experiments show that evolution with our generative representation produces better robots than those evolved with a non-generative representation.
Similarity networks as a knowledge representation for space applications
NASA Technical Reports Server (NTRS)
Bailey, David; Thompson, Donna; Feinstein, Jerald
1987-01-01
Similarity networks are a powerful form of knowledge representation that are useful for many artificial intelligence applications. Similarity networks are used in applications ranging from information analysis and case based reasoning to machine learning and linking symbolic to neural processing. Strengths of similarity networks include simple construction, intuitive object storage, and flexible retrieval techniques that facilitate inferencing. Therefore, similarity networks provide great potential for space applications.
Development of the Representation of Space in Normal Children: The Drawing of a Village.
ERIC Educational Resources Information Center
Miljkovitch, M.
The purpose of this study is to show that there is a gradual and measurable development in the drawing of space representation concepts. A further purpose is to show that children's drawings of a village (which represent relations among concepts) may be a better measure of their conceptual maturity than their drawings of a man (which represent a…
NASA Astrophysics Data System (ADS)
Meyer, Harvey B.
2017-09-01
We present a Lorentz-covariant, Euclidean coordinate-space expression for the hadronic vacuum polarisation, the Adler function and the leading hadronic contribution to the anomalous magnetic moment of the muon. The representation offers a high degree of flexibility for an implementation in lattice QCD. We expect it to be particularly helpful for the quark-line disconnected contributions.
On the n-symplectic structure of faithful irreducible representations
NASA Astrophysics Data System (ADS)
Norris, L. K.
2017-04-01
Each faithful irreducible representation of an N-dimensional vector space V1 on an n-dimensional vector space V2 is shown to define a unique irreducible n-symplectic structure on the product manifold V1×V2 . The basic details of the associated Poisson algebra are developed for the special case N = n2, and 2n-dimensional symplectic submanifolds are shown to exist.
ERIC Educational Resources Information Center
Srinivasan, Mahesh; Carey, Susan
2010-01-01
When we describe time, we often use the language of space ("The movie was long"; "The deadline is approaching"). Experiments 1-3 asked whether--as patterns in language suggest--a structural similarity between representations of spatial length and temporal duration is easier to access than one between length and other dimensions of experience, such…
Biologically Plausible, Human-Scale Knowledge Representation.
Crawford, Eric; Gingerich, Matthew; Eliasmith, Chris
2016-05-01
Several approaches to implementing symbol-like representations in neurally plausible models have been proposed. These approaches include binding through synchrony (Shastri & Ajjanagadde, ), "mesh" binding (van der Velde & de Kamps, ), and conjunctive binding (Smolensky, ). Recent theoretical work has suggested that most of these methods will not scale well, that is, that they cannot encode structured representations using any of the tens of thousands of terms in the adult lexicon without making implausible resource assumptions. Here, we empirically demonstrate that the biologically plausible structured representations employed in the Semantic Pointer Architecture (SPA) approach to modeling cognition (Eliasmith, ) do scale appropriately. Specifically, we construct a spiking neural network of about 2.5 million neurons that employs semantic pointers to successfully encode and decode the main lexical relations in WordNet, which has over 100,000 terms. In addition, we show that the same representations can be employed to construct recursively structured sentences consisting of arbitrary WordNet concepts, while preserving the original lexical structure. We argue that these results suggest that semantic pointers are uniquely well-suited to providing a biologically plausible account of the structured representations that underwrite human cognition. Copyright © 2015 Cognitive Science Society, Inc.
Collins, Tom; Tillmann, Barbara; Barrett, Frederick S; Delbé, Charles; Janata, Petr
2014-01-01
Listeners' expectations for melodies and harmonies in tonal music are perhaps the most studied aspect of music cognition. Long debated has been whether faster response times (RTs) to more strongly primed events (in a music theoretic sense) are driven by sensory or cognitive mechanisms, such as repetition of sensory information or activation of cognitive schemata that reflect learned tonal knowledge, respectively. We analyzed over 300 stimuli from 7 priming experiments comprising a broad range of musical material, using a model that transforms raw audio signals through a series of plausible physiological and psychological representations spanning a sensory-cognitive continuum. We show that RTs are modeled, in part, by information in periodicity pitch distributions, chroma vectors, and activations of tonal space--a representation on a toroidal surface of the major/minor key relationships in Western tonal music. We show that in tonal space, melodies are grouped by their tonal rather than timbral properties, whereas the reverse is true for the periodicity pitch representation. While tonal space variables explained more of the variation in RTs than did periodicity pitch variables, suggesting a greater contribution of cognitive influences to tonal expectation, a stepwise selection model contained variables from both representations and successfully explained the pattern of RTs across stimulus categories in 4 of the 7 experiments. The addition of closure--a cognitive representation of a specific syntactic relationship--succeeded in explaining results from all 7 experiments. We conclude that multiple representational stages along a sensory-cognitive continuum combine to shape tonal expectations in music. (PsycINFO Database Record (c) 2014 APA, all rights reserved).
Self-organization of globally continuous and locally distributed information representation.
Wada, Koji; Kurata, Koji; Okada, Masato
2004-01-01
A number of findings suggest that the preferences of neighboring neurons in the inferior temporal (IT) cortex of macaque monkeys tend to be similar. However, a recent study reports convincingly that the preferences of neighboring neurons actually differ. These findings seem contradictory. To explain this conflict, we propose a new view of information representation in the IT cortex. This view takes into account sparse and local neuronal excitation. Since the excitation is sparse, information regarding visual objects seems to be encoded in a distributed manner. The local excitation of neurons coincides with the classical notion of a column structure. Our model consists of input layer and output layer. The main difference from conventional models is that the output layer has local and random intra-layer connections. In this paper, we adopt two rings embedded in three-dimensional space as an input signal space, and examine how resultant information representation depends on the distance between two rings that is denoted as D. We show that there exists critical value for the distance Dc. When D > Dc the output layer becomes able to form the column structure, this model can obtain the distributed representation within the column. While the output layer acquires the conventional information representation observed in the V1 cortex when D < Dc. Moreover, we consider the origin of the difference between information representation of the V1 cortex and that of the IT cortex. Our finding suggests that the difference in the information representations between the V1 and the IT cortices could be caused by difference between the input space structures.
Representations of the language recognition problem for a theorem prover
NASA Technical Reports Server (NTRS)
Minker, J.; Vanderbrug, G. J.
1972-01-01
Two representations of the language recognition problem for a theorem prover in first order logic are presented and contrasted. One of the representations is based on the familiar method of generating sentential forms of the language, and the other is based on the Cocke parsing algorithm. An augmented theorem prover is described which permits recognition of recursive languages. The state-transformation method developed by Cordell Green to construct problem solutions in resolution-based systems can be used to obtain the parse tree. In particular, the end-order traversal of the parse tree is derived in one of the representations. An inference system, termed the cycle inference system, is defined which makes it possible for the theorem prover to model the method on which the representation is based. The general applicability of the cycle inference system to state space problems is discussed. Given an unsatisfiable set S, where each clause has at most one positive literal, it is shown that there exists an input proof. The clauses for the two representations satisfy these conditions, as do many state space problems.
NASA Astrophysics Data System (ADS)
Saraceno, Marcos; Ermann, Leonardo; Cormick, Cecilia
2017-03-01
The problem of finding symmetric informationally complete positive-operator-valued-measures (SIC-POVMs) has been solved numerically for all dimensions d up to 67 [A. J. Scott and M. Grassl, J. Math. Phys. 51, 042203 (2010), 10.1063/1.3374022], but a general proof of existence is still lacking. For each dimension, it was shown that it is possible to find a SIC-POVM that is generated from a fiducial state upon application of the operators of the Heisenberg-Weyl group. We draw on the numerically determined fiducial states to study their phase-space features, as displayed by the characteristic function and the Wigner, Bargmann, and Husimi representations, adapted to a Hilbert space of finite dimension. We analyze the phase-space localization of fiducial states, and observe that the SIC-POVM condition is equivalent to a maximal delocalization property. Finally, we explore the consequences in phase space of the conjectured Zauner symmetry. In particular, we construct a Hermitian operator commuting with this symmetry that leads to a representation of fiducial states in terms of eigenfunctions with definite semiclassical features.
Nieder, Andreas; Miller, Earl K
2003-01-09
Whether cognitive representations are better conceived as language-based, symbolic representations or perceptually related, analog representations is a subject of debate. If cognitive processes parallel perceptual processes, then fundamental psychophysical laws should hold for each. To test this, we analyzed both behavioral and neuronal representations of numerosity in the prefrontal cortex of rhesus monkeys. The data were best described by a nonlinearly compressed scaling of numerical information, as postulated by the Weber-Fechner law or Stevens' law for psychophysical/sensory magnitudes. This nonlinear compression was observed on the neural level during the acquisition phase of the task and maintained through the memory phase with no further compression. These results suggest that certain cognitive and perceptual/sensory representations share the same fundamental mechanisms and neural coding schemes.
Rapid production of optimal-quality reduced-resolution representations of very large databases
Sigeti, David E.; Duchaineau, Mark; Miller, Mark C.; Wolinsky, Murray; Aldrich, Charles; Mineev-Weinstein, Mark B.
2001-01-01
View space representation data is produced in real time from a world space database representing terrain features. The world space database is first preprocessed. A database is formed having one element for each spatial region corresponding to a finest selected level of detail. A multiresolution database is then formed by merging elements and a strict error metric is computed for each element at each level of detail that is independent of parameters defining the view space. The multiresolution database and associated strict error metrics are then processed in real time for real time frame representations. View parameters for a view volume comprising a view location and field of view are selected. The error metric with the view parameters is converted to a view-dependent error metric. Elements with the coarsest resolution are chosen for an initial representation. Data set first elements from the initial representation data set are selected that are at least partially within the view volume. The first elements are placed in a split queue ordered by the value of the view-dependent error metric. If the number of first elements in the queue meets or exceeds a predetermined number of elements or whether the largest error metric is less than or equal to a selected upper error metric bound, the element at the head of the queue is force split and the resulting elements are inserted into the queue. Force splitting is continued until the determination is positive to form a first multiresolution set of elements. The first multiresolution set of elements is then outputted as reduced resolution view space data representing the terrain features.
Smart active pilot-in-the-loop systems
NASA Astrophysics Data System (ADS)
Thomas, Segun
1995-04-01
Representation of on-orbit microgravity environment in a 1-g environment is a continuing problem in space engineering analysis, procedures development and crew training. A way of adequately depicting weightlessness in the performance of on-orbit tasks is by a realistic (or real-time) computer based representation that provides the look, touch, and feel of on-orbit operation. This paper describes how a facility, the Systems Engineering Simulator at the Johnson Space Center, is utilizing recent advances in computer processing power and multi- processing capability to intelligently represent all systems, sub-systems and environmental elements associated with space flight operations. It first describes the computer hardware and interconnection between processors; the computer software responsible for task scheduling, health monitoring, sub-system and environment representation; control room and crew station. It then describes, the mathematical models that represent the dynamics of contact between the Mir and the Space Shuttle during the upcoming US and Russian Shuttle/Mir space mission. Results are presented comparing the response of the smart, active pilot-in-the-loop system to non-time critical CRAY model. A final example of how these systems are utilized is given in the development that supported the highly successful Hubble Space Telescope repair mission.
Dissipation and entropy production in open quantum systems
NASA Astrophysics Data System (ADS)
Majima, H.; Suzuki, A.
2010-11-01
A microscopic description of an open system is generally expressed by the Hamiltonian of the form: Htot = Hsys + Henviron + Hsys-environ. We developed a microscopic theory of entropy and derived a general formula, so-called "entropy-Hamiltonian relation" (EHR), that connects the entropy of the system to the interaction Hamiltonian represented by Hsys-environ for a nonequilibrium open quantum system. To derive the EHR formula, we mapped the open quantum system to the representation space of the Liouville-space formulation or thermo field dynamics (TFD), and thus worked on the representation space Script L := Script H otimes , where Script H denotes the ordinary Hilbert space while the tilde Hilbert space conjugates to Script H. We show that the natural transformation (mapping) of nonequilibrium open quantum systems is accomplished within the theoretical structure of TFD. By using the obtained EHR formula, we also derived the equation of motion for the distribution function of the system. We demonstrated that by knowing the microscopic description of the interaction, namely, the specific form of Hsys-environ on the representation space Script L, the EHR formulas enable us to evaluate the entropy of the system and to gain some information about entropy for nonequilibrium open quantum systems.
A New Algorithm with Plane Waves and Wavelets for Random Velocity Fields with Many Spatial Scales
NASA Astrophysics Data System (ADS)
Elliott, Frank W.; Majda, Andrew J.
1995-03-01
A new Monte Carlo algorithm for constructing and sampling stationary isotropic Gaussian random fields with power-law energy spectrum, infrared divergence, and fractal self-similar scaling is developed here. The theoretical basis for this algorithm involves the fact that such a random field is well approximated by a superposition of random one-dimensional plane waves involving a fixed finite number of directions. In general each one-dimensional plane wave is the sum of a random shear layer and a random acoustical wave. These one-dimensional random plane waves are then simulated by a wavelet Monte Carlo method for a single space variable developed recently by the authors. The computational results reported in this paper demonstrate remarkable low variance and economical representation of such Gaussian random fields through this new algorithm. In particular, the velocity structure function for an imcorepressible isotropic Gaussian random field in two space dimensions with the Kolmogoroff spectrum can be simulated accurately over 12 decades with only 100 realizations of the algorithm with the scaling exponent accurate to 1.1% and the constant prefactor accurate to 6%; in fact, the exponent of the velocity structure function can be computed over 12 decades within 3.3% with only 10 realizations. Furthermore, only 46,592 active computational elements are utilized in each realization to achieve these results for 12 decades of scaling behavior.
Partially massless fields during inflation
NASA Astrophysics Data System (ADS)
Baumann, Daniel; Goon, Garrett; Lee, Hayden; Pimentel, Guilherme L.
2018-04-01
The representation theory of de Sitter space allows for a category of partially massless particles which have no flat space analog, but could have existed during inflation. We study the couplings of these exotic particles to inflationary perturbations and determine the resulting signatures in cosmological correlators. When inflationary perturbations interact through the exchange of these fields, their correlation functions inherit scalings that cannot be mimicked by extra massive fields. We discuss in detail the squeezed limit of the tensor-scalar-scalar bispectrum, and show that certain partially massless fields can violate the tensor consistency relation of single-field inflation. We also consider the collapsed limit of the scalar trispectrum, and find that the exchange of partially massless fields enhances its magnitude, while giving no contribution to the scalar bispectrum. These characteristic signatures provide clean detection channels for partially massless fields during inflation.
NASA Astrophysics Data System (ADS)
Hixson, Laurie L.; Houts, Michael G.; Clement, Steven D.
2004-02-01
The extent to which, if any, full power ground nuclear testing of space reactors should be performed has been a point of discussion within the industry for decades. Do the benefits outweigh the risks? Are there equivalent alternatives? Can a test facility be constructed (or modified) in a reasonable amount of time? Is the test article an accurate representation of the flight system? Are the costs too restrictive? The obvious benefits of full power ground nuclear testing; obtaining systems integrated reliability data on a full-scale, complete end-to-end system; come at some programmatic risk. Safety related information is not obtained from a full-power ground nuclear test. This paper will discuss and assess these and other technical considerations essential in the decision to conduct full power ground nuclear-or alternative-tests.
Model Selection for Monitoring CO2 Plume during Sequestration
DOE Office of Scientific and Technical Information (OSTI.GOV)
2014-12-31
The model selection method developed as part of this project mainly includes four steps: (1) assessing the connectivity/dynamic characteristics of a large prior ensemble of models, (2) model clustering using multidimensional scaling coupled with k-mean clustering, (3) model selection using the Bayes' rule in the reduced model space, (4) model expansion using iterative resampling of the posterior models. The fourth step expresses one of the advantages of the method: it provides a built-in means of quantifying the uncertainty in predictions made with the selected models. In our application to plume monitoring, by expanding the posterior space of models, the finalmore » ensemble of representations of geological model can be used to assess the uncertainty in predicting the future displacement of the CO2 plume. The software implementation of this approach is attached here.« less
Large-Scale Modeling of Wordform Learning and Representation
ERIC Educational Resources Information Center
Sibley, Daragh E.; Kello, Christopher T.; Plaut, David C.; Elman, Jeffrey L.
2008-01-01
The forms of words as they appear in text and speech are central to theories and models of lexical processing. Nonetheless, current methods for simulating their learning and representation fail to approach the scale and heterogeneity of real wordform lexicons. A connectionist architecture termed the "sequence encoder" is used to learn…
Andersen, Lau M.
2018-01-01
An important aim of an analysis pipeline for magnetoencephalographic data is that it allows for the researcher spending maximal effort on making the statistical comparisons that will answer the questions of the researcher, while in turn spending minimal effort on the intricacies and machinery of the pipeline. I here present a set of functions and scripts that allow for setting up a clear, reproducible structure for separating raw and processed data into folders and files such that minimal effort can be spend on: (1) double-checking that the right input goes into the right functions; (2) making sure that output and intermediate steps can be accessed meaningfully; (3) applying operations efficiently across groups of subjects; (4) re-processing data if changes to any intermediate step are desirable. Applying the scripts requires only general knowledge about the Python language. The data analyses are neural responses to tactile stimulations of the right index finger in a group of 20 healthy participants acquired from an Elekta Neuromag System. Two analyses are presented: going from individual sensor space representations to, respectively, an across-group sensor space representation and an across-group source space representation. The processing steps covered for the first analysis are filtering the raw data, finding events of interest in the data, epoching data, finding and removing independent components related to eye blinks and heart beats, calculating participants' individual evoked responses by averaging over epoched data and calculating a grand average sensor space representation over participants. The second analysis starts from the participants' individual evoked responses and covers: estimating noise covariance, creating a forward model, creating an inverse operator, estimating distributed source activity on the cortical surface using a minimum norm procedure, morphing those estimates onto a common cortical template and calculating the patterns of activity that are statistically different from baseline. To estimate source activity, processing of the anatomy of subjects based on magnetic resonance imaging is necessary. The necessary steps are covered here: importing magnetic resonance images, segmenting the brain, estimating boundaries between different tissue layers, making fine-resolution scalp surfaces for facilitating co-registration, creating source spaces and creating volume conductors for each subject. PMID:29403349
Andersen, Lau M
2018-01-01
An important aim of an analysis pipeline for magnetoencephalographic data is that it allows for the researcher spending maximal effort on making the statistical comparisons that will answer the questions of the researcher, while in turn spending minimal effort on the intricacies and machinery of the pipeline. I here present a set of functions and scripts that allow for setting up a clear, reproducible structure for separating raw and processed data into folders and files such that minimal effort can be spend on: (1) double-checking that the right input goes into the right functions; (2) making sure that output and intermediate steps can be accessed meaningfully; (3) applying operations efficiently across groups of subjects; (4) re-processing data if changes to any intermediate step are desirable. Applying the scripts requires only general knowledge about the Python language. The data analyses are neural responses to tactile stimulations of the right index finger in a group of 20 healthy participants acquired from an Elekta Neuromag System. Two analyses are presented: going from individual sensor space representations to, respectively, an across-group sensor space representation and an across-group source space representation. The processing steps covered for the first analysis are filtering the raw data, finding events of interest in the data, epoching data, finding and removing independent components related to eye blinks and heart beats, calculating participants' individual evoked responses by averaging over epoched data and calculating a grand average sensor space representation over participants. The second analysis starts from the participants' individual evoked responses and covers: estimating noise covariance, creating a forward model, creating an inverse operator, estimating distributed source activity on the cortical surface using a minimum norm procedure, morphing those estimates onto a common cortical template and calculating the patterns of activity that are statistically different from baseline. To estimate source activity, processing of the anatomy of subjects based on magnetic resonance imaging is necessary. The necessary steps are covered here: importing magnetic resonance images, segmenting the brain, estimating boundaries between different tissue layers, making fine-resolution scalp surfaces for facilitating co-registration, creating source spaces and creating volume conductors for each subject.
Ordinal feature selection for iris and palmprint recognition.
Sun, Zhenan; Wang, Libin; Tan, Tieniu
2014-09-01
Ordinal measures have been demonstrated as an effective feature representation model for iris and palmprint recognition. However, ordinal measures are a general concept of image analysis and numerous variants with different parameter settings, such as location, scale, orientation, and so on, can be derived to construct a huge feature space. This paper proposes a novel optimization formulation for ordinal feature selection with successful applications to both iris and palmprint recognition. The objective function of the proposed feature selection method has two parts, i.e., misclassification error of intra and interclass matching samples and weighted sparsity of ordinal feature descriptors. Therefore, the feature selection aims to achieve an accurate and sparse representation of ordinal measures. And, the optimization subjects to a number of linear inequality constraints, which require that all intra and interclass matching pairs are well separated with a large margin. Ordinal feature selection is formulated as a linear programming (LP) problem so that a solution can be efficiently obtained even on a large-scale feature pool and training database. Extensive experimental results demonstrate that the proposed LP formulation is advantageous over existing feature selection methods, such as mRMR, ReliefF, Boosting, and Lasso for biometric recognition, reporting state-of-the-art accuracy on CASIA and PolyU databases.
NASA Astrophysics Data System (ADS)
Paramonov, P. V.; Vorontsov, A. M.; Kunitsyn, V. E.
2015-10-01
Numerical modeling of optical wave propagation in atmospheric turbulence is traditionally performed with using the so-called "split"-operator method, when the influence of the propagation medium's refractive index inhomogeneities is accounted for only within a system of infinitely narrow layers (phase screens) where phase is distorted. Commonly, under certain assumptions, such phase screens are considered as mutually statistically uncorrelated. However, in several important applications including laser target tracking, remote sensing, and atmospheric imaging, accurate optical field propagation modeling assumes upper limitations on interscreen spacing. The latter situation can be observed, for instance, in the presence of large-scale turbulent inhomogeneities or in deep turbulence conditions, where interscreen distances become comparable with turbulence outer scale and, hence, corresponding phase screens cannot be statistically uncorrelated. In this paper, we discuss correlated phase screens. The statistical characteristics of screens are calculated based on a representation of turbulent fluctuations of three-dimensional (3D) refractive index random field as a set of sequentially correlated 3D layers displaced in the wave propagation direction. The statistical characteristics of refractive index fluctuations are described in terms of the von Karman power spectrum density. In the representation of these 3D layers by corresponding phase screens, the geometrical optics approximation is used.
Semiclassical propagation: Hilbert space vs. Wigner representation
NASA Astrophysics Data System (ADS)
Gottwald, Fabian; Ivanov, Sergei D.
2018-03-01
A unified viewpoint on the van Vleck and Herman-Kluk propagators in Hilbert space and their recently developed counterparts in Wigner representation is presented. Based on this viewpoint, the Wigner Herman-Kluk propagator is conceptually the most general one. Nonetheless, the respective semiclassical expressions for expectation values in terms of the density matrix and the Wigner function are mathematically proven here to coincide. The only remaining difference is a mere technical flexibility of the Wigner version in choosing the Gaussians' width for the underlying coherent states beyond minimal uncertainty. This flexibility is investigated numerically on prototypical potentials and it turns out to provide neither qualitative nor quantitative improvements. Given the aforementioned generality, utilizing the Wigner representation for semiclassical propagation thus leads to the same performance as employing the respective most-developed (Hilbert-space) methods for the density matrix.
Multigrid one shot methods for optimal control problems: Infinite dimensional control
NASA Technical Reports Server (NTRS)
Arian, Eyal; Taasan, Shlomo
1994-01-01
The multigrid one shot method for optimal control problems, governed by elliptic systems, is introduced for the infinite dimensional control space. ln this case, the control variable is a function whose discrete representation involves_an increasing number of variables with grid refinement. The minimization algorithm uses Lagrange multipliers to calculate sensitivity gradients. A preconditioned gradient descent algorithm is accelerated by a set of coarse grids. It optimizes for different scales in the representation of the control variable on different discretization levels. An analysis which reduces the problem to the boundary is introduced. It is used to approximate the two level asymptotic convergence rate, to determine the amplitude of the minimization steps, and the choice of a high pass filter to be used when necessary. The effectiveness of the method is demonstrated on a series of test problems. The new method enables the solutions of optimal control problems at the same cost of solving the corresponding analysis problems just a few times.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Arendt, Dustin L.; Volkova, Svitlana
Analyzing and visualizing large amounts of social media communications and contrasting short-term conversation changes over time and geo-locations is extremely important for commercial and government applications. Earlier approaches for large-scale text stream summarization used dynamic topic models and trending words. Instead, we rely on text embeddings – low-dimensional word representations in a continuous vector space where similar words are embedded nearby each other. This paper presents ESTEEM,1 a novel tool for visualizing and evaluating spatiotemporal embeddings learned from streaming social media texts. Our tool allows users to monitor and analyze query words and their closest neighbors with an interactive interface.more » We used state-of- the-art techniques to learn embeddings and developed a visualization to represent dynamically changing relations between words in social media over time and other dimensions. This is the first interactive visualization of streaming text representations learned from social media texts that also allows users to contrast differences across multiple dimensions of the data.« less
Regularized Stokeslet representations for the flow around a human sperm
NASA Astrophysics Data System (ADS)
Ishimoto, Kenta; Gadelha, Hermes; Gaffney, Eamonn; Smith, David; Kirkman-Brown, Jackson
2017-11-01
The sperm flagellum does not simply push the sperm. We have established a new theoretical scheme for the dimensional reduction of swimming sperm dynamics, via high-frame-rate digital microscopy of a swimming human sperm cell. This has allowed the reconstruction of the flagellar waveform as a limit cycle in a phase space of PCA modes. With this waveform, boundary element numerical simulation has successfully captured fine-scale sperm swimming trajectories. Further analyses on the flow field around the cell has also demonstrated a pusher-type time-averaged flow, though the instantaneous flow field can temporarily vary in a more complicated manner - even pulling the sperm. Applying PCA to the flow field, we have further found that a small number of PCA modes explain the temporal patterns of the flow, whose core features are well approximated by a few regularized Stokeslets. Such representations provide a methodology for coarse-graining the time-dependent flow around a human sperm and other flagellar microorganisms for use in developing population level models that retain individual cell dynamics.
Re-presentations of space in Hollywood movies: an event-indexing analysis.
Cutting, James; Iricinschi, Catalina
2015-03-01
Popular movies present chunk-like events (scenes and subscenes) that promote episodic, serial updating of viewers' representations of the ongoing narrative. Event-indexing theory would suggest that the beginnings of new scenes trigger these updates, which in turn require more cognitive processing. Typically, a new movie event is signaled by an establishing shot, one providing more background information and a longer look than the average shot. Our analysis of 24 films reconfirms this. More important, we show that, when returning to a previously shown location, the re-establishing shot reduces both context and duration while remaining greater than the average shot. In general, location shifts dominate character and time shifts in event segmentation of movies. In addition, over the last 70 years re-establishing shots have become more like the noninitial shots of a scene. Establishing shots have also approached noninitial shot scales, but not their durations. Such results suggest that film form is evolving, perhaps to suit more rapid encoding of narrative events. Copyright © 2014 Cognitive Science Society, Inc.
A multiscale method for a robust detection of the default mode network
NASA Astrophysics Data System (ADS)
Baquero, Katherine; Gómez, Francisco; Cifuentes, Christian; Guldenmund, Pieter; Demertzi, Athena; Vanhaudenhuyse, Audrey; Gosseries, Olivia; Tshibanda, Jean-Flory; Noirhomme, Quentin; Laureys, Steven; Soddu, Andrea; Romero, Eduardo
2013-11-01
The Default Mode Network (DMN) is a resting state network widely used for the analysis and diagnosis of mental disorders. It is normally detected in fMRI data, but for its detection in data corrupted by motion artefacts or low neuronal activity, the use of a robust analysis method is mandatory. In fMRI it has been shown that the signal-to-noise ratio (SNR) and the detection sensitivity of neuronal regions is increased with di erent smoothing kernels sizes. Here we propose to use a multiscale decomposition based of a linear scale-space representation for the detection of the DMN. Three main points are proposed in this methodology: rst, the use of fMRI data at di erent smoothing scale-spaces, second, detection of independent neuronal components of the DMN at each scale by using standard preprocessing methods and ICA decomposition at scale-level, and nally, a weighted contribution of each scale by the Goodness of Fit measurement. This method was applied to a group of control subjects and was compared with a standard preprocesing baseline. The detection of the DMN was improved at single subject level and at group level. Based on these results, we suggest to use this methodology to enhance the detection of the DMN in data perturbed with artefacts or applied to subjects with low neuronal activity. Furthermore, the multiscale method could be extended for the detection of other resting state neuronal networks.
Sea-ice deformation in a coupled ocean-sea-ice model and in satellite remote sensing data
NASA Astrophysics Data System (ADS)
Spreen, Gunnar; Kwok, Ron; Menemenlis, Dimitris; Nguyen, An T.
2017-07-01
A realistic representation of sea-ice deformation in models is important for accurate simulation of the sea-ice mass balance. Simulated sea-ice deformation from numerical simulations with 4.5, 9, and 18 km horizontal grid spacing and a viscous-plastic (VP) sea-ice rheology are compared with synthetic aperture radar (SAR) satellite observations (RGPS, RADARSAT Geophysical Processor System) for the time period 1996-2008. All three simulations can reproduce the large-scale ice deformation patterns, but small-scale sea-ice deformations and linear kinematic features (LKFs) are not adequately reproduced. The mean sea-ice total deformation rate is about 40 % lower in all model solutions than in the satellite observations, especially in the seasonal sea-ice zone. A decrease in model grid spacing, however, produces a higher density and more localized ice deformation features. The 4.5 km simulation produces some linear kinematic features, but not with the right frequency. The dependence on length scale and probability density functions (PDFs) of absolute divergence and shear for all three model solutions show a power-law scaling behavior similar to RGPS observations, contrary to what was found in some previous studies. Overall, the 4.5 km simulation produces the most realistic divergence, vorticity, and shear when compared with RGPS data. This study provides an evaluation of high and coarse-resolution viscous-plastic sea-ice simulations based on spatial distribution, time series, and power-law scaling metrics.
Volkmann, Niels
2004-01-01
Reduced representation templates are used in a real-space pattern matching framework to facilitate automatic particle picking from electron micrographs. The procedure consists of five parts. First, reduced templates are constructed either from models or directly from the data. Second, a real-space pattern matching algorithm is applied using the reduced representations as templates. Third, peaks are selected from the resulting score map using peak-shape characteristics. Fourth, the surviving peaks are tested for distance constraints. Fifth, a correlation-based outlier screening is applied. Test applications to a data set of keyhole limpet hemocyanin particles indicate that the method is robust and reliable.
Wigner functions for nonparaxial, arbitrarily polarized electromagnetic wave fields in free space.
Alonso, Miguel A
2004-11-01
New representations are defined for describing electromagnetic wave fields in free space exactly in terms of rays for any wavelength, level of coherence or polarization, and numerical aperture, as long as there are no evanescent components. These representations correspond to tensors assigned to each ray such that the electric and magnetic energy densities, the Poynting vector, and the polarization properties of the field correspond to simple integrals involving these tensors for the rays that go through the specified point. For partially coherent fields, the ray-based approach provided by the new representations can reduce dramatically the computation times for the physical properties mentioned earlier.
Multigrid Methods in Electronic Structure Calculations
NASA Astrophysics Data System (ADS)
Briggs, Emil
1996-03-01
Multigrid techniques have become the method of choice for a broad range of computational problems. Their use in electronic structure calculations introduces a new set of issues when compared to traditional plane wave approaches. We have developed a set of techniques that address these issues and permit multigrid algorithms to be applied to the electronic structure problem in an efficient manner. In our approach the Kohn-Sham equations are discretized on a real-space mesh using a compact representation of the Hamiltonian. The resulting equations are solved directly on the mesh using multigrid iterations. This produces rapid convergence rates even for ill-conditioned systems with large length and/or energy scales. The method has been applied to both periodic and non-periodic systems containing over 400 atoms and the results are in very good agreement with both theory and experiment. Example applications include a vacancy in diamond, an isolated C60 molecule, and a 64-atom cell of GaN with the Ga d-electrons in valence which required a 250 Ry cutoff. A particular strength of a real-space multigrid approach is its ready adaptability to massively parallel computer architectures. The compact representation of the Hamiltonian is especially well suited to such machines. Tests on the Cray-T3D have shown nearly linear scaling of the execution time up to the maximum number of processors (512). The MPP implementation has been used for studies of a large Amyloid Beta Peptide (C_146O_45N_42H_210) found in the brains of Alzheimers disease patients. Further applications of the multigrid method will also be described. (in collaboration D. J. Sullivan and J. Bernholc)
Quantum mechanics on phase space: The hydrogen atom and its Wigner functions
NASA Astrophysics Data System (ADS)
Campos, P.; Martins, M. G. R.; Fernandes, M. C. B.; Vianna, J. D. M.
2018-03-01
Symplectic quantum mechanics (SQM) considers a non-commutative algebra of functions on a phase space Γ and an associated Hilbert space HΓ, to construct a unitary representation for the Galilei group. From this unitary representation the Schrödinger equation is rewritten in phase space variables and the Wigner function can be derived without the use of the Liouville-von Neumann equation. In this article the Coulomb potential in three dimensions (3D) is resolved completely by using the phase space Schrödinger equation. The Kustaanheimo-Stiefel(KS) transformation is applied and the Coulomb and harmonic oscillator potentials are connected. In this context we determine the energy levels, the amplitude of probability in phase space and correspondent Wigner quasi-distribution functions of the 3D-hydrogen atom described by Schrödinger equation in phase space.
Uncertainties in data-model comparisons: Spatio-temporal scales for past climates
NASA Astrophysics Data System (ADS)
Lohmann, G.
2016-12-01
Data-model comparisons are hindered by uncertainties like varying reservoir ages or potential seasonality bias of the recorder systems, but also due to the models' difficulty to represent the spatio-temporal variability patterns. For the Holocene we detect a sensitivity to horizontal resolution in the atmosphere, the representation of atmospheric dynamics, as well as the dynamics of the western boundary currents in the ocean. These features can create strong spatial heterogeneity in the North Atlantic and Pacific Oceans over long timescales (unlike a diffusive spatio-temporal scale separation). Futhermore, it is shown that such non-linear mechanisms could create a non-trivial response to seasonal insolation forcing via an atmospheric bridge inducing non-uniform temperature anomalies over the northern continents on multi-millennial time scales. Through the fluctuation-dissipation-theorem, climate variability and sensitivity are ultimately coupled. It is argued that some obvious biases between models and data may be linked to the missing key persistent component of the atmospheric dynamics, the North Atlantic blocking activity. It is shown that blocking is also linked to Atlantic multidecadal ocean variability and to extreme events. Interestingly, several proxies provide a measure of the frequency of extreme events, and a proper representation is a true challenge for climate models. Finally, case studies from deep paleo are presented in which changes in land-sea distribution or subscale parameterizations can cause relatively large effects on surface temperature. Such experiments can explore the phase space of solutions, but show the limitation of past climates to constrain climate sensitivity.
Navigating Mythic Space in the Digital Age
ERIC Educational Resources Information Center
Foley, Drew Thomas
2012-01-01
In prior ages, alternate worlds are associated with symbolic expressions of storied space, here termed "mythic space." The digital age brings new forms of virtual space that are co-existent with physical space. These virtual spaces may be understood as a contemporary representation of mythic space. This dissertation explores the paths by…
Marini, Francesco; Tagliabue, Chiara F; Sposito, Ambra V; Hernandez-Arieta, Alejandro; Brugger, Peter; Estévez, Natalia; Maravita, Angelo
2014-01-01
The way in which humans represent their own bodies is critical in guiding their interactions with the environment. To achieve successful body-space interactions, the body representation is strictly connected with that of the space immediately surrounding it through efficient visuo-tactile crossmodal integration. Such a body-space integrated representation is not fixed, but can be dynamically modulated by the use of external tools. Our study aims to explore the effect of using a complex tool, namely a functional prosthesis, on crossmodal visuo-tactile spatial interactions in healthy participants. By using the crossmodal visuo-tactile congruency paradigm, we found that prolonged training with a mechanical hand capable of distal hand movements and providing sensory feedback induces a pattern of interference, which is not observed after a brief training, between visual stimuli close to the prosthesis and touches on the body. These results suggest that after extensive, but not short, training the functional prosthesis acquires a visuo-tactile crossmodal representation akin to real limbs. This finding adds to previous evidence for the embodiment of functional prostheses in amputees, and shows that their use may also improve the crossmodal combination of somatosensory feedback delivered by the prosthesis with visual stimuli in the space around it, thus effectively augmenting the patients' visuomotor abilities. © 2013 Published by Elsevier Ltd.
Computing with scale-invariant neural representations
NASA Astrophysics Data System (ADS)
Howard, Marc; Shankar, Karthik
The Weber-Fechner law is perhaps the oldest quantitative relationship in psychology. Consider the problem of the brain representing a function f (x) . Different neurons have receptive fields that support different parts of the range, such that the ith neuron has a receptive field at xi. Weber-Fechner scaling refers to the finding that the width of the receptive field scales with xi as does the difference between the centers of adjacent receptive fields. Weber-Fechner scaling is exponentially resource-conserving. Neurophysiological evidence suggests that neural representations obey Weber-Fechner scaling in the visual system and perhaps other systems as well. We describe an optimality constraint that is solved by Weber-Fechner scaling, providing an information-theoretic rationale for this principle of neural coding. Weber-Fechner scaling can be generated within a mathematical framework using the Laplace transform. Within this framework, simple computations such as translation, correlation and cross-correlation can be accomplished. This framework can in principle be extended to provide a general computational language for brain-inspired cognitive computation on scale-invariant representations. Supported by NSF PHY 1444389 and the BU Initiative for the Physics and Mathematics of Neural Systems,.
Face-space architectures: evidence for the use of independent color-based features.
Nestor, Adrian; Plaut, David C; Behrmann, Marlene
2013-07-01
The concept of psychological face space lies at the core of many theories of face recognition and representation. To date, much of the understanding of face space has been based on principal component analysis (PCA); the structure of the psychological space is thought to reflect some important aspects of a physical face space characterized by PCA applications to face images. In the present experiments, we investigated alternative accounts of face space and found that independent component analysis provided the best fit to human judgments of face similarity and identification. Thus, our results challenge an influential approach to the study of human face space and provide evidence for the role of statistically independent features in face encoding. In addition, our findings support the use of color information in the representation of facial identity, and we thus argue for the inclusion of such information in theoretical and computational constructs of face space.
Multiple time-scales and the developmental dynamics of social systems
Flack, Jessica C.
2012-01-01
To build a theory of social complexity, we need to understand how aggregate social properties arise from individual interaction rules. Here, I review a body of work on the developmental dynamics of pigtailed macaque social organization and conflict management that provides insight into the mechanistic causes of multi-scale social systems. In this model system coarse-grained, statistical representations of collective dynamics are more predictive of the future state of the system than the constantly in-flux behavioural patterns at the individual level. The data suggest that individuals can perceive and use these representations for strategical decision-making. As an interaction history accumulates the coarse-grained representations consolidate. This constrains individual behaviour and provides the foundations for new levels of organization. The time-scales on which these representations change impact whether the consolidating higher-levels can be modified by individuals and collectively. The time-scales appear to be a function of the ‘coarseness’ of the representations and the character of the collective dynamics over which they are averages. The data suggest that an advantage of multiple timescales is that they allow social systems to balance tradeoffs between predictability and adaptability. I briefly discuss the implications of these findings for cognition, social niche construction and the evolution of new levels of organization in biological systems. PMID:22641819
Multiple time-scales and the developmental dynamics of social systems.
Flack, Jessica C
2012-07-05
To build a theory of social complexity, we need to understand how aggregate social properties arise from individual interaction rules. Here, I review a body of work on the developmental dynamics of pigtailed macaque social organization and conflict management that provides insight into the mechanistic causes of multi-scale social systems. In this model system coarse-grained, statistical representations of collective dynamics are more predictive of the future state of the system than the constantly in-flux behavioural patterns at the individual level. The data suggest that individuals can perceive and use these representations for strategical decision-making. As an interaction history accumulates the coarse-grained representations consolidate. This constrains individual behaviour and provides the foundations for new levels of organization. The time-scales on which these representations change impact whether the consolidating higher-levels can be modified by individuals and collectively. The time-scales appear to be a function of the 'coarseness' of the representations and the character of the collective dynamics over which they are averages. The data suggest that an advantage of multiple timescales is that they allow social systems to balance tradeoffs between predictability and adaptability. I briefly discuss the implications of these findings for cognition, social niche construction and the evolution of new levels of organization in biological systems.
Gao, Y Nina
2018-04-06
The Resource-Based Relative Value Scale Update Committee (RUC) submits recommended reimbursement values for physician work (wRVUs) under Medicare Part B. The RUC includes rotating representatives from medical specialties. To identify changes in physician reimbursements associated with RUC rotating seat representation. Relative Value Scale Update Committee members 1994-2013; Medicare Part B Relative Value Scale 1994-2013; Physician/Supplier Procedure Summary Master File 2007; Part B National Summary Data File 2000-2011. I match service and procedure codes to specialties using 2007 Medicare billing data. Subsequently, I model wRVUs as a function of RUC rotating committee representation and level of code specialization. An annual RUC rotating seat membership is associated with a statistically significant 3-5 percent increase in Medicare expenditures for codes billed to that specialty. For codes that are performed by a small number of physicians, the association between reimbursement and rotating subspecialty representation is positive, 0.177 (SE = 0.024). For codes that are performed by a large number of physicians, the association is negative, -0.183 (SE = 0.026). Rotating representation on the RUC is correlated with overall reimbursement rates. The resulting differential changes may exacerbate existing reimbursement discrepancies between generalist and specialist practitioners. © Health Research and Educational Trust.
A unified development of several techniques for the representation of random vectors and data sets
NASA Technical Reports Server (NTRS)
Bundick, W. T.
1973-01-01
Linear vector space theory is used to develop a general representation of a set of data vectors or random vectors by linear combinations of orthonormal vectors such that the mean squared error of the representation is minimized. The orthonormal vectors are shown to be the eigenvectors of an operator. The general representation is applied to several specific problems involving the use of the Karhunen-Loeve expansion, principal component analysis, and empirical orthogonal functions; and the common properties of these representations are developed.
ERIC Educational Resources Information Center
Bussey, Thomas J.
2013-01-01
Biochemistry education relies heavily on students' ability to visualize abstract cellular and molecular processes, mechanisms, and components. As such, biochemistry educators often turn to external representations to provide tangible, working models from which students' internal representations (mental models) can be constructed, evaluated, and…
Motor and linguistic linking of space and time in the cerebellum.
Oliveri, Massimiliano; Bonnì, Sonia; Turriziani, Patrizia; Koch, Giacomo; Lo Gerfo, Emanuele; Torriero, Sara; Vicario, Carmelo Mario; Petrosini, Laura; Caltagirone, Carlo
2009-11-20
Recent literature documented the presence of spatial-temporal interactions in the human brain. The aim of the present study was to verify whether representation of past and future is also mapped onto spatial representations and whether the cerebellum may be a neural substrate for linking space and time in the linguistic domain. We asked whether processing of the tense of a verb is influenced by the space where response takes place and by the semantics of the verb. Responses to past tense were facilitated in the left space while responses to future tense were facilitated in the right space. Repetitive transcranial magnetic stimulation (rTMS) of the right cerebellum selectively slowed down responses to future tense of action verbs; rTMS of both cerebellar hemispheres decreased accuracy of responses to past tense in the left space and to future tense in the right space for non-verbs, and to future tense in the right space for state verbs. The results suggest that representation of past and future is mapped onto spatial formats and that motor action could represent the link between spatial and temporal dimensions. Right cerebellar, left motor brain networks could be part of the prospective brain, whose primary function is to use past experiences to anticipate future events. Both cerebellar hemispheres could play a role in establishing the grammatical rules for verb conjugation.
Wavelet based free-form deformations for nonrigid registration
NASA Astrophysics Data System (ADS)
Sun, Wei; Niessen, Wiro J.; Klein, Stefan
2014-03-01
In nonrigid registration, deformations may take place on the coarse and fine scales. For the conventional B-splines based free-form deformation (FFD) registration, these coarse- and fine-scale deformations are all represented by basis functions of a single scale. Meanwhile, wavelets have been proposed as a signal representation suitable for multi-scale problems. Wavelet analysis leads to a unique decomposition of a signal into its coarse- and fine-scale components. Potentially, this could therefore be useful for image registration. In this work, we investigate whether a wavelet-based FFD model has advantages for nonrigid image registration. We use a B-splines based wavelet, as defined by Cai and Wang.1 This wavelet is expressed as a linear combination of B-spline basis functions. Derived from the original B-spline function, this wavelet is smooth, differentiable, and compactly supported. The basis functions of this wavelet are orthogonal across scales in Sobolev space. This wavelet was previously used for registration in computer vision, in 2D optical flow problems,2 but it was not compared with the conventional B-spline FFD in medical image registration problems. An advantage of choosing this B-splines based wavelet model is that the space of allowable deformation is exactly equivalent to that of the traditional B-spline. The wavelet transformation is essentially a (linear) reparameterization of the B-spline transformation model. Experiments on 10 CT lung and 18 T1-weighted MRI brain datasets show that wavelet based registration leads to smoother deformation fields than traditional B-splines based registration, while achieving better accuracy.
A Combined Eulerian-Lagrangian Data Representation for Large-Scale Applications.
Sauer, Franz; Xie, Jinrong; Ma, Kwan-Liu
2017-10-01
The Eulerian and Lagrangian reference frames each provide a unique perspective when studying and visualizing results from scientific systems. As a result, many large-scale simulations produce data in both formats, and analysis tasks that simultaneously utilize information from both representations are becoming increasingly popular. However, due to their fundamentally different nature, drawing correlations between these data formats is a computationally difficult task, especially in a large-scale setting. In this work, we present a new data representation which combines both reference frames into a joint Eulerian-Lagrangian format. By reorganizing Lagrangian information according to the Eulerian simulation grid into a "unit cell" based approach, we can provide an efficient out-of-core means of sampling, querying, and operating with both representations simultaneously. We also extend this design to generate multi-resolution subsets of the full data to suit the viewer's needs and provide a fast flow-aware trajectory construction scheme. We demonstrate the effectiveness of our method using three large-scale real world scientific datasets and provide insight into the types of performance gains that can be achieved.
A transparently scalable visualization architecture for exploring the universe.
Fu, Chi-Wing; Hanson, Andrew J
2007-01-01
Modern astronomical instruments produce enormous amounts of three-dimensional data describing the physical Universe. The currently available data sets range from the solar system to nearby stars and portions of the Milky Way Galaxy, including the interstellar medium and some extrasolar planets, and extend out to include galaxies billions of light years away. Because of its gigantic scale and the fact that it is dominated by empty space, modeling and rendering the Universe is very different from modeling and rendering ordinary three-dimensional virtual worlds at human scales. Our purpose is to introduce a comprehensive approach to an architecture solving this visualization problem that encompasses the entire Universe while seeking to be as scale-neutral as possible. One key element is the representation of model-rendering procedures using power scaled coordinates (PSC), along with various PSC-based techniques that we have devised to generalize and optimize the conventional graphics framework to the scale domains of astronomical visualization. Employing this architecture, we have developed an assortment of scale-independent modeling and rendering methods for a large variety of astronomical models, and have demonstrated scale-insensitive interactive visualizations of the physical Universe covering scales ranging from human scale to the Earth, to the solar system, to the Milky Way Galaxy, and to the entire observable Universe.
Srinivasan, Mahesh; Carey, Susan
2010-01-01
When we describe time, we often use the language of space (The movie was long; The deadline is approaching). Experiments 1–3 asked whether—as patterns in language suggest—a structural similarity between representations of spatial length and temporal duration is easier to access than one between length and other dimensions of experience, such as loudness. Adult participants were shown pairings of lines of different length with tones of different duration (Experiment 1) or tones of different loudness (Experiment 2). The length of the lines and duration or loudness of the tones was either positively or negatively correlated. Participants were better able to bind particular lengths and durations when they were positively correlated than when they were not, a pattern not observed for pairings of lengths and tone amplitudes, even after controlling for the presence of visual cues to duration in Experiment 1 (Experiment 3). This suggests that representations of length and duration may functionally overlap to a greater extent than representations of length and loudness. Experiments 4 and 5 asked whether experience with and mastery of words like long and short—which can flexibly refer to both space and time—itself creates this privileged relationship. Nine-month-old infants, like adults, were better able to bind representations of particular lengths and durations when these were positively correlated (Experiment 4), and failed to show this pattern for pairings of lengths and tone amplitudes (Experiment 5). We conclude that the functional overlap between representations of length and duration does not result from a metaphoric construction processes mediated by learning to flexibly use words such as long and short. We suggest instead that it may reflect an evolutionary recycling of spatial representations for more general purposes. PMID:20537324
Alchemical and structural distribution based representation for universal quantum machine learning
NASA Astrophysics Data System (ADS)
Faber, Felix A.; Christensen, Anders S.; Huang, Bing; von Lilienfeld, O. Anatole
2018-06-01
We introduce a representation of any atom in any chemical environment for the automatized generation of universal kernel ridge regression-based quantum machine learning (QML) models of electronic properties, trained throughout chemical compound space. The representation is based on Gaussian distribution functions, scaled by power laws and explicitly accounting for structural as well as elemental degrees of freedom. The elemental components help us to lower the QML model's learning curve, and, through interpolation across the periodic table, even enable "alchemical extrapolation" to covalent bonding between elements not part of training. This point is demonstrated for the prediction of covalent binding in single, double, and triple bonds among main-group elements as well as for atomization energies in organic molecules. We present numerical evidence that resulting QML energy models, after training on a few thousand random training instances, reach chemical accuracy for out-of-sample compounds. Compound datasets studied include thousands of structurally and compositionally diverse organic molecules, non-covalently bonded protein side-chains, (H2O)40-clusters, and crystalline solids. Learning curves for QML models also indicate competitive predictive power for various other electronic ground state properties of organic molecules, calculated with hybrid density functional theory, including polarizability, heat-capacity, HOMO-LUMO eigenvalues and gap, zero point vibrational energy, dipole moment, and highest vibrational fundamental frequency.
Classical and quantum cosmology of minimal massive bigravity
NASA Astrophysics Data System (ADS)
Darabi, F.; Mousavi, M.
2016-10-01
In a Friedmann-Robertson-Walker (FRW) space-time background we study the classical cosmological models in the context of recently proposed theory of nonlinear minimal massive bigravity. We show that in the presence of perfect fluid the classical field equations acquire contribution from the massive graviton as a cosmological term which is positive or negative depending on the dynamical competition between two scale factors of bigravity metrics. We obtain the classical field equations for flat and open universes in the ordinary and Schutz representation of perfect fluid. Focusing on the Schutz representation for flat universe, we find classical solutions exhibiting singularities at early universe with vacuum equation of state. Then, in the Schutz representation, we study the quantum cosmology for flat universe and derive the Schrodinger-Wheeler-DeWitt equation. We find its exact and wave packet solutions and discuss on their properties to show that the initial singularity in the classical solutions can be avoided by quantum cosmology. Similar to the study of Hartle-Hawking no-boundary proposal in the quantum cosmology of de Rham, Gabadadze and Tolley (dRGT) massive gravity, it turns out that the mass of graviton predicted by quantum cosmology of the minimal massive bigravity is large at early universe. This is in agreement with the fact that at early universe the cosmological constant should be large.
Lucky numbers: spatial neglect affects physical, but not representational, choices in a lotto task.
Loetscher, Tobias; Nicholls, Michael E R; Towse, John N; Bradshaw, John L; Brugger, Peter
2010-05-01
Spatial neglect can be characterized by a "magnetic attraction" towards the right side of a visual stimulus array and a selection of stimuli from that hemispace. This study examined whether these distinctive characteristics in visuo-motor space are also evident in representational number space. Given that numbers are thought to be represented along a left-to-right oriented mental number line, an affinity for the spontaneous selection of larger numbers was anticipated for neglect patients. Contrary to this expectation, neglect patients (n=20) picked a similar range of numbers compared to controls (n=17) when generating a number between 1000 and 10,000 and when playing an imaginary lottery game. There was, however, a positive correlation between the biases for the imaginary lottery, number generation and a number bisection task - demonstrating that exploration asymmetries along the mental number line are consistent within individuals across tasks. Some of the patients selected smaller numbers in all of these tasks, confirming reports of dissociations between physical and numerical-representational forms of neglect. Conversely, only four (20%) of the patients could reliably be classified as demonstrating a neglect in number space. When filling out a physical lottery ticket, the neglect patients showed the expected bias towards picking numbers placed on the right-hand side of the ticket. These results demonstrate that the magnetic attraction towards the right side of mental representations is rather weak and that representational forms of neglect only occasionally co-exist with neglect in physical space. Copyright 2009 Elsevier Srl. All rights reserved.
Navigation based on a sensorimotor representation: a virtual reality study
NASA Astrophysics Data System (ADS)
Zetzsche, Christoph; Galbraith, Christopher; Wolter, Johannes; Schill, Kerstin
2007-02-01
We investigate the hypothesis that the basic representation of space which underlies human navigation does not resemble an image-like map and is not restricted by the laws of Euclidean geometry. For this we developed a new experimental technique in which we use the properties of a virtual environment (VE) to directly influence the development of the representation. We compared the navigation performance of human observers under two conditions. Either the VE is consistent with the geometrical properties of physical space and could hence be represented in a map-like fashion, or it contains severe violations of Euclidean metric and planar topology, and would thus pose difficulties for the correct development of such a representation. Performance is not influenced by this difference, suggesting that a map-like representation is not the major basis of human navigation. Rather, the results are consistent with a representation which is similar to a non-planar graph augmented with path length information, or with a sensorimotor representation which combines sensory properties and motor actions. The latter may be seen as part of a revised view of perceptual processes due to recent results in psychology and neurobiology, which indicate that the traditional strict separation of sensory and motor systems is no longer tenable.
Wasserman, E A; Chakroff, A; Saxe, R; Young, L
2017-10-01
Characterizing how representations of moral violations are organized, cognitively and neurally, is central to understanding how people conceive and judge them. Past work has identified brain regions that represent morally relevant features and distinguish moral domains, but has not yet advanced a broader account of where and on what basis neural representations of moral violations are organized. With searchlight representational similarity analysis, we investigate where category membership drives similarity in neural patterns during moral judgment of violations from two key moral domains: Harm and Purity. Representations converge across domains in a network of regions resembling the mentalizing network. However, Harm and Purity violation representations respectively converge in different regions: precuneus (PC) and left inferior frontal gyrus (LIFG). Examining substructure within moral domains, Harm violations converge in PC regardless of subdomain (physical harms, psychological harms), while Purity subdomains (pathogen-related violations, sex-related violations) converge in distinct sets of regions - mirroring a dissociation observed in principal-component analysis of behavioral data. Further, we find initial evidence for representation of morally relevant features within these two domain-encoding regions. The present analyses offer a case study for understanding how organization within the complex conceptual space of moral violations is reflected in the organization of neural patterns across the cortex. Copyright © 2017 Elsevier Inc. All rights reserved.
Representation of solution for fully nonlocal diffusion equations with deviation time variable
NASA Astrophysics Data System (ADS)
Drin, I. I.; Drin, S. S.; Drin, Ya. M.
2018-01-01
We prove the solvability of the Cauchy problem for a nonlocal heat equation which is of fractional order both in space and time. The representation formula for classical solutions for time- and space- fractional partial differential operator Dat + a2 (-Δ) γ/2 (0 <= α <= 1, γ ɛ (0, 2]) and deviation time variable is given in terms of the Fox H-function, using the step by step method.
Hyperfunction solutions of the zero rest mass equations and representations of LIE groups
DOE Office of Scientific and Technical Information (OSTI.GOV)
Dunne, E.G.
1984-01-01
Recently, hyperfunctions have arisen in an essential way in separate results in mathematical physics and in representation theory. In the setting of the twistor program, Wells, with others, has extended the Penrose transform to hyperfunction solutions of the zero rest mass equations, showing that the fundamental isomorphisms hold for this larger space. Meanwhile, Schmid has shown the existence of a canonical globalization of a Harish-Chandra module, V, to a representation of the group. This maximal globalization may be realized as the completion of V in a locally convex vector space in the hyperfunction topology. This thesis shows that the formermore » is a particular case of the latter where the globalization can be done by hand. This explicit globalization is then carried out for a more general case of the Radon transform on homogeneous spaces.« less
A Hilbert Space Representation of Generalized Observables and Measurement Processes in the ESR Model
NASA Astrophysics Data System (ADS)
Sozzo, Sandro; Garola, Claudio
2010-12-01
The extended semantic realism ( ESR) model recently worked out by one of the authors embodies the mathematical formalism of standard (Hilbert space) quantum mechanics in a noncontextual framework, reinterpreting quantum probabilities as conditional instead of absolute. We provide here a Hilbert space representation of the generalized observables introduced by the ESR model that satisfy a simple physical condition, propose a generalization of the projection postulate, and suggest a possible mathematical description of the measurement process in terms of evolution of the compound system made up of the measured system and the measuring apparatus.
Summary of Cumulus Parameterization Workshop
NASA Technical Reports Server (NTRS)
Tao, Wei-Kuo; Starr, David OC.; Hou, Arthur; Newman, Paul; Sud, Yogesh
2002-01-01
A workshop on cumulus parameterization took place at the NASA Goddard Space Flight Center from December 3-5, 2001. The major objectives of this workshop were (1) to review the problem of representation of moist processes in large-scale models (mesoscale models, Numerical Weather Prediction models and Atmospheric General Circulation Models), (2) to review the state-of-the-art in cumulus parameterization schemes, and (3) to discuss the need for future research and applications. There were a total of 31 presentations and about 100 participants from the United States, Japan, the United Kingdom, France and South Korea. The specific presentations and discussions during the workshop are summarized in this paper.
Automatic rock detection for in situ spectroscopy applications on Mars
NASA Astrophysics Data System (ADS)
Mahapatra, Pooja; Foing, Bernard H.
A novel algorithm for rock detection has been developed for effectively utilising Mars rovers, and enabling autonomous selection of target rocks that require close-contact spectroscopic measurements. The algorithm demarcates small rocks in terrain images as seen by cameras on a Mars rover during traverse. This information may be used by the rover for selection of geologically relevant sample rocks, and (in conjunction with a rangefinder) to pick up target samples using a robotic arm for automatic in situ determination of rock composition and mineralogy using, for example, a Raman spectrometer. Determining rock samples within the region that are of specific interest without physically approaching them significantly reduces time, power and risk. Input images in colour are converted to greyscale for intensity analysis. Bilateral filtering is used for texture removal while preserving rock boundaries. Unsharp masking is used for contrast enhance-ment. Sharp contrasts in intensities are detected using Canny edge detection, with thresholds that are calculated from the image obtained after contrast-limited adaptive histogram equalisation of the unsharp masked image. Scale-space representations are then generated by convolving this image with a Gaussian kernel. A scale-invariant blob detector (Laplacian of the Gaussian, LoG) detects blobs independently of their sizes, and therefore requires a multi-scale approach with automatic scale se-lection. The scale-space blob detector consists of convolution of the Canny edge-detected image with a scale-normalised LoG at several scales, and finding the maxima of squared LoG response in scale-space. After the extraction of local intensity extrema, the intensity profiles along rays going out of the local extremum are investigated. An ellipse is fitted to the region determined by significant changes in the intensity profiles. The fitted ellipses are overlaid on the original Mars terrain image for a visual estimation of the rock detection accuracy, and the number of ellipses are counted. Since geometry and illumination have the least effect on small rocks, the proposed algorithm is effective in detecting small rocks (or bigger rocks at larger distances from the camera) that consist of a small fraction of image pixels. Acknowledgements: The first author would like to express her gratitude to the European Space Agency (ESA/ESTEC) and the International Lunar Exploration Working Group (ILEWG) for their support of this work.
Quantum dressing orbits on compact groups
NASA Astrophysics Data System (ADS)
Jurčo, Branislav; Šťovíček, Pavel
1993-02-01
The quantum double is shown to imply the dressing transformation on quantum compact groups and the quantum Iwasawa decompositon in the general case. Quantum dressing orbits are described explicitly as *-algebras. The dual coalgebras consisting of differential operators are related to the quantum Weyl elements. Besides, the differential geometry on a quantum leaf allows a remarkably simple construction of irreducible *-representations of the algebras of quantum functions. Representation spaces then consist of analytic functions on classical phase spaces. These representations are also interpreted in the framework of quantization in the spirit of Berezin applied to symplectic leaves on classical compact groups. Convenient “coherent states” are introduced and a correspondence between classical and quantum observables is given.
Progress in knowledge representation research
NASA Technical Reports Server (NTRS)
Lum, Henry
1985-01-01
Brief descriptions are given of research being carried out in the field of knowledge representation. Dynamic simulation and modelling of planning systems with real-time sensor inputs; development of domain-independent knowledge representation tools which can be used in the development of application-specific expert and planning systems; and development of a space-borne very high speed integrated circuit processor are among the projects discussed.
Representations of Shape in Object Recognition and Long-Term Visual Memory
1993-02-11
in anything other than linguistic terms ( Biederman , 1987 , for example). STATUS 1. Viewpoint-Dependent Features in Object Representation Tarr and...is object- based orientation-independent representations sufficient for "basic-level" categorization ( Biederman , 1987 ; Corballis, 1988). Alternatively...space. REFERENCES Biederman , I. ( 1987 ). Recognition-by-components: A theory of human image understanding. Psychological Review, 94,115-147. Cooper, L
The electrostatic persistence length of polymers beyond the OSF limit.
Everaers, R; Milchev, A; Yamakov, V
2002-05-01
We use large-scale Monte Carlo simulations to test scaling theories for the electrostatic persistence length l(e) of isolated, uniformly charged polymers with Debye-Hückel intrachain interactions in the limit where the screening length kappa(-1) exceeds the intrinsic persistence length of the chains. Our simulations cover a significantly larger part of the parameter space than previous studies. We observe no significant deviations from the prediction l(e) proportional to kappa(-2) by Khokhlov and Khachaturian which is based on applying the Odijk-Skolnick-Fixman theories of electrostatic bending rigidity and electrostatically excluded volume to the stretched de Gennes-Pincus-Velasco-Brochard polyelectrolyte blob chain. A linear or sublinear dependence of the persistence length on the screening length can be ruled out. We show that previous results pointing into this direction are due to a combination of excluded-volume and finite chain length effects. The paper emphasizes the role of scaling arguments in the development of useful representations for experimental and simulation data.
Compressed digital holography: from micro towards macro
NASA Astrophysics Data System (ADS)
Schretter, Colas; Bettens, Stijn; Blinder, David; Pesquet-Popescu, Béatrice; Cagnazzo, Marco; Dufaux, Frédéric; Schelkens, Peter
2016-09-01
signal processing methods from software-driven computer engineering and applied mathematics. The compressed sensing theory in particular established a practical framework for reconstructing the scene content using few linear combinations of complex measurements and a sparse prior for regularizing the solution. Compressed sensing found direct applications in digital holography for microscopy. Indeed, the wave propagation phenomenon in free space mixes in a natural way the spatial distribution of point sources from the 3-dimensional scene. As the 3-dimensional scene is mapped to a 2-dimensional hologram, the hologram samples form a compressed representation of the scene as well. This overview paper discusses contributions in the field of compressed digital holography at the micro scale. Then, an outreach on future extensions towards the real-size macro scale is discussed. Thanks to advances in sensor technologies, increasing computing power and the recent improvements in sparse digital signal processing, holographic modalities are on the verge of practical high-quality visualization at a macroscopic scale where much higher resolution holograms must be acquired and processed on the computer.
Number-space mapping in human infants.
de Hevia, Maria Dolores; Spelke, Elizabeth S
2010-05-01
Mature representations of number are built on a core system of numerical representation that connects to spatial representations in the form of a mental number line. The core number system is functional in early infancy, but little is known about the origins of the mapping of numbers onto space. In this article, we show that preverbal infants transfer the discrimination of an ordered series of numerosities to the discrimination of an ordered series of line lengths. Moreover, infants construct relationships between numbers and line lengths when they are habituated to unordered pairings that vary positively, but not when they are habituated to unordered pairings that vary inversely. These findings provide evidence that a predisposition to relate representations of numerical magnitude to spatial length develops early in life. A central foundation of mathematics, science, and technology therefore emerges prior to experience with language, symbol systems, or measurement devices.
Protein space: a natural method for realizing the nature of protein universe.
Yu, Chenglong; Deng, Mo; Cheng, Shiu-Yuen; Yau, Shek-Chung; He, Rong L; Yau, Stephen S-T
2013-02-07
Current methods cannot tell us what the nature of the protein universe is concretely. They are based on different models of amino acid substitution and multiple sequence alignment which is an NP-hard problem and requires manual intervention. Protein structural analysis also gives a direction for mapping the protein universe. Unfortunately, now only a minuscule fraction of proteins' 3-dimensional structures are known. Furthermore, the phylogenetic tree representations are not unique for any existing tree construction methods. Here we develop a novel method to realize the nature of protein universe. We show the protein universe can be realized as a protein space in 60-dimensional Euclidean space using a distance based on a normalized distribution of amino acids. Every protein is in one-to-one correspondence with a point in protein space, where proteins with similar properties stay close together. Thus the distance between two points in protein space represents the biological distance of the corresponding two proteins. We also propose a natural graphical representation for inferring phylogenies. The representation is natural and unique based on the biological distances of proteins in protein space. This will solve the fundamental question of how proteins are distributed in the protein universe. Copyright © 2012 Elsevier Ltd. All rights reserved.
Changes in the representation of space and time while listening to music
Schäfer, Thomas; Fachner, Jörg; Smukalla, Mario
2013-01-01
Music is known to alter people's ordinary experience of space and time. Not only does this challenge the concept of invariant space and time tacitly assumed in psychology but it may also help us understand how music works and how music can be understood as an embodied experience. Yet research about these alterations is in its infancy. This review is intended to delineate a future research agenda. We review experimental evidence and subjective reports of the influence of music on the representation of space and time and present prominent approaches to explaining these effects. We discuss the role of absorption and altered states of consciousness and their associated changes in attention and neurophysiological processes, as well as prominent models of human time processing and time experience. After integrating the reviewed research, we conclude that research on the influence of music on the representation of space and time is still quite inconclusive but that integrating the different approaches could lead to a better understanding of the observed effects. We also provide a working model that integrates a large part of the evidence and theories. Several suggestions for further research in both music psychology and cognitive psychology are outlined. PMID:23964254
Changes in the representation of space and time while listening to music.
Schäfer, Thomas; Fachner, Jörg; Smukalla, Mario
2013-01-01
Music is known to alter people's ordinary experience of space and time. Not only does this challenge the concept of invariant space and time tacitly assumed in psychology but it may also help us understand how music works and how music can be understood as an embodied experience. Yet research about these alterations is in its infancy. This review is intended to delineate a future research agenda. We review experimental evidence and subjective reports of the influence of music on the representation of space and time and present prominent approaches to explaining these effects. We discuss the role of absorption and altered states of consciousness and their associated changes in attention and neurophysiological processes, as well as prominent models of human time processing and time experience. After integrating the reviewed research, we conclude that research on the influence of music on the representation of space and time is still quite inconclusive but that integrating the different approaches could lead to a better understanding of the observed effects. We also provide a working model that integrates a large part of the evidence and theories. Several suggestions for further research in both music psychology and cognitive psychology are outlined.
Kosovich, John J.
2008-01-01
In support of U.S. Geological Survey (USGS) disaster preparedness efforts, this map depicts 1:24,000- and 1:100,000-scale quadrangle footprints over a color shaded relief representation of the State of Florida. The first 30 feet of relief above mean sea level are displayed as brightly colored 5-foot elevation bands, which highlight low-elevation areas at a coarse spatial resolution. Standard USGS National Elevation Dataset (NED) 1 arc-second (nominally 30-meter) digital elevation model (DEM) data are the basis for the map, which is designed to be used at a broad scale and for informational purposes only. The NED source data for this map consists of a mixture of 30-meter- and 10-meter-resolution DEMs. The NED data were derived from the original 1:24,000-scale USGS topographic map bare-earth contours, which were converted into gridded quadrangle-based DEM tiles at a constant post spacing (grid cell size) of either 30 meters (data before the mid-1990s) or 10 meters (mid-1990s and later data). These individual-quadrangle DEMs were then converted to spherical coordinates (latitude/longitude decimal degrees) and edge-matched to ensure seamlessness. Figure 1 shows a similar representation for the entire U.S. Gulf Coast, using coarsened 30-meter NED data. Areas below sea level typically are surrounded by levees or some other type of flood-control structures. State and county boundary, hydrography, city, and road layers were modified from USGS National Atlas data downloaded in 2003. Quadrangle names, dated April, 2006, were obtained from the Federal Geographic Names Information System. The NED data were downloaded in 2004.
Sub-kilometer Numerical Weather Prediction in complex urban areas
NASA Astrophysics Data System (ADS)
Leroyer, S.; Bélair, S.; Husain, S.; Vionnet, V.
2013-12-01
A Sub-kilometer atmospheric modeling system with grid-spacings of 2.5 km, 1 km and 250 m and including urban processes is currently being developed at the Meteorological Service of Canada (MSC) in order to provide more accurate weather forecasts at the city scale. Atmospheric lateral boundary conditions are provided with the 15-km Canadian Regional Deterministic Prediction System (RDPS). Surface physical processes are represented with the Town Energy Balance (TEB) model for the built-up covers and with the Interactions between the Surface, Biosphere, and Atmosphere (ISBA) land surface model for the natural covers. In this study, several research experiments over large metropolitan areas and using observational networks at the urban scale are presented, with a special emphasis on the representation of local atmospheric circulations and their impact on extreme weather forecasting. First, numerical simulations are performed over the Vancouver metropolitan area during a summertime Intense Observing Period (IOP of 14-15 August 2008) of the Environmental Prediction in Canadian Cities (EPiCC) observational network. The influence of the horizontal resolution on the fine-scale representation of the sea-breeze development over the city is highlighted (Leroyer et al., 2013). Then severe storms cases occurring in summertime within the Greater Toronto Area (GTA) are simulated. In view of supporting the 2015 PanAmerican and Para-Pan games to be hold in GTA, a dense observational network has been recently deployed over this region to support model evaluations at the urban and meso scales. In particular, simulations are conducted for the case of 8 July 2013 when exceptional rainfalls were recorded. Leroyer, S., S. Bélair, J. Mailhot, S.Z. Husain, 2013: Sub-kilometer Numerical Weather Prediction in an Urban Coastal Area: A case study over the Vancouver Metropolitan Area, submitted to Journal of Applied Meteorology and Climatology.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Mozrzymas, Marek; Horodecki, Michał; Studziński, Michał
We consider the structure of algebra of operators, acting in n-fold tensor product space, which are partially transposed on the last term. Using purely algebraical methods we show that this algebra is semi-simple and then, considering its regular representation, we derive basic properties of the algebra. In particular, we describe all irreducible representations of the algebra of partially transposed operators and derive expressions for matrix elements of the representations. It appears that there are two kinds of irreducible representations of the algebra. The first one is strictly connected with the representations of the group S(n − 1) induced by irreduciblemore » representations of the group S(n − 2). The second kind is structurally connected with irreducible representations of the group S(n − 1)« less
Three-Dimensional Messages for Interstellar Communication
NASA Astrophysics Data System (ADS)
Vakoch, Douglas A.
One of the challenges facing independently evolved civilizations separated by interstellar distances is to communicate information unique to one civilization. One commonly proposed solution is to begin with two-dimensional pictorial representations of mathematical concepts and physical objects, in the hope that this will provide a foundation for overcoming linguistic barriers. However, significant aspects of such representations are highly conventional, and may not be readily intelligible to a civilization with different conventions. The process of teaching conventions of representation may be facilitated by the use of three-dimensional representations redundantly encoded in multiple formats (e.g., as both vectors and as rasters). After having illustrated specific conventions for representing mathematical objects in a three-dimensional space, this method can be used to describe a physical environment shared by transmitter and receiver: a three-dimensional space defined by the transmitter--receiver axis, and containing stars within that space. This method can be extended to show three-dimensional representations varying over time. Having clarified conventions for representing objects potentially familiar to both sender and receiver, novel objects can subsequently be depicted. This is illustrated through sequences showing interactions between human beings, which provide information about human behavior and personality. Extensions of this method may allow the communication of such culture-specific features as aesthetic judgments and religious beliefs. Limitations of this approach will be noted, with specific reference to ETI who are not primarily visual.
A Mass Diffusion Model for Dry Snow Utilizing a Fabric Tensor to Characterize Anisotropy
NASA Astrophysics Data System (ADS)
Shertzer, Richard H.; Adams, Edward E.
2018-03-01
A homogenization algorithm for randomly distributed microstructures is applied to develop a mass diffusion model for dry snow. Homogenization is a multiscale approach linking constituent behavior at the microscopic level—among ice and air—to the macroscopic material—snow. Principles of continuum mechanics at the microscopic scale describe water vapor diffusion across an ice grain's surface to the air-filled pore space. Volume averaging and a localization assumption scale up and down, respectively, between microscopic and macroscopic scales. The model yields a mass diffusivity expression at the macroscopic scale that is, in general, a second-order tensor parameterized by both bulk and microstructural variables. The model predicts a mass diffusivity of water vapor through snow that is less than that through air. Mass diffusivity is expected to decrease linearly with ice volume fraction. Potential anisotropy in snow's mass diffusivity is captured due to the tensor representation. The tensor is built from directional data assigned to specific, idealized microstructural features. Such anisotropy has been observed in the field and laboratories in snow morphologies of interest such as weak layers of depth hoar and near-surface facets.
Diffeomorphic Sulcal Shape Analysis on the Cortex
Joshi, Shantanu H.; Cabeen, Ryan P.; Joshi, Anand A.; Sun, Bo; Dinov, Ivo; Narr, Katherine L.; Toga, Arthur W.; Woods, Roger P.
2014-01-01
We present a diffeomorphic approach for constructing intrinsic shape atlases of sulci on the human cortex. Sulci are represented as square-root velocity functions of continuous open curves in ℝ3, and their shapes are studied as functional representations of an infinite-dimensional sphere. This spherical manifold has some advantageous properties – it is equipped with a Riemannian metric on the tangent space and facilitates computational analyses and correspondences between sulcal shapes. Sulcal shape mapping is achieved by computing geodesics in the quotient space of shapes modulo scales, translations, rigid rotations and reparameterizations. The resulting sulcal shape atlas preserves important local geometry inherently present in the sample population. The sulcal shape atlas is integrated in a cortical registration framework and exhibits better geometric matching compared to the conventional euclidean method. We demonstrate experimental results for sulcal shape mapping, cortical surface registration, and sulcal classification for two different surface extraction protocols for separate subject populations. PMID:22328177
NASA Technical Reports Server (NTRS)
Mennell, R. C.
1975-01-01
Experimental aerodynamic investigations were conducted on a sting mounted .0405-scale representation of the 140C outer mold line space shuttle orbiter configuration in the Rockwell International 7.75 x 11.00 foot low speed wind tunnel. The primary test objectives were to define the orbiter wheel well pressure loading and its effects on landing gear thermal insulation and to investigate the pressure environment experienced by both the horizontal flight nose probe and air vent door probes. Steady state and dynamic pressure values were recorded in the orbiter nose gear well, left main landing gear well, horizontal flight nose probe, and both left and right air vent door probe. All steady state pressure levels were measured by Statham differential pressure transducers while dynamic pressure levels were recorded by Kulite high frequency response pressure sensors.
Eulerian frequency analysis of structural vibrations from high-speed video
DOE Office of Scientific and Technical Information (OSTI.GOV)
Venanzoni, Andrea; Siemens Industry Software NV, Interleuvenlaan 68, B-3001 Leuven; De Ryck, Laurent
An approach for the analysis of the frequency content of structural vibrations from high-speed video recordings is proposed. The techniques and tools proposed rely on an Eulerian approach, that is, using the time history of pixels independently to analyse structural motion, as opposed to Lagrangian approaches, where the motion of the structure is tracked in time. The starting point is an existing Eulerian motion magnification method, which consists in decomposing the video frames into a set of spatial scales through a so-called Laplacian pyramid [1]. Each scale — or level — can be amplified independently to reconstruct a magnified motionmore » of the observed structure. The approach proposed here provides two analysis tools or pre-amplification steps. The first tool provides a representation of the global frequency content of a video per pyramid level. This may be further enhanced by applying an angular filter in the spatial frequency domain to each frame of the video before the Laplacian pyramid decomposition, which allows for the identification of the frequency content of the structural vibrations in a particular direction of space. This proposed tool complements the existing Eulerian magnification method by amplifying selectively the levels containing relevant motion information with respect to their frequency content. This magnifies the displacement while limiting the noise contribution. The second tool is a holographic representation of the frequency content of a vibrating structure, yielding a map of the predominant frequency components across the structure. In contrast to the global frequency content representation of the video, this tool provides a local analysis of the periodic gray scale intensity changes of the frame in order to identify the vibrating parts of the structure and their main frequencies. Validation cases are provided and the advantages and limits of the approaches are discussed. The first validation case consists of the frequency content retrieval of the tip of a shaker, excited at selected fixed frequencies. The goal of this setup is to retrieve the frequencies at which the tip is excited. The second validation case consists of two thin metal beams connected to a randomly excited bar. It is shown that the holographic representation visually highlights the predominant frequency content of each pixel and locates the global frequencies of the motion, thus retrieving the natural frequencies for each beam.« less
NASA Astrophysics Data System (ADS)
Jiang, Guo-Qian; Xie, Ping; Wang, Xiao; Chen, Meng; He, Qun
2017-11-01
The performance of traditional vibration based fault diagnosis methods greatly depends on those handcrafted features extracted using signal processing algorithms, which require significant amounts of domain knowledge and human labor, and do not generalize well to new diagnosis domains. Recently, unsupervised representation learning provides an alternative promising solution to feature extraction in traditional fault diagnosis due to its superior learning ability from unlabeled data. Given that vibration signals usually contain multiple temporal structures, this paper proposes a multiscale representation learning (MSRL) framework to learn useful features directly from raw vibration signals, with the aim to capture rich and complementary fault pattern information at different scales. In our proposed approach, a coarse-grained procedure is first employed to obtain multiple scale signals from an original vibration signal. Then, sparse filtering, a newly developed unsupervised learning algorithm, is applied to automatically learn useful features from each scale signal, respectively, and then the learned features at each scale to be concatenated one by one to obtain multiscale representations. Finally, the multiscale representations are fed into a supervised classifier to achieve diagnosis results. Our proposed approach is evaluated using two different case studies: motor bearing and wind turbine gearbox fault diagnosis. Experimental results show that the proposed MSRL approach can take full advantages of the availability of unlabeled data to learn discriminative features and achieved better performance with higher accuracy and stability compared to the traditional approaches.
Li, Ping; Schloss, Benjamin; Follmer, D Jake
2017-10-01
In this article we report a computational semantic analysis of the presidential candidates' speeches in the two major political parties in the USA. In Study One, we modeled the political semantic spaces as a function of party, candidate, and time of election, and findings revealed patterns of differences in the semantic representation of key political concepts and the changing landscapes in which the presidential candidates align or misalign with their parties in terms of the representation and organization of politically central concepts. Our models further showed that the 2016 US presidential nominees had distinct conceptual representations from those of previous election years, and these patterns did not necessarily align with their respective political parties' average representation of the key political concepts. In Study Two, structural equation modeling demonstrated that reported political engagement among voters differentially predicted reported likelihoods of voting for Clinton versus Trump in the 2016 presidential election. Study Three indicated that Republicans and Democrats showed distinct, systematic word association patterns for the same concepts/terms, which could be reliably distinguished using machine learning methods. These studies suggest that given an individual's political beliefs, we can make reliable predictions about how they understand words, and given how an individual understands those same words, we can also predict an individual's political beliefs. Our study provides a bridge between semantic space models and abstract representations of political concepts on the one hand, and the representations of political concepts and citizens' voting behavior on the other.
Correspondence Search Mitigation Using Feature Space Anti-Aliasing
2007-01-01
trackers are widely used in astro -inertial nav- igation systems for long-range aircraft, space navigation, and ICBM guidance. When ground images are to be...frequency domain representation of the point spread function, H( fx , fy), is called the optical transfer function. Applying the Fourier transform to the...frequency domain representation of the image: I( fx , fy, t) = O( fx , fy, t)H( fx , fy) (4) In most conditions, the projected scene can be treated as a
NASA Astrophysics Data System (ADS)
Gorbunov, Michael E.; Cardellach, Estel; Lauritsen, Kent B.
2018-03-01
Linear and non-linear representations of wave fields constitute the basis of modern algorithms for analysis of radio occultation (RO) data. Linear representations are implemented by Fourier Integral Operators, which allow for high-resolution retrieval of bending angles. Non-linear representations include Wigner Distribution Function (WDF), which equals the pseudo-density of energy in the ray space. Representations allow for filtering wave fields by suppressing some areas of the ray space and mapping the field back from the transformed space to the initial one. We apply this technique to the retrieval of reflected rays from RO observations. The use of reflected rays may increase the accuracy of the retrieval of the atmospheric refractivity. Reflected rays can be identified by the visual inspection of WDF or spectrogram plots. Numerous examples from COSMIC data indicate that reflections are mostly observed over oceans or snow, in particular over Antarctica. We introduce the reflection index that characterizes the relative intensity of the reflected ray with respect to the direct ray. The index allows for the automatic identification of events with reflections. We use the radio holographic estimate of the errors of the retrieved bending angle profiles of reflected rays. A comparison of indices evaluated for a large base of events including the visual identification of reflections indicated a good agreement with our definition of reflection index.
Extended spin symmetry and the standard model
NASA Astrophysics Data System (ADS)
Besprosvany, J.; Romero, R.
2010-12-01
We review unification ideas and explain the spin-extended model in this context. Its consideration is also motivated by the standard-model puzzles. With the aim of constructing a common description of discrete degrees of freedom, as spin and gauge quantum numbers, the model departs from q-bits and generalized Hilbert spaces. Physical requirements reduce the space to one that is represented by matrices. The classification of the representations is performed through Clifford algebras, with its generators associated with Lorentz and scalar symmetries. We study a reduced space with up to two spinor elements within a matrix direct product. At given dimension, the demand that Lorentz symmetry be maintained, determines the scalar symmetries, which connect to vector-and-chiral gauge-interacting fields; we review the standard-model information in each dimension. We obtain fermions and bosons, with matter fields in the fundamental representation, radiation fields in the adjoint, and scalar particles with the Higgs quantum numbers. We relate the fields' representation in such spaces to the quantum-field-theory one, and the Lagrangian. The model provides a coupling-constant definition.
Fuzzy parametric uncertainty analysis of linear dynamical systems: A surrogate modeling approach
NASA Astrophysics Data System (ADS)
Chowdhury, R.; Adhikari, S.
2012-10-01
Uncertainty propagation engineering systems possess significant computational challenges. This paper explores the possibility of using correlated function expansion based metamodelling approach when uncertain system parameters are modeled using Fuzzy variables. In particular, the application of High-Dimensional Model Representation (HDMR) is proposed for fuzzy finite element analysis of dynamical systems. The HDMR expansion is a set of quantitative model assessment and analysis tools for capturing high-dimensional input-output system behavior based on a hierarchy of functions of increasing dimensions. The input variables may be either finite-dimensional (i.e., a vector of parameters chosen from the Euclidean space RM) or may be infinite-dimensional as in the function space CM[0,1]. The computational effort to determine the expansion functions using the alpha cut method scales polynomially with the number of variables rather than exponentially. This logic is based on the fundamental assumption underlying the HDMR representation that only low-order correlations among the input variables are likely to have significant impacts upon the outputs for most high-dimensional complex systems. The proposed method is integrated with a commercial Finite Element software. Modal analysis of a simplified aircraft wing with Fuzzy parameters has been used to illustrate the generality of the proposed approach. In the numerical examples, triangular membership functions have been used and the results have been validated against direct Monte Carlo simulations.
NASA Astrophysics Data System (ADS)
Black, R. X.
2017-12-01
We summarize results from a project focusing on regional temperature and precipitation extremes over the continental United States. Our project introduces a new framework for evaluating these extremes emphasizing their (a) large-scale organization, (b) underlying physical sources (including remote-excitation and scale-interaction) and (c) representation in climate models. Results to be reported include the synoptic-dynamic behavior, seasonality and secular variability of cold waves, dry spells and heavy rainfall events in the observational record. We also study how the characteristics of such extremes are systematically related to Northern Hemisphere planetary wave structures and thus planetary- and hemispheric-scale forcing (e.g., those associated with major El Nino events and Arctic sea ice change). The underlying physics of event onset are diagnostically quantified for different categories of events. Finally, the representation of these extremes in historical coupled climate model simulations is studied and the origins of model biases are traced using new metrics designed to assess the large-scale atmospheric forcing of local extremes.
Enabling large-scale viscoelastic calculations via neural network acceleration
NASA Astrophysics Data System (ADS)
Robinson DeVries, P.; Thompson, T. B.; Meade, B. J.
2017-12-01
One of the most significant challenges involved in efforts to understand the effects of repeated earthquake cycle activity are the computational costs of large-scale viscoelastic earthquake cycle models. Deep artificial neural networks (ANNs) can be used to discover new, compact, and accurate computational representations of viscoelastic physics. Once found, these efficient ANN representations may replace computationally intensive viscoelastic codes and accelerate large-scale viscoelastic calculations by more than 50,000%. This magnitude of acceleration enables the modeling of geometrically complex faults over thousands of earthquake cycles across wider ranges of model parameters and at larger spatial and temporal scales than have been previously possible. Perhaps most interestingly from a scientific perspective, ANN representations of viscoelastic physics may lead to basic advances in the understanding of the underlying model phenomenology. We demonstrate the potential of artificial neural networks to illuminate fundamental physical insights with specific examples.
Individuals and Leadership in an Australian Secondary Science Department: A Qualitative Study
NASA Astrophysics Data System (ADS)
Melville, Wayne; Wallace, John; Bartley, Anthony
2007-12-01
In this article, we consider the complex and dynamic inter-relationships between individual science teachers, the social space of their work and their dispositions towards teacher leadership. Research into the representation of school science departments through individual science teachers is scarce. We explore the representations of four individual teachers to the assertions of teacher leadership proposed by Silva et al. (Teach Coll Rec, 102(4):779-804, 2000). These representations, expressed during regular science department meetings, occur in the social space of Bourdieu's "field" and are a reflection of the "game" of science education being played within the department. This departmentally centred space suggests an important implication when considering the relationship between subject departments and their schools. The development of an individual's representation of teacher leadership and the wider "field" of science education appears to shape the individual towards promoting their own sense of identity as a teacher of science, rather than as a teacher within a school. Our work suggests that for these individuals, the important "game" is science education, not school improvement. Consequently, the subject department may be a missing link between efforts to improve schools and current organizational practices.
Quantization and Superselection Sectors I:. Transformation Group C*-ALGEBRAS
NASA Astrophysics Data System (ADS)
Landsman, N. P.
Quantization is defined as the act of assigning an appropriate C*-algebra { A} to a given configuration space Q, along with a prescription mapping self-adjoint elements of { A} into physically interpretable observables. This procedure is adopted to solve the problem of quantizing a particle moving on a homogeneous locally compact configuration space Q=G/H. Here { A} is chosen to be the transformation group C*-algebra corresponding to the canonical action of G on Q. The structure of these algebras and their representations are examined in some detail. Inequivalent quantizations are identified with inequivalent irreducible representations of the C*-algebra corresponding to the system, hence with its superselection sectors. Introducing the concept of a pre-Hamiltonian, we construct a large class of G-invariant time-evolutions on these algebras, and find the Hamiltonians implementing these time-evolutions in each irreducible representation of { A}. “Topological” terms in the Hamiltonian (or the corresponding action) turn out to be representation-dependent, and are automatically induced by the quantization procedure. Known “topological” charge quantization or periodicity conditions are then identically satisfied as a consequence of the representation theory of { A}.
Schermerhorn, Alice C; Cummings, E Mark; Davies, Patrick T
2008-02-01
The authors examine mutual family influence processes at the level of children's representations of multiple family relationships, as well as the structure of those representations. From a community sample with 3 waves, each spaced 1 year apart, kindergarten-age children (105 boys and 127 girls) completed a story-stem completion task, tapping representations of multiple family relationships. Structural equation modeling with autoregressive controls indicated that representational processes involving different family relationships were interrelated over time, including links between children's representations of marital conflict and reactions to conflict, between representations of security about marital conflict and parent-child relationships, and between representations of security in father-child and mother-child relationships. Mixed support was found for notions of increasing stability in representations during this developmental period. Results are discussed in terms of notions of transactional family dynamics, including family-wide perspectives on mutual influence processes attributable to multiple family relationships.
International Space Station (ISS)
1995-04-17
International Cooperation Phase III: A Space Shuttle docked to the International Space Station (ISS) in this computer generated representation of the ISS in its completed and fully operational state with elements from the U.S., Europe, Canada, Japan, and Russia.
Task planning and control synthesis for robotic manipulation in space applications
NASA Technical Reports Server (NTRS)
Sanderson, A. C.; Peshkin, M. A.; Homem-De-mello, L. S.
1987-01-01
Space-based robotic systems for diagnosis, repair and assembly of systems will require new techniques of planning and manipulation to accomplish these complex tasks. Results of work in assembly task representation, discrete task planning, and control synthesis which provide a design environment for flexible assembly systems in manufacturing applications, and which extend to planning of manipulatiuon operations in unstructured environments are summarized. Assembly planning is carried out using the AND/OR graph representation which encompasses all possible partial orders of operations and may be used to plan assembly sequences. Discrete task planning uses the configuration map which facilitates search over a space of discrete operations parameters in sequential operations in order to achieve required goals in the space of bounded configuration sets.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Błaszak, Maciej, E-mail: blaszakm@amu.edu.pl; Domański, Ziemowit, E-mail: ziemowit@amu.edu.pl
In the paper is presented an invariant quantization procedure of classical mechanics on the phase space over flat configuration space. Then, the passage to an operator representation of quantum mechanics in a Hilbert space over configuration space is derived. An explicit form of position and momentum operators as well as their appropriate ordering in arbitrary curvilinear coordinates is demonstrated. Finally, the extension of presented formalism onto non-flat case and related ambiguities of the process of quantization are discussed. -- Highlights: •An invariant quantization procedure of classical mechanics on the phase space over flat configuration space is presented. •The passage tomore » an operator representation of quantum mechanics in a Hilbert space over configuration space is derived. •Explicit form of position and momentum operators and their appropriate ordering in curvilinear coordinates is shown. •The invariant form of Hamiltonian operators quadratic and cubic in momenta is derived. •The extension of presented formalism onto non-flat case and related ambiguities of the quantization process are discussed.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kollias, Pavlos
2016-09-06
This the final report for the DE-SC0007096 - Advancing Clouds Lifecycle Representation in Numerical Models Using Innovative Analysis Methods that Bridge ARM Observations and Models Over a Breadth of Scales - PI: Pavlos Kollias. The final report outline the main findings of the research conducted using the aforementioned award in the area of cloud research from the cloud scale (10-100 m) to the mesoscale (20-50 km).
NASA Astrophysics Data System (ADS)
Ngom, Ndèye Fatou; Monga, Olivier; Ould Mohamed, Mohamed Mahmoud; Garnier, Patricia
2012-02-01
This paper focuses on the modeling of soil microstructures using generalized cylinders, with a specific application to pore space. The geometric modeling of these microstructures is a recent area of study, made possible by the improved performance of computed tomography techniques. X-scanners provide very-high-resolution 3D volume images ( 3-5μm) of soil samples in which pore spaces can be extracted by thresholding. However, in most cases, the pore space defines a complex volume shape that cannot be approximated using simple analytical functions. We propose representing this shape using a compact, stable, and robust piecewise approximation by means of generalized cylinders. This intrinsic shape representation conserves its topological and geometric properties. Our algorithm includes three main processing stages. The first stage consists in describing the volume shape using a minimum number of balls included within the shape, such that their union recovers the shape skeleton. The second stage involves the optimum extraction of simply connected chains of balls. The final stage copes with the approximation of each simply optimal chain using generalized cylinders: circular generalized cylinders, tori, cylinders, and truncated cones. This technique was applied to several data sets formed by real volume computed tomography soil samples. It was possible to demonstrate that our geometric representation supplied a good approximation of the pore space. We also stress the compactness and robustness of this method with respect to any changes affecting the initial data, as well as its coherence with the intuitive notion of pores. During future studies, this geometric pore space representation will be used to simulate biological dynamics.
Reserve networks based on richness hotspots and representation vary with scale
Susan A. Shriner; Kenneth R. Wilson; Curtis H. Flather
2006-01-01
While the importance of spatial scale in ecology is well established, few studies have investigated the impact of data grain on conservation planning outcomes. In this study, we compared species richness hotspot and representation networks developed at five grain sizes. We used species distribution maps for mammals and birds developed by the Arizona and New Mexico Gap...
NASA Technical Reports Server (NTRS)
Mennell, R. C.
1973-01-01
Experimental aerodynamic investigations were conducted on an 0.0405 scale representation of the -89B (2A) Space Shuttle Orbiter in a 7.75 x 11.00 ft low speed wind tunnel during the time period from July 27, 1973 to August 3, 1973. The primary test objective was to investigate the aerodynamic effects of engine nacelle grouping and location on the orbiter ferry mission configuration. Five nacelles were tested, both individually mounted as well as mounted in a podded configuration, at the baseline position and moved 45.0 in. aft (full scale). Orbiter control effectiveness, both with and without nacelles, was recorded at elevon deflections of 0 deg, 5 deg, 10 deg, -10 deg and -20 deg and aileron deflections, about 0 deg elevon, of 0 deg, 5 deg, 10 deg, and 15 deg. The model was sting mounted on a 2.5 inch diameter internal strain gage balance entering through the base region. The nominal angle of attack range was -4 deg or = alpha or = 30 deg. Yaw polars were recorded over the beta range of -10 deg or = beta or = at fixed angles of attack of 0 deg and 10 deg.
Cognitive Mapping Based on Conjunctive Representations of Space and Movement
Zeng, Taiping; Si, Bailu
2017-01-01
It is a challenge to build robust simultaneous localization and mapping (SLAM) system in dynamical large-scale environments. Inspired by recent findings in the entorhinal–hippocampal neuronal circuits, we propose a cognitive mapping model that includes continuous attractor networks of head-direction cells and conjunctive grid cells to integrate velocity information by conjunctive encodings of space and movement. Visual inputs from the local view cells in the model provide feedback cues to correct drifting errors of the attractors caused by the noisy velocity inputs. We demonstrate the mapping performance of the proposed cognitive mapping model on an open-source dataset of 66 km car journey in a 3 km × 1.6 km urban area. Experimental results show that the proposed model is robust in building a coherent semi-metric topological map of the entire urban area using a monocular camera, even though the image inputs contain various changes caused by different light conditions and terrains. The results in this study could inspire both neuroscience and robotic research to better understand the neural computational mechanisms of spatial cognition and to build robust robotic navigation systems in large-scale environments. PMID:29213234
THE FUTURE OF TOXICOLOGY-PREDICTIVE TOXICOLOGY ...
A chemistry approach to predictive toxicology relies on structure−activity relationship (SAR) modeling to predict biological activity from chemical structure. Such approaches have proven capabilities when applied to well-defined toxicity end points or regions of chemical space. These approaches are less well-suited, however, to the challenges of global toxicity prediction, i.e., to predicting the potential toxicity of structurally diverse chemicals across a wide range of end points of regulatory and pharmaceutical concern. New approaches that have the potential to significantly improve capabilities in predictive toxicology are elaborating the “activity” portion of the SAR paradigm. Recent advances in two areas of endeavor are particularly promising. Toxicity data informatics relies on standardized data schema, developed for particular areas of toxicological study, to facilitate data integration and enable relational exploration and mining of data across both historical and new areas of toxicological investigation. Bioassay profiling refers to large-scale high-throughput screening approaches that use chemicals as probes to broadly characterize biological response space, extending the concept of chemical “properties” to the biological activity domain. The effective capture and representation of legacy and new toxicity data into mineable form and the large-scale generation of new bioassay data in relation to chemical toxicity, both employing chemical stru
Combinatorial quantisation of the Euclidean torus universe
NASA Astrophysics Data System (ADS)
Meusburger, C.; Noui, K.
2010-12-01
We quantise the Euclidean torus universe via a combinatorial quantisation formalism based on its formulation as a Chern-Simons gauge theory and on the representation theory of the Drinfel'd double DSU(2). The resulting quantum algebra of observables is given by two commuting copies of the Heisenberg algebra, and the associated Hilbert space can be identified with the space of square integrable functions on the torus. We show that this Hilbert space carries a unitary representation of the modular group and discuss the role of modular invariance in the theory. We derive the classical limit of the theory and relate the quantum observables to the geometry of the torus universe.
Scollan-Koliopoulos, Melissa; Rapp, Kenneth J; Bleich, David
2012-01-01
The purpose of this study was to estimate the benefit of using a cultural characteristics scale to help diabetes educators understand how African Americans cope with diabetes. Illness representations are influenced by culture. Race and ethnicity as a proxy for culture provides an incomplete understanding of the mechanism by which cultural values influence representations of diabetes. A descriptive correlational design was employed by recruiting hospitalized adults with type 2 diabetes at 3 metropolitan northeast coast sites. The TRIOS Afrocentric cultural characteristics measure and the Illness perception Questionnaire were administered by paper-and-pencil to a diverse sample. Black race and African American ethnicity was used as a proxy for culture and compared to levels of agreement on an Afrocentric cultural scale to determine the relative ability to explain variance in illness representations of diabetes. The TRIOS measure adapted to diabetes care explained variance in illness representations of diabetes, while African American ethnicity/black race was not able to explain variance in illness representations. Clinicians would benefit from considering the degree to which a patient identifies with particular cultural characteristics when tailoring interventions to manipulate illness representations that are not concordant with biomedical representations.
LETTER TO THE EDITOR: Landau levels on the hyperbolic plane
NASA Astrophysics Data System (ADS)
Fakhri, H.; Shariati, M.
2004-11-01
The quantum states of a spinless charged particle on a hyperbolic plane in the presence of a uniform magnetic field with a generalized quantization condition are proved to be the bases of the irreducible Hilbert representation spaces of the Lie algebra u(1, 1). The dynamical symmetry group U(1, 1) with the explicit form of the Lie algebra generators is extracted. It is also shown that the energy has an infinite-fold degeneracy in each of the representation spaces which are allocated to the different values of the magnetic field strength. Based on the simultaneous shift of two parameters, it is also noted that the quantum states realize the representations of Lie algebra u(2) by shifting the magnetic field strength.
NASA Astrophysics Data System (ADS)
Lyakh, Dmitry I.
2018-03-01
A novel reduced-scaling, general-order coupled-cluster approach is formulated by exploiting hierarchical representations of many-body tensors, combined with the recently suggested formalism of scale-adaptive tensor algebra. Inspired by the hierarchical techniques from the renormalisation group approach, H/H2-matrix algebra and fast multipole method, the computational scaling reduction in our formalism is achieved via coarsening of quantum many-body interactions at larger interaction scales, thus imposing a hierarchical structure on many-body tensors of coupled-cluster theory. In our approach, the interaction scale can be defined on any appropriate Euclidean domain (spatial domain, momentum-space domain, energy domain, etc.). We show that the hierarchically resolved many-body tensors can reduce the storage requirements to O(N), where N is the number of simulated quantum particles. Subsequently, we prove that any connected many-body diagram consisting of a finite number of arbitrary-order tensors, e.g. an arbitrary coupled-cluster diagram, can be evaluated in O(NlogN) floating-point operations. On top of that, we suggest an additional approximation to further reduce the computational complexity of higher order coupled-cluster equations, i.e. equations involving higher than double excitations, which otherwise would introduce a large prefactor into formal O(NlogN) scaling.
Special relativity in a discrete quantum universe
NASA Astrophysics Data System (ADS)
Bisio, Alessandro; D'Ariano, Giacomo Mauro; Perinotti, Paolo
2016-10-01
The hypothesis of a discrete fabric of the universe, the "Planck scale," is always on stage since it solves mathematical and conceptual problems in the infinitely small. However, it clashes with special relativity, which is designed for the continuum. Here, we show how the clash can be overcome within a discrete quantum theory where the evolution of fields is described by a quantum cellular automaton. The reconciliation is achieved by defining the change of observer as a change of representation of the dynamics, without any reference to space-time. We use the relativity principle, i.e., the invariance of dynamics under change of inertial observer, to identify a change of inertial frame with a symmetry of the dynamics. We consider the full group of such symmetries, and recover the usual Lorentz group in the relativistic regime of low energies, while at the Planck scale the covariance is nonlinearly distorted.
Machine Learning Toolkit for Extreme Scale
DOE Office of Scientific and Technical Information (OSTI.GOV)
2014-03-31
Support Vector Machines (SVM) is a popular machine learning technique, which has been applied to a wide range of domains such as science, finance, and social networks for supervised learning. MaTEx undertakes the challenge of designing a scalable parallel SVM training algorithm for large scale systems, which includes commodity multi-core machines, tightly connected supercomputers and cloud computing systems. Several techniques are proposed for improved speed and memory space usage including adaptive and aggressive elimination of samples for faster convergence , and sparse format representation of data samples. Several heuristics for earliest possible to lazy elimination of non-contributing samples are consideredmore » in MaTEx. In many cases, where an early sample elimination might result in a false positive, low overhead mechanisms for reconstruction of key data structures are proposed. The proposed algorithm and heuristics are implemented and evaluated on various publicly available datasets« less
Imaging Molecular Motion: Femtosecond X-Ray Scattering of an Electrocyclic Chemical Reaction
NASA Astrophysics Data System (ADS)
Minitti, M. P.; Budarz, J. M.; Kirrander, A.; Robinson, J. S.; Ratner, D.; Lane, T. J.; Zhu, D.; Glownia, J. M.; Kozina, M.; Lemke, H. T.; Sikorski, M.; Feng, Y.; Nelson, S.; Saita, K.; Stankus, B.; Northey, T.; Hastings, J. B.; Weber, P. M.
2015-06-01
Structural rearrangements within single molecules occur on ultrafast time scales. Many aspects of molecular dynamics, such as the energy flow through excited states, have been studied using spectroscopic techniques, yet the goal to watch molecules evolve their geometrical structure in real time remains challenging. By mapping nuclear motions using femtosecond x-ray pulses, we have created real-space representations of the evolving dynamics during a well-known chemical reaction and show a series of time-sorted structural snapshots produced by ultrafast time-resolved hard x-ray scattering. A computational analysis optimally matches the series of scattering patterns produced by the x rays to a multitude of potential reaction paths. In so doing, we have made a critical step toward the goal of viewing chemical reactions on femtosecond time scales, opening a new direction in studies of ultrafast chemical reactions in the gas phase.
Imaging Molecular Motion: Femtosecond X-Ray Scattering of an Electrocyclic Chemical Reaction.
Minitti, M P; Budarz, J M; Kirrander, A; Robinson, J S; Ratner, D; Lane, T J; Zhu, D; Glownia, J M; Kozina, M; Lemke, H T; Sikorski, M; Feng, Y; Nelson, S; Saita, K; Stankus, B; Northey, T; Hastings, J B; Weber, P M
2015-06-26
Structural rearrangements within single molecules occur on ultrafast time scales. Many aspects of molecular dynamics, such as the energy flow through excited states, have been studied using spectroscopic techniques, yet the goal to watch molecules evolve their geometrical structure in real time remains challenging. By mapping nuclear motions using femtosecond x-ray pulses, we have created real-space representations of the evolving dynamics during a well-known chemical reaction and show a series of time-sorted structural snapshots produced by ultrafast time-resolved hard x-ray scattering. A computational analysis optimally matches the series of scattering patterns produced by the x rays to a multitude of potential reaction paths. In so doing, we have made a critical step toward the goal of viewing chemical reactions on femtosecond time scales, opening a new direction in studies of ultrafast chemical reactions in the gas phase.
Multiscale Cloud System Modeling
NASA Technical Reports Server (NTRS)
Tao, Wei-Kuo; Moncrieff, Mitchell W.
2009-01-01
The central theme of this paper is to describe how cloud system resolving models (CRMs) of grid spacing approximately 1 km have been applied to various important problems in atmospheric science across a wide range of spatial and temporal scales and how these applications relate to other modeling approaches. A long-standing problem concerns the representation of organized precipitating convective cloud systems in weather and climate models. Since CRMs resolve the mesoscale to large scales of motion (i.e., 10 km to global) they explicitly address the cloud system problem. By explicitly representing organized convection, CRMs bypass restrictive assumptions associated with convective parameterization such as the scale gap between cumulus and large-scale motion. Dynamical models provide insight into the physical mechanisms involved with scale interaction and convective organization. Multiscale CRMs simulate convective cloud systems in computational domains up to global and have been applied in place of contemporary convective parameterizations in global models. Multiscale CRMs pose a new challenge for model validation, which is met in an integrated approach involving CRMs, operational prediction systems, observational measurements, and dynamical models in a new international project: the Year of Tropical Convection, which has an emphasis on organized tropical convection and its global effects.
Local air temperature tolerance: a sensible basis for estimating climate variability
NASA Astrophysics Data System (ADS)
Kärner, Olavi; Post, Piia
2016-11-01
The customary representation of climate using sample moments is generally biased due to the noticeably nonstationary behaviour of many climate series. In this study, we introduce a moment-free climate representation based on a statistical model fitted to a long-term daily air temperature anomaly series. This model allows us to separate the climate and weather scale variability in the series. As a result, the climate scale can be characterized using the mean annual cycle of series and local air temperature tolerance, where the latter is computed using the fitted model. The representation of weather scale variability is specified using the frequency and the range of outliers based on the tolerance. The scheme is illustrated using five long-term air temperature records observed by different European meteorological stations.
Fusion basis for lattice gauge theory and loop quantum gravity
NASA Astrophysics Data System (ADS)
Delcamp, Clement; Dittrich, Bianca; Riello, Aldo
2017-02-01
We introduce a new basis for the gauge-invariant Hilbert space of lattice gauge theory and loop quantum gravity in (2 + 1) dimensions, the fusion basis. In doing so, we shift the focus from the original lattice (or spin-network) structure directly to that of the magnetic (curvature) and electric (torsion) excitations themselves. These excitations are classified by the irreducible representations of the Drinfel'd double of the gauge group, and can be readily "fused" together by studying the tensor product of such representations. We will also describe in detail the ribbon operators that create and measure these excitations and make the quasi-local structure of the observable algebra explicit. Since the fusion basis allows for both magnetic and electric excitations from the onset, it turns out to be a precious tool for studying the large scale structure and coarse-graining flow of lattice gauge theories and loop quantum gravity. This is in neat contrast with the widely used spin-network basis, in which it is much more complicated to account for electric excitations, i.e. for Gauß constraint violations, emerging at larger scales. Moreover, since the fusion basis comes equipped with a hierarchical structure, it readily provides the language to design states with sophisticated multi-scale structures. Another way to employ this hierarchical structure is to encode a notion of subsystems for lattice gauge theories and (2 + 1) gravity coupled to point particles. In a follow-up work, we have exploited this notion to provide a new definition of entanglement entropy for these theories.
Minimal left-right symmetric intersecting D-brane model
NASA Astrophysics Data System (ADS)
Anchordoqui, Luis A.; Antoniadis, Ignatios; Goldberg, Haim; Huang, Xing; Lüst, Dieter; Taylor, Tomasz R.
2017-01-01
We investigate left-right symmetric extensions of the standard model based on open strings ending on D-branes, with gauge bosons due to strings attached to stacks of D-branes and chiral matter due to strings stretching between intersecting D-branes. The left-handed and right-handed fermions transform as doublets under S p (1 )L and S p (1 )R, and so their masses must be generated by the introduction of Higgs fields in a bifundamental (2 ,2 ) representation under the two S p (1 ) gauge groups. For such D-brane configurations the left-right symmetry must be broken by Higgs fields in the doublet representation of S p (1 )R and therefore Majorana mass terms are suppressed by some higher physics scale. The left-handed and right-handed neutrinos pair up to form Dirac fermions which control the decay widths of the right-handed W' boson to yield comparable branching fractions into dilepton and dijet channels. Using the most recent searches at LHC13 Run II with 2016 data we constrain the (gR,mW') parameter space. Our analysis indicates that independent of the coupling strength gR, gauge bosons with masses mW'≳3.5 TeV are not ruled out. As the LHC is just beginning to probe the TeV scale, significant room for W' discovery remains.
ERIC Educational Resources Information Center
Taylor, Roger S.; Grundstrom, Erika D.
2011-01-01
Given that astronomy heavily relies on visual representations it is especially likely for individuals to assume that instructional materials, such as visual representations of the Earth-Moon system (EMS), would be relatively accurate. However, in our research, we found that images in middle-school textbooks and educational webpages were commonly…
Representations of Parent-Child Alliances in Children's Family Drawings
ERIC Educational Resources Information Center
Leon, Kim; Wallace, Tamar; Rudy, Duane
2007-01-01
The purpose of this study was to investigate relationships between children's representations of parent-child alliances (PCA) and their peer relationship quality, using a new scale that was developed to rate representations of PCA in children's family drawings. The parent-child alliance pattern is characterized by a relationship between parent and…
Subgrid-scale parameterization and low-frequency variability: a response theory approach
NASA Astrophysics Data System (ADS)
Demaeyer, Jonathan; Vannitsem, Stéphane
2016-04-01
Weather and climate models are limited in the possible range of resolved spatial and temporal scales. However, due to the huge space- and time-scale ranges involved in the Earth System dynamics, the effects of many sub-grid processes should be parameterized. These parameterizations have an impact on the forecasts or projections. It could also affect the low-frequency variability present in the system (such as the one associated to ENSO or NAO). An important question is therefore to know what is the impact of stochastic parameterizations on the Low-Frequency Variability generated by the system and its model representation. In this context, we consider a stochastic subgrid-scale parameterization based on the Ruelle's response theory and proposed in Wouters and Lucarini (2012). We test this approach in the context of a low-order coupled ocean-atmosphere model, detailed in Vannitsem et al. (2015), for which a part of the atmospheric modes is considered as unresolved. A natural separation of the phase-space into a slow invariant set and its fast complement allows for an analytical derivation of the different terms involved in the parameterization, namely the average, the fluctuation and the long memory terms. Its application to the low-order system reveals that a considerable correction of the low-frequency variability along the invariant subset can be obtained. This new approach of scale separation opens new avenues of subgrid-scale parameterizations in multiscale systems used for climate forecasts. References: Vannitsem S, Demaeyer J, De Cruz L, Ghil M. 2015. Low-frequency variability and heat transport in a low-order nonlinear coupled ocean-atmosphere model. Physica D: Nonlinear Phenomena 309: 71-85. Wouters J, Lucarini V. 2012. Disentangling multi-level systems: averaging, correlations and memory. Journal of Statistical Mechanics: Theory and Experiment 2012(03): P03 003.
Ahlqvist-Björkroth, Sari; Korja, Riikka; Junttila, Niina; Savonlahti, Elina; Pajulo, Marjukka; Räihä, Hannele; Aromaa, Minna
2016-07-01
Marital distress, parental depression, and weak quality of parental representations are all known risk factors for parent-child relationships. However, the relation between marital distress, depressive symptoms, and parents' prenatal representation is uncertain, especially regarding fathers. The present study aimed to explore how mothers' and fathers' prenatal experience of marital distress and depressive symptoms affects the organization of their prenatal representations in late pregnancy. Participants were 153 pregnant couples from a Finnish follow-up study called "Steps to the Healthy Development and Well-being of Children" (H. Lagström et al., ). Marital distress (Revised Dyadic Adjustment Scale; D.M. Busby, C. Christensen, D. Crane, & J. Larson, 1995) and depressive symptoms (Edinburgh Postnatal Depression Scale) were assessed at 20 gestational weeks, and prenatal representations (Working Model of the Child Interview; D. Benoit, K.C.H. Parker, & C.H. Zeanah, 1997; C.H. Zeanah, D. Benoit, M. Barton, & L. Hirshberg, 1996) were assessed between 29 and 32 gestational weeks. The mothers' risks of distorted representations increased significantly when they had at least minor depressive symptoms. Marital distress was associated with the fathers' prenatal representations, although the association was weak; fathers within the marital distress group had less balanced representations. Coexisting marital distress and depressive symptoms were only associated with the mothers' representations; lack of marital distress and depressive symptoms increased the likelihood for mothers to have balanced representations. The results imply that marital distress and depressive symptoms are differently related to the organizations of mothers' and fathers' prenatal representations. © 2016 Michigan Association for Infant Mental Health.
3D hierarchical spatial representation and memory of multimodal sensory data
NASA Astrophysics Data System (ADS)
Khosla, Deepak; Dow, Paul A.; Huber, David J.
2009-04-01
This paper describes an efficient method and system for representing, processing and understanding multi-modal sensory data. More specifically, it describes a computational method and system for how to process and remember multiple locations in multimodal sensory space (e.g., visual, auditory, somatosensory, etc.). The multimodal representation and memory is based on a biologically-inspired hierarchy of spatial representations implemented with novel analogues of real representations used in the human brain. The novelty of the work is in the computationally efficient and robust spatial representation of 3D locations in multimodal sensory space as well as an associated working memory for storage and recall of these representations at the desired level for goal-oriented action. We describe (1) A simple and efficient method for human-like hierarchical spatial representations of sensory data and how to associate, integrate and convert between these representations (head-centered coordinate system, body-centered coordinate, etc.); (2) a robust method for training and learning a mapping of points in multimodal sensory space (e.g., camera-visible object positions, location of auditory sources, etc.) to the above hierarchical spatial representations; and (3) a specification and implementation of a hierarchical spatial working memory based on the above for storage and recall at the desired level for goal-oriented action(s). This work is most useful for any machine or human-machine application that requires processing of multimodal sensory inputs, making sense of it from a spatial perspective (e.g., where is the sensory information coming from with respect to the machine and its parts) and then taking some goal-oriented action based on this spatial understanding. A multi-level spatial representation hierarchy means that heterogeneous sensory inputs (e.g., visual, auditory, somatosensory, etc.) can map onto the hierarchy at different levels. When controlling various machine/robot degrees of freedom, the desired movements and action can be computed from these different levels in the hierarchy. The most basic embodiment of this machine could be a pan-tilt camera system, an array of microphones, a machine with arm/hand like structure or/and a robot with some or all of the above capabilities. We describe the approach, system and present preliminary results on a real-robotic platform.
Diffeomorphism Group Representations in Relativistic Quantum Field Theory
DOE Office of Scientific and Technical Information (OSTI.GOV)
Goldin, Gerald A.; Sharp, David H.
We explore the role played by the di eomorphism group and its unitary representations in relativistic quantum eld theory. From the quantum kinematics of particles described by representations of the di eomorphism group of a space-like surface in an inertial reference frame, we reconstruct the local relativistic neutral scalar eld in the Fock representation. An explicit expression for the free Hamiltonian is obtained in terms of the Lie algebra generators (mass and momentum densities). We suggest that this approach can be generalized to elds whose quanta are spatially extended objects.
NASA Astrophysics Data System (ADS)
Jarvis, P. D.; Corney, S. P.; Tsohantjis, I.
1999-12-01
A covariant spinor representation of iosp(d,2/2) is constructed for the quantization of the spinning relativistic particle. It is found that, with appropriately defined wavefunctions, this representation can be identified with the state space arising from the canonical extended BFV-BRST quantization of the spinning particle with admissible gauge fixing conditions after a contraction procedure. For this model, the cohomological determination of physical states can thus be obtained purely from the representation theory of the iosp(d,2/2) algebra.
Surface energy fluxes and their representation in CMIP5 models
NASA Astrophysics Data System (ADS)
Wild, M.
2016-12-01
Energy fluxes at the Earth surface play a key role in the determination of surface climate and in the coupling of atmosphere, land and ocean components. Unlike their counterparts at the top of atmosphere (TOA), surface fluxes cannot be directly measured from satellites, but have to be inferred from the space-born observations using additional models to account for atmospheric perturbations, or from the limited number of surface observations. Uncertainties in the energy fluxes at the surface have therefore traditionally been larger than at the TOA, and have limited our knowledge on the distribution of the energy flows within the climate system. Accordingly, current climate models still largely differ in their representation of surface and atmospheric energy fluxes. Since the mid-1990s, accurate flux measurements became increasingly available from surface networks such as BSRN, which allow to better constrain the surface energy fluxes. There is, however, still a lack of flux measurements particularly over oceans. Further, the larger-scale representativeness of the station records needs to be assessed to judge their suitability as anchor sites for gridded flux products inferred from satellites, reanalyses and climate models. In addition, historic records need to be carefully quality-checked and homogeneized. In parallel, satellite-derived products of surface fluxes profit from the great advancement in space-born observations since the turn of the millennium, and from improved validation capabilities with surface observations. Ultimately, it is the combination of surface and space-born observations, reanalyses and modeling approaches that will advance our knowledge on the distribution of the surface energy fluxes. Uncertainties remain in the determination of surface albedo, skin temperatures and the partitioning of surface net radiation into the sensible and latent heat. Climate models over generations up to present day (CMIP5) tend to overestimate the downward shortwave and underestimate the downward longwave radiation. A challenge also remains the consistent representation of the global energy and water cycles. Yet it is shown that those climate models with a realistic surface radiation balance also simulate global precipitation amounts within the uncertainty range of observational estimates.
Citygml and the Streets of New York - a Proposal for Detailed Street Space Modelling
NASA Astrophysics Data System (ADS)
Beil, C.; Kolbe, T. H.
2017-10-01
Three-dimensional semantic city models are increasingly used for the analysis of large urban areas. Until now the focus has mostly been on buildings. Nonetheless many applications could also benefit from detailed models of public street space for further analysis. However, there are only few guidelines for representing roads within city models. Therefore, related standards dealing with street modelling are examined and discussed. Nearly all street representations are based on linear abstractions. However, there are many use cases that require or would benefit from the detailed geometrical and semantic representation of street space. A variety of potential applications for detailed street space models are presented. Subsequently, based on related standards as well as on user requirements, a concept for a CityGML-compliant representation of street space in multiple levels of detail is developed. In the course of this process, the CityGML Transportation model of the currently valid OGC standard CityGML2.0 is examined to discover possibilities for further developments. Moreover, a number of improvements are presented. Finally, based on open data sources, the proposed concept is implemented within a semantic 3D city model of New York City generating a detailed 3D street space model for the entire city. As a result, 11 thematic classes, such as roadbeds, sidewalks or traffic islands are generated and enriched with a large number of thematic attributes.
How category learning affects object representations: Not all morphspaces stretch alike
Folstein, Jonathan R.; Gauthier, Isabel; Palmeri, Thomas J.
2012-01-01
How does learning to categorize objects affect how we visually perceive them? Behavioral, neurophysiological, and neuroimaging studies have tested the degree to which category learning influences object representations, with conflicting results. Some studies find that objects become more visually discriminable along dimensions relevant to previously learned categories, while others find no such effect. One critical factor we explore here lies in the structure of the morphspaces used in different studies. Studies finding no increase in discriminability often use “blended” morphspaces, with morphparents lying at corners of the space. By contrast, studies finding increases in discriminability use “factorial” morphspaces, defined by separate morphlines forming axes of the space. Using the same four morphparents, we created both factorial and blended morphspaces matched in pairwise discriminability. Category learning caused a selective increase in discriminability along the relevant dimension of the factorial space, but not in the blended space, and led to the creation of functional dimensions in the factorial space, but not in the blended space. These findings demonstrate that not all morphspaces stretch alike: Only some morphspaces support enhanced discriminability to relevant object dimensions following category learning. Our results have important implications for interpreting neuroimaging studies reporting little or no effect of category learning on object representations in the visual system: Those studies may have been limited by their use of blended morphspaces. PMID:22746950
Dendrites, deep learning, and sequences in the hippocampus.
Bhalla, Upinder S
2017-10-12
The hippocampus places us both in time and space. It does so over remarkably large spans: milliseconds to years, and centimeters to kilometers. This works for sensory representations, for memory, and for behavioral context. How does it fit in such wide ranges of time and space scales, and keep order among the many dimensions of stimulus context? A key organizing principle for a wide sweep of scales and stimulus dimensions is that of order in time, or sequences. Sequences of neuronal activity are ubiquitous in sensory processing, in motor control, in planning actions, and in memory. Against this strong evidence for the phenomenon, there are currently more models than definite experiments about how the brain generates ordered activity. The flip side of sequence generation is discrimination. Discrimination of sequences has been extensively studied at the behavioral, systems, and modeling level, but again physiological mechanisms are fewer. It is against this backdrop that I discuss two recent developments in neural sequence computation, that at face value share little beyond the label "neural." These are dendritic sequence discrimination, and deep learning. One derives from channel physiology and molecular signaling, the other from applied neural network theory - apparently extreme ends of the spectrum of neural circuit detail. I suggest that each of these topics has deep lessons about the possible mechanisms, scales, and capabilities of hippocampal sequence computation. © 2017 Wiley Periodicals, Inc.
A sparse grid based method for generative dimensionality reduction of high-dimensional data
NASA Astrophysics Data System (ADS)
Bohn, Bastian; Garcke, Jochen; Griebel, Michael
2016-03-01
Generative dimensionality reduction methods play an important role in machine learning applications because they construct an explicit mapping from a low-dimensional space to the high-dimensional data space. We discuss a general framework to describe generative dimensionality reduction methods, where the main focus lies on a regularized principal manifold learning variant. Since most generative dimensionality reduction algorithms exploit the representer theorem for reproducing kernel Hilbert spaces, their computational costs grow at least quadratically in the number n of data. Instead, we introduce a grid-based discretization approach which automatically scales just linearly in n. To circumvent the curse of dimensionality of full tensor product grids, we use the concept of sparse grids. Furthermore, in real-world applications, some embedding directions are usually more important than others and it is reasonable to refine the underlying discretization space only in these directions. To this end, we employ a dimension-adaptive algorithm which is based on the ANOVA (analysis of variance) decomposition of a function. In particular, the reconstruction error is used to measure the quality of an embedding. As an application, the study of large simulation data from an engineering application in the automotive industry (car crash simulation) is performed.
Shape component analysis: structure-preserving dimension reduction on biological shape spaces.
Lee, Hao-Chih; Liao, Tao; Zhang, Yongjie Jessica; Yang, Ge
2016-03-01
Quantitative shape analysis is required by a wide range of biological studies across diverse scales, ranging from molecules to cells and organisms. In particular, high-throughput and systems-level studies of biological structures and functions have started to produce large volumes of complex high-dimensional shape data. Analysis and understanding of high-dimensional biological shape data require dimension-reduction techniques. We have developed a technique for non-linear dimension reduction of 2D and 3D biological shape representations on their Riemannian spaces. A key feature of this technique is that it preserves distances between different shapes in an embedded low-dimensional shape space. We demonstrate an application of this technique by combining it with non-linear mean-shift clustering on the Riemannian spaces for unsupervised clustering of shapes of cellular organelles and proteins. Source code and data for reproducing results of this article are freely available at https://github.com/ccdlcmu/shape_component_analysis_Matlab The implementation was made in MATLAB and supported on MS Windows, Linux and Mac OS. geyang@andrew.cmu.edu. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
Categorical clustering of the neural representation of color.
Brouwer, Gijs Joost; Heeger, David J
2013-09-25
Cortical activity was measured with functional magnetic resonance imaging (fMRI) while human subjects viewed 12 stimulus colors and performed either a color-naming or diverted attention task. A forward model was used to extract lower dimensional neural color spaces from the high-dimensional fMRI responses. The neural color spaces in two visual areas, human ventral V4 (V4v) and VO1, exhibited clustering (greater similarity between activity patterns evoked by stimulus colors within a perceptual category, compared to between-category colors) for the color-naming task, but not for the diverted attention task. Response amplitudes and signal-to-noise ratios were higher in most visual cortical areas for color naming compared to diverted attention. But only in V4v and VO1 did the cortical representation of color change to a categorical color space. A model is presented that induces such a categorical representation by changing the response gains of subpopulations of color-selective neurons.
Xu, Xin; Huang, Zhenhua; Graves, Daniel; Pedrycz, Witold
2014-12-01
In order to deal with the sequential decision problems with large or continuous state spaces, feature representation and function approximation have been a major research topic in reinforcement learning (RL). In this paper, a clustering-based graph Laplacian framework is presented for feature representation and value function approximation (VFA) in RL. By making use of clustering-based techniques, that is, K-means clustering or fuzzy C-means clustering, a graph Laplacian is constructed by subsampling in Markov decision processes (MDPs) with continuous state spaces. The basis functions for VFA can be automatically generated from spectral analysis of the graph Laplacian. The clustering-based graph Laplacian is integrated with a class of approximation policy iteration algorithms called representation policy iteration (RPI) for RL in MDPs with continuous state spaces. Simulation and experimental results show that, compared with previous RPI methods, the proposed approach needs fewer sample points to compute an efficient set of basis functions and the learning control performance can be improved for a variety of parameter settings.
Human Orbitofrontal Cortex Represents a Cognitive Map of State Space.
Schuck, Nicolas W; Cai, Ming Bo; Wilson, Robert C; Niv, Yael
2016-09-21
Although the orbitofrontal cortex (OFC) has been studied intensely for decades, its precise functions have remained elusive. We recently hypothesized that the OFC contains a "cognitive map" of task space in which the current state of the task is represented, and this representation is especially critical for behavior when states are unobservable from sensory input. To test this idea, we apply pattern-classification techniques to neuroimaging data from humans performing a decision-making task with 16 states. We show that unobservable task states can be decoded from activity in OFC, and decoding accuracy is related to task performance and the occurrence of individual behavioral errors. Moreover, similarity between the neural representations of consecutive states correlates with behavioral accuracy in corresponding state transitions. These results support the idea that OFC represents a cognitive map of task space and establish the feasibility of decoding state representations in humans using non-invasive neuroimaging. Copyright © 2016 Elsevier Inc. All rights reserved.
Categorical Clustering of the Neural Representation of Color
Heeger, David J.
2013-01-01
Cortical activity was measured with functional magnetic resonance imaging (fMRI) while human subjects viewed 12 stimulus colors and performed either a color-naming or diverted attention task. A forward model was used to extract lower dimensional neural color spaces from the high-dimensional fMRI responses. The neural color spaces in two visual areas, human ventral V4 (V4v) and VO1, exhibited clustering (greater similarity between activity patterns evoked by stimulus colors within a perceptual category, compared to between-category colors) for the color-naming task, but not for the diverted attention task. Response amplitudes and signal-to-noise ratios were higher in most visual cortical areas for color naming compared to diverted attention. But only in V4v and VO1 did the cortical representation of color change to a categorical color space. A model is presented that induces such a categorical representation by changing the response gains of subpopulations of color-selective neurons. PMID:24068814
Lessons learned from the design of chemical space networks and opportunities for new applications.
Vogt, Martin; Stumpfe, Dagmar; Maggiora, Gerald M; Bajorath, Jürgen
2016-03-01
The concept of chemical space is of fundamental relevance in chemical informatics and computer-aided drug discovery. In a series of articles published in the Journal of Computer-Aided Molecular Design, principles of chemical space design were evaluated, molecular networks proposed as an alternative to conventional coordinate-based chemical reference spaces, and different types of chemical space networks (CSNs) constructed and analyzed. Central to the generation of CSNs was the way in which molecular similarity relationships were assessed and a primary focal point was the network-based representation of biologically relevant chemical space. The design and comparison of CSNs based upon alternative similarity measures can be viewed as an evolutionary path with interesting lessons learned along the way. CSN design has matured to the point that such chemical space representations can be used in practice. In this contribution, highlights from the sequence of CSN design efforts are discussed in context, providing a perspective for future practical applications.
Lessons learned from the design of chemical space networks and opportunities for new applications
NASA Astrophysics Data System (ADS)
Vogt, Martin; Stumpfe, Dagmar; Maggiora, Gerald M.; Bajorath, Jürgen
2016-03-01
The concept of chemical space is of fundamental relevance in chemical informatics and computer-aided drug discovery. In a series of articles published in the Journal of Computer- Aided Molecular Design, principles of chemical space design were evaluated, molecular networks proposed as an alternative to conventional coordinate-based chemical reference spaces, and different types of chemical space networks (CSNs) constructed and analyzed. Central to the generation of CSNs was the way in which molecular similarity relationships were assessed and a primary focal point was the network-based representation of biologically relevant chemical space. The design and comparison of CSNs based upon alternative similarity measures can be viewed as an evolutionary path with interesting lessons learned along the way. CSN design has matured to the point that such chemical space representations can be used in practice. In this contribution, highlights from the sequence of CSN design efforts are discussed in context, providing a perspective for future practical applications.
Effect of Within-Category Spacing on Free Recall
ERIC Educational Resources Information Center
Borges, Marilyn A.; Mandler, George
1972-01-01
Contrary to previous experiments which found recall with blocked spacing always superior to recall with random" spacings, these experiments found that total recall was a function of two independent factors: (a) category representation, and (b) items per category represented (IPC). Both factors are dependent upon within-category spacing.…
ERIC Educational Resources Information Center
Cocchini, Gianna; Watling, Rosamond; Della Sala, Sergio; Jansari, Ashok
2007-01-01
Successful interaction with the environment depends upon our ability to retain and update visuo-spatial information of both front and back egocentric space. Several studies have observed that healthy people tend to show a displacement of the egocentric frame of reference towards the left. However representation of space behind us (back space) has…
On the Representation of Subgrid Microtopography Effects in Process-based Hydrologic Models
NASA Astrophysics Data System (ADS)
Jan, A.; Painter, S. L.; Coon, E. T.
2017-12-01
Increased availability of high-resolution digital elevation are enabling process-based hydrologic modeling on finer and finer scales. However, spatial variability in surface elevation (microtopography) exists below the scale of a typical hyper-resolution grid cell and has the potential to play a significant role in water retention, runoff, and surface/subsurface interactions. Though the concept of microtopographic features (depressions, obstructions) and the associated implications on flow and discharge are well established, representing those effects in watershed-scale integrated surface/subsurface hydrology models remains a challenge. Using the complex and coupled hydrologic environment of the Arctic polygonal tundra as an example, we study the effects of submeter topography and present a subgrid model parameterized by small-scale spatial heterogeneities for use in hyper-resolution models with polygons at a scale of 15-20 meters forming the surface cells. The subgrid model alters the flow and storage terms in the diffusion wave equation for surface flow. We compare our results against sub-meter scale simulations (acts as a benchmark for our simulations) and hyper-resolution models without the subgrid representation. The initiation of runoff in the fine-scale simulations is delayed and the recession curve is slowed relative to simulated runoff using the hyper-resolution model with no subgrid representation. Our subgrid modeling approach improves the representation of runoff and water retention relative to models that ignore subgrid topography. We evaluate different strategies for parameterizing subgrid model and present a classification-based method to efficiently move forward to larger landscapes. This work was supported by the Interoperable Design of Extreme-scale Application Software (IDEAS) project and the Next-Generation Ecosystem Experiments-Arctic (NGEE Arctic) project. NGEE-Arctic is supported by the Office of Biological and Environmental Research in the DOE Office of Science.
White, Claire E; Provis, John L; Proffen, Thomas; Riley, Daniel P; van Deventer, Jannie S J
2010-04-07
Understanding the atomic structure of complex metastable (including glassy) materials is of great importance in research and industry, however, such materials resist solution by most standard techniques. Here, a novel technique combining thermodynamics and local structure is presented to solve the structure of the metastable aluminosilicate material metakaolin (calcined kaolinite) without the use of chemical constraints. The structure is elucidated by iterating between least-squares real-space refinement using neutron pair distribution function data, and geometry optimisation using density functional modelling. The resulting structural representation is both energetically feasible and in excellent agreement with experimental data. This accurate structural representation of metakaolin provides new insight into the local environment of the aluminium atoms, with evidence of the existence of tri-coordinated aluminium. By the availability of this detailed chemically feasible atomic description, without the need to artificially impose constraints during the refinement process, there exists the opportunity to tailor chemical and mechanical processes involving metakaolin and other complex metastable materials at the atomic level to obtain optimal performance at the macro-scale.
Patané, Ivan; Farnè, Alessandro; Frassinetti, Francesca
2016-01-01
A large literature has documented interactions between space and time suggesting that the two experiential domains may share a common format in a generalized magnitude system (ATOM theory). To further explore this hypothesis, here we measured the extent to which time and space are sensitive to the same sensorimotor plasticity processes, as induced by classical prismatic adaptation procedures (PA). We also exanimated whether spatial-attention shifts on time and space processing, produced through PA, extend to stimuli presented beyond the immediate near space. Results indicated that PA affected both temporal and spatial representations not only in the near space (i.e., the region within which the adaptation occurred), but also in the far space. In addition, both rightward and leftward PA directions caused opposite and symmetrical modulations on time processing, whereas only leftward PA biased space processing rightward. We discuss these findings within the ATOM framework and models that account for PA effects on space and time processing. We propose that the differential and asymmetrical effects following PA may suggest that temporal and spatial representations are not perfectly aligned.
NASA Astrophysics Data System (ADS)
McWilliams, J. C.; Lane, E.; Melville, K.; Restrepo, J.; Sullivan, P.
2004-12-01
Oceanic surface gravity waves are approximately irrotational, weakly nonlinear, and conservative, and they have a much shorter time scale than oceanic currents and longer waves (e.g., infragravity waves) --- except where the primary surface waves break. This provides a framework for an asymptotic theory, based on separation of time (and space) scales, of wave-averaged effects associated with the conservative primary wave dynamics combined with a stochastic representation of the momentum transfer and induced mixing associated with non-conservative wave breaking. Such a theory requires only modest information about the primary wave field from measurements or operational model forecasts and thus avoids the enormous burden of calculating the waves on their intrinsically small space and time scales. For the conservative effects, the result is a vortex force associated with the primary wave's Stokes drift; a wave-averaged Bernoulli head and sea-level set-up; and an incremental material advection by the Stokes drift. This can be compared to the "radiation stress" formalism of Longuet-Higgins, Stewart, and Hasselmann; it is shown to be a preferable representation since the radiation stress is trivial at its apparent leading order. For the non-conservative breaking effects, a population of stochastic impulses is added to the current and infragravity momentum equations with distribution functions taken from measurements. In offshore wind-wave equilibria, these impulses replace the conventional surface wind stress and cause significant differences in the surface boundary layer currents and entrainment rate, particularly when acting in combination with the conservative vortex force. In the surf zone, where breaking associated with shoaling removes nearly all of the primary wave momentum and energy, the stochastic forcing plays an analogous role as the widely used nearshore radiation stress parameterizations. This talk describes the theoretical framework and presents some preliminary solutions using it. McWilliams, J.C., J.M. Restrepo, & E.M. Lane, 2004: An asymptotic theory for the interaction of waves and currents in coastal waters. J. Fluid Mech. 511, 135-178. Sullivan, P.P., J.C. McWilliams, & W.K. Melville, 2004: The oceanic boundary layer driven by wave breaking with stochastic variability. J. Fluid Mech. 507, 143-174.
Drummond, Leslie; Shomstein, Sarah
2013-01-01
The relative contributions of objects (i.e., object-based) and underlying spatial (i.e., space-based representations) to attentional prioritization and selection remain unclear. In most experimental circumstances, the two representations overlap thus their respective contributions cannot be evaluated. Here, a dynamic version of the two-rectangle paradigm allowed for a successful de-coupling of spatial and object representations. Space-based (cued spatial location), cued end of the object, and object-based (locations within the cued object) effects were sampled at several timepoints following the cue with high or low certainty as to target location. In the high uncertainty condition spatial benefits prevailed throughout most of the timecourse, as evidenced by facilitatory and inhibitory effects. Additionally, the cued end of the object, rather than a whole object, received the attentional benefit. When target location was predictable (low uncertainty manipulation), only probabilities guided selection (i.e., evidence by a benefit for the statistically biased location). These results suggest that with high spatial uncertainty, all available information present within the stimulus display is used for the purposes of attentional selection (e.g., spatial locations, cued end of the object) albeit to varying degrees and at different time points. However, as certainty increases, only spatial certainty guides selection (i.e., object ends and whole objects are filtered out). Taken together, these results further elucidate the contributing role of space- and object-representations to attentional guidance. PMID:24367302
Semantic, perceptual and number space: relations between category width and spatial processing.
Brugger, Peter; Loetscher, Tobias; Graves, Roger E; Knoch, Daria
2007-05-17
Coarse semantic encoding and broad categorization behavior are the hallmarks of the right cerebral hemisphere's contribution to language processing. We correlated 40 healthy subjects' breadth of categorization as assessed with Pettigrew's category width scale with lateral asymmetries in perceptual and representational space. Specifically, we hypothesized broader category width to be associated with larger leftward spatial biases. For the 20 men, but not the 20 women, this hypothesis was confirmed both in a lateralized tachistoscopic task with chimeric faces and a random digit generation task; the higher a male participant's score on category width, the more pronounced were his left-visual field bias in the judgement of chimeric faces and his small-number preference in digit generation ("small" is to the left of "large" in number space). Subjects' category width was unrelated to lateral displacements in a blindfolded tactile-motor rod centering task. These findings indicate that visual-spatial functions of the right hemisphere should not be considered independent of the same hemisphere's contribution to language. Linguistic and spatial cognition may be more tightly interwoven than is currently assumed.
Timelines Revisited: A Design Space and Considerations for Expressive Storytelling.
Brehmer, Matthew; Lee, Bongshin; Bach, Benjamin; Riche, Nathalie Henry; Munzner, Tamara
2017-09-01
There are many ways to visualize event sequences as timelines. In a storytelling context where the intent is to convey multiple narrative points, a richer set of timeline designs may be more appropriate than the narrow range that has been used for exploratory data analysis by the research community. Informed by a survey of 263 timelines, we present a design space for storytelling with timelines that balances expressiveness and effectiveness, identifying 14 design choices characterized by three dimensions: representation, scale, and layout. Twenty combinations of these choices are viable timeline designs that can be matched to different narrative points, while smooth animated transitions between narrative points allow for the presentation of a cohesive story, an important aspect of both interactive storytelling and data videos. We further validate this design space by realizing the full set of viable timeline designs and transitions in a proof-of-concept sandbox implementation that we used to produce seven example timeline stories. Ultimately, this work is intended to inform and inspire the design of future tools for storytelling with timelines.
NASA Astrophysics Data System (ADS)
Tubman, Norm; Whaley, Birgitta
The development of exponential scaling methods has seen great progress in tackling larger systems than previously thought possible. One such technique, full configuration interaction quantum Monte Carlo, allows exact diagonalization through stochastically sampling of determinants. The method derives its utility from the information in the matrix elements of the Hamiltonian, together with a stochastic projected wave function, which are used to explore the important parts of Hilbert space. However, a stochastic representation of the wave function is not required to search Hilbert space efficiently and new deterministic approaches have recently been shown to efficiently find the important parts of determinant space. We shall discuss the technique of Adaptive Sampling Configuration Interaction (ASCI) and the related heat-bath Configuration Interaction approach for ground state and excited state simulations. We will present several applications for strongly correlated Hamiltonians. This work was supported through the Scientific Discovery through Advanced Computing (SciDAC) program funded by the U.S. Department of Energy, Office of Science, Advanced Scientific Computing Research and Basic Energy Sciences.
Thinking Egyptian: Active Models for Understanding Spatial Representation.
ERIC Educational Resources Information Center
Schiferl, Ellen
This paper highlights how introductory textbooks on Egyptian art inhibit understanding by reinforcing student preconceptions, and demonstrates another approach to discussing space with a classroom exercise and software. The alternative approach, an active model for spatial representation, introduced here was developed by adapting classroom…
Öllinger, Michael; Jones, Gary; Knoblich, Günther
2014-03-01
The nine-dot problem is often used to demonstrate and explain mental impasse, creativity, and out of the box thinking. The present study investigated the interplay of a restricted initial search space, the likelihood of invoking a representational change, and the subsequent constraining of an unrestricted search space. In three experimental conditions, participants worked on different versions of the nine-dot problem that hinted at removing particular sources of difficulty from the standard problem. The hints were incremental such that the first suggested a possible route for a solution attempt; the second additionally indicated the dot at which lines meet on the solution path; and the final condition also provided non-dot locations that appear in the solution path. The results showed that in the experimental conditions, representational change is encountered more quickly and problems are solved more often than for the control group. We propose a cognitive model that focuses on general problem-solving heuristics and representational change to explain problem difficulty.
Spatial displacement of numbers on a vertical number line in spatial neglect.
Mihulowicz, Urszula; Klein, Elise; Nuerk, Hans-Christoph; Willmes, Klaus; Karnath, Hans-Otto
2015-01-01
Previous studies that investigated the association of numbers and space in humans came to contradictory conclusions about the spatial character of the mental number magnitude representation and about how it may be influenced by unilateral spatial neglect. The present study aimed to disentangle the debated influence of perceptual vs. representational aspects via explicit mapping of numbers onto space by applying the number line estimation paradigm with vertical orientation of stimulus lines. Thirty-five acute right-brain damaged stroke patients (6 with neglect) were asked to place two-digit numbers on vertically oriented lines with 0 marked at the bottom and 100 at the top. In contrast to the expected, nearly linear mapping in the control patient group, patients with spatial neglect overestimated the position of numbers in the lower middle range. The results corroborate spatial characteristics of the number magnitude representation. In neglect patients, this representation seems to be biased towards the ipsilesional side, independent of the physical orientation of the task stimuli.
Mental Imagery Scale: a new measurement tool to assess structural features of mental representations
NASA Astrophysics Data System (ADS)
D'Ercole, Martina; Castelli, Paolo; Giannini, Anna Maria; Sbrilli, Antonella
2010-05-01
Mental imagery is a quasi-perceptual experience which resembles perceptual experience, but occurring without (appropriate) external stimuli. It is a form of mental representation and is often considered centrally involved in visuo-spatial reasoning and inventive and creative thought. Although imagery ability is assumed to be functionally independent of verbal systems, it is still considered to interact with verbal representations, enabling objects to be named and names to evoke images. In literature, most measurement tools for evaluating imagery capacity are self-report instruments focusing on differences in individuals. In the present work, we applied a Mental Imagery Scale (MIS) to mental images derived from verbal descriptions in order to assess the structural features of such mental representations. This is a key theme for those disciplines which need to turn objects and representations into words and vice versa, such as art or architectural didactics. To this aim, an MIS questionnaire was administered to 262 participants. The questionnaire, originally consisting of a 33-item 5-step Likert scale, was reduced to 28 items covering six areas: (1) Image Formation Speed, (2) Permanence/Stability, (3) Dimensions, (4) Level of Detail/Grain, (5) Distance and (6) Depth of Field or Perspective. Factor analysis confirmed our six-factor hypothesis underlying the 28 items.
ERIC Educational Resources Information Center
Bengtson, Barbara J.
2013-01-01
Understanding the linear relationship of numbers is essential for doing practical and abstract mathematics throughout education and everyday life. There is evidence that number line activities increase learners' number sense, improving the linearity of mental number line representations (Siegler & Ramani, 2009). Mental representations of…
Progress with modeling activity landscapes in drug discovery.
Vogt, Martin
2018-04-19
Activity landscapes (ALs) are representations and models of compound data sets annotated with a target-specific activity. In contrast to quantitative structure-activity relationship (QSAR) models, ALs aim at characterizing structure-activity relationships (SARs) on a large-scale level encompassing all active compounds for specific targets. The popularity of AL modeling has grown substantially with the public availability of large activity-annotated compound data sets. AL modeling crucially depends on molecular representations and similarity metrics used to assess structural similarity. Areas covered: The concepts of AL modeling are introduced and its basis in quantitatively assessing molecular similarity is discussed. The different types of AL modeling approaches are introduced. AL designs can broadly be divided into three categories: compound-pair based, dimensionality reduction, and network approaches. Recent developments for each of these categories are discussed focusing on the application of mathematical, statistical, and machine learning tools for AL modeling. AL modeling using chemical space networks is covered in more detail. Expert opinion: AL modeling has remained a largely descriptive approach for the analysis of SARs. Beyond mere visualization, the application of analytical tools from statistics, machine learning and network theory has aided in the sophistication of AL designs and provides a step forward in transforming ALs from descriptive to predictive tools. To this end, optimizing representations that encode activity relevant features of molecules might prove to be a crucial step.
Heterogeneous recurrence monitoring and control of nonlinear stochastic processes
DOE Office of Scientific and Technical Information (OSTI.GOV)
Yang, Hui, E-mail: huiyang@usf.edu; Chen, Yun
Recurrence is one of the most common phenomena in natural and engineering systems. Process monitoring of dynamic transitions in nonlinear and nonstationary systems is more concerned with aperiodic recurrences and recurrence variations. However, little has been done to investigate the heterogeneous recurrence variations and link with the objectives of process monitoring and anomaly detection. Notably, nonlinear recurrence methodologies are based on homogeneous recurrences, which treat all recurrence states in the same way as black dots, and non-recurrence is white in recurrence plots. Heterogeneous recurrences are more concerned about the variations of recurrence states in terms of state properties (e.g., valuesmore » and relative locations) and the evolving dynamics (e.g., sequential state transitions). This paper presents a novel approach of heterogeneous recurrence analysis that utilizes a new fractal representation to delineate heterogeneous recurrence states in multiple scales, including the recurrences of both single states and multi-state sequences. Further, we developed a new set of heterogeneous recurrence quantifiers that are extracted from fractal representation in the transformed space. To that end, we integrated multivariate statistical control charts with heterogeneous recurrence analysis to simultaneously monitor two or more related quantifiers. Experimental results on nonlinear stochastic processes show that the proposed approach not only captures heterogeneous recurrence patterns in the fractal representation but also effectively monitors the changes in the dynamics of a complex system.« less
van Dijck, Jean-Philippe; Fias, Wim; Andres, Michael
2015-10-01
It has been proposed that the metrics of space, time and other magnitudes relevant for action are coupled through a generalized magnitude system that also contribute to number representation. Several studies capitalized on stimulus-response compatibility effects to show that numbers map onto left-right representations and grasp representations as a function of their magnitude. However, the tasks typically used do not allow disentangling magnitude from serial order processing. Here, we devised a working memory (WM) task where participants had to remember random sequences of numbers and perform a precision/whole-hand grip (Experiment 1) or a uni-manual left/right button press (Experiment 2) in response to numbers presented during the retention interval. This task does allow differentiating the interference of number magnitude and serial order with each set of responses. Experiment 1 showed that precision grips were initiated faster than whole-hand grips in response to small numbers, irrespective of their serial position in WM. In contrast, Experiment 2 revealed an advantage of right over left button presses as serial position increased, without any influence of number magnitude. These findings demonstrate that grasping and left-right movements overlap with distinct dimensions of number processing. These findings are discussed in the light of different theories explaining the interactions between numbers, space and action.
Sahan, Muhammet Ikbal; Verguts, Tom; Boehler, Carsten Nicolas; Pourtois, Gilles; Fias, Wim
2016-08-01
Selective attention is not limited to information that is physically present in the external world, but can also operate on mental representations in the internal world. However, it is not known whether the mechanisms of attentional selection operate in similar fashions in physical and mental space. We studied the spatial distributions of attention for items in physical and mental space by comparing how successfully distractors were rejected at varying distances from the attended location. The results indicated very similar distribution characteristics of spatial attention in physical and mental space. Specifically, we found that performance monotonically improved with increasing distractor distance relative to the attended location, suggesting that distractor confusability is particularly pronounced for nearby distractors, relative to distractors farther away. The present findings suggest that mental representations preserve their spatial configuration in working memory, and that similar mechanistic principles underlie selective attention in physical and in mental space.
Kernhof, Karin; Kaufhold, Johannes; Grabhorn, Ralph
2008-01-01
In this study, we examined how retrospective reports of experiencing traumatic sexual abuse in childhood relates to both the development of self-representations and object representations and the occurrence of interpersonal problems. A total of 30 psychosomatic female patients who reported sexual abuse in childhood were compared with a corresponding number of eating-disordered patients and a nonclinical control group. The object relations technique (ORT; Phillipson, 1955), evaluated using the Social Cognition and Object Relations Scale (SCORS; Westen, 1985, 1991b), and the Inventory of Interpersonal Problems (Horowitz, Rosenberg, Baer, & Ureno, 1988) were used to measure the groups. The patients reporting sexual abuse achieved significantly lower scores in the cognitive scales of the SCORS; in the affective scales, they differed from the control group but not from the patients with an eating disorder. Concerning interpersonal problems, the patients reporting childhood sexual abuse reported interpersonal conflicts more frequently. The results of the study support the influence of traumatic sexual abuse on the formation of self-representations and object representations and on the occurrence of interpersonal conflicts.
Microphysics, Radiation and Surface Processes in the Goddard Cumulus Ensemble (GCE) Model
NASA Technical Reports Server (NTRS)
Tao, Wei-Kuo; Starr, David (Technical Monitor)
2002-01-01
One of the most promising methods to test the representation of cloud processes used in climate models is to use observations together with Cloud Resolving Models (CRMs). The CRMs use more sophisticated and realistic representations of cloud microphysical processes, and they can reasonably well resolve the time evolution, structure, and life cycles of clouds and cloud systems (size about 2-200 km). The CRMs also allow explicit interaction between out-going longwave (cooling) and in-coming solar (heating) radiation with clouds. Observations can provide the initial conditions and validation for CRM results. The Goddard Cumulus Ensemble (GCE) Model, a CRM, has been developed and improved at NASA/Goddard Space Flight Center over the past two decades. The GCE model has been used to understand the following: 1) water and energy cycles and their roles in the tropical climate system; 2) the vertical redistribution of ozone and trace constituents by individual clouds and well organized convective systems over various spatial scales; 3) the relationship between the vertical distribution of latent heating (phase change of water) and the large-scale (pre-storm) environment; 4) the validity of assumptions used in the representation of cloud processes in climate and global circulation models; and 5) the representation of cloud microphysical processes and their interaction with radiative forcing over tropical and midlatitude regions. Four-dimensional cloud and latent heating fields simulated from the GCE model have been provided to the TRMM Science Data and Information System (TSDIS) to develop and improve algorithms for retrieving rainfall and latent heating rates for TRMM and the NASA Earth Observing System (EOS). More than 90 referred papers using the GCE model have been published in the last two decades. Also, more than 10 national and international universities are currently using the GCE model for research and teaching. In this talk, five specific major GCE improvements: (1) ice microphysics, (2) longwave and shortwave radiative transfer processes, (3) land surface processes, (4) ocean surface fluxes and (5) ocean mixed layer processes are presented. The performance of these new GCE improvements will be examined. Observations are used for model validation.
Representation of natural numbers in quantum mechanics
DOE Office of Scientific and Technical Information (OSTI.GOV)
Benioff, Paul
2001-03-01
This paper represents one approach to making explicit some of the assumptions and conditions implied in the widespread representation of numbers by composite quantum systems. Any nonempty set and associated operations is a set of natural numbers or a model of arithmetic if the set and operations satisfy the axioms of number theory or arithmetic. This paper is limited to k-ary representations of length L and to the axioms for arithmetic modulo k{sup L}. A model of the axioms is described based on an abstract L-fold tensor product Hilbert space H{sup arith}. Unitary maps of this space onto a physicalmore » parameter based product space H{sup phy} are then described. Each of these maps makes states in H{sup phy}, and the induced operators, a model of the axioms. Consequences of the existence of many of these maps are discussed along with the dependence of Grover's and Shor's algorithms on these maps. The importance of the main physical requirement, that the basic arithmetic operations are efficiently implementable, is discussed. This condition states that there exist physically realizable Hamiltonians that can implement the basic arithmetic operations and that the space-time and thermodynamic resources required are polynomial in L.« less
Coherent States for Kronecker Products of Non Compact Groups: Formulation and Applications
NASA Technical Reports Server (NTRS)
Bambah, Bindu A.; Agarwal, Girish S.
1996-01-01
We introduce and study the properties of a class of coherent states for the group SU(1,1) X SU(1,1) and derive explicit expressions for these using the Clebsch-Gordan algebra for the SU(1,1) group. We restrict ourselves to the discrete series representations of SU(1,1). These are the generalization of the 'Barut Girardello' coherent states to the Kronecker Product of two non-compact groups. The resolution of the identity and the analytic phase space representation of these states is presented. This phase space representation is based on the basis of products of 'pair coherent states' rather than the standard number state canonical basis. We discuss the utility of the resulting 'bi-pair coherent states' in the context of four-mode interactions in quantum optics.
The wheelchair as a full-body tool extending the peripersonal space
Galli, Giulia; Noel, Jean Paul; Canzoneri, Elisa; Blanke, Olaf; Serino, Andrea
2015-01-01
Dedicated multisensory mechanisms in the brain represent peripersonal space (PPS), a limited portion of space immediately surrounding the body. Previous studies have illustrated the malleability of PPS representation through hand-object interaction, showing that tool use extends the limits of the hand-centered PPS. In the present study we investigated the effects of a special tool, the wheelchair, in extending the action possibilities of the whole body. We used a behavioral measure to quantify the extension of the PPS around the body before and after Active (Experiment 1) and Passive (Experiment 2) training with a wheelchair and when participants were blindfolded (Experiment 3). Results suggest that a wheelchair-mediated passive exploration of far space extended PPS representation. This effect was specifically related to the possibility of receiving information from the environment through vision, since no extension effect was found when participants were blindfolded. Surprisingly, the active motor training did not induce any modification in PPS representation, probably because the wheelchair maneuver was demanding for non-expert users and thus they may have prioritized processing of information from close to the wheelchair rather than at far spatial locations. Our results suggest that plasticity in PPS representation after tool use seems not to strictly depend on active use of the tool itself, but is triggered by simultaneous processing of information from the body and the space where the body acts in the environment, which is more extended in the case of wheelchair use. These results contribute to our understanding of the mechanisms underlying body–environment interaction for developing and improving applications of assistive technological devices in different clinical populations. PMID:26042069
NASA Astrophysics Data System (ADS)
Melas, Evangelos
2017-07-01
The original Bondi-Metzner-Sachs (BMS) group B is the common asymptotic symmetry group of all asymptotically flat Lorentzian radiating 4-dim space-times. As such, B is the best candidate for the universal symmetry group of General Relativity (G.R.). In 1973, with this motivation, McCarthy classified all relativistic B-invariant systems in terms of strongly continuous irreducible unitary representations (IRS) of B. Here we introduce the analogue B(2, 1) of the BMS group B in 3 space-time dimensions. B(2, 1) itself admits thirty-four analogues both real in all signatures and in complex space-times. In order to find the IRS of both B(2, 1) and its analogues, we need to extend Wigner-Mackey's theory of induced representations. The necessary extension is described and is reduced to the solution of three problems. These problems are solved in the case where B(2, 1) and its analogues are equipped with the Hilbert topology. The extended theory is necessary in order to construct the IRS of both B and its analogues in any number d of space-time dimensions, d ≥3 , and also in order to construct the IRS of their supersymmetric counterparts. We use the extended theory to obtain the necessary data in order to construct the IRS of B(2, 1). The main results of the representation theory are as follows: The IRS are induced from "little groups" which are compact. The finite "little groups" are cyclic groups of even order. The inducing construction is exhaustive notwithstanding the fact that B(2, 1) is not locally compact in the employed Hilbert topology.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Butko, Yana A., E-mail: yanabutko@yandex.ru, E-mail: kinderknecht@math.uni-sb.de; Grothaus, Martin, E-mail: grothaus@mathematik.uni-kl.de; Smolyanov, Oleg G., E-mail: Smolyanov@yandex.ru
2016-02-15
Evolution semigroups generated by pseudo-differential operators are considered. These operators are obtained by different (parameterized by a number τ) procedures of quantization from a certain class of functions (or symbols) defined on the phase space. This class contains Hamilton functions of particles with variable mass in magnetic and potential fields and more general symbols given by the Lévy-Khintchine formula. The considered semigroups are represented as limits of n-fold iterated integrals when n tends to infinity. Such representations are called Feynman formulae. Some of these representations are constructed with the help of another pseudo-differential operator, obtained by the same procedure ofmore » quantization; such representations are called Hamiltonian Feynman formulae. Some representations are based on integral operators with elementary kernels; these are called Lagrangian Feynman formulae. Langrangian Feynman formulae provide approximations of evolution semigroups, suitable for direct computations and numerical modeling of the corresponding dynamics. Hamiltonian Feynman formulae allow to represent the considered semigroups by means of Feynman path integrals. In the article, a family of phase space Feynman pseudomeasures corresponding to different procedures of quantization is introduced. The considered evolution semigroups are represented as phase space Feynman path integrals with respect to these Feynman pseudomeasures, i.e., different quantizations correspond to Feynman path integrals with the same integrand but with respect to different pseudomeasures. This answers Berezin’s problem of distinguishing a procedure of quantization on the language of Feynman path integrals. Moreover, the obtained Lagrangian Feynman formulae allow also to calculate these phase space Feynman path integrals and to connect them with some functional integrals with respect to probability measures.« less
Grey-box state-space identification of nonlinear mechanical vibrations
NASA Astrophysics Data System (ADS)
Noël, J. P.; Schoukens, J.
2018-05-01
The present paper deals with the identification of nonlinear mechanical vibrations. A grey-box, or semi-physical, nonlinear state-space representation is introduced, expressing the nonlinear basis functions using a limited number of measured output variables. This representation assumes that the observed nonlinearities are localised in physical space, which is a generic case in mechanics. A two-step identification procedure is derived for the grey-box model parameters, integrating nonlinear subspace initialisation and weighted least-squares optimisation. The complete procedure is applied to an electrical circuit mimicking the behaviour of a single-input, single-output (SISO) nonlinear mechanical system and to a single-input, multiple-output (SIMO) geometrically nonlinear beam structure.
A challenge to chaotic itinerancy from brain dynamics
NASA Astrophysics Data System (ADS)
Kay, Leslie M.
2003-09-01
Brain hermeneutics and chaotic itinerancy proposed by Tsuda are attractive characterizations of perceptual dynamics in the mammalian olfactory system. This theory proposes that perception occurs at the interface between itinerant neural representation and interaction with the environment. Quantifiable application of these dynamics has been hampered by the lack of definable history and action processes which characterize the changes induced by behavioral state, attention, and learning. Local field potentials measured from several brain areas were used to characterize dynamic activity patterns for their use as representations of history and action processes. The signals were recorded from olfactory areas (olfactory bulb, OB, and pyriform cortex) and hippocampal areas (entorhinal cortex and dentate gyrus, DG) in the brains of rats. During odor-guided behavior the system shows dynamics at three temporal scales. Short time-scale changes are system-wide and can occur in the space of a single sniff. They are predictable, associated with learned shifts in behavioral state and occur periodically on the scale of the intertrial interval. These changes occupy the theta (2-12 Hz), beta (15-30 Hz), and gamma (40-100 Hz) frequency bands within and between all areas. Medium time-scale changes occur relatively unpredictably, manifesting in these data as alterations in connection strength between the OB and DG. These changes are strongly correlated with performance in associated trial blocks (5-10 min) and may be due to fluctuations in attention, mood, or amount of reward received. Long time-scale changes are likely related to learning or decline due to aging or disease. These may be modeled as slow monotonic processes that occur within or across days or even weeks or years. The folding of different time scales is proposed as a mechanism for chaotic itinerancy, represented by dynamic processes instead of static connection strengths. Thus, the individual maintains continuity of experience within the stability of fast periodic and slow monotonic processes, while medium scale events alter experience and performance dramatically but temporarily. These processes together with as yet to be determined action effects from motor system feedback are proposed as an instantiation of brain hermeneutics and chaotic itinerancy.
Integrating spatially explicit representations of landscape perceptions into land change research
Dorning, Monica; Van Berkel, Derek B.; Semmens, Darius J.
2017-01-01
Purpose of ReviewHuman perceptions of the landscape can influence land-use and land-management decisions. Recognizing the diversity of landscape perceptions across space and time is essential to understanding land change processes and emergent landscape patterns. We summarize the role of landscape perceptions in the land change process, demonstrate advances in quantifying and mapping landscape perceptions, and describe how these spatially explicit techniques have and may benefit land change research.Recent FindingsMapping landscape perceptions is becoming increasingly common, particularly in research focused on quantifying ecosystem services provision. Spatial representations of landscape perceptions, often measured in terms of landscape values and functions, provide an avenue for matching social and environmental data in land change studies. Integrating these data can provide new insights into land change processes, contribute to landscape planning strategies, and guide the design and implementation of land change models.SummaryChallenges remain in creating spatial representations of human perceptions. Maps must be accompanied by descriptions of whose perceptions are being represented and the validity and uncertainty of those representations across space. With these considerations, rapid advancements in mapping landscape perceptions hold great promise for improving representation of human dimensions in landscape ecology and land change research.
NASA Astrophysics Data System (ADS)
Krein, Michael
After decades of development and use in a variety of application areas, Quantitative Structure Property Relationships (QSPRs) and related descriptor-based statistical learning methods have achieved a level of infamy due to their misuse. The field is rife with past examples of overtrained models, overoptimistic performance assessment, and outright cheating in the form of explicitly removing data to fit models. These actions do not serve the community well, nor are they beneficial to future predictions based on established models. In practice, in order to select combinations of descriptors and machine learning methods that might work best, one must consider the nature and size of the training and test datasets, be aware of existing hypotheses about the data, and resist the temptation to bias structure representation and modeling to explicitly fit the hypotheses. The definition and application of these best practices is important for obtaining actionable modeling outcomes, and for setting user expectations of modeling accuracy when predicting the endpoint values of unknowns. A wide variety of statistical learning approaches, descriptor types, and model validation strategies are explored herein, with the goals of helping end users understand the factors involved in creating and using QSPR models effectively, and to better understand relationships within the data, especially by looking at the problem space from multiple perspectives. Molecular relationships are commonly envisioned in a continuous high-dimensional space of numerical descriptors, referred to as chemistry space. Descriptor and similarity metric choice influence the partitioning of this space into regions corresponding to local structural similarity. These regions, known as domains of applicability, are most likely to be successfully modeled by a QSPR. In Chapter 2, the network topology and scaling relationships of several chemistry spaces are thoroughly investigated. Chemistry spaces studied include the ZINC data set, a qHTS PubChem bioassay, as well as the protein binding sites from the PDB. The characteristics of these networks are compared and contrasted with those of the bioassay Structure Activity Landscape Index (SALI) subnetwork, which maps discontinuities or cliffs in the structure activity landscape. Mapping this newly generated information over underlying chemistry space networks generated using different descriptors demonstrates local modeling capacity and can guide the choice of better local representations of chemistry space. Chapter 2 introduces and demonstrates this novel concept, which also enables future work in visualization and interpretation of chemical spaces. Initially, it was discovered that there were no community-available tools to leverage best-practice ideas to comprehensively build, compare, and interpret QSPRs. The Yet Another Modeling System (YAMS) tool performs a series of balanced, rational decisions in dataset preprocessing and parameter/feature selection over a choice of modeling methods. To date, YAMS is the only community-available informatics tool that performs such decisions consistently between methods while also providing multiple model performance comparisons and detailed descriptor importance information. The focus of the tool is thus to convey rich information about model quality and predictions that help to "close the loop" between modeling and experimental efforts, for example, in tailoring nanocomposite properties. Polymer nanocomposites (PNC) are complex material systems encompassing many potential structures, chemistries, and self assembled morphologies that could significantly impact commercial and military applications. There is a strong desire to characterize and understand the tradespace of nanocomposites, to identify the important factors relating nanostructure to materials properties and determine an effective way to control materials properties at the manufacturing scale. Due to the complexity of the systems, existing design approaches rely heavily on trial-and-error learning. By leveraging existing experimental data, Materials Quantitative Structure-Property Relationships (MQSPRs) relate molecular structures to the polar and dispersive components of corresponding surface tensions. In turn, existing theories relate polymer and nanofiller polar and dispersive surface tension components to the dispersion state and interfacial polymer relaxation times. These quantities may, in the future, be used as input to continuum mechanics approaches shown able to predict the thermomechanical response of nanocomposites. For a polymer dataset and a particle dataset, multiple structural representations and descriptor sets are benchmarked, including a set of high performance surface-property descriptors developed as part of this work. The systematic variation of structural representations as part of the informatics approach reveals important insight in modeling polymers, and should become common practice when defining new problem spaces.
Graphical Representations of Electronic Search Patterns.
ERIC Educational Resources Information Center
Lin, Xia; And Others
1991-01-01
Discussion of search behavior in electronic environments focuses on the development of GRIP (Graphic Representor of Interaction Patterns), a graphing tool based on HyperCard that produces graphic representations of search patterns. Search state spaces are explained, and forms of data available from electronic searches are described. (34…
Multimodal Pedagogies in Diverse Classrooms: Representation, Rights and Resources
ERIC Educational Resources Information Center
Stein, Pippa
2012-01-01
Multimodal Pedagogies in Diverse Classrooms examines how the classroom can become a democratic space founded on the integration of different histories, modes of representation, feelings, languages and discourses, and is essential reading for anyone interested in the connection between multimodality, pedagogy, democracy and social justice in…
Learned Vector-Space Models for Document Retrieval.
ERIC Educational Resources Information Center
Caid, William R.; And Others
1995-01-01
The Latent Semantic Indexing and MatchPlus systems examine similar contexts in which words appear and create representational models that capture the similarity of meaning of terms and then use the representation for retrieval. Text Retrieval Conference experiments using these systems demonstrate the computational feasibility of using…
DOE Office of Scientific and Technical Information (OSTI.GOV)
Plimak, L.I., E-mail: Lev.Plimak@mbi-berlin.de; Olsen, M.K.
2014-12-15
In this work we present the formal background used to develop the methods used in earlier works to extend the truncated Wigner representation of quantum and atom optics in order to address multi-time problems. Analogs of Wick’s theorem for the Weyl ordering are verified. Using the Bose–Hubbard chain as an example, we show how these may be applied to constructing a mapping of the system in question to phase space. Regularisation issues and the reordering problem for the Heisenberg operators are addressed.
1981-02-01
converting Bu’s to Bal s Case 2: Pa,cc (t) = 0.25 + 0.075t = PaA(t) =1.0 In this case a space (and hence time) varying representation of the attrition rate...34 a Attrition rates can be made time ( space ) dependent. * Note that the attrition law is assumed for illustration only to be in accordance with a...34 Systems Reserach Lab., Dept. of Industrial Eng., University of Michigan. Gaver, D.P. and Tonguc K. (1979) "Modelling the influnece of information on
Visual Analytics of integrated Data Systems for Space Weather Purposes
NASA Astrophysics Data System (ADS)
Rosa, Reinaldo; Veronese, Thalita; Giovani, Paulo
Analysis of information from multiple data sources obtained through high resolution instrumental measurements has become a fundamental task in all scientific areas. The development of expert methods able to treat such multi-source data systems, with both large variability and measurement extension, is a key for studying complex scientific phenomena, especially those related to systemic analysis in space and environmental sciences. In this talk, we present a time series generalization introducing the concept of generalized numerical lattice, which represents a discrete sequence of temporal measures for a given variable. In this novel representation approach each generalized numerical lattice brings post-analytical data information. We define a generalized numerical lattice as a set of three parameters representing the following data properties: dimensionality, size and post-analytical measure (e.g., the autocorrelation, Hurst exponent, etc)[1]. From this representation generalization, any multi-source database can be reduced to a closed set of classified time series in spatiotemporal generalized dimensions. As a case study, we show a preliminary application in space science data, highlighting the possibility of a real time analysis expert system. In this particular application, we have selected and analyzed, using detrended fluctuation analysis (DFA), several decimetric solar bursts associated to X flare-classes. The association with geomagnetic activity is also reported. DFA method is performed in the framework of a radio burst automatic monitoring system. Our results may characterize the variability pattern evolution, computing the DFA scaling exponent, scanning the time series by a short windowing before the extreme event [2]. For the first time, the application of systematic fluctuation analysis for space weather purposes is presented. The prototype for visual analytics is implemented in a Compute Unified Device Architecture (CUDA) by using the K20 Nvidia graphics processing units (GPUs) to reduce the integrated analysis runtime. [1] Veronese et al. doi: 10.6062/jcis.2009.01.02.0021, 2010. [2] Veronese et al. doi:http://dx.doi.org/10.1016/j.jastp.2010.09.030, 2011.
Wavelet-based multiscale window transform and energy and vorticity analysis
NASA Astrophysics Data System (ADS)
Liang, Xiang San
A new methodology, Multiscale Energy and Vorticity Analysis (MS-EVA), is developed to investigate sub-mesoscale, meso-scale, and large-scale dynamical interactions in geophysical fluid flows which are intermittent in space and time. The development begins with the construction of a wavelet-based functional analysis tool, the multiscale window transform (MWT), which is local, orthonormal, self-similar, and windowed on scale. The MWT is first built over the real line then modified onto a finite domain. Properties are explored, the most important one being the property of marginalization which brings together a quadratic quantity in physical space with its phase space representation. Based on MWT the MS-EVA is developed. Energy and enstrophy equations for the large-, meso-, and sub-meso-scale windows are derived and their terms interpreted. The processes thus represented are classified into four categories: transport; transfer, conversion, and dissipation/diffusion. The separation of transport from transfer is made possible with the introduction of the concept of perfect transfer. By the property of marginalization, the classical energetic analysis proves to be a particular case of the MS-EVA. The MS-EVA developed is validated with classical instability problems. The validation is carried out through two steps. First, it is established that the barotropic and baroclinic instabilities are indicated by the spatial averages of certain transfer term interaction analyses. Then calculations of these indicators are made with an Eady model and a Kuo model. The results agree precisely with what is expected from their analytical solutions, and the energetics reproduced reveal a consistent and important aspect of the unknown dynamic structures of instability processes. As an application, the MS-EVA is used to investigate the Iceland-Faeroe frontal (IFF) variability. A MS-EVA-ready dataset is first generated, through a forecasting study with the Harvard Ocean Prediction System using the data gathered during the 1993 NRV Alliance cruise. The application starts with a determination of the scale window bounds, which characterize a double-peak structure in either the time wavelet spectrum or the space wavelet spectrum. The resulting energetics, when locally averaged, reveal that there is a clear baroclinic instability happening around the cold tongue intrusion observed in the forecast. Moreover, an interaction analysis shows that the energy released by the instability indeed goes to the meso-scale window and fuel the growth of the intrusion. The sensitivity study shows that, in this case, the key to a successful application is a correct decomposition of the large-scale window from the meso-scale window.
Covariant scalar representation of ? and quantization of the scalar relativistic particle
NASA Astrophysics Data System (ADS)
Jarvis, P. D.; Tsohantjis, I.
1996-03-01
A covariant scalar representation of iosp(d,2/2) is constructed and analysed in comparison with existing BFV-BRST methods for the quantization of the scalar relativistic particle. It is found that, with appropriately defined wavefunctions, this iosp(d,2/2) produced representation can be identified with the state space arising from the canonical BFV-BRST quantization of the modular-invariant, unoriented scalar particle (or antiparticle) with admissible gauge-fixing conditions. For this model, the cohomological determination of physical states can thus be obtained purely from the representation theory of the iosp(d,2/2) algebra.
2017-01-01
Studies comparing neuronal activity at the dorsal and ventral poles of the hippocampus have shown that the scale of spatial information increases and the precision with which space is represented declines from the dorsal to ventral end. These dorsoventral differences in neuronal output and spatial representation could arise due to differences in computations performed by dorsal and ventral CA1 neurons. In this study, we tested this hypothesis by quantifying the differences in dendritic integration and synaptic plasticity between dorsal and ventral CA1 pyramidal neurons of rat hippocampus. Using a combination of somatic and dendritic patch-clamp recordings, we show that the threshold for LTP induction is higher in dorsal CA1 neurons and that a G-protein-coupled inward-rectifying potassium channel mediated regulation of dendritic plateau potentials and dendritic excitability underlies this gating. By contrast, similar regulation of LTP is absent in ventral CA1 neurons. Additionally, we show that generation of plateau potentials and LTP induction in dorsal CA1 neurons depends on the coincident activation of Schaffer collateral and temporoammonic inputs at the distal apical dendrites. The ventral CA1 dendrites, however, can generate plateau potentials in response to temporally dispersed excitatory inputs. Overall, our results highlight the dorsoventral differences in dendritic computation that could account for the dorsoventral differences in spatial representation. SIGNIFICANCE STATEMENT The dorsal and ventral parts of the hippocampus encode spatial information at very different scales. Whereas the place-specific firing fields are small and precise at the dorsal end of the hippocampus, neurons at the ventral end have comparatively larger place fields. Here, we show that the dorsal CA1 neurons have a higher threshold for LTP induction and require coincident timing of excitatory synaptic inputs for the generation of dendritic plateau potentials. By contrast, ventral CA1 neurons can integrate temporally dispersed inputs and have a lower threshold for LTP. Together, these dorsoventral differences in the threshold for LTP induction could account for the differences in scale of spatial representation at the dorsal and ventral ends of the hippocampus. PMID:28280255
Malik, Ruchi; Johnston, Daniel
2017-04-05
Studies comparing neuronal activity at the dorsal and ventral poles of the hippocampus have shown that the scale of spatial information increases and the precision with which space is represented declines from the dorsal to ventral end. These dorsoventral differences in neuronal output and spatial representation could arise due to differences in computations performed by dorsal and ventral CA1 neurons. In this study, we tested this hypothesis by quantifying the differences in dendritic integration and synaptic plasticity between dorsal and ventral CA1 pyramidal neurons of rat hippocampus. Using a combination of somatic and dendritic patch-clamp recordings, we show that the threshold for LTP induction is higher in dorsal CA1 neurons and that a G-protein-coupled inward-rectifying potassium channel mediated regulation of dendritic plateau potentials and dendritic excitability underlies this gating. By contrast, similar regulation of LTP is absent in ventral CA1 neurons. Additionally, we show that generation of plateau potentials and LTP induction in dorsal CA1 neurons depends on the coincident activation of Schaffer collateral and temporoammonic inputs at the distal apical dendrites. The ventral CA1 dendrites, however, can generate plateau potentials in response to temporally dispersed excitatory inputs. Overall, our results highlight the dorsoventral differences in dendritic computation that could account for the dorsoventral differences in spatial representation. SIGNIFICANCE STATEMENT The dorsal and ventral parts of the hippocampus encode spatial information at very different scales. Whereas the place-specific firing fields are small and precise at the dorsal end of the hippocampus, neurons at the ventral end have comparatively larger place fields. Here, we show that the dorsal CA1 neurons have a higher threshold for LTP induction and require coincident timing of excitatory synaptic inputs for the generation of dendritic plateau potentials. By contrast, ventral CA1 neurons can integrate temporally dispersed inputs and have a lower threshold for LTP. Together, these dorsoventral differences in the threshold for LTP induction could account for the differences in scale of spatial representation at the dorsal and ventral ends of the hippocampus. Copyright © 2017 the authors 0270-6474/17/373940-16$15.00/0.
ERIC Educational Resources Information Center
Monreal, Timothy
2016-01-01
Henri Lefebvre (1991) wrote, "[representational] space is alive: it speaks" (p. 42). This article explores how we might "listen" to space in education by examining the role of space in one school's decision to adopt the International Baccalaureate's Middle Years Programme [IB MYP]. It builds upon recent scholarship that applies…
Resignifying the Negative Space: Troubling the Representation of Learning
ERIC Educational Resources Information Center
Fendler, Rachel
2017-01-01
Informed by the results of a collaborative project carried out with six secondary school students, this paper reflects on the methodological and epistemological issues related to the representation of informal learning practices. Borrowing a concept from the arts, I suggest that a representationalist logic in both schooling and educational…
A Nomad Faculty: English Professors Negotiate Self-Representation in University Web Space.
ERIC Educational Resources Information Center
Hess, Micky
2002-01-01
Calls for increased awareness of the self-representation, gender, labor, and intellectual property issues that surround faculty members' homepages, arguing that faculty members construct identity online in context of the university as workplace. Examines the homepages of 18 faculty members within English programs. Draws on research from…
Individuals and Leadership in an Australian Secondary Science Department: A Qualitative Study
ERIC Educational Resources Information Center
Melville, Wayne; Wallace, John; Bartley, Anthony
2007-01-01
In this article, we consider the complex and dynamic inter-relationships between individual science teachers, the social space of their work and their dispositions towards teacher leadership. Research into the representation of school science departments through individual science teachers is scarce. We explore the representations of four…
Poelmans, Ward; Van Raemdonck, Mario; Verstichel, Brecht; De Baerdemacker, Stijn; Torre, Alicia; Lain, Luis; Massaccesi, Gustavo E; Alcoba, Diego R; Bultinck, Patrick; Van Neck, Dimitri
2015-09-08
We perform a direct variational determination of the second-order (two-particle) density matrix corresponding to a many-electron system, under a restricted set of the two-index N-representability P-, Q-, and G-conditions. In addition, we impose a set of necessary constraints that the two-particle density matrix must be derivable from a doubly occupied many-electron wave function, i.e., a singlet wave function for which the Slater determinant decomposition only contains determinants in which spatial orbitals are doubly occupied. We rederive the two-index N-representability conditions first found by Weinhold and Wilson and apply them to various benchmark systems (linear hydrogen chains, He, N2, and CN(-)). This work is motivated by the fact that a doubly occupied many-electron wave function captures in many cases the bulk of the static correlation. Compared to the general case, the structure of doubly occupied two-particle density matrices causes the associate semidefinite program to have a very favorable scaling as L(3), where L is the number of spatial orbitals. Since the doubly occupied Hilbert space depends on the choice of the orbitals, variational calculation steps of the two-particle density matrix are interspersed with orbital-optimization steps (based on Jacobi rotations in the space of the spatial orbitals). We also point to the importance of symmetry breaking of the orbitals when performing calculations in a doubly occupied framework.
Fock space, symbolic algebra, and analytical solutions for small stochastic systems.
Santos, Fernando A N; Gadêlha, Hermes; Gaffney, Eamonn A
2015-12-01
Randomness is ubiquitous in nature. From single-molecule biochemical reactions to macroscale biological systems, stochasticity permeates individual interactions and often regulates emergent properties of the system. While such systems are regularly studied from a modeling viewpoint using stochastic simulation algorithms, numerous potential analytical tools can be inherited from statistical and quantum physics, replacing randomness due to quantum fluctuations with low-copy-number stochasticity. Nevertheless, classical studies remained limited to the abstract level, demonstrating a more general applicability and equivalence between systems in physics and biology rather than exploiting the physics tools to study biological systems. Here the Fock space representation, used in quantum mechanics, is combined with the symbolic algebra of creation and annihilation operators to consider explicit solutions for the chemical master equations describing small, well-mixed, biochemical, or biological systems. This is illustrated with an exact solution for a Michaelis-Menten single enzyme interacting with limited substrate, including a consideration of very short time scales, which emphasizes when stiffness is present even for small copy numbers. Furthermore, we present a general matrix representation for Michaelis-Menten kinetics with an arbitrary number of enzymes and substrates that, following diagonalization, leads to the solution of this ubiquitous, nonlinear enzyme kinetics problem. For this, a flexible symbolic maple code is provided, demonstrating the prospective advantages of this framework compared to stochastic simulation algorithms. This further highlights the possibilities for analytically based studies of stochastic systems in biology and chemistry using tools from theoretical quantum physics.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Rosales-Zarate, Laura E. C.; Drummond, P. D.
We calculate the quantum Renyi entropy in a phase-space representation for either fermions or bosons. This can also be used to calculate purity and fidelity, or the entanglement between two systems. We show that it is possible to calculate the entropy from sampled phase-space distributions in normally ordered representations, although this is not possible for all quantum states. We give an example of the use of this method in an exactly soluble thermal case. The quantum entropy cannot be calculated at all using sampling methods in classical symmetric (Wigner) or antinormally ordered (Husimi) phase spaces, due to inner-product divergences. Themore » preferred method is to use generalized Gaussian phase-space methods, which utilize a distribution over stochastic Green's functions. We illustrate this approach by calculating the reduced entropy and entanglement of bosonic or fermionic modes coupled to a time-evolving, non-Markovian reservoir.« less
Geometric Representations of Condition Queries on Three-Dimensional Vector Fields
NASA Technical Reports Server (NTRS)
Henze, Chris
1999-01-01
Condition queries on distributed data ask where particular conditions are satisfied. It is possible to represent condition queries as geometric objects by plotting field data in various spaces derived from the data, and by selecting loci within these derived spaces which signify the desired conditions. Rather simple geometric partitions of derived spaces can represent complex condition queries because much complexity can be encapsulated in the derived space mapping itself A geometric view of condition queries provides a useful conceptual unification, allowing one to intuitively understand many existing vector field feature detection algorithms -- and to design new ones -- as variations on a common theme. A geometric representation of condition queries also provides a simple and coherent basis for computer implementation, reducing a wide variety of existing and potential vector field feature detection techniques to a few simple geometric operations.
Strategies to Evaluate the Visibility Along AN Indoor Path in a Point Cloud Representation
NASA Astrophysics Data System (ADS)
Grasso, N.; Verbree, E.; Zlatanova, S.; Piras, M.
2017-09-01
Many research works have been oriented to the formulation of different algorithms for estimating the paths in indoor environments from three-dimensional representations of space. The architectural configuration, the actions that take place within it, and the location of some objects in the space influence the paths along which is it possible to move, as they may cause visibility problems. To overcome the visibility issue, different methods have been proposed which allow to identify the visible areas and from a certain point of view, but often they do not take into account the user's visual perception of the environment and not allow estimating how much may be complicated to follow a certain path. In the field of space syntax and cognitive science, it has been attempted to describe the characteristics of a building or an urban environment by the isovists and visibility graphs methods; some numerical properties of these representations allow to describe the space as for how it is perceived by a user. However, most of these studies are directed to analyze the environment in a two-dimensional space. In this paper we propose a method to evaluate in a quantitative way the complexity of a certain path within an environment represented by a three-dimensional point cloud, by the combination of some of the previously mentioned techniques, considering the space visible from a certain point of view, depending on the moving agent (pedestrian , people in wheelchairs, UAV, UGV, robot).
Source imaging of potential fields through a matrix space-domain algorithm
NASA Astrophysics Data System (ADS)
Baniamerian, Jamaledin; Oskooi, Behrooz; Fedi, Maurizio
2017-01-01
Imaging of potential fields yields a fast 3D representation of the source distribution of potential fields. Imaging methods are all based on multiscale methods allowing the source parameters of potential fields to be estimated from a simultaneous analysis of the field at various scales or, in other words, at many altitudes. Accuracy in performing upward continuation and differentiation of the field has therefore a key role for this class of methods. We here describe an accurate method for performing upward continuation and vertical differentiation in the space-domain. We perform a direct discretization of the integral equations for upward continuation and Hilbert transform; from these equations we then define matrix operators performing the transformation, which are symmetric (upward continuation) or anti-symmetric (differentiation), respectively. Thanks to these properties, just the first row of the matrices needs to be computed, so to decrease dramatically the computation cost. Our approach allows a simple procedure, with the advantage of not involving large data extension or tapering, as due instead in case of Fourier domain computation. It also allows level-to-drape upward continuation and a stable differentiation at high frequencies; finally, upward continuation and differentiation kernels may be merged into a single kernel. The accuracy of our approach is shown to be important for multi-scale algorithms, such as the continuous wavelet transform or the DEXP (depth from extreme point method), because border errors, which tend to propagate largely at the largest scales, are radically reduced. The application of our algorithm to synthetic and real-case gravity and magnetic data sets confirms the accuracy of our space domain strategy over FFT algorithms and standard convolution procedures.
Four decades of modeling methane cycling in terrestrial ecosystems: Where we are heading?
NASA Astrophysics Data System (ADS)
Xu, X.; Yuan, F.; Hanson, P. J.; Wullschleger, S. D.; Thornton, P. E.; Tian, H.; Riley, W. J.; Song, X.; Graham, D. E.; Song, C.
2015-12-01
A modeling approach to methane (CH4) is widely used to quantify the budget, investigate spatial and temporal variabilities, and understand the mechanistic processes and environmental controls on CH4 fluxes across spatial and temporal scales. Moreover, CH4 models are an important tool for integrating CH4 data from multiple sources, such as laboratory-based incubation and molecular analysis, field observational experiments, remote sensing, and aircraft-based measurements across a variety of terrestrial ecosystems. We reviewed 39 terrestrial CH4 models to characterize their strengths and weaknesses and to design a roadmap for future model improvement and application. We found that: (1) the focus of CH4 models have been shifted from theoretical to site- to regional-level application over the past four decades, expressed as dramatic increases in CH4 model development on regional budget quantification; (2) large discrepancies exist among models in terms of representing CH4 processes and their environmental controls; (3) significant data-model and model-model mismatches are partially attributed to different representations of wetland characterization and inundation dynamics. Three efforts should be paid special attention for future improvements and applications of fully mechanistic CH4 models: (1) CH4 models should be improved to represent the mechanisms underlying land-atmosphere CH4 exchange, with emphasis on improving and validating individual CH4 processes over depth and horizontal space; (2) models should be developed that are capable of simulating CH4 fluxes across space and time (particularly hot moments and hot spots); (3) efforts should be invested to develop model benchmarking frameworks that can easily be used for model improvement, evaluation, and integration with data from molecular to global scales. A newly developed microbial functional group-based CH4 model (CLM-Microbe) was further used to demonstrate the features of mechanistic representation and integration with multiple source of observational datasets.
Re-engineering NASA's space communications to remain viable in a constrained fiscal environment
NASA Astrophysics Data System (ADS)
Hornstein, Rhoda Shaller; Hei, Donald J., Jr.; Kelly, Angelita C.; Lightfoot, Patricia C.; Bell, Holland T.; Cureton-Snead, Izeller E.; Hurd, William J.; Scales, Charles H.
1994-11-01
Along with the Red and Blue Teams commissioned by the NASA Administrator in 1992, NASA's Associate Administrator for Space Communications commissioned a Blue Team to review the Office of Space Communications (Code O) Core Program and determine how the program could be conducted faster, better, and cheaper. Since there was no corresponding Red Team for the Code O Blue Team, the Blue Team assumed a Red Team independent attitude and challenged the status quo, including current work processes, functional distinctions, interfaces, and information flow, as well as traditional management and system development practices. The Blue Team's unconstrained, non-parochial, and imaginative look at NASA's space communications program produced a simplified representation of the space communications infrastructure that transcends organizational and functional boundaries, in addition to existing systems and facilities. Further, the Blue Team adapted the 'faster, better, cheaper' charter to be relevant to the multi-mission, continuous nature of the space communications program and to serve as a gauge for improving customer services concurrent with achieving more efficient operations and infrastructure life cycle economies. This simplified representation, together with the adapted metrics, offers a future view and process model for reengineering NASA's space communications to remain viable in a constrained fiscal environment. Code O remains firm in its commitment to improve productivity, effectiveness, and efficiency. In October 1992, the Associate Administrator reconstituted the Blue Team as the Code O Success Team (COST) to serve as a catalyst for change. In this paper, the COST presents the chronicle and significance of the simplified representation and adapted metrics, and their application during the FY 1993-1994 activities.
Exactly solvable quantum cosmologies from two killing field reductions of general relativity
NASA Astrophysics Data System (ADS)
Husain, Viqar; Smolin, Lee
1989-11-01
An exact and, possibly, general solution to the quantum constraints is given for the sector of general relativity containing cosmological solutions with two space-like, commuting, Killing fields. The dynamics of these model space-times, which are known as Gowdy space-times, is formulated in terms of Ashtekar's new variables. The quantization is done by using the recently introduced self-dual and loop representations. On the classical phase space we find four explicit physical observables, or constants of motion, which generate a GL(2) symmetry group on the space of solutions. In the loop representations we find that a complete description of the physical state space, consisting of the simultaneous solutions to all of the constraints, is given in terms of the equivalence classes, under Diff(S1), of a pair of densities on the circle. These play the same role that the link classes play in the loop representation solution to the full 3+1 theory. An infinite dimensional algebra of physical observables is found on the physical state space, which is a GL(2) loop algebra. In addition, by freezing the local degrees of freedom of the model, we find a finite dimensional quantum system which describes a set of degenerate quantum cosmologies on T3 in which the length of one of the S1's has gone to zero, while the area of the remaining S1×S1 is quantized in units of the Planck area. The quantum kinematics of this sector of the model is identical to that of a one-plaquette SU(2) lattice gauge theory.
Re-engineering NASA's space communications to remain viable in a constrained fiscal environment
NASA Technical Reports Server (NTRS)
Hornstein, Rhoda Shaller; Hei, Donald J., Jr.; Kelly, Angelita C.; Lightfoot, Patricia C.; Bell, Holland T.; Cureton-Snead, Izeller E.; Hurd, William J.; Scales, Charles H.
1994-01-01
Along with the Red and Blue Teams commissioned by the NASA Administrator in 1992, NASA's Associate Administrator for Space Communications commissioned a Blue Team to review the Office of Space Communications (Code O) Core Program and determine how the program could be conducted faster, better, and cheaper. Since there was no corresponding Red Team for the Code O Blue Team, the Blue Team assumed a Red Team independent attitude and challenged the status quo, including current work processes, functional distinctions, interfaces, and information flow, as well as traditional management and system development practices. The Blue Team's unconstrained, non-parochial, and imaginative look at NASA's space communications program produced a simplified representation of the space communications infrastructure that transcends organizational and functional boundaries, in addition to existing systems and facilities. Further, the Blue Team adapted the 'faster, better, cheaper' charter to be relevant to the multi-mission, continuous nature of the space communications program and to serve as a gauge for improving customer services concurrent with achieving more efficient operations and infrastructure life cycle economies. This simplified representation, together with the adapted metrics, offers a future view and process model for reengineering NASA's space communications to remain viable in a constrained fiscal environment. Code O remains firm in its commitment to improve productivity, effectiveness, and efficiency. In October 1992, the Associate Administrator reconstituted the Blue Team as the Code O Success Team (COST) to serve as a catalyst for change. In this paper, the COST presents the chronicle and significance of the simplified representation and adapted metrics, and their application during the FY 1993-1994 activities.
Bastien, Olivier; Ortet, Philippe; Roy, Sylvaine; Maréchal, Eric
2005-03-10
Popular methods to reconstruct molecular phylogenies are based on multiple sequence alignments, in which addition or removal of data may change the resulting tree topology. We have sought a representation of homologous proteins that would conserve the information of pair-wise sequence alignments, respect probabilistic properties of Z-scores (Monte Carlo methods applied to pair-wise comparisons) and be the basis for a novel method of consistent and stable phylogenetic reconstruction. We have built up a spatial representation of protein sequences using concepts from particle physics (configuration space) and respecting a frame of constraints deduced from pair-wise alignment score properties in information theory. The obtained configuration space of homologous proteins (CSHP) allows the representation of real and shuffled sequences, and thereupon an expression of the TULIP theorem for Z-score probabilities. Based on the CSHP, we propose a phylogeny reconstruction using Z-scores. Deduced trees, called TULIP trees, are consistent with multiple-alignment based trees. Furthermore, the TULIP tree reconstruction method provides a solution for some previously reported incongruent results, such as the apicomplexan enolase phylogeny. The CSHP is a unified model that conserves mutual information between proteins in the way physical models conserve energy. Applications include the reconstruction of evolutionary consistent and robust trees, the topology of which is based on a spatial representation that is not reordered after addition or removal of sequences. The CSHP and its assigned phylogenetic topology, provide a powerful and easily updated representation for massive pair-wise genome comparisons based on Z-score computations.
Niskanen, Eini; Julkunen, Petro; Säisänen, Laura; Vanninen, Ritva; Karjalainen, Pasi; Könönen, Mervi
2010-08-01
Navigated transcranial magnetic stimulation (TMS) can be used to stimulate functional cortical areas at precise anatomical location to induce measurable responses. The stimulation has commonly been focused on anatomically predefined motor areas: TMS of that area elicits a measurable muscle response, the motor evoked potential. In clinical pathologies, however, the well-known homunculus somatotopy theory may not be straightforward, and the representation area of the muscle is not fixed. Traditionally, the anatomical locations of TMS stimulations have not been reported at the group level in standard space. This study describes a methodology for group-level analysis by investigating the normal representation areas of thenar and anterior tibial muscle in the primary motor cortex. The optimal representation area for these muscles was mapped in 59 healthy right-handed subjects using navigated TMS. The coordinates of the optimal stimulation sites were then normalized into standard space to determine the representation areas of these muscles at the group-level in healthy subjects. Furthermore, 95% confidence interval ellipsoids were fitted into the optimal stimulation site clusters to define the variation between subjects in optimal stimulation sites. The variation was found to be highest in the anteroposterior direction along the superior margin of the precentral gyrus. These results provide important normative information for clinical studies assessing changes in the functional cortical areas because of plasticity of the brain. Furthermore, it is proposed that the presented methodology to study TMS locations at the group level on standard space will be a suitable tool for research purposes in population studies. 2010 Wiley-Liss, Inc.
NASA Technical Reports Server (NTRS)
Brewer, E. B.
1975-01-01
A 0.013 scale model of the solid rocket booster (SRB) used to launch the space shuttle was tested at a Mach number of 3.7 and Reynolds numbers of 1,500,000 and 3,500,000 per foot. The objective of the test was to obtain aerodynamic heat transfer data on the surface of scaled models of the SRB at simulated full scale reentry flight conditions. Three separate models were utilized to measure film coefficients over an angle of attack range from 0 deg to 180 deg at 0 deg sideslip. All three models were representations of the MCR0200 baseline configuration and varied only by the way they were mounted in the tunnel. Model A, sting mounted thru the model base, was utilized for testing between 0 deg and 40 deg angle of attack. Model B was blade mounted from the top of the model and was tested between 60 deg and 120 deg angle of attack. Model C was sting mounted thru the model nose and utilized for testing between 140 deg and 180 deg angle of attack.
Alsmadi, Othman M K; Abo-Hammour, Zaer S
2015-01-01
A robust computational technique for model order reduction (MOR) of multi-time-scale discrete systems (single input single output (SISO) and multi-input multioutput (MIMO)) is presented in this paper. This work is motivated by the singular perturbation of multi-time-scale systems where some specific dynamics may not have significant influence on the overall system behavior. The new approach is proposed using genetic algorithms (GA) with the advantage of obtaining a reduced order model, maintaining the exact dominant dynamics in the reduced order, and minimizing the steady state error. The reduction process is performed by obtaining an upper triangular transformed matrix of the system state matrix defined in state space representation along with the elements of B, C, and D matrices. The GA computational procedure is based on maximizing the fitness function corresponding to the response deviation between the full and reduced order models. The proposed computational intelligence MOR method is compared to recently published work on MOR techniques where simulation results show the potential and advantages of the new approach.
Scalar spectral measures associated with an operator-fractal
DOE Office of Scientific and Technical Information (OSTI.GOV)
Jorgensen, Palle E. T., E-mail: jorgen@math.uiowa.edu; Kornelson, Keri A., E-mail: kkornelson@ou.edu; Shuman, Karen L.
2014-02-15
We study a spectral-theoretic model on a Hilbert space L{sup 2}(μ) where μ is a fixed Cantor measure. In addition to μ, we also consider an independent scaling operator U acting in L{sup 2}(μ). To make our model concrete, we focus on explicit formulas: We take μ to be the Bernoulli infinite-convolution measure corresponding to scale number 1/4 . We then define the unitary operator U in L{sup 2}(μ) from a scale-by-5 operation. The spectral-theoretic and geometric properties we have previously established for U are as follows: (i) U acts as an ergodic operator; (ii) the action of U ismore » not spatial; and finally, (iii) U is fractal in the sense that it is unitarily equivalent to a countable infinite direct sum of (twisted) copies of itself. In this paper, we prove new results about the projection-valued measures and scalar spectral measures associated to U and its constituent parts. Our techniques make use of the representations of the Cuntz algebra O{sub 2} on L{sup 2}(μ)« less
NASA Astrophysics Data System (ADS)
Spero, Tanya L.; Otte, Martin J.; Bowden, Jared H.; Nolte, Christopher G.
2014-10-01
Spectral nudging—a scale-selective interior constraint technique—is commonly used in regional climate models to maintain consistency with large-scale forcing while permitting mesoscale features to develop in the downscaled simulations. Several studies have demonstrated that spectral nudging improves the representation of regional climate in reanalysis-forced simulations compared with not using nudging in the interior of the domain. However, in the Weather Research and Forecasting (WRF) model, spectral nudging tends to produce degraded precipitation simulations when compared to analysis nudging—an interior constraint technique that is scale indiscriminate but also operates on moisture fields which until now could not be altered directly by spectral nudging. Since analysis nudging is less desirable for regional climate modeling because it dampens fine-scale variability, changes are proposed to the spectral nudging methodology to capitalize on differences between the nudging techniques and aim to improve the representation of clouds, radiation, and precipitation without compromising other fields. These changes include adding spectral nudging toward moisture, limiting nudging to below the tropopause, and increasing the nudging time scale for potential temperature, all of which collectively improve the representation of mean and extreme precipitation, 2 m temperature, clouds, and radiation, as demonstrated using a model-simulated 20 year historical period. Such improvements to WRF may increase the fidelity of regional climate data used to assess the potential impacts of climate change on human health and the environment and aid in climate change mitigation and adaptation studies.
Ascarrunz, F G; Kisley, M A; Flach, K A; Hamilton, R W; MacGregor, R J
1995-07-01
This paper applies a general mathematical system for characterizing and scaling functional connectivity and information flow across the diffuse (EC) and discrete (DG) input junctions to the CA3 hippocampus. Both gross connectivity and coordinated multiunit informational firing patterns are quantitatively characterized in terms of 32 defining parameters interrelated by 17 equations, and then scaled down according to rules for uniformly proportional scaling and for partial representation. The diffuse EC-CA3 junction is shown to be uniformly scalable with realistic representation of both essential spatiotemporal cooperativity and coordinated firing patterns down to populations of a few hundred neurons. Scaling of the discrete DG-CA3 junction can be effected with a two-step process, which necessarily deviates from uniform proportionality but nonetheless produces a valuable and readily interpretable reduced model, also utilizing a few hundred neurons in the receiving population. Partial representation produces a reduced model of only a portion of the full network where each model neuron corresponds directly to a biological neuron. The mathematical analysis illustrated here shows that although omissions and distortions are inescapable in such an application, satisfactorily complete and accurate models the size of pattern modules are possible. Finally, the mathematical characterization of these junctions generates a theory which sees the DG as a definer of the fine structure of embedded traces in the hippocampus and entire coordinated patterns of sequences of 14-cell links in CA3 as triggered by the firing of sequences of individual neurons in DG.
Lossless Coding Standards for Space Data Systems
NASA Technical Reports Server (NTRS)
Rice, R. F.
1996-01-01
The International Consultative Committee for Space Data Systems (CCSDS) is preparing to issue its first recommendation for a digital data compression standard. Because the space data systems of primary interest are employed to support scientific investigations requiring accurate representation, this initial standard will be restricted to lossless compression.
The Role of Familiarity for Representations in Norm-Based Face Space
Faerber, Stella J.; Kaufmann, Jürgen M.; Leder, Helmut; Martin, Eva Maria; Schweinberger, Stefan R.
2016-01-01
According to the norm-based version of the multidimensional face space model (nMDFS, Valentine, 1991), any given face and its corresponding anti-face (which deviates from the norm in exactly opposite direction as the original face) should be equidistant to a hypothetical prototype face (norm), such that by definition face and anti-face should bear the same level of perceived typicality. However, it has been argued that familiarity affects perceived typicality and that representations of familiar faces are qualitatively different (e.g., more robust and image-independent) from those for unfamiliar faces. Here we investigated the role of face familiarity for rated typicality, using two frequently used operationalisations of typicality (deviation-based: DEV), and distinctiveness (face in the crowd: FITC) for faces of celebrities and their corresponding anti-faces. We further assessed attractiveness, likeability and trustworthiness ratings of the stimuli, which are potentially related to typicality. For unfamiliar faces and their corresponding anti-faces, in line with the predictions of the nMDFS, our results demonstrate comparable levels of perceived typicality (DEV). In contrast, familiar faces were perceived much less typical than their anti-faces. Furthermore, familiar faces were rated higher than their anti-faces in distinctiveness, attractiveness, likability and trustworthiness. These findings suggest that familiarity strongly affects the distribution of facial representations in norm-based face space. Overall, our study suggests (1) that familiarity needs to be considered in studies of mental representations of faces, and (2) that familiarity, general distance-to-norm and more specific vector directions in face space make different and interactive contributions to different types of facial evaluations. PMID:27168323
The Role of Familiarity for Representations in Norm-Based Face Space.
Faerber, Stella J; Kaufmann, Jürgen M; Leder, Helmut; Martin, Eva Maria; Schweinberger, Stefan R
2016-01-01
According to the norm-based version of the multidimensional face space model (nMDFS, Valentine, 1991), any given face and its corresponding anti-face (which deviates from the norm in exactly opposite direction as the original face) should be equidistant to a hypothetical prototype face (norm), such that by definition face and anti-face should bear the same level of perceived typicality. However, it has been argued that familiarity affects perceived typicality and that representations of familiar faces are qualitatively different (e.g., more robust and image-independent) from those for unfamiliar faces. Here we investigated the role of face familiarity for rated typicality, using two frequently used operationalisations of typicality (deviation-based: DEV), and distinctiveness (face in the crowd: FITC) for faces of celebrities and their corresponding anti-faces. We further assessed attractiveness, likeability and trustworthiness ratings of the stimuli, which are potentially related to typicality. For unfamiliar faces and their corresponding anti-faces, in line with the predictions of the nMDFS, our results demonstrate comparable levels of perceived typicality (DEV). In contrast, familiar faces were perceived much less typical than their anti-faces. Furthermore, familiar faces were rated higher than their anti-faces in distinctiveness, attractiveness, likability and trustworthiness. These findings suggest that familiarity strongly affects the distribution of facial representations in norm-based face space. Overall, our study suggests (1) that familiarity needs to be considered in studies of mental representations of faces, and (2) that familiarity, general distance-to-norm and more specific vector directions in face space make different and interactive contributions to different types of facial evaluations.
Auditory peripersonal space in humans.
Farnè, Alessandro; Làdavas, Elisabetta
2002-10-01
In the present study we report neuropsychological evidence of the existence of an auditory peripersonal space representation around the head in humans and its characteristics. In a group of right brain-damaged patients with tactile extinction, we found that a sound delivered near the ipsilesional side of the head (20 cm) strongly extinguished a tactile stimulus delivered to the contralesional side of the head (cross-modal auditory-tactile extinction). By contrast, when an auditory stimulus was presented far from the head (70 cm), cross-modal extinction was dramatically reduced. This spatially specific cross-modal extinction was most consistently found (i.e., both in the front and back spaces) when a complex sound was presented, like a white noise burst. Pure tones produced spatially specific cross-modal extinction when presented in the back space, but not in the front space. In addition, the most severe cross-modal extinction emerged when sounds came from behind the head, thus showing that the back space is more sensitive than the front space to the sensory interaction of auditory-tactile inputs. Finally, when cross-modal effects were investigated by reversing the spatial arrangement of cross-modal stimuli (i.e., touch on the right and sound on the left), we found that an ipsilesional tactile stimulus, although inducing a small amount of cross-modal tactile-auditory extinction, did not produce any spatial-specific effect. Therefore, the selective aspects of cross-modal interaction found near the head cannot be explained by a competition between a damaged left spatial representation and an intact right spatial representation. Thus, consistent with neurophysiological evidence from monkeys, our findings strongly support the existence, in humans, of an integrated cross-modal system coding auditory and tactile stimuli near the body, that is, in the peripersonal space.
Crowley, Rebecca S.; Legowski, Elizabeth; Medvedeva, Olga; Tseytlin, Eugene; Roh, Ellen; Jukic, Drazen
2007-01-01
Objective Determine effects of computer-based tutoring on diagnostic performance gains, meta-cognition, and acceptance using two different problem representations. Describe impact of tutoring on spectrum of diagnostic skills required for task performance. Identify key features of student-tutor interaction contributing to learning gains. Design Prospective, between-subjects study, controlled for participant level of training. Resident physicians in two academic pathology programs spent four hours using one of two interfaces which differed mainly in external problem representation. The case-focused representation provided an open-learning environment in which students were free to explore evidence-hypothesis relationships within a case, but could not visualize the entire diagnostic space. The knowledge-focused representation provided an interactive representation of the entire diagnostic space, which more tightly constrained student actions. Measurements Metrics included results of pretest, post-test and retention-test for multiple choice and case diagnosis tests, ratios of performance to student reported certainty, results of participant survey, learning curves, and interaction behaviors during tutoring. Results Students had highly significant learning gains after one tutoring session. Learning was retained at one week. There were no differences between the two interfaces in learning gains on post-test or retention test. Only students in the knowledge-focused interface exhibited significant metacognitive gains from pretest to post-test and pretest to retention test. Students rated the knowledge-focused interface significantly higher than the case-focused interface. Conclusions Cognitive tutoring is associated with improved diagnostic performance in a complex medical domain. The effect is retained at one-week post-training. Knowledge-focused external problem representation shows an advantage over case-focused representation for metacognitive effects and user acceptance. PMID:17213494
Crowley, Rebecca S; Legowski, Elizabeth; Medvedeva, Olga; Tseytlin, Eugene; Roh, Ellen; Jukic, Drazen
2007-01-01
Determine effects of computer-based tutoring on diagnostic performance gains, meta-cognition, and acceptance using two different problem representations. Describe impact of tutoring on spectrum of diagnostic skills required for task performance. Identify key features of student-tutor interaction contributing to learning gains. Prospective, between-subjects study, controlled for participant level of training. Resident physicians in two academic pathology programs spent four hours using one of two interfaces which differed mainly in external problem representation. The case-focused representation provided an open-learning environment in which students were free to explore evidence-hypothesis relationships within a case, but could not visualize the entire diagnostic space. The knowledge-focused representation provided an interactive representation of the entire diagnostic space, which more tightly constrained student actions. Metrics included results of pretest, post-test and retention-test for multiple choice and case diagnosis tests, ratios of performance to student reported certainty, results of participant survey, learning curves, and interaction behaviors during tutoring. Students had highly significant learning gains after one tutoring session. Learning was retained at one week. There were no differences between the two interfaces in learning gains on post-test or retention test. Only students in the knowledge-focused interface exhibited significant metacognitive gains from pretest to post-test and pretest to retention test. Students rated the knowledge-focused interface significantly higher than the case-focused interface. Cognitive tutoring is associated with improved diagnostic performance in a complex medical domain. The effect is retained at one-week post-training. Knowledge-focused external problem representation shows an advantage over case-focused representation for metacognitive effects and user acceptance.
Spinor Geometry and Signal Transmission in Three-Space
NASA Astrophysics Data System (ADS)
Binz, Ernst; Pods, Sonja; Schempp, Walter
2002-09-01
For a singularity free gradient field in an open set of an oriented Euclidean space of dimension three we define a natural principal bundle out of an immanent complex line bundle. The elements of both bundles are called internal variables. Several other natural bundles are associated with the principal bundle and, in turn, determine the vector field. Two examples are given and it is shown that for a constant vector field circular polarized waves travelling along a field line can be considered as waves of internal variables. Einstein's equation epsilon = m [middle dot] c2 is derived from the geometry of the principal bundle. On SU(2) a relation between spin representations and Schrodinger representations is established. The link between the spin 1/2-model and the Schrodinger representations yields a connection between a microscopic and a macroscopic viewpoint.
NASA Astrophysics Data System (ADS)
Viswanath, Satish; Rosen, Mark; Madabhushi, Anant
2008-03-01
Current techniques for localization of prostatic adenocarcinoma (CaP) via blinded trans-rectal ultrasound biopsy are associated with a high false negative detection rate. While high resolution endorectal in vivo Magnetic Resonance (MR) prostate imaging has been shown to have improved contrast and resolution for CaP detection over ultrasound, similarity in intensity characteristics between benign and cancerous regions on MR images contribute to a high false positive detection rate. In this paper, we present a novel unsupervised segmentation method that employs manifold learning via consensus schemes for detection of cancerous regions from high resolution 1.5 Tesla (T) endorectal in vivo prostate MRI. A significant contribution of this paper is a method to combine multiple weak, lower-dimensional representations of high dimensional feature data in a way analogous to classifier ensemble schemes, and hence create a stable and accurate reduced dimensional representation. After correcting for MR image intensity artifacts, such as bias field inhomogeneity and intensity non-standardness, our algorithm extracts over 350 3D texture features at every spatial location in the MR scene at multiple scales and orientations. Non-linear dimensionality reduction schemes such as Locally Linear Embedding (LLE) and Graph Embedding (GE) are employed to create multiple low dimensional data representations of this high dimensional texture feature space. Our novel consensus embedding method is used to average object adjacencies from within the multiple low dimensional projections so that class relationships are preserved. Unsupervised consensus clustering is then used to partition the objects in this consensus embedding space into distinct classes. Quantitative evaluation on 18 1.5 T prostate MR data against corresponding histology obtained from the multi-site ACRIN trials show a sensitivity of 92.65% and a specificity of 82.06%, which suggests that our method is successfully able to detect suspicious regions in the prostate.
Software agents for the dissemination of remote terrestrial sensing data
NASA Technical Reports Server (NTRS)
Toomey, Christopher N.; Simoudis, Evangelos; Johnson, Raymond W.; Mark, William S.
1994-01-01
Remote terrestrial sensing (RTS) data is constantly being collected from a variety of space-based and earth-based sensors. The collected data, and especially 'value-added' analyses of the data, are finding growing application for commercial, government, and scientific purposes. The scale of this data collection and analysis is truly enormous; e.g., by 1995, the amount of data available in just one sector, NASA space science, will reach 5 petabytes. Moreover, the amount of data, and the value of analyzing the data, are expected to increase dramatically as new satellites and sensors become available (e.g., NASA's Earth Observing System satellites). Lockheed and other companies are beginning to provide data and analysis commercially. A critical issue for the exploitation of collected data is the dissemination of data and value-added analyses to a diverse and widely distributed customer base. Customers must be able to use their computational environment (eventually the National Information Infrastructure) to obtain timely and complete information, without having to know the details of where the relevant data resides and how it is accessed. Customers must be able to routinely use standard, widely available (and, therefore, low cost) analyses, while also being able to readily create on demand highly customized analyses to make crucial decisions. The diversity of user needs creates a difficult software problem: how can users easily state their needs, while the computational environment assumes the responsibility of finding (or creating) relevant information, and then delivering the results in a form that users understand? A software agent is a self-contained, active software module that contains an explicit representation of its operational knowledge. This explicit representation allows agents to examine their own capabilities in order to modify their goals to meet changing needs and to take advantage of dynamic opportunities. In addition, the explicit representation allows agents to advertize their capabilities and results to other agents, thereby allowing the collection of agents to reuse each others work.
NASA Astrophysics Data System (ADS)
Li, Hui; Sriver, Ryan L.
2018-01-01
High-resolution Atmosphere General Circulation Models (AGCMs) are capable of directly simulating realistic tropical cyclone (TC) statistics, providing a promising approach for TC-climate studies. Active air-sea coupling in a coupled model framework is essential to capturing TC-ocean interactions, which can influence TC-climate connections on interannual to decadal time scales. Here we investigate how the choices of ocean coupling can affect the directly simulated TCs using high-resolution configurations of the Community Earth System Model (CESM). We performed a suite of high-resolution, multidecadal, global-scale CESM simulations in which the atmosphere (˜0.25° grid spacing) is configured with three different levels of ocean coupling: prescribed climatological sea surface temperature (SST) (ATM), mixed layer ocean (SLAB), and dynamic ocean (CPL). We find that different levels of ocean coupling can influence simulated TC frequency, geographical distributions, and storm intensity. ATM simulates more storms and higher overall storm intensity than the coupled simulations. It also simulates higher TC track density over the eastern Pacific and the North Atlantic, while TC tracks are relatively sparse within CPL and SLAB for these regions. Storm intensification and the maximum wind speed are sensitive to the representations of local surface flux feedbacks in different coupling configurations. Key differences in storm number and distribution can be attributed to variations in the modeled large-scale climate mean state and variability that arise from the combined effect of intrinsic model biases and air-sea interactions. Results help to improve our understanding about the representation of TCs in high-resolution coupled Earth system models, with important implications for TC-climate applications.
Ramsden, Helen L; Sürmeli, Gülşen; McDonagh, Steven G; Nolan, Matthew F
2015-01-01
Neural circuits in the medial entorhinal cortex (MEC) encode an animal's position and orientation in space. Within the MEC spatial representations, including grid and directional firing fields, have a laminar and dorsoventral organization that corresponds to a similar topography of neuronal connectivity and cellular properties. Yet, in part due to the challenges of integrating anatomical data at the resolution of cortical layers and borders, we know little about the molecular components underlying this organization. To address this we develop a new computational pipeline for high-throughput analysis and comparison of in situ hybridization (ISH) images at laminar resolution. We apply this pipeline to ISH data for over 16,000 genes in the Allen Brain Atlas and validate our analysis with RNA sequencing of MEC tissue from adult mice. We find that differential gene expression delineates the borders of the MEC with neighboring brain structures and reveals its laminar and dorsoventral organization. We propose a new molecular basis for distinguishing the deep layers of the MEC and show that their similarity to corresponding layers of neocortex is greater than that of superficial layers. Our analysis identifies ion channel-, cell adhesion- and synapse-related genes as candidates for functional differentiation of MEC layers and for encoding of spatial information at different scales along the dorsoventral axis of the MEC. We also reveal laminar organization of genes related to disease pathology and suggest that a high metabolic demand predisposes layer II to neurodegenerative pathology. In principle, our computational pipeline can be applied to high-throughput analysis of many forms of neuroanatomical data. Our results support the hypothesis that differences in gene expression contribute to functional specialization of superficial layers of the MEC and dorsoventral organization of the scale of spatial representations.
Multi-scale Gaussian representation and outline-learning based cell image segmentation.
Farhan, Muhammad; Ruusuvuori, Pekka; Emmenlauer, Mario; Rämö, Pauli; Dehio, Christoph; Yli-Harja, Olli
2013-01-01
High-throughput genome-wide screening to study gene-specific functions, e.g. for drug discovery, demands fast automated image analysis methods to assist in unraveling the full potential of such studies. Image segmentation is typically at the forefront of such analysis as the performance of the subsequent steps, for example, cell classification, cell tracking etc., often relies on the results of segmentation. We present a cell cytoplasm segmentation framework which first separates cell cytoplasm from image background using novel approach of image enhancement and coefficient of variation of multi-scale Gaussian scale-space representation. A novel outline-learning based classification method is developed using regularized logistic regression with embedded feature selection which classifies image pixels as outline/non-outline to give cytoplasm outlines. Refinement of the detected outlines to separate cells from each other is performed in a post-processing step where the nuclei segmentation is used as contextual information. We evaluate the proposed segmentation methodology using two challenging test cases, presenting images with completely different characteristics, with cells of varying size, shape, texture and degrees of overlap. The feature selection and classification framework for outline detection produces very simple sparse models which use only a small subset of the large, generic feature set, that is, only 7 and 5 features for the two cases. Quantitative comparison of the results for the two test cases against state-of-the-art methods show that our methodology outperforms them with an increase of 4-9% in segmentation accuracy with maximum accuracy of 93%. Finally, the results obtained for diverse datasets demonstrate that our framework not only produces accurate segmentation but also generalizes well to different segmentation tasks.
Multi-scale Gaussian representation and outline-learning based cell image segmentation
2013-01-01
Background High-throughput genome-wide screening to study gene-specific functions, e.g. for drug discovery, demands fast automated image analysis methods to assist in unraveling the full potential of such studies. Image segmentation is typically at the forefront of such analysis as the performance of the subsequent steps, for example, cell classification, cell tracking etc., often relies on the results of segmentation. Methods We present a cell cytoplasm segmentation framework which first separates cell cytoplasm from image background using novel approach of image enhancement and coefficient of variation of multi-scale Gaussian scale-space representation. A novel outline-learning based classification method is developed using regularized logistic regression with embedded feature selection which classifies image pixels as outline/non-outline to give cytoplasm outlines. Refinement of the detected outlines to separate cells from each other is performed in a post-processing step where the nuclei segmentation is used as contextual information. Results and conclusions We evaluate the proposed segmentation methodology using two challenging test cases, presenting images with completely different characteristics, with cells of varying size, shape, texture and degrees of overlap. The feature selection and classification framework for outline detection produces very simple sparse models which use only a small subset of the large, generic feature set, that is, only 7 and 5 features for the two cases. Quantitative comparison of the results for the two test cases against state-of-the-art methods show that our methodology outperforms them with an increase of 4-9% in segmentation accuracy with maximum accuracy of 93%. Finally, the results obtained for diverse datasets demonstrate that our framework not only produces accurate segmentation but also generalizes well to different segmentation tasks. PMID:24267488
Ramsden, Helen L.; Sürmeli, Gülşen; McDonagh, Steven G.; Nolan, Matthew F.
2015-01-01
Neural circuits in the medial entorhinal cortex (MEC) encode an animal’s position and orientation in space. Within the MEC spatial representations, including grid and directional firing fields, have a laminar and dorsoventral organization that corresponds to a similar topography of neuronal connectivity and cellular properties. Yet, in part due to the challenges of integrating anatomical data at the resolution of cortical layers and borders, we know little about the molecular components underlying this organization. To address this we develop a new computational pipeline for high-throughput analysis and comparison of in situ hybridization (ISH) images at laminar resolution. We apply this pipeline to ISH data for over 16,000 genes in the Allen Brain Atlas and validate our analysis with RNA sequencing of MEC tissue from adult mice. We find that differential gene expression delineates the borders of the MEC with neighboring brain structures and reveals its laminar and dorsoventral organization. We propose a new molecular basis for distinguishing the deep layers of the MEC and show that their similarity to corresponding layers of neocortex is greater than that of superficial layers. Our analysis identifies ion channel-, cell adhesion- and synapse-related genes as candidates for functional differentiation of MEC layers and for encoding of spatial information at different scales along the dorsoventral axis of the MEC. We also reveal laminar organization of genes related to disease pathology and suggest that a high metabolic demand predisposes layer II to neurodegenerative pathology. In principle, our computational pipeline can be applied to high-throughput analysis of many forms of neuroanatomical data. Our results support the hypothesis that differences in gene expression contribute to functional specialization of superficial layers of the MEC and dorsoventral organization of the scale of spatial representations. PMID:25615592
NASA Technical Reports Server (NTRS)
Jaap, John; Meyer, Patrick; Davis, Elizabeth
1997-01-01
The experiments planned for the International Space Station promise to be complex, lengthy and diverse. The scarcity of the space station resources will cause significant competition for resources between experiments. The scheduling job facing the Space Station mission planning software requires a concise and comprehensive description of the experiments' requirements (to ensure a valid schedule) and a good description of the experiments' flexibility (to effectively utilize available resources). In addition, the continuous operation of the station, the wide geographic dispersion of station users, and the budgetary pressure to reduce operations manpower make a low-cost solution mandatory. A graphical representation of the scheduling requirements for station payloads implemented via an Internet-based application promises to be an elegant solution that addresses all of these issues. The graphical representation of experiment requirements permits a station user to describe his experiment by defining "activities" and "sequences of activities". Activities define the resource requirements (with alternatives) and other quantitative constraints of tasks to be performed. Activities definitions use an "outline" graphics paradigm. Sequences define the time relationships between activities. Sequences may also define time relationships with activities of other payloads or space station systems. Sequences of activities are described by a "network" graphics paradigm. The bulk of this paper will describe the graphical approach to representing requirements and provide examples that show the ease and clarity with which complex requirements can be represented. A Java applet, to run in a web browser, is being developed to support the graphical representation of payload scheduling requirements. Implementing the entry and editing of requirements via the web solves the problems introduced by the geographic dispersion of users. Reducing manpower is accomplished by developing a concise representation which eliminates the misunderstanding possible with verbose representations and which captures the complete requirements and flexibility of the experiments.
A Sequential Ensemble Prediction System at Convection Permitting Scales
NASA Astrophysics Data System (ADS)
Milan, M.; Simmer, C.
2012-04-01
A Sequential Assimilation Method (SAM) following some aspects of particle filtering with resampling, also called SIR (Sequential Importance Resampling), is introduced and applied in the framework of an Ensemble Prediction System (EPS) for weather forecasting on convection permitting scales, with focus to precipitation forecast. At this scale and beyond, the atmosphere increasingly exhibits chaotic behaviour and non linear state space evolution due to convectively driven processes. One way to take full account of non linear state developments are particle filter methods, their basic idea is the representation of the model probability density function by a number of ensemble members weighted by their likelihood with the observations. In particular particle filter with resampling abandons ensemble members (particles) with low weights restoring the original number of particles adding multiple copies of the members with high weights. In our SIR-like implementation we substitute the likelihood way to define weights and introduce a metric which quantifies the "distance" between the observed atmospheric state and the states simulated by the ensemble members. We also introduce a methodology to counteract filter degeneracy, i.e. the collapse of the simulated state space. To this goal we propose a combination of resampling taking account of simulated state space clustering and nudging. By keeping cluster representatives during resampling and filtering, the method maintains the potential for non linear system state development. We assume that a particle cluster with initially low likelihood may evolve in a state space with higher likelihood in a subsequent filter time thus mimicking non linear system state developments (e.g. sudden convection initiation) and remedies timing errors for convection due to model errors and/or imperfect initial condition. We apply a simplified version of the resampling, the particles with highest weights in each cluster are duplicated; for the model evolution for each particle pair one particle evolves using the forward model; the second particle, however, is nudged to the radar and satellite observation during its evolution based on the forward model.
Schematic representations of local environmental space guide goal-directed navigation
Marchette, Steven A.; Ryan, Jack; Epstein, Russell A.
2016-01-01
To successfully navigate to a target, it is useful to be able to define its location at multiple levels of specificity. For example, the location of a favorite coffee mug can be described in terms of which room it is in, or in terms of where it is within the room. An appealing hypothesis is that these levels of description are retrieved from memory by accessing the same representation at progressively finer levels of granularity—first remembering the general location of an object and then “zooming in.” Here we provide evidence for an alternative view, in which navigational behavior is guided by independent representations at multiple spatial scales. Subjects learned the locations of objects that were positioned within four visually distinct but geometrically similar buildings, which were in turn positioned within a broader virtual park. They were then tested on their knowledge of object location by asking them to navigate to the remembered location of each object. We examined errors during the test phase for confusions among geometrically analogous locations in different buildings—that is, navigating to the right location in the wrong building. We observed that subjects frequently made these confusions, which are analogous to remembering a passage’s location on the page of a book but not remembering the page that the passage is on. This suggests that subjects were recalling the object’s local location without recalling its global location. Further manipulations across seven experiments indicated that geometric confusions were observed even between buildings that were not metrically identical as long as geometrical equivalence could be defined. However, removing the walls so that the larger environment was no longer divided into subspaces abolished these errors. Taken together, our results suggest that human spatial memory contains two separable representations of “where” an object can be found: (i) a schematic map of where an object lies with respect to local landmarks and boundaries; (ii) a representation of the identity and location of each local environment. PMID:27814459
Flint, Robert D; Scheid, Michael R; Wright, Zachary A; Solla, Sara A; Slutzky, Marc W
2016-03-23
The human motor system is capable of remarkably precise control of movements--consider the skill of professional baseball pitchers or surgeons. This precise control relies upon stable representations of movements in the brain. Here, we investigated the stability of cortical activity at multiple spatial and temporal scales by recording local field potentials (LFPs) and action potentials (multiunit spikes, MSPs) while two monkeys controlled a cursor either with their hand or directly from the brain using a brain-machine interface. LFPs and some MSPs were remarkably stable over time periods ranging from 3 d to over 3 years; overall, LFPs were significantly more stable than spikes. We then assessed whether the stability of all neural activity, or just a subset of activity, was necessary to achieve stable behavior. We showed that projections of neural activity into the subspace relevant to the task (the "task-relevant space") were significantly more stable than were projections into the task-irrelevant (or "task-null") space. This provides cortical evidence in support of the minimum intervention principle, which proposes that optimal feedback control (OFC) allows the brain to tightly control only activity in the task-relevant space while allowing activity in the task-irrelevant space to vary substantially from trial to trial. We found that the brain appears capable of maintaining stable movement representations for extremely long periods of time, particularly so for neural activity in the task-relevant space, which agrees with OFC predictions. It is unknown whether cortical signals are stable for more than a few weeks. Here, we demonstrate that motor cortical signals can exhibit high stability over several years. This result is particularly important to brain-machine interfaces because it could enable stable performance with infrequent recalibration. Although we can maintain movement accuracy over time, movement components that are unrelated to the goals of a task (such as elbow position during reaching) often vary from trial to trial. This is consistent with the minimum intervention principle of optimal feedback control. We provide evidence that the motor cortex acts according to this principle: cortical activity is more stable in the task-relevant space and more variable in the task-irrelevant space. Copyright © 2016 the authors 0270-6474/16/363623-10$15.00/0.
Self-consistent pseudopotential calculation of the bulk properties of Mo and W
DOE Office of Scientific and Technical Information (OSTI.GOV)
Zunger, A.; Cohen, M.L.
The bulk properties of Mo and W are calculated using the recently developed momentum-space approach for calculating total energy via a nonlocal pseudopotential. This approach avoids any shape approximation to the variational charge density (e.g., muffin tins), is fully self-consistent, and replaces the multidimensional and multicenter integrals akin to real-space representations by simple and readily convergent reciprocal-space lattice sums. We use first-principles atomic pseudopotentials which have been previously demonstrated to yield band structures and charge densities for both semiconductors and transition metals in good agreement with experiment and all-electron calculations. Using a mixed-basis representation for the crystalline wave function, wemore » are able to accurately reproduce both the localized and itinerant features of the electronic states in these systems. These first-principles pseudopotentials, together with the self-consistent density-functional representation for both the exchange and the correlation screening, yields agreement with experiment of 0.2% in the lattice parameters, 2% and 11% for the binding energies of Mo and W, respectively, and 12% and 7% for the bulk moduli of Mo and W, respectively.« less
Operator product expansion for conformal defects
NASA Astrophysics Data System (ADS)
Fukuda, Masayuki; Kobayashi, Nozomu; Nishioka, Tatsuma
2018-01-01
We study the operator product expansion (OPE) for scalar conformal defects of any codimension in CFT. The OPE for defects is decomposed into "defect OPE blocks", the irreducible representations of the conformal group, each of which packages the contribution from a primary operator and its descendants. We use the shadow formalism to deduce an integral representation of the defect OPE blocks. They are shown to obey a set of constraint equations that can be regarded as equations of motion for a scalar field propagating on the moduli space of the defects. By employing the Radon transform between the AdS space and the moduli space, we obtain a formula of constructing an AdS scalar field from the defect OPE block for a conformal defect of any codimension in a scalar representation of the conformal group, which turns out to be the Euclidean version of the HKLL formula. We also introduce a duality between conformal defects of different codimensions and prove the equivalence between the defect OPE block for codimension-two defects and the OPE block for a pair of local operators.
Social representations, individual and collective mind: a study of Wundt, Cattaneo and Moscovici.
Tateo, Luca; Iannaccone, Antonio
2012-03-01
The paper presents a discussion on the role of Social Representations in the articulation between individual and collective dimensions of mental activity. An analysis of some concepts in the works of Wundt and Cattaneo is the starting point for a discussion of the relationship between individual processes, practices, artifacts, symbolic systems and functions of Social Representations in the development of culture and individuals. In this perspective, Social Representations could be considered a space of negotiation of the meaning. The relationship between Social Representations, symbolic systems, practices and sense making involves the elaboration of the tension between continuity and innovation, which is developed through communication and practice along time in the interaction between individual and collective minds.
Multiscale 3-D shape representation and segmentation using spherical wavelets.
Nain, Delphine; Haker, Steven; Bobick, Aaron; Tannenbaum, Allen
2007-04-01
This paper presents a novel multiscale shape representation and segmentation algorithm based on the spherical wavelet transform. This work is motivated by the need to compactly and accurately encode variations at multiple scales in the shape representation in order to drive the segmentation and shape analysis of deep brain structures, such as the caudate nucleus or the hippocampus. Our proposed shape representation can be optimized to compactly encode shape variations in a population at the needed scale and spatial locations, enabling the construction of more descriptive, nonglobal, nonuniform shape probability priors to be included in the segmentation and shape analysis framework. In particular, this representation addresses the shortcomings of techniques that learn a global shape prior at a single scale of analysis and cannot represent fine, local variations in a population of shapes in the presence of a limited dataset. Specifically, our technique defines a multiscale parametric model of surfaces belonging to the same population using a compact set of spherical wavelets targeted to that population. We further refine the shape representation by separating into groups wavelet coefficients that describe independent global and/or local biological variations in the population, using spectral graph partitioning. We then learn a prior probability distribution induced over each group to explicitly encode these variations at different scales and spatial locations. Based on this representation, we derive a parametric active surface evolution using the multiscale prior coefficients as parameters for our optimization procedure to naturally include the prior for segmentation. Additionally, the optimization method can be applied in a coarse-to-fine manner. We apply our algorithm to two different brain structures, the caudate nucleus and the hippocampus, of interest in the study of schizophrenia. We show: 1) a reconstruction task of a test set to validate the expressiveness of our multiscale prior and 2) a segmentation task. In the reconstruction task, our results show that for a given training set size, our algorithm significantly improves the approximation of shapes in a testing set over the Point Distribution Model, which tends to oversmooth data. In the segmentation task, our validation shows our algorithm is computationally efficient and outperforms the Active Shape Model algorithm, by capturing finer shape details.
Multiscale 3-D Shape Representation and Segmentation Using Spherical Wavelets
Nain, Delphine; Haker, Steven; Bobick, Aaron
2013-01-01
This paper presents a novel multiscale shape representation and segmentation algorithm based on the spherical wavelet transform. This work is motivated by the need to compactly and accurately encode variations at multiple scales in the shape representation in order to drive the segmentation and shape analysis of deep brain structures, such as the caudate nucleus or the hippocampus. Our proposed shape representation can be optimized to compactly encode shape variations in a population at the needed scale and spatial locations, enabling the construction of more descriptive, nonglobal, nonuniform shape probability priors to be included in the segmentation and shape analysis framework. In particular, this representation addresses the shortcomings of techniques that learn a global shape prior at a single scale of analysis and cannot represent fine, local variations in a population of shapes in the presence of a limited dataset. Specifically, our technique defines a multiscale parametric model of surfaces belonging to the same population using a compact set of spherical wavelets targeted to that population. We further refine the shape representation by separating into groups wavelet coefficients that describe independent global and/or local biological variations in the population, using spectral graph partitioning. We then learn a prior probability distribution induced over each group to explicitly encode these variations at different scales and spatial locations. Based on this representation, we derive a parametric active surface evolution using the multiscale prior coefficients as parameters for our optimization procedure to naturally include the prior for segmentation. Additionally, the optimization method can be applied in a coarse-to-fine manner. We apply our algorithm to two different brain structures, the caudate nucleus and the hippocampus, of interest in the study of schizophrenia. We show: 1) a reconstruction task of a test set to validate the expressiveness of our multiscale prior and 2) a segmentation task. In the reconstruction task, our results show that for a given training set size, our algorithm significantly improves the approximation of shapes in a testing set over the Point Distribution Model, which tends to oversmooth data. In the segmentation task, our validation shows our algorithm is computationally efficient and outperforms the Active Shape Model algorithm, by capturing finer shape details. PMID:17427745
Space-time modeling using environmental constraints in a mobile robot system
NASA Technical Reports Server (NTRS)
Slack, Marc G.
1990-01-01
Grid-based models of a robot's local environment have been used by many researchers building mobile robot control systems. The attraction of grid-based models is their clear parallel between the internal model and the external world. However, the discrete nature of such representations does not match well with the continuous nature of actions and usually serves to limit the abilities of the robot. This work describes a spatial modeling system that extracts information from a grid-based representation to form a symbolic representation of the robot's local environment. The approach makes a separation between the representation provided by the sensing system and the representation used by the action system. Separation allows asynchronous operation between sensing and action in a mobile robot, as well as the generation of a more continuous representation upon which to base actions.
Sawamura, Jitsuki; Morishita, Shigeru; Ishigooka, Jun
2016-02-09
Previously, we applied basic group theory and related concepts to scales of measurement of clinical disease states and clinical findings (including laboratory data). To gain a more concrete comprehension, we here apply the concept of matrix representation, which was not explicitly exploited in our previous work. Starting with a set of orthonormal vectors, called the basis, an operator Rj (an N-tuple patient disease state at the j-th session) was expressed as a set of stratified vectors representing plural operations on individual components, so as to satisfy the group matrix representation. The stratified vectors containing individual unit operations were combined into one-dimensional square matrices [Rj]s. The [Rj]s meet the matrix representation of a group (ring) as a K-algebra. Using the same-sized matrix of stratified vectors, we can also express changes in the plural set of [Rj]s. The method is demonstrated on simple examples. Despite the incompleteness of our model, the group matrix representation of stratified vectors offers a formal mathematical approach to clinical medicine, aligning it with other branches of natural science.
Spaces of Possibility in Pre-Service Teacher Education
ERIC Educational Resources Information Center
Ryan, Mary
2011-01-01
Pre-service teacher education is a spatialised enterprise. It operates across a number of spaces that may or may not be linked ideologically and/or physically. These spaces can include daily practices, locations, infrastructure, relationships and representations of power and ideology. The interrelationships between and within these (sometimes…
Decomposition of the polynomial kernel of arbitrary higher spin Dirac operators
DOE Office of Scientific and Technical Information (OSTI.GOV)
Eelbode, D., E-mail: David.Eelbode@ua.ac.be; Raeymaekers, T., E-mail: Tim.Raeymaekers@UGent.be; Van der Jeugt, J., E-mail: Joris.VanderJeugt@UGent.be
2015-10-15
In a series of recent papers, we have introduced higher spin Dirac operators, which are generalisations of the classical Dirac operator. Whereas the latter acts on spinor-valued functions, the former acts on functions taking values in arbitrary irreducible half-integer highest weight representations for the spin group. In this paper, we describe how the polynomial kernel spaces of such operators decompose in irreducible representations of the spin group. We will hereby make use of results from representation theory.
REPRESENTATIONS OF WEAK AND STRONG INTEGRALS IN BANACH SPACES
Brooks, James K.
1969-01-01
We establish a representation of the Gelfand-Pettis (weak) integral in terms of unconditionally convergent series. Moreover, absolute convergence of the series is a necessary and sufficient condition in order that the weak integral coincide with the Bochner integral. Two applications of the representation are given. The first is a simplified proof of the countable additivity and absolute continuity of the indefinite weak integral. The second application is to probability theory; we characterize the conditional expectation of a weakly integrable function. PMID:16591755
Building blocks of topological quantum chemistry: Elementary band representations
NASA Astrophysics Data System (ADS)
Cano, Jennifer; Bradlyn, Barry; Wang, Zhijun; Elcoro, L.; Vergniory, M. G.; Felser, C.; Aroyo, M. I.; Bernevig, B. Andrei
2018-01-01
The link between chemical orbitals described by local degrees of freedom and band theory, which is defined in momentum space, was proposed by Zak several decades ago for spinless systems with and without time reversal in his theory of "elementary" band representations. In a recent paper [Bradlyn et al., Nature (London) 547, 298 (2017), 10.1038/nature23268] we introduced the generalization of this theory to the experimentally relevant situation of spin-orbit coupled systems with time-reversal symmetry and proved that all bands that do not transform as band representations are topological. Here we give the full details of this construction. We prove that elementary band representations are either connected as bands in the Brillouin zone and are described by localized Wannier orbitals respecting the symmetries of the lattice (including time reversal when applicable), or, if disconnected, describe topological insulators. We then show how to generate a band representation from a particular Wyckoff position and determine which Wyckoff positions generate elementary band representations for all space groups. This theory applies to spinful and spinless systems, in all dimensions, with and without time reversal. We introduce a homotopic notion of equivalence and show that it results in a finer classification of topological phases than approaches based only on the symmetry of wave functions at special points in the Brillouin zone. Utilizing a mapping of the band connectivity into a graph theory problem, we show in companion papers which Wyckoff positions can generate disconnected elementary band representations, furnishing a natural avenue for a systematic materials search.
New Insights into the Fractional Order Diffusion Equation Using Entropy and Kurtosis.
Ingo, Carson; Magin, Richard L; Parrish, Todd B
2014-11-01
Fractional order derivative operators offer a concise description to model multi-scale, heterogeneous and non-local systems. Specifically, in magnetic resonance imaging, there has been recent work to apply fractional order derivatives to model the non-Gaussian diffusion signal, which is ubiquitous in the movement of water protons within biological tissue. To provide a new perspective for establishing the utility of fractional order models, we apply entropy for the case of anomalous diffusion governed by a fractional order diffusion equation generalized in space and in time. This fractional order representation, in the form of the Mittag-Leffler function, gives an entropy minimum for the integer case of Gaussian diffusion and greater values of spectral entropy for non-integer values of the space and time derivatives. Furthermore, we consider kurtosis, defined as the normalized fourth moment, as another probabilistic description of the fractional time derivative. Finally, we demonstrate the implementation of anomalous diffusion, entropy and kurtosis measurements in diffusion weighted magnetic resonance imaging in the brain of a chronic ischemic stroke patient.
NASA Technical Reports Server (NTRS)
Mennell, R.; Hughes, T.
1974-01-01
Experimental aerodynamic investigations were conducted on a sting-mounted 0.0405 scale representation of the 140A/B space shuttle orbiter in a 7.75 ft by 11 ft low speed wind tunnel during the period from November 14, 1973 to December 6, 1973. Establishment of basic longitudinal stability characteristics in and out of ground effect, and the establishment of lateral-directional stability characteristics in free air were the primary test objectives. The following effects and configurations were tested: (1) two dual podded nacelle configurations; (2) stability and control characteristics at nominal elevon deflections, rudder deflections, airleron deflections, rudder flare angles, and body flap deflections; (3) effects of various elevon and elevon/fuselage gaps on longitudinal stability and control; (4) pressures on the vertical tail at spanwise stations using pressure bugs; (5) aerodynamic force and moment data measured in the stability axis system by an internally mounted, six-component strain gage balance. For Vol. 1, see N74-32324.
Mapping historical landscape changes with the use of a space-time cube
NASA Astrophysics Data System (ADS)
Bogucka, Edyta P.; Jahnke, Mathias
2018-05-01
In this contribution, we introduce geographic concepts in the humanities and present the results of a spacetime visualization of ancient buildings over the last centuries. The techniques and approaches used were based on cartographic research to visualize spatio-temporal information. As a case study, we applied cartographic styling techniques to a model of the Royal Castle in Warsaw and its different spatial elements, which were constructed and destroyed during their eventful history. In our case, the space-time cube approach seems to be the most suitable representation of this spatio-temporal information. Therefore, we digitized the different footprints of the castle during the ancient centuries as well as the landscape structure around, and annotated them with monarchies, epochs and time. During the digitization process, we had to cope with difficulties like sources in various scales and map projections, which resulted in varying accuracies. The results were stored in KML to support a wide variety of visualization platforms.
Magnetic space-based field measurements
NASA Technical Reports Server (NTRS)
Langel, R. A.
1981-01-01
Because the near Earth magnetic field is a complex combination of fields from outside the Earth of fields from its core and of fields from its crust, measurements from space prove to be the only practical way to obtain timely, global surveys. Due to difficulty in making accurate vector measurements, early satellites such as Sputnik and Vanguard measured only the magnitude survey. The attitude accuracy was 20 arc sec. Both the Earth's core fields and the fields arising from its crust were mapped from satellite data. The standard model of the core consists of a scalar potential represented by a spherical harmonics series. Models of the crustal field are relatively new. Mathematical representation is achieved in localized areas by arrays of dipoles appropriately located in the Earth's crust. Measurements of the Earth's field are used in navigation, to map charged particles in the magnetosphere, to study fluid properties in the Earth's core, to infer conductivity of the upper mantels, and to delineate regional scale geological features.
Structural kinetic modeling of metabolic networks.
Steuer, Ralf; Gross, Thilo; Selbig, Joachim; Blasius, Bernd
2006-08-08
To develop and investigate detailed mathematical models of metabolic processes is one of the primary challenges in systems biology. However, despite considerable advance in the topological analysis of metabolic networks, kinetic modeling is still often severely hampered by inadequate knowledge of the enzyme-kinetic rate laws and their associated parameter values. Here we propose a method that aims to give a quantitative account of the dynamical capabilities of a metabolic system, without requiring any explicit information about the functional form of the rate equations. Our approach is based on constructing a local linear model at each point in parameter space, such that each element of the model is either directly experimentally accessible or amenable to a straightforward biochemical interpretation. This ensemble of local linear models, encompassing all possible explicit kinetic models, then allows for a statistical exploration of the comprehensive parameter space. The method is exemplified on two paradigmatic metabolic systems: the glycolytic pathway of yeast and a realistic-scale representation of the photosynthetic Calvin cycle.
Pore-level numerical analysis of the infrared surface temperature of metallic foam
NASA Astrophysics Data System (ADS)
Li, Yang; Xia, Xin-Lin; Sun, Chuang; Tan, He-Ping; Wang, Jing
2017-10-01
Open-cell metallic foams are increasingly used in various thermal systems. The temperature distributions are significant for the comprehensive understanding of these foam-based engineering applications. This study aims to numerically investigate the modeling of the infrared surface temperature (IRST) of open-cell metallic foam measured by an infrared camera placed above the sample. Two typical approaches based on Backward Monte Carlo simulation are developed to estimate the IRSTs: the first one, discrete-scale approach (DSA), uses a realistic discrete representation of the foam structure obtained from a computed tomography reconstruction while the second one, continuous-scale approach (CSA), assumes that the foam sample behaves like a continuous homogeneous semi-transparent medium. The radiative properties employed in CSA are directly determined by a ray-tracing process inside the discrete foam representation. The IRSTs for different material properties (material emissivity, specularity parameter) are computed by the two approaches. The results show that local IRSTs can vary according to the local compositions of the foam surface (void and solid). The temperature difference between void and solid areas is gradually attenuated with increasing material emissivity. In addition, the annular void space near to the foam surface behaves like a black cavity for thermal radiation, which is ensued by copious neighboring skeletons. For most of the cases studied, the mean IRSTs computed by the DSA and CSA are close to each other, except when the material emissivity is highly weakened and the sample temperature is extremely high.
A coarse-to-fine approach for medical hyperspectral image classification with sparse representation
NASA Astrophysics Data System (ADS)
Chang, Lan; Zhang, Mengmeng; Li, Wei
2017-10-01
A coarse-to-fine approach with sparse representation is proposed for medical hyperspectral image classification in this work. Segmentation technique with different scales is employed to exploit edges of the input image, where coarse super-pixel patches provide global classification information while fine ones further provide detail information. Different from common RGB image, hyperspectral image has multi bands to adjust the cluster center with more high precision. After segmentation, each super pixel is classified by recently-developed sparse representation-based classification (SRC), which assigns label for testing samples in one local patch by means of sparse linear combination of all the training samples. Furthermore, segmentation with multiple scales is employed because single scale is not suitable for complicate distribution of medical hyperspectral imagery. Finally, classification results for different sizes of super pixel are fused by some fusion strategy, offering at least two benefits: (1) the final result is obviously superior to that of segmentation with single scale, and (2) the fusion process significantly simplifies the choice of scales. Experimental results using real medical hyperspectral images demonstrate that the proposed method outperforms the state-of-the-art SRC.
Pinsard, Basile; Boutin, Arnaud; Doyon, Julien; Benali, Habib
2018-01-01
Functional MRI acquisition is sensitive to subjects' motion that cannot be fully constrained. Therefore, signal corrections have to be applied a posteriori in order to mitigate the complex interactions between changing tissue localization and magnetic fields, gradients and readouts. To circumvent current preprocessing strategies limitations, we developed an integrated method that correct motion and spatial low-frequency intensity fluctuations at the level of each slice in order to better fit the acquisition processes. The registration of single or multiple simultaneously acquired slices is achieved online by an Iterated Extended Kalman Filter, favoring the robust estimation of continuous motion, while an intensity bias field is non-parametrically fitted. The proposed extraction of gray-matter BOLD activity from the acquisition space to an anatomical group template space, taking into account distortions, better preserves fine-scale patterns of activity. Importantly, the proposed unified framework generalizes to high-resolution multi-slice techniques. When tested on simulated and real data the latter shows a reduction of motion explained variance and signal variability when compared to the conventional preprocessing approach. These improvements provide more stable patterns of activity, facilitating investigation of cerebral information representation in healthy and/or clinical populations where motion is known to impact fine-scale data. PMID:29755312
Pinsard, Basile; Boutin, Arnaud; Doyon, Julien; Benali, Habib
2018-01-01
Functional MRI acquisition is sensitive to subjects' motion that cannot be fully constrained. Therefore, signal corrections have to be applied a posteriori in order to mitigate the complex interactions between changing tissue localization and magnetic fields, gradients and readouts. To circumvent current preprocessing strategies limitations, we developed an integrated method that correct motion and spatial low-frequency intensity fluctuations at the level of each slice in order to better fit the acquisition processes. The registration of single or multiple simultaneously acquired slices is achieved online by an Iterated Extended Kalman Filter, favoring the robust estimation of continuous motion, while an intensity bias field is non-parametrically fitted. The proposed extraction of gray-matter BOLD activity from the acquisition space to an anatomical group template space, taking into account distortions, better preserves fine-scale patterns of activity. Importantly, the proposed unified framework generalizes to high-resolution multi-slice techniques. When tested on simulated and real data the latter shows a reduction of motion explained variance and signal variability when compared to the conventional preprocessing approach. These improvements provide more stable patterns of activity, facilitating investigation of cerebral information representation in healthy and/or clinical populations where motion is known to impact fine-scale data.
NASA Astrophysics Data System (ADS)
Mould, Jeremy R.; Huchra, John P.; Freedman, Wendy L.; Kennicutt, Robert C., Jr.; Ferrarese, Laura; Ford, Holland C.; Gibson, Brad K.; Graham, John A.; Hughes, Shaun M. G.; Illingworth, Garth D.; Kelson, Daniel D.; Macri, Lucas M.; Madore, Barry F.; Sakai, Shoko; Sebo, Kim M.; Silbermann, Nancy A.; Stetson, Peter B.
2000-12-01
In the article ``The Hubble Space Telescope Key Project on the Extragalactic Distance Scale. XXVIII. Combining the Constraints on the Hubble Constant'' (ApJ, 529, 786 [2000]), by Jeremy R. Mould, John P. Huchra, Wendy L. Freedman, Robert C. Kennicutt, Jr., Laura Ferrarese, Holland C. Ford, Brad K. Gibson, John A. Graham, Shaun M. G. Hughes, Garth D. Illingworth, Daniel D. Kelson, Lucas M. Macri, Barry F. Madore, Shoko Sakai, Kim M. Sebo, Nancy A. Silbermann, and Peter B. Stetson, some sign errors need to be corrected. 1. In equation (A2) the minus signs should be plus signs. The correct version is Vcosmic=VH+Vc,LG+Vin,Virgo+Vin,GA+Vin,Shap+... 2. In Table A1 the declination of the Great Attractor (GA) is -44°, and that of the Shapley supercluster is -31°, i.e., south declination, not north, as implied in the table. The first error is the authors' and the second occurred in the publication process. In both cases the computer code was correct, and the errors are in the published representation. None of the results presented in the paper are therefore affected in any way. The authors thank Dr. Jim Condon for pointing out the error in equation (A2)
Strongly interacting dynamics beyond the standard model on a space-time lattice.
Lucini, Biagio
2010-08-13
Strong theoretical arguments suggest that the Higgs sector of the standard model of electroweak interactions is an effective low-energy theory, with a more fundamental theory expected to emerge at an energy scale of the order of a teraelectronvolt. One possibility is that the more fundamental theory is strongly interacting and the Higgs sector is given by the low-energy dynamics of the underlying theory. I review recent works aimed at determining observable quantities by numerical simulations of strongly interacting theories proposed in the literature to explain the electroweak symmetry-breaking mechanism. These investigations are based on Monte Carlo simulations of the theory formulated on a space-time lattice. I focus on the so-called minimal walking technicolour scenario, an SU(2) gauge theory with two flavours of fermions in the adjoint representation. The emerging picture is that this theory has an infrared fixed point that dominates the large-distance physics. I shall discuss the first numerical determinations of quantities of phenomenological interest for this theory and analyse future directions of quantitative studies of strongly interacting theories beyond the standard model with lattice techniques. In particular, I report on a finite size scaling determination of the chiral condensate anomalous dimension gamma, for which 0.05 < or = gamma < or = 0.25.
Toward GEOS-6, A Global Cloud System Resolving Atmospheric Model
NASA Technical Reports Server (NTRS)
Putman, William M.
2010-01-01
NASA is committed to observing and understanding the weather and climate of our home planet through the use of multi-scale modeling systems and space-based observations. Global climate models have evolved to take advantage of the influx of multi- and many-core computing technologies and the availability of large clusters of multi-core microprocessors. GEOS-6 is a next-generation cloud system resolving atmospheric model that will place NASA at the forefront of scientific exploration of our atmosphere and climate. Model simulations with GEOS-6 will produce a realistic representation of our atmosphere on the scale of typical satellite observations, bringing a visual comprehension of model results to a new level among the climate enthusiasts. In preparation for GEOS-6, the agency's flagship Earth System Modeling Framework [JDl] has been enhanced to support cutting-edge high-resolution global climate and weather simulations. Improvements include a cubed-sphere grid that exposes parallelism; a non-hydrostatic finite volume dynamical core, and algorithm designed for co-processor technologies, among others. GEOS-6 represents a fundamental advancement in the capability of global Earth system models. The ability to directly compare global simulations at the resolution of spaceborne satellite images will lead to algorithm improvements and better utilization of space-based observations within the GOES data assimilation system
DOE Office of Scientific and Technical Information (OSTI.GOV)
Pratapa, Phanisri P.; Suryanarayana, Phanish; Pask, John E.
We present the Clenshaw–Curtis Spectral Quadrature (SQ) method for real-space O(N) Density Functional Theory (DFT) calculations. In this approach, all quantities of interest are expressed as bilinear forms or sums over bilinear forms, which are then approximated by spatially localized Clenshaw–Curtis quadrature rules. This technique is identically applicable to both insulating and metallic systems, and in conjunction with local reformulation of the electrostatics, enables the O(N) evaluation of the electronic density, energy, and atomic forces. The SQ approach also permits infinite-cell calculations without recourse to Brillouin zone integration or large supercells. We employ a finite difference representation in order tomore » exploit the locality of electronic interactions in real space, enable systematic convergence, and facilitate large-scale parallel implementation. In particular, we derive expressions for the electronic density, total energy, and atomic forces that can be evaluated in O(N) operations. We demonstrate the systematic convergence of energies and forces with respect to quadrature order as well as truncation radius to the exact diagonalization result. In addition, we show convergence with respect to mesh size to established O(N 3) planewave results. In conclusion, we establish the efficiency of the proposed approach for high temperature calculations and discuss its particular suitability for large-scale parallel computation.« less
Pratapa, Phanisri P.; Suryanarayana, Phanish; Pask, John E.
2015-12-02
We present the Clenshaw–Curtis Spectral Quadrature (SQ) method for real-space O(N) Density Functional Theory (DFT) calculations. In this approach, all quantities of interest are expressed as bilinear forms or sums over bilinear forms, which are then approximated by spatially localized Clenshaw–Curtis quadrature rules. This technique is identically applicable to both insulating and metallic systems, and in conjunction with local reformulation of the electrostatics, enables the O(N) evaluation of the electronic density, energy, and atomic forces. The SQ approach also permits infinite-cell calculations without recourse to Brillouin zone integration or large supercells. We employ a finite difference representation in order tomore » exploit the locality of electronic interactions in real space, enable systematic convergence, and facilitate large-scale parallel implementation. In particular, we derive expressions for the electronic density, total energy, and atomic forces that can be evaluated in O(N) operations. We demonstrate the systematic convergence of energies and forces with respect to quadrature order as well as truncation radius to the exact diagonalization result. In addition, we show convergence with respect to mesh size to established O(N 3) planewave results. In conclusion, we establish the efficiency of the proposed approach for high temperature calculations and discuss its particular suitability for large-scale parallel computation.« less
Relationship among Environmental Pointing Accuracy, Mental Rotation, Sex, and Hormones
ERIC Educational Resources Information Center
Bell, Scott; Saucier, Deborah
2004-01-01
Humans rely on internal representations to solve a variety of spatial problems including navigation. Navigation employs specific information to compose a representation of space that is distinct from that obtained through static bird's-eye or horizontal perspectives. The ability to point to on-route locations, off-route locations, and the route…
The Council Estate: Representation, Space and the Potential for Performance
ERIC Educational Resources Information Center
Beswick, Katie
2011-01-01
The image of the archetypal housing estate is often used in popular representation, from documentary and television to music video, to symbolise the urban "grit" of contemporary inner-city life. In the theatre, urban political and "working-class" drama has been set on or around estates in attempts to deconstruct or expose the…
High-Dimensional Semantic Space Accounts of Priming
ERIC Educational Resources Information Center
Jones, Michael N.; Kintsch, Walter; Mewhort, Douglas J. K.
2006-01-01
A broad range of priming data has been used to explore the structure of semantic memory and to test between models of word representation. In this paper, we examine the computational mechanisms required to learn distributed semantic representations for words directly from unsupervised experience with language. To best account for the variety of…
Facilitating the Genesis of Functional Working Spaces in Guided Explorations
ERIC Educational Resources Information Center
Miranda, Vicente Carrión; Pluvinage, François; Adjiage, Robert
2016-01-01
Approximating given real-valued functions by affine functions is among the most basic activities with functions. In this study we examine two contexts in which two such approximations are performed. The first involves a microscopic representation of functions for the study of tangents; the second a macroscopic representation of functions for the…
ERIC Educational Resources Information Center
Ciaramelli, Elisa; Rosenbaum, R. Shayna; Solcz, Stephanie; Levine, Brian; Moscovitch, Morris
2010-01-01
The ability to navigate in a familiar environment depends on both an intact mental representation of allocentric spatial information and the integrity of systems supporting complementary egocentric representations. Although the hippocampus has been implicated in learning new allocentric spatial information, converging evidence suggests that the…
Erlikhman, Gennady; Gurariy, Gennadiy; Mruczek, Ryan E.B.; Caplovitz, Gideon P.
2016-01-01
Oftentimes, objects are only partially and transiently visible as parts of them become occluded during observer or object motion. The visual system can integrate such object fragments across space and time into perceptual wholes or spatiotemporal objects. This integrative and dynamic process may involve both ventral and dorsal visual processing pathways, along which shape and spatial representations are thought to arise. We measured fMRI BOLD response to spatiotemporal objects and used multi-voxel pattern analysis (MVPA) to decode shape information across 20 topographic regions of visual cortex. Object identity could be decoded throughout visual cortex, including intermediate (V3A, V3B, hV4, LO1-2,) and dorsal (TO1-2, and IPS0-1) visual areas. Shape-specific information, therefore, may not be limited to early and ventral visual areas, particularly when it is dynamic and must be integrated. Contrary to the classic view that the representation of objects is the purview of the ventral stream, intermediate and dorsal areas may play a distinct and critical role in the construction of object representations across space and time. PMID:27033688
Coarse-Scale Biases for Spirals and Orientation in Human Visual Cortex
Heeger, David J.
2013-01-01
Multivariate decoding analyses are widely applied to functional magnetic resonance imaging (fMRI) data, but there is controversy over their interpretation. Orientation decoding in primary visual cortex (V1) reflects coarse-scale biases, including an over-representation of radial orientations. But fMRI responses to clockwise and counter-clockwise spirals can also be decoded. Because these stimuli are matched for radial orientation, while differing in local orientation, it has been argued that fine-scale columnar selectivity for orientation contributes to orientation decoding. We measured fMRI responses in human V1 to both oriented gratings and spirals. Responses to oriented gratings exhibited a complex topography, including a radial bias that was most pronounced in the peripheral representation, and a near-vertical bias that was most pronounced near the foveal representation. Responses to clockwise and counter-clockwise spirals also exhibited coarse-scale organization, at the scale of entire visual quadrants. The preference of each voxel for clockwise or counter-clockwise spirals was predicted from the preferences of that voxel for orientation and spatial position (i.e., within the retinotopic map). Our results demonstrate a bias for local stimulus orientation that has a coarse spatial scale, is robust across stimulus classes (spirals and gratings), and suffices to explain decoding from fMRI responses in V1. PMID:24336733
NASA Astrophysics Data System (ADS)
Mazoyer, M.; Roehrig, R.; Nuissier, O.; Duffourg, F.; Somot, S.
2017-12-01
Most regional climate models (RCSMs) face difficulties in representing a reasonable pre-cipitation probability density function in the Mediterranean area and especially over land.Small amounts of rain are too frequent, preventing any realistic representation of droughts orheat waves, while the intensity of heavy precipitating events is underestimated and not welllocated by most state-of-the-art RCSMs using parameterized convection (resolution from10 to 50 km). Convective parameterization is a key point for the representation of suchevents and recently, the new physics implemented in the CNRM-RCSM has been shown toremarkably improve it, even at a 50-km scale.The present study seeks to further analyse the representation of heavy precipitating eventsby this new version of CNRM-RCSM using a process oriented approach. We focus on oneparticular event in the south-east of France, over the Cévennes. Two hindcast experimentswith the CNRM-RCSM (12 and 50 km) are performed and compared with a simulationbased on the convection-permitting model Meso-NH, which makes use of a very similarsetup as CNRM-RCSM hindcasts. The role of small-scale features of the regional topogra-phy and its interaction with the impinging large-scale flow in triggering the convective eventare investigated. This study provides guidance in the ongoing implementation and use of aspecific parameterization dedicated to account for subgrid-scale orography in the triggeringand closure conditions of the CNRM-RCSM convection scheme.
Sensory motor remapping of space in human–machine interfaces
Mussa-Ivaldi, Ferdinando A.; Casadio, Maura; Danziger, Zachary C.; Mosier, Kristine M.; Scheidt, Robert A.
2012-01-01
Studies of adaptation to patterns of deterministic forces have revealed the ability of the motor control system to form and use predictive representations of the environment. These studies have also pointed out that adaptation to novel dynamics is aimed at preserving the trajectories of a controlled endpoint, either the hand of a subject or a transported object. We review some of these experiments and present more recent studies aimed at understanding how the motor system forms representations of the physical space in which actions take place. An extensive line of investigations in visual information processing has dealt with the issue of how the Euclidean properties of space are recovered from visual signals that do not appear to possess these properties. The same question is addressed here in the context of motor behavior and motor learning by observing how people remap hand gestures and body motions that control the state of an external device. We present some theoretical considerations and experimental evidence about the ability of the nervous system to create novel patterns of coordination that are consistent with the representation of extrapersonal space. We also discuss the perspective of endowing human–machine interfaces with learning algorithms that, combined with human learning, may facilitate the control of powered wheelchairs and other assistive devices. PMID:21741543
Povinelli, Daniel J; Reaux, James E; Frey, Scott H
2010-01-01
Considerable attention has been devoted to behaviors in which tools are used to perform actions in extrapersonal space by extending the reach. Evidence suggests that these behaviors result in an expansion of the body schema and peripersonal space. However, humans often use tools to perform tasks within peripersonal space that cannot be accomplished with the hands. In some of these instances (e.g., cooking), a tool is used as a substitute for the hand in order to pursue actions that would otherwise be hazardous. These behaviors suggest that even during the active use of tools, we maintain non-isomorphic representations that distinguish between our hands and handheld tools. Understanding whether such representations are a human specialization is of potentially great relevance to understand the evolutionary history of technological behaviors including the controlled use of fire. We tested six captive adult chimpanzees to determine whether they would elect to use a tool, rather than their hands, when acting in potentially hazardous vs. nonhazardous circumstances located within reach. Their behavior suggests that, like humans, chimpanzees represent the distinction between the hand vs. tool even during active use. We discuss the implications of this evidence for our understanding of tool use and its evolution.
Gender in facial representations: a contrast-based study of adaptation within and between the sexes.
Oruç, Ipek; Guo, Xiaoyue M; Barton, Jason J S
2011-01-18
Face aftereffects are proving to be an effective means of examining the properties of face-specific processes in the human visual system. We examined the role of gender in the neural representation of faces using a contrast-based adaptation method. If faces of different genders share the same representational face space, then adaptation to a face of one gender should affect both same- and different-gender faces. Further, if these aftereffects differ in magnitude, this may indicate distinct gender-related factors in the organization of this face space. To control for a potential confound between physical similarity and gender, we used a Bayesian ideal observer and human discrimination data to construct a stimulus set in which pairs of different-gender faces were equally dissimilar as same-gender pairs. We found that the recognition of both same-gender and different-gender faces was suppressed following a brief exposure of 100 ms. Moreover, recognition was more suppressed for test faces of a different-gender than those of the same-gender as the adaptor, despite the equivalence in physical and psychophysical similarity. Our results suggest that male and female faces likely occupy the same face space, allowing transfer of aftereffects between the genders, but that there are special properties that emerge along gender-defining dimensions of this space.
The vestibular system: a spatial reference for bodily self-consciousness
Pfeiffer, Christian; Serino, Andrea; Blanke, Olaf
2014-01-01
Self-consciousness is the remarkable human experience of being a subject: the “I”. Self-consciousness is typically bound to a body, and particularly to the spatial dimensions of the body, as well as to its location and displacement in the gravitational field. Because the vestibular system encodes head position and movement in three-dimensional space, vestibular cortical processing likely contributes to spatial aspects of bodily self-consciousness. We review here recent data showing vestibular effects on first-person perspective (the feeling from where “I” experience the world) and self-location (the feeling where “I” am located in space). We compare these findings to data showing vestibular effects on mental spatial transformation, self-motion perception, and body representation showing vestibular contributions to various spatial representations of the body with respect to the external world. Finally, we discuss the role for four posterior brain regions that process vestibular and other multisensory signals to encode spatial aspects of bodily self-consciousness: temporoparietal junction, parietoinsular vestibular cortex, ventral intraparietal region, and medial superior temporal region. We propose that vestibular processing in these cortical regions is critical in linking multisensory signals from the body (personal and peripersonal space) with external (extrapersonal) space. Therefore, the vestibular system plays a critical role for neural representations of spatial aspects of bodily self-consciousness. PMID:24860446
DOE Office of Scientific and Technical Information (OSTI.GOV)
Froning, H. David; Meholic, Gregory V.
2010-01-28
This paper briefly explores higher dimensional spacetimes that extend Meholic's visualizable, fluidic views of: subluminal-luminal-superluminal flight; gravity, inertia, light quanta, and electromagnetism from 2-D to 3-D representations. Although 3-D representations have the potential to better model features of Meholic's most fundamental entities (Transluminal Energy Quantum) and of the zero-point quantum vacuum that pervades all space, the more complex 3-D representations loose some of the clarity of Meholic's 2-D representations of subluminal and superlumimal realms. So, much new work would be needed to replace Meholic's 2-D views of reality with 3-D ones.
Representation of the Auroral and Polar Ionosphere in the International Reference Ionosphere (IRI)
NASA Technical Reports Server (NTRS)
Bilitza, Dieter; Reinisch, Bodo
2013-01-01
This issue of Advances in Space Research presents a selection of papers that document the progress in developing and improving the International Reference Ionosphere (IRI), a widely used standard for the parameters that describe the Earths ionosphere. The core set of papers was presented during the 2010 General Assembly of the Committee on Space Research in Bremen, Germany in a session that focused on the representation of the auroral and polar ionosphere in the IRI model. In addition, papers were solicited and submitted from the scientific community in a general call for appropriate papers.
NASA Astrophysics Data System (ADS)
Plymen, Roger; Robinson, Paul
1995-01-01
Infinite-dimensional Clifford algebras and their Fock representations originated in the quantum mechanical study of electrons. In this book, the authors give a definitive account of the various Clifford algebras over a real Hilbert space and of their Fock representations. A careful consideration of the latter's transformation properties under Bogoliubov automorphisms leads to the restricted orthogonal group. From there, a study of inner Bogoliubov automorphisms enables the authors to construct infinite-dimensional spin groups. Apart from assuming a basic background in functional analysis and operator algebras, the presentation is self-contained with complete proofs, many of which offer a fresh perspective on the subject.
Bag of Lines (BoL) for Improved Aerial Scene Representation
DOE Office of Scientific and Technical Information (OSTI.GOV)
Sridharan, Harini; Cheriyadat, Anil M.
2014-09-22
Feature representation is a key step in automated visual content interpretation. In this letter, we present a robust feature representation technique, referred to as bag of lines (BoL), for high-resolution aerial scenes. The proposed technique involves extracting and compactly representing low-level line primitives from the scene. The compact scene representation is generated by counting the different types of lines representing various linear structures in the scene. Through extensive experiments, we show that the proposed scene representation is invariant to scale changes and scene conditions and can discriminate urban scene categories accurately. We compare the BoL representation with the popular scalemore » invariant feature transform (SIFT) and Gabor wavelets for their classification and clustering performance on an aerial scene database consisting of images acquired by sensors with different spatial resolutions. The proposed BoL representation outperforms the SIFT- and Gabor-based representations.« less
Generative Representations for Computer-Automated Design Systems
NASA Technical Reports Server (NTRS)
Hornby, Gregory S.
2004-01-01
With the increasing computational power of Computers, software design systems are progressing from being tools for architects and designers to express their ideas to tools capable of creating designs under human guidance. One of the main limitations for these computer-automated design programs is the representation with which they encode designs. If the representation cannot encode a certain design, then the design program cannot produce it. Similarly, a poor representation makes some types of designs extremely unlikely to be created. Here we define generative representations as those representations which can create and reuse organizational units within a design and argue that reuse is necessary for design systems to scale to more complex and interesting designs. To support our argument we describe GENRE, an evolutionary design program that uses both a generative and a non-generative representation, and compare the results of evolving designs with both types of representations.
Biologically Plausible, Human-scale Knowledge Representation
ERIC Educational Resources Information Center
Crawford, Eric; Gingerich, Matthew; Eliasmith, Chris
2016-01-01
Several approaches to implementing symbol-like representations in neurally plausible models have been proposed. These approaches include binding through synchrony (Shastri & Ajjanagadde, 1993), "mesh" binding (van der Velde & de Kamps, 2006), and conjunctive binding (Smolensky, 1990). Recent theoretical work has suggested that…